[From the U.S. Government Printing Office, www.gpo.gov]
i: Z C) I v TE 3 7: vv (a 1 7- 1 I v I Tk. 'Lo "'IM2EW"@E\ ISIL Jill -'7z- v OP (T K71@ (7@ r -r 1 -1 (71y@@_V@' 11 V'I'V@-101-i"(N' 4co @r 7, HISTORICAL TRENDS WATER QUALITY AND FISHERIES: ALBEMARLE-PAMLICO SOUNDS With Emphasis on the Pamlico River Estuary .A Report to the National Ocean Pollution Program and the National Sea Grant College Program Donald W. Stanley Institute for Coastal and Marine Resources East Carolina University Greenville, NC 27858-4353 September 1992 U.S. DEPARTMENT OF COMMERCE Barbara Hackman Franklin, Secretary National Oceanic and Atmospheric Administration John A. Knauss, Under Secretary COASTAL OCEAN OFFICE Donald E. Scavia, Director Cn Cn National Ocean Pollution Program A" W. Lawrence Pugh, Director LIBRARy NOAA/CCEH 1990 HOBSON AVE. CFIAS. SC 29408 -2623 H This publication is sponsored by the National Ocean Pollution Program, National Oceanic and Atmospheric Administration, U.S. Department of Commerce. The project was administered under grant NA86AA-D-SGO46 as project R/SF-2 through the UNC Sea Grant College Program, North Carolina State University, Raleigh, NC. Additional support came from Texasgulf Chemicals, Inc., and from East Carolina University. Additional copies ofthis publication are available from UNC Sea Grant, Box 8605, North Carolina State University, Raleigh, NC 27695-8605. Order UNC-SG-92-04. This document should be referenced as: Stanley, Donald W. 1992. HistoricalTrends: Water Quality and Fisheries, Albemarle- Pamlico Sounds, With Emphasis on the Pamlico River Estuary. University of North Carolina Sea Grant College Program Publication UNC-SG-92-04. Institute for Coastal and Marine Resources, East Carolina University, Greenville, NC. 215 pp. Cover Illustration: Drawn by Steve Daniels, and reproduced from Doug Young (editor). 1980. North Carolina and the Sea, prepared by the North Carolina Marine Science Council,N.C. Office ofMarineAffairs, N.C. Department ofAdministration, Raleigh, NC. Contents Preface / v Chapter 1: Profile of the Al bema rle- Pamlico System The Physical-Chemical Environment / I Geological Origin and Evolution / Climate / Freshwater Inflows / Tidal Exchange, Circulation, and Flushing / Salinity and Nutrients Principal Uses / 8 Settlement and Population Growth / Land Use / Commercial Fisheries / Recreation / Industry and Ports Chapter 2: Major Environmental Concerns Eutrophication -- As Evidenced by Blue-Green Algal Blooms / 15 Wetlands Loss / 16 Loss of Submerged Aquatic Vegetation / 18 Declines in Fisheries / 18 Fish Diseases and Kills / 19 Impairment of Nursery Area Function / 19 Shellfish Closures / 20 Toxicant Effects / 20 Chapter 3: Trends in Nutrient Production: An Estimate Based on Changing Land Use and Population Methods / 24 Results / 29 Land Use / Harvested Cr-opland Nutrient Mass Balance / Farm Animals Inventory and Nutrient Production / Point Source Nutrient Production / Trends in Nutrient Production by All Sources Discussion / 46 Chapter 4: Pamlico River Estuary Water Quality Trends History of Water Quality Studies in the A/P System / 53 Methods / 54 DataSources / Changes inAnalyticalMethods / TrendAnalysis Techniques Results and Discussion / 58 Climatic Factors and River Flow / Water Temperature, Salinity, andpH IV Contents Nitrogen / Phosphorus / Nutrient Limitation in the Pamlico / Dissolved Oxygen / Chlorophyll a / Phytoplankton Species Composition and Biomass Chapter 5: Stratification and Bottom Water Hypoxia in the Pamlico River Estuary Introduction / 78 Methods / 79 Results and Discussion / 81 Seasonal and Spatial Variability / Short-Ter7n Variability / Spear7nan Correlation Results / Interannual Trends / Event Frequency / Effects of Hypoxia on Pamlico Biota Conclusions / 88 Chapter 6: The Pamlico River: Comparison with Other Estuaries Introduction / 92 Nutrients / 92 Dissolved Oxygen / 95 Chlorophyll a and Phytoplankton Biomass / 97 Chapter 7: Trends in the Sounds' Fisheries Commercial Fisheries / 103 The Database / Edible Finfish Blue Crabs Shrimp Oysters Recreational Fisheries/ 115 References/ 117 Appendices / 133 Preface Despite great interest in - and large many stations in Galveston Bay and along expenditures for -estuarine water quality the Houston Ship Channel since the late and fisheries management, there have not 1960s. Likewise, there is a twenty-rive been evaluations of long-term trends in year record of water quality from 20-30 conditions of most of our estuaries. Conse- stations in the Pamlico River Estuary in quently, little is known about the effective- North Carolina. In the third estuary, ness of past and present management Narragansett Bay, no routine monitoring programs. program has been carried out, but enough This is one of several products of a independent studies have incorporated study of long-term trends in water quality water quality parameters to permit con- and fishery resources in three important struction of a comparable long-term data U.S. estuaries: 1) Narragansett Bay, Rhode set. In addition to water quality data Island, 2) the Albemarle-Pamlico Sound bases, there are catch statistics and records system in North Carolina, and 3) Galveston of management efforts for important fish- Bay, Texas. The project had four specific eries in each bay. objectives: These estuaries are characterized by a 1. To document long-term trends in range of pollution problems, some of which water quality and, where possible, identify are unique to each, while others are shared causes, consequences and significance. by all. Narragansett Bay and Galveston 2. To assess whether problems are Bayrepresent heavily industrialized, urban similar or unique to each estuary. estuaries with a long history of pollution. 3. To assess whether progress is being They are subjected to intense port and made in improving conditions in water shipping activities, massive industrial dis- quality and fishery resources and whether charges and major domestic sewage load- there are examples of success that would ings from urbanized centers of population: be useful for estuarine managers and Houston in Galveston Bay; and Providence, researchers elsewhere. Central Falls and East Providence in Nar- 4. To glean examples of the useful inte- ragansett Bay. In contrast, the Albemarle- gration of research and policy. Pamlico Sound system is a relatively un- The three estuaries chosen for this developed estuary without major shipping study have sufficient long-term data to lanes, industrial activity ora denselyurban- permit trend analyses and inter-estuarine ized coastline. Instead, it is characterized comparisons. In two of them, monitoring by extensive wetlands along its shoreline programs have been carried out for at least with agriculture and forests as the major two decades. The Texas Department of land use types within its watershed. Yet it Health and the Texas Water Commission also is perceived as having a history of and its predecessors, the Water Quality water quality problems. Board and the Department of Water Re- This is one of three separate - but sources, have been monitoring dissolved comparable - reports that have been pre- oxygen, nutrients, metals and bacteria at pared on trends in pollutant loadings, water V! Preface quality and pertinent fisheries for each of Pamlico River, has been sampled inten- the estuaries. The other two are: sively on a continuous basis over the past two decades. Two others, the lower Chowan Stanley, Donald W. 1992. Historical Trends: River and the Neuse River, have been Water Quality and Fisheries, Galveston sampled intensively during studies lasting Bay. University of North Carolina Sea 2-to-5 years, and infrequently at other Grant College Program Publication UNC- times. The open waters ofAlbemarle Sound SG-92-03. Institute for Coastal and Marine were sampled intensively for a two-year Resources, East Carolina University, period in the early 1970s, but there has Greenville, NC. 100 pp. never been an intensive water quality sam- Desbonnet, A. and V. Lee. 1991. Historical pling for the open waters of Pamlico Sound. Trends: Water Quality and Fisheries, Because the Pamlico River data set is, by Narragansett Bay. The University ofRhode far, the most comprehensive, I have decided Island Coastal Resources Center to restrict my analysis of trends in water Contribution No. 100 and National Sea quality to this sub-estuary. Grant Publication #RIU-T-91-001. One ofthe most widely-held perceptions Graduate School of Oceanography, about the Pamlico River is that it has Narragansett, RI. 101 pp. worse bottom-water dissolved "problems" Three major topics are covered in this now than in the past, and that this is report: 1) nutrient production in the drain- adversely impacting the estuary's fishery age basin, 2) estuarine water quality, and resources. Hence, Chapter 5 addresses the 3) fisheries. Preceding the first of these are factors responsible for low dissolved oxygen two introductory chapters. The first gives episodes in the estuary. Chapter 6 sum- some basic information about the physical marizes some information about compari- setting, hydrology, uses, and living re- sons between the Pamlico River and other sources oftheAlbemarle-Pamlic6 estuarine estuaries, in terms of nutrient and phyto- system. Chapter 2 briefly summarizes the plankton concentrations. major environmental issues for the estuary. Historical records of commercial land- In Chapter 3 1 attempt to develop an esti- ings offinfish and shellfish are available on mate of changes in potential point and a county-by county basis for all of the nonpoint source nutrient loading to the Albemarle-Pamlico region. Unfortunately, estuary over the past century. Actually, however, the data reflect where the fish this part of the study was not included in were brought to shore, not where they the original research plan. Rather, it were caught, so that it is impossible to evolved from a combination of my curiosity equate landings in counties around the about what nutrient loading rates to the Pamlico River Estuary to catch in the estuary might have been in the past, before estuary. Thus, in Chapter 7 report, which "cultural" eutrophication, and my frustra- examines trends in fisheries, I was forced tion resulting from the lack of adequate into looking at the Albemarle-Pamlico re- riverine nutrient concentration data upon gion as a whole, rather than focusing on which to base a direct estimate of historical individual sub-estuaries. loading trends. Primary funding for this research was Chapter 4 deals with historical trends provided by the National Ocean Pollution in water quality within the estuary. For a Program Office of the National Oceanic number ofreasons, water quality sampling and Atmospheric Administration, U.S. in the Albemarle-Pamlico region has been Department of Commerce. The * project very uneven. Only one sub-estuary, the was administered as Grant R/SF-2 through the UNC Sea Grant College Program, North Preface V11 Carolina State University, Raleigh, NC. Community Development, Morehead City; Additional support came from Texasgulf Ms. KatyWest, Division ofMarine Fish- Chemicals, Inc. and from East Carolina eries, North Carolina Department of Natu- University. ral Resources and Community Develop- Several persons in North Carolina and ment, Morehead City; Virginia state agencies provided courteous Staff of the U.S. Government Docu- and friendly assistance as I collected the ments Section of the North Carolina State information needed for the study. They University Library, Raleigh; include: Staff of the Virginia State Library, Mr. David Clawson, District Sanitarian, Richmond; and Shellfish Sanitation Program, Division of Ms. Renee Hawkins of the Virginia Marine Fisheries, North Carolina Depart- State Water Control Board, Richmond. ment ofNatural Resources and Community Many hundreds of hours were spent Development, Morehead City; transcribing data from the printed records Mr. George Gilbert, Assistant Super- into computer files. East Carolina Univer- visor, Shellfish Sanitation Program, Divi- sity students and staff involved in this task sion of Marine Fisheries, North Carolina included Ray Taft, Jeff Taft, Sharon Reid, Department of Natural Resources and Colleen Reid, Deborah Daniel, Anne Community Development, Morehead City; Anderson and Kay Evans. I thank M. Mr. JeffFrench, Marine Biologist, Divi- Brinson, J. Dorney, and K. Evans for re- sion of Marine Fisheries, North Carolina viewing an earlier draft. Mark Hollings- Department of Natural Resources and worth provided invaluable assistance in the preparation of the final draft. Greenville, North Carolina D.W.S. December, 1991 CHAPTER Profile of the Albemarle-Pamlico Estuarine System It is not the purpose of this chapter to Say "coast" in North Carolina, and provide a comprehensive analysis of the everybody thinks beach, specifically the ecology of the Albemarle-Pamlico Estuary. broad, sandy aprons of the barrier islands. Rather, it is a briefsketch intended to focus Everything west of the beach is merely the reader's attention on the system's something through which to pass en route to features which are most relevant to the the water. And there is plenty of water. water quality and fisheries data that will It sometimes seems as if nature created be presented below. Details of the ecology the Coastal Plain so water would have of the Pamlico River Estuary and Albe- something to lap against and sky would have marle Sound can be found in two Estuarine something to rest upon. The Coastal Plain is Profiles by Copeland et al. (1983; 1984). a beautiful mosaic: sun-bleached tidal marsh Giese et al. (1979) provide details of the as broad as the eye can follow; level beach hydrology ofeach ofthe major sub-estuaries planing into the surf; mullet skipping on the in the Albemarle-Pamlico Sound system. water of the sound; boats of every size, shape and design; and magnificentflights of The Physical-Chemical ducks and geese. Arrow-straight highways Environment where rows of crops flicker past the window The Pamlico Sound covers an area of like pickets on a fence. You can plow it, about 5,335 kM2, making it the largest graze it, till it, timber it, fish it, trap it, swim sound formed behind the barrier beaches it, and sail it. Bask in its warmth, boat it, along the Atlantic Coast of the United run it, drive it and follow it through States. Giese et al. (1979) estimate that centuries by reading its history in church the total volume of water in the sound graveyards. averages about 26 billion m, or about 21 It is, above all, a land in community with million acre-feet. The average depth is water and plow, where the good earth and only about 4.9 m, and the maximum depth bountiful sea provide all the rewards needed is only 7.3 m (Figure 1.1 and Table 1.1). to those who spill their sweat. There are numerous tributaries and G. Morris (1985) embayments along the western shore of River are one in the same. The Tar River the Pamlico Sound. Two of these - the is the major freshwater source for the Tar-Pamlico River Estuary and the Neuse estuary, but downstream from Washing- River Estuary - are by far the largest. ton, the name Pamlico River has tradi- The Tar-Pamlico extends approximately tionally been used. The combined surface 65 krn from near the town of Washington, area of the Tar-Pamlico Estuary and its NC to its confluence with Pamlico Sound. sub-tributaries is about 582 kM2 . However, Actually, the Tar River and the Pamlico Chapter I CHOWAN ALBEMARLE SOUND ROANOKE R-PAMLICO PAMLICO SOUND 7 NEUSE Ch. ATLANTIC OCEAN KM 0 10 20 30 40 7 Ce 10 20 30 0 MILES Figure 1.1. Map of the Albemarle-Pamlico Estuarine System. Profile of the Albemarle-Pamllco Estuarine System 3 depths are shallow, averaging only about than 5.5 m deep. Its volume is about 3.4 m. The other important Pamlico Sound 5,310,000 acre feet (Giese et al. 1979). tributary embayment is the Neuse River Estuary. Beginning near the confluence of Geological Origin and Evolution the Neuse River and the smaller Trent The Albemarle-Pamlico system began River at New Bern, NC, the Neuse River to form sometime after 17,000 years BP, Estuary extends 65 km to the mouth in the when the last major glacial ice advance southwest corner of Pamlico Sound, only a reached its maximum development. At short distance south of the mouth of the that time sea level was as much as 130-160 Tar-Pamlico River estuary. The Neuse m lower than today. Consequently, the Estuary is similar in size and depth to the shoreline was far out on the continental Tar-Pamlico. The Neuse covers approxi- shelf. Sand dunes were built up along the mately 394 kM2, and averages 3.6 m in shore by winds blowing toward the land. depth. As the ice melted and sea level rose again, The Albemarle Sound, extending about between 17 thousand and 5 thousand years 88 km from the mouths of the Roanoke and ago, these dunes were separated from the Chowan Rivers eastward to the outer shore in places, thus forming a string of banks, covers an area of about 2,419 kM2 . barrier islands. Breaching during storms It averages about 11 km wide, and has a caused inlets to develop and lagoons to be maximum depth of nearly 9 m, but most of flooded and eventually become wide, shal- the central area of the bay is little more low sounds. Further sea level rise, as well as continual wave action, caused the islands to migrate toward the land (Gade and Table 1.1. Hydrologic datafor Albemarle and Stillwell 1986). Today some of these barrier Pamlico Sounds (fi-om, Giese et al. 1979). islands (popularly known as the Outer A. Drainage area Banks) are moving landward each year at Albemarle Sound 17,879 mi" 46,309 kin' up to 3 m, while sea level is risingabout 0.3 Chowan River 4,943 mi" 12,802 kin cm per year (Pilkey et al. 1978). Roanoke River 9,666 mil 25,035 km' Other 3,288 mil 8,516 km' The sounds are underlain with sedi- Pamlico Sound 10,460 mil 27,092 kin ments and sedimentary rock of marine Tar-Pamlico River 4,300 m? 11,137 km: Neuse River 5,598 Mi2 14,499 km' origin. These sediments were deposited Other 562 mi" 1,456 km' Total 28,357 mP 73,445 km, over at least the past 100 million years B. Surface area while the ocean covered portions of the Albemarle Sound & coastal plain (Brown et al. 1972). The tributaries 934 Mi2 2,419 kin' uppermost veneer of unconsolidated sedi- Pamlico.Sound & -s tributaries 2,064 Mi2 5,335 km' ments were laid down 25 to 1 million year Pamlico River estuary 225 mi' 582 kM2 ago in the Miocene and Pliocene epochs. Neuse River estuary 152 Mill 394 kM2 Total 2,998 m P 7,765 kmg These are extremely varied and include C. Volurne gravels, sands, clays, peats, and all possible Albemarle Sound 5,310,000 acre-ft 6.5 kM3 combinations (Copeland et al. 1984). The Pamlico Sound 21,000,000 acre-ft 26 kM3 present day surface sediments of the estu- Pamlico River estuary 662,308 acre-ft o.82 km' aries are composed primarily of fine sand, Neuse River estuary 1,082,306 acre-ft 1.34 kins silts and clays. Pickett (1965) noted that fine sand covers most of the bottom of D. Avercige Depth Pamlico Sound, with silt present primarily Albemarle Sound 16 ft 4.6 in Pamlico Sound 16 It 4.9 in in the deep areas of the northern basin and Pamlico River estuary 11 ft 3.4 in in the channels extending into the sound Neuse River estuary 12 ft 3.6 in 4 Chapter I from the mouths of the Neuse and Pamlico Climate rivers. Medium sand covers the higher North Carolina lies within a general energy areas near shoals and the tidal climatic region known as Humid Sub- inlets from the ocean. Similarly, Pels (1967) tropical. Moisture is adequate throughout found the bottom sediments of Albemarle the year to support forest as well as a Sound to consist mainly of fine-to-medium variety of agricultural crops, with only sand around the margins of the sound, limited, localized needs for irrigation or with a gradation southward to silt and clay artificial drainage. Temperatures are in the deepest areas. moderate with long summers and brief winters. An extended summer drought may result from dominance ofthe Bermuda high pressure off the east coast. Warm, moist air from the tropics dominates sum- Table 1.2. Water Budget for the Albemarle- mer conditions while cooler, drier conti- Pamlico Soundsystem (from Giese etal. 1979). nental polar air controls winter weather (Gade and -Stillwell 1986). Process Value Dailymean air temperatures overmost ofeastern North Carolina and southeastern Albemarle Sound Virginia range between 5*C and 10*C in A. Freshwater Inflow January, the coldest month, and between Chowan River 4,600 cfs; 24'C and 270C in July, the warmest month. Roanoke River 8,900 cfs Other 2,900 cfs Annual precipitation averages about 127 Total 16,400 cfs Cm/year throughout the basin, but in some B. Precipitation on Albemarle years it may be very much lower or higher Sound and associated open- than this. For example, at New Bern, NC, water areas 3,400 efs the annual precipitation over the past 100 years has ranged between 88 and 203 em/ C. Evaporation from Albemarle year (Wilder et al. 1978). In northeastern Sound and associated open- North Carolina, evapotranspiration aver- water areas 2,600 cfs ages about 86 em per year, and results in D. Total outflow of Albemarle the return of roughly two thirds of the Sound into Pamlico Sound: rainfall back to the atmosphere. Generally, D=A+B-C 17,200 efs except in spring and early summer, Pamlico Sound precipitation exceeds evapotranspiration A. Freshwater Inflow (Wilder et al, 1978). Tar-Pan-Aico River 5,400 cfs Neuse River 6,100 cfs Freshwater Inflows Other 500 cfs Mostofthe freshwater for the Albemarle Total 12,000 cfs and Pamlico Sounds comes from four large B. Inflow from Albemarle Sound rivers: the Chowan, Roanoke, Tar, and to Pamlico Sound 17,200 cf1s Neuse. The Roanoke and Chowan, which are the two major rivers in the Albemarle C. Precipitation on Pamlico Sound 8,250 cfs basin, drain 25,035 kM2 and 12,802 kM2, D. Evaporation from Pamlico Sound 5,740 cf., respectively, in northeastern North Caro- lina and southern Virginia. The Roanoke E. Net inflow to Pamlico Sound: basin extends to the foothills of the Appala- E=A+B+C-D 31,710 cfs chian Mountains. The Tar and Neuse Profile of the Albemarle-Pamlico Estuarine System 5 Rivers, which supply most of the freshwater Ocracoke, Hatteras, and Oregon Inlets. to the Pamlico Sound, have watershed This limited access, in combination with areas equal to 11, 13 7 kM2 and 14,499 kM2' the broad expanse of the sound, results in respectively. ocean tides being dampened to less than 6 The total freshwater discharge from cm, except near the inlets (Roelofs and theserivers into the Albemarle and Pamlico Bumpus, 1953; Giese et al. 1979). Often, Sounds cannot be measured, because the wind-driven tides are dominant over lunar low stream slopes and tidal influence near tides in both the sound and adjoining trib- the river mouths make measurement of utary estuaries. The large size of Pamlico stream flow by conventional techniques Sound allows ample opportunity for wind impossible in these areas. Consequently, setup over long fetches. U.S. Geological the most downstream gauging stations studies in the Neuse and Tar-Pamlico estu- operated by the U.S. Geological Survey lie aries, summarized in Giese et al. (1979), in the higher areas to the west. Wilder et indicate these wind tides are normally in al. (1978) showed that the data that are the range of 0.3 to 0.6 m. available from the gauging stations can be The Albemarle Sound system has no extrapolated to give reasonably accurate direct outlet to the ocean. Instead, it estimates of runoff from the whole connects to Pamlico Sound and Oregon Albemarle-Pamlico watershed. They found Inlet through Croatan and Roanoke that on a long-term basis, average flows on Sounds; hence, dampeningof lunar tides is a unit basis through all of the major rivers even greater in the Albemarle than in the are within narrow limits, ranging from Pamlico. Normal wind tides in the sound 0.80 cubic feet per second (CFS) perMi2for average about the same as in Pamlico the Roanoke River to 1.05 CFS/mi2for the Sound, and the water level can change Neuse River. Thus, multiplication of these relatively rapidly with shifting wind unit discharge rates times the total basin directions and velocities accompanying area yields estimates ofthe total freshwater frontal storm passage (Giese et al. 1979). input. On a short-term basis, wind driven Giese et al. (1979) presented estimates currents are often dominant over riverine of inflow calculated by this method, along flows in both the sounds and adjoining with data on precipitation and evaporation, estuaries. Within the estuaries, the velocity in their detailed monthly and annual gross of wind-driven currents may be increased water budgets for the two sounds (Table because of funneling effects. A second 1.2). The runoff is highest in the late factor which contributes to the relative winter and lowest in the late summer and importance of wind-driven currents in the fall. This is out of phase with the annual system is that velocities due to freshwater precipitation cycle described earlier (higher inflow are low. Pamlico Sound and its rainfall in the summer than in the winter). estuaries are drowned river valleys. Con- The explanation for the discrepancy is that sequently, the river channels are oversized evapotranspiration rates are much higher for the amount of water they now carry, in the summertime than in winter. resulting in low velocities. In the long term, however, freshwater inflow is more Tidal Exchange, Circulation, and important than wind in affecting net flow Flushing because the effects of winds blowing from Pamlico Sound is connected with the various directions tend to cancel each other ocean through several relativelysmall open- over time. This is true throughout the ings in the Outer Banks, primarily Albemarle-Pamlico system (Giese et al. 1979). 6 Chapter I up to around 100 days for low flow condi- 180 tions (Figure 1.2). The average flushing 160 time, based on long-term flow data, is 140 about 24 days for the Tar-Pamlico. 120- 2 100-1 So- Salinity and Nutrients z 60 Salinities are generally lower in the CO 40 Albemarle system than in the Pamlico 20 L system for two reasons. First, the fresh- 0 0 2 4 6 8 10 12 14 16 water input:sound volume ratio for Albe- FRESHWATER INFLOW (CFS X 1000) marle Sound is larger than that for Pamlico Figure 1.2. Flushing times for the Tar- Sound. The higher current strength result- Pamlico estuary as a function of river flow. Tar ing from this more effectively blocks saline River flow gauged at Tarboro, NC. water intrusion. Secondly, seawater that does reach Albemarle Sound has already been diluted in Pamlico Sound (Giese et al. Giese et al. (1979) computed estimates 1979). Consequently, western Albemarle of the replacement time for freshwater in Sound is essentially a freshwater system, the Albemarle and Pamlico Sounds by and even the eastern-most areas of the comparing the estimated freshwater input sound typically have salinities less than 5 per month with the volumes of the sounds. ppt. Pamlico Sound salinities decrease On average, it would take about 11 months from around 30 ppt near the barrier island for the flow into Pamlico Sound to equal inlets to approximately 15 ppt at the the volume of the sound. Based on their Pamlico River and Neuse River sub-estuary monthly inflow estimates, the water mouths (Giese et al. 1979; Stanley 1988b). replacement times would vary between 19 Giese et al. (1979) contend that wind and 6 months. Actually, the range is velocity and direction are the dominant greater than this because of extremes in short-term influences on salinity in the inflow that occur in some years. Similar sounds, whereas variations in freshwater estimates for Albemarle Sound range inflows are the primary influence on the between 9 and 3.5 months with a mean of seasonal salinity patterns. about 5.5 months. These estimates suggest Salinity in turn influences to some that the Albemarle flushes about twice as extent the concentrations ofdissolved plant- rapidly as the Pamlico. growth nutrients in the estuary. For A more realistic estimate of estuarine example, in the lower freshwater tidal residence times requires taking into account areas of the rivers, nitrate nitrogen (NO 3- tidal exchange effects. To do so, one may N) generally exceeds 20 AM, but decreases use the method of Ketchum (1950) to calcu- rapidly downstream with increasing late the amount offreshwater in the estuary salinity. Part of this decrease is due simply based on the salinity of the system. One to dilution by low-nitrate ocean water, so then computes the amount of freshwater it that in the open areas of Pamlico Sound, would take to flush that freshwater from the nitrate concentrations are probably the system (Pilson 1985). Using this proce- less than 1 AM most of the time. Other dure, I calculated flushing times for the forms of nitrogen and phosphorus also are Tar-Pamlico River estuary as a function of generally most concentrated in the upper freshwater inflow. The results are that the ends of the estuaries (Stanley 1988b; residence times for this estuary range from Bowden and Hobbie 1977; Hobbie and the around 10 days under high flow conditions Profile of the Albemarle-Pamlico Estuarine System 7 Smith 1975). Of course, rates of biological budgets, several general conclusions seem uptake and remineralization, and rates of obvious (Table 1.3). First, there are not input from the watershed also are factors drastic differences in the nonpoint areal N regulating the estuarine nutrient concen- and P loading rates from one basin to trations. Because there are so many another. For N the range is from 216 kg/ dynamic processes affecting estuarine square km in the Tar-Pamlico to 365 kg/ nutrients, their concentrations vary widely, square km in the Neuse. The nonpoint P both spatially and temporally, and it is loadingvaries from 21 kg/square km in the difficult to generalize. Chowan to 33 kg/square km in the Neuse. Annual nutrient loading rates have Second, point-source N loading (on an areal beenestimated forseveral oftheAlbemarle- basis) is highest in the Neuse and lowest in Pamlico sub-estuaries (NCDNRCD 1982, the Tar-Pamlico, but in all cases is only 1983,1987b). While detailed comparisons about 20% of the total N load. Point mustbe made with caution, since no uniform sources contribute about half the total P methodology was used to construct the loading, except in the Pamlico where they Table 1.3. Nutrient loading estimates for sub-basins of the Albemarle- Pamlico Sound system. N N P P Basin Land Area Annual Annual Annual Annual (kM2) Loading Loading Loading Loading (kg/sq. km) (kg x 10') (kgtsq. km) (kg x 101) Chowan 12,673 4,197 443 Point 881 165 Nonpoint 261 3,316 21 278 Roanoke 25,063 5,436 486 R.R. Res. 21,780 3,845 279 Bel. Res. 3,283 Point 593 133 Nonpoint 303 998 22 73 Tar-Pan-ilico 11,650 3,223 933 Point 625 201 Nonpoint 216 2,522 26 312 Texasgulf 76 419 Neuse 15,979 7,358 962 Point 1,513 430 Nonpoint 365 5,845 33 532 Total 65,365 20,214 2,824 Point Nonpoint 290 27 Notes: 1. Roanoke and Chowan data from NCDNRCD (1982) 2. Tar-Pamlico dat from NCDNRCD (1987) 3. Neuse data from NCDNRCD (1983) 4. "R.R. Res." refers to the Roanoke River Reservoir 5. 'rexasgulF refers to discharge from the Texasgulf phosphate mining facility 8 Chapter 1 are two-thirds of the total because of the The population was overwhelmingly rural large input from Texasgulf Chemicals, at this time. There were only two small which accounts for about one-half the total urban areas, New Bern at the head of the P going into the Tar-Pamlico. Finally, Neuse River estuary and Raleigh in the except for the Tar-Pamlico phosphorus load- upper Neuse basin. Each had about 4,500 ing, none of the Albemarle-Pamlico tribu- inhabitants. tary areal loading rates are unusually high Since 1850 there has been only modest in comparison to other U.S. river basins for population growth in the Chowan Basin, which estimates have been made (e.g., but much more rapid growth in the Clesceri et al. 1986; Rast and Lee 1983). Roanoke, Tar-Pamlico, and Neuse basins (Figure.1.3). In 1987, it was estimated that Principal Uses 2.37 million persons lived in the Albemarle- Settlement and Population Growth Pamlico basin, with most of these in the The Albemarle-Pamlico region was the first area of North Carolina to be settled by to 2500 - -------- ------- --- a Europeans, but the development proceeded z 9 20M - slowly until recent times, so that at present 5 0 1500- the area remains one of the State's most I rural. Sir Walter Raleigh explored the z 0 Pamlico Sound, landing at Roanoke Island in 1584. In 1587, Raleigh appointed John 0 Will MR MR MR 0 1790 1810 1830 1850 1870 1890 1910 1930 1950 1970 1087 White governor of what was to become the a' "Lost Colony" on Roanoke Island. Settle- YEAR ments in the Jamestown, Virginia area Chowan Roanoke M Tar after 1607 became the nucleus for the Neuse Coastai colonization of northeastern North Caro- lina. Early communities began north of Figure 1.3. Growth ofhumanpopulation in each Albemarle Sound in the mid and late 1600s, ofthe mcjorAlbemarle-Pamlico estuarine system and migration farther south led to the sub-basins. establishment of the town of Bath on the Pamlico River estuary in 1704. At the time of the first United States census in 1790, the total basin population was about Roanoke 380,000. The Roanoke and Chowan sub- -- 24796 basins in the northeastern part of North 36% Carolina and southern Virginia contained Neuse about three-fourths of the total, with 14306 21% 140,000 and 100,000 inhabitants, respec- tively (Figure 1.3). 10% Southern and western migration con- 18% 15% Coastal tinued with the founding of New Bern at 7025 the head of the Neuse estuary in the early 18th century (Lefler 1965). By 1850 there Chowan Tar were over 600,000 persons in the basin, 12730 10448 with most of the growth having occurred in Figure 1.4. Distribution of Albemarle-Pamlico the western Roanoke basin and in the Tar- land areas (square kilometers) among the major Pamlico and Neuse basins to the south. sub-basins. 10% Profile of the Albemarle-Pamlico Estuarine System 9 Roanoke and Neuse basins. no effect from seasonal visitors (Tschetter Most areas immediately adjacent to 1989). the Sounds are sparsely populated in comparison to more inland areas. For Land Use example, although 10% of the Albemarle- Current land use patterns in the Pamlico watershed drains directly into the Albemarle-Pamlico also reflect its rural sounds (i.e., is downstream from the mouths nature. The region is predominantly for- of the four major rivers), those "coastal" ested and agricultural (Figure 1.5). Forest areas contain only about 5% of the total lands comprise 60% of the total basin area, basin population today (Figures 1.3 and and about 20% of the land is in crops. The 1.4). However, present growth rates in percentage of the basin that is urbanized is three of the coastal counties - Dare, estimated to be no more than about 2%. Currituck and Carteret - are among the There are modest differences in land use highest in the State, and this trend is among the sub-basins of the system (Figure projected to continue in the near future 1.6). The forest land coverage ranges from (Tschetter 1989). Nevertheless, the 54% in the Neuse River, Tar-Pamlico River, Albemarle-Pamlico basin in general, and and Albemarle Sound "coastal" basins to the immediate coastal area in particular, 63% and 67% in the Roanoke River and continue to be more rural than areas Chowan River basins, respectively. Con- surrounding most of the large estuaries versely, the cropland acreage is highest in farther north along the Atlantic coast. the Neuse, Tar-Pamlico and Albemarle The coastal counties experience wide Sound regions (25-28%) and lowest in the fluctuations in population due to seasonal Roanoke River basin (14%). The Neuse tourism. Tschetter (1989) estimated that Basin as a whole is more urban (4%) than Dare Countys population increased to over any of the other sub-basins, but of course 4 times that of the permanent population almost all of this is in the upper end of the during the peak seasonal day in 1987. basin, in the Raleigh-Durham area. Other coastal counties and some counties on the west side of the sound experience Commercial Fisheries smaller population fluctuations, perhaps The Albemarle-Pamlico system is a in the 20-50 percent range. Counties farther major contributor to the commercial fish- inland in the AP basin experience little or eries catch in North Carolina, as evidenced by the fact that about 80% of the total edible harvest each year is landed there. Pamlico Sound is very different from Forest W% Albemarle Sound, however, both in terms of the commercial catch poundage and the Pasture composition of the catch. It has been 5% estimated that in 1980, for example, Pamlico Sound contributed 78% ofthe total Other inshore catch, in contrast to Albemarle 14% Sound, which contributed only 14% of the Uxrban total commercial catch (Copeland et al. 2% Crops 1984). 20% Freshwater and anadromous species of Figure 1.5. Land use within the Albemarle- finfish dominate the catch in Albemarle Pamlico estuarine system watershed (1985). Sound and its tributary rivers, the Chowan 1 0 Chapter I Albemarle River Chowan River Forest 54% Forest 67% Pasture Pasture ....................... 3% 1% Urban 0% Other Other 11% 17% Crops Urban Crops 28% 0% 19% Neuse River Pamlico River Forest Forest 54% 59% Pasture Pasture 3% 1 % ....... ... .. Urban Other 4% 15% Other Crops 26% Crops 15% 25% Roanoke River Tar-Pamlico River Forest Forest 54%- 63% Pasture 8% Pasture 3% Other Urban Other 13% 1 % 15% Urban Crops Crops 2% 14% 26% Figurel.6. Land use within each ofthe mqjor sub-basins of the Albemarle-Pamlico estuarine system watershed. Profile of the Albemarle-Pamlico Estuarine System 1 1 and the Roanoke, where most of the catch Ross 1986; Godwin et al. 1971). is made during the spring spawning runs. Farther south, in Pamlico Sound and In recentyears the most important anadro- its tributary estuaries, the commercial mous species have been the alewife (Alosa catch consists primarily of blue crabs pseudoharengus) and blueback herring (Callinectes sapidus), white, brown and (Alosa aestivalis). In the official landing pink shrimp (Penaeus sp.), oysters statistics of the National Marine Fisheries (Crassostrea virginica), hard clams Service, these two species are combined as (Mercenaria mercenaria), bay scallops "alewives." Another common name is "river (Argopecten irradians), and seasonally herring" (Godwin et al. 1971). American abundant species ofedible marine finfishes. shad (Alosa sapidissima) and striped bass These include grey seatrout, or "weakfish" (Morone saxatilis) are two other anadro- (Cynoscion regalis), flounder (mostly Para, mous species in the Albemarle. The shad lichthys dentatus and P. lethostigma), were once very abundant, but the catch Atlantic croaker (Micropogon undulatus), declined drastically in the early 1900s. bluefish (Pomatomus saltatrix), spot Striped bass is perhaps the best known, (Leiostomus xanthurus) and mullet (Mugil and certainly the most studied, finfish in cephalus and M. curema). theAlbemarle region. Amodest commercial Between 1980 and 1987, the annual fishery for resident species of catfish and landings of edible finfish in the Albemarle- bullheads (genus Ictalurus) has developed Pamlico system averaged 57.3 million in the last 25 years or so (Epperley and pounds, and the shellfish harvest averaged Table 1.4. Albemarle-Pamlico Commercial landings catch composition (1980-1987 auerages). Data are from N.C. Diuision of Marine Fisheries (1980-1987). % oftotal % of finfish % of shellfish Species lbs/year catch catch catch Edible Finfish 57,298,432 60.2 1. Grey Seatrout 12,325,898 12.9 21.6 2. Flounder 10,071,075 10.6 17.6 3. Croaker 9,678,043 10.2 16.9 4. Alewives 6,578,158 6.9 11.5 5. Bluefish 4,180,627 4.4 7.3 6. Spot 3,593,872 3.8 6.3 7. Mullet 1,312,485 1.4 2.3 8. Catfish 1,108,679 1.2 1.9 9. American Shad 261,034 0.3 0.5 10. Striped Bass 230,140 0.2 0.4 11. Other 7,958,421 8.4 13.8 Shellfish 37,876,224 39.8 1. Blue Crabs 30,311,632 31.8 80.0 2. Shrimp 4,969,160 5.2 13.1 3. Hard Clams (meat) 846,452 0.9 2.2 4. Oysters (meat) 633,781 0.6 1.4 5. Bay Scallops (meat) 533,781 0.6 1.4 6. Other 962,270 1.0 2.7 (Squid, Sea Scallops) 1 2 Chapter I about 38 million pounds (Table 1.4). Four Sounds remains largely unknown. Other species -grey seatrout, flounder, croaker than for striped bass, there are essentially and alewives - account for about two- no historical ecological data upon which to thirds of the total edible finfish harvest. base recreational fishing trend analyses. Averaging 30 million pounds landed per year, blue crabs have dominated the shell- Industry and Ports fish landings (80% of the total), and are the North Carolina is currently the nation's most abundant single species in the entire eighth largest state in manufacturing em- commercial edible harvest (32%). About 5 ployment. Manufacturing is fairly uni- million pounds of shrimp are landed formly distributed throughout the state annually, along with lesser quantities of except in two areas where it is much less hard clams and other mollusks (.25-1 intense: the southwestern Mountain and million pounds per year). northeastern Tidewater areas (Gade and Atlantic menhaden (Brevoortia Stillwell 1986). Large firms (with over 250 tyrannus) is an industrial finfish species employees) are especially scarce in the that spends part of its life in the estuaries Albemarle-Pamlico region; in 1980, there but is harvested offshore in theAtlantic. In were fewer than 30 of them in the 14 terms of volume, no other fishery in North counties adjacent to the Sounds (Wilms Carolina has ever come close to menhaden and Powell [no date given]). In fact, there (Whitehurst 1973). In 1984, 178 million are only three large water-dependent pounds of menhaden were landed at North manufacturing plants that discharge Carolina ports (North Carolina Division of directly into an estuary of the Albemarle- Marine Fisheries 1984). Pamlico system. Two are Weyerhaeuser pulp and paper mills; one on the lower Recreation Roanoke River at Plymouth, NC, and Tourism, already one of North Caro- another above New Bern, NC, on the lower lina's larger industries, is projected to grow Neuse River. The third is a phosphate even larger in the near future, surpassing mine and manufacturing plant owned by three ofthe States traditional major indus- Texasgulf Inc. on the south shore of the tries: tobacco, textiles, and furniture. Dare Pamlico River estuary. County is by far the leader in tourism in the In the early 1950s, large deposits of coastal region. Revenues there have in- phosphate were discovered in Beaufort and creased at an explosive rate fromiust $11.6 Hyde Counties. The deposits were formed million in 1971 to nearly $350 million in 25 million years ago as thick layers ofsmall 1987 (both figures adjusted to 1984 dollars) calcium phosphate pellets; theywere subse- (Tschetter 1989). quently covered with up to 30 meters of Fishing was the first major water- sand and clay. By 1966, the Texas Gulf related recreational activity to develop in Sulphur Company (now Texasgulf, Inc.) the Albemarle-Pamlico region, and today, mine was in full-scale operation in an area recreational fishing is a major activity in immediately adjacent to the Pamlico River the coastal region (see Chapter 7). Recent near Aurora, NC. At the Aurora facility studies have quantified it in social and Texasgulf concentrates the ore and uses economic terms (Johnson et al. 1986). Also, part of it in the manufacture of phosphoric Johnson and Perdue (1986) estimated the acid. The rest is sold to fertilizer manu- marina and marine manufacturing income facturers. The plant also discharges phos- attributable to recreational fishing. Unfor- phorus and fluoride enriched freshwater tunately the ecological impact on the into the estuary. Controversy surrounding Profile of the Albemarle-Pamlico Estuarine System 1 3 the impact of Texasgulf on the Pamlico Philadelphia, etc. River has grown steadily over the past Pamlico River tonnage rose rapidly in decade. The company's reputation has themid-1960s, coincident withtheopening been tarnished by a series of Clean Air Act ofthe Texasgulfphosphate mine, and today violations and small-scale chemical spills, about half of the total Albemarle-Pamlico some of which have led to hefty fines. waterborne commerce is related to the Today fisherman and other local citizens, mine. Liquid sulphur (17% of the total along with some North Carolina state offi- tonnage) is brought to the Texasgulf plant cials and scientists, suspect that the dis- and fertilizer materials (34% of the total) charges are responsible for widespread are barged south to Morehead City for damage to the estuary, but so far, the shipment out of the region. The third evidence is mostly circumstantial. largest cargo in the sounds is pulpwood The Albemarle-Pamlico probably has (25% of total tonnage) en route to mills on the lowest amount of port activity of any the lower Neuse and Roanoke Rivers and estuarine system, in its size category, in upstream in the Chowan River. the nation. The only ports of any signif- The fact that no significant port develop- icance in North Carolina are to the south, ment occurred in the Albemarle-Pamlico at Morehead City and at Wilmington. region has been attributed to the difficulties Waterborne commerce, as reflected by ship- of navigating the shallow, shifting inlets ping tonnage, is trivial in the sounds. In through the Outer Banks and the large 1984, only 2 million tons of waterborne expanse of shallow waters between the cargo were transported in the all of the Banks and the mainland to the west (Gade sounds and rivers in the Albemarle-Pamlico and Stillwell 1986). Poor transportation system (Morehead City port activity not between the coastal counties and other included). By way of comparison, during regions of the state may have been a factor the same year the Port of Wilmington, NC, also, but of course it is difficult to ascertain alone handled about three times as much whether this was primarily a cause for, or cargo. And Wilmington is a very smal I port effect of, the lack of port development. in comparison to Charleston, Norfolk, CHAPTER2 Major Environmental Concerns During the past decade, concerns about A decade after the environmentalmovement the environmental health of various parts spawned a great surge of new laws and the Albemarle-Pamlico system have been commitments to clean up and protect voiced more and more frequently in threatened resources, the people ofNorth magazine and newspaper articles, on Carolina are losing the battle against water television news reports, and by environ- pollution. Meanwhile, the life ofour coastal mental groups, scientists and government waters continues to ebb away, choking on agency personnel. At the present time, the estuary is being studied more intensively mud, algae, chemical poisons and the than ever before because of the U . S. threat and promise of ever more. State Environmental Protection Agency's on- regulators say the pollution problems goingAlbemarle-Pamlico Estuarine Study confronting the coast are so complex, they (APES). The APES 5-Year Study Plan are strugglingiust to understand them, let (NCDNRCD 1987b) lists a number of so- alone implement controls. called "major environmental concerns" for P. Haskins (1981) the Albemarle-Pamlico. A draft Status and Trends Report for the Albemarle- documented in 1980, 1981, and 1983 Pamlico estuarine system includes much (Christian et al. 1986). The Chowan blooms more detailed information on some ofthese were largely composed of the nitrogen- topics (Copeland 1989). The followingsum- fixing species Aphanizomenon flos aquae, mary is based, in part, on material from Anabaena spiroides and Anabaena flos that document. Several ofthe concerns are aquae, while in the Neuse Microcystis addressed in other Chapters of this report; aeruginosa has been the dominant blue- hence, they are discussed only briefly here. green (Paerl 1982, 1987). Fortunately, the blooms have been Eutrophication - As limited to the riverine and freshwater tidal Evidenced by Blue-Green portions of the estuaries because the blue- Algal Blooms green species comprising them cannot Blooms of noxious phytoplankton are tolerate saltwater. In the Chowan, the often a very obvious indication of cultural blooms extended over a 30 km stretch enrichment of estuarine waters with between Holiday Island and the river's nutrients, primarily nitrogen and phos- mouth near Edenton, NC. The Neuse phorus. Such blooms have occurred during blooms persist for a period ranging from some, but not all, recent summers along several weeks to months. Chlorophyll a the lower Chowan and Neuse Rivers. The levels typically are several hundred /ig( most spectacular blooms in the Chowan liter (NCDNRCD 1982; Christian et al. occurred in 1972, 1978, and 1983 1986). (NCDNRCD 1987b). Neuse blooms were Research has improved our knowledge ofseveral factors contributingto the blooms, 1 6 Chapter 2 but scientists have not yet integrated all and more regularly, than any other estuary the information needed to explain when in North Carolina (Stanley 1988b). In fact, and where the blooms will occur. The it is one of the few areas of the Albemarle- relationship between increased nitrogen Pamlico system for which there is a complete and phosphorus and blue-green blooms is enough record to permit an analysis of well established for freshwater lakes, but historical trends (see Chapter 4). is not nearly so well understood for estuaries like the Chowan and Neuse. Generally, WetlandS LOSS estuarine algal growth is considered to be Although the Albemarle-Pamlico region more nitrogen limited than phosphorus is relatively undeveloped, human activities limited (Boynton et al. 1982), but trying to in the area have altered and destroyed quantify this has proven very difficult, for habitats that are part of, or tightly-linked several reasons. For one thing, the flo, to, the estuarine ecosystem. Dredging, through nature ofestuaries causes them to draining and f illing are the activities caus- behave like rivers sometimes, when ingmost ofthe changes and these activities freshwater input is high, and like lakes at are usually associated with one of three other times when inflow is low. This hydro- industries: agriculture, residential housing logic variability causes problems in predict- development, or commercial forestry. ing water and nutrient flushing rates, as Reproductive, migratory and feeding pat- well as algal concentrations. For the Neuse, terns for a wide variety of aquatic and Christian et al. (1986) showed that blue- terrestrial organisms are thought to be green blooms could not form unless water affected, but details are lacking for most temperature is high and river discharge is species. Thus, the relative values of the low, because otherwise the water is swept wetlands are poorly known and, in most into Pamlico Sound before the blue-green cases, restoration or mitigation forimpacted algae densities have time enough to build areas has yet to be evaluated on an economic up to bloom levels. This probably explains basis. why blooms develop only in low-flow Adams et al. (1989) recently prepared summers, despite the fact that plenty of a report on the status and trends of the the nutrients are present every year. wetlands in the Albemarle-Pamlieo region; There is much uncertainty whether the some of their findings are summarized blue-green problem is worse now than in below. past decades. It is said that the blooms are A. Tidal Salt Marshes: In 1962, there more frequent now (e.g., NCDNRCD 1987b), were estimated to be a total of 4,897 hect- but there is no historical systematic sam- ares of salt marsh in Pamlico Sound, and pling record to confirm this. It is certainly none in the Albemarle Sound. Most of the possible that blooms werejustas common marsh area was in Carteret County (83%), earlier, but, like most other symptoms of with the remainder in Hyde (13%) and environmental degradation, were paid little Dare (4%) Counties (Wilson 1962). Amore attention. This is unfortunate, because recent estimate is not available. Tidal salt such a record would give support to the marshes are ofdirect benefit for humankind popular opinion that reduction of nutrient due to their function in supporting finfish loading (and presumably nutrient concen- and shellfish fisheries, waterfowl popula- tration) in the estuaries will reduce or tions, and aesthetics. These benefits have eliminate the blooms in the future. been appreciated for at least three decades; The Pamlico River Estuary has been thus, salt marshes are afforded a relatively monitored for nutrients and algae longer, Major Environmental Concerns 1 7 high level of protection in most states, which has a long history of water quality including North Carolina. problems and is undergoing rapid develop- B. Nontidal Brackish Marshes: These ment and land use changes. It is thought are eight times as extensive as salt marshes to be functionally similar to the nontidal in Pamlico Sound; in 1962, there were brackish marsh, although obviously the about 40,000 hectares. Carteret County plant and animal species composition is had 15,621 hectares (39% of total), and somewhat different. Where it is abundant, most of the rest was in Hyde, Pamlico and much importance is given to waterfowl and Dare Counties (Wilson 1962). Tradition- sports fishing resources. A relatively large ally, these marshes have been altered to number of permits were issued allowing create impoundments to attract waterfowl, alteration of wetlands in the Currituck with little attention being paid to the costs Sound area between 1970 and 1984 (Stock- of such alteration. Despite their large ton and Richardson 1987). The proximity areal coverage, less is known about the of this area to a major metropolitan area ecological functioning of these marshes (Norfolk and Virginia Beach, Virginia) than is known for tidal salt marshes. In makes it very attractive for outdoor recre- addition, large areas of marsh were altered ation and development of second homes. in the past by digging ditches for mosquito E. Riparian lAlluvial Forested Wet- control, a practice that elicited a call for a lands: North Carolina and other southern moratorium on ditching (Kuenzler and states have extensive forested wetlands. Marshall 1973). The ditching no longer There are several types, including bottom- occurs, but the potential for these areas to land hardwood forests along rivers and recover to their original, unaltered condition streams, cypress strands, willow strands, is not known. The brackish marshes are and small headwater branches and drains. protected by the same mechanisms used Functionally, however, they have many for other wetlands. similarities. One is their capacity to act as C. Fringe Swamps: These are forested water pollution filters. A very good syn- wetlands that occupy the shorelines of thesis of past research on this subject was Albemarle Sound and the mouths of some made by Kuenzler (1989). He found that of its major tributaries. They represent a those alongstrearns can remove large quan- transition between aquatic ecosystems and tities ofsuspended sediments from cropland interior wetlands. Near the shoreline, runoff as well as nitrogen and phosphorus they are characterized by groves of dead or from both point sources and nonpoint dying cypress trees under permanently sources of pollution. For example, it was flooded conditions, a very common - and estimated that the systems removed 64% picturesque - sight in the Albemarle of the total nitrogen and 43% of the total region. Brinson (1989) estimates that they phosphorus from upland sources in the occupy about three-fourths of the southern Chowan River watershed (Kuenzler and shoreline of Albemarle Sound and almost Craig 1986). all the shoreline of the Alligator River. These wetlands have been destroyed They were harvested for timber in the rapidly in recent decades. Turner et al. past, but no studies have been made to (1981) reported the combined loss of 30,000 document the effects of the harvesting on acres ofbottornland hardwood forests from the ecology of the swamps. about 1960 to 1975 in North Carolina and D. Nontidal Freshwater Marsh: Most South Carolina. Such losses represent a of this marsh type (3,500 hectares) occurs small fraction of the total forest land so in the northern part of Currituck Sound, that they are not reflected by the statistics 1 8 Chapter 2 in total forest land acreage trends (see Currituck Sound (Adams et al. 1989). In Chapter 3). Nevertheless, the decrease terms of present conditions, Brinson and represents a substantially larger fraction Davis (1989) carried out one of the most of the total wetland area. Such reductions recent surveys and found great variability must be affectingwater quality, given their in SAV abundance from one area to another. high pollutant removal capacities. The The marine SAV community in the National Wetlands Policy Forum is develop- Albemarle-Pamlico system appears rela- ingrecommendations designed to stop, then tively stable, according to Thayer et al. reverse, wetland losses. (Kuenzler 1989). (1984). Eelgrass, a major component of Implementation of these and other policies this community, recovered substantially developed by Federal and State authorities from the wasting disease of the 1930s. mayturn.out tobe one ofthe most important However, there is concern about future estuarine water quality management development activities that might affect actions in the near future. SAV habitat, and about clam-kicking, a mechanical clam harvesting procedure Loss of Submerged Aquatic which is thought to damage SAV (Peterson Vegetation et al. 1983, 1987). Reduction in submerged aquatic vegeta- Declines in Fisheries tion is of crucial environmental concern because a decline represents a reduction in Declines in commercial fisheries have fisheries and waterfowl habitats. In the occurred in the Albemarle-Pamlico region mid-1970s and before, submerged aquatic following historic highs in the 1970s. For vegetation (SAV) was common in the upper nearly 40 years, the total finfish catch half of the Pamlico River estuary (Davis remained relatively stable. But between and Brinson 1976). By 1985, however, 1968 and 1981, it rose dramatically to biomass had been reduced to about 1% of about three times what it had been pre that of the 1970s and only widgeongrass viously. Since then, it has fallen back to was present (Davis and Brinson 1989). An about 1.5 times the 1930-1970 mean. It is after-the-fact analysis of the decline sug- this short-term decline in the past 8 years gests that unusual weather conditions in that has caught the attention of many 1978 contributed to the problem. Any people, and it has been widely publicized. tendency toward reestablishment of Similarly, the total commercial shellfish Vallisneria canericana (wild celery), previ- harvest rose gradually until the late 1960s, ously the most important species in the fell back slightly in the early 1970s, then estuary, probably was negated by ex- began a very steep increase in the late tremely high salinities prevalent in 1981 1970s, reaching an all-time high in 1979 (Davis and Brinson 1989). that was about twice the average for the The decline of SAV in the Pamlico River preceding two decades. But again, it has has been mentioned frequently in discus- been the decline since 1980 (down to about sions of the problems in the Albemarle- 1.5 times the 1950-1970 mean) that has Pamlico, and it is usually compared to the been the focus of attention. Trends for SAV decline documented in the Chesapeake individual fisheries are very mixed, with Bay (Orth and Moore 1982). There has some commercial catches risingat the same been a tendency to extrapolate the Pamlico time others were declining. For example, situation to other areas of the sounds. But since 1950, blue crab landings have actually, there is no historical evidence on doubled, shrimp landings have shown little SAV abundance for any other region except trend (but have displayed great inter- Major EnvIronmental Concerns 1 9 annual fluctuations), while oysters have other fish species examined during the declined. Flounder, croaker, and spot study were infected (Noga et al. 1989). landings all skyrocketed in the early 1970s, No primary causes for the diseases and since 1980 have fallen back, but remain have been established. The current working high in relation to the long-term means. hypothesis is that environmental stress Anadromous species generally have de- increases the susceptibility of the fishes to clined, either on a long-term, more-or-less the diseases. Salinity, in particular, is one continuous basis (alewives and American factor that is being examined, but to date shad), or in recentyears followingan earlier there have been no controlled experiments increase (striped bass and catfish). The performed to test a specific hypothesis. fishery declines are generally attributed to Another widely publicized perception a combination of over-fishing declining in North Carolina is that the number of water quality, and critical habitat loss or fish kills in the estuaries has increased in alteration (NCDNRCD 1987b). Reasons for recent years. Once again, unfortunately, the earlier increases in harvest are seldom there is no program to sample system- discussed. Trends in commercial fisheries atically; rather, the number of kills reported are covered in more detail in Chapter 7 of toauthorities is thebasis forthis conclusion. this report. Most reported kills occur in the Pamlico River, and menhaden are most often the Fish Diseases and Kills species involved (see Chapter 5). The most Episodes of infectious diseases that are frequent cause given by State agency scien- associated with the presence of some tists for the kills is low dissolved oxygen in microbes or parasites have been observed the bottom waters of the estuary (Stanley in the Albemarle-Pamlico system, as well 1985). Many feel that bottom water anoxia as elsewhere along the U.S. east coast. A is more common in the Pamlico now than "red sore" disease reached epidemic pro- in the past, even though the available data portions in some commercial species in for the past 20 years suggests otherwise Albemarle Sound during the 1970s (Esch (see Chapters 4 and 5). and Hazen 1980). In the Pamlico River estuary, the most prevalent of these prob- Impairment of Nursery Area lems seems to be ulcerative mycosis (UM), Function a fungal infection (Noga et al. 1989). The Initial development of the post-larval perception that these diseases are more stages of many fish and shellfish species serious nowthan in the past is not strongly occurs in primary nursery areas (PNAs) debated, despite the lack of any long-term located in the uppermost areas of estuaries systematic monitoring record. A recent, and their tributaries. The marshes and two-year monitoring effort (1985-1987) was small embayments fringingAlbemarle and conducted in the Pamlico River to assess Pamlico Sounds provide essential nursery the occurrence and species distribution of functions for a majority of the commercial ulcerative mycosis. Overall, 16% of the species in the North Carolina coastal area. menhaden sampled had UM lesions, but Because of their location, PNAs are very there was a strong seasonality in disease, sensitive to activities on adjacent uplands. with the highest incidences occurring in Freshwater drainage, land-use changes the Spring and Fall. At those times, up to and eutrophication can jeopardize the 100% of the menhaden in individual trawl functional aspects ofthe primary nurseries. samples were infected. Less than 1% Of However, the exact extent of impairment 2,0 Chapter 2 apparently is difficult to estimate, even area, but Core Sound and Bogue Sounds when historical data are present. For are affected (See Chapter 7 for more details). example, in North Ca *rolina, the Wildlife New techniques to more accurately mea- Resources Commission, the Division of sure contamination and potential human Marine Fisheries, and university research- impact are needed so that management ers have collected information concerning can more effectively allocate shellfish abundance of juvenile fishes in PNAs of resources. Relationships between contami- Pamlico Sound for some two decades, but nation and land-use characteristics are there has never been a definitive analysis poorly understood. of environmental or fish population trends in the nursery areas (Adams et al. 1989). Toxicant Effects The nursery areas are defined, for Very little is known about the effects of management purposes, on the basis of the toxicants on estuarine organisms or the numbers of juvenile fishes caught in a distribution of toxic substances in the standardized samplingroutine. Suchdesig- Albemarle-Pamlico Estuarine System. A nated areas are protected against damag- preliminary report has just been issued on ing fishing practices through regulations the first-ever systematic survey of of the Marine Fisheries Commission and Albemarle-Pamlico sediment heavy metals enforced by the Division of Marine Fish- concentrations. This report deals with the eries. Trawling, as well as oyster and clam Pamlico River estuary, the first of foursub- kicking (using propeller wash to excavate regions to be sampled over the next several clams) are prohibited in such areas. Impacts years (Riggs et al. 1989). The results of the from land use activities are less well-con- report are summarized in Table 2. 1. The trolled, and there is suspicion that in the authors of the report concluded that the future, these activities will pose the most low metals concentrations within Choco- serious threats to the long-term health of winity Bay surface sediments are similar the nursery areas. More specifically, the to concentrations occurring in subsurface greatest weakness in existing regulatory samples throughout the Pamlico (data not programs is thought to lie in controlling shown). The subsurface samples are inter- non-point sources of water pollution and in preted to represent the natural background regulating development landward of the during preindustrial conditions. If this is nurseries (Adams et al. 1989). the case, then the Chocowinity Bay sedi- ments show little metals enrichment from Shellfish Closures man's activities. On the other hand, Closure due to pathogenic microbial averages for all the Pamlico samples were contamination of shellfish waters in North about twice those for Chocowinity Bay, Carolina has remained relatively constant and in Kennedy Creek, a very 'Small over the past few years. About 50,000 tributary in the upper estuary at Wash- acres of productive shellfish bottoms are ington, NC, toxic metals may have been currently closed on temporary or perma- enriched by up to ten times the pre-man nent basis. Often, after heavy rainfall, concentrations. One factor not considered additional acreage is closed for several by the report's authors is the effect of days to several weeks. Albemarle Sound is sediment composition on metals concentra- not a contributor to commercial shellfish, tions. The percent organic matter and the but Pamlico Sound has oysters, clams, and sand-clay ratio are known to affect the bay scallops in several areas. Most of the affinity of estuarine sediments exposed to closure is to the south of the Pamlico Sound (otherwise) equal loadings ofmetals (White Major Environmenfal Concerns 2 1 A al. 1985). Riggs et al. (1989) did present data indicating that both of these factors varied considerably among their sampling locations, but their metals data apparently were not normalized with regard to these differences (J. Bray, personal communica- tion). The Pamlico concentrations data, taken as a whole, appear to be typical of estuaries that are considered to be relatively unpolluted with the metals. Table 2.1. Heavy metal concentrations (Ag1g) in the most and leastpollutedportions of the PamlicoRiver. "Pamlico average"is the trimmed mean for the whole system (i.e., all values more than 2 standard deviations from the mean were eliminated). Kennedy Creek is the most polluted and Chocowinity Bay is the least polluted portion of the system (from Riggs et al. 1989). Metal Pamlico Kennedy Creek Chocowinity Bay Average Average Min Max Average Min Max Arsenic 12.80 21.20 5.80 35.40 7.80 3.60 12.60 Cadmium 0.36 0.85 0.30 1.70 0.18 0.00 0.40 Chromium 10.50 27.30 5.90 58.80 4.60 2.50 8.30 Copper 13.60 51.50 17.60 84.40 6.40 3.50 9.80 Nickel 2.70 8.40 1.50 13.30 1.00 0.10 2.10 Lead 35.90 68.50 29.80 86.90 21.70 11.90 40.90 Zinc 77.00 377.90 151.20 490.30 35.60 17.10 56.60 Mercury 0.09 0.44 0.16 1.30 0.06 0.03 0.08 CHAPTER3 Trends in Nutrient Production: An Estimate Based on Changing Land Use and Population Of the wide variety of chemicals The ultimate question is: Even if stringent discharged into estuaries, two plant growth point and nonpoint source nutrient controls nutrients, nitrogen (N) and phosporus (P), are adopted, can [estuaries] survive in a have been identified again and again as desirable natural state in the face of among the most critical, with the potential continuing increases in nutrient sources for widespread impact on estuarine re- resulting from population growth and sources. Frequently, increases in popula- changing land use? Only time will tell. tion density, fertilizer use and conversion C.F. D'Elia (1987) of forest land to agriculture are cited as the causes for increased nutrients leading to 3) the amount contained in the manure of eutrophication in estuaries (e.g., Macknis farm animals. Loading, on the other hand, 1985; North Carolina DNRCD 1987). refers to the quantities of nutrient actually While it is intuitively obvious that in- reaching the estuary. There is a difference creased estuarine nutrient loading ought between the two because ofprocess ingthat to occur as the basin population grows, occurs as nutrients are transported from usually there are little or no historical data the sources toward the estuary. The produc- to clearly show the quantitative relation- tion rate normally exceeds the loading ships between the anthropogenic changes rate, because there are losses along the and changes in nutrient loading. Scores of way, due to such processes as sedimentation current N and P loading estimates have (for P) and denitrification (for N). been made for various estuarine drainage The reader should keep in mind that basins, including the Neuse, Chowan, and the estimates made in this study are for Tar-Pamlico River estuaries in NorthCaro- production, not loading. Loading from the lina (see Chapter 1), but studies ofhistorical basin can be measured directly by multiply- trends in nutrient loadinghave rarelybeen ing stream discharges times nutrient con- made. The objective of this study was to centrations. The data for the computations use historical population and agriculture normally come from monitoring flows and statistics for estimating trends in annual concentrations at the head of the estuary. N and P production within each of the The advantage of this method is obvious; it major Albemarle-Pamlico sub-basins. gives a direct measure of the actual quantity Actually, there is probably a large differ- of nutrient discharged from the watershed. ence between nutrientproduction within a However, the technique could not be used watershed and loading to an estuary. For in this study because of a lack of long-term purposes ofthis study, nutrientproduction monitoring of N and P concentrations at refers to the sum of 1) the nutrients dis- the mouths of the streams and rivers empty- charged from point sources, 2) that esti- inginto the estuaries in North Carolina. In mated to come from each non-point source fact, there are very few estuaries for which (e.g. field, forest, or the atmosphere), and 24 Chapter 3 such a data set is available. Another cropland, 3) other non-forested farmland disadvantage is that this method gives no (mostly idle cropland), 4) forests, 5) pas- indication of the sources of the nutrients. tureland, 6) urban land, and 7) all other land areas. Point sources included munici- Methods pal wastewater treatment plant and indus- Trends in land use and nutrient trial discharges. Atmospheric N depo- production in theAlbemarle-Pamlico basin sition was also included in the estimates. were estimated for the period 1880 through The primary sources for agricultural 1987 by summing computed estimates of land use, crop and animal statistics were annual point and nonpoint source produc- the censuses conducted by the U.S. Bureau tion for each county in the basin. The of the Census and the North Carolina and procedures were based on those of Thomas Virginia Departments ofAgriculture. Num- and Gilliam (1978), Craig and Kuenzler bers of each type of farm animals, acreages (1983), and Lowrance et al. (1985). For and harvests of the major crop types, and counties that are partly inside the basin, acreages of the pastureland and "other all data were weighted by the percentage farm land" categories came from the census of the county within the basin (Figure 3. 1, reports (Table 3.2). Forest acreage statistics Table 3. 1, Appendix 3. 1). Nonpoint sources were compiled from U.S. Department of considered included 1) eight categories of Agriculture Forest Service Resource Bulle- farm animals, 2) harvested agricultural tins for North Carolina and Virginia (Table 40 53 3 8 1 11 16 52 5 1 22 51 28 ...... 37 6 59 N 47 30 39 26 55 33 .67 68 69 54 23@- 14 58 56 10 49 61 42 63 31 46 24 1, 27 12. 20 17 21 41 4 18 It' 64 KILOMETERS 60 62 38 Is 0 20 40 60 80 66 "1 50 2 34 25 32 6S 36 3 ................ . ............... 45 3S 9 Figure 3.1. Map showing counties in each of the Albemarle-Pamlico 8ub-basins. The counties are identified in Table 3. 1. Trends in Nutrient Production 25 Table 3.1. North Carolina and Virginiacounties in Table 3.2. Sources ofdataon agricultural landuse, the Albemarle-Parnlico basin (numbers correspond crop harvests, farm animals, fertilizer sales, forest to those on map in Kgure 3. 1). and urban land areas, population, and municipal and industrial discharges. Map Map Map No. Name No. Name No. Name Agricultural Land Use, Crop Harvests and Farm Animals Inventory 1. Appomattox 24. Granville 47. Patrick U.S. Bureau of the Census. 1880-1982. Primary source. 2. Beaufort 25. Greene 48 Perquimane N.C. Department of Agriculture. 1923-1988. North 3. Bedford 26. Greeneville 49. Person CarolinaAgricultural statistics. Annual Bulletins and 4. Bertie 27. Guilford 60. Pitt Reports. 5. Botetourt 28. Halifax (VA) 61. Pittsylvania Virginia DepartmentofAgricultur-e. 1920-1988. Virlinia 6. Brunswick 29. Halifax (NQ 62. Prince George Agriculture Statistics (Annual Reports). 7. Camden 30. Henry 53. Roanoke 8. Campbell 31. Hertford 64. Rockingham Forest Data 9. Carteret 32. Hyde 65. Southampton Virginia 10.Caswell 33. Isle of Wight 66. Stokes U.S. Forest Service (1943); Cruilmhank and Evans (1945); 11. Charlotte 34. Johnston 67. Surry (VA) Larson and Bryan (1959); Sheffield (1976, 1977a, 12.Chowan 35. Jones 68. SurTy (NC) 1977b); Cost (1976); Brown (1985, 1986); Brown and 13. Craven 36. Lenoir 59. Sussex Craver (1985). 14. Currituck 37. Lunenburg 60. Tyrrell North Carolina 16. Dare 38. Martin 61. Vance U.S. Forest Service (1943); Cruikshank (1940); 16. Dinwiddie 39. Mecklenberg 62. Wake Cruikshank and Evans (1945); Larson (1957); Knight 17. Durham 40. Montgomery 63. Warren and McClure (1966); Welch and Knight (1974); Cost 18. Edgecombe 41. Nash 64. Washington (1974); Welch (1975); Bechtold (1985). 19. Floyd 42. Northampton 66. Wayne 20. Forsyth 43. Nottoway 66. Wilson Fertilizer Sales 21. Franklin (NQ 44. Omnge 67. Suffolk Virgiiiia Department ofAgriculture. 1956-1988. Fertilizer 22. Fmnklin (VA) 46. Pamlico 68. Chesapeake used and results of inspection (annual reports). 23. Gates 46. Pasquotank 69. Virginia Beach Richmond. U.S. Bureau of the Census. 1954, 1959, 1964. County data on fertilizer materials applied to croplands. Hargett and Berry (1985). Mehring et al. (1985). North Carolina Department of Agriculture. Various dates between 1956 and 1988. Data for some years Table 3.3. Coefficients used to compute nitrogen contained in the N.C. agricultural statistics mports and phosphorus production by five different land issued annually. use categories and by different types offarm animals. Values for forest are from Loehr (1974), values for Population and Urban Land Areas other land Uses are from Beaulac and Reckhow U.S. Bureau of the Census. 1880-1983. Census of (1980); values for animals are fi-om Barker (1987). Population. U.S. Bureau of the Census. 1949-1988. County and City Land use category Nitrogen Phosphorus Data Book. or animal type (kglyear) ft/year) Municipal and Industrial Discharges N.C. Stream Sanitation Committee (1946, 1957, 1959, Other Farmland 3.00/ha 0.40/ha 1961).. Other Land 3.00/ha 0.40/ha U.S. Public Health Service (1944, 1951, 1958, 1963). Forest 1.50/ha 0.20/ha U.S. Environmental Protection Agency (1971). Pastureland 4.00/ha 0.60/ha Hall (1970). Urban Land 6.00/ha 1. 10/ha Vir%inia State Water Control Board (1976). N.C. DivisionofEnvir-onmental Management (1986,1989) Virginia State Water Control Board: NPDES Self- Cattle Monitoring Data (1989). Dairy 121.00/animal 22.00/animal North Carolina Division ofErivironmental Management: Beef 48.10/animal 13.10/animal NPDES Self-Monitoring Data (1986-1989). Swine 11.90/animal 4.20/animal N.C. Board of Health. Various Dates. Annual reports. Horses 46.40/animal 11.00/animal Sheep 6.80/animal 1.50/animal Poultry Broilers 0.40/animal 0.10/animal Layers 0.56/animal 0.20/animal Turkeys 1.36/animal 0.52/animal 26 Chapter 3 3.2). Urban land areas were tallied from of non-forested, nonagricultural lands out- U.S. Bureau of Census data (Table 3.2). side the boundaries of the towns and cities Here "urban" areas are defined as the land (i.e., business properties, house lots, roads, areas within the limits of towns and cities ponds, cleared power line right-of-ways, with populations greater than 2,500. The etc.). "other" land use categorv was calculated as Quantities of N and P released in the the total basin land area minus the sum of excreta of farm animals were estimated by all the other land use type acreages. This multiplying numbers of animals times co- miscellaneous category consists primarily efficients (Table 3.3). Mass balance models Table 3.4. Atmospheric deposition of (D) in kglhalyear and mean concentration (C) in @kgl I of nitrogen andphosphorus at several locations within, or near, the AP watershed. N03-N NH4-N Total-P Location Year Precip. (D) (C) (D) (C) (D) (C) Ref. (in.) North Carolina 1975 5.54 (NO,+NH 4) 0.21 1 Duke Forest, NC 1972 1.46 0.74 0.28 21 2 Tar River Swamp,NC 1976 0.49 63 8 Rhode River 1974 108.6 3.91 360 0.57 53 3 Watershed, MD 1975 142.4 4.65 327 1.13 79 3 1976 115 5.57 484 0.74 65 3 Creeping Swamp,NC 1977 0.70 64 7 Clinton, NC 1980 116.5 2.60 223 1.66 134 ... 4 1981 113 2.37 210 1.66 138 --- 4 1983 127.2 2.24 176 1.71 136 --- 4 Lewiston, NC 1980 87.3 2.53 290 1.32 161 --- 4 1981 79.5 1.69 213 1.01 127 --- 4 1982 116.4 2.53 217 1.71 147 --- 4 1983 106.1 2.75 262 0.00 4 1984 133.7 3.75 280 1.32 99 --- 4 1986 117.6 1.96 167 1.24 153 --- 4 Raleigh, NC 1980 94.1 2.39 254 1.79 190 --- 4 1981 81.3 1.56 192 1.24 163 --- 4 1982 114.7 2.48 217 2.10 183 --- 4 1983 126.7 2.64 209 0.00 4 1984 123.9 2.30 186 1.84 149 4 1985 93.3 1.76 189 1.61 173 --- 4 Greenville, NC 1968 119 8.00 672 1.30 109 5 Roanoke, VA 1958 127 8.90 701 2.40 189 5 Cape Hatteras, NC 1958 137 3.20 234 1.20 88 6 1. Wells and Jorgensen 1975; 2. Wells et al. 1972; 3. Miklas et al. 1977; 4. Olsen and Watson 1986; Olsen and Slavich 1986; 5. Junge 1958; 6. Galloway et al. 1984; 7. Kuenzler et al. 1980; 8. Holmes 1977. Trends In Nutrient Production 27 for N and P were calculated for agricultural The amount of fertilizer applied cropland, following the methods of Craig annually to cropland was assumed to be and Kuenzler (1983) and Lowrance et al. equal to the amounts sold in, or shipped to, (1985). The annual cropland nutrient bud- the counties. Historical data on fertilizer gets for each AP sub-basin were estimated sales were taken from a number of sources by: (Table 3.2). Actually, most of the data are (Precipitation + Fertilizer + Symbiotic N-Fixation) - reported as tons of "mixed fertilizer" and (Harvest + Denitrification) = N Balance; and "fertilizer materials" either received in the (Precipitation + Fertilizer) - (Harvest) = P Balance. counties from manufacturers for retailers The "balances" when positive, were and consumers (North Carolina), orsold by each county (Virginia). To convert tons of assumed to represent the maximum "crop- mixed fertilizer and fertilizer materials land pollution potential"; i.e., the quantity into tons of elemental N and P, I multiplied of nutrient that could leave the watershed by the percentages of N and P in each type through surface or subsurface flow. Of of material sold. The N fixation rate used course, this assumes that nutrient storage for soybeans was 105 kg/ha per year (93.5 in the soil system is not changing (Frissel lb/acre per year) (Frissel 1978), and for 1978). peanuts the rate was assumed to be 112 Wet precipitation inputs for each year kg1ha per year (99.7 lb/acre peryear) (Craig were calculated by multiplying the total and Kuenzler 1983). The amounts of N annual precipitation (average of several and P harvested were determined by multi- sites within the Albemarle-Pamlico (AP) plying the nutrient content by the annual basin, times the estimated N and P concen- yields (e.g., bushels/acre) ofthe majorcrops trations, times land areas. N and P concen- (Gilbertson et al. 1978; Romaine 1965) trations in precipitation for the mid-1980s (Table 3.5). Finally, denitrification rates were based on measurements from were assumed to be 15% of the applied National Atmospheric Deposition Program fertilizer N (Porter 1975; Thomas and stations in the AP basin, and on other recent measurements (Table 3.4); but his- torical Nconcentrations had to be calculated indirectly. This was done by assuming Table 3.5. Nitrogen and phosphorus content in that N deposition in 1880 was 20% of the harvested crop materials (Gilbertson et al. 1978, rate today, and that the rate of change Romaine 1965). since 1880 has been exponential. These Harvest Pounds/Harvest Unit assumptions are, in turn, based on mea- Crop Unit Nitrogen Phosphorus sured (present-day) atmospheric N deposi- tion rates in remote areas (Table 3.4) and Com (gmin) Bushel 0.900 0.153 Com (silage) Ton 4.0 0.45 on estimated historical trends in N oxide Oats (grain) Bushel 0.625 0.113 production in the southeastern U.S. (see Wheat (grain) Bushel 1.250 0.275 Discussion). The total atmospheric N Hay Alfalfa Ton 45.000 4.500 deposition was twice the wet precipitation Bluegrass Ton 30.000 4.600 loading, based on the assumption that dry Coastal Bermuda Ton 23.125 3.876 Cowpea Ton 60.000 5.500 deposition equals wet deposition (see Peanut Ton 46.667 4.889 Discussion). No information on historical Red Clover Ton 40.000 4.400 trends in atmospheric P production or Soybean Ton 45.000 4.600 Timothy Ton 24.000 4.400 deposition were available; therefore, a con- Cotton Pound 0.018 0.002 stant rate of deposition (0.5 kg/ha/yr) was Peanuts (nuts) Pounds 0.036 0.002 assumed, based on measurements in the Soybeans (grain) Bushels 3.750 0.375 AP region (Table 3.4). Tobacco (leaves) Pounds 0.038 0.004 28 Chapter 3 Gilliam 1978). discharges within eachAP sub-basin (>O.l Nutrient production was not calculated mgd), as well as information on N and P by this mass balance approach for any land concentrations in the industrial discharges. use category other than harvested cropland. The most difficult parameters to estimate Instead, export coefficients (kg N and P per were the treatment factors that would be ha per year) were multiplied times total applied to each discharge. Fortunately, sub-basin acreages to give the "expected" there were periodic inventories ofmunicipal nutrient yields from pastureland, forests, wastewater facilities from 1942 through urban, other farm lands, and "other"areas. 1985 (Table 3.2) which included detailed N and P "yield" coefficients foreach of these information on the levels of treatment pro- land-use categories were taken from the vided by each facility and the size of the literature (Table 3.3). "sewered" population. Another valuable Both municipal and industrial dis- source was the N.C. Department of Health charges *were included in the point-source annual reports, which yielded information nutrient production estimates. For indus- on the early history of municipal waste- trial sources the annual production was water treatment in North Carolina. For calculated by multiplying daily discharge years before 1942, the sewered population times thetotal NorP effluent concentration was assumed to be equal to the city times 365. Municipal production was population (U.S. Census Bureau data), back computed as to the time when the sewage collection system for the town was first constructed. kg N or P/year The per capita annual N and P produc- Sewered * Per capita Treatment * 365 tion was taken as 4.6 kg N and 1.2 kg P population daily N or P factor (Gakstatter et al. 1978), and the N treat- production ment factors ranged from 1 (untreated) to 0.47 (secondary treatment), depending on where sewered population is the estimated the type of wastewater treatment practiced number of persons served by the citys by the municipal treatment plant. P treat- wastewater collection system. Information ment factors ranged from 1.0 to 0.74 (Table on industrial and municipal discharges 3.6)_ was gleaned from several sources. The From 1880 through 1920 the nutrient NPDES Compliance Monitoring data files production estimates were computed at were searched to provide lists of all current 10-year intervals, correspondingto the U.S. Agricultural census dates. After 1920, more frequent agriculture census data were Table 3.6. Per capita total nitrogen and total available so that I was able to make phosphorus loads (kglyear) in wastewater effluents calculations at 4-to-5 year intervals. Many as a function of treatment type (Gakstatter et al. of the data were first compiled in the 1978). -Treatment factors are equal to the load for a English units of measure (acres of land, given treatment type divided by the load for no pounds of crop harvest, tons of fertilizer treatment. sold, square miles of county land area, etc.) Nitrogen Phosphorus in which they were originally recorded Treatment type kg/year Factor kg/year Factor (e.g., Appendix 3.3). But at some stage in None 4.6 1.00 1.2 1.00 the procedure, all these values were Primary 4.2 0.90 1.1 0.90 converted to metric units, and the summed Secondary Trickling filter 2.9 0.62 1.0 0.82 nutrient production rates are expressed as Activated sludge 2.2 0.47 1.0 0.82 kg(ha/year, or metric tons per year. Stabilization pond 1.9 0.42 0.9 0.74 Results are presented for the whole Trends in Nutrient Production 29 Albemarle-Pamlico watershed, as well as Pastured land increased from about 0.8 for each of the major sub-basins: Chowan million acres (0.32 million ha) in 1925 to a River, Roanoke River, Tar-Pamlico River, peak of 1.1 million acres (0.44 million ha) Neuse River, and "Coastal". The Coastal in the mid-1950s, and has since declined to sub-basin includes all land area down- around 0.85 million acres (0.34 million ha). stream from the mouths of the river estu- In addition to the 1.1 million acre decline in aries, primarily parts of Camden, Curri- harvested cropland since 1925, there must tuck, Dare, Hyde, Pamlico, Pasquotank, have been about 2 million acres of other Perquimans, Tyrrell and Washington land in farms "lost" duringthat time period, Counties in North Carolina (Figure 3.1, since the total "acres in farms"has declined Appendix 3.1). In some of the figures and from 11 million to around 8 million (4.45 tables (especially Appendix tables), the million to 3.2 million ha) (Figure 3.3a). "Coastal" sub-basin is further sub-divided Finally, urban land areas (defined here as into the "Albemarle" and "Pamlico" sub- land in towns and cities >2,500 population) basins, in reference to the sound into which increased rapidly beginning about 1930, the land drains. and today amounts to around 0.3 million acres (0.12 million ha), or about 2% of the Results total AP basin land area. Land Use There are not good data on any of the There have been relatively small major land use categories, except harvested changes in the amounts of land in each of cropland, before 1930, so that the 1880- the major land-use categories in the 1925 values used in the nutrient production Albemarle-Pamlico basin use during the calculations are only estimates, but prob- past century (Figures 3.2 and 3.3, Appendix ably are not far off. Judging from the 3.2). Forest has always been the most number of cattle on farms, the known prevalent land use in the basin, ranging cropland acreages, and the total land in between 57.6% and 63.7% of the total farms values, and assuming that urban basin land area. There was a peak in forest land use was much less than 1% before acreage in the 1960s. Harvested cropland, 1930, the forested areas must have been the second most prevalent land use, peaked about the same in the late 1800s as in at 3.55 million acres (1.4 million ha) in 1925. That is the assumption I have made 1940 and has generally declined since, to for purposes of the nutrient production 2.43 million (1.0 million ha) in 1987. calculations. Actually, the errors in this assumption are probably much less impor- Figure 3.2. Percentages of land use by six 7- major categories for the Albemarle-Pamlico to M Urban a estuarine system drainage area, 1925-1982. M = 01ther 75%-= Other Farmland Is S Pasture 0 crops CO 50%_ 0 M Forest CL 25%- E A 0% 80 90 0 10 20 25 30 35 40 45 50 54 50 64 69 74 78 52 87 Year (1880-1987) 30 Chapter 3 Figure 3.3. Historical Chowan Roanoke Tar A trends in land areas (land in farms, harvested cropland, 0-15 Neuse Coastal Pasture-land, forest, and C urban) by sub-basin in the .2 Albemarle-Pamlico drainage basin. E 9- cd LL .G 6 3- 0 80 90 0 10 20 25 30 35 40 45 50 54 59 64 69 74 78 82 87 Year (1880-1987) 4000 B Coastal 0 Neuse 3000- Ter Roanoke Chowan 2000 CI e 0 1000- 0 80 90 0 10 20 25 30 35 40 45 50 54 59 64 69 74 78 82 87 Year (1880-1987) 1200 C Coastal "00 M N.use 0 Tar 800- Roanoke Chowan 600- 400- 200- Cd CL 80 90 0 10 20 25 3@ 315 410 415 510 514 519 614 619 714 78 82 87 Year (1880-1987) Trends in Nutrient Production 31 Figure 3.3. continued 12 - D Coastal lo- Neuse Tar .2 8- Roanoke Chowan 0) 6- 4 0 LL 2- 0.. . . . . 80 90 0 10 20 25 30 35 40 45 50 54 59 64 69 74 78 82 87 Year (1880-1987) 350 - E Coastal 300 - Neuse 250 - Tar Roanoke 0 M 200 - Chowar. U) ISO- 0) 100- 50- 0- 80 0 10 20 25 30 35 40 45 50 64 59 64 69 74 78 82 87 Year (1880- 1987) tant than those in choosing the export planted in significant acreages in the 1930s coefficients (see Discussion). and 1940s, but up until about 1960 never Some crops are much more important made up more than 5-10% of the total. in the AP basin now than in the past, while However, by 1987 there were 0.85 million others have become relatively unimportant acres (0.34 million ha) of soybeans, which over the years (Figure 3.4, Appendix 3.3). was about one-third of the total harvested In terms of acres harvested, corn has been cropland. dominant throughout the past century, In contrast, tobacco and, especially cot- accounting for between 0.8 million acres ton, acreages have declined in the and 1.5 million acres (0.32-0.61 million Albemarle-Pamlico basin (Figure 3.4). ha), or, on average, about 35% of the total Annual tobacco plantings peaked in the harvested cropland. The second most wide- 1930s and 1940s at around 0.6 million ly planted crop today, soybeans, was first acres (0.24 million ha), but now are down 32 Chapter 3 1000- Figure 3.4. Historical trends A in amount offarm land used Coastal for six major crops, by sub- r_ 800- Nauss basin, in the Albemarle- cc cc Pamlico basin, 1880-1987. M Tar 0 Roanoke 600- 4) Chowan CD 400- C 0 200- 0 0- 80 90 0 10 20 25 30 35 40 45 54 59 64 69 74 78 82 87 Year (1880-1987) 2000- B 0 1800- Chowan Roanoke Tar cc 1600- Neuse Coastal cc :3 0 1400- 1200- 1000- < 800- 0 600- 400- cc 200- 0- 80 90 0 10 20 25 30 35 40 45 50 54 59 @9 ;4 ;8 8`7 Year (1880-1987) 800- D 700- Coastal Neuse (A 600- Tar cc w = 500- Roanoke 0 Chowan 400- 300- >% 200- to X NMI too- I ! O_q 90 0 20 25 30 35 40 45 50 64 5 so 0 1 9 64 69 74 78 82 87 Year (1880-1987) Trends In Nutrient Production 33 Figure 3.4. continued 400- Coastal Neuse to 300- Tar 0 Roanoke t Chowan 200- .PC too- 0- 80 90 0 10 20 25 30 35 40 45 50 54 59 64 69 74 78 82 87 Year (1880-1987) 1200- G Coastal 'Oa 'ODO Cd Tar 0 800- Roanoke Chowan GDO - r- 400- .0 200- 0 --F I---- I --- 80 90 0 10 20 26 30 36 40 45 50 54 59 64 69 74 78 82 87 Year (1880-1987) 700- = Coastal 6w - Neuse CIS 500- Tar 0) :3 0 Roanoke 400- Chowan 300- 0 200- J2 100- 10- so 90 0 10 20 25 30 354 0 45 @O 64 @9 @4 @9 78 82 87 Year (1880-1987) 34 Chapter 3 to around 0.2 million acres (0.08 million million acres orO.12 million ha) but declined ha), or approximately 7% of total cropland rapidly, then rose slightly in the 1950s, acreage. Cotton production in the basin and have since fallen back to become was very important up until the 1930s, but insignificant in recent times in comparison then it declined rapidly and had practically to other crops. Peanut production in the ceased by about 1970. At its peak in the AP basin increased rapidly in the early 1920s, cotton was the second most widely part of this century, and in terms of acres planted crop, taking up as much as 35% of grown, peaked around 1945 at 0.35 million the total cropland in some years. Wheat acres (0.14 million ha). Since 1954, the and other small grains have never been peanut acreage has remained nearly con- dominant crops in this area. In 1987 only stant at about 0.23 million (0.09 million about 12% ofAP basin cropland (0.3 million ha). Finally, hay crops are a relatively acres or 0.12 million ha) was devoted to minor part of the total cropland use today wheat, and this was the second highest (<10% of total). This crop was somewhat acreage planted in wheat, at least during a more important in the past, but was never census year, over the past 100 years. Oats dominant. The largest hay acreages were were widely grown in the late 1800s, (0.3 in the 1940s, when they peaked at around 160- A 140- = Coastal Figure 3.5. Trends in nitrogen Cd and phosphorus sold as 0 M Nauss commercial fertilizer, by sub- =0 Tar basin, in theAlbemarle-Parnlico loo- Roanoke drainage basin, 1880-1987. M Chowan 80- t Go- 40- 0 Z 20- a, C 0 - 9 80 @O 1@ 20 25 30 35 40 45 50 54 59 64 69 74 78 82 87 Year (1880-1987) M 50- V B Coastal 0 4o- Nauss Tar Roanoke 30- M Chowan LL 20- 0 CL to- OD 0 0_@Al 12 80 90 0 10 20 25 @0 35 40 45 50 54 69 64 69 74 78 82 87 Year (1880-1987) Trends In Nutrient Production 35 0.7 million acres (0.28 million ha). increased about 7-fold between 1940 and 1978, when a peak of 140,000 tons N (127.6 Harvested Cropland Nuffient Mass million kg N) was reached. N fertilizer Balance sales, like P sales, have declined slightly in Since about 1900, the major nutrient the 1980s, but some of the apparent decline inputs to croplands have been N and P may be attributable to low demand (i.e., fertilizer. Large increases in the use of poor weather) during the census years, fertilizers have occurred in the AP basin rather than to a long-term downward trend. over the past 50 years (Figure 3.5, Appendix That was certainly the case in 1987, when 3.4). Annual P sales peaked in the 1960s acres planted, fertilizer use, and harvest at around 45,000 tons P (40.9 million kgp), were all lower than normal due to drought but have declined to 25,000-30,000 tons P conditions in much of the region. (22.7-27.3 million kgP) in the 1980s (Figure The other variable nutrient input on 3.5b). Meanwhile, however, there has the cropland has been atmospheric deposi- been a very rapid rise in the amount of N tion. As will be discussed below, there fertilizer sold. In fact, annual sales probably has been about a five-fold increase in the areal rate ofatmospheric N deposition Figure 3.6. Trends in yield (pounds 120- A and bu8hels per acre) for 8even major crop8 in theAlbemarle-Pamlico basin, too- 1880-1987. Com 80- oats Go - Wheat V 40- 20- Soybeans 0__ 80 90 0 10 20 25 30 35 40 45 @O @4 5@ @4 6@ 74 78 82 87 Year (1880-1987) 35M - B 3000 - PeanLft 2500- 2000- 0 Tobacco S 1500- Wheat Soybeans 4Nanul Tobacco .LD 1000- Coldon 500 0 80 90 0 10 20 26 30 35 40 45 50 54 59 64 69 74 78 82 87 Year (1880-1987) 36 Chapter 3 TableS.7. Croplands N and P mass balance, on a per hectare basis, for selected years. Input/Output 1880 1900 1920 1940 1959 1974 1987 (kg N/ha) N fertilizer 0.84 5.07 17.40 16.34 41.25 111.04 96.70 Harvest -8.77 -12.78 -19.42 -29.73 -47.71 -80.41 -83.99 N fixation 0.00 6.26 9.01 17.31 19.79 36.17 46.02 Denitrification -0.12 -0.76 -2.61 -2.45 -6.18 -16.65 -14.50 Precipitation 0.80 0.80 1.10 2.25 3.32 3.93 4.32 Balance -7.25 -1.40 5.48 3.71 10.47 54.08 48.54 (kg P/ha) Fertilizer 1.69 8.45 22.41 16.70 32.68 36.05 24.96 Precipitation 0.27 0.29 0.31 0.36 0.55 0.54 0.59 Harvest -1.48 -1.94 -2.70 -2.70 -6.03 -10.17 -10.24 Balance 0.48 6.81 20.02 14.36 27.19 26.42 15.30 250- in the AP basin over the past Fort Nft Precip century. However, the 2W - Harv Dent Balance atmospheric N input to crop- iso- lands today is still very small 'a 11)0- in comparison to fertilizer N r_ Inputs 0 and N fixation. 50- With increasing fertilizer 0 soon and pesticides use, and more -510 Outputs productive crop varieties, in- -iou - creases in yields (bushels or _150- pounds per acre) for some 8@ 9`0 0 10 20 30 40 5@ @9 78 87 crops has been very Year (1880-1987) impressive (Figure 3.6, Appendices 3.5, 3.6). The so- greatestyield increases came Balance between about 1940 and the Harv 1970s. For example, corn 3o- Precip yield increased about 5-fold, Fart from around 20 bushels/acre r- 20- 0 to over 100 bushels/acre. Inputs @i 10- Wheat yields improved about 22 4-fold, oats by a factor ofabout 001 M 2.5, and soybean yield -10- Outputs approximately doubled over -2U - the past 40 years or so. There 0 10 20 30 40 50 59 _T_ 69 78 87 ave been impressive Yew (1880-1987) increases in the tobacco and peanut yields also (Figure Figure 3.7. Historical trends in croplandnitrogen andphosphorus 3.6). mass balances in the Albemarle-Pamlico basin, 1880-1987. Cropland nutrient mass balances for all of the AP basin Trends in Nutrient Production 37 Figure 3.8. Historial trends in 16DO - numbers ofeightmajorcategories A of farm animals, by sub-basin, 1400- M Chowan ME Roanoke Tar in theAlbemarle-Pamlico basin, NeuSe coastal 1880-1987. 1200- 10DO - 0 800- 6w - S @: 400- 200 so 90 0 10 20 253 03 5 40 4550 64 59 64 69 74 ; 8 @2 87 Year (1880-1987) 600- Chowan Roanoke Tar 5M Neuse Coastal 400- 300- 0 200- 100 0 80 90 0 10 20 25 30 35 40 45 50 64 59 64 69 74 78 82 87 Year (1880-1987) 200- Coastal Neuse ISO- Tar Roanoke Chowan 0 loo- to 4) 11111111111111 '11 Tar 50 - 0 80 90 0 10 20 25 30 35 40 45 50 54 59 64 69 74 78 82 87 Year (1880-1987) 38 Chapter 3 140- D Figure 3.8. continued Coastal 120- Neuse V too- Tar C Roanoke So- Chowan o 60- 40- 0 20 0- so 90 0 10 20 26 30 35 40 45 50 64 69 64 69 74 78 82 87 Year (1880-1987) 180- ISO- Coastal 140- Neuse Tar 120- Roanoke 100- Chowan 80- 60- 40 20- 0- 80 90 0 10 20 25 30 35 40 45 50 64 59 @4 @9 74 78 82 87 Year (1880-1987) 20- F Chowan Roanoke Tar Neuse Coastal .2 to- 0-1 so 90 0 10 20 26 30 35 40 45 So 54 59 64 69 74 78 82 87 Year (1880-1987) Trends In Nutrient Production 39 20- Figure 3.8. continued M Chowan Roanoke Tar G M Nauss Coastal 16- 0 to- 0 L. CO 6- 0- so 90 0 10 20 25 30 36 40 45 50 54 59 64 69 74 78 82 87 Year (1880-1987) 2500- H coastal 20DO - Nauss Tar Roanoke 1500- Chowan 0 500 0 so 90 0 10 20 25 30 35 40 45 50 54 59 S4 69 74 78 82 87 Year (1880-1987) are shown in Figure 3.7. The N "balance", about the same as that described above for which represents the difference between the whole AP basin; what differences there inputs and outputs, has increased gradually are due simply to differences in the amount from near zero, or less than zero, in the late of harvested cropland. There was a rapid 1800s, to around 50 million kg N per year increase in the 1950-1970 period, with a by 1964, but appears to not have changed leveling off since then (Table 3.7). Excess greatly since then. The P "balance", on the cropland P also followed about the same other hand, increased most rapidly in the pattern described above forthe whole basin, early 1900s, reaching a peak of about 36 and the per hectare values have ranged million kg P in the 1950s. Since, then, the from 0.5 kg in 1880 to as high as 31.3 kg in P balance has declined to about 20 million 1969. In recent years the excess P has been kg P, or about the same amount as in the around 15 kg/ha. period 1910-1940. The annual excess cropland N has ranged from -7.2 kg/ha in the late 1880 to as high as 54.1 kg/ha in 1974. The trend is 40 Chapter 3 of increase, so that now there are more Farm AnImal Inventories and than ever (1.4 million) of these animals. Nutrient Production The increases in swine since 1959 have In every census since 1880, swine have taken place in the Tar, Neuse, and Coastal been the most numerous large farm animal sub-basins, while inventories in the in the Albemarle-Pamlico basin (Figure Roanoke and Chowan basins have fallen 3.8, Appendix 3.7). Between 1880 and slightly. Swine production is concentrated 1940, the swine inventory fluctuated be- in the central coastal plain in North Caro- tween 500,000 and 850,000 head, but after lina; thus the Tar River Basin has 23% of 1945 it rose steadily, and by 1959 there all the hogs in the AP system, and 38% are were over 1 million head. A decline in the in the Neuse River basin. early 1960s was followed by another period Cattle, on the other hand, have always been most numerous in the northwestern 80- Figure 3.9. Historical trends in annual nitrogen and z Chowan Roanoke= Tar phosphorus produced in 60 - excreta of farm animals Neuse Coastal (millions of kg) in each sub- basin of the Albemarle- 40- Pamlico drainage area, 1880- 1987. W ,-20- z 2 0- 80 90 0 10 20 30 40 50 59 69 78 87 YEAR (1880-1987) 25- CHOWAN ROANOKE= TAR Z 20 - 0 E3 NEUSE COASTAL 10- Uj 5- 01 80 90 10 20 30 40 50 59 69 78 87 YEAR (1880-1987) Trends In Nutrient Production 41 part ofthe AP basin. Total numbers ranged Table 3.8. Major nutrient point sources in the between 250,000 and 350,000 up until the Albemarle-Pamlico basin. Numbers correspond to 1940s, but showed no particular trend. ranks inFigure3.10. M =Municipal; I= Industrial. Since then, there has been a general Number Facility Type Sub-basin increase, to around 570,000 today (Figure 3.8). Most of the increase has been in the 1 Raleigh, NC M Neuse 2 Weyerhaeuser I Roanoke Roanoke River basin, probably in the 3 Union Camp I Chowan western Piedmont and Appalachian foot- 4 Weyerhaeuser I Neuse hills sections. Since 1930, the number of 6 Roanoke, VA M Roanoke 6 Durham, NC (Northaide) M Neuse cattle in that basin has nearly tripled, and 7 Rocky Mount, NC M Tar there has been nearly a doubling in the 8 Danville, VA M Roanoke 9 Greenville, NC M Tar Chowan basin. But in the more southerly 10 Cary, NC M Neuse Tar, Neuse, and Coastal basins, the 11 Wilson, NC M Neuse increases have been much smaller. 12 Goldsboro, NC M Neuse 13 Martinsville, VA M Roanoke Numbers of mules peaked in the 1940s 14 Kinston, NC M Neuse at around 180,000, but they, along with 16 Texasgulf Chemicals I Tar horses and sheep, have become an 16 Havelock, NC M Neuse 17 New Bern, NC M Neuse insignificant part of the total farm animals 18 Reidsville, NC M Roanoke inventory in the past two decades (Figure 19 Salem, VA M Roanoke 3.8). Mules could not compete with tractors, 20 Eden, NC M * Roanoke which rapidly began to take the place of human and animal power in southern transportation for farm families. Finally, agriculture in the late 1940s. In just two sheep raising in the AP basin declined decades, between 1950 and 1970, the mule rapidly during the first quarter of this had practically disappeared from farms in century, as reflected in the inventories, the AP region. Likewise, inventories of which went from 155,000 animals in 1880 horses had shown a steep decline earlier in to only 30,000 by 1925 (Figure 3.8). the 1920s, as automobiles and trucks Poultry production in some areas of the became the more common method of AP basin has increased dramatically in the Figure 3.10. Rankingofpoint 600- sources in the Albemarle- cr) Pamlico basin, in terms ofkgN 0 500- producedper year in 1986. z Nitrogen Phosphorus M 400- 0 300- 200- cc W 100- 0 1 3 5 7 9 11 13 15 17 19 1986 RANKING 42 Chapter 3 past two decades. Growth of the poultry today. Some Piedmont and coastal areas in industry has been one of the most notable North Carolina have become areas of in- developments in southern agriculture since tense poultry production. The industry World War 11. Historically, poultry on tends to be locally concentrated. For most southern farms had been a barnyard example, in 1987 about one half the total business to provide eggs for the table and numberof chickens in North Carolina were to earn a little "egg money" for groceries in only 6 of the State's 100 counties (N.C. and other things. Chicken was not eaten Department of Agriculture 1988). One regularly but was something families ate such area is in the central coastal plain, on Sunday and on special occasions. within the Tar and Neuse River watersheds. Chickens were kept mainly for the eggs. Thus nearly half of the total broilers and But by the mid- 1940's, there had developed chickens inventoried in the AP region in "businessmen-farmer teams" for the com- 1987 were in those two sub-basins (Figure mercial production of "eating chickens", or 3.8). Turkey farming is even more focused; "broilers." The businessman hatched the in 1987, 80% of the total inventory was in eggs, contracted with farmers to raise the the Neuse basin (Figure 3.8). Total AP chicks on feed that he supplied from his poultry inventories (broilers, chickens, and mill to growers on credit, and finally pro- turkeys) grewslowly from around 2 million cessed and marketed the birds. Farmers in 1880 to approximately 6 million in 1959. provided the housing, labor, and manage- Since then, however, poultry inventories ment in return for an assured market (Fite have increased at an amazing rate, so that 1984). by 1987 there were over 37 million of these This "vertical integration"of the indus- animals in the Albemarle-Pamlico Basin. try, along with increased efficiency of feed N production from farm animals in- utilization, led to lower prices (relative to creased slowly between 1880 and 1969, other meats). This, i n turn, helped increase but has increased rapidly since 1969, so consumer demand, producing a boom in that over the past century this N source broiler and egg production that continues has almost doubled (Figure 3.9, Appendix 5- ALBEMARLE-PAMLICO BASIN Figure 3.11. 77rends in point source loadings of -C0 4 -M Industrial nitrogen (N) and Z phosphorus (P) fi-om point 0 Municipal sources in the Albemarle- 3- Pamlico watershed, 1880- N = NITROGEN P = PHOSPHORUS 1887. cr 2 - W 80 90 00 10 20 30 40 50 60 70 80 86 NP NP NP NP NP NP NP NP NP NP NP NP YEAR n Trends In Nutrient Production 43 3.8). In 1880 animal produced about 40 there is little variation in the level of treat- million kg N, compared to 45 million kg in ment (i.e., percent N and P removal) within 1969. But the 1987 value was almost 75 the region. However, the rate of increase million kg/year. Cattle have contributed slowed, at least temporarily, about mid- 40%-60% of the total animal N in most century as secondary treatment became census years, and swine have usually made more widespread (Figure 3.11). the second largest contribution (15%-25%). In 1986 the estimated total municipal In the past, horses, mules, and poultry also N and P loading's were 3.07 million kg and made significant contributions to the 1.06 million kg, respectively. About half animal excreta N. But in recent yearsJust the total N came from cities and towns in three animal types - cattle, swine, and the Neuse basin, 28% from the Roanoke poultry - have been responsible for more basin, 16% from the Tarbasin, 5% from the than 95% of the total. Since 1978, the Chowan basin, and only about 3% from the percentages have been about 50% from coastal areas (Figure 3.11). Municipal P cattle, 20% from swine, and 30% from loading was distributed among the basins poultry. in about the same proportions. Animal excreta P amounted to about Although the AP basin is relatively 11 million kgin 1880, and was only slightly unindustrialized, there are a few major higher (12 million kg) in 1969. By 1987 the industries that contribute large quantities animal P had increased to over 21 million of N and P; in some cases much more than kg/year. The pattern has been similar to the municipal sources. In 1986 the indus- that for N, both in terms of the changes in trial sources contributed about 1.04 million production rate, and the percentages con- kg N and 0.56 million kg P. This amounts tributed by each animal type. In recent to about one-fourth and one-third the total years about 40% of the P has come from AP basin point source N and P, respectively. cattle, about 30% from swine, and about Two types of industries - pulp and paper 30% from poultry. mills and phosphate mining - predomi- nate, in terms of N and P production. Most PoInt-Source Nutrient Production of these have come to the region since The urban population, and hence the World War II. There are pulp/paper mills estimated sewered population, in the on the lower Roanoke River, tributaries of Albemarle-Pamlico, has risen rapidly in the Chowan river, and the lower Neuse recent years, and today the largest urban River. Point source loading in the Chowan centers are in the western areas of the sub- River basin is especially dominated by the basins, primarily in the Raleigh-Durham industrial sources, which produce about area in North Carolina (Neuse Riverbasin) twice as much N and P as the municipal and in the Roanoke, Virginia area (Roanoke plants in this relatively unurbanized basin Riverbasin). A high percentage ofthe total (Figure3.11). The Tar-Pamlico River pre- municipal loadingcomes from a small num- sents an unusual situation also. There, the ber of the largest cities (Figure 3.10 and Texasgulf phosphate mine discharge Table 3.8). Tracking this population in- dominates the point source P loading. Since crease, point source loading in the AP it was built in 1964, this single source has basin rose rapidly during the first half of accounted for two-thirds to three-fourths this century (Figure 3.11, Appendix 3.9), of the total annual point source P produced and the geographical distribution of the in the Tar-Pamlico basin. municipal loadinghas corresponded closely to the population patterns, suggestingthat 44 Chapter 3 60- A 50- z 2 40- POINT SOURCES 30- URBAN RUNOFF FARM ANIMALS W >- 20- CROPLAND RUNOFF 1-1 z PASTURE RUNOFF 0 @61. 10- OTHER RUNOFF FOREST RUNOFF 0- 80 90 0 10 20 30 40 50 59 69 78 87 YEAR Figare3.12. Trends in estimated total nitrogen production, from all point and non-point sources, in the Albemarle-Pamlico watershed and from each major sub-basin, 1880-1987. Similar assumptions were made for P, Trends In Total Nuffient Productlon with one difference; the cropland P produc- by All Sources tion was assumed to be one-fifth of the Time series plots for trends in estimated computed P balance. total N production from all sources, both For the whole Albemarle-Pamlico basin, nonpoint and point, are given in Figure the total annual N production from all 3.12. Several important assumptions have sources is estimated to have nearly doubled been made regarding these estimates: over the past century, from around 30 1. The production by forests, other land million kg in 1880 to 55 million kg in 1987. (here the sum of two land use types Between 1880 and 1959, the increase was described above: "other farmland" and only about5 million kg(18%). Then, prima- "other land"), pasture, and urban lands rily because of the rapid increase in the was calculated by multiplying acreages cropland balance in the 1960s, the total N times constant yield coefficients. I production rose rapidly, but appears to 2. The cropland N production was have remained nearly constant in the 1970s assumed to be equal to one-third of the and 1980s. cropland N balance calculated above. The percentage contributions by each 3. Animal N production was assumed N source have changed greatly over the to be equal to 5% ofthe animal N in excreta. past century. In 1880, the most important Trends in Nutrient Production 45 14- B "12 - z 210 - _j _j POINT SOURCES 8- URBAN RUNOFF FARM ANIMALS 6- W CROPLAND RUNOFF 4- PASTURE RUNOFF 0 @e 2- OTHER RUNOFF FOREST RUNOFF 0- 80 90 0 10 20 30 40 50 59 69 78 87 YEAR Figure 3.13. Trends in estimated phosphorus production, from all point and non-point sources, in the Albemarle-Pamlico watershed, and from each mqjor sub-basin. sources were forest (45%) and "other" lands 1900s, but is no greater today than in (35%). Pasture and farm animals contrib- 1930, although there have been relatively uted almost all the remainder (Figure 3.12). large short-term fluctuations. The Coastal Today, according to these estimates, the basin N production also rose fairly gradu- forest, other lands, and pasture N produc- ally, from around 3 million kg in 1880 to tion is about the same, in terms of kglyear, about 5.3 million kg in 1978. In this area, but new sources have diminished the the increases from cropland have been relative importance of these three. The offset, to some extent, by decreases from most important new N source is cropland forest and "other" land. The Roanoke excess N, which now makes up about 30% basin followed a pattern similar to that for of the total. Animals, urban runoff, and the Tar and Neuse; i.e., a gradual increase point sources together contribute about up until the 1950s, followed by a rapid rise in 17% of the total. N production in the 1960s. But in the Two of the sub-basins, the Tar and the Roanoke, the overall increase has not been Neuse, appear to have experienced larger as great as in the other two sub-basins. In relative increases in N production than the other words, the Roanoke N product ion Chowan, Roanoke, or Coastal sub-basins has increased by about 50% over the past (Figure 3.12). In the Chowan basin, N century, whereas in the Tar and the Neuse production rose gradually in the early basins, the increases have been 80% and 46 Chapter 3 115 %respectively. Most of this difference variable. The long-term, gradual increase appears to be due to much greater increases in P production appears to be continuing, in cropland N balance in the Tar and Neuse although there was less P produced in 1982 than in the less agricultural Roanoke basin. and 1987 than in the two previous census The most notable difference between years. total N production and total P production in theAP basin is that P production appears DiScussion to have declined in recent years, particu- Likely sources of error associated with larly in the Chowan and Roanoke sub- the municipal loading estimates include basins (Figure 3.13). For the whole AP the sewered population values and the watershed, total P production rose rapidly treatment factors used in the calculations. from around 4.5 million kg in 1880 to As noted above (see Methods) the sewered nearly 10 million kg by 1920. Following a population for years before the first munic- decline in the 1930s, the P production rates ipal treatment plant inventory in 1942 began to increase again, reaching an all- was assumed to be equal to the populations time high of about 12.5 million kg/year of the cities and towns. This caused some around 1960. Since then, P production has overestimation of the nutrient loading. fallen back to about 10 million kg/year. So, However, this errorwouldmake little differ- overall the increase duringthe past century ence in the overall loading estimates since has been about 110%, but during the past the "potential" sewered population then quarter century there may have actually was so small. The problem with using been a 20% decrease. As in the case of N "treatment factors" is that the facilities in production, much of the change in P pro- a given city often have not performed at the duction has been caused by changes in the expected efficiencies, for a number of cropland balance. In recent years, this reasons, includingstorm-related bypassing source has accounted for about 30% of the of rawsewage in combined systems, waste- total P; in some years in the 1960s it was water flows exceeding the design capacity as much as 60% ofthe total. The other new of the systems, and poor maintenance of P sources, point and urban runoff, make up the equipment. The latter was reported to about 10% and 3%, respectively, of the be a serious problem in many cities and total today. towns in the AP basin during the 1950s There are quite large differences in the (N.C. Stream Sanitation Committee 1959). trends for each of the sub-basins. In the Thus, the actual nutrient loading would be Chowan and Roanoke, the decreases in greater than I estimated if this type of recent years are most noticeable, particu- error became serious. larly in the Chowan. There, the cropland Nevertheless, comparison of my esti- P mass balance has declined by almost mates with those made by others using 75% since 1954, causing about a 50% different techniques shows that, for recent decrease in the estimated total P produc- times at least, the "treatment factors" tion. The same pattern in the Roanoke has method gives reasonably accurate esti- led to about a 30% decrease. P production mates. The data I used for comparison in the Tar and Neuse basins appears not to come primarily from calculations made by have changed greatly in recent times, multiplying average effluent discharges although there are substantial year-to- (MGD) times average N and P concentra- year changes. The coastal sub-basin is the tions in the effluent (mg/1). The products area in the AP watershed where the P for all municipal plants in the basin are production trend has been the least then summed to give the total expected Trends In Nutrient Production 47 TableS.9. Comparison ofpointsource loadings e8timatedby two different techniques. "Flow x Con."refem to multiplication ofeffluent discharge rates WGD) times nutrientconcentrations (mg1 1). "T. Factom"refers to the use oftreatmentfactor8, usedin combination with estimates ofseweredpopulation. Numbers inparenthe8es (beside kg 1year values) refer to data sources given at bottom of table. Nitrogen (Ikg@) Phosphorus ftlyr) "Flow x Con." 'T. Factors" "Flow x Con." "T. Factors" Basin/Year Method Method Method Method Tar-Pamlico (1986-88) Municipal 545,496(l) 490,542 95,598(1) 165,046 Texasgulf 71,373(l) 70,000 346,647(l) 391,000 Chowan (1980) 881,000(2) 722,798 165,300(2) 136,631 Neuse (1980-82) 1,510,000 (3) 1,470,626 430,000(3) 437,911 'N.C. Division of Environmental Management (1989) 2N.C. Division of Environmental Management (1982) 'N.C. Division of Environmental Management (1983) loading. The results (Table 3.9) agree median Neuse Riverbasin N and P effluent reasonably well with my calculations. Note levels were 13 mg N/liter and 6 mg P/liter that the 1988 Tar River values reflect a (data provided by NC Division of Environ- reduction in P loading that resulted from a mental Management), which is typical for 1987 ban ofphosphate detergents in North secondary treatment processes such as Carolina. Thus, this value is approximately trickling filters and activated sludge. 40% lower than my estimate for 1987 (before Before 1950 there was no significant N the ban), which is about the same as the or P removal from wastewater discharged percentage reduction attributed to the P into the rivers of the AP basin. Although detergent ban by state officials (N.C. sewage collection systems had been con- DNRCD 1989). 1 had to use the less direct structed for most of the larger cities in the "treatment factors"approach because moni- early 1900s, as late as 1945 about two toring of treatment plant effluent N and P thirds of the sewered population was using concentrations in North Carolina and Vir- systems that provided no treatment (N.C. ginia did not begin until about 1980; thus, Stream Sanitation Committee 1946). the "flow times concentration" method com- Rather, the raw sewage was simply dis- monly used today could not be used for charged into nearby streams and rivers. estimating historical loadings. About half of the sewage that was treated Gakstatter et al. (1978) surveyed medi- received only primary treatment, which an P and N concentrations in the effluents removes, at best, only about 10% of the N from over 800 municipal wastewater plant and P. Thus, N and P loading was growing using various treatment processes. Their at about the same rate as the sewered data show that conventional secondary population. As secondary treatment came treatment removes little P and only about into widespread use in the 1950s and 1960s, 25-45% ofthe N. Tertiary treatment consid- the overall nutrient removal efficiencies erably increases the N and P removal, but increased, causing a slowing in the rate of this advanced treatment is not yet used in increase in municipal nutrient loading. enough plants to make a difference in the But there has been little additional im- overall loading. For example, in 1985 the provement since then because further in- 48 Chapter 3 creases in treatment efficiencies have not under laboratory or greenhouse conditions. occurred, or have occurred more slowly to Thomas and Gilliam (1978) concluded that keep up with increases in urban population. it is generally accepted as beingas accurate The greatest source of error in the non- as any. point nutrient production estimates un- The very large increase in the cropland doubtedly comes from uncertainties in the N balance (inputs minus outputs) between areal export coefficients, rather than from 1959 and 1964 is probably somewhat the acreages. Measured export coefficients misleading, since N (and P) fertilizer sales were compiled by Beaulac (1980) from in 1964 seem to have been unusually large, scores of studies and presented in tabular especially in comparison to the relatively and graphical form in Beaulac and Reckhow small (for that time) harvest. Nevertheless, (1980). They discussed factors that affect there was apparently a rather steep the coefficients for each land-use type and increase in the "excess N"duringthe period urged that for application to a particular 1954-1964. Apparently, yields were not geographic area, only those coefficients increasing as rapidly as was the rate of from studies in similarareas be considered. application of N to the croplands. Later, in However, there are two potential problems the 1970s and 1980s, the fertilization rate in usingthis simple, obvious criterion. First, seemed to level off, or perhaps decline there may be no data available that seems slightly. This appears to be the main suitable for a given area, or secondly, there reason for the stabilization in theNbalance. maybe so much variability in the area to be It is interestingto note however, that since modeled that choosing a truly representa- the early 1960s, there appears to have tive coefficient value is very difficult. Unfor- been no increase in the amount of excess N tunately, most of the studies have been on croplands. The trend in cropland P made for watersheds with mixed land uses balance in recentyears is even more surpris- rather thanjust one. Nevertheless, I tried ing, in that there seems to have been about to choose coefficients as carefully as pos- a 50% reduction in the cropland "excess" P sible, considering those presented in since 1954. Beaulac and Reckhow (1980), and in other Estimating historical trends in sources (e.g., Loehr 1974). atmospheric N oxide concentrations is Soil scientists are much more certain difficult, because of the weak historical about what factors affect rates of data base for precipitation chemistry. denitrification than they are about the Before 1955 there were only sporadic actual rates in the field. Studies in North measurements (apparently none in the AP Carolina and elsewhere have shown that basin) and Stansland et al. (1986) have the rate is inversely related to drainage concluded that their reliability is so and directly related to the presence of soil questionable that they should not be used horizons which restrict water movement. for trend analysis. C.E. Junge (1958) Gambrell et al. (1975) measured essentially published results of the first large scale no denitrification on one moderately well study of rain water chemistry in the U.S., drained soil and as much as 60 kg/ha on a for the period July 1955-July 1956. His set poorly drained soil; both sites were within of 60 stations included one at Cape the AP basin. The figure of 15% loss of Hatteras, NC, where NO, concentrations applied N lost by denitrification that I used ranged generally between 0.15 and 0.30 is very frequently used in computations of mg/liter. Ammonia was also measured; it N balances. Apparently it originated from fluctuated seasonally but averaged about denitrification experiments conducted 0.04 mg/liter. A more thorough study was Trends in Nutrient Production 49 made in the AP basin area about ten years burned. It is the uncertainty about changes later, and the results were reported in in the emission factors that is most prob- Fisher (1968). A trend ofincreasingnitrate lematic. Based on estimates of emission northwest from the coast was found; from factors and data on fuel consumption, Husar 0. 17 to 0.40 mg NO./liter (average annual) (1986) estimated that in the southeastern in the Pamlico Sound area to 1.00 mg/liter U.S., N oxides production increased in an in the western end of the Roanoke River exponential fashion from less than 1 million basin. Ammonium concentrations were ton/year in 1900 to around 6 million tons/ considerably lower, averaging about 0.1 year by the mid- 1970s. Husar showed that mg NH./liter over the whole AP basin. his results were similar to those of Calculated annual nitrate and ammonium Gschwandtner et al., (1985) who also esti- loadings for the AP basin were about 2 mated trends in atmospheric N oxide emis- tons/square mile and 0.35 tons/square mile, sions since 1900. respectively (Fisher 1968). Since there are no reliable measure- The most recent data are from stations ments of AP basin atmospheric N levels that was established in 1978, as a part of before 1950, 1 was forced to make historical the National Atmospheric Deposition estimates by combining data on present- Program (NADP). Data from several NADP day concentrations from remote areas, stations in the AP basin (most in the current concentration data for the AP basin, Piedmont and Central Coastal Plain areas) and the suspected exponential rate of in- indicate that between 1981 and 1985 the crease described above. The remote areas precipitation weighted mean NO, values are assumed to represent condi- concentrations (mg/liter) averaged about tions in the AP area in the late 1800s. The 0.9; whereas the NH, averaged around 0.2 values came from NADP data summarized (Olsen and Watson 1984; Olsen and Slavich by Galloway et al. (1984). They showed 1985, 1986; Sweeney and Olsen 1987). that in the remote areas, the (presumably) .Thus, for purposes of the loading "background" nitrate levels are around 4 calculations, I assumed that total IiM N (0.23 mg NO./liter). Assuming that atmospheric N concentrations in the nitrate:ammonia ratio has not changed, precipitation (NO, + NHS + other combined I estimated the atmospheric precipitation forms) was approximately 0.36 mg/liter N for 1880 to have been 0.07 mg/liter (as (as N) in the mid-1980s. Over eastern N). If this estimate is close to the real 1880 North America the total wet and total dry concentration, then the current (mid 1980s) deposition are thought to be of approxi- levels would represent about a 5-fold mately equal magnitude (Stansland et al. increase over the past century. 1986); therefore I doubled the calculated Yet another problem concerningatmos- precipitation loadingto give the total atmo- pheric N deposition effects on nutrient spheric N loads. production in the AP basin has to do with Another problem in estimating his tori- the uncertainty about the percentage of cal trends in atmospheric N oxides is that the increased deposition that actually they are formed primarily by the fixation of leaves the forest, pasture, or other land. atmospheric N at high temperatures of Recently, a controversial report on the role combustion rather than by oxidation of the of acid rain in polluting coastal waters with N contained in the fuels. Thus the "emission N was prepared by the Environmental factors" (i.e., the rate of N oxide emission Defense Fund (Fisher et al. 1988). This per unit of fuel N) have to be taken into EDF report contended that one-fourth of account, as well as the quantities of fuel all N contributed by human activity to the 50 Chapter 3 Chesapeake Bay originates in acid rain came to a similar conclusion after compar- and associated dry deposition falling ingprecipitation nitrate loadingand stream directly on the bay or onto its watershed. nitrate transport for several areas within Atmospheric N, it was concluded, exceeds the AP basin. sewage outfalls and runoffof animal waste The relatively low values and small as a N source to the bay. These results geographical variability in forest may also were based on an assumption that forests give some indirect indication that historical retain 80% of the atmospheric N, pasture increases in atmospheric N deposition have and croplands, retain 70%, and urban lands not made such a large impact on the total 35%. Given that atmospheric N deposition AP basin nutrient export as might be ex- is so large in comparison to other present- pected. Forest N yield estimates available day inputs, it is no surprise that even if in the literature are nearly all from studies 0%-30% (from forests and croplands) of carried out during the past two decades; the atmospheric N is assumed to leave the i.e., recent enough to reflect effects of the and, then this becomes an important relatively high atmospheric N deposition contribution to the streams and estuaries rates that developed by the middle of this - especially when it is assumed (as both century. EDF and I did) that only 5% of animal N The N and P loading estimates made by leaves the pastures and other sites of others for the Chowan, Neuse and Tar production. River basins are roughly one-third to one- But as the re* port noted, there is consid- half the 1987 estimated total N and P erhble variability in measures losses of production calculated above (compare Table atmospheric N from various land use cate- 1.3, Chapter 1 with Figures 3.12 and 3.13). gories; in some studies in areas similar to But those other estimates were also made those drainedby the rivers in the AP basin, using-in most cases -some combination the retention of atmospheric N has been of land use yield coefficients, instream. flow found to be very high. Weller et al. (1986), times nutrient concentration calculations, for example, found that a coastal plain and summed point source loading. It would watershed in Virginia retained 97% of the probably be futile to try to determine the atmospheric N deposited on it, and in a reasons for the differences in each case, but recently-published book on forest nutrition I suspect that the major difference has to management it was stated that"withsome do with the use oftheir instream concentra- notable exceptions (such as high elevation tion times flow calculations vs. my reliance spruce/fir forests in the northeastern United on cropland mass balances, and land use States), the majority of forest ecosystems coefficients. In general, the actual instream. are N limited, so most nitrate deposited in nutrient loads, and the loading to the acid rain is retained - indeed, nitric acid estuaries, is considerably less than the may fertilize forest ecosystems" (Binkley quantities of nutrients produced at the 1986, p. 208). Thus, forests appear to sources, as was mentioned in the intro- "buffer" a large part of the atmospheric N duction to this chapter. they intercept. For example, Lowrance et Of course, there is no long-term his- al. (1985) showed that for several torical instream data for any part of the AP agricultural-forested watersheds in Geor- basin that could be used for comparison gia, the N output via streamflow was always with the nutrient production estimates considerably less than the atmospheric N presented here, but there are at least some input, despite considerable additional N recent instream data for comparison. Chris- input from fertilization. Fisher (1968) tian et al. (1987) have monitored N and P Trends in Nutrient Production 51 concentrations in the lower Neuse River basins, has lead to greatly increased N and above New Bern. They multiplied N and P P loading in recent years. I have assumed concentrations in grab samples times mean that only 5% of the N and P produced by daily river flows to give total annual in- farm animals leaves the pastures, feedlots, stream loading estimates. Their results, and barns. However, if the loss were 3.5 million kg N per year and 0. 8 million kg increased to 10% or 15%, then there would P/year, are 1/4 as large as my N estimate be a substantial impact on the total nutrient and 1/3 as large as my P estimate for production. Such an increase may not be nutrient production in the Neuse Basin. unrealistic, given that many ofthese animal This difference is similar to what Craig and operations involve the use of feed lots or Kuenzler (1983) found in a similar buildings in which hundreds (swine) to comparison for the Chowan River. Their tens-of-thousands (poultry) of animals are explanation was that lowland swamp confined in very small areas. In such cases, forests along these coastal rivers represent these become essentially point discharges, a major sinks for nutrients, removing 83% and indeed the wastes are now often treated of the total N and 51% of the total P from by aeration lagoons or other techniques water draining into the lower Chowan. similar to those employed by conventional Such losses, Kuenzler (1989) noted, are municipal treatment plants. Unfortu- within the range of values derived from nately, however, the animal waste treat- detailed input-output studies of swamp ment facilities are not nearly as strongly forests within the Southeast. regulated as municipal point sources, but It is clear from the historical trend data North Carolina State officials are becoming presented above that the rapidly increasing increasingly wary ofthe potential problems farm animal numbers, particularly swine (North Carolina DNRCD 1986). and poultry, in the Neuse and Tar-Pamlico CHAPTER4 Pamlico River Estuary Water Quality Trends History of Water Quality Studies "In reality, nutrients are choking us. in the Albema rle- Pamlico There's no doubt about it. That river out System there is dying because of its nutrient load. That's my opinion and many other Very little hydrographic and water fishermen's opinion on this river. " quality data have been collected for the I W. Phillips (1987) open waters of the Pamlico Sound. The small boats that are often used to sample North Carolina Division of Environmental in the river estuaries. Management has never included the sound Also, there are no major permanent proper in its water quality monitoring pro- university or government research labora- gram, and university researchers also have tories on the shores of either the Albemarle shied away from the sound as a site for or Pamlico Sounds. Researchers from the their studies. Before 1963, temperature Duke University and University of North and salinity were the only hydrographic Carolina labs in the Morehead City-Beau- variables that had been monitored there. fort, NC, area seldom venture northward The data were from surveys published by into Pamlico Sound. Rather, most of the Winslow (1889), Grave (1904), Coker research on water quality in the Pamlico (1907), and Roelofs and Bumpus (1953). and Albemarle Sound region has been car- Woods (1967) collected temperature, salin- ried out by scientists from three State ity, dissolved oxygen, chlorophyll a, and university campuses farther inland: North total phosphorus data from June 1963 to Carolina State University in Raleigh, the October 1966. His stations were located in University of North Carolina at Chapel southwestern Pamlico Sound and in the Hill, and East Carolina University at lower Tar-Pamlico and Neuse River estu- Greenville. aries, and they were sampled monthly. Since the early 1960s, researchers from Apparently, these are the only Do and these institutions have, for the most part, nutrient data ever collected in the Sound. focused their attention in three areas: Data for the open waters of Albemarle 1) the Pamlico River Estuary, 2) theNeuse Sound are also sparse, except for a two- River Estuary, and 3) western Albemarle year period of intensive sampling during Sound (Chowan River and the lower the early 1970s (Bowden and Hobbie 1977). Roanoke River). These are also the sites Probably the most important reason where the North Carolina state agencies, for this lack of attention to the sounds is the principally the Division of Environmental perception that the most serious water Management and the Division of Marine quality problems are confined to the tribu- Fisheries, have made most of their studies. tary river estuaries along their western The Pamlico River is one of the few shores. Another factor is that the sounds areas in the Albemarle-Pamlico system for are too shallow for even small oceanographic which there is enough water quality data research vessels, and too large for the to permit a time series analysis of trends. 54 Chapter 4 It is, in fact, one of the most thoroughly for most other estuaries in the region. monitored estuaries in the Southeast Routine monitoring of nutrients began in region. Since the mid-1960s, there have 1967 and was continued through 1973. been numerous ecological research and Various hydrographic variables (salinity, monitoring projects, funded by both the dissolved oxygen, temperature, pH, and phosphate mining industry (Texasgulf, Inc. chlorophyll a) were also measured. Since and North Carolina Phosphate Corpora- 1975, the sampling for N and P nutrients tion) and government agencies (principally and related hydrography has continued the University of North Carolina Water uninterrupted, thanks to a co-operative Resources Research Institute and the UNC agreement between Texasgulf, Inc. and Sea Grant College Program). the Institute for Coastal and Marine Re- Research topics have included basic sources at East Carolina University. In hydrography and water-column nutrient addition to these monitoring efforts, two dynamics (Hobbie 1970a, 1970b, 1974; Pamlico research projects (Davis et al. Hobbie et al. 1972; Copeland and Hobbie 1978; Kuenzler et al. 1979) collected signif- 1972; Harrison and Hobbie 1974; Hobbie icant amounts of nutrient and hydrography et al. 1975; Lauria and O'Melia 1980; data between 1975 and 1977. Despite the Kuenzler et al. 1979; Stanley 1984b, 1986a, accumulation of a large quantity of data, it 1986b, 1987, 1988a, 1989), sediment bio- has never been analyzed in the kind of geochemistry and benthic nutrient cycling thorough, systematic fashion that would (Matson et al. 1983; Kuenzler et al. 1984), be needed to address some of the growing organic carbon and deoxygenation (Sick environmental issues for the estuary. 1967; Davis et al. 1978), bacteria hetero- trophy (Crawford et al. 1974), phyto- Methods plankton ecology (Sherk 1969, Hobbie 197 1; Data Sources Carpenter 1971a, 1971b; Stanley 1983, The nutrient and hydrographic data 1984a; Stanley and Daniel 1985a, 1985b, used in this study were produced by two 1986), submerged macrophytes (Davis and long-term monitoring studies and two Brinson 1976, 1989), distribution and bio- shorter-term research projects. The first mass of ctenophores (Miller 1974), zoo- monitoring study ran from 1967 to 1973 plankton abundance (Peters 1968), meio- and was led by John Hobbie of North benthos (Reid 1970, 1978), macrobenthos Carolina State University. It was supported (Tenore 1968, 1970, 1972), fish (Miller and by funds from two sources: 1) the Office of Dunn 1980; Currin et al. 1984); and fish Water Resources Research, U.S. Depart- disease (Noga et al. 1989). Much of this ment ofthe Interior, through the University work has been summarized in an estuarine of North Carolina Water Resources Re- profile prepared for the U.S. Fish and search Institute, and 2) Texas Gulf Sulfur Wildlife Service by Copeland et al. (19,84). Company (nowTexasgulf, Inc.). The initial In addition, several studies of the tribu- objective was to study the effects of phos- taries of SouthCreekwere presentedinthe phorus from the phosphate mining opera- Journal of the Elisha Mitchell Scientific tion (Copeland and Hobbie 1972). Later Society (Volume 10 1, No. 2, 1985). the scope of the project was broadened to Nitrogen and phosphorus dynamics include nitrogen. have continued to receive a great deal of After the NC State University sampling attention by Pamlico investigators since ended, there was an 18-month lapse until the late 1960s. Consequently, there is East Carolina University began a new much more nutrient data for the river than program in January 1975. This study was Pamlico River Estuary Water Quality Trends 55 made possible by funds provided by Texas- phosphorus measurements were substi- gulfto the University's Institute forCoastal tuted for the total N and P analyses, but and Marine Resources (ICMR). This pro- the totals can still be computed by summa- gram has run continuously since 1975. tion of the dissolved and particulate In addition to these two long-term moni- fractions. toring programs, there were two research Texasgulf has maintained weather in- projects in the mid-1970s which produced struments at their plant on the south shore significant amounts of nutrient and hydro- of the Pamlico River since before 1969. The graphic data. One was an investigation of company provided data on wind (total miles nitrogen and phosphorus cycling in the per day), precipitation, and air temperature estuary that was headed by Ed Kuenzler of for the trend analyses. The U.S. Geological the University ofNorth Carolina at Chapel Survey maintains a flow gauging station Hill. The other research project, under the on the Tar River near Tarboro, NC. Their direction of Graham Davis and Mark Brin- data (daily average cfs) are published each son from the Biology Department at East year in the "Water Resources Data" series Carolina University, dealt primarily with (e.g., USGS 1987). organic carbon and deoxygenation in the I have also compiled information on Pamlico River. Both of these projects were station locations and identification num- funded by the UNC Water Resources bers used by the four studies (Appendix Research Institute. 4.2). The exact locations of the ICMR Nutrient and hydrographic data from stations (1975-1986) are known. However, these studies are contained in 18 project I had to estimate the latitude and longitude completion reports and technical reports for each of the stations used in the three (Appendix 4.1). Rather than cite each of other studies, because the reports show these, I will often refer to the four projects them on maps, but give no precise locations. as: 1) "Hobbie," 2) 91CMR," 3) "Davis et Notice that in some cases, stations from al.," and 4) "Kuenzler et al ... .. Hobbie" different projects were located at the same refers to all the data collected between position. For example, stations 22 and 1 1967 and 1973, and "ICMW' to the East used by Davis et al. were at the same Carolina University monitoring program position as ICMR station 11 sampled be- (1975-1990). tween January and June 1975, and ICMR In 1967, only surface water tempera- station 12 sampled since July 1975. ture, salinity and phosphorus concentra- tions were monitored. Bottom water tem- Changes in Analytical Methods perature and salinity were added in mid- A potentially serious problem in a study 1968, and surface and bottom water oxygen of this kind is that samplingand analytical in late 1968. Then in mid-1969, Hobbie methodologies may have varied so much expanded the program again to include over the years that comparison of the data surface water pH, and two surface nitrogen is impossible. Therefore, I have reviewed fractions (ammonia and nitrate). Finally, and compiled notes on the methods used by in 1970, surface water total nitrogen, total the four projects. These notes are in Appen- dissolved nitrogen and chlorophyll a were dix 4.3 and are summarized in Table 4.1. added to the suite of parameters analyzed. Fortunately, all these parameters except Trend Analysis Techniques two have continued to be measured up It soon became apparent that the time until the present. In 1985 surface water series analyses would be impossible unless particulate nitrogen and particulate I grouped the stations, because in the early 56 Chapter 4 Table 4.1. Methods used for Pamlico nutrient and hydrographic measurement8. Parameter Study Instrument or Method Reference 1. Water temperature Hobbie Thermistor A Kuenzler Thermistor A Davis Thermistor B ICMR Thermistor B 2. Salinity Hobbie Induction salinometer A Kuenzler Induction salinometer A Davis Conductivity probe B ICMR Conductivity probe B 3. Dissolved oxygen Hobbie Winkler titration C Kuenzler Winkler titration D Davis Oxygen electrode E ICMR Oxygen electrode E 4. pH Hobbie Electrode F Kuenzler Electrode F Davis Electrode G ICMR Electrode H 6. Total phosphorus Hobbie Persulfate digestion/mixed color reagent 1,J,K Kuenzler Persulfate digestion/automated mixed color reagent L Davis Persulfate digestion/mixed color reagent M ICMR Persulfate digestion/mixed color reagent (automated in 1985) L,M,N 6. Total dissolved Hobbie Persulfate digestion/mixed color reagent IK phosphorus Kuenzler Persulfate digestion/automated mixed colore reagent L Davis Persulfate digestion/mixed color reagent M ICMR Persulfate digestion/mixed color reagent (automated in 1985) N 7. Orthophosphate, Hobbie Mixed color reagent I,K phosphorus Kuenzler Mixed color reagent (automated) L Davis Mixed color reagent M ICMR Mixed color reagent (automated in 1985) N 8. Ammonia nitrogen Hobbie Alkaline hypochlorite/nitrite diazotization O,K Kuenzler Indophenol. L Davis Indophenol P,Q ICMR (1975-79) Ion selective electrode R (1980-86) Indophenol. P 9. Nitrate nitrogen Hobbie Cadmium reduction/nitrite diazotization S,K Kuenzler Cadmium reduction (automated/nitmte diazotization L Davis UV spectrophotometric T ICMR (1975) Brucine T (1975-86) Cadmium reduction/nitrite diazotization. (automated 1985) U 10. Total dissolved Hobbie UV oxidation/nitrite diazotization V,K nitrogen Kuenzler Keldahl (automated) L Davis Keldahl M ICMR (1975-79) Keldahl/ammonia electrode L (1980-86) Kjeldahl/indophenol L,P (1985-86) Persulfate digestionfindophenol N 11. Total nitrogen Hobbie UV oxidation/nitrite diazotization V,K Davis Keldahl M ICMR (1975-79) Keldahl/ammonia electrode L (1980-85) Keldahl/indophenol L,P (1985-86) Persulfate digestion/indophenol N Pamlico River Estuary Water Quality Trends 57 Table 4.1. continued Parameter Study Instrument or Method Reference 12. Particulate N and P ICMR (1986-86) Persulfate digestion/indophenol N 13. Chlorophyll a Hobbie Acetone extraction/spectrophotometric FU KuenzIer Acetone extraction/spectrophotometric w Davis Acetone extraction/spectrophotometric U ICMR Acetone extraction/spectrophotometric U 14. Phytoplankton Hobbie Utermohl concentration/light microscopy X ICMR Membrane filtration ooncentration/light microscopy D A. Beckman induction Salinometer Model RS5-3 meter and probe B. Yellow Springs Instrument Co. Model 33 S-C-T meter and probe C. Carpenter (1965) D. American Public Health Association (1976) E. Yellow Springs Instrument Co. Model 61A meter and probe F. Unknown G. Coming Model 10 H. Various instruments used 1. Menzel and Corwin (1965) J. Murphy and Riley (1962) K. Strickland and Parsons (1968) L. U.S. Environmental Protection Agency (1974) M. U.S. Environmental Protection Agency (1976) N. U.S. Environmental Protection Agency (1979) 0. Richards and lGetch (1961) P. Solorzano (1969) Q. Scheiner (1976) R. Orion Model ? S. Morris and Riley (1963) T. American Public Health Association (1971) U. Strickland and Parsons (1972) V. Armstrong et al. (1966) W. Lorenzen (1967) X. Utermohl (1958) years many of them were sampled for Results and Discussion relatively short periods. Also there have It is very important that the reader been only a few locations sampled during keep in mind the purpose and limitations all of the 20-year study period. Therefore, of trend analysis. First, one wishes to I partitioned the river into ten segments, know whether or not there has been a A-J, with boundaries as shown in Figure statistically significant change in the 4. 1. Appendix 4.2 indicates which sampling parameter under examination. This is the stations fall into each of the segments. one question which is directly addressed by The Seasonal Kendall-Tau test indi- the Seasonal Kendall test. If a trend is cated there were no long-term trends in determined to be significant, the next ques- flow, salinity, delta Sigma-t, or DO in the tion is: "How large is the changeT'Remem- Pamlico between 1975 and 1989. For each ber that "significant change," as used in a of the four stations, none of the test results statistical context, does not necessarily were significant at the 90% level (a<0.1) mean large. The Kendall slope gives an estimate of the average rate of change over the whole test period. But even though the slope estimate might be large, it is meaning- less unless the trend is determined to be 58 Chapter 4 statistically significant. Ontheotherhand, there is a functional relationship between some statistically significant trends might the variables. As long as one remembers have very small slopes. that the statistical results cannot prove or Also, keep in mind that the Kendall disprove the connection, there is nothing test measures monotonic changes over the wrongwith consideringthem to be evidence whole test period; it cannot detect short- of a possible relationship. term ups and downs during that period. Therefore, the outcome ofthe test naturally Climatic Factors and River Flow will be influenced somewhat by the time Three climatic variables (air tempera- interval chosen. Even in instances where ture, wind, precipitation) and river flow there are no reversals in the trend, the rate were included in the Pamlico trend analysis of increase or decrease might vary, but the because changes in these variables, espe- slope estimator will give no information cially river flow, might help explain trends about these rate changes. in some of the other variables of more Obviously, the trend analysis results direct concern. However, as will be shown cannot explain the causes for significant below, only one of these four factors has trends in the variables. Nevertheless, it is changed significantly over the past twenty tempting to assume a cause and effect years. relationship between two parameters when Air temperatures at the Texasgulfplant the trend in one could logically explain a on the south side of the river are usually trend in the other. This is a dangerous trap lowest in January, averaging around 42'F which one must constantly be aware of (5.5'Q, while July temperatures average during the course of a study like this. On higher than any other month, around 80'F the other hand, it is certainly possible that 7111-30- KILOMETERS 0 5 10 is WASHINGTON J6 A 35*30' C o. D Y. E !te T6 F G Figure 4.1. Map showing division of the Pamlico River estuary into ten segments used in the trend analyses. Pamlico River Estuary Water Quality Trends 59 Table 4.2. Seasonal Kendall Test results for air temperature, wind, precipitation and Tar River flow. Time Interval Parameter 1967-1986 1975-1986 Monthly Mean Air Temperature z 0.307 1.821 Slope 0.017 0.129 P 0.719 0.069* Total Wind Miles z 0.831 1.128 Slope 0.192 0.409 P 0.407 0.358 Total Monthly Precipitation z 0.447 Slope 0.000 P 0.653 Monthly Mean Tar River Flow z 0.253 Slope 1.750 P 0.803 P<0.1 (Significant) P<0.01 (Highly Significant) (26.60C) (Figure 4.2). Over the past 20 years, the variation in the monthly means has been greater in the winter (up to 12"F 90 above normal for January) than in the 80 A summer. This difference is also clearly Z E. 70 shown in Figure 4.2, which shows that 6 -@ a. 60 m there has been little variability in the w 50 summers, while the winters were relatively 7( @ 40 warm in the 1971-1975 period, very cold in 301 1 1976 and 1977, and have tended to be 1965 1970 1975 1980 1985 1990 warmer each year since the late 1970s. YEAR Despite these fluctuations in the winter ir 90 B and summer maxima temperatures, the ;-( 80 Seasonal Kendall test results were that Z C 70 6- Q: 60 there was no statistically significant trend 22 in the mean monthly air temperature be- 50 M tween 1967 and 1986 (Table 4.2). However, 40 IN. 30 since 1975, there has been a significant (p J F M A M J J A S 0 N D = .069) upward trend, averaging 0.13'F MONTH per year. Figure 4.2. Daily mean air temperature (7), For any given month there can be great averaged by month, at the Texasgulf Chemicals Co. year-to-year variability in the average daily plant on the south shore of the Pamlico River wind (Figure 4.3) but the overall pattern is estuary. (A) monthly averages, January 1969- that average velocities are highest in late December 1986. (B) maximum, minimum and winter and lowest in late summer. The median of averages for each month. difference between the March and August wind velocities averages around 30 percent 60 Chapter 4 (115 total miles vs. 78 total miles per day). evapotranspiration that occurs during the Again, however, the interannual variability summer. Daily mean flows at Tarboro, is great, so that some summer months averaged by month, normally vary from have had higher winds than the average about 800 cfs in September to around 4000 for the winter months. Overall, there was efs in March (Figure 4.5b). Changes i 'n flow no trend toward increasing or decreasing can be very sudden and of great magnitude winds during the 1967-1986 period (Table (Figure 4.5a). 4.2). There have been some short-term Monthly precipitation at the Texasgulf trends in Tar River flow, but no overall, plant has ranged from less than 0.5 inches long-term change since 1967. Figure 4.5a to over 17 inches during the study period shows, for example, that between 1984 (Figure 4.4), but normally it peaks at around and 1986, there was a decrease in the late 6 inches in July and is lowest in November, winter and early spring flows. A decline in about 2.5 inches. The Seasonal Kendall winter flows also occurred between 1979 test showed no significant trend in the and 1981. Overall, 1981 was the lowest monthly precipitation totals between 1967 flow year in the study period. Other low and 1986 (Table 4.2). flow years were 1967, 1974, and 1986. Even though precipitation onto the However, the Seasonal Kendall test for the watershed is highest in the summer, Tar two decades between 1967 and 1986 gave River flow is usually highest in the late no significant upward or downward trend winter months, a pattern that is typical for in the mean monthly flow (Table 4.2). eastern North Carolina (Giese et al. 1979) and the region (Nixon 1983). This seasonal 2 pattern is caused by the increased >, 6 A @ 1': 15 z 0 a 150 0 10 W VIM. A _j 120 ME j I W 5 cc go MIN. IL 0 1969 1974 1979 1984 1989 60 Z YEAR 30 J F M A M J J A S 0 N D MONTH 20 160 W B 15 120 _j < 10 @<- 80 z AX MEAN 0 t__ 5 40 Z 0. 0 1965 1970 1975 1980 1985 1990 J F M A M J J A S 0 N D YEAR Figure 4.3. Wind (total milesper day), averaged by Figure4.4. Total monthlyprecipitation (inches) at month, at the Texasgulf Chemicals Co. plant on the the Texa8gulf Chemicals Co. plant on the south south shore of the Pamlico River estuary. (A) shore of the Pamlico River estuary. (A) Monthly Monthly averages, January 1969-December 1986. totals, January 1969-December 1986. (B) Maximum, (B) Maximum, minimum, and median of monthly minimum, and median of totals for each month. averages. Pamlico River Estuary Wafer Quality Trends 61 Water Temperature, SalInIty and pH 10000 A Water temperature is the most predict- 8000 able of all the parameters that have been 6000 monitored in the Pamlico studies. Surface 4000 temperatures in the estuary typically range 2000 from around 4C to about 3C over the course of the year (Figure 4.6). The lowest 1965 1970 1975 1980 1985 1990 temperatures occur in January in most years, and the peak temperatures come in YEAR JulyandAugust. On some samplingdates, 12000 B there is as much as 5C variation in temper- 10000 atures, but much ofthis difference probably 8000 results from the samples being taken at 6000 different times of the day. It takes 4-6 MEAN 4000 hours to visit all the stations in the estuary. Bottom water temperatures exhibit the 2000 same seasonal pattern and range as the 0 J F M A M J J A S 0 N D surface temperatures. Occasionally there MONTH is strongthermal stratification in the water column, but this is rare. Normally the Figure 4.5. Daily mean flow cfs), averaged by difference between surface and bottom tem- month, of the Tar River at Tarboro, NC. (A) Monthly averages, January 1967-December 1986. peratures is less than 2C (e.g., Stanley (B) Maximum, minimum, and median of averages 1988a). The Seasonal Kendall test indi- for each month. cated no significant trend in surface water temperature (Table 4.3) for the three river segments examined. Likewise, no trends were found in the bottom water tempera- ture data (Table 4.3). Figure 4.6. Surface water 12 temperature (C)in thePamlico 11 10 River estuary during 1984, as a 9 function of time (x-axis) and 8 distance (-axis). Top of plot is T station 12 upriver (see Methods A 7N for explanation of distance T TS I 6 scale). 0 5 N 4 3 2 1A 1 J F M A M J J A S O N D SURFACE TEMPERATURE (O) S-12 12-18 18-24 24-38 30 62 Chapter 4 Table 4.3. Seasonal Kendall Test results. Segment B = Upriver, Segment E = Midriver, Segment H Downriver. P<0.1 (Signiftcant); P<0.01 (Highly Significant). River Segments and Time Intervals 1967-1986 1975-1986 Parameter B E H B E H Surface Dissolved Oxygen z 3.745 3.292 4.301 1.172 3.089 2.268 Slope 0.060 0.050 0.080 0.030 0.090 0.090 P 0.002 0.002 <0.002 0.242 <0.002 0.023 Bottom Dissolved Oxygen z -1.560 1.310 -1.830 -0.930 -0.880 -0.180 Slope 0.040 0.030 -0.060 -0.040 -0.040 -0.020 P 0.120 0.190 0.067 0.352 0.384 0.857 Bottom Dissolved Oxygen z -1.624 1.593 -2.217 -1.696 -0.376 -0.721 % Saturation Slope -0.406 0.400 -0.523 -1.100 -0.130 -0.446 P 0.103 0.112 0.027 0.091 0.704 0.472 Surface Salinity z 2.220 0.600 -1.530 0.690 0.930 -1.070 Slope 0.050 0.030 -0.100 0.030 0.090 -0.130 P 0.026 0.555 0.124 0.490 0.352 0.285 Bottom Salinity z 1.930 -1.090 -2.830 -1.280 0.930 -0.100 Slope 0.070 -0.060 -0.130 0.110 0.090 -0.010 P 0.054 0.276 0.005 0.201 0.352 0.920 Surface Temperature z -0.240 -0.100 -0.430 0.420 0.890 0.870 Slope -0.025 -0.019 -0.060 0.144 0.231 0.317 P 0.810 0.920 0.667 0.674 0.373 0.384 Bottom Temperature z 0.103 0.270 1.456 0.409 1.067 0.830 Slope 0.003 0.006 0.046 0.022 0.033 0.050 P 0.912 0.787 0.147 0.682 0.285 0.412 pH z -0.716 -3.543 -3.752 0.397 2.158 0.070 Slope -0.006 -0.039 -0.037 0.012 0.042 0.021 P 0.478 <0.002 <0.002 0.697 0.032 0.484 Orthophosphate P z 1.390 2.070 2.880 1.489 -1.136 3.141 Slope 0.025 0.080 0.040 0.051 -0.077 0.086 P 0.165 0.040 0.004 0.136 0.254 0.003 Total Phosphorus z 4.453 4.699 5.547 1.546 0.085 4.882 Slope 0.149 0.234 0.146 0.142 0.013 0.255 P <0.002 <0.002 <0.002 0.124 0.940 <0.002 Pamlico River Estuary Water Quality Trends 63 Table 4.3. continued River Segments and Time Intervals 1967-1986 1975-1986 Parameter B E H B E H Total Dissolved P z 5.723 4.644 5.156 2.487 0.327 2.917 Slope 0.115 0.222 0.112 0.198 0.061 0.213 P <0.002 <0.002 <0.002 0.013 0.741 0.004 Ammonia Nitrogen z -5.512 -5.357 -6.131 -1.642 -1.073 -2.003 Slope -0.303 -0.250 -0.228 -0.179 -0.100 -0.233 P <0.002 <0.002 <0.002 0.101 0.285 0.046 Nitrate Nitrogen z -2.813 1.327 3.010 0.062 0.838 -0.333 Slope -0.280 -0.019 0.026 0.005 0.015 -0.017 P 0.005 0.187 0.003 0.522 0.407 0.741 Total Nitrogen z 4.721 4.536 2.871 2.618 2.923 0.238 Slope 1.547 1.356 0.845 1.664 1.807 0.150 P <0.002 <0.002 0.004 0.009 0.004 0.818 Total Dissolved N z 1.169 1.467 0.183 1.385 1.488 -1.059 Slope 0.260 0.292 0.040 0.450 0.619 -0.709 P 0.242 0.142 0.857 0.168 0.136 0.289 Chlorophyll A z 2.648 -1.398 -1.293 3.218 2.937 -0.034 Slope 0.294 -0.156 -0.140 0.635 0.451 -0.004 P 0.008 0.165 0.197 <0.002 0.003 0.976 Seasonal salinity patterns in the There are also interannual variations Pamlico are affected mainly by variation in in salinity which become obvious only when freshwater runoff (Copeland and Hobbie data from a number of years are compared 1972; Stanley 1986). Typically, salinity is (Figure 4.8). For example, 1967-1970, lowest during the late winter and early 1976-1977,1981,1985 and 1986 were rela- spring when freshwater inflow is highest tively high salinityyears, while 1978-1979 (Figure 4.7). The salinity increases to and 1983-1984 were low salinity years. In maximum values during the summer and some periods, the salinity graduallytrended fall, coincident with lowest river flow. In downward (1968-1971) or upward (1983- some years this seasonal pattern may be 1986), but in other instances, the change upset by unusually high or low freshwater was more abrupt. For example, between inflow associated with hurricanes orperiods the 1979-1980 winter and the 1980-1981 of drought. Examples of such events are winter, the mean salinity appears to have given in descriptions ofdata from individual increased about 8 ppt. years by Hobbie (1974) and Stanley (1986a, The Seasonal Kendall test indicated 1986b, 1987). that surface salinity has increased upriver in segment B since 1967. The trend was 64 Chapter 4 statistically significant (p = 0.026) with a trend in river flow which would be expected slope of 0.05 ppt per year, or 0.9 ppt during if the upriver salinity is trending upward. the 18-year sampling period. In the down- On the other hand, trends in pH and nitrate river segment, H, the trend was downward nitrogen described belowcould be explained but the significance level (p = .124) was not by these salinity trends. In short, no quite low enough to be classified as statis- definitive conclusions can be drawn from tically significant. Salinity has not changed these data regardinga salinity trend in the in the middle segment (Table 4.3). river since 1968. Bottom water salinity upriver in seg- The Pamlico report prepared by North ment B has also trended upward slightly Carolina DNRCD (1987a) cited an analysis during the past two decades. The change by Sholar (1980), and included a time- detected by the Kendall test was statis- series salinity plot from his report, which tically significant (p = 0.054) at a rate of showed a decrease in the mean annual 0.07 ppt per year, or about 1.25 ppt during salinity for the"Painlico Sound area" (sta- the sampling period. Farther downriver, tions not given) over the period 1948-1980. no significant trend was detected in seg- Comparison of Sholar's trend plot with the ment E (mid-river), but a highly significant "Mean of All Stations" plot in Figure 4.8 (p = 0.005) downward trend was detected suggests to me that if Sholar's analyses in segment H nearthe mouth ofthe estuary. were extended to include the highersalinity The rate ofdecrease was -0. 13 ppt per year, years following 1980, it is likely that no which amounts to 2.3 ppt, or about 15%, overall (1948-1986) trend would be seen. during the 18 year sampling interval. The pH in estuaries is influenced by the It is difficult to explain the salinity mixing of seawater and freshwater and by trend results, or to see a pattern in them. the rates of microbial (algal and bacterial) The fact that there were significant trends respiration and algal photosynthesis in for the 1968-1986 period, but none for the the water. Freshwater typically has pH's 1975-1986 period, suggests that most of lower than seawater, and the situation can the change occurred between 1968 and be complicated in estuaries like the Pamlico 1975. The trend upriver was positive, but bythe inflowofwater flushed from swamps downriver it was negative, and I can think that is often quite acid (low pH) (Hobbie et of no explanation for this contradiction. al. 1972). When algal photosynthesis is Also, there was no significant downward high, the pH is also high because the algae 12 Figure 4.7. Surface salinity (ppt) in the Pamlico River 10 77 estuary during 1984, as a function of time (x-axis) and T -axis). Top ofplot is 7 distance (y A 7W M MatmMAWMEWTIM WIM T is MARMIMEMNEUMM N1031hi station 12 upriver (see Methods 1 6 0"MMIMM3008 UMM" for explanation of distance 0 5 scale). N 4 ARM MINH i F M A M J J A S 0 N D SURFACE SALINrrY (ppt) 4 2-4 4-6 6-10 19-15 3.15 Pamlico River Estuary Water Quality Trends 65 have removed most of the carbon dioxide this pattern is that freshwater from the and made the water basic. Respiration, on Tar River has much higher nitrate concen- the other hand, adds carbon dioxide to the trations than does Pamlico Sound water at water, thus increasing the acidity and the other end of the estuary. But a second- lowering the pH. ary cause is that nitrate often behaves The pH in the Pamlico usually ranges nonconservatively in the estuary. That is from around 6.5 to over 8.5, but because it to say, the decline in nitrate concentration is influenced by several variables, there in the estuary is caused by more than are not very clear spatial or temporal pat- simple dilution by seawater. Nitrate is terns. About all that can be said is that it used up (assimilated) by phytoplankton, tends to be lower upriver than downriver, which are scarce in the Tar River but and it sometimes goes up during the algal abundant in the upper estuary, and there blooms that occur in the river in the late is apparently little replacement of the winter and early spring. assimilated nitrate. Consequently, nitrate Highly significant downward trends in concentrations usually exhibit a temporal- pH (p <0.002) were detected by the Seasonal spatial pattern in the estuary that is the Kendall trend test for segments H and E inverse of the salinity pattern, but nitrate between 1975 and 1986 (Table 4.3). The levels decrease more rapidly than salinity slopes were about 0.04 pH units per year, increases, especially in the upper end ofthe which amounts to a change of 0.68 units estuary. This accounts for the nonlinear over the sampling period. The lower pH relationship between salinity and nitrate could be related to declining salinity, at (Figure 4.9). least in segment H. As explained above, The most significant change in nitrate lower salinity (i.e., increased freshwater nitrogen in the Pamlico during the past 20 inflow) should lead to lower pH. years occurred upriver, where there appar- ently has been a decline. The Seasonal Nitrogen Kendall test results indicated a highly Nitrate Nitrogen: Nitrate nitrogen is significant (p = 0.005) decrease in nitrate one of the most variable nutrients in the for river segment B (upriver) during the Pamlico, but there is a seasonal pattern in period between 1967 and 1986. But there this variability. In most years, highest was no significant change for the 1975- concentrations occur upriverduringwinter, 1986 period, suggesting that the decline coincident with peak Tar River flows, and occurred during the early 1970s. The lowest concentrations occur downriver average rate of change was about 0.3 PNV during the summer. The primary cause of year, or 5.1 @Mduringthe 17-yearsampling is MEAN OF AL. STAn ONS 100 P 15 80 0. E@, 12 z 60 9 z 40 6 3 20 0 0 1965 1970 1975 1980 1985 1990 0 5 10 15 20 25 YEAR SALINITY (ppt) Figure 4.8. Surface salinity (ppt) in the Parnlico Figure 4.9. Nitrate nitrogen (,@LM) versus salinity River estuary, 1967-1986. Values plotted are (ppt). Dataarefrom stations 1, 5,8, 10and 12 (1975- averages of all stations 8cunpled. 1986). 66 Chapter 4 period. This change represents approxi- offset losses from assimilation and dilution, mately a 25% decrease from the 1970 and at some times of the year it is a more median nitrate level. Based on the relation- important source of ammonia than inflow- ship between nitrate and salinity described ingTar River water (Kuenzler et al. 1979). above, it would be reasonable to conclude Ammonia abundance in the estuary that this decrease was due, at least in part, appears to be trending downward at a to the salinity increase detected in this rapid rate. During the period 1967-1986, segment. the decline was highly significant (p< 0.002) The Seasonal Kendall test indicated a for all three river segments examined highly significant (p = 0.003), but small (Table 4.3). The average rate of decrease (0.4 pM), nitrate increase downriver (seg- was quite rapid - about 0.3 gM/year up- ment H) over the 1967-1986 period. Again, river (segment B) and around 0.23 AMI this change could be explained by salinity, year farther downriver (segment H). For which was shown above to have decreased segment B, this is equivalent to about a in this segment. But this could also be 60% decline over the 17-year period of simply an artifact resulting from changes record. The decline is especially noticeable in analytical sensitivities. Before 1975, when one compares values from the early nitrate levels lower than 0.1 /.LM were 1970s with those for 1984-1986. Once reported frequently, but after 1980, the again, it should be remembered that data values less than 0.71 14M were reported as from the period 1975 through the end of 0.71 jLM, the lower limit of detection 1979 had to be eliminated from consider- (Appendix 4.3). This change in data ation in the trend test because of the high reporting probably had little effect on the minimum detection limit associated with upriver trend results, because the nitrates the method used for the analyses in those there were usually higher than 0.71 gM, years. but it may have contributed to the apparent Total Nitrogen: Total nitrogen (TN), upward trend in the downriver segment, which consists of total dissolved nitrogen H, where nitrate is much less abundant. plus particulate nitrogen, is the most diffi- The nitrate data from 1975 through 1979 cult nitrogen fraction to measure accu- were omitted from the Kendall test because rately. The problem has to do with uncer- of the very high (3.57,4M) lower detection tainties about the completeness ofthe diges- limit reported during that period. In any tion used to break down the organic con- case, there has been no significant change stituents. There have been several changes in nitrate levels downriver since 1975. in the methodology used to analyze Pamlico AmmoniaNitrogen: Ammonia nitrogen TN, and there is much uncertainty about is also more abundant in Tar River water the efficiency of some of the methods used than in Pamlico Sound water, but in the (see Appendix 4.3). Pamlico River estuary, concentrations do TN concentrations have fluctuated not range as widely as nitrate concentra- widely, and sometimes abruptly, during tions. In general, they are between 1 and the 17-year period of record (see Figure 31 8 ttM upriver (segment B), <0.71 pLM to 6 in Stanley 1988). However, I strongly gM downriver (segment H) and inter- suspect that much ofthis variability can be mediate in the middle segments. This rela- traced to methodological problems. For tively constant pattern probably results example, I doubt that the abrupt decline in from ammonia production in the sediments 1977 and the sudden rise in 1980 are real. and water associated with organic matter There were changes in the methodologies decomposition. This production tends to at each of these times. Also, the apparent Pamlico River Estuary Water Quality Trends 67 wide fluctuations during 1975-1977 prob- changes in biology and hydrography ably are due in part to the fact that data of the river. The very high values for from this period are from three different dissolved organic nitrogen in 1970- sampling programs (Kuenzler et al., Davis 1971 (August through December) et al., and ICMR), each of which used a correlate well with the very low stream different method for the TN analyses. Of flow. On the other hand, when the course, this is only speculation and unfortu- streams started to flow again in mid- January there was a reduction in nately there is noway to determine whether dissolved organic nitrogen concentra- or not this is the correct explanation. The tion followed by an eventual increase methods used to measure TN have been which may well correlate with the less variable since 1980, and during this increased biological productivity at period there have not been such abrupt that time. During 1971-1972, the dis- fluctuations as in the earlier years. solved organic nitrogen concentrations The trend test indicated highly signif- were very low during the heavy rains icant increases in TN in all three segments of October and November. On the between 1967 and 1986 and in segments B other hand, the high rates of flow in and E between 1975 and 1986. But, as May seem to contain quite high amounts ofdissolved organic nitrogen. indicated above, there are reasons to doubt A number of hypotheses can be put the validity of these results. I think the forth as to the reason for abrupt most likely explanation for the apparent changes, such as there is a flushing trends is that the digestion method used in effect of high waters on swamps that the early analyses (ultraviolet radiation), increases the dissolved organic nitro- gave less complete breakdown ofthe organic gen in the rivers and streams. Also it nitrogen than the more rigorous wet chem- is possible that DON is being produced ical digestions used later (see Appendix 4.3 during algal blooms. At this time, for more details). This would explain the however, we do not have enough infor- apparent increase in the TN concentrations. mation as to the source and fates of these compounds that are lumped Once again, however, this is only specula- under the name dissolved organic tion, and I cannot be sure that had the nitrogen. Certainly the biologically methodology remained constant, there active part is very small ... Yet, these would not have been an upward trend in compounds are still potentially impor- the concentrations. tant as they contain a great deal of Total Dissolved Nitrogen: Total dis- nitrogen and their total concentrations solved nitrogen is not a particular chemical are always greater than the total con- form of nitrogen, but rather includes a centrations of the dissolved inorganic large number of compounds, including nitrogen" (Hobbie 1974, pages 73-75). ammonia and nitrate, that passed through The Seasonal Kendall test showed that the glass fiber filter when the dissolved there has been no significant change in and particulate fractions are separated. total dissolved nitrogen in the Pamlico Hobbie (1974) subtracted the inorganic (Table 4.3). However, as noted above, the forms (nitrate and ammonia) from TDN to methods used to measure TN and TDN obtain estimates ofdissolved organic nitro- have changed several times over the study gen (DON), but could not explain changes period, so this result may not be valid. in the DON data: ". . . The yearly cycle of the dissolved Phosphorus organic nitrogen concentration is also Concentrations of all three forms of difficult to interpret in terms of known phosphorus measured in the Pamlico 68 Chapter 4 samples (total phosphorus [TP1, total dis- topic in every Pamlico report he prepared. solved phosphorus [TDP], and orthophos- In a 1971 report, he made these comments: phate phosphorus [OP]) are generally high- er in the summer than in the winter. For Earlystudies centered around the example, in 1984, dissolved orthophosphate possible effects that the establishment concentrations were often >2 pM during of a phosphate mine on the south side the summer and fall, and less than 2 gm of the river (Texas Gulf Sulfur Corp.) during the winter. Both TDP and TP fol- would have on the water chemistry andbiology. It is nowapparent(Hobbie lowed the same temporal pattern as OP. 1970a) that there is enough phosphorus TDP ranged from around 2- 10 I.LM in winter naturally present in the river and that samples to 10-20 1AM in summer samples. the phosphorus added from the phos- TP was only slightly higher, indicating phate mine operations has no added that particulate phosphorus makes up a effect on the biology." relatively small fraction of the total P in "The natural levels of P in the the estuary. estuary are in the 1-2 jkg-at P/liter Nixon (1983) noted that this summer range (1 gg-at P equals 31 @Lg) for increase in phosphorus is a feature common [orthophosphate phosphorus]. As a to many estuaries, and he discussed several result of the mining activities, levels possible explanations, but concluded that as high as 93 pg-at/liter have been measured. However, the release is no single factor can explain the pattern in intermittent and the higher phos- all the estuaries. Judging from the informa- phorus water is found as patches that tion presented in Nixon's discussion, and move seaward along the south shore of other available information, I suspect that the estuary. Because of removal of two factors are important in the Pamlico. phosphorus by the sediments, removal The first is increased bottom water hypoxia by microorganisms, and dispersion in the summer. As shown by Kuenzler et dilution, the patches of high phos- al. (1984) for the Pamlico River, and by phorus water do not reach Pamlico similar studies for many other estuaries Sound. There does appear to be, how- (e.g., TaftandTaylor [1976] forChesapeake ever, an increase over the past three or fouryears in the concentration ofphos- Bay), this hypoxia increases the release of phorus entering the estuary in the phosphate from the sediments. Second, river water. This may be the result of Tar River flowdecreases in the summer, so increased sewage treatment and of that there is less dilution ofthe phosphorus- increased use of detergents" (Hobbie rich Texasgulfeffluent and s lower flushing 1971, pages 5-8). of the discharge from the estuary. In another report (Copeland and Hobbie There is also spatial variability in the 1972) summarizing the 1967-1969 sam- phosphorus -levels that usually follows a pling, three conclusions were given regard- pattern. Highest concentrations are found ing phosphorus in the estuary: 1) there in the middle section-of the river, especially had been a tripling of total phosphorus adjacent to the Texasgulf discharge, with levels in the upper river, 2) the middle intermediate concentrations upriver and river was greatly affected by the high con- lowest concentrations at the outer end of the estuary near Pamlico Sound. centrations of total phosphorus entering For obvious reasons, there has always from Texas Gulf Sulfur, and 3) the lower been a great deal of interest in trends in section ofthe river also seemed to be strongly phosphorus in the Pamlico, so it is not affected by Texas Gulf Sulphur's activities. surprising that Hobbie wrote about this Pamlico River Estuary Water Quality Trends 69 Finally, after his monitoring program there were also increases in TDP in seg- ended in 1973, Hobbie had this to say ments H and B, but not in the middle river about the 1971-1973 phosphorus data: segment, E. Orthophosphate increased in segments H and E between 1967 and 1986, It is interesting to remember the but only in the downriver segment, H, increase of phosphorus in the upper since 1975. The average annual rate of stations and the entire river that were increase varied from 0.04 AM/year to about seen over the first four or five years of 0.086/.kl%Vyear. For the downriver segment, phosphorus measurements. Although H, these rates translate to an overall in- high amounts of phosphorus are still seen in the upper parts ofthe river, the crease of about 0.7 AM since 1967. increase does not appear to have con- The fact that phosphorus abundance tinued past 1970 or so" (Hobbie 1974, has not changed in the mid-river segment page 50). since 1975 probably is a reflection ofdeclin- ing P loading from Texasgulf, counter- Results of the Seasonal Kendall tests balanced, to some extent, by increased seem to confirm Hobbie's observation that loading from the Tar River. Monthly load- phosphorus was increasing in the river in ing of P (in tonnes) from the plant site has the late 1960s. The increase in TP was decreased by about two-thirds since the shown to be highly significant (p<0.002) in mid-1970s (Figure 4.10). It would seem all three river segments examined for the that this large reduction ought to have time period 1967-1986 (Table 4.3). The produced a significant downward trend in average rate of increase at the middle phosphate in the river, given that the segment, E, was 0.23 AM/year, or about 4.4 Texasgulf discharge accounts for approxi- AM over the 19-year sampling period. This mately 40% of the total P loading to the amounts to approximately a doubling of river (North Carolina DNRCD 1987). But, the 1967 TP levels. In the upriver and the decreased TG load probably has been downriver segments, B and H, the TP levels offset to some extent by increased loading trended upward at about half this rate. from the Tar River, so that the overall However, when only the period 1975-1986 pattern is one of little change since 1975. was examined, it was found that there was Unfortunately, there are no historical Tar a significant increase in TP only downriver River loading data which could be used to in segment H (p<0.002). But the average test this hypothesis. annual rate of increase in this segment since 1975 has been 0.25 AM/year, nearly Nutrient Limitcytion in the Pamlico twice the rate over the longer period. Nitrogen-to-phosphorus ratios are often Total dissolved phosphorus and ortho- computed for aquatic ecosystems to indicate phosphate phosphorus have also increased which of the two nutrients is most likely to signif icantly, particularly in the lowerestu- be limiting to phytoplankton growth. The ary. The trend test results are about the ratios can be calculated several ways, but same as for TP, which is not surprising most often they are made by dividing the since OP and TDP are the major fractions water-column concentrations of total dis- comprising TP. For TDP, the increases solved inorganic nitrogen (DIN) by the con- between 1967 and 1986 were highly signif- centration of orthophosphate phosphorus icant (p<0.002 for all three segments), and (OP). The significance of this ratio stems the rate of increase was highest in the from the fact that algal production is deter- middle segment (Table 4.3). During the mined in part by the need for nitrogen and more recent sampling period, 1975-1986, phosphorus in proportions (atomic) of 16:1, 70 Chapter 4 respectively (Redfield 1934). Water-column ity in algal composition ratios, and hence it DIN:OP ratios less than the "Redfield Ratio" is probably more realistic to view indicate that nitrogen is less abundant composition ratios as ranging from around than phosphorus relative to the phytoplank- 10:1 to 20:1 (Boynton et al. 1982). ton's need. On the other hand, values Calculated ratios of water column higher than 16:1 indicate that phosphorus DIN:OP suggest that nitrogen is more likely is less abundant. Thus, ifthe phytoplankton than phosphorus to be limiting upriver in continue to grow and there is no N or P the Pamlico during the summer and down- replenishment in the water, one nutrient river at all times of the year. Figures 4. 11- will be exhausted (i.e., become "limiting'l 4.13 give the ratios at five stations along before the other, depending on the ratio. the salinity gradient 'between 1979 and Studies by Parsons et al. (1961) and Rhee 1986. In the lower half of the estuary (1978) indicated that there is some variabil- (stations 1 and 5), DIN:OP ratios are almost W always less than the ideal Redfield ratio 0 150 (16: 1), or the 10: 1-20:1 range of N:P ratios ;;z - F_ 120 normally found in algal cells. Upriver, the Z 00 90 ratios increase, more because of increasing 0 a. @3 W 60 DIN (principally nitrate), rather than M z k@ z decreasing phosphate. There is also a 30 AA1*4 strong seasonal pattern in the ratios at all 01 - 1973 1978 1983 19M stations. This pattern is determined prima- YEAR rily by the nitrate levels, which vary more than either ammonia or nitrate over the Figure 4.10. Texasgulf phosphorus discharge course ofthe year. Figure 4.14 more clearly (tonnes), by month, 1974-1986. 100 STA11ON 1 1000 STATION 8 100 a. 10 a. 0 10 - 0.1 0.1 80 81 82 83 84 85 86 87 80 81 82 83 84 85 86 87 YEAR YEAR 100 TATION 5 1000 STATION 10 100 a. 10 CL 10 0.11 0.1 80 al 82 83 84 85 86 87 80 81 82 83 84 85 86 87 YEAR YEAR Figure 4.11. Ratio of total dissolved inorganic Figure 4.12. Ratio of total dissolved inorganic nitrogen (DIN) to orthophosphatephosphorus (OP) nitrogen (DIN) to orthophosphatephosphorus (OP) in the Pamlico River estuary, 1979-1986. (A)station in the Pamlico Riverestuary, 1979-1986. Wstation 1, (B) station 5. 8, (B) station 10. Pamlico River Estuary Water Quality Trends 71 shows the decline in the N:P ratio with there were no statistically significant trends increasing salinity. Most instances of N:P in the concentrations, but the percent satu- higher than 16:1 occur upriver in the winter ration data did show a significant down- months when river flows, and hence nitrate ward trend in segment H (Table 4.3). The levels, are highest. Similar results for annual average percent saturation declined other estuaries are discussed later in this from about 70% to 60% over 18 years. report. There was no significant trend in the seg- It is very important to realize that ment B and segment E data. Dissolved these N:P ratios are only evidence for pos- oxygen dynamics in the Pamlico River are sible N or P limitation, not proof that such described in more detail in Chapter 5. limitation exists. Phytoplankton must con- sume the nutrients faster than they are Chlorophyll a resupplied, from either internal recycling Chlorophyll a is a reliable indicator of or outside input, in order for one or the algal biomass that has been monitored in other to become limiting. In fact, other the Pamlico since 1970. The most impor- factors, such as light or temperature, often tant findings from this sampling are that control algal growth to such an extent that blooms of algae occur each late winter or the nutrients are not exhausted. In these early spring, but the median chlorophyll a circumstances, the N:P ratio has no influ- levels peak in the summer months. The ence on the growth. In other words, both winter blooms occur in the middle reaches the absolute and the relative N and P concentrations must be considered (along with the resupply rate!) when one specu- 1000 TATI ON 12 lates on algal nutrient limitation. The 100 importance of limitation by factors other a- 0 than nutrients is often overlooked in the 10 heat of debate associated with the long- Q running N vs. P limitation controversy. 1 But given the high turbidity, particularly 0.1 upriver in winter (Kuenzler et al. 1979), 80 81 82 83 84 85 86 87 and the wide temperature fluctuations that YEAR characterize estuaries like the Pamlico, Figure 4.13. Ratio of total dissolved inorganic these factors probably override nutrient nitrogen (DIN) to orthophosphatephosphorus (OP) influences, at least during some parts of in the Pamlico River estuary, 1979-1986, at station the year. 12. Dissolved Oxygen 100 The trend test (Table 4.3) showed a 10 t highly significant (p<0.002) upward trend IL % in surface water dissolved oxygen for all O@ 1 three river segments tested. The estimated A I 0.1 slopes were 0.05-0.08 mg/liter per year, which amounts to an increase of 0.9-1.4 mg 0.01 02/liter, or approximately 10%, over the 0 5 10 15 20 18-year period of record. The reasons for SALINITY (ppt) this apparent increase are unknown. Figure 4.14. DIN. OP ratio versus salinity in the For bottom water dissolved oxygen, Pamlico River estuary, 1979-1986. Data from stations 1, 5, 8, 10 and 12. 72 Chapter 4 of the estuary (Stanley 1987; Hobbie 1974). For the mid-river segment, E, there Two other features of the blooms are that was no significant change in chlorophyll a theyare short-lived, and they usually occur over the whole samplingperiod, 1970-1986. at only one or two sampling stations. Also, But when the shorter period 1975-1986 river flow can play an important role in the was tested, a significant increase (p = 0.003) timing and location of the winter blooms. was detected. In other words, chlorophyll In some years, high water inflow from the apparently declined in this river segment Tar flushes out much ofthe algal population duringthe 1970s, and then increased again from the river. in the 1980s. The time-series plot (Figure The trend test results indicate that 51 in Stanley 1988) for this segment clearly chlorophyll a concentrations have increased shows the decrease from concentrations in the middle and upper segments, B and typically between 10 and 20 jig/liter in the E, of the Pamlico, but not in the downriver early 1970s to often < 10 jkg/liter in the mid- segment, H. Upriver in segment B, the 1970s. Of course, these data are from increase was highly significant (p<0.01), different sampling programs, but I could during both time intervals tested. The find no evidence ofchanges in the analytical average annual rates of increase were 0.29 techniques that could explain the differ- ;kg/liter per year and 0.64 /ig/liter per year ences. Therefore, I must assume that the for 1967-1986 and 1975-1986, respectively. decline was real. This is equivalent to about a 50 percent A very noticeable feature of the chloro- increase duringthe 16-year period ofrecord. phyll time-series plots is that in recent years the bloom peaks appear to be more frequent and higher, particularly upriver in segment B. But closer examination 25 A showed no clear long-term trend in the 20 DECEMBER-MARCH frequency of high values. I made a plot of 15 the percentage ofvalues over 40 gg/liter for ach year since the sampling began in VEMBE (L 10 0 R e < 7 5 1970 (Figure 4.15). Note that there were no data for 1974, and the 1985 data were 01970 1975 1980 1985 not used because some of them are suspect. YEAR In 1979, the North Carolina Environmental Management Commission adopted a chlo- 30 B rophyll a quality standard of 40 gg/liter for 25 LOWER UPPER all lakes, sounds, estuaries, reservoirs 20 and other slow-moving waters not desig- MIDDLE nated as trout waters" (North Carolina 10 Department ofNatural Resources and Com- 5 0 mun ity Development 1987, page 38). This 1970 1975 1980 1985 standard applies during the months April YEAR through November. In most years, the highest number ofPamlico samples exceed- Figure 4.15. Pamlico River estuary chlorophyll a. ing4O pg/liter occurred in the wintermonths Percentage of sample values greater than 40 AgI of December through March, when the liter for eachyear (1970-1986). (A)Datagroupedby standard is not applicable (Figure 4.15a). twoperiods (April-November andDecember-March). (B) Data grouped by river segment: "upper" = The percentage ofApril-November samples segments A, Band W@niddle"= segments D, E and violating the standard has ranged from PM oil F, "lower" = segments G, H and L Pamlico River Estuary Water Quality Trends 73 <1% in 1970, 1975-1976 and 1980, to 5-10. Farther downriver in the middle around 10% in 1986. There has been no reach (segments D, E and F), the percent- clear trend in these percentages. Overall ages were about the same, but in the lower the early 1970s values are about the same river (segments G-I), no more than 6% of as those for the early-to-mid 1980s. The dip the samples had over 40 lig chlorophyll a/ in the mid-1970s maybe real, ormaybe an liter in anyyear. Again, there has been no artifact associated with the relatively infre obvious change in this pattern since the quent late winter sampling between 1975 sampling was begun in 1970. and 1979. Inmost years, high chlorophyll a values Phytoplankton Species Composition were more frequent in the upper and middle and Biomass river areas than in the lower estuary Phytoplankton have not been moni- (Figure4.15b). In the upper area - encom- tored regularly for a long period in the passing river segments A, B and C -up to Pamlico River. Therefore, there are not 24% of the values were >40 /ig/liter (1986). sufficient data to permit analysis of trends More typically, the percentage was around by the Seasonal Kendall procedure. How- A 100 - Figure 4.16. Phytoplankton biomass (averaged by sampling so - X X date) in the Pamlico River for (A) 1966-1968 and (B) 1983-1985. Wet weight (mg1liter) for each cla8s expressed aspercent oftotal DIN I X: so - biomos8. BAC = Bacillario- phyceae, CHL = Chlorophyceae, ao - CHR = Chry8ophyceae, black Cyanophyceae, DIN = Dino- 40 - phyceae, UNK Unknown. 30- tt- nt 20- 0 1966 1967 1968 B 100 UNK 70 50- 40 - CHL 30 - 20 .... . .. ........ 1983 1984 1985 74 Chapter 4 ever, there have been two major studies of the same ones used for the nutrient and phytoplankton species, numbers and bio- hydrography study. mass in the Pamlico. Since these studies The data suggest that phytoplankton were separated by a time interval ofapprox- species composition in the Pamlico has not imately 15 years, I thought it might be changed substantially during the past two useful to compare the results, which might decades. Figure 4.16 shows phytoplankton at least give clues about the presence or biomass broken down by class, for both the absence of long-term changes in the estu- 1966-1968 samples and the 1983-1983 sam- ary's phytoplankton. The first study was ples. The plotted data are means of all by Hobbie (197 1) for the time period August stations sampled on each date. In both 1966 through April 1968. Samples came sample periods, four classes made up the from the same stations used for nutrient bulk of the total biomass. These were and hydrographic monitoring. The second diatoms (Class Bacillariophyceae), green phytoplankton study, sponsored by North algae (Class Chlorophyceae), chrysophytes, Carolina Phosphate Corporation, was made (Class Chrysophyceae), and dinoflagellates during the period April 1982 through (Class Dinophyceae). Diatoms usually com- December 1985 (Stanley 1983, 1984a; prised around 10-20% of the total biomass, Stanley and Daniel 1985a, 1985b, 1986). although there is considerable scatter, as Samples were collected approximately there also is for each of the other algal every other week from stations in the river classes. Diatoms were most important in and in South Creek. River stations were the winter and spring. The green algae were also relatively important in the spring, comprising, on average, 58% and 17% of the total biomass in 1983 and 1984, respec- 10 tively (Stanley and Daniel 1985b). At 9 A other times of the year in 1983 and 1984, 8 and in all of 1966-1968, they were an 7 insignificant part ofthe total. The seasonal z W 6 pattern for the chrysophytes is clearer; 0 (9 5 they definitely were more abundant in the 4 summer than at other times, both during 19W 1967 1968 1969 the 1966-1968 and 1983-1985 sampling YEAR periods. In some instances, they averaged 8 70-90% of the total biomass. Overall, the B most abundant algal class was the dino- 7 flagellates, which made up 80% or more of 6 % % the total on many dates, particularly in the 6M % z 5 fall and winter. From the data presented in Figure 4 3 1 4.17, it would appear that algal cell density 1983 1984 1985 1986 and biomass (data not shown) were sub- YEAR stantially higher in the late 1960s than Figure 4.17. Averagephytoplankton de now. Between 1966 and 1968, the cell cell ns'ty densities (averaged on each sample date (logcell8 Iliter) in the Pamlico Riverestuary during two 8amplingperiods. (A) 1966-1968 and (B) 1983- for all stations) were mostly between 107 1985. and 1011 ceils/liter, which was 10- 100 times B higher than the typical 1983-1985 cell den- Pamlico River Estuary Water Quality Trends 75 sity. Similarly, biomass in the 1966-1968 that data from different periods would be period appears to have been about ten comparable. Unfortunately, turnover in times higher than in the 1983-1985 sam- technical personnel and the tendency to pling period. There is considerable scatter conduct short-term studies make this an in the data from both periods. unlikely solution. However, there are four reasons to In his report on the 1966-1968 data, suspect that these apparent declines in cell Hobbie made some interesting comments density and biomass are not real. First, regarding phytoplankton and eutrophica- about three-quarters of the samples col- tion in the Pamlico: lected during the 1966-1968 study were from the winter when dinoflagellate blooms Overall, the algae indicate that (Heterucapsatriquetra) are greatest. Conse- the Pamlico River estuary is a highly quently, there were a few samples with eutrophic body of water. Whether or very high densities and biomasses which not it should be called polluted depends greatly affected the means. If there had upon the definition of pollution chosen and also upon someone's opinion as to been more (presumably low biomass) sam- the state of the river before man's ples from otherseasons, the average would activities began in the drainage basin. have been considerably lower. Second, in Because the algae are not a menace or several samples, Hobbie found extremely hindrance to fishing or recreation, I do high numbers of a very small unidentified not believe the estuary is polluted. alga that was less than 2 gnis in volume. The natural fauna are still present This species contributed nothing to the and so far the algae are the only indi- biomass but considerably increased the cator showing pollution. Of course, average cell density. Third, a check of the any more nutrient enrichment should cell volumes assigned to some of the most be avoided as the next step may be deoxygenation of the water. This de- abundant species showed that Hobbie's oxygenation would undoubtedly kill estimates were, in some cases, higher than many fish and shellfish. Although it is those used in the more recent study. For just speculation at this point, it is very example, Hobbie estimated the volume for likely that if the algae bloom occurred Heterocapsa triquetra as 3360 jzms, com- during the summer months, the in- pared to 2011 /-tm-1 by Stanley and Daniel creased respiration associated with the (1985a). And finally, the trend in chloro- higher water temperature might well phyll a in the river over the past two reduce the oxygen to a low level. For decades contradicts these phytoplankton this reason, it is important to under- biomass results. stand how the phytoplankton are operating and to avoid any changes to It is unfortunate that the algal biomass the estuary regime that would create data are not comparable, but perhaps there an algal bloom in summer" (Hobbie is a lesson to be learned from this attempt. 1971, page 35). It would seem that estimating algal cell density and biomass is an "art" as much as Some comments should also be made a "science," because of the difficulty asso- regarding blue-green algae in the Pamlico, ciated with identifyingthe extremely small since blooms of these nuisance algae have forms that make up so much of the phyto- become common in some areas of coastal plankton. Perhaps the only solution is to North Carolina in recent years. In particu- have one person commit himself or herself lar, the lower Chowan River and the lower to making counts for an estuary over a long Neuse River experience severe blue-green period of time. This would at least insure algae blooms during some, but not all, internal consistency in the time series so 76 Chapter 4 summers (North Carolina Department of lies in the difficulty, alluded to above, of Natural Resources and Community Devel- correctly identifying these tiny algae. Most opment 1982; Christian et al. 1988). First, are less than 2 Pm in diameter, so that they it should be noted that the blooms in these appear as tiny dots under the 40OX mag- two systems have been restricted to fresh nification used to make the cell counts. waters, or waters of very low salinity. The One person may count these as algae, comparable region in the Tar-Pamlico while another might disregard them as would be upstream of Washington (i.e., pollen grains or other non-algal items. upriver from station 12 used for the Texas- This is certainly possible, but there is no gulf monitoring program). Although no way to know if this actually happened. sampling for algae has been done in that Whether or not blue-green algae are area, it is probably safe to assume that no present in the Pamlico estuary, it is clear blooms have occurred there of the magni- from both the 1966-1968 and 1983-1983 tude and spatial extent comparable to those studies that they do not contribute signifi- in the Chowan and Neuse. Hobbie (1971) cantly to the total algal biomass. Using apparently found blue-greens to be numeri- Hobbie's raw data, I calculated that the cally abundant at some times in the Pamlico blue-greens usually made up less than River estuary, but Stanley and Daniel 10% of the total biomass in the late 1960s. (1985b) did not find them in large numbers Similarly, duringthe more recent sampling in the more recent study. It is possible that period (1983-1985), there were only a few this discrepancy represents a change in species of blue-green algae and they the river's algal species composition, but I accounted for less than 1% of the algal suspect that the more likely explanation density and biomass in the river (Stanley and Daniel 1985). CHAPTER5 Stratification and Bottom Water Hypoxia in the Pamlico River Estuary* Introduction "One of the things we can do is to look at The severity of dissolved oxygen (DO) places like the Chesapeake Bay, the depletion in the bottom waters of estuaries Hudson River and the San Francisco Bay. appears to range widely, depending on a They were showing the same signs of stress combination of factors includingmorphom- about 10 years ago that the Pamlico is etry, vertical density stratification, and showing now . . . the signals are there. perhaps nutrient and organic matter in- B.J. Copeland (1987) puts. Persistent bottom-water hypoxia is obvious need for better description and common in stratified estuaries that have deep channels. Examples include Chesa- quantification of the roles of freshwater peake Bay and some of its tributaries (Taft discharge, lunar tides, and winds as physi- et al. 1980; Officer et al. 1984; Kuo and cal energy inputs influencing vertical mix- Neilson 1987; Kuo et al. 1991) and parts of ing. But so far, only a few such studies the Puget Sound System (Christensen and have been made. In Chesapeake Bay, Packard 1976). Coastal ocean areas such multi-year observations and mathematical as the Atlantic inner continental shelfsouth modeling have shown that wind is respon- of Long Island, NY (Swanson and Sinder- sible for breakup of the summer stratifica- mann 1979; Falkowski et al. 1980) and the tion in the early fall and that wind-induced northern Gulf of Mexico (Boesch 1983; destratification continues through mid- Harper et al. 1981) also have experienced spring (Goodrich et al. 1987; Blumberg severe hypoxia. Fortnightly mixingrelated and Goodrich 1990). It has been determined to spring-neap tidal cycles has been ob- that for Mobile Bay - a shallow, bar-built served in some estuaries, including the estuary - the tide is less important than James, Rappahannock, and York rivers river flow and wind-driven circulation (Haas 1977; D'Elia et al. 198 1; Ruzecki and (Schroeder and Wiseman 1986; Schroeder Evans 1986). In shallow estuaries wind et al. 1990). It seems reasonable that wind mixing tends to decrease water column and river flow may strongly influence stratification more frequently, so that bot- stratification and bottom oxygen condi- tom water hypoxia is generally of short tions in many of our nation's estuaries, duration and limited in spatial extent. In given that over half have mean depths <5 Mobile Bay, forexample, periods ofstratif-j- in (Nixon 1988), and that many of those cation and mixing occur as frequently as along the southern Atlantic and Gulfcoasts daily (Turner et al. 1987; Schroeder et al. are isolated from strong lunar tides by 1990). chains of barrier islands. Given that stratification is a key factor In this paper we examine the relation- in the establishment of hypoxia, there is an ships amongbottom water oxygen, vertical stratification, and the factors responsible *coauthored by S. W. Nixon, Graduate School of Oceanography, University ofRhode Islanc4 Narragansett, Rhode Island 78 Chapter 5 for stratification-destratification in the Banks, a chain ofbarrier islands separating Pamlico River Estuary in North Carolina. Pamlico Sound from the Atlantic Ocean. The study is based primarily on a 15-year However, "wind tides" of 0.5-1.0 m are not set of biweekly oxygen, salinity, tempera- uncommon, and are most likely following ture, and nutrient concentration measure- several days of sustained winds from ments, but we also have incorporated some directions approximately parallel to the recent continuous monitoring results. estuarine axis (Giese et al. 1979). Prevail- The Pamlico is a shallow (2.7 m mean ing summertime winds in the Pamlico depth), oligohaline-mesohaline estuary ex- region are from the SW and NE. tending 65 km from Washington, NC, to Seasonal salinity patterns in the estu- the western edge of Pamlico Sound (Figure ary are set primarily by variation in Tar 5.1). The estuary varies in width from River flow. Typically, surface salinity is <8 about 0.5 km near Washington to about ppt duringthe late winterand earlyspring. 6.5 km at its mouth. The Pamlico "River" is The salinity increases to maximum values actually the estuary ofthe Tar River, which (10-15 ppt) during fall. However, there is drains most of the 14,000 kM2basin area. considerable interannual variability. Dur- Total freshwater flow into the Pamlico ingdrought years the salinitymay approach typically ranges between 28 mls-1 in October that ofPamlico Sound (20-24 ppt). Temper- and 112 m3s-1 in February (Giese et al. atures in the estuary typically range from 1979). Freshwater flushing times corre- 40C in January to 300C in August. Details sponding to this flow range are estimated of the hydrography and ecology of the to be between 80 and 28 days. Lunar tides estuary are given in Giese et al. (1979) and in the estuary are almost negligible (7 cm), Copeland et al. (1984). due to restrictions imposed by the Outer NORTH CAROLINA 2 a W 3 J 200, Tiw 2 USGS 3 3 5 2 3 TEXASGU LF N 5 2 .3 6 2 0 2 4 6 8 KILOMETERS 2, Figure 5.1. Location ofwater quality scunpling stations (10,8,5, and 1) and the U.S. Geological Survey continuous monitoring station (USGS) in the Pamlico River Estuary. Depth contours in M. Stratification and Bottom Water Hypoxia 79 Hypoxia, or "dead water" as it is known concentrations read from the air-calibrated locally, has become one of the most impor- meter were corrected to ambient water tant environmental issues for the Pamlico. temperature and salinity. Measurements Hypoxia in the estuary was first docu- were made at two depths: approximately mented in the late 1960s (Hobbie et al. one-half meter below the surface and one- 1975), and was investigated more thor- half meter above the bottom. These will be oughly in the mid- 1970s (Davis et al. 1978), referred to as "surface" and "bottom" read- but knowledge about it seems to have ings. Samples for chlorophyll a, and N and become widespread only in more recent P were collected only at the surface. Chlo- times. A recurring theme in many news- rophyll a was measured by the method of paper articles, regulatory agency docu- Strickland and Parsons (1972), and the N ments, and some of the scientific literature and P analyses were by methods given in written during the late 1980s is that nutri- USEPA (1979) and APHA (1985). ent inputs promote large blooms of phyto- In addition, we will present excerpts plankton that eventually die, decompose, from a time-series (3-hr measurement inter- andcontribute inamajorwayto lowoxygen val) of near-surface and near-bottom DO, conditions during summer. In addition, temperature, and salinity (determined from most fish kills in the estuary in recent temperature and specific conductance mea- years have been attributed to hypoxia in surements). The data are from a study the bottom waters. Many citizens, and carried out by the U.S. Geological Survey, some scientists, suspect that bottom water using a Minimonitor, a U.S.G.S. designed anoxia and fish kills are more common in instrument controlled by a CR10 micro- the estuary now than in the past. logger with data storage in an SM-192, which has permanent memory. The moni- Methods tor was mounted on the piling supporting Most of the data used in this study are Pamlico River Light 5 (a U.S. Coast Guard from an ongoing water quality monitorin navigation channel marker) about halfway program sponsored by Texasgulf Che @ between our stations 5 and 8 (Figure 5.1). mi- cals, Inc. and carried out by East Carolina The near-bottom. and near-surface probes University since 1975. Salinity, tempera- were 1.2 in and 3.6 in above streambed, ture, dissolved oxygen, NO.,-N, NH 4-N, PO 4- respectively. Mean low water depth at this P, and chlorophyll a are among the suite of marker is estimated to be 4.5 in. The variables measured approximately every Minimonitor was serviced at 2-week inter- other week at 20 sampling stations in the vals. Vertical profiles of temperature, spe- Pamlico. For this study we chose to use cific conductance, and Do were measured data from four of these stations; they are and compared to monitor readings. After all located near mid-channel along the axis the probes were cleaned, monitor and field of the estuary. Station 1 is near the mouth readings were again compared. If the field at Pamlico Sound, and Stations 5,8, and 10 and monitor readings differed only by a are progressively farther toward the head relatively small amount, the monitor was of the estuary (Figure 5.1). Mean low tide adjusted to agree with field readings. If the water depths are approximately 5.0 in, 4.5 difference between the monitor and field m, 4.5 in, and 3.5 in, respectively. Tempera- readings was large, probes or the entire ture and salinity were measured with a monitor were replaced with a laboratory- YSI Model 33 S-C-T meter, and dissolved calibrated unit. The monitor was returned oxygen was measured with a YSI Model 51 to the laboratory for routine recalibration oxygen meter and electrode. Oxygen at 3-month intervals (Bales 1990). 80 Chapter 5 Wind velocity data, provided by Texas- freshwater drainage into the estuary is gulf Chemicals, Inc., were recorded at their proportional to the gauged flow (Giese et plant site about midway down the estuary al. 1979). on the south shore (Figure 5.1). Wind We used the Spearman Rank Correla- speeds were converted to stress using the tion procedure to investigate relationships quadratic law with a drag coefficient of 1.5 among the hydrographic variables. This is x 10-8 (Garratt 1977). Daily mean Tar a nonparametric test of the presence or River discharge data are' from the U.S. absence of association between two vari- Geological Survey gage at Tarboro, NC, ables. It can also estimate the strength of which is 80 km upstream from the estuary; the relationship, if one exists (Conover consequently there can be substantial 1980; Daniel 1978). The computed coeffi- travel time lags between it and the estu- cient (R) will range between -1 (perfect arine sampling stations. Aboutone-halfof inverse relationship) and + 1 (perfect direct the drainage basin is ungauged, but pre- relationship). The Spearman test is in- cipitation rates and runoffgrates are similar to those in the gauged areas, so that total 100- 60-% SAT. 80- 40-60% SAT. 80. 4-5 MG/1 A so- 2040% SAT 60 3-4 MG/1 0-20% SAT. 4O- 20 40 2-3 Mg/l FREQUENCY (%OF SAMPLES) p 40- 1-2 Mg/l 20 .1mg/10 20 0 0-5 5-10 10-15 15-20 20-25 25 0 PERATURE(06 uency of four DO percent J F M A M J J A S O N D F6 Figure 5.3. Freq MONTH saturation ranges for six temperature ranges. Includes all data from fourmonitoring stations for the period 1975-89. 140- 120- <20 96 20-40 % 40-60 % B 8O 100. 60-80% 80-100 % 70 0-20% SATURATION U. 80. AL 60 60 50. 40 40- 20 30 0 J F M A M J J A S 0 N D MONTH 10- Figure 5.2. Frequency of five DO concen- 0-1 1-2 2-3 34 4-6 >5 DELTA SIGMA-T tration ranges (A) and percent saturation Figure 5.4. Frequency of Sample8 with <20% ranges (B) for each month. All data from four DO saturation for six delta SigmaT ranges. monitoring stations for the -period 197326-89 Includes only measurements made when water included. temperature was >150C. Stratification and Bottom Water Hypoxia 81 eluded in SYSTAT, a statistics package was considered to show statistical available for microcomputers. We imple- significance. mented Version 4.0 of SYSTAT, which is documented in the user's manual byWilkin- Results and Discussion son (1988), on a microcomputer. Seosonal and Spatial Variabillty The Seasonal Kendall-Tau test was Frequency distribution plots ofall mea- used to examine the flow, salinity, delta surements made between 1975 and 1989 s igma-t, and bottom Do data for long-term show a distinct seasonal pattern in Pam- trends. The test, which was developed by lico bottom water oxygen (Figure 5.2a). Hirsch et al. (1982) is a nonparametric Concentrations <5 mg 1-1 are least common procedure suitable for application to water- in the winter months (0-15%) and most quality parameters which are often skewed, common in July (75%). About one-third of serially correlated, and affected by season- the July measurements are < 1 mg 1-1. This ality. The test compares all possible pattern is in part a reflection of the effect combinations of pairs of values over time, that annual water temperature and salinity assigning a plus if an increase occurs from cycles in the estuary have on oxygen solu- one value to the next, or a minus if a bility. But other factors must be involved, decrease occurs. If more pluses occur than since the percent saturation frequency plot minuses, then an increasing trend is indi- shows the same pattern (Figure 5.2b). cated; conversely, more minuses than pluses indicate a decreasing trend. The 60 pairs of values compared are from the 4-5 mg/1 JANUARY-DECEMBER same "seasonal" period - in this case, 40 3-4mg/1 months. In other words, only January 2-3 mg/1 values were compared with other January 130 1-2 mg/1 values, only June values were compared : 1 Mg/1 with June values, etc. The data within 20 each month were summarized as means, A 10 and the test was run on the monthly means. A significance level (alpha) of 0.10 or less 0 10 8 5 1 STATION 100- 100 100% JANUARY-DECEMBER >6 80- 9L bu - IL 40-60 % 4-6 2 1 20-40 % 60. 2-4 060- 20 % 80 40 40 B 20 20 0 20 J F M A M J J A S 0 N D 10 8 MONTH STATION Figure 5.5. Frequency of three delta Sigma-t Figure 5.6. Frequency of five DO concentration ranges (bottom water - surface water) for each ranges (A) and percent saturation ranges (B) month. Includes all data from our monitoring for each monitoring station. Includes all data for the period 1975-89 stations for t 82 Chapter 5 Instances of strongundersaturation (<40%) hypoxia increases with increasing strength are rare in the, winter but frequent in the ofwater-column stratification, as measured summer months (39-61%). by delta Sigma-t. On the other hand, the A plot of all bottom water DO percent scarcity of hypoxia during winter (< 150C) saturations, grouped into six water temper- cannot be due to a lack of water-column ature ranges (Figure 5.3), reveals a sharp stratification because a frequency plot of increase in the probability of moderate delta Sigma-t indicates that stratification hypoxia at temperatures >150C. Below is even more common in the winter than in this temperature, only 4% of the DO mea- the summer (Figure 5.5). Thus, it appears surements, were *less than 40% saturation, that the combination of stratification and but above 150C, 38% were< 40% saturation, warm water temperature is most conducive andabove 256C over halfthe measurements to the development ofbottom water hypoxia (52%) were <40% saturation. Severe hy- in the Pamlico. poxia (<20% saturation) is also most preva- Severe hypoxia occurs more frequently lent at the higher water temperatures. In in the upper half of the estuary than near addition, Figure 5.4 shows that for tempera- the mouth (Figures 5.6 and 5.7). When tures above 150C the frequency of severe data for all months are considered, around SW SE NW W SW SSWW NESW WSW NW S W NW W SE W SW NE S SW NW SW 80 JUNE-SEPTEMBER A 70 4-5mg/1 224 . . . . . . 4 3-4 mg/1 FLOW 60 - 168- 3 2-3 mg.1 50 1.2 mg/1 112 2 56- 40- 0 WIND STRESS (dyne cm)-2 0 30 WIND A 2- SURFACE 20 4- 10 6- 0 0 8- 10 5 1 8 . . . . . . . . . . . . STATION 10 12i 16 20 24 28 1 1 15 MAY JUNE W NE NE NE NE N N NW SW SW SW NE E 112 4 JUNE-SEPTEMBER 100 80-100% B C WND 84- -3 EEI 80-W % . . . . . . . . . 80 60 40 % 56- -2 CD W 20-40 % FLOW 60- 28- 0 . . . . .. 0 z B 4- 20 8 SURFACE. 16 12- 0- a 5 BOTTOM 10 STATION 2345678910111213 SEPTEMBER 1989 Figure 5.7. Frequency offive DO concentration Figure 5.8. Surface and bottom salinity, Tar ranges (A) and percent saturation ranges (B) River flow, and wind stress and direction for for each monitoring station. Includes only two periods during 1989. Salinity and wind June-September data for the period 1975-89. data are plotted at 3-hr intervals, and flow is the daily mean. StratIfIcation and Bottom Water HypoxIa 83 15% of the upper- and mid-estuary mea- estuary are important factors influencing surements (Stations 10, 8, and 5) give the timingofthese events. Three sequences, oxygen concentrations <1 mg 1-1, while at representing a variety of wind and flow Station 1 near the mouth only 2% of the conditions between May and November, values are below 1 mg 1-1 (Figure 5.6a). will be summarized. However, there is less spatial variation in The first time-series covers a period the frequency of oxygen concentrations in characterized by rapidly decliningTarRiver the 1-5 mg 1-1 range. About 30% of Station discharge (Figure 5.8a). On May 12 the 10 values fall in this range, compared to discharge at Tarboro was 250 mss-I - 25% at stations farther down the estuary. about three times the long-term average The percent saturations also showa greater for that time of year. By late May flow had spatial difference in the lowest range than fallen to more typical rates, around 40 mss- in the higher ranges (Figure 5.6b). From 1, and it changed little from then until the 18 to 23% of samples from the upper- and end of the interval on June 5. Surface mid-estuary stations are less than 20% salinity responded to the declining fresh- saturated, compared to only 4% at Station water input by rising from 1 ppt early in 1. A similar analysis of data from the the period to 5 ppt at the end. Despite summer months (June -September) shows relatively low wind stress (<0.5 dyne cm-2) that even though the frequency of low early in the period, there was little strati- oxygen increases during warm weather, fication, as evidenced by the small differ- the spatial pattern does not change; i.e., ences between surface and bottom salini- low oxygen is still most common in the ties. Thus, river flow appeared to be the upper regions of the estuary (Figure 5.7). Concentrations less than 1 mg 1-1 occur in one-third of the samples from the upper estuary, but in only 4% ofthe samples from S SW SW N NE NE NE NWNE NE SW SW SW NW SE S SW W NW NE NE NE NW NNW NE SW SW SW SE near the mouth. The percent saturation 12 ......... is ii -it i.. data show the same pattern. One possible -10- explanation for these spatial patterns is 6- that because of its orientation in relation to A 4- 0 the directions of the prevailing winds, the 0 2-1111 E upper estuary is not as well mixed as the 0 20- -4 lower estuary. Correlation analysis evi- PLOW 3 dence that supports this conclusion will be Sao- 2 presented below. LL Nb@ 1 0 0 Z Short-Term Variability Unfortunately, the long-term monitor- -9 4- ;;M- he ing data provide little insight into t short-term dynamics of stratification and TTO hypoxia in the Pamlico, due to the relatively ....... 16 20 24 28 1 5 9 13 long sampling interval (two-three weeks). OCTOBER NOVEMBER But data from the 1989 continuous monitor- Figure 5.9. Surface and bottom aalinity, Tar ing study show that stratification/hypoxia River flow, wind stress and direction, and events can develop and break down very bottom water DO concentration for the period rapidly. These data also stronglysuggest October 16-November 14,1989. Salinity, wind, that wind and freshwater flow into the and DO data areplotted at 3-hr interval8; flow is the daily mean. 84 Chapter 5 dominant control then. But as flow de- seiching within the estuary. As the storm creased, wind became more important, as approached, wind stress increased and demonstrated by the development of weak shifted to the NE. This mixed the water stratification (2 ppt) on 19 May after wind column and began to drive saltier water in stress subsided below 1 dyne CM-2 . This from the eastern end of the estuary, so that stratification was broken up three days by the time the storm had passed on 6 later as the winds increased. From then September, salinities throughout the water until the end of the period, wind velocities column had risen to about 11 ppt. Grad- were variable, with only brief periods of ually, over the next 4-5 days, the wind calm. Consequently, there were no sus- shifted back to the SW, and surface salinities tained stratification events. decreased slowly to 8-9 ppt. Also, the wind The second sequence (2-13 September) velocities declined, allowinga vertical salin- was highlighted by below normal ity gradient of about 5 ppt to develop. After freshwater discharge and a strong wind 9 September both increasi ng bottom sali n- event associated with the passage of a ity and decreasing surface salinity con- storm front. The period began with weak tributed to the widening vertical salinity westerly winds, high surface salinity (9 gradient. ppt), and weak stratification (Figure 5.8b). No oxygen data are available for these Alens ofsaltier water in the vicinity appears first two sequences, but there are Do data to have intruded twice for brief periods on for the final sequence, spanning the period 2 and 3 September. This movement may mid-October to mid-November, 1989 (Fig- havebeen related totidal forcingor internal ure 5.9). This sequence is also interesting Table 5.1. Spearman Rank Correlations Table 5.2. Spearman Rank Correlations between bottom water DO and selected between D Sigma4 and selected variables. variables. F=flow on day ofDO measurement; F=flow on day of DO measurement; F-5, F-10, F-5, F-10, and F-15=5, 10, and 15-day lagged and F-15=5, 10, and 15-day lagged flows; flows; WS=Wind stress on day of DO WS=wind stress on day of DO measurement; measurement; WS-1 and WS-2=1 and 2-day WS-1 and WS-2=1 and 2-day lagged wind lagged wind stress; BSAL=bottom water stress; BSAL=bottom water salinit . Surface y salinity; CHLA=chlorophyll a; andDSIGMAT samples were analyzed for N and P =deltaSigma-t. Surface samples were analyzed concentrations. for N and P concentrations. Station Station Variable Variable 10 8 5 1 10 8 5 1 F -0.210* -0.081 0.009 0.111 F 0.149 -0.030 0.030 -0.167 F-5 -0.204* -0.085 0.027 0.128 F-5 0.139 0.034 0.026 -0.361** F-10 -0.173 0.110 0.114 0.205 F-10 0.112 -0.150 -0.012 -0.201 F-15 -0.199* .0.030 0.159 0.231* F-15 0.166 -0.087 -0.045 -0.108 WS -0.184* -0.257* -0.197* -0.221* WS 0.072 0.279** 0.184* 0.062 WS-1 -0.202* -0.319** -0.234* -0.300** WS-1 0.199* 0.293** 0.279** 0.344** WS-2 -0.108 -0.178 0.028 -0.127 WS-2 0.140 0.305*** 0.134 0.178 BSAL 0.732*** 0.560*** 0.452*** 0.266* BSAL -0.477*** -0.446*** -0.400*** _0.145 NO 3-N -0.262** 0.203* -0.109 -0.484*** NO,-N 0.284** 0.298** 0.146 0.357** NH 4-N -0.225* -0.288** -0.160 -0.377** NH,-N 0.104 0.241* 0.134 0.366** P04-P -0.066 -0.060 -0.160 -0.377** PO'-P 0.113 -0.066 -0.113 -0.067 P<.05 CHIA -0.175 -0.155 0.035 * -0.023 .-P<01 DSIGMAT -0.665*** -0.674*** -0.742** -0.432*** ... P<.ooi *P<05 **P<01 .*.P<.001 Stratification and Bottom Water Hypoxia 85 because it includes large, short-term fluctu- ing wind stress combined to turn the water ations in Tar River discharge and wind column over in a matter of a few hours stress, which interacted to produce four during the evening. distinct episodes of stratification. The first Within 48 hours, another stratification was in progress at the beginning of the event had begun to develop (30 October). sequence on 16 October. Tar River flow This time, winds switched from the NE to had declined from a previous peak to 20 the NW, and decreased in velocity. This m8s'l, winds were blowing slowly from the event lasted about 4 days, with a vertical south, and there was a 6 ppt difference salinity gradient of about 4-6 ppt and bot- between surface and bottom salinities. Also, tom water DO reduced to around 2 mg 1-1. bottom water DO was extremely low - It ended late on 2 October following in- well below 1 mg 1-1. The next day, a strong creased wind stress the previous night. afternoon wind from the south eroded the The fourth episode began almost salinity gradient, but was not sufficient to immediately, and for the next three days destroy it. Even stronger winds on the (4-6 November), there was weak stratifi- 19th temporarily broke up the gradient, cation that was nearly broken on several and finally on the 20th it was destroyed occasions, but apparently did not com- following a third day of strong afternoon pletely disappear, since the bottom water wind. At this time, the bottom water DO DO continued to fall, reaching 1 ing 1-1 on rose dramatically, reaching saturation con- the 6th. The vertical salinity gradient centration (9 mg 1-1) by 21 October. Subsid- strengthened on the next day, weakened ing winds on the 22nd and 23rd led to brief on the 9th following stronger winds, and periods of stratification and lowered DO. fluctuated between 2 and 6 ppt for the Again, these very sharp fluctuations may remainder of the sampling period. Bottom have been caused by short-term tidal or DO also fluctuated, mostly between 2 and seiching effects. 4 mg 1-1. Meanwhile, in response to widespread In summary, these time series data precipitation over the Tar basin, a flow suggest that, at least in the mid-estuary, pulse had been building steadily for about stratification events and bottom water 4 days, reaching a peak of 125 m3s-1 at oxygen levels are tightly coupled with varia- Tarboro on 22 October. That pulse reached tions in freshwater discharge and wind the estuary station three days layer, quickly stress. Stratification can change in a matter reducing the surface salinity to 5 ppt, and of hours, and episodes lasting from one to setting up the second stratification event, several days seem to be common. which eventually amounted to a 5 ppt vertical gradient. Bottom water DO fell Spearman Correlation Results rapidly from 6 ing 1-1 on 27 October to Results of the Spearman Rank Correla- around 1 mg 1-1 the following day. This tion analyses tended to corroborate conclu- seems to be a clear example ofstratification sions drawn from the frequency plots and caused by a moderate pulse of freshwater the continuous monitoring data. Several spreading out over the estuary surface variables were tested for correlation with under low wind stress conditions. In addi- bottom water DO concentration at each of tion, encroachment of saline Sound water, the four long-term monitoring stations. as evidenced by the slowly increasing bot- Only data from 1975-89 samplings when tom salinity, strengthened the density gra- the water temperature was > 150C were dient even more. On the 28th, both the used (Table 5. 1). Delta Sigma-t (bottom - pass ingof the Tar River pulse and increas- surface), gave the highest correlation co- 86 Chapter 5 efficient. The oxygen vs. delta Sigma-t sponse to the strength of the flushing relationship was inverse and was strongest exerted by freshwater inflow. at the three stations farthest up the estuary. Wind stress was significantly correlated The only physical variable showinga signifi- with stratification (Table 5.2) at all stations cant positive correlation to bottom water when the previous day's wind was Do was wind stress lagged by one day, considered, but only at one station when a another indication of the rapidity with 2-day lag was used. In addition, the which stratification events are established strength of these correlations trended and broken up. Tar River discharge, lagged upward toward the lower end ofthe estuary. 5, 10, or 15 days, seemed to be less impor- This seems logical, since the shape and tant, as the only significant combination orientation of the Pamlico is such that was the 5 -day lagged flow at Station 1. The fetch over which the prevailing SW and NE significant positive correlations between winds blow increases toward the mouth. bottom oxygen and surface N03 -N are inter- preted to result from the presence of larger Interannual Tr6nds fractions of high No. river water during Seasonal and interannual variability mixing periods when there is no hypoxia. of salinity in the Pamlico is determined Note that there was a strong negative primarily by freshwater runoff. Typically, correlation between DO and bottom salin- salinity is lowest during the late winter ity. The positive correlation between bot- and early spring when freshwater inflow is tom oxygen and surface NH Vandthenega- highes. The salinity increases to maximum tive correlation between delta Sigma-t and values in the summer and fall, coincident surface NH, (see Table 5.2) are interesting with lowest Tar River flow. In some years in that they suggest that stratification in this seasonal pattern may be upset by the Pamlico may lead to depletion of this extended periods of precipitation or nutrient in the surface layer. drought. For example, 1978, 1979, and Additional Spearman analyses were 1987 were relatively high flow and low made to test for associations between delta salinity years, while droughts in 1981 and Sigma-t, and two factors that could influ- 1988 resulted in unusually high salinities ence the strength of the stratification - (see Chapter 4). Tar River flow and wind stress (Table 5.2). Watercolumn stratification in the estu- Flows were lagged 0, 5, 10, and 15 days, ary is much more variable than bottom and wind stress was lagged 0, 1 and 2 days. salinity on a short-term basis. The only The computed correlation coefficients be- apparent long-term pattern in stratifica- tween flow and delta Sigma-t were signifi- tion is that its strength and variability are cant (p<.05) for only Station 10 at the reduced duringyears when bottom salinity upper end of the estuary. As would be is relatively low, such as 1978-79 and 1987. expected, time lags of 0 and 5 days gave the This is to be expected, since delta sigma-t strongest correlation for the upper stations, is influenced primarily by differences whereas 10 and 15-day lags gave the highest between bottom and surface salinities. coefficients for the outer end of the estuary. The Seasonal Kendall-Tau test indi- There is a curious trend in the flow vs. delta cated there were no long-term trends in Sigma-t coefficients, from negative in the flow, salinity, delta Sigma-t, or DO in the upper estuary to increasingly positive at Pamlico between 1975 and 1989. For each the lower station. This result could be of the four stations, none of the test results interpreted to be a result of the salt wedge were significant at the 90% level (alpha moving up and down the estuary in re- <0.1). Stratification and Bottom Water Hypoxia 87 There is evidence that, at this frequency Event Frequency of reoxygenation, oxygen demand by the Using hourly wind measurements col- sediments and water column is sufficient lected by Texasgulf duringthe summers of to lead to hypoxia or anoxia. If the average 1980-1985, we calculated the resultant summer Pamlico benthic oxygen uptake daily vectors ofthe axial (alongthe channel, rate of 378 PMOI M-2 h-1 measured by Kuen- 2950NW or 1150SE) and coaxial (cross- zler et al. (1984) is applied to the area of channel, 250NE or 2050SW) components of sediment in the upper and mid sections of the relative wind stress on the Pamlico. At the estuary where hypoxia is most frequent this level of analysis, the definition of a (142.4 kM2, see Nixon 1989, Appendix A), "strong" wind is somewhat arbitrary, but it appears that the total benthic oxygen the choice of a cross-channel vector equal uptake might amount to about 41,339 kgd- or greater than 100,000 kM2d-2or an axial 1. If we assume that one-half of the total vector equal or greater than 50,000 kM2 d- volume of 322.2 x 10'3ins ofwater contained 2 (0.24 and 0.12 dyne cm,2) seemed reason- in this part of the estuary is below the able based on the frequency with which pycnocline, then the sediments could lower such winds occur and a consideration that the oxygen content of the bottom water the generally weaker axial winds may pro- only by some 0.26 mg 1-1 d-1. At this rate, the duce vertical mixing at lower speeds be- total oxygen consumed by the sediments cause of their longer fetches. It would be duringthe longest average interval between useful in subsequent work to consider this strong wind events (12.4 days in August) problem in more detail. would lower the concentration by about 3.2 If the preliminary definition is accepted, mg I`. strong cross -channel and axial wind events Respiration by plankton and bacteria occurred, on average, with the frequencies in the water appears to be somewhat given in Table 5.3 during the summers of greater. Data presented by Davis et al. 1980-1985. Thus, there might be, on aver- (1978, their Figure 4) show concentrations age, a vertical mixingand reoxygenation of of 2-3 ing 1-1 ofparticulate organic carbon in the bottom water approximately every 8.6 the waters of the Pamlico during summer. days during June, every 11.5 days during At this concentration, their oxygen uptake July, every 12.4 days during August, and regressions (see their Figure 52) indicate every 6.5 days during September. that 8-14 ing 1-1 of oxygen were consumed during five days in July and 3-5 ing 1-1 were consumed during five days in August. Table 5.3. Frequency of occurrence (number These rates of water column respiration per month) of strong cross4hannel and axial are 2.3 to 10.8 times greater that the five- windevents duringthe summers of1980-1985. day oxygen uptake by the sediments and Assuming that only one day of strong wind is are sufficiently great that hypoxia and needed to destratify the estuary, we have anoxia could eas ily result if the water were considered two or more sequential days Of only mixed every 6.5 to 12.4 days. The sum strong wind as one event. Eventaareaeparated of these estimated benthic and water col- by two or more days of weaker wind. umn respiration rates (0.82-2.95 ing I-ld-1) Month Cross-Channel Axial Total compares reasonably well with the ob- served oxygen loss rates during periods of June 1.8 1.7 3.5 stratification in the fall of 1989 (Figure July 2.0 0.7 2.7 5.9). It seems clear that it is the balance August 2.2 0.3 2.5 between oxygen uptake and the frequency September 3.0 1.6 4.6 of strong wind events that largely deter- 88 Chapter 5 minesthe spatial extent and duration of volved in most episodes, and the great the low oxygen problem in the bottom majority of the kills were reported during waters of the Pamlico. the summer. In some cases, dissolved oxy- gen was measured and found to be low in Effects of Hypoxia on Pamlico Blota the kill vicinity; in other instances low DO Anoxia or hypoxia in estuarine bottom was inferred from circumstantial evidence waters obviously has the potential to seri- (e.g., "sulfide-like odors'). Unfortunately, ously impact benthic organisms, either most of these investigations took place acutely via kills or chronically via physio- several days after the kills, so that precise logical stress. The short-term effects were determination of circumstances at the time documented in the Pamlico during the late of the kill was very difficult. It should also 1960s by Tenore (1972), who found that be noted that hypoxia-related kills of fish, macrobenthos in deeper waters of the estu- particularly menhaden, occur frequently ary had low species diversity and density in many other estuaries along the mid- in the summer, and that variations in the Atlantic and Gulf coasts of the U.S. (e.g., density were correlated positively with Turner et al. 1987), under circumstances anoxia/hypoxia. Large kills of the benthos, similar to those surrounding the Pamlico occurred quickly in the affected areas fol- episodes. lowing the onset of hypoxia. However, these areas were recolonized by the follow- Conclusions ing winter. There have been no follow-up While hypoxia is not the only environ- studies to determine whether the benthos mental issue of concern in the Pamlico, it is density and distributions have changed in certainly one of the most important. Be- the Pamlico over the past two decades. It cause there are documented and potential would be helpful to be able to correlate the links between low oxygen and kills of fish degree of impact on the benthos with and commercially valuable shellfish, the changes in the areal extent, frequency, public has been more attentive to this issue and persistence of hypoxia events. But the than to most others. As noted above, many data base to allow such an analysis is not believe that increasing nutrient inputs are available. promoting larger blooms of phytoplankton '71ounder walk" is the local term de- that eventually lead to more "dead water" scribing movements of large numbers Of and fish kills than in the past. the fish into shallow waters along the However, the results of our analysis of Pamlico. The phenomenon typically occurs the historical data do not support such a in the summer during extended periods of view. 'Mere has been no trend toward hot weatherandcalm winds, and is usually lower bottom water DO over the past 15 interpreted as evidence ofan hypoxic event years. In addition, the Spearman Correla- in the estuary. Data obtained from the tion results detected no cause-and-effect North Carolina Division of Environmental relationship between nutrients or algal Management show that low DO was abundance and bottom water DO. Of suspected to be the cause of most fish kills course, it could be argued that lag effects investigated in the Pamlico during the are involved which would not be detected past two decades (NCDNRCD, unpublished by comparing contemporaneous measure- data). Most of the reported kills were not ments. However, one of us (Nixon 1989) in the main stem of the estuary, but rather has searched - without success - for near the heads of relatively small tributary evidence of a link between either: 1) the creeks. Menhaden were the species in- size of the winter-spring blooms of phyto- Stratification and Bottom Water Hypoxia 89 plankton in the estuary and the frequency in reducing the rate of increase in nutrient and extent of hypoxic conditions in the loading may be beneficial in the future. bottom waters of the estuary the following But reduction in N loading, at least within summer, or 2) the summer bloom and the any practical constraint, may not result in severity of hypoxia. an increase in the oxygen content of the The North Carolina Division ofEnviron- stratified bottom water of the estuary mental Management has recently desig- during summer. At that time of year, the nated the Tar-Pamlico as "Nutrient Sens i- waters of the Pamlico are "wind sensitive," tive Water,"with the goal ofreducing nitro- and we will have to accept the intermittent gen loadingto improve water quality in the hypoxia and anoxia as natural features of estuary. We would not argue that success the system. CHAPTER6 The Pamlico River: Comparisons with Other Estuaries Introduction "One of the things we can do is to look at In the past, relatively few comparative places like the Chesapeake Bay, the studies of estuarine water quality have Hudson River and the San Francisco Bay. been made. It has been speculated that the They were showing the same signs of stress reasons for this include: 1) the widespread about 10 years ago that the Pamlico is belief among ecologists that estuaries are showing now. . . the signals are there. so variable that attempts to generalize B.J. Copeland (1987) from one to another are bound to fail; and information contained in the Nixon report. 2) the great difficulty oforganizing, funding, Anyone interested in comparative estuarine and executing studies of more than one ecology should consult this source; it is one system (Nixon 1983). During the 1990s, of the most comprehensive reports on the the U.S. Environmental Protection Agency subject available at this time. plans to carry out a major, national com- Another comparative study that pro- parative study of estuaries as part of its vided useful data was authored by Boynton Environmental Monitoring and Assess- etal. (1982). Theyrevi ddataconcerning ment Program (EMAP). ewe In addition, few comparative analyses nutrients, phytoplankton production, and ofexistingdata for different estuaries have chlorophyll a from 63 different estuarine been published. S.W. Nixon, an estuarine systems. Finally, I have attempted to ecologist experienced in comparative syn- make some comparisons between the Pam- theses, points out that attempts at such lico River and the nearby Neuse River reviews are hampered by the relatively estuary. Unpublished 1985 and 1986 nutri- small number of estuaries that have been ent and hydrographic data from the Neuse thoroughly studied, by differences in study were used to illustrate similarities methodology used to produce the data, and and differences between it and the Pamlico by the problems that arise from spatial and River. temporal variability within each system N utrients (Nixon 1983). Nixon (1983) used previously published Comparing cycles of orthophosphate and unpublished information for his com- phosphorus in 14 estuaries, Nixon (1983) parative study of fourteen estuaries on the found that annual mean concentrations Atlantic, Gulf, and Pacific Coasts of the were less than 1 pM in Chesapeake Bay, in United States. Fortunately, the Pamlico the mid and lower regions of the Potomac River was one of the estuaries included in River Estuary, in Apalachicola Bay, Flor- the study. Topics covered include physical ida, and in Kaneohe Bay, Hawaii. Highest characteristics, nutrients, phytoplankton mean concentrations were found in the and primary production, zooplankton, Pamlico River (approximately 4 gM) and in icthyoplankton, benthos, and fish. In this South San Francisco Bay (about 25 pM). chapter, I have relied heavily on All the other systems had mean annual 92 Chapter 6 phosphate levels of 1-3 1AM. One feature effects ofdifferent flushingrates were taken common to most of the estuaries, including into account (Figure 6.1b). This correction the Pamlico River, is the summer increase was made by multiplying the annual input in phosphate, particularly at their lower by the approximate mean annual fresh- reaches. Presumably, the high Pamlico water replacement time. The estuarine phosphate is due to the large discharge data appeared to follow the same relation- from the Texasgulf phosphate mine on the ship found for lakes by Schindler (1978). south shore of the estuary (see Chapter 3). A comparison of salinity and nutrients The relationship between phosphate in the Pamlico River and the Neuse River input and concentrations that Nixon devel- showed that except for orthophosphate oped may provide a clue as to whether or phosphorus, there was little difference be- not the Pamlico phosphate levels would tween the two estuaries. Volume-weighted decrease if loadingfrom Texasgulf, orother monthly medians for the period January sources, were decreased. From a plot of 1985 to December 1986 were calculated phosphate input versus mean annual phos- and are plotted in Figure 6.2. This method phate concentration for all the estuaries of presenting the data eliminates bias aris- surveyed (Figure 6.1a), Nixon concluded ing from different sampling station loca- that indeed there is a correlation between tions in each estuary relative to the salinity the two. There was considerable scatter in gradients. The problem is most severe for the data, but this was reduced when the factors that vary greatly along the salinity gradient. The weighted monthly median salinities ranged from 8 ppt to about 13 ppt 2,100 in the Neuse and from 8-12 ppt in the :3 4. A Pamlico. Both estuaries had highest 0 CL 10 salinities in the fall and lowest salinities in the late winter. Nitrate nitrogen was z MP around 1 1LM in both the Neuse and Pamlico z 1 M% < during the summer, and 5-12 tkM in the z < winter (Figure 6.2b). February and March W 0.1 1 10 100 1000 median values were higher in the Pamlico, P04 INPUT (M MOL M 3 Y1 but November and December values were higher in the Neuse. Overall, there seems 100 to be no significant difference in the nitrate B between the two estuaries. Similarly, 0 a- 10 ammonia nitrogen was higher in the Neuse _j some months and in the Pamlico during z 0 a USE z 1 other months (Figure 6.2c), but there z E S appears to be no substantial difference W 0.1 overall. 1 10 100 Both estuaries, had highest orthophos- P04 LOADING (M MOL M phate phosphorus in the summer months (Figure 6.2d), and lowest values in the Figure 6.1. A. Mean annual concentrations of winter. The winter values were. similar for inorganicphosphorus (ILM) in several estuaries as aboth - around 1 /iM - but the Pamlico function of the estimated annual inputs of had higher summer phosphate than the phosphorus. P = Pamlico River estuary. B. Same as above except that inputs have been corrected for Neuse. The difference was nearly two-fold differences in flushing times (Redrawn fi-om Kgure for most months between June and Decem- 14 in Nixon 1983). The Pamlico River: Comparisons with Other Estuaries 93 ber. This difference probably reflects the Bay. The Pamlico average was 18 AM, influence of P loading from the Texasgulf about the same as the Patuxent River (TG) facility into the Pamlico. The more-or- Estuary, Chesapeake Bay, Potomac River, less constant TG loading ought to be most and North San Francisco Bay (Nixon 1983). noticeable in the low-flow periods (i.e., Nixon's plots of mean annual DIN concen- summer and fall) when Tar River P loading tration versus DIN input and loading is reduced. (Figure 6.3), prepared in the same manner Nixon (1983) also compiled data on as the DIP loading versus concentration annual cycles of inorganic nitrogen (DIN) plots described above, led him to conclude for a number of estuaries, including the that there is a linear relationship between Pamlico River. Two of his general conclu- nitrogen loadingand the average concentra- sions about DIN cycles apply to the Pamlico: tions observed in the estuaries. But the 1) nitrate is often more abundant than slope of a line drawn through this data ammonia during spring and fall in the would be less than one, indicating that DIN lower salinity systems, and 2) concentra- concentrations do not rise or fall in estuaries tions of nitrate appear highest in the upper in 1:1 proportion to changing loading. It portion of the estuaries. However, the appears that a doubling in the loading rate range in annual mean concentrations was ought to produce about a 50% increase in very large; from about 1 AM in Kaneohe mean concentration. Bay, Hawaii, to over 100 AM in Delaware 20- m 14 - = 12- B z a.15- NEUSE PAMLICO W10- NEUSE PAMLICO IL 0 0 8- M 6- X z -j 5- W 4- 2- Ir 0- 0- J F M A M J J A S 0 N D J F M A M J J A S 0 N D MONTH MONTH M12- =L C a D z a.10- W6- NEUSE PAMLICO W NEUSE PAMLICO 8 !R 8- 04 - 6- z <2- 0 4- 2 20- 0 0 K 2 J F M A M J J A S 0 *'N D cr J F M A M J J A S 0 N D MONTH 0 MONTH Figure6.2. Salinity, nitrogen andphosphorus in the Pamlico River and Neuse River estuaries, 1985-1986. Values are volume-weighted monthly medians. (A) Salinity (ppt), (B) Nitrate nitrogen (AM), (C)Ammonia nitrogen (AM), (D) orthophosphate phosphorus (AM). 94 Chapter 6 1000 A There continues to be much controversy Z and uncertainty surrounding the issue of 100 nutrient limitation in estuaries. Over the past two decades, the general consensus 10 has been that nitrogen is more likely than phosphorus to limit algal growth. Boynton l 10 100 1000 10000 et al. (1982) compiled data on N:P concen- DIN INPUT (M MOL M -3y trations and ratios from nearly 30 estuaries, including the Pamlico River (Figure 6.4). 1000 Here are their conclusions: B 100 'The data ... support the notion that nitrogen is consistently less abundant P 10 than phosphorus during periods of peak [algal] productivity in a wide variety of estuarine ecosystems. In 0.1 1 10 100 1000 most cases, those those that do not DIN LOADING (M MOL M .3 Y-1 follow this patternare heavilyenriched by point and diffuse nutrient sources Figure 6.3. A. Mean annual concentrations of throughout the year (e.g., HighVenice inorganic nitrogen (IM) in several estuaries as a Lagoon, Hudson River). On the right function ofthe estimated annual inputs ofnitrogen. side of [Figure 6.4], actual concentra- P = Pamlico River estuary. B. same as above except tions of DIN and DIP [orthophosphate that inputs have been corrected for differences in phosphorus] at the time of peak produc- flushing times (Redrawn from Figure 17 in Nixon 1983). Nitrogen Phosphorus Ratios ug-at 14 RIVER DOMINATED 0 10 20 30 40 N P PAMLICO RIVER, NORTH CAROLINA NARRAGANSETT BAY, RHODE ISLAND WESTERN WADDEN SEA, NETHERLANDS 1.5 120 3.0/ 2.0 EASTERN WADDEN SEA, NETHERLANDS 0.5 4.0/2.5 KID-PATUXENT RIVER. MARYLAND 4.2/2.3 LONG ISLAND SOUND. N.Y. LOWER SAN FRANCISCO BAY, CALIF. 20.6 / 3.8 BARATARIA BAY. LOUISIANA 4.6/0.8 UPPER SAN FRANCISCO BAY, CALIF. VICTORIA HARBOR, BRITISH COLUMBIA 1.5 MID-CHESAPEAKE BAY,MD. 0.5 20.6. UPPER PATUXENT RIVER, MARYLAND 1.12.0 HUDSON RIVER, NEW YORK 60.0 /3.0 APALACHICOLA BAY. FLORIDA ............. 61 5.0 /0.16 UPPER CHESAPEAKE BAY. NO. 240 10.0 /0.1 52 Figure6A. Seasonal mean DIN.DIP ratios from16 river-dominated estuarine ecosystems. Horizontalbar8 indicate the annual ranges in DIN.DIP ratios, solid triangles represent ratio at time of maximum productivity. Absolute concentrations (AM) at time ofpeak productivity are on the right. Vertical band represents the typical range of algal composition ratios (part of figure 5 in Boynton et al. 1982). The Pamlico River: Comparisons with Other Estuaries 95 tion are shown. Clearly, actual concen- estuary during the late spring, while N trations vary considerably between limitation is more significant at the mouth various estuaries and it is an open of the estuary during the summer. question whether these concentrations are limiting. However, nitrogen enrich- ment in estuarine areas often stimu- Dissolved oxygen lates algal growth, indicating that de- Chesapeake Bay was one of only two spite relatively high ambient concen- estuaries found to have serious low Do trations, nitrogen limitation of phyto- problems in a review of 14 systems by planktonic production can occur Nixon (1983) (the other was Mobile Bay). (Ryther and Dunstan 1971; Williams The low oxygen phenomenon has been 1972; Goldman et al. 1983; Thayer experienced for many years in the Chesa- 1974)" (Boynton et al. 1982, page 78). peake, he noted, and may be, in part at least, a natural feature of the system. The Some ecologists, after making detailed Bay's deep channel, lying between broad, studies of individual estuaries, have come shallow, very productive waters, maycollect to the conclusion that phytoplankton and concentrate much ofthe organic matter growth limitation shifts from N to P at fixed in the shallows. Nixon speculated different times of the year. There seems to that this enrichment, combined with a be a seasonal pattern in the shifts. For well-stratified water column, may cause example, Webb and Eldridge (1988) con- the anomalous low oxygen feature. In ducted experiments in the lowerYork River Mobile Bay, the deep channel (Mobile Ship that showed the phytoplankton were P Channel) is well oxygenated and the low limited in the late fall and winter, and N oxygen water is spread out over shallows limited in the late spring and summer, that have been isolated from much of the They speculated that seasonal shifts in p tidal circulation by shoals and dredge spoil and N inputs to the estuary were the most (Nixon 1983). likely cause of the shift. In the York River, I recently attempted an assessment of P shows maximum concentrations in sum- dissolved oxygen conditions in the twenty- mer and the minimum in winter; the major three estuaries in North Carolina, South input ofN is nitrate from wintertime runoff. Carolina, and Georgia for which some data Recall that this is the same as the pattern were available (Stanley 1985). One con- for the Pamlico River (see Chapter 4). clusion from this review was that none of These results parallel those from stud- these estuaries suffer from extended, ies in a low salinity portion of the Chesa- widely-ranginghypoxia. Rather, the events peake Bay system (D'Elia et al. 1986), and appear to be of short duration and do not inotherareas ofthebay (Fisheretal. 1988-, appear to have a serious impact on the Malone 1988; Love et al. 1988). Despite estuaries, although benthic fauna are extreme nutrient enrichment in the head- affected temporarily. Lack of long-term waters of the Delaware estuary, phyto- monitoringdata for all these systems except plankton productivity in the middle and the Pamlico River makes it impossible to lower estuary alternates between light, determine exactly how much impact cul- phosphorus and nitrogen limitation over tural eutrophication has had on the oxygen the seasonal cycle, according to (Pennock conditions. and Sharp 1988). It is also their view th--'- Turner et al. (1987) showed that oxygen these factors var*y spatially over the salinity depletion in the bottom waters of Mobile gradient. In general, Delaware Bay P Bay is caused by the same factors operating limitation is most prominent in the mid- in the Pamlico River. They found that 96 Chapter 6 hypoxia was directly related to the intensity their new findings as follows: of water column stratification, which, in turn, was coincidental with low wind "Analysis of the complete data base on speeds. More than 80% of the variation in measurements of dissolved oxygen in DO content in their samples was explained the Chesapeake Bay for the period by variations in the vertical salinity 1950-1985 results in two conclusions: gradient. a) there has been no statistically significant pattern of increase in An analysis showing a trend toward summer anoxia of bay waters over the worsening dissolved oxygen conditions in past 36 years, and b) annual the bottom waters of Chesapeake Bay has stream flow-induced stratification is the been widely publicized (e.g., Officer et al. controlling factor in the annual volume 1984), but the study conclusions have been of summer anoxic waters in the bay, at questioned by other bay-area scientists greater than the 99.99% confidence (Seliger and Boggs 1988) who have re- level. These conclusions are in sharp examined the data. They summarized contrast with those of an EPA-funded 5-year study of the bay and with those Chlorophyll a, Mg m-3 0 65 10 15 20 2-5 1 1 1 1 MEYERS CREEK. MEW JERSEY SP Su GULF OF ST. LAWRENCE , CANADA W Sp FRASER RIVER. BRITISH COLUMBIA W SU STRAIT OF GEORGIA, BRITISH COLUMBIA W SU VICTORIA HARBOR, BRITISH COLUMBIA W- Su HUDSON RIVER, NEW YORK W Su ALTAMAHA RIVER MOUTH, GEORGIA W MID-ALTAMAHA RIVER, GEORGIA W Su WACCASASSA RIVER. FLORIDA BURRARD INLET, BRITISH COLUMBIA W,F Sp YTHAN ESTUARY, SCOTLAND Sp 0 Su APALACHICOLA BAY, FLORIDA F S P DUWANISH RIVER, WASHINGTON W Su LONG ISLAND SOUND, N.Y. W Su NARRAGANSETT BAY. R.I. W, F Sp MID-CHESAPEAKE BAY, NO. W F COLUMBIA RIVER, WASH. W Su WESTERN WADDEN SEA. NETHERLANDS W W.-Su EASTERN WADOEN SEA, NETHERLANDS BARATARIA BAY. LOUISIANA F 66 W. Sp UPPER CHESAPEAKE BAY. NO. a Suq, F MID-PATUXENT RIVER, NO. 38 Su LOWER PAMLICO RIVER. N.C. Su. F W. Sp RARITAN BAY, N.J. W 12& 45 Su UPPER PATUXENT RIVER. NO. W Su Figure 6.5. Summary ofchlorophyll aconcentrations in 25 estuaries. Annual ranges and Seasons in which maximum and minimum concentrations occurred are indicated. Solid triangle indicates chlorophyll a concentration at time of maximum productivity (part of Figure 4 in Boynton et al. 1982). The Pamlico River: Comparisons with Other Estuaries 97 of a major review of anoxia published any evidence for increased summer in Science [Officer et al. 19841, namely anoxia since the 1950s, the scientific that anoxia in the bay has increased basis of this program should be re- by a factor of 15 since 1950 and that evaluated" benthic respiration, rather than strati- (Seliger and Boggs 1988). fication, has been the controlling factor in this 15fold increase in anoxia. This Chlorophyll a and apparent increase in anoxia has been Phytoplankton Biomass attributed to increased nutrients and has been assumed to be a major factor In his comparative estuarine study, in the decline of fish and shellfish Nixon (1983) also presented data on the species in the bay. A federal and standing crop of phytoplankton, as esti- multi-state program for restoring the mated by chlorophyll a. The estimated bay biota is based on reversing this 15- annual mean for the Pamlico River was fold increase in anoxia by reducing about 16 ug/liter. For all the estuaries, the nutrients in the bay. In the absence of range was from about 2 jig/liter in Kaneohe Phytoplankton Production, g C m-2 d (net) 0 0.5 1.0 1.5 2.0 2.5 W SU I I I I I ST. LAWRENCE RIVER, CANADA W Su UPPER SAN FRANCISCO BAY, CALIF. W-. SU FRASER RIVER, BRITISH COLUMBIA 2qo UPPER PATUXENT RIVER, MD. w -su STRAIT OF GEORGIA. BRITISH COLUMBIA W Su WESTERN WADDEN SEA, NETHERLANDS W Su SWARTVLEI, SOUTH AFRICA Sp WACCASASSA RIVER, FLORIDA W a SU EASTERN WADDEN SEA, NETHERLANDS W 0 SU MEYERS CREEK, NEW JERSEY SPSu UPPER CHESAPEAKE BAY, NO. W. SP6 Su HUDSON RIVER, NEW YORK W Su LONG ISLAND SOUND. NY , Su DUMANISH RIVER, WASH. W Su COCHIN BACKWATER, INDIA W S P BARATARIA BAY, LOUISIANA W SU LOWER SAN FRANC1SCO DAY, CALIF. W sis, r mio-PATXUEANT RIVER. MD. W SU RARITAN BAY, NEW JERSEY Su NARRAGANSETT DAY. RHODE ISLAND W 4 BURRARD INLET. BR1T1SH COLUMBIA W Sp APALACHICOLA BAY, FLORIDA W-SP MID-CHESAPEAKE BAY. RD. W F PAMLICO RIVER, NORTH CAROLINA F Su W SU ALTAMAHA RIVER MOUTH, GEORGIA Figure6.6. Summary of average daily phytoplanktonproduction rates (solid dot) in 25 estuarine systems. Horizontal bars indicate annual ranges. Season in which maximum and minimum rates occurred is also indicated W, winter, Sp, spring, Su, summer, F, fall) (part of Figure 3 in Boynton etal. 1982). 98 Chapter 6 Bay, Hawaii, to almost 20 jig/liter for the 10 _J A Patuxent River estuary. A winter-spring P bloom was found to occur in a number of the estuaries, including the Pamlico, of z 10 z course, but was inconspicuous or absent in z others. Some estuaries had strong mid- summer blooms. 0.1 1 10 100 1000 Boynton et al. (1982) also presented DIN LOADING (M MOL M -3 comparative data on chlorophyll a and average daily primary production rates in < 10 thePamlico Riverand in 44 other estuarine _J B systems (Figures 6.5 and 6.6). The Pamlico P % data used in this comparison were from the z 10 early-to-mid 1970s. In terms ofboth chloro- z < phyll a and primary productivity, the z Pamlico ranked as one of the highest of the river-dominated estuaries included in the 0.01 0.1 1 10 100 comparison. However, there is so much P04 LOADING (M MOL M overlap amongthe top third of the systems, Figure 6.7. Mean annual chlorophyll a as a that real differences, if they exist, are function oftheestimatedannual loadingofdissolved obscured. These plots also cannot take into inorganic nitrogen (top) and dissolved inorganic account the considerable year-to-year vari- phosphorus (bottom). P = Pamlico River. The ability in algal biomass and productivity regression line relating mean annual chi a in lakes within each estuary, so that individual toPloading is from Schindler (1978) (redrawnfi-om Figure 20 in Nixon 1983). rankings are impossible. The authors of this paper drew no conclusions regarding the order of the rankings, such as effects of nutrient loading, hydrography, or climate. _40- One of the most interesting of all the ;:z comparisons in the Nixon study described ca = 30- NEUSE PAMLICO above was between nutrient loading and to chlorophyll a (Figure 6.7). The results were _J described as follows: -J20- I have made a preliminary 010- . . . . . . . . . . . . attempt to relate the annual mean chl 0 a averaged over each estuary to the input of inorganic nitrogen and phos- J F M A M J J A S 0 N D MONTH phorus... The results are not without scatter, but as abeginningl thinkthey are impressive enough to merit Figure6.8. Chlorophyll a in the Pamlico River and attention and further effort.... The Neuse River estuaries, 1986. Values plotted are response of estuarine phytoplankton volume-weighted monthly medians. may not be as dramatic as that of lakes. While nitrogen and phosphorus loadings increased 2000 times from Kaneohe Bay to the most heavily enriched MERL microcosm, the annual standing crop of chl a only increased The Pamlico River: Comparisons with Other Estuaries 99 Table 6.1. Summary ofphytoplankton data fi-om several east coast estuaries. BAC = Bacillariophyceae (diatoms), CHL Chlorophyceae, CYA = Cyanophyceae, CHR = Chrysophyceae, and DIN = Dinophyceae. S =total number ofspecies found;- D =average cell density (cells 1"), andB =averagebiomass (mgwetmass 1-1). South Creek, S: 146 47 17 2 7 10 21 0-10 This Study D: 3.9 x 1(r 14 11 6 61 6 2 B: 1.60 14 14 <1 16 51 4 South Creek, D: 52.7 x 106 <15 Hobbie (1971) B: 9.11 Pamlico River, S: 173 50 18 3 6 8 15 0-20 Stanley and Daniel (1985) D: 4.2 x 106 3 14 <1 59 20 3 B: 3.37 3 7 <1 8 80 1 Gales Creek, NC, S: 339 55 7 - 5 22 11 Campbell (1973) Cape Fear River, NC S: 203 66 12 4 1 7 10 11-15 Carpenter (1971) Chowan River, NC B: 5.61 20 11 22 1 29 17 0 Stanley and Hobbie (1981) Neuse River, NC S: 297 23 37 14 9 4 13 0-10 Stanley (unpublished) D: 12.5 x 100 12 16 63 3 <1 5 B: 3.48 15 34 2 6 17 26 Currituck Sound, NC, S: 204 Tyndall (1980) D: 6.6 x 106 B: 0.48 13 20 22 5 17 22 Chesapeake Bay, S: 149 49 13 2 6 17 13 5-20 Van Valkenburg et al. (1978) D: 10 x 106 21 21 10 18 10 20 B: 3.97 28 <1 <1 6 56 8 Chesapeake Bay, S: 219 59 1 4 4 19 13 >20 Old Plantation Creek, Marshall (1980) James River Estuary, S: 74 70 9 1 0 11 9 >15 Marshall (1967) D: 1.3 x 106 Narragansett Bay, S:75 57 2 0 3 19 19 28-30 Smayda (1957) D: 6.7 x 106 94 6 100 Chapter 6 about 30-fold. The consequences of studies were nonquantitative, emphasiz- such an increase may still be pro- ing systematics, rather than cell counts, or found, of course, and evidence of an had used preservation techniques (e.g., apparently linear response to nutrient formalin solutions) that destroy the micro- input confirms the importance of flagellates which make up so much of the eutrophication as a concern in estu- arine management. Since maximum total phytoplankton biomass in estuaries. chl a levels increase with increasing Hobbie was able to compare his results average values ... it follows that more with those from a study by Patten et al. intense blooms are part ofthe response (1963) of the phytoplankton in the York to increased nutrient input. These River estuary, and he concluded that the blooms, more than the average yearly cycles in these two systems were standing crops, may have the greatest similar. Both rivers had mostly flagellates impact on estuarine water quality" upriver and more diatoms toward the (Nixon 1983, page 25-26). mouth. Also, both had blooms of the Of course, individual estuaries like the dinoflagellateHeterocapsatriquetra (called Peridinium t7iquetrum inthe Hobbie [19711 Pamlico are unlikely to experience changes in nutrient loading as great as the range report) in late winter and early spring. among these estuaries. Figure 6.7 shows Although he gave no details, Hobbie com- that the rates of change of chlorophyll a mented that "the rest of the algae species found in the Pamlico Riverestuaryare also with increasingN and P loadingare actually found in Chesapeake Bay and farther quite small. This suggests that if N or P north" (Hobbie 1971, page 30). loading in the Pamlico were to decrease by By 1985, quantitative phytoplankton 50%, the chlorophyll might be expected to studies had been made for several east decline by only about 10%. coast estuaries. Stanley and Daniel (1985b) Chlorophyll a concentrations in the compiled the results from these for com- Pamlico were similar to those in the Neuse parison with their more recent Pamlico River estuary in 1985 and 1986, despite survey (Table 6. 1). They discussed several the higher phosphorus levels in the Pamlico similarities between the Pamlico phyto- (Figure 6.8). The volume-weighted monthly plankton pattern and those from the other median chlorophyll a's were highest in estuaries. First, the Pamlico species com- both estuaries in the summer months and position, as reflected in the percentages of lowest in the winter months. Fifteen to species in each algal class, was similar to twenty-five jig/liter values were typical those for most other estuaries included in during the summer, while the winter con- the comparison. Generally, diatoms (class centrations were generally 8 4g/liter or Bacillariophyceae) was the most diverse less. Summer chlorophyll a values seemed group, followed by the Chlorophyceae to be slightly higher in the Neuse, although (green algae) and Dinophyceae (dino- the difference is probably not statistically flagellates). Together, these three groups significant. It should be noted that data usually comprised 75% or more of the total from the lower Neuse River, where blue- species. green algal blooms occur, were not used in Another similarity was that chryso- these comparisons. phytes and dinoflagellates appear to be At the time of Hobbie's 1971 Pamlico predominant in terms of average cell den- study, there had been very few studies sity and biomass. In addition, the average published of phytoplankton species com- wet weight biomass and density did not position and biomass along the south- range widely among those estuaries for eastern U.S. coast. Most of the earlier The Pamlico River: Comparisons with Other Estuaries 101 which estimates were available. Biomass most other estuaries. The overall similari- averaged 3.37 mg/liter in the Pamlico, 5.61 ties in patterns of algal abundance in estu- mg/liter in the lower Chowan River, 3.48 aries of this region are striking, given the mg/liter in the lower Neuse River, 3.97 mg/ great seasonal and spatial variability with- liter in Chesapeake Bay, and 0.48 mg/liter in each of the estuaries. In fact, it appears in Currituck Sound. from this comparison that average algal Finally, the microflagellates have been abundance in the estuaries of this region is found to contribute heavily to the total much less variable than the seasonal and algal biomass in the Pamlico (Stanley and spatial variation within any one of the Daniel 1985), in Chesapeake Bay (Van systems. Valkenburg et al. 1978), and probably in CHAPTER7 Trends in the Sounds' Fisheries TheAlbemarle-Pamlico system has sup- The fish, oyster and game problem of North ported commercial fisheries for over a Carolina demands serious attention and century, but as the newspaper editorial vigorous remedies for their restoration. excerpt (at right) suggests, there were We hang our heads in shame when problems for the industry almost from its Wilmington restauranteurs advertise beginning. This editorial was prompted by Norfolk oysters, while the once famous a fisheries convention held at Wilmington, New River oyster has practically NC in December 1911 "to take some action disappearedfrom the market Instead of in regard to the great depletion of the robbing our rivers and bays and sounds of fishingindustries in the State" (Pratt 1912). their fish and oysters, we should be Politicians, fisheries "experts" and local conserving theM taking plenty and leaving fishermen participated in the convention. plenty to increase the supply. But like Many hypotheses were raised to explain many other matters that have to be solved the demise of the fisheries, and the by our law-making bodies, it is hard to get discussion was intense - at times heated; an application of common sense. but little concrete evidence was available Wilmington Star (1911) to substantiate most of the claims and counterclaims. However, the convention commercial species are reported by county, was followed by some new state regulations and annual totals are published in the intended to "protect and perpetuate" the North CarolinaLandings series. Chestnut fishing industry. and Davis (1975) compiled the data from This scenario has, of course, been the annual reports for the 1880-1973 pe- repeated many times since, as North riod in their Synopsis of Marine Fisheries Carolina and other coastal states have in North Carolina. I used the data in that struggled to balance diverse, often synopsis, along with statistics for more competing, interests in various schemes to recentyears in theAnnual Summary (1974- manage the commercial and recreational 1979) or monthly reports (1980-1987) of fisheries in our nations estuaries. North Carolina landings published jointly by the North Carolina Division of Marine Commercial Fisheries Fisheries and the U.S. National Marine The Database Fisheries Service (National Marine Fish- The first comprehensive statistical sur- eries Service 1974-1979; North Carolina vey for North Carolina was made in 1880 Division of Marine Fisheries 1980-1987). ' Only the data from counties in the N.C. and partial or complete surveys have been made at varying intervals since then. Com- Division of Marine Fisheries Central and plete statistics are available for the years: Northern Districts were tallied to give the 1880, 1887-1890, 1897, 1902, 1908, 1918, totals reported in this study. These dis- 1923, 1927-1932, 1934, 1936-1940, 1945, tricts include all the coastal counties from and 1950 to date. Monthly landings ofeach Carteret northward (Chestnut and Davis 104 Chapter 7 1975). analysis of the status and trends of the The usual limitations of commercial Albemarle-Pamlico commercial and recre- landings statistics should be kept in mind. ational fisheries was made by Hogarth et First, and most important, they measure al. (1989). the quantity of fish landed, which is not necessarily a good indicator of the abun- Edible Finfish dance of the species. One reason for this The development of commercial discrepancy is that fishing"effort" is gener- fisheries in the Albemarle-Pamlico region, ally not taken into account. Effort fluctu- especially along the Outer Banks, was ates in response to changes in demand (i.e., retarded in the 1800s by the difficulty of price per pound) for the species, fishery delivering seafoods, while they were fresh, technology, the cost of fishing (e.g., fuel from these remote areas to the inland prices), weather, and restrictions imposed consumers. Consequently, the earliest by state and federal agencies. Second, the fisheries were engaged in catching those fact that fish are landed in a particular types of fish which could be preserved for county does not necessarily mean that later sale. Thus, the first commercial they were caught in nearby waters. Even fisheries up the rivers and sounds worse, no distinction is made in the sum- concentrated on such species as alewives mary landings reports between fish caught (herring) and shad, which could be smoked in the sounds and those caught offshore in orsaltedwithoutlos ing their flavor. These the Atlantic Ocean. Finally, the older data anadromous species were caught in large are somewhat suspect because there prob- numbers during their annual spawning ably was underreporting and because dif- migrations with seines operated from the ferent species in the same group were not mainland along the shores of Albemarle always tallied separately (Chestnut and Sound and the Chowan River. These Davis 1975). fisheries, along with whaling, were the A good description ofthe biology ofeach limit ofcommercial fishingalongthe North of the major commercial species and some Carolina coast until the mid-1800s (Stick analyses of trends in the North Carolina 1958; Godwin et al. 1971). commercial landings up through the mid- Commercial fishing really began on a 1940s were made by the following con- large scale in North Carolina following the tributors to the Study of Marine Fisheries Civil War, as coastal residents came to in North Carolina (Taylor 1951): E.W. recognize the potential income represented Roelofs (for edible finfishes), A.F. Chestnut by the seafood in the nearby waters. Seine (oysters), C. Broad (shrimp), J.C. Pearson fishing spread, and by the 1870s, shad (blue crabs), and WA. Ellison, Jr. (menha- fisheries were operating around Roanoke den). Later reviews of the catch data can Island and in Pamlico Sound. An important be found in reports by Godwin et al. (1971) mullet fishery developed in Core Sound at and the North Carolina Division of Marine about the same time. The catch was salted Fisheries (1984). David Stick's (1958) book, and taken to Morehead City where it could entitled The Outer Banks of North Caro- be shipped out by train (Stick 1958). Pound lina, contains a chapter on the history of nets were introduced about 1869 and, along fisheries along the North Carolina coast, with gill nets, proved so efficient that most with interesting details gleaned from a of the Albemarle haul-seines gradually review of the late nineteenth century went out of business. During the late printed material and from interviews with 1800s and early 19008, extensive fisheries residents of the area. The most recent developed for sturgeon near some of the Trends In the Sound's FIsheries .105 inlets. But this lasted only a few years Albemarle-Pamlico edible finfish harvest, before sturgeon became scarce (Stick 1958; but the fishery has been characterized by Godwin et al. 1971). tremendous year-to-year variations. For Improvements in transportation were example, the highest landings on record very slow in coming to this area, so that occurred in 1969, but a sharp drop (about around the turn of the century, when statistics began to be kept on the commercial fisheries, the most important 25- ones were still alewives and shad, along ALEWIFE with the sound and beach mullet fishery. U) 20 - Between 1887 and 1900, these three z 15- accounted for about two-thirds of the total 3 0- edible finfish harvest (Figures 7.1-7.3). It Z10- was not until after World War II that 0 extensive ocean trawling began for species -3 such as flounder (Godwin et al. 1971). 0 Up until the early 1970s, alewives, or 1885 1905 1925 1945 1965 1985 "river herring," continued to be the single YEAR most important component of the 2.5- CATFISH & BULLHEADS 2- z 100- EDIBLE FINFISH 80- z 1- z 0 :) 60- -J 0.5 0 _j IL Z 41D - 01 0 1885 1905 1925 1945 1965 1985 -J 20- YEAR 0- 1885 1905 1925 1945 1965 1985 10- YEAR 8- AMERICAN SHAD 50 z D 6- SHELLFISH 0 840. CL z Z 4 030- 0 fl@ -J 2- Z20- 0 0 _j _J10- 1885 1905 1925 1945 1965 1985 YEAR 0 1885 1905 1925 1945 1965 1985 YEAR Figure 7.2. Trends in anadromous species landings in the Albemarle-Pamlico Sound Figure 7.1. Trends in total edible finfish and system. "Alewife" includes alewives (Alo8a pseudoharengus) and blueback herring (Aloaa shellfish commercial landings in the aeetivalis). Another common name for the Albemarle-Pamlico Sound system. Data group is "river herring." Data are from sources sources are given in text. given in text. 106 Chapter 7 20 _20 GREY SEATROUT FLOUNDER 15 15 l0 10 5 5 0 0 1885 1910 1935 1960 1985 1885 1910 1935 1960 1985 YEAR YEAR 25 7 CROAKER 20 6 BLUEFISH 5 15 4 3 10 2 5- 1 0 0 1885 1910 1935 1960 1985 1885 1910 1935 1960 1985 YEAR YEAR 10 SPOT 4 MULLET 8 3 6- 2 4 1 2 0 0 1885 1910 1935 1960 1985 1885 1910 1935 1960 1985 YEAR YEAR Figure 7.3. Trends in annual landings of the major types of edible finishes in the Albemarle- Pamlico Sound system. Data are from sources given in text. 50%) occurred the following year (Figure catch (Godwin et al. 1971). However, the 7.2). The fishery declined to around 7 report went on to say that "the failure of million pounds per year in the mid-1970s the fisheryto recoversince thereduction of and has fluctuated around that level since, foreign fishing is probably related to poor although an all-time low was reached in water quality in the Chowan River and 1987. ADivision ofMarine Fisheries report Albemarle Sound." No specific hypotheses in 1984 attributed at least the initial decline linking water quality to the fishery were to increases in offshore landings by foreign mentioned. vessels, which apparently led to later Around 1900, six-to-eight million agreements with the foreign governments pounds of shad (primarily American shad) involved to reduce their offshore herring were caught in the Albemarle region each Trends in the Sound's Fisheries 107 year, but during the first half of this cen- Besides the increased fishing pressure, tury, the fishery declined precipitously in there may be other factors involved in the North Carolina, and in other states along striped bass decline. ManoochandRulifson the Atlantic seaboard. Since that time, the (1989) used results from long-term studies fishery has not recovered, and during the ofstriped bass reproduction in the Roanoke last decade has lingered around 0.2 to 0.5 River to develop a hypothesis linking river million pounds per year (Figure 7.2). Due flow and the survival ofyoungstriped bass. to the drastic decline of this species, it was Theiranalyses are based primarily on data studied extensively in the 1950s and 1960s. collected each year since 1956 by a North Walburgand Nichols (1967) cited the three Carolina State University researcher, W.W. factors which are so frequently mentioned Hassler. The followingdescription oftrends in discussions of fishery declines: 1) habi- in those data is excerpted from the Manooch tat destruction, 2) pollution, and 3) over- and Rulifson report: fishing. Dams on some of the rivers have prevented the shad from reaching their "Although no apparent trends were natural spawning grounds and eliminated detected in the total striped bass egg many miles of nursery areas. Pollution, production in the river, the viability particularly that which lowers dissolved rate of those eggs declined drastically oxygen levels in the water, are thought to beginning in the mid-1970s. Egg viability ranged from 80% to 96% from be harmful, particularly forjuvenile shad. 1960 through 1974, but declined to Paper mills located on the lower reaches of 56% in 1975 and ranged from 23% to the Chowan, Roanoke and Neuse rivers in 74% in the succeeding years through North Carolina produce high oxygen-de- 1987 (Figure 7.5). In the past, the manding organic wastes (i.e., BOD) which Roanoke/Albemarle striped bass popu- may have contributed significantly to this lation has been supported by dominant problem, particularly in the past when yearclasses produced at approximately there was little treatment to remove the 5-year intervals. A dominant year BOD. Finally, Walburgand Nichols (1967) class, indicated by a juvenile concluded that fishing pressure has been abundance index of at least 10 young- of-year fish per trawl tow, has notbeen an important factor in shad abundance, produced since 1976 (Figure 7.5). The but up until at least 1971, there were no estimated number of striped bass in laws or regulations in North Carolina which the spawning migration remained specifically applied to the management of within historical levels through the the shad fishery (Godwin et al. 1971). mid-1970s, but in 1980, that number After an apparent decline in the early also declined. Since 1981, the 1900S catches ofstriped bass rose gradually estimated spawning population has between 1920 and the mid 1960s (Figure remained below 100 thousand fish." 7.4). Then, beginningin 1967, striped bass The authors of this report go on to were caught by ocean trawlers fishing off discuss several aspects of the life cycle of the northern Outer Banks. The landings striped bass which are affected by river quadrupled, from one-half million pounds flow. They conclude that the construction to 2 million pounds, and remained high for ofsix upstream dams on the Roanoke River several years. Then, after a record catch of in the 1950s and 1960s, and the resulting 2.3 million pounds in 1970, the landings water flow regulation, has had a negative began a decline that was not halted until impact on the striped bass. Finally, the the early 1980s, but by then the catches report makes recommendations to the U.S. were at historic lows of 100-200 thousand Army Corps of Engineers and the electric pounds. 108 Chapter 7 2.5- 6- - LANDINGS EGGSSPAWNED V) 5- z 2- 0 4- 1.5- Z3- 0 -J2- z 0.5 n 0 0 01 CL 1885 1910 1935 1960 1985 1956 1964 1972 1980 1988 YEAR YEAR 80- 100- RECREAT10NAL CATCH 80- 60- U_ 0 60- U)40- z W 0 40- z cc @20- Uj 20- EGG VIABILITY 0 0. 0- 1956 1964 1972 1980 1988 1956 1964 1972 1980 1988 YEAR YEAR 0.6- 30- 0.5- SPAWNERS JUVENILE ABUNDANCE INDEX 0.4 - 20- U_ 00.3- CO z 0.2- 0 :3 0.1 - 01 1956 1964 1972 1980 1988 1956 1964 1972 1980 1988 YEAR YEAR Figure 7.4. Trends in Albemarle-Pamlico Figure 7.5. Trends in eggs spawned, egg region commercial catch of striped bass, and viability, andjuvenile abundance indexfor the Roanoke River recreationalcatch, andnumbers Roanoke River striped bass population. Data of spawning striped bass. Commercial catch are from Mannoch and Rulifson (1989). data arefrom sourcesgiven in text. Recreational catch and spawningpopulation data are from Mannoch and Rulifson (1989). Trends in the Sound's Fisheries 109 power company, who operate the dams. In order to increase striped bass reproductive "Blue crabs are very abundant on this success, discharges from the reservoirs coast, but they are not much in demand should be regulated during the spawning as food. Above Morehead City and period so that flow in the lower Roanoke is Beaufort, the fishermen take them in immense numbers in their drag-nets kept as close as possible to the average while fishing for sea-trout, mullet and rate, for that time of year, that existed other fish, and consider them a great before the dams were built (Manooch and annoyance, as it is difficult to remove Rulifson 1989). them from the nets. They kill nearly The declines in anadromous species all that are captured in this way by a landings have been more than offset since blow from a stick carried along for the 1960 by dramatic increases in catches of purpose, and then throw them away, five edible marine finfishes: grey seatrout, or use them as manure. A few are kept flounder, croaker, bluefish and spot. Trends for food, but none are sold, beyond an in landings of these five have been very occasional barrel-full, mostly soft- similar. They all increased rapidly in the shelled, which are sent to some of the 1970s, peaked around 1980, and have fallen larger inland towns." back somewhat since then (Figure 7.3). In the 1930s, the crab industry began The North Carolina Division of Marine to grow, partly because of new crabbing Fisheries has monitoredjuvenile fish abun- methods, but mainly because of an dance within the Albemarle-Pamlico sys- increasing demand for imported crabmeat tem since 1979. The data are used to in northern markets. Pearson (1951) generate year-class strengths for four fin- described the close inverse relationship fish species: Atlantic croaker, spot, south- that existed in the 1930s and 1940s between ern flounder, and weakfish (grey sea trout). crab harvests in North Carolina and the No significant trends for any of these speies Chesapeake Bay. In years when the abun- are indicated between 1979 and 1988. dance of crabs in Chesapeake Bay was Years of relatively high abundance were insufficient to satisfy the markets, more 1982 and 1986 for southern flounder, 1981 North Carolina crabs were harvested and and 1986 for weakf ish, and 1983 for Atlan- exported to markets in the Chesapeake tic croaker. The absence of downward region. This led to the beliefby some North trends indicates that any stress on these Carolina fishermen that a high natural species (such as overfishing) is not great abundance of crabs in one region was enough to cause a decline in relative juve- accompanied by a low abundance in the nile production. Fluctuations are most other and vice versa. likely due to yearly variations in environ- The rapid increase in North Carolina mental parameters, such as temperature, crab landings after 1950 (Figure 7.6) was salinity, weather patterns, and/or currents- undoubtedly due in part to decreased These factors all affect larval transport dependence on the Chesapeake markets. and survival (Hogarth, et al. 1989). At the same time, more and more processing Blue Crabs factories were beingbuilt in North Carolina. Prior to 1930, there were no more than half There was a minor blue crab fishery in a dozen crab-picking plants in the state. North Carolina as early as the 1880s and Although a crab meat canning industry 1890s, but the demand was apparently had been established in Beaufort in 1943, much smaller than the catch, as indicated by 1946, there were still only 16 crab in this 1887 report by Rathbun: houses in the state, compared to over 100 110 Chapter 7 on Chesapeake Bay (Pearson 195 1). How- who fished for spot, croaker and butterfish ever, in the late 1960s, several factories, in Pamlico Sound (Earll 1887). But later each employing hundreds ofworkers, were the demand began to increase gradually. built along the western shores of Pamlico Between 1912 and 1915, Federal Bureau Sound (Godwin et al. 1971), and by 1984, of Fisheries personnel at Beaufort used an there were more than 25 processing plants otter trawl to collect specimens for their in the area (North Carolina Division of research. North Carolina fishermen Marine Fisheries 1984). adapted and modified this gear and the After reaching historic highs of around shrimp fishery began to grow rapidly 20 million pounds in 1964 the landings (Figure 7.6). The landings increased to an declined nearly 50% by 1968, presumably all-time peak of 13 million pounds in 1953 due to mass mortalities of blue crabs that (Godwin et al. 1971). occurred from North Carolina to Florida. 'Destruction of the estuarine habitat of An emergency investigation was authorized young shrimp" was mentioned by Godwin to find the cause, but by the time the study et al. (1971) as the probable cause of the finally began, the mortalities were over decline in shrimp harvests after 1953, but and landings had returned to their former no details were given. There has been no levels. The study showed the presence of obvious trend in the shrimp landings since several pesticides and disease organisms 1960, but often they have fluctuated widely in blue crabs, but failed to make any from one year to the next (Figure 7.6). conclusions concerning possible causes for Such variations are to be expected in a the mortalities (Godwin et al. 1971). fishery based on an annual crop which is After 1969, the crab harvest again greatly dependent on environmental declined for several years, to a low of 11 conditions duringthe critical growth period million pounds in 1975. Briefnotes included (North Carolina Division of Marine in the Annual Summaries of landings Fisheries 1984). Salinity and temperature during that period included suggestions are two variables widely thought to have that since demand was good and prices great influence on the annual harvests. were high, "only a general scarcity of crabs Although no statistical analysis appears to could account for the decline in landings" have been made between these factors and (National Marine Fisheries Service 1974). the shrimp landings, they are frequently But in a few years, the annual catches mentioned in discussions of fluctuations in began a steep rise again, so that by 1980, the annual catches. For example, the low they were higher than ever - nearly 35 catches in 1978, 1981 and 1984 were million pounds. Landings for all years in attributed to unusually cold winters and this decade except one have been above 25 heavy springrains (North Carolina Division million pounds (Figure 7.6), making crabs of Marine Fisheries 1984; National Marine the single most important component of Fisheries Service 1978, 1981). the North Carolina commercial fishery, in terms of pounds harvested. Oysters Before the Civil War, shellfish such as Shrimp the oyster were more important as an Shrimp, like blue crabs, have shown a industry in the northeastern states than in remarkable growth in popularity as a choice the southern states primarily because of seafood since the early part of this century. better railroad systems, but in the late In the 1880s, shrimp were also regarded as 1800s, it became an even bigger industry "trash," and thrown away by haul-seiners in the north due to a new steam canning Trends In the Sound's Fisheries 40 14- 35- BLUE CRABS SHRIMP 212- Z 30- z 025- :110- (L 0 LL 20- CL 8- 0 LL 15. 0 6- U) (0 z 10- Z 4- 0 0 2- 0 1885 1910 1935 1960 1985 2 0- YEAR 1885 1910 1935 1960 1985 YEAR 1.2 8- Cn HARD CLAMS (MEAT) U) 0 1- 07- OYSTERS (MEAT) z z :)6- 0.8- 0 0 IL5- IL U. 0.6 - U.4- 0 0 rn 0.4 - co3- z z 02- C) 0.2 - :1 0 20- _J 1885 1910 1935 1960 1985 1885 1910 1935 1960 1985 YEAR YEAR 2- 3.5- BAY SCALLOPS (MEAT) OTHER SHELLFISH z 3- n z 0 :) 2.5- 0 CL 2- U.1 - U_ 0 01.5- co z U) 0 z .J 0 _J 2 0 0. 1885 1910 1935 1960 1985 1885 1910 1935 1960 1985 YEAR YEAR Figure 7.6. Trends in annual landings of the major types ofshellfish in the Albemarle-Pamlico Sound region (N.C. Dividion of Marine Fisheries "Central and Northern Districts"). Shrimp landing pounds are "heads on. " Data sources are given in text. process for oysters, the expanded railroad were located in New Bern, Beaufort, systems to carry them to markets, and a Washington, and other small cities in the booming postwar economy which allowed region. The most important beds were in more people to buy products like oysters. It the vicinity of Ocracoke Inlet (Winslow was not long before the supply was 1889). The late 18808 scarcity of oysters in exhausted in estuaries such as the the Chesapeake Bay region had an Chesapeake Bay, and new sources ofoysters important impact on oyster production in were needed. North Carolina; experienced Chesapeake Before about 1890, Oysters were oystermen and their dredging fleet moved harvested in North Carolina only to supply into North Carolina waters. The influx of local markets. In the 18808, these markets these oystermen, with their more efficient 112 Chapter 7 dredging and tonging methods used in cluded that the reason for the decline was Maryland and Virginia, led to sudden "close and indiscriminate dredging in the increased production for North Carolina, past two seasons." coinciding with the decline in Maryland In the 1880s, conservation groups, (Chestnut 1951). North Carolina scientists and concerned citizens were oystermen complained bitterly: becoming aware that certain fisheries were declining. The American Fisheries Society, "The people here are poor and depend founded in 1870, was one of the first groups entirely upon the waters for support. to call for government action, and in 1872, But the Virginia men are down here the federal government created the United and have taken entire possession ofall States Fish Commission to investigate the oyster grounds; their boats are fishery problems. North Carolina, like much largerthan those here, and when these are at work the Virginians will other states, was prompted to follow the run down upon them and tear them federal government's example, and in 1887, up; and when they try to retaliate it is formed its first shell-fish commission to useless, for they are armed to the teeth examine local fishery problems much of with Winchester rifles and some have the early efforts of the commission were 36 lb. guns. Unless something is done directed at oysters. to stop their dredging, these people Through a series of laws and regulations will be in a starving condition in twelve enacted particularly in the period from months" (Whitehurst 1891). 1891 to 1925, the Fisheries Commission The exploitation of Pamlico Sound by attempted to control the growth and the northern fleet was brief, for laws were development of the shellfish industry in immediately passed shortening the season North Carolina. But the agency had only and prohibiting non-residents from dredg- marginal success early on, for at least ing in the State (Thorson 1982). Mean- three reasons, accordingto Thorson (1982): while, the local residents adopted the dredg- 1) commercial fisheries are difficult to ing methods that had been introduced, so manage because they are affected by so that when the season was lengthened in many variables; 2) there was little known 1897, production of oysters greatly in- about the ecology of the fishes and creased. The followingyear new and exten- shellfishes, and the Fisheries Commission sive beds were discovered two miles or carried out very little scientific research of more offshore in Pamlico Sound. More its own; and 3) the agency was oysters were harvested that year (1898) underfunded and understaffed. than ever before or since in the history of Oyster landings in the Albemarle- the industry. The supply seemed inex- Pamlico system have trended downward haustible, and increased preparations were almost continuously since the late 1890s made for the next year. But when the (Figure 7.6), a pattern similar to that for season opened in 1899, oysters were scarce. most other oyster producing areas. With What followed was typical of the debates, one exception, annual catches since 1953 and uncertainties, that have persisted ever have all been less than 1 million pounds, since about the reasons for fluctuations in generally fluctuating between 200 annual harvests of oysters and other com- thousand and 500 thousand pounds. The mercial fish and shellfish. Some attrib- catch in 1987 was 1.2 million pounds, the uted the scarcity to overfishing, others to highest in 34 years. severe storms that had occurred in August Trends in the North Carolina oyster and October of 1899. Grave (1904) con- harvests up until 1945 were discussed by Trends in the Sound's Fisheries 113 Chestnut (1951), who attributed the ups and threatened the economy of shellf"ish and downs to a variety of causes. These producingstates. Consequently, the indus- included varying intensity of harvesting try, along with various state and federal effort, changes in laws and regulations, health agencies, began to formulate a plan planting of oysters and shells, the Great for sanitary control oftheshellfish industry Depression, and fears about disease (N.C. State Board of Health 1956). One of outbreaks in other parts of the country the responsibilities of the Shellfish which presumably were caused by eating Sanitation Program in each state is to oysters. monitor shellfish growing areas for the Chestnut's discussion is most notable purpose of determining which areas shall for the one variable not mentioned as a be open to shellfish harvesting. In North factor in the NC oyster harvest: water Carolina, the first survey was made quality. Ina companion paper summarizing sometime between 1925 and 1930, and the hydrography of the sounds, by Nelson additional surveys have been made Marshal, it was surmised that at the time periodically since then. In recent years, (the late 1940s) "pollution of North the most thorough surveys ofall the State's Carolina's marine waters is restricted to a shellfishing grounds are made about every few local situations mostly in the vicinity of three years - Data collected during these towns and cities where toilet sewage, and, surveys provides some information about in a few instances, industrial sewage, is trends in sewage pollution in various either untreated or inadequately handled" regions. Today, waters are closed to (Marshall 195 1, p 58). He cited as evidence oystermen when tests show there are more for this conclusion the State Board ofHealth than 14 fecal coliform organisms per 100 statistics on areas closed to the harvesting ml of water, a standard established by the of oysters. As of April, 1949, about 27,000 U.S. Food and Drug Administration and acres were closed. In fact, this is one ofonly the Public Health Service. The original two references to pollution in the volume measures set up in the 1920s were 70 fecal containing this paper. The other concerns coliform bacteria per 100 ml ofwater (Peters the effect of poor water quality on the shad 1989). fishery farther inland in some ofthe coastal North Carolina has about 2 million rivers. This lack of emphasis on water acres of coastal waters, but portions of qualityas an issue affectingthe NC fisheries these waters are low-salinity and freshwa- in the 1940s is significant, in light of the ter areas that do not support shellfish. fact that this was probably the most Waters suitable for shellfish comprise 1.42 thorough synthesis ofavailable knowledge million acres ofthis total, accordingto N.C. of the estuaries of North Carolina up until Shellfish Sanitation Program estimates. that time. In 1988, 51.7 thousand acres (3.6%) of Shellfish Sanitation Programs designed these waters were closed to shellfishing to monitor and regulate oyster and clam (North Carolina Division of Health Ser- harvesting in North Carolina and other vices 1988). Only about 30% (15 thousand producer states have been in existence for acres) of the total closed area was in the about 65 years. During 1924 and 1925, Pamlico-Albemarle region north of Core outbreaks of typhoid fever in Chicago, New Sound. Most of the prohibited areas were York, Washington and several other cities south of Pamlico Sound, in the Morehead were determined to have been caused by City/Beaufort area and in Brunswick sewage-polluted oysters. The resulting County south of Wilmington. publicity paralyzed the oyster industry The data collected since 1971 indicate 114 Chapter 7 that in the Albemarle-Pamlico region industry in North Carolina is heavily closures in some areas are increasing much influenced by economic factors, some more rapidly than in others. Figure 7.7 originating outside the state. Forexample, shows that, since 197 1, the total amount of clams are normally more important in the prohibited area in the Pamlico-Albemarle Albemarle-Pamlico region than oysters, area has not changed a great deal. but fluctuations in clam prices can have an However, the lack of a trend is somewhat effect on the oyster harvest. Most North misleading, as was pointed out in a recent Carolinaclams areexportedto the northern Shellfish Sanitation Program report. states. But in years when the supply there Improvements in some areas have been is plentiful, clam prices may decline so offset by increases in closures in a few much that N.C. fishermen go after the areas with the most rapid population oysters with more effort than. at other growth, such as Dare County, where the times when clam prices are higher. permanent population increased 40% Early attempts at oyster rehabilitation between 1980 and 1986. Dare County by the state began in the 1920s and 1930s, increased 65% in prohibited shellfishing but were later judged to have been acreage during the same period. In Hyde unsuccessful due to a lack of knowledge of County, the population growth was oyster biology and selection of unsuitable negligible, but there were agricultural planting areas. In 1947, the state enacted activities that led to an increase of 818 legislation to begin a new program of acres closed since 1980 (North Carolina planting seed oysters and shells by the Division of Health Services 1988). Division of Commercial Fisheries, which Naturally, state officials are worried that was augmented by University of North such rapid growth in some of these coastal Carolina Institute of Fisheries Research areas could greatly increase the shellfish studies. An analysis of the oyster program closures in the future. in 1970 showed that despite the efforts to In addition to sewage pollution, other improve the fishery, the landings had factors such as weather, diseases, continued to decline. In 1970, the return of economics, and management activities play commercial production to the fishery was important roles in setting the annual harvest of oysters and clams in the Albemarle-Pamlico region. In some years, 20- the conditionally-approved areas may be ACRES CLOSED closed for several days or weeks following 15- heavy rains, which lead to temporary co increases in the fecal coliform counts. Also, z 610- parasitic organisms that kill oysters are a n serious threat to the fishery. "Dermo" (the ox 5 - infectious protozoan Dermocystidium marinum = Perkinsus marinus) is the most 01 prevalent disease, but.another, named 1970 1975 1980 1985 1990 MSX, showed up in 1988 in some beds YEAR (Davis 1989). In the same year, red tides Figure 7.7. Trends in saline waters closed to came to North Carolina for the first time in shellfishing in the Albemarle-Pamlico region memory, causing all oystering to cease (Pamlico, Craven, Beaufort, Hyde, Dare, and just one week after the season had opened. part of Carteret Counties). Dataprovided by Finally, like other fisheries, the oyster N.C. Division of Health Services, Shellfish Sanitation Program. Trends In the Sound's FIsherles 115 only three-tenths of a bushel of oysters for mainland, there were few roads near the each bushel of seed oysters and shell sounds. It was 1919 before the first planted. Thus, it was concluded that "the automobile reached the Outer Banks. In present oyster rehabilitation program the late 1920s, a hard-surfaced road was cannot improve oyster production and built on Roanoke Island and a toll bridge probably cannot even prevent further was built to connect the island with Nags decline in the industry" (Godwin et al. Head, on Bodie Island. However, there 1971). was no bridge linkingRoanoke Island with Nevertheless, the Oyster Rehabilita- the mainland. About 1930, the state began tion Program has been continued. The a road and bridge program that would quantities of shell planted increased from gradually link the entire region. By 1940, around 100 thousand bushels in the late theAlbemarle Soundarea was crisscrossed 1970s to an average of about 300 thousand with paved roads and linked by bridges, bushels peryear by the mid- 1980s. A 1984 but the Banks remained inaccessible to report predicted that the outlook for the automobile traffic. AfterWorldWarII,the oyster fishery was good, based on the state built a paved road between Oregon Division's strong commitment to a large Inlet and Hatteras Village. RoanokeIsland scale cultch planting and relaying pro- was finally linked to the mainland by a grain (North Carolina Division of Marine bridge completed in 1963 (Johnson et al. Fisheries 1984). One Division official re- 1986), and later another bridge was opened cently estimated that this activity increases to traffic between Kitty Hawk and the the oyster harvest by 50% in North Caro- mainland. Since then, a fourth bridge link lina. has been built, connecting Bodie Island (Nags Head, Kitty Hawk, and Kill Devil Recreational Fisheries Hills) with Hatteras Island to the south. By the mid-1800s, recreational fishing Today, the barrier islands southofHatteras had attained the status of a recognized still have no bridge links to the mainland, sport in coastal North Carolina. Most of but the state operates a regular (car- the fishing was in the rivers, creeks and carrying) ferry schedule between Hatteras lakes, but sound waters, and even the and Ocracoke and between Ocracoke and ocean, were becoming increasingly Swan Quarter and Cedar Island. attractive. In 1838, the first hotel at Nags Accessibility by automobile spurred Head on the Outer Banks was completed, rapid growth of recreation on the Outer and by the 1850s, there were cottages Banks. By 1957, tourism had replaced belonging to non-residents on the banks. commercial fishing as the number one BytheCivilWar, itwas popular forplanters industry in Dare County. In 1940, there and businessmen from eastern North were no motels in Hatteras Village or on Carolina to take their families to the Outer Roanoke Island and only two at Nag's Banks duringthe summer months (Johnson Head. By 1955, there were 15 hotels, 60 et al. 1986; Stick 1958). motels, and approximately 500 rental But the growth of sport fishing in the cottages in Dare County. Duringthe 1970s, region - particularly on the Outer Banks Dare County's growth rate exceeded the - was slow in the early 20th century, state average rate by almost 6 times, and because the area was so isolated and between 1971 and 1986, travel and tourism inaccessible. Until well into the century, revenues in the county increased from $11 water transportation was the only way to million to over $340 million, making Dare reach the Outer Banks. And even on the the states' leader in the tourism industry 116 Chapter 7 (Brower et al. 1989). 1970s. The estimated harvest has ranged Obviously then, there is indirect from a high of 65,399 fish in 1971 to only evidence that recreational fishing in the 3,131 fish in 1985 (Figure 7.4). The catch Albemarle-Pamlico system has grown, per unit effort for 1981, 1982 and 1983 especially since World War 11. Today, the were the lowest on record for the 28-year recreational fisheries are an important period of record. However, as Hassler and component of the overall fishery harvest. Taylor (1984) noted in their analysis of In fact, for a number of important species, these data, it should be noted that striped the recreational harvest probably exceeds bass size limits and creel limits were the commercial harvest. Some of these changed in 1981. Also, bow netting and species are bluefish, spotted scatroot, red fight netting were eliminated in that year. drum, and Spanish mackerel. The North The new and more restrictive regulations Carolina Division of Marine Fisheries were responsible for some part of the (DMF)began collectingdataon recreational decreased catches and catches per unit landings in 1987. effort. Unfortunately, however, there is no In fact, since 1980, the regulations on long-term record of catch, or any direct both commercial and sport harvesting of measure of effort, for the important striped bass have become more and more recreational fish species, with one restrictive, in an effort by the North exception. Beginningin 1956, W.W. Hassler Carolina Division of Marine Fisheries and and his colleagues conducted studies to the Wildlife Resources Commission to provide long-term information on the status preserve the Roanoke striped bass stock. and abundance of striped bass in the Manooch and Rulifson (1989) presented a Roanoke River and Albemarle Sound. Sport summary table showing a total of 42 catch and effort data for striped bass in the regulation changes between 1979 and 1988 Roanoke River were tabulated over a 140- concerning striped bass fishing. Included mile area from the mouth of the river to the were many new regulations that would Roanoke Rapids dam. Most years, about tend to decrease the recreational catch, 75% of the total striped bass catch was such as increased minimum size limits, made in the area just below the dam, and creel limits, shortened seasons and the about 25% in downstream locations. elimination of some gear types. The recreational striped bass catch, Environmental factors that may be like the commercial catch, had generally affecting the Roanoke striped bass have declined in the Roanoke since the early been discussed above. References Adams. D.A., G.W. Thayer, G. Davis, M.M. Beaulac, M.N. and K.H. Reckhow. 1980. Brinson, R. Collier, C. Peterson, R. Rulifson, Modeling phosphorus loading and lake re- T.L. Quay, and N.L. Christensen, Jr. 1989. sponse under uncertainty: a manual and Critical Areas. In: Copeland, B.J. (ed.) compilation of export coefficients. U.S. [Draft] Technical Status and Trends Re- EPA 440/5-80-011. Washington, DC. port for the Albemarle-Pamlico Estuarine Bechtold, W.A. 1985. Forest statistics for System. Albemarle- Pamlico Estuarine North Carolina, 1984. Resource Bulletin Study (APES) North Carolina Department SE-78. U.S. Department of Agriculture, of Natural Resources and Community De- Forest Service, Southeastern Forest Ex- velopment. Raleigh. periment Station, Asheville, NC. 62 pp. American Public Health Association. 1971. Bendschneider, K. and R.J. Robinson. 1952. A Standard methods for the examination of new spectrophotometric method for the de- water and wastewater. 13thed. American termination of nitrite in seawater. Journal Public Health Association, New York. 874 of Marine Research 11:87-96. PP. Binkley, D. 1986. 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Public Health Service Publication No. Smithsonian Institution Press, Washing- 1065,Volume 3. U.S. Department of Health, ton, D, D.C. Education and Welfare, Washington, D.C. Wells, C.A., D. Whigham, and H. Leith. 1972. Utermohl, H. 1958. Zur vervollkimmung der Investigation ofmineral nutrient cycling in quantitative phytoplankton methodisk. a upland Piedmontforest. J. ElishaMitchell Mitt. int. Verein. Limnol. 9:1-38. Sci. Soc. 88:66-78. Van Valkenburg, S.D., J.K. Jones and D.R. Wells, C.G. and J.R. Jorgensen. 1975. Nutri- Heinle. 1978. A comparison by size class ent cycling in loblolly pine plantations. pp. and volume of detritus versus phytoplank- 137-158In B. Bernier and C.H. Winget eds. ton in Chesapeake Bay. Estuarine and Forest Soils and Forest LandManagement. Coastal Marine Science 6:569-582. Les Presses de luniversite Laval, Quebec, Virginia Department ofAgriculture. 1920-1988. Canada. Virginia Agriculturie Statistics (Annual White, W.A., T.R. Calnan, R.A. Morton, R.S. Reports and Bulletins). Richmond. Kimble, T.G. Littleton, J.H. McGowen, H.S. Virginia DepartmentofAgriculture. 1956-1988. Nance and K-E. Schmedes. 1985. Sub- Fertilizer used and results of inspection merged lands in Texas, Galveston-Houston (annual reports). Richmond. area: sediments, geochemistry, benthic References 131 macroinvertebrates, and associated wet- Williams, R.B. 1972. Nutrient levels and phy- lands. Bureau of Economic Geology, The toplankton productivity in the estuary, pp. University of Texas at Austin. 59-89, In: R.A. Chadwick (ed.), Proc. Coastal Whitehurst, J.W. 1971. The menhaden fishing Marsh and Estuary Management Sympo- industry in North Carolina. The University sium, La. State Division. of Continuing of North Carolina Sea Grant College Pro- Education, Baton Rouge, LA. gram Publication UNC-SG-72-12. Raleigh, Wilms, D.C. and W.G. Powell. [no date given]. NC. 51 pp. Eastern North Carolina: An atlas of demo- Whitledge, T.E. 1985. Nationwide review of graphic and economic trends. Regional oxygen depletion and eutrophication in es- Development Institute, East Carolina Uni- tuarine and coastal waters: northeast re- versity. Greenville NC. 21 pp. gion. Report to the U.S. Department of Wilson, KA. 1962. North Carolina wetlands, Commerce, National Oceanic and Atmo- their distribution and management. N.C. spheric Administration. Brookhaven Na- Wildlife Resources Commission, Raleigh. tional Laboratory, Upton, NY. 169 pp. Wilder, H.B., T.M. Robison, and K.L. Lindskov. Winslow ' F. 1889. Report on the sounds and 1978. Water resources of northeast North estuaries of North Carolina, with reference Carolina. U.S. Geological Survey, Water to oyster culture. Bulletin of the U.S. Coast Resources Investigation 77-81. Washing- and Geodetic Survey, No. 10. 136 pp. ton, DC. 113 pp. Woods, W.J. 1967. Hydrographic studies in Wilkinson, L. 1986. SYSTAT. The System for Pamlico Sound. pp. 104-114, In: Proceed- Statistics. SYSTAT, Inc., Evanston, IL. ings of a symposium on hydrology of the Wilkinson, L. 1988. SYSTAT. The System for coastal waters of North Carolina, at North Statistics. SYSTAT, Inc., Evanston, IL. 822 Carolina State University, Raleigh. May p- 12, 1967. University of North Carolina Water Resources Research Institute Re- port No. 5. Raleigh. Appendices 133 Appendices Appendix 1. 1. Population of North Carolina and Virginia counties in the Albemarle- Pamlico basin. The total population figures given for the individual sub-basins have been adjusted (i.e., reduced) according to the percentage of the county land areas within the AN watershed. County State 1790 1800 1810 1820 1830 1840 1850 Beaufort NC 5,462 6,242 7,203 9,850 10,969 12,225 13,816 Bertie NC 12,606 11,249 11,218 10,805 12,262 12,175 12,851 Camden NC 4,033 4,191 5,347 6,347 6,733 5,663 6,049 Carteret NC 3,732 4,399 4,823 5,609 6,597 6,591 6,939 Caswell NC 10,096 8,701 11,757 13,253 15,185 14,693 15,269 Chowan NC 5,011 5,132 5,297 6,464 6,697: 6,690 6,721 Craven NC 10,469 10,245 12,676 13,394 13,734 13,438 14,709 Currituck NC 5,219 6,928 6,985 8,098 7,655 6,073 7,236 Dare NC Durham NC Edgecombe NC 10,255 10,421 12,423 13,276 14,935 15,708 17,189 Forsyth NC 11,168 Franklin NC 7,559 8,529 10,166 9,741 10,665 10,980 11,713 Gates NC 5,392 5,881 5,965 6,837 7,866 8,161 8,426 Granville NC 10,982 14,015 15,476 18,222 19,355 18,187 21,249 Greene NC 6,893 4,128 4,867 4,533 6,413 6,595 6,169 Guilford NC 7,191 9,442 11,420 14,511 18,737 19,175 19,754 Halifax NC 13,965 13,945 13,620 17,237 17,739 16,865 16,589 Hertford NC 5,828 6,701 6,052 7,712 8,537 7,484 8,142 Hyde NC 4,120 4,829 6,029 4,967 6,184 6,458 7,636 Johnston NC 5,634 6,301 6,867 9,607 10,938 10,599 13,726 Jones NC 4,822 4,339 4,968 5,216 5,608 4,945 5,038 Lenoir NC 4,005 5,572 6,799 7,723 7,605 7,828 Martin NC 6,080 5,629 5,987 6,320 8,539 7,637 8,307 Nash NC 7,393 6,975 7,268 8,185 8,490 9,047 10,657 Northampton NC 9,981 12,353 13,082 13,242 13,391 13,369 13,335 onslow NC 5,387 5,623 6,669 7,016 7,814 7,527 8,283 Orange NC 12,216 16,362 20,135 23,492 23,908 24,356 17,055 Pamlico NC Pasquotank NC 5,497 5,379 7,674 8,008 8,641 8,514 8,950 Perquimans NC 5,440 5,708 6,052 6,587 7,419 7,346 7,332 Person NC 6,402 6,642 9,029 10,027 9,790 10,781 134 Appendices Appendix 1.1. Continued County State 1790 1800 1810 1820 1830 1840 1850 Pitt NC 8,275 9,084 9,169 10,001 12,093 11,806 13,397 Rockingham NC 6,187 8,277 10,316 11,474 12,935 13,442 14,495 Stokes NC 8,528 11,026 11,645 14,033 16,196 16,265 9,206 Surry NC 7,191 9,805 10,366 12,320 14,504 15,079 18,443 Tyrrell NC 4,744 3,395 3,364 4,319 4,732 4,657 5,113 Vance NC Wake NC 10,192 13,437 17,086 20,102 20,398 21,118 24,888 Warren NC 9,207 11,284 11,004 11,158 11,887 12,919 13,912 Washington NC 2,422 3,464 3,986 4,552 4,525 5,664 Wayne NC 6,133 6,772 8,687 9,040 10,331 10,891 13,486 Wilson NC Appomattox VA 9,193 Bedford VA 10,531 14,125 16,148 19,305 20,246 20,203 24,080 Botetourt VA 10,524 10,427 13,301 13,589 16,354 11,679 14,908 Brunswick VA 12,827 16,339 15,411 16,687 15,767 14,346 13,894 Campbell VA 7,685 9,866 11,001 16,569 20,350 21,030 23,245 Charlotte VA 10,078 11,912 13,161 13,290 15,252 14,595 13,955 Dinwiddie VA 13,934 15,374 18,190 20,482 21,901 22,558 25,118 Floyd VA 4,453 6,458 Franklin VA 6,842 9,302 10,724 12,017 14,911 15,832 17,430 Greensville VA 6,362 6,727 6,853 6,858 7,117 6,366 5,639 Halifax VA 14,722 19,377 22,133 19,060 28,034. 25,936 25,962 Henry VA 8,479 5,259 5,611 5,624 7,100 7,335 8,872 Isle of WightVA 9,028 9,342 9,186 10,139 10,517 9,972 9,353 Lunenburg VA 8,959 10,381 12,265 10,662 11,957 11,055 11,692 Mecklenberg VA 14,733 17,008 18,453 19,786 20,477 20,724 20,630 Montgomery VA 13,228 9,044 8,409 8,733 12,306 7,405 8,359 Mottoway VA 9,401 9,278 9,658 10,130 9,719 8,437 Patrick VA 4,331 4,695 5,089 7,395 8,032 9,609 Pittsylvania VA 11,579 12,697 17,172 21,232 26,034 26,398 28,796 Prince GeorgeVA 8,173 7,425 8,050 8,030 8,367 7,175 7,596 Roanoke VA 5,499 8,477 Southampton VA 12,864 13,925 13,497 14,170 16,074 14,525 13,521 Surry VA 6,227 6,535 6,885 6,594 7,109 6,480 5,679 Sussex VA 10,549 11,062 11,362 11,884 12,720 11,229 �,820 Total 449,134 519,415 579,126 640,248 720,507 711,144 772,244 Chowan River 100,869 116,649 120,885 127,550 135,533 127,832 127,015 Roanoke River 139,952 164,236 184,885 204,916 242,690 244,086 263,537 Albemarle Sound 29,127 31,495 36,252 40,902 43,668 40,853 44,275 Tar-Pamlico R. 53,033 58,541 64,036 71,628 78,866 80,797 89,025 Meuse River 56,851 66,869 80,183 91,520 99,888 99,937 108,301 Pamlico sound 2,296 2,691 3,340 2,801 3,475 3,620 4,255 Appendices 135 Appendix 1.1. Continued County State 1860 1870 1880 1890 1900 Beaufort NC 14,766 13,011 17,474 21,072 26,404 Bertie NC 14,310 12,950 16,399 19,176 20,538 Camden NC 5,343 5,361 6,274 5,667 5,474 Carteret NC 8,186 9,010 9,784 10,825 11,811 Caswell NC 16,215 16,081 17,825 16,028 15,028 Chowan NC 6,842 6,450 7,900 9,167 10,258 Craven NC 16,268 20,516 19,729 20,533 24,160 Currituck NC 7,415 5,131 6,476 6,747 6,529 Dare NC 2,778 3,243 3,768 4,757 Durham NC 18,041 26,233 Edgecombe NC 17,376 22,970 26,181 24,113 26,591 Forsyth NC 12,692 13,050 18,070 28,434 35,261 Franklin NC 14,107 14,134 29,829 21,090 25,116 Gates NC 8,443 7,724 8,897 10,254 10,413 Granville NC 23,396 24,831 31,286 24,484 23,263 Greene NC 7,925 8,687 10,037 10,039 12,038 Guilford NC 29,056 21,736 23,585 28,052 39,074 Halifax NC 19,442 29,408 30,300 28,908 30,793 Hertford NC 9,504 9,273 11,843 13,851 14,294 Hyde , NC 7,732 6,445 7,765 8,903 9,278 Johnston NC 15,656 16,897 23,461 27,239 32,250 Jones NC 5,730 5,002 7,491 7,403 8,226 Lenoir NC 10,220 10,434 15,344 14,879 18,639 Martin NC 10,195 9,647 13,140 15,221 15,383 Nash NC 11,687 11,077 17,731 20,707 25,478 Northampton NC 13,372 14,749 20,032 21,242 21,150 Onslow NC 8,856 7,569 9,829 10,303 11,940 Orange NC 16,947 17,507 23,689 14,948 14,690 Pamlico NC 6,323 7,146 8,045 Pasquotank NC 8,940 8,131 10,369 10,748 13,660 Perquimans NC 7,238 7,945 9,466 9,293 10,091 Person NC 11,221 11,170 13,719 15,151 16,685 Pitt NC 16,080 17,376 21,794 25,519 30,889 Rockingham NC 16,746 15,708 21,744 25,363 33,163 Stokes NC 10,402 11,208 15,353 17,199 19,866 Surry NC 10,380 11,252 15,302 19,282 25,515 Tyrrell NC 4,944 4,173 4,545 4,225 4,980 Vance NC 17,581 16,684 Wake NC 28,627 35,617 47,939 49,207 54,626 Warren NC 15,726 17,768 22,619 19,360 19,151 Washington NC 6,357 6,516 8,928 10,200 10,608 Wayne NC 14,905 18,144 24,951 26,100 31,356 Wilson NC 9,720 12,258 16,064 18,644 23,596 Appomattox VA 8,889 8,950 10,080 9,589 9,662 Bedford VA 25,068 25,327 31,205 31,213 30,356 Botetourt VA 11,516 11,329 14,809 14,854 17,161 136 Appendices Appendix 1.1. Continued County State 1860 1870 1880 1890 1900 Brunswick VA 14,809 13,427 16,707 17,245 18,217 Campbell VA 26,197 28,384 36,250 41,087 23,256 Charlotte VA 14,471 14,513 16,653 15,077 15,343 Dinwiddie VA 30,198 30,702 32,870 13,515 15,374 Floyd VA 8,236 9,824 13,255 14,405 15,388 Franklin VA 20,098 18,364 25,084 24,985 25,953 Greensville VA 6,374 6,362 8,407 8,230 9,758 Halifax VA 26,520 27,828 23,588 34,424 37,197 Henry VA 12,105 12,303 16,009 18,208 19,265 Isle of WightVA 9,977 8,320 10,572 11,313 13,102 Lunenburg VA 11,983 10,403 11,535 11,372 11,705 Mecklenberg VA 20,096 21,318 24,610 25,359 26,551 Montgomery VA 10,617 12,556 16,693 17,742 15,852 Nottoway VA 8,836 9,291 11,156 11,582 12,366 Patrick VA 9,359 10,161 12,833 14,147 15,403 Pittsylvania VA 32,104 31,343 52,589 50,941 46,894 Prince GeorgeVA 8,411 7,820 10,054 7,872 7,752 Roanoke VA 8,048 9,350 13,105 30,101 15,837 Southampton VA 12,915 12,285 18,012 20,078 22,848 Surry VA 6,133 5,585 7,391 8,256 8,469 Sussex VA 10,175 7,885 10,062 11,100 12,082 Total 846,102 873,324 1,116,259 1,198,807 1,289,775 Chowan River 136,252 129,470 159,100 149,971 161,296 Roanoke River 286,223 295,286 373,454 421,261 407,307 Albemarle Sound 43,965 41,908 51,105 52,768 58,159 Tar-Pamlico R. 100,488 112,434 150,083 152,551 171,460 Neuse River 131,542 149,205 197,858 215,333 254,546 Pamlico Sound 4,344 4,853 8,490 9,699 10,729 Appendices 137 Appendix 1.1. Continued County State 1910 1920 1930 1940 Beaufort NC 30,877 31,024 35,026 36,431 Bertie NC 23,039 23,993 25,844 26,201 Camden NC 5,640 5,382 5,461 5,440 Carteret NC 13,776 15,384 16,900 18,284 Caswell NC 14,858 15,759 18,214 20,032 Chowan NC 11,303 10,649 11,282 11,572 Craven NC 25,594 29,048 30,685 31,298 Currituck NC 7,693 7,268 6,710 6,709 Dare NC 4,841 5,115 5,202 6,041 Durham NC 35,276 42,219 67,196 80,244 Edgecombe NC 32,101 37,995 47,894 49,162 Forsyth NC 47,311 77,269 111,681 126,475 Franklin NC 24,692 26,667 29,456 30,382 Gates NC 10,455 10,537 10,551 10,060 Granville NC 25,102 26,846 28,723 29,344 Greene NC 13,083 16,212 18,656 18,548 Guilford NC 60,497 79,272 133,010 153,916 Halifax NC 37,646 43,766 53,246 56,512 Hertford NC 15,436 16,294 17,542 19,352 Hyde NC 8,840 8,386 8,550 7,860 Johnston NC 41,401 48,998 57,621 63,798 Jones NC 8,721 9,912 10,428 10,926 Lenoir NC 22,769 29,555 35,716 41,211 Martin NC 17,797 20,838 23,400 26,111 Nash NC 33,727 41,061 52,782 55,608 Northampton NC 22,232 23,184 27,161 28,299 Onslow NC 14,125 14,703 15,289 17,939 orange NC 15,064 17,895 21,171 23,072 Pamlico NC 9,966 9,060 9,299 9,706 Pasquotank NC 16,693 17,670 19,143 20,568 Perquimans NC 11,054 11,137 10,668 9,773 Person NC 17,356 18,973 22,039 25,029 Pitt NC 36,340 45,569 54,466 61,244 Rockingham NC 36,442 44,149 51,083 57,898 Stokes NC 20,151 20,575 22,290 22,656 Surry NC 29,705 32,464 39,749 41,783 Tyrrell NC 5,219 4,849 5,164 5,556 Vance NC 19,425 22,799 27,294 29,961 Wake NC 63,229 75,155 94,757 109,544 Warren NC 20,266 21,593 23,364 23,145 Washington NC 11,062 11,429 11,603 12,323 Wayne NC 35,698 43,640 53,013 58,328 Wilson NC 28,269 36,813 44,914 50,219 Appomattox VA 8,904 9,255 8,402 9,020 Bedford VA 29,549 30,669 29,091 29,687 Botetourt VA 17,727 16,557 15,457 16,447 138 Appendices Appendix I. I. Continued County State 1910 1920 1930 1940 Brunswick VA 19,244 21,025 20,486 19,575 Campbell VA 23,043 26,716 22,885 26,048 Charlotte VA 15,785 17,540 16,061 15,861 Dinwiddie VA 15,442 17,949 18,492 18,166 Floyd VA 14,092 13,115 11,698 11,967 Franklin VA 26,480 26,283 24,337 25,864 Greensville VA 11,890 11,606 13,388 14,866 Halifax VA 40,044 41,374 41,283 41,271 Henry VA 18,459 29,238 20,088 26,481 Isle of WightVA 14,929 14,433 13,409 13,381 Lunenburg VA 12,780 15,260 14,058 13,844 Mecklenberg VA 28,956 31,208 32,622 31,933 Montgomery VA 17,268 18,595 19,605 21,206 Nottoway VA 13,462 14,161 14,866 15,556 Patrick VA 17,195 16,850 15,787 16,613 Pittsylvania VA 50,709 56,493 61,424 61,697 Prince GeorgeVA 7,848 12,915 10,311 12,226 Roanoke VA 19,623 22,395 35,289 42,897 Southampton VA 26,302 27,555 26,870 26,442 Surry VA 9,715 9,305 7,096 6,193 Sussex VA 13,664 12,834 12,100 12,485 Total 1,457,881 1,664,437 1,919,348 2,078,286 Chowan River 176,392 187,148 188,454 191,659 Roanoke River 437,061 491,723 525,304 564,084 Albemarle.Sound 64,365 64,446 65,729 67,371 Tar-Pamlico R. 198,375 225,741 267,433 281,927 Neuse River 299,103 358,655 438,650 488,704 Pamlico Sound 11,417 10,950 11,222 11,425 Appendices 139 Appendix 1.1. Continued County State 1950 1960 1970 1980 1987 Beaufort NC 37,134 36,014 35,980 40,355 45,000 Bertie NC 26,439 24,350 20,528 21,024 22,000 Camden NC 5,223 5,598 5,453 5,829 6,000 Carteret NC 23,059 30,940 31,603 41,092 52,000 Caswell NC 20,870 19,912 19,055 20,705 22,000 Chowan NC 12,540 11,729 10,764 12,558 13,000 Craven NC 48,823 58,733 62,554 71,043 83,000 Currituck NC 6,201 6,601 6,976 11,089 13,000 Dare NC 5,405 5,935 6,995 13,377 18,000 Durham NC 101,639 111,995 132,681 152,785 166,000 Edgecombe NC 51,634 54,226 54,226 55,988 59,000 Forsyth NC 146,135 189,428 215,118 243,683 262,000 Franklin NC 31,341 28,755 26,820 30,055 33,000 Gates NC 9,555 9,254 8,524 8,875 9,000 Granville NC 31,793 33,110 32,762 34,043 37,000 Greene NC 18,024 16,741 14,967 16,117 17,000 Guilford NC 191,057 246,520 288,645 317,154 328,000 Halifax NC 58,377 58,956 53,884 55,286 56,000 Hertford NC 21,453 22,718 23,529 23,368 24,000 Hyde NC 6,479 5,765 5,571 5,873 8,900 Johnston NC 65,906 62,936 61,737 70,599 79,000 Jones NC 11,004 11,005 9,779 9,705 10,000 Lenoir NC 45,953 55,276 55,204 59,819 60,000 Martin NC 27,938 27,139 24,730 25,948 26,000 Nash NC 59,919 61,002 59,122 67,153 72,000 Northampton NC 28,432 26,811 23,099 22,584 22,000 Onslow NC 42,047 82,706 103,126 112,784 129,000 Orange NC 34,435 42,970 57,567 77,055 84,000 Pamlico NC 9,993 9,850 9,467 10,398 11,000 Pasquotank NC 24,347 25,630 26,824 28,462 29,000 Perquimans NC 9,602 9,178 8,351 9,486 11,000 Person NC 24,361 26,394 25,914 29,164 31,000 Pitt NC 63,789 69,942 73,900 90,146 99,000 Rockingham NC 64,816 69,629 72,402 83,426 86,000 Stokes NC 21,520 22,314 23,782 33,086 36,000 Surry NC 45,593 48,205 51,415 59,449 62,000 Tyrrell NC 5,048 4,520 3,806 3,975 4,000 Vance NC 32,101 32,002 32,691 36,748 39,000 Wake NC 136,450 169,082 229,006 301,327 371,000 Warren NC 23,539 19,652 15,810 16,232 17,000 Washington NC 13,180 13,488 14,038 14,801 14,000 Wayne NC 64,267 82,059 85,408 97,054 100,000 Wilson NC 54,506 57,716 57,486 63,132 65,000 Appomattox VA 8,764 9,148 9,784 11,971 13,000 Bedford VA 29,627 31,028 26,728 34,927 40,000 Botetourt, VA 15,766 16,715 18,193 23,270 25,000 140 Appendices Appendix 1.1. Continued County State 1950 1960 1970 1980 1987 Brunswick VA 20,136 17,779 16,172 15,632 16,000 Campbell VA 28,877 32,958 34,248 45,424 49,000 Charlotte VA 14,057 13,368 12,366 12,266 12,000 Dinwiddie VA 18,839 22,183 21,668 22,602 22,000 Floyd VA 11,251 10,462 9,775 11,563 12,000 Franklin VA 24,560 25,925 28,163 35,740 38,000 Greensville VA 16,319 16,155 9,604 10,903 11,000. Halifax VA 41,442 33,637 30,076 30,599 30,000 Henry VA 31,219 40,335 50,901 57,654 58,000 Isle of wightvA 14,906 17,164 18,285 21,603 24,000 Lunenburg VA 14,116 12,523 11,687 12,124 12,000 Mecklenberg VA 33,497 31,428 29,426 29,444 30,000 Montgomery VA 29,780 32,923 47,157 63,516 69,000 Nottoway VA 15,479 15,141 14,260 14,666 14,000 Patrick VA 15,642 15,282 15,282 17,647 18,000 Pittsylvania VA 66,096 58,296 58,789 66,147 68,000 Prince GeorgeVA 19,697 20,270 24,371 25,733 27,000 Roanoke VA 41,486 61,693 53,817 72,945 78,000 Southampton VA 26,522 27,195 18,582 18,731 19,000 Surry VA 6,220 6,220 5,882 6,046 6,000 Sussex VA 12,785 12,411 11,464 10,874 10,000 Total 2,319,010 2,587,025 2,757,979 3,174,859 3,431,900 Chowan River 202,199 201,504 180,563 185,925 187,500 Roanoke River 591,367 622,439 627,608 728,357 763,470 Albemarle Sound 69,813 70,856 71,045 83,398 90,595 Tar-Pamlico R. 294,867 297,327 290,695 319,906 342,664 Neuse River 568,141 645,904 721,831 858,542 964,740 Pamlico Sound 10,693 10,712 10,909 14,435 18,567 Appendices 141 A p p e n d ix 3. 1 . County land areas in five major sub-basins of the Albemarle/Pamlico Estuarine system watershed. "Percent of County Area" is the value used to adjust county totals (for population, agricultural acreages and yields, and all other non-point source variables) to give estimates of the county's contribution to the basin County Area (sq. m.) Land Area in Basin County state Land Water Sum Square Percent Miles of C. Area CHOWAN RIVER Bertie MC 698 33 731 170 24.4 Brunswick VA 563 518 92.0 Chowan MC 172 57 230 110 63.9 Dinwiddie VA 507 466 92.0 Gates MC 337 7 344 252 74.8 Greensville VA 300 300 100.0 Hertford NC 353 6 359 353 100.0 Isle of Wight VA 319 160 50.0 Lunenburg VA 432 432 100.0 Mecklenberg VA 616 105 17.0 Northampton NC 547 547 357 65.3 Nottoway VA 316 167 53.0 Prince George VA 266 136 51.0 Southampton VA 603 603 100.0 Suffolk City VA 409 123 30.0 Surry VA 281 169 60.0 Sussex VA 491 491 100.0 TOTAL 7,210 4,911 ROANOKE RIVER Appomattox VA 336 95 28.4 Beaufort NC 826 135 961 8 1.0 Bedford VA 747 641 85.8 Bertie NC 698 33 731 518 74.2 Botetourt VA 545 71 13.1 Brunswick VA 563 45 8.0 Campbell VA 505 427 84.6 Caswell NC 428 428 383 89.5 Charlotte VA 477 477 100.0 Floyd VA 381 31 8.2 Forsyth NC 419 419 124 29.6 Franklin VA 683 683 100.0 Granville NC 544 544 186 34.2 Guilford NC 657 657 12 1.8 Halifax NC 742 742 302 40.7 Halifax VA 816 816 100.0 Henry VA 382 382 100.0 Martin NC 462 462 342 74.0 Mecklenburg VA 616 511 83.0 Montgomery VA 390 168 43.0 142 Appendices Appendix 3. 1. Continued County Area (sq. m.) Land Area in Basin County State Land Water Sum Square Percent Miles of C. Area Northampton NC 547 547 190 34.7 Orange NC 400 400 7 1.8 Patrick VA 481 425 88.3 Person NC 401 401 250 62.3 Pittsylvania VA 995 995 100.0 Roanoke VA 251 228 90.8 Rockingham NC 569 569 476 83.7 Stokes NC 457 457 386 84.5 Surry NC 536 536 15 2.8 Vance NC 269 269 145 53.9 Warren NC 441 441 171 38.8 Washington NC 343 85 428 56 16.3 TOTAL 16,907 9,567 TAR-PAMLICO Beaufort NC 826 135 961 776 93.9 Edgecombe NC 511 511 511 100.0 Franklin NC 494 494 426 86.2 Granville NC 544 544 220 40.4 Halifax NC 742 742 440 59.3 Hyde NC 613 736 1,349 159 25.9 Martin NC 462 462 120 26.0 Nash NC 544 544 402 73.9 Pamlico NC 338 228 566 27 8.0 Person NC 401 401 32 8.0 Pitt NC 655 655 372 56.8 Vance NC 269 269 124 46.1 Warren NC 441 441 270 61.2 Washington NC 343 85 428 89 25.9 Wilson NC 375 375 63 16.8 TOTAL 7,558 4,031 NEUSE RIVER Beaufort NC 826 135 961 43 5.2 Carteret NC 536 532 1,068. ill 20.7 Craven NC 699 60 759 643 92.0 Durham NC 299 299 216 72.2 Franklin NC 494 494 65 13.2 Granville NC 544 544 138 25.4 Greene NC 269 269 269 100.0 Johnston NC 793 793 793 100.0 Jones NC 468 468 369 78.8 Lenoir NC 400 400 400 100.0 Nash NC 544 544 142 26.1 Orange NC 400 400 209 52.3 Appendices 143 Appendix 3. 1. Continued County Area (sq. m.) Land Area in Basin County state Land Water Sum Square Percent Miles of C. Area Pamlico NC 338 228 566 165 48.9 Person NC 401 401 119 29.7 Pitt NC 655 655 283 43.2 Wake NC 859 859 723 84.2 Wayne NC 557 557 520 93.4 Wilson NC 375 375 312 83.2 TOTAL 9,457 5,520 COASTAL Albemarle Sound Bertie NC 698 33 731 10 1.4 Camden NC 239 77 316 239 100.0 Chowan NC 172 57 230 62 36.1 Currituck NC 246 177 423 246 100.0 Dare NC 391 880 1,271 225 57.6 Gates NC 337 7 344 85 25.2 Hyde NC 613 736 1,349 128 20.9 Pasquotank NC 228 65 293 228 100.0 Perquimans NC 246 89 335 246 100.0 Tyrrell NC 390 169 559 390 100.0 Washington NC 343 85 428 198 57.8 TOTAL 3,903 2,057 Pamlico Sound Carteret NC 536 532 1,068 15 2.8 Dare NC 391 880 1,271 167 42.4 Hyde NC 613 736 1,349 326 53.2 Pamlico NC 338 228 566 145 42.9 TOTAL 1,877 653 Notes: a. Area south of 35' latitude (i.e., Core and Bogue Sounds) excluded from Coastal sub- basin b. Pamlico-Albemarle boundary is a line running east-west through Manteo, N.C. c. Tar-Pamlico River estuary basin includes all coastal drainage west of the mouth of the estuary. The boundary between Tar-Pamlico and Pamlico Sound (Coastal) corresponds to the eastern edge of USGS cataloging unit 03020104 (see maps in NOAA National Estuarine Atlas for identification of these units (NOAA 1985)). d. The southern boundary of Pamlico Sound is a line between Hog Island and Swash Inlet (southwest of this line is Core Sound) - Note that NOAA National Estuarine Atlas has this boundary farther southwest, at a line between Marshallberg and Core Banks. e. The boundary between Chowan River Basin and Albemarle Sound is mouth of Chowan River near Edenton, corresponding to boundary between USGS cataloging units 03010203 and 03010205. 144 Appendices Appendix 3.1 Continued f. Albemarle Sound corresponds to USGS cataloging unit 03010205. g. Pamlico Sound corresponds to USGS cataloging unit 03020105. h. Eastern boundary of Neuse River basin = boundary between USGS cataloging units 03020204 and 03020106. i. Eastern boundary of Roanoke River basin boundary between USGS cataloging units 03010107 and 03010205. Appendices 145 Appendix 3.2a. Acres of Land in Farms 1880 1890 1900 1910 1920 Chowan River 2464949 2365240 2456909 2313583 2097147 Roanoke River 4967022 5068506 5283595 5315135 5076096 Albemarle Sound 666732 600988 549003 1269179 492413 Tar-Pamlico R. 1859608 1824614 1878555 1836714 1650105 Neuse River 2684615 2679392 2677646 2671131 2359364 Pamlico Sound 100326 93821 91390 89467 83981 Total Coastal 767058 694810 640393 1358646 576394 Total 12743253 12632562 12937098 13495209 11759107 1925 1930 1935 1940 1945 Chowan River 1938618 1928197 2058922 2002257 1945566 Roanoke River 4785518 4901548 5037644 4823633 4678175 Albemarle Sound 431990 446340 445547 457963 448986 Tar-Pamlico R. 1518034 1531564 1800901 1723753 1738125 Neuse River 2153428 2113459 2424232 2282723 2325327 Pamlico Sound 76134 69267 77256 70737 59460 Total Coastal 508124 515607 522803 528700 508447 Total 10903722 10990375 11844502 11361065 11195640 1950 1954 1959 1964 1969 Chowan River 2036286 1964801 1678576 1505628 1435360 Roanoke River 4741180 4470567 4094046 3787973 3303075 Albemarle sound 476410 456960 446638 430965 406375 Tar-Pamlico R. 1851346 1775610 1685385 1565672 1497199 Neuse River 2459176 2351979 2133319 1974766 1775826 Pamlico Sound 67413 69741 70407 66588 62602 Total Coastal 543823 526702 517045 497554 468977 Total 11631811 11089659 10108371 9331593 8480437 1974 1978 1982 1987 chowan River 1346248 1295363 1214301 1177872 Roanoke River 2841138 2752780 2655110 2575457 Albemarle Sound 405070 447050 469384 455303 Tar-Pamlico R. 1257590 1285257 1202536 1166460 Neuse River 1597807 1592321 1473881 1429665 Pamlico Sound 69163 69634 80138 77734 Total Coastal 474233 516684 549523 533037 Total 7517017 7442404 7095350 6882489 146 Appendices Appendix 3.2b. Acres of Harvested Cropland 1880 1890 1900 1910 1920 Chowan River 428302 477991 529202 Roanoke River 1045276 1096797 1114829 Albemarle Sound 174349 156921 192890 Tar-Pamlico R. 472982 485395 551255 Neuse River 628622 715262 806725 Pamlico sound 19829 17983 30145 Total Coastal 194178 174904 223035 Total 2769360 2950347 3225045 1925 1930 1935 1940 1945 Chowan River 514563 553523 536273 563039 578564 Roanoke River 1068344 1113728 1063036 1156245 1102232 Albemarle Sound 203374 205196 212333 214223 217026 Tar-Pamlico R. 589380 623476 623346 672674 646010 Neuse River 812425 801286 853217 919896 915909 Pamlico Sound 30104 28884 29498 30645 29944 Total Coastal 233478 234080 241831 244868 246970 Total 3218190 3326093 3317703 3556722 3489685 1950 1954 1959 1964 1969 Chowan River 550976 525518 500087 444313 442954 Roanoke River 1009016 964181 846882 707756 592530 Albemarle sound 209160 216972 221581 213997 228732 Tar-Pamlico R. 668130 642814 607239 518450 454082 Neuse River 919543 897536 797235 673052 599697 Pamlico Sound 28070 28798 29862 29798 32049 Total Coastal 237231 245770 251442 243795 260781 Total 3384895 3275818 3002886 2587367 2350043 1974 1978 1982 1987 chowan River 507897 521092 552496 458237 Roanoke River 638962 658832 693834 412340 Albemarle sound 271252 320775 348359 313078 Tar-Pamlico R. 537258 592236 618788 529547 Neuse River 715831 782523 808933 665532 Pamlico Sound 38967 44916 55826 49081 Total Coastal 310219 365691 404185 362159 Total 2710167 2920374 3078236 2427815 AppendIces 147 Appendix 3.2c. Acres of Pastureland. "E" Indicates interpolated (i.e., estimated values) 1880E 1890E 1900B 1910E 1920E chowan River 102597 102597 10259 710259 7102597 Roanoke River 577820 577820 577820 577820 577820 Albemarle Sound 11624 11624 11624 11624 11624 Tar-Pamlico R. 54387 54387 54387 54387 54387 Neuse River 59654 59654 59654 59654 59654 Pamlico Sound 1772 1772 1772 1772 1772 Total Coastal 13397 13397 13397 13397 13397 Total 807855 807855 807855 807855 807855 1925 1930 1935 1940 1945 Chowan River 102597 119365 99317 105373 111430 Roanoke River 577820 604630 604854 644213 683571 Albemarle Sound 11624 16380 14292 14651 15010 Tar-Pamlico R. 54387 52271 57147 63361 69574 Neuse River 59654 73687 70303 79901 89500 Pamlico Sound 1772 2380 2918 2528 2138 Total Coastal 13397 18760 17210 17179 17148 Total 807855 868713 848831 910027 971223 1950 1954 1959 1964 1969 Chowan River 134737 158095 125814 122233 114944 Roanoke River 677105 649190 573672 585665 533586 Albemarle Sound 18742 30597 21423 17969 18789 Tar-Pamlico R. 87827 118383 101139 105367 104417 Neuse River 115986 137943 120729 121578 110111 Pamlico sound 2136 3883 4798 3087 4885 Total Coastal 20878 34480 26221 21056 23674 Total 1036534 1098091 947576 955899 886733 1974 1978 1982 1987E Chowan River 154561 102693 103336 103336 Roanoke River 566171 496487 505091 505091 Albemarle Sound 18420 14590 10336 10336 Tar-Pamlico R. 122847 91387 78804 78804 Neuse River 137980 106237 93067 93067 Pamlico Sound 5187 4294 2459 2459 Total coastal 23607 18884 12794 12794 Total 1005165 815688 793092 793092 148 Appendices Appendix 3.2d. Acres of "other land" in farms; generally the sum of two land categories in the agriculre census reports: 1) Other Cropland (Idle, Crop Failure, etc.) and 2) Other Land - Not Pasture and Range (i.e., house lots, ponds, roads, etc.). Harvested cropland, non-forested pastureland, and forested lands are not included in this landuse category. "E" indicates values estimated by interpolation 1880E 1890E 1900E 1910E 1920E Chowan River 300461 300461 300461 300461 300461 Roanoke River 951039 951039 951039 951039 951039 Albemarle Sound 43533 43533 43533 43533 43533 Tar-Pamlico R. 196642 196642 196642 196642 196642 Neuse River 285889 285889 285889 285889 285889 Pamlico Sound 18491 18491 18491 18491 18491 Total 1796054 1796054 1796054 1796054 1796054 Coastal 62024 62024 62024 62024 62024 1925 1930 1935 1940 1945 Chowan River 300461 255712 247368 170800 137025 Roanoke River 951039 854695 815374 638900 523509 Albemarle Sound 43533 41655 35929 29707 16847 Tar-Pamlico R. 196642 156457 182137 119154 123019 Neuse River 285889 232745 212408 171269 142240 Pamlico sound 18491 5198 8845 6327 4789 Total 1796054 1546462 1502061 1136157 947429 Coastal 62024 46853 44774 36034 21636 1950 1954 1959 1964 1969 Chowan River 156098 107639 111867 124987 156938 Roanoke River 622008 475913 508789 492693 465201 Albemarle sound 36012 18343 23795 42397 44102 Tar-Pamlico R. 146107 113000 139261 173697 226112 Neuse River 194216 156896 189233 216248 301567 Pamlico Sound 7288 5421 6874 7548 5310 Total 1161729 877212 979819 1057569 1199231 Coastal 43299 23764 30669 49945 49413 1974 1978 1982 1987E Chowan River 98802 109107 91147 91147 Roanoke River 323489 376364 317112 317112 Albemarle Sound 27570 29476 29325 29325 Tar-Pamlico R. 120576 151130 107819 107819 Neuse River 172335 181918 132203 132203 Pamlico Sound 2751 4866 5013 5013 Total 745523 852860 682619 682619 Coastal 30322 34342 34338 34338 Appendices 149 Appendix 3.2e. Acres of Forest. "Ell Indicates interpolated (i.e., estimated) values 1880E 1890E 1900B 1910E 1920E Chowan River 2063556 2063556 2063556 2063556 2063556 Roanoke River 3375191 3375191 3375191 3375191 3375191 Albemarle Sound 857692 857692 857692 857692 857692 Tar-Pamlico R. 1342457 1342457 1342457 1342457 1342457 Neuse River 1914105 1914105 1914105 1914105 1914105 Pamlico Sound 298843 298843 298843 298843 298843 Total Coastal 1156535 1156535 1156535 1156535 1156535 Total 9851844 9851844 9851844 9851844 9851844 1925E 1930E 1935E 1940 1945E Chowan River 2063556 2063556 2063556 2063556 2082702 Roanoke River 3375191 3375191 3375191 3375191 3506594 Albemarle Sound 857692 857692 857692 857692 882699 Tar-Pamlico R. 1342457 1342457 1342457 1342457 1389694 Neuse River 1914105 1914105 1914105 1914105 1949371 Pamlico sound 298843 298843 298843 298843 302491 Total Coastal 1156535 1156535 1156535 1156535 1185190 Total 9851844 9851844 9851844 9851844 10113551 1950E 1954E 1959 1964 1969E Chowan River 2101848 2120994 2140140 2178594 2208389 Roanoke River 3637997 3769399 3900802 4021611 4008157 Albemarle Sound 907706 932713 957720 890980 865470 Tar-Pamlico R. 1436932 1484169 1531406 1527421 1508630 Neuse River 1984637 2019902 2055168 2060987 2032545 Pamlico Sound 306139 309787 313435 281047 277998 Total Coastal 1213845 1242500 1271155 1172027 1143468 Total 10375258 10636964 10898671 10960640 10901189 1974 1978E 1982 1987 chowan River 2238184 2166571 2094957 2094957 Roanoke River 3994704 3929931 3865158 3865158 Albemarle Sound 839960 773923 707887 707887 Tar-Pamlico R. 1489839 1444911 1399982 1399982 Neuse River 2004102 1952878 1901654 1901654 Pamlico Sound 274949 260658 246366 246366 Total Coastal 1114909 1034581 954253 954253 Total 10841738 10528871 10216003 10216003 150 Appendices Appendix 3.2f. Acres of Urban Land. "E" Indicates interpolated (i.e., estimated) values 1880B 1890E 1900E 1910B 1920E Chowan River 0 0 0 0 0 Roanoke River 0 0 0 0 0 Albemarle sound 0 0 0 0 0 Tar-Pamlico R. 0 0 0 0 0 Neuse River 0 0 0 0 0 Pamlico sound 0 0 0 0 0 Total Coastal 0 0 0 0 0 Total 0 0 0 0 0 1925E 1930E 1935E 1940 1945E chowan River 0 0 0 0 0 Roanoke River 0 2000 5000 10240 16000 Albemarle Sound 0 0 0' 0 0 Tar-Pamlico R. 0 1000 2000 3840 3840 Neuse River 0 3000 7000 13440 14000 Pamlico Sound 0 0 0 0 0 Total Coastal 0 0 0 0 0 Total 0 6000 14000 27520 33840 1949 1954E 1959 1964E 1969 Chowan River 0 960 1920 1920 1920 Roanoke River 21120 40000 62720 70000 76160 Albemarle Sound 0 2000 4480 5000 5760 Tar-Pamlico R. 3840 12000 18560 23000 27520 Neuse River 15360 30000 58880 70000 85120 Pamlico sound 0 0 0 0 0 Total Coastal 0 2000 4480 5000 5760 Total 40320 84960 146560 169920 196480 1974E 1978E 1982 1987 Chowan River 3100 4400 5760 7000 Roanoke River 82000 89000 95360 100000 Albemarle Sound 5400 5200 5120 5000 Tar-Pamlico R. 30000 33000 36480 39000 Neuse River 95000 110000 126080 150000 Pamlico Sound 0 0 0 0 Total coastal 5400 5200 5120 5000 Total 215500 241600 268800 301000 Appendices 151 Appendix 3.2g. Acres "Other Land", calculated by subtracting sum of harvested cropland, pasture, other farmland, forested land and urban land from total land area 1880 1890 1900 1910 1920 Chowan River 248189 245361 198499 167122 147289 Roanoke River 172914 206666 121394 166274 103361 Albemarle Soun 229281 237954 246709 246919 210741 Tar-Pamlico R. 513051 485735 500640 454492 434779 Neuse River 643890 571417 557250 536196 465787 Pamlico Sound 78985 80715 80831 73724 68668 Total 1886310 1827848 1705323 1644727 1430625 coastal 308266 318669 327540 320643 279409 1925 1930 1935 1940 1945 Chowan River 161928 150947 196590 240336 233383 Roanoke River 149846 171997 258784 297452 290334 Albemarle Soun 200256 195557 196233 200206 184898 Tar-Pamlico R. 396653 403859 372433 378034 347382 Neuse River 460087 507336 475128 433548 421141 Pamlico Sound 68710 82615 77816 79577 78558 Total 1437481 1512311 1576984 1629153 1555697 coastal 268966 278172 274049 279783 263456 1950 1954 1959 1964 1969 Chowan River 199445 229897 263276 271057 217959 Roanoke River 154995 223557 229375 244515 446606 Albemarle Soun 144860 115854 87482 146137 153627 Tar-Pamlico R. 236684 209155 181915 231585 258758 Neuse River 302418 289883 310915 390294 403120 Pamlico Sound 74287 70032 62951 96441 97678 Total 1112689 1138378 1135913 1380029 1577748 coastal 219147 185886 150433 242578 251305 1974 1978 1982 1987 Chowan River 140560 239241 295407 479574 Roanoke River 516915 571626 645686 1239652 Albemarle Soun 153877 172516 215454 280180 Tar-Pamlico R. 279001 266857 337647 532188 Neuse River 406912 398604 470223 721907 Pamlico sound 96065 103186 108256 120014 Total 1593330 1752030 2072673 3373513 Coastal 249942 275702 323709 400194 152 Appendices Appendix 3.3a. Acres of Cotton 1880 1890 1900 1910 1920 Chowan River 88793 82613 53869 49240 78840 Roanoke River 70835 79539 55479 61555 65597 Albemarle sound 26617 28447 20792 32705 36445 Tar-Pamlico R. 177765 198983 125439 188211 173018 Neuse River 218561 258981 201940 250561 248026 Pamlico Sound 3398 3313 2682 7096 8029 Total Coastal 30015 31760 23475 39801 44474 Total 585970 651877 460202 589368 609954 1925 1930 1935 1940 1945 Chowan River 131248 114726 67794 44336 47847 Roanoke River 109380 93829 58149 36765 37771 Albemarle Sound 47896 36180 17723 9772 13366 Tar-Pamlico R. 255884 209202 120769 78933 83691 Neuse River 318540 263494 155061 88517 99389 Pamlico Sound 5413 4925 2281 1925 2505 Total Coastal 53309 41105 20004 11697 15871 Total 868361 722355 421776 260248 284568 1950 1954 1959 1964 1969 Chowan River 58204 37028 32360 43949 23589 Roanoke River 49128 33119 27138 39170 19172 Albemarle Sound 8633 5018 3523 2666 743 Tar-Pamlico R. 104717 65138 54174 62812 24843 Neuse River 117427 69780 57240 40509 6045 Pamlico Sound 1090 188 166 53 2 Total Coastal 9723 5206 3688 2719 746 Total 339198 210270 174601 189159 74395 1974 1978 1982 1987 Chowan River 18717 4085 10861 16782 Roanoke River 16475 3586 8781 15192 Albemarle sound 561 145 2055 5010 Tar-Pamlico R. 21246 6847 16010 23540 Neuse River 2018 379 813 3243 Pamlico Sound 0 0 0 0 Total Coastal 561 145 2055 5010 Total 59017 15041 38521 63767 Appendices 153 Appendix 3.3b. Acres of Corn 1880 1890 1900 1910 1920 Chowan River 250538 223285 247696 227704 218000 Roanoke River 438406 405352 469645 439683 435434 Albemarle Sound 130990 123063 123291 106009 105400 Tar-Pamlico R. 227416 215942 251102 218008 210797 Neuse River 310732 320067 382387 342766 338137 Pamlico Sound 14765 12787 13630 14905 15727 Total Coastal 145755 135850 136921 120914 121126 Total 1372847 1300496 1487751 1349075 1323494 1925 1930 1935 1940 1945 Chowan River 167531 168164 189603 206713 196529 Roanoke River 360268 369001 397501 406418 356745 Albemarle Sound 82458 63821 96254 99345 96222 Tar-Pamlico R. 174197 180371 243641 263587 238970 Neuse River 270262 284565 364595 375396 383849 Pamlico Sound 12832 13560 17364 17439 14095 Total Coastal 95290 77381 113618 116784 110317 Total 1067548 1079483 1308958 1368898 1286410 1950 1954 1959 1964 1969 chowan River 187997 196799 163185 122244 122487 Roanoke River 306596 270905 220661 159497 110830 Albemarle Sound 87304 90849 98910 78459 71830 Tar-Pamlico R. 240621 244216 253064 161115 140425 Neuse River 407992 428207 448365 298669 274622 Pamlico Sound 10146 10953 49696 9166 9139 Total Coastal 97451 101802 148606 87625 80968 Total 1240657 1241929 1233881 829150 729333 1974 1978 1982 1987 chowan River 170285 192011 163193 107545 Roanoke River 143423 156428 139871 93580 Albemarle Sound 109513 138304 136877 101746 Tar-Pamlico R. 198971 223166 187257 162888 Neuse River 321874 322969 294461 256582 Pamlico Sound 15845 16373 21956 15731 Total Coastal 125358 154677 158833 117477 Total 959911 1049251 943615 738071 154 Appendices Appendix 3.3d. Acres of Hay 1880 1890 1900 1910 1920 Chowan River 2833 13146 15560 35712 36812 Roanoke River 35658 67925 77205 98942 125720 Albemarle Sound 1195 2239 2959 5199 14069 Tar-Pamlico R. 1692 6046 9913 19061 27175 Neuse River 1803 9173 14818 32196 37473 Pamlico Sound 50 243 570 1922 2005 Total Coastal 1245 2482 3529 7121 16074 Total 43232 98773 121026 193032 243253 1925 1930 1935 1940 1945 Chowan River 42355 174382 180169 173971 39437 Roanoke River 131498 144099 191857 258985 264423 Albemarle Sound 15795 21764 31302 23926 7039 Tar-Pamlico R. 31118 48939 103188 104084 64779 Neuse River 36540 41341 108717 120655 124524 Pamlico Sound 1858 1285 4698 1829 1553 Total Coastal 17653 23049 36000 25755 8593 Total 259163 431811 619931 683450 501756 1950 1954 1959 1964 1969 Chowan River 44746 77269 62507 43164 20645 Roanoke River 276568 322427 251549 177750 136053 Albemarle Sound 2314 9800 3883 4166 1339 Tar-Pamlico R. 59615 81630 60094 33795 13534 Neuse River 88847 71991 41947 23911 15364 Pamlico Sound 614 521 335 254 335 Total Coastal 2928 10321 4218 4421 1674 Total 472704 563638 420315 283040 187270 1974 1978 1982 1987 Chowan River 20377 23008 25020 26951 Roanoke River 139586 157796 169578 176775 Albemarle Sound 1563 672 532 1158 Tar-Pamlico R. 12603 14954 15743 21013 Neuse River 16947 22813 23082 23218 Pamlico Sound 315 291 126 224 Total Coastal 1877 963 658 1382 Total 191391 219534 234081 249339 Appendices 155 Appendix Me. Acres of Oats 1880 1890 1900 1910 1920 chowan River 50531 41540 16339 10074 2890 Roanoke River 211057 175138 110177 57683 25164 Albemarle Sound 6741 9866 3047 2568 1075 Tar-Pamlico R. 34304 47167 18338 10882 4061 Neuse River 37656 53483 26171 18823 7683 Pamlico Sound 891 1692 975 1040 849 Total Coastal 7631 11558 4022 3608 1925 Total 341180 328887 175048 101071 41721 1925 1930 1935 1940 1945 chowan River 692 972 927 1051 2741 Roanoke River 7004 5936 6253 7785 9634 Albemarle Sound 287 261 333 617 1845 Tar-Pamlico R. 489 621 1375 3903 9228 Neuse River 905 999 1088 2750 8314 Pamlico Sound 586 512 326 498 1705 Total Coastal 873 773 659 1115 3550 Total 9963 9301 10302 16604 33467 1950 1954 1959 1964 1969 chowan River 4387 16739 7491 2992 2640 Roanoke River 14892 27036 24038 11205 9715 Albemarle sound 1433 2269 2260 4219 4951 Tar-Pamlico R. 8873 17977 15659 7068 5974 Neuse River 11921 24547 21480 10790 9673 Pamlico Sound 1592 1508 806 494 917 Total Coastal 3025 3777 3066 4712 5868 Total 43096 90075 71733 36767 33870 1974 1978 1982 1987 Chowan River 1176 1168 1016 141 Roanoke River 6334 8582 4931 2745 Albemarle Sound 1874 1494 820 1481 Tar-Pamlico R. 3658 4452 6263 5603 Neuse River 5270 10582 7812 9408 Pamlico Sound 161 98 221 52 Total Coastal 2035 1591 1042 1533 Total 18474 26376 21063 19430 156 Appendices Appendix 3.3f. Acres of Peanuts 1880 1890 1900 1910 1920 Chowan River 43593 107910 156465 139240 Roanoke River 1833 26947 54044 45511 Albemarle Sound 1393 6640 10173 8821 Tar-Pamlico R. 2040 20352 46721 23425 Neuse River 1035 3350 8448 1330 Pamlico Sound 14 36 86 7 Total Coastal 1407 6677 10259 8827 Total 49908 165236 275936 218334 1925 1930 1935 1940 1945 Chowan River 135647 166071 170454 168057 176011 Roanoke River 55275 61234 67678 68230 75478 Albemarle Sound 15412 19636 19696 19494 23358 Tar-Pamlico R. 31045 45324 53889 56417 69992 Neuse River 2371 7365 8119 6885 10096 Pamlico Sound 40 62 127 63 25 Total Coastal 15452 19699 19823 19557 23383 Total 239789 299693 319964 319145 354959 1950 1954 1959 1964 1969 Chowan River 160008 119086 120134 121017 127649 Roanoke River 65477 48899 47984 50255 53498 Albemarle Sound 13807 10125 10057 10180 9806 Tar-Pamlico R. 56024 43081 42957 45031 42063 Neuse River 5547 4481 4514 4581 4620 Pamlico Sound 7 5 1 1 1 Total Coastal 13815 10129 10058 10181 9807 Total 300871 225676 225646 231065 237636 1974 1978 1982 1987 Chowan River 129255 129644 123493 108993 Roanoke River 48493 50655 47186 46577 Albemarle Sound 9378 9523 8610 8817 Tar-Pamlico R. 40863 42655 37836 37615 Neuse River 3826 4363 3794 3265 Pamlico Sound 0 0 0 0 Total Coastal 9378 9523 8610 8817 Total 231816 236840 220919 205267 Appendices 157 Appendix 3.3c. Acres of Corn for Silage 1880 1890 1900 1910 1920 Chowan River Roanoke River Albemarle Sound Tar-Pamlico R. Neuse River Pamlico sound Total Coastal Total 1925 1930 1935 1940 1945 Chowan River 846 1375 1134 Roanoke River 3727 4252 3849 Albemarle sound 78 113 212 Tar-Pamlico R. 313 554 494 Neuse River 763 1524 1557 Pamlico sound 0 0 1 Total Coastal 78 114 213 Total 5728 7819 7246 1950 1954 1959 1964 1969 Chowan River 1619 4037 2992 5317 9503 Roanoke River 5462 11634 14497 29016 47205 Albemarle sound 335 249 359 763 821 Tar-Pamlico R. 746 2264 3130 3962 5999 Neuse River 1252 3911 4270 6951 10717 Pamlico Sound 1 27 239 241 445 Total Coastal 336 276 597 1004 1266 Total 9416 22121 25486 46250 74689 1974 1978 1982 1987 Chowan River 7397 6812 5759 5499 Roanoke River 39163 46626 40682 38316 Albemarle sound 908 298 1252 440 Tar-Pamlico R. 5449 6051 9833 5020 Neuse River 7822 10292 9743 6200 Pamlico Sound 538 341 427 161 Total Coastal 1446 639 1679 600 Total 61277 70419 67695 55636 158 Appendices Appendix 3.3g. Acres of Soybeans 1880 1890 1900 1910 1920 Chowan River 2949 Roanoke River 1397 Albemarle Sound 26374 Tar-Pamlico R. 5339 Neuse River 5120 Pamlico Sound 3169 Total Coastal 29544 Total 44349 1925 1930 1935 1940 1945 Chowan River 8933 12513 18790 90183 Roanoke River 14777 19338 26125 27507 Albemarle Sound 42193 57143 65478 78317 Tar-Pamlico R. 11168 29198 57222 61972 Neuse River 14941 39769 71296 109879 Pamlico Sound 6310 6696 7726 8101 Total Coastal 48503 63840 73205 86418 Total 98322 164657 246637 375958 1950 1954 1959 1964 1969 Chowan River 13709 31156 66400 69531 76568 Roanoke River 6473 12498 26025 31957 49190 Albemarle sound 73605 85081 84354 104840 118302 Tar-Pamlico R. 41547 56355 81861 111900 121313 Neuse River 23013 26223 52555 114592 109261 Pamlico Sound 10451 12262 14732 18020 18601 Total Coastal 84056 97343 99086 122860 136903 Total 168797 223575 325928 450840 493234 1974 1978 1982 1987 Chowan River 123513 136243 174778 167038 Roanoke River 82613 100538 127257 108167 Albemarle Sound 136261 157918 182765 138418 Tar-Pamlico R. 163577 208060 238801 180141 Neuse River 161536 252510 297729 228632 Pamlico Sound 20014 24329 30638 24009 Total Coastal 156275 182247 213403 162427 Total 687514 879598 1051967 846405 Appendices 159 Appendix 3.3h. Acres of Tobacco 1880 1890 1900 1910 1920 Chowan River 11165 10042 18886 18399 32064 Roanoke River 108719 106789 156046 170347 216137 Albemarle Sound 5 0 32 19 388 Tar-Pamlico R. 5280 12343 47566 41952 98919 Neuse River 5721 11570 53540 67735 145568 Pamlico Sound 7 0 24 9 239 Total Coastal 13 0 56 27 627 Total 130897 140744 276094 298460 493315 1925 1930 1935 1940 1945 Chowan River 28068 31943 23787 37470 29090 Roanoke River 186729 216422 140627 196871 155236 Albemarle Sound 366 1429 5683 1143 1070 Tar-Pamlico R. 79407 141815 83896 136672 112652 Neuse River 128633 220503 127651 229675 189140 Pamlico Sound 233 451 12942 798 586 Total Coastal 600 1880 18624 1941 1656 Total 423437 612563 394586 602630 487774 1950 1954 1959 1964 1969 Chowan River 27470 30982 23479 19120 16168 Roanoke River 146410 160193 109731 98666 86564 Albemarle sound 1096 5791 842 772 634 Tar-Pamlico R. 103466 115046 77909 69810 63185 Neuse River 171673 190239 126790 114722 98907 Pamlico Sound 580 764 466 423 330 Total Coastal 1676 6555 1307 1194 964 Total 450695 503015 339215 303513 265788 1974 1978 1982 1987 Chowan River 17403 16973 14782 9613 Roanoke River 86936 92758 73742 47323 Albemarle Sound 469 509 567 344 Tar-Pamlico R. 62357 67683 55613 36753 Neuse River 102543 115434 97329 63606 Pamlico Sound 355 486 281 214 Total Coastal 824 995 849 558 Total 270062 293844 242316 157853 160 Appendices Appendix 3.3i, Acres of Wheat 1880 1890 1900 1910 1920 chowan River 24441 16910 17730 11775 18408 Roanoke River 180601 174947 201298 169663 199870 Albemarle Sound 8801 669 159 39 318 Tar-Pamlico R. 26525 17777 12683 6706 8521 Neuse River 54149 46786 33055 15787 23387 Pamlico Sound 717 49 66 31 120 Total Coastal 9519 717 225 70 438 Total 295235 257139 264991 204001 250625 1925 1930 1935 1940 1945 Chowan River 11540 12778 17797 12062 18395 Roanoke River 117466 141902 147326 104118 103720 Albemarle Sound 124 20 81 77 921 Tar-Pamlico R. 2238 3467 12806 8382 18452 Neuse River 7596 9605 17459 12417 35555 Pamlico Sound 13 0 4 1 159 Total Coastal 137 20 86 78 1081 Total 138977 167773 195473 137057 177202 1950 1954 1959 1964 1969 Chowan River 13334 14334 21462 12826 12805 Roanoke River 89233 80048 106233 63502 38854 Albemarle Sound 125 1272 8754 19569 19253 Tar-Pamlico R. 8434 13068 28698 17984 18589 Neuse River 16818 21010 43602 33247 22985 Pamlico Sound 66 186 899 2338 1739 Total Coastal 190 1458 9653 21907 20992 Total 128009 129918 209648 149466 114225 1974 1978 1982 1987 Chowan River 28469 10058 64870 31886 Roanoke River 61646 29983 84923 50776 Albemarle Sound 26694 19426 70587 49483 Tar-Pamlico R. 28048 14890 91088 65576 Neuse River 35863 18566 99534 78998 Pamlico Sound 3673 1656 9425 7765 Total Coastal 30367 21081 80012 57248 Total 184393 94578 420426 284483 Appendices 161 Appendix 3.4a. Tons of Nitrogen Sold as Fertilizer 1880 1890 1900 1910 1920 Chowan River 164 440 1043 2378 3907 Roanoke River 247 664 1573 3587 5894 Albemarle Sound 51 138 327 747 1227 Tar-Pamlico R. 211 568 1346 3069 5044 Neuse River 316 850 2013 4591 7545 Pamlico Sound 5 13 30 68 112 Total Coastal 56 151 357 815 1338 Total 1046 2818 6671 15214 25000 1925 1930 1935 1940 1945 Chowan River 6663 4575 3417 3759 5230 Roanoke River 9503 8064 6146 6362 9110 Albemarle Sound 1785 1487 994 1491 2037 Tar-Pamlico R. 8275 7143 5038 4910 7015 Neuse River 11837 10248 7567 7229 10575 Pamlico sound 197 171 225 205 208 Total Coastal 1982 1658 1218 1696 2245 Total 40185 33618 25322 25895 36120 1950 1954 1959 1964 1969 Chowan River 6016 9076 8390 17134 14248 Roanoke River 10822 14613 14104 30498 25881 Albemarle Sound 2632 3035 3095 7243 8613 Tar-Pamlico R. 8638 10997 10898 24648 19373 Neuse River 13765 16446 16370 36624 33921 Pamlico Sound 252 369 377 718 846 Total Coastal 2883 3403 3473 7961 9459 Total 44075 56490 55194 118829 104851 1974 1978 1982 1987 Chowan River 18773 19142 17035 11762 Roanoke River 26999 28488 25801 21223 Albemarle Sound 15085 17645 17440 14338 Tar-Pamlico R. 28382 29976 25055 21612 Neuse River 41668 44641 39992 32044 Pamlico sound 1186 1352 1792 1629 Total Coastal 16271 18996 19232 15967 Total 134068 143222 129097 104595 162 Appendices Appendix 3.4b. Tons of Phosphorus Sold as Fertilizer 1880 1890 1900 1910 1920 Chowan River 432 930 2293 5228 6639 Roanoke River 601 1294 3192 7280 9245 Albemarle Sound 81 175 432 985 1251 Tar-Pamlico R. 334 720 1776 4049 5142 Neuse River 500 1077 2656 6058 7692 Pamlico Sound 7 16 39 90 114 Total Coastal 89 191 471 1075 1365 Total 2093 4508 11119 25357 32199 1925 1930 1935 1940 1945 Chowan River 6807 4673 4472 4964 6524 Roanoke River 8961 7604 7424 7756 10490 Albemarle Sound 1094 912 780 1181 1525 Tar-Pamlico R. 5073 4379 3956 3891 5250 Neuse River 7256 6282 5942 5728 7915 Pamlico sound 121 105 177 162 156 Total Coastal 1215 1017 957 1344 1680 Total 31237 25885 24686 25623 33804 1950 1954 1959 1964 1969 Chowan River 6970 10442 9505 9480 7858 Roanoke River 11574 14242 13863 14705 13369 Albemarle Sound 1830 1816 1852 2123 2557 Tar-Pamlico R. 6005 6580 6521 7225 5752 Neuse River 9569 9840 9795 10736 10071 Pamlico Sound 175 221 226 211 251 Total Coastal 2005 2036 2078 2334 2808 Total 38073 45095 43721 46443 41827 1974 1978 1982 1987 Chowan River 6208 5921 5150 3486 Roanoke River 9583 9309 7577 6016 Albemarle Sound 4503 4630 4135 3194 Tar-Pamlico R. 8473 7866 5941 4814 Neuse River 12440 11714 9482 7138 Pamlico Sound 354 355 425 363 Total Coastal 4858 4985 4560 3557 Total 43535 41773 34691 26998 AppendIces 163 Appendix 3.5a. Bales of Cotton 1880 1890 1900 1910 1920 Chowan River 36767 17971 24443 23821 44543 Roanoke River 27184 16805 25959 30617 37445 Albemarle sound 9611 8063 10229 13407 22855 Tar-Pamlico R. 81565 50841 65111 98006 134161 Neuse River 104197 80523 100556 138952 178777 Pamlico Sound 1372 927 711 4175 5699 Total Coastal 10983 8991 10939 17582 28554 Total 260696 175131 227008 308979 423480 1925 1930 1935 1940 1945 Chowan River 62331 63383 60825 30970 50064 Roanoke River 51462 49041 40055 15141 38501 Albemarle Sound 21117 11432 13047 3860 12446 Tar-Pamlico R. 136751 88898 82523 30050 79109 Neuse River 157801 101745 97313 38709 96914 Pamlico sound 2047 1910 1650 956 1783 Total Coastal 23164 13342 14697 4816 14229 Total 431509 316410 295412 119687 278818 1950 1954 1959 1964 1969 Chowan River 33778 27508 28154 46517 15124 Roanoke River 32947 26910 23232 41056 13013 Albemarle sound 4703 3356 3398 2852 498 Tar-Pamlico R. 73595 50830 44815 63826 16269 Neuse River 84040 60573 47930 35551 3744 Pamlico Sound 311 167 145 51 3 Total Coastal 5014 3523 3543 2904 501 Total 229374 169343 147674 189854 48651 1974 1978 1982 1987 Chowan River 17378 4908 14419 18017 Roanoke River 14924 4351 10608 15148 Albemarle Sound 578 168 2540 5214 Tar-Pamlico R. 20060 8293 17559 21897 Neuse River 1485 264 891 2965 Pamlico Sound 0 0 0 0 Total coastal 578 168 2540 5214 Total 54424 17985 46017 63241 164 Appendices Appendix 3.5b. Bushels of Corn 1880 1890 1900 1910 1920 Chowan River 2580321 1783225 3395444 3029246 3990502 Roanoke River 6390943 5835343 8012306 7472801 7608621 Albemarle Sound 1652943 1310229 1618098 1087012 1682459 Tar-Pamlico R. 2374348 1798219 3051659 2858427 3932986 Neuse River 3208132 2846654 4335728 5076657 6465703 Pamlico sound 181492 183185 153446 308657 361435 Total Coastal 1834435 1493414 1771543 1395669 2043894 Total 16388179 13756855 20566681 19832800 24041707 1925 1930 1935 1940 1945 Chowan River 2704572 3372395 3435016 4376747 4513973 Roanoke River 6613568 7331185 6806592 7816335 8130134 Albemarle Sound 1344970 1308184 2008679 2494120 2401026 Tar-Pamlico R. 2698231 3420667 4433788 5611212 5099416 Neuse River 4341535 5559168 6597272 8809941 8084821 Pamlico Sound 232955 275169 286255 405263 263539 Total Coastal 1577925 1583353 2294934 2899383 2664564 Total 17935831 21266768 23567602 29513618 28492908 1950 1954 1959 1964 1969 Chowan River 6494775 5738784 7201377 6818532 9302938 Roanoke River 9233717 6868661 8226236 10379137 6443124 Albemarle Sound 2587068 3894377 6213976 5801976 6540886 Tar-Pamlico R. 7644613 6476970 11018351 9463849 10394339 Neuse River 12148043 8885929 17251153 19536249 19426012 Pamlico Sound 245768 443082 628593 780275 865986 Total Coastal 2832835 4337460 6842569 6582251 7406871 Total 38353983 32307804 50539686 52780018 52973285 1974 1978 1982 1987 chowan River 13611823 15785668 16169257 5953410 Roanoke River 9492475 11544728 12593749 4748006 Albemarle sound 10990675 13156736 15444793 7250844 Tar-Pamlico R. 14698451 17080824 18367998 9900133 Neuse River 24502563 24347440 29374311 13487117 Pamlico sound 1489838 1484495 2362476 1319660 Total Coastal 12480513 14641231 17807269 8570504 Total 74785826 83399891 94312584 42659170 Appendices 165 Appendix 3.5c. Tons of Corn Silage 1880 1890 1900 1910 1920 Chowan River Roanoke River Albemarle sound Tar-Pamlico R. Neuse River Pamlico Sound Total Coastal Total 1925 1930 1935 1940 1945 Chowan River 4075 9046 8955 Roanoke River 28929 37497 36250 Albemarle Sound 352 1053 1656 Tar-Pamlico R. 1589 3387 3601 Neuse River 4220 7519 10073 Pamlico Sound 0 2 4 Total Coastal 352 1056 1661 Total 39164 58505 60540 1950 1954 1959 1964 1969 Chowan River 14835 30458 37518 77414 90188 Roanoke River 55945 96680 135691 321846 542101 Albemarle Sound 3163 2629 3825 8318 12606 Tar-Pamlico R. 5790 15341 27109 40897 83793 Neuse River 8334 26652 40248 82221 145385 Pamlico Sound 5 215 2304 3684 6678 Total Coastal 3168 2844 6129 12002 19284 Total 88071 171975 246695 534379 880750 1974 1978 1982 1987 Chowan River 98726 91645 90982 45867 Roanoke River 519828 625478 588957 340074 Albemarle Sound 12570 4808 21270 5821 Tar-Pamlico R. 69044 84118 147682 64657 Neuse River 122850 126897 152093 63289 Pamlico sound 6910 4736 6829 1686 Total Coastal 19480 9544 28099 7507 Total 829928 937683 1007813 521393 166 Appendices Appendix 3.5d. Tons of Hay 1880 1890 1900 1910 1920 Chowan River 12159 17826 30547 71328 Roanoke River 56644 74909 100828 267320 Albemarle Sound 2490 3623 5841 16934 Tar-Pamlico R. 6992 10466 17859 43976 Neuse River 11650 14328 29311 49570 Pamlico Sound 237 589 1495 1810 Total Coastal 2728 4212 7336 18743 Total 90172 121742 185881 450937 1925 1930 1935 1940 1945 Chowan River 29560 86940 93913 122374 66452 Roanoke River 121940 136268 165126 259755 294935 Albemarle Sound 14673 17120 23567 20771 18212 Tar-Pamlico R. 20900 36523 93189 93189 105376 Neuse River 30521 44008 98366 131238 126279 Pamlico Sound 1323 1358 3530 2039 1666 Total Coastal 15995 18478 27097 22810 19878 Total 218917 322217 477690 629366 612920 1950 1954 1959 1964 1969 Chowan River 53629 63377 56810 47990 31850 Roanoke River 331596 301569 310592 214602 210094 Albemarle sound 2733 7707 3599 4405 2187 Tar-Pamlico R. 60710 71853 57547 27453 19347 Neuse River 93879 66066 45361 30035 26618 Pamlico Sound 666 648 528 460 748 Total Coastal 3399 8354 4126 4865 2934 Total 543214 511219 474435 324946 290844 1974 1978 1982 1987 Chowan River 32328 34199 43668 46380 Roanoke River 225393 242063 271379 288225 Albemarle sound 2642 1344 719 1824 Tar-Pamlico R. 18052 25816 24680 35723 Neuse River 30047 44757 42492 42408 Pamlico Sound 685 988 331 395 Total Coastal 3327 2332 1050 2219 Total 309148 349167 383269 414954 Appendices 167 Appendix 3.59. Bushels of Oats 1880 1890 1900 1910 1920 Chowan River 386707 341517 168181 136679 35084 Roanoke River 1886163 1722809 1123882 678405 301943 Albemarle Sound 67624 90663 35006 34214 21984 Tar-Pamlico R. 305308 381034 191441 150210 70350 Neuse River 298664 389653 243286 268022 111296. Pamlico Sound 11966 24361 20204 22626 24813 Total Coastal 79590 115024 55209 56839 46797 Total 2956432 2950038 1781999 1290156 565470 1925 1930 1935 1940 1945 Chowan River 11755 17703 12581 23608 65555 Roanoke River 111841 82064 107769 158210 239399 Albemarle Sound 8714 7097 5703 14107 57463 Tar-Pamlico R. 13085 14935 31859 113601 281787 Neuse River 13274 22805 23259 120010 240640 Pamlico Sound 19932 15177 7677 52219 49859 Total Coastal 28645 22275 13379 66327 107322 Total 178600 159782 188846 481756 934704 1950 1954 1959 1964 1969 Chowan River 131267 310629 279104 127631 151914 Roanoke River 409194 948772 831315 827771 456825 Albemarle Sound 35936 88759 91170 275456 512172 Tar-Pamlico R. 242227 692799 646177 344859 359026 Neuse River 355281 1040658 878348 555153 572605 Pamlico Sound 38041 55422 30892 25327 64176 Total Coastal 73977 144181 122062 300783 576348 Total 1211947 3137038 2757007 2156197 2116718 1974 1978 1982 1987 chowan River 63068 55811 47604 15388 Roanoke River 326768 349033 248465 204652 Albemarle Sound 128250 104960 61917 108318 Tar-Pamlico R. 133162 248459 430836 338685 Neuse River 323151 666404 467676 539835 Pamlico sound 11598 7926 19304 2918 Total Coastal 139848 112885 81221 111236 Total 985997 1432592 1275801 1209796 168 Appendices Apendix 3.5f. Pounds of Peanuts 1880 1890 1900 1910 1920 Chowan River 868127 3435236 4574972 6289441 Roanoke River 54276 1016758 1746418 1934532 Albemarle Sound 44089 283921 368065 502844 Tar-Pamlico R. 54415 774099 1309557 919211 Neuse River 22242 116395 252704 45432 Pamlico Sound 346 704 2159 189 Total Coastal 44436 284625 370224 503033 Total 1043496 5627113 8253875 9691649 1925 1930 1935 1940 1945 Chowan River 4852267 7857887 8376692 203529487 209273601 Roanoke River 2222494 2907866 3541864 79771795 94679528 Albemarle Sound 637763 852723 1078052 24067774 30077984 Tar-Pamlico R. 1090946 2058876 2627873 63326752 79864486 Neuse River 57752 195316 200009 4477110 10743407 Pamlico Sound 318 868 2451 3481 16196 Total Coastal 638081 853591 1080504 24071255 30094179 Total 8861541 13873536 15826942 375176399 424655202 1950 1954 1959 1964 1969 Chowan River 207193638 160840580 204276530 237366038 282612868 Roanoke River 69206953 67487920 72818431 101851750 109207568 Albemarle Sound 15156266 14887880 15074636 22544474 23070871 Tar-Pamlico R. 53779524 51555148 61993240 88275842 79416764 Neuse River 4500102 4382160 5781551 7612521 8283414 Pamlico sound 2451 5188 462 348 1139 Total coastal 15158717 14893068 15075098 22544821 23072011 Total 349838934 299158876 359944850 457650973 502592624 1974 1978 1982 1987 Chowan River 328300754 382115025 341206623 295386590 Roanoke River 111797996 135771715 127294528 124277990 Albemarle Sound 22639236 25969901 25345996 27115030 Tar-Pamlico R. 89562118 146562587 98692782 92197940 Neuse River 6998270 35740533 8806143 7797900 Pamlico sound 216 0 0 0 Total Coastal 22639452 25969901 25345996 27115030 Total 659298589 726159761 601346070 546775450 Appendices 169 Appendix 3.5g. Bushels of Soybeans 1880 1890 1900 1910 1920 Chowan River 45548 Roanoke River 9584 Albemarle Sound 289658 Tar-Pamlico R. 60596 Neuse River 46004 Pamlico Sound 42957 Total Coastal 332615 Total 494347 1925 1930 1935 1940 1945 chowan River 34323 46794 52104 116156 Roanoke River 29069 33684 47453 42204 Albemarle Sound 464078 537930 704247 731619 Tar-Pamlico R. 104572 170183 361723 283479 Neuse River 163651 167586 250994 192794 Pamlico Sound 93359 53649 58735 83836 Total Coastal 557437 591579 762982 815455 Total 889052 1009827 1475255 1450089 1950 1954 1959 1964 1969 Chowan River 236466 465038 1487899 1518075 2045949 Roanoke River 112219 275584 602187 704143 1178296 Albemarle Sound 1316943 1693153 1866033 2368258 3475810 Tar-Pamlico R. 666069 1022885 1866714 2617079 3062273 Neuse River 368139 375981 1089787 2778967 2760935 Pamlico Sound 139682 230326 351806 447476 536108 Total Coastal 1456625 1923479 2217839 2815733 4011918 Total 2839518 4062966 7264427 10433998 13059371 1974 1978 1982 1987 chowan River 2929171 3512261 4828998 3557430 Roanoke River 1723080 2187226 2924666 2196480 Albemarle Sound 3817049 4533536 5479864 4025264 Tar-Pamlico R. 3540330 4791327 6084392 4482856 Neuse River 4245568 5236890 7366296 5374026 Pamlico Sound 497502 702853 935811 719397 Total Coastal 4314551 5236389 6415675 4744661 Total 16752701 20964094 27620026 20355453 170 AppendIces Appendix 3.5h. Pounds of Tobacco 1880 1890 1900 1910 1920 Chowan River 6269098 4220492 13699551 15876712 16265270 Roanoke River 56073138 42368301 91989652 86590815 93269843 Albemarle Sound 1212 0 18840 10635 238419 Tar-Pamlico R. 2757909 4760453 31558725 26181703 64068964 Neuse River 2892930 4103194 38346601 45289260 98497641 Pamlico Sound 937 0 17187 7991 189562 Total Coastal 2149 0 36027 18626 427981 Total 67995224 55452441 175630555 173957115 272529699 1925 1930 1935 1940 1945 Chowan River 18424320 22331862 15855802 32123338 31517197 Roanoke River 149172059 135730521 100850413 167347622 159318828 Albemarle sound 326747 583447 515514 4923557 1048656 Tar-Pamlico R. 46043627 88175177 77013284 126920402 118536048 Neuse River 78861495 145151157 129685318 217519328 199018836 Pamlico sound 408669 234638 169135 681150 489941 Total Coastal 735416 818085 684649 5604707 1538597 Total 293236916 392206802 324089466 549515398 509929506 1950 1954 1959 1964 1969 Chowan River 28969457 30041395 29734396 38666393 28165711 Roanoke River 149750682 174097894 140131708 202389028 152428157 .Albemarle Sound 836629 1710682 1793296 2562191 1122894 Tar-Pamlico R. 117955288 138088449 110966851 154115035 113444082 Neuse River 179626088 234193810 183553067 260415723 182744698 Pamlico Sound 459520 905577 2329885 3223609 546659 Total Coastal 1296149 2616258 4123181 5785800 1669553 Total 477597644 579037806 468509202 661371979 478452200 1974 1978 1982 1987 Chowan River 31000432 32375653 26119977 24507040 Roanoke River 158764930 176451829 143526408 94965940 Albemarle sound 874867 1474616 1212179 818740 Tar-Pamlico R. 104214173 118533466 115527339 76950630 Neuse River 213084360 243842750 204103936 136178610 Pamlico Sound 591018 914422 555941 439710 Total Coastal 1465886 2389038 1768121 1258450 Total 508529780 573592737 491045782 333860670 Appendices 171 Appendix 3.5i. Bushels of Wheat 1880 1890 1900 1910 1920 Chowan River 213776 159017 171018 128393 156907 Roanoke River 1235672 1507691 1367172 1472155 2131825 Albemarle Sound 40203 3956 997 355 3511 Tar-Pamlico R. 169908 120911 68390 53916 94652 Neuse River 306268 304797 179663 133703 191829 Pamlico Sound 5779 436 453 258 1275 Total Coastal 45982 4392 1450 613 4785 Total 1971605 2096808 1787693 1788781 2579998 1925 1930 1935 1940 1945 Chowan River 140283 258350 194871 158889 336152 Roanoke River 1320564 1400670 1333794 1214630 1681375 Albemarle sound 1913 294 1092 719 16616 Tar-Pamlico R. 21900 37910 156452 106429 312899 Neuse River 72842 94246 164333 147263 644666 Pamlico Sound ill 0 26 12 2500 Total Coastal 2024 294 1118 731 19116 Total 1557614 1791470 1850568 1627942 2994209 1950 1954 1959 1964 1969 Chowan River 236507 350810 263400 344314 629845 Roanoke River 1666350 1879971 1390338 1741241 1563666 Albemarle Sound 1402 30130 1402 664247 959675 Tar-Pamlico R. 115155 315693 115555 603972 848491 Neuse River 214187 514359 214437 1162102 1060861 Pamlico Sound 871 5492 871 77881 77890 Total Coastal 2273 35622 2273 742128 1037566 Total 2234472 3096455 1986003 4593758 5140428 1974 1978 1982 1987 Chowan River 1055139 324018 1970039 1245035 Roanoke River 2161180 896969 2460805 2027765 Albemarle Sound 1033841 477510 2975475 2653952 Tar-Pamlico R. 998769 514940 3092312 2684475 Neuse River 1252918 602222 3258152 3156290 Pamlico Sound 130467 68359 417439 361765 Total Coastal 1164308 545869 3392914 3015717 Total 6632315 2884017 14174221 12129282 172 Appendices Appendix 3.6. Crop Yields, calculated by dividing harvest by harvested acres 1880 1890 1900 1910 1920 COTTON (lb/acre) 222 134 247 262 347 CORN (bu/acre) 11.9 10.6 13.8 14.7 18.2 HAY (tons dry/acre) 0.91 1.01 0.96 1.85 OATS (bu/acre) 8.7 9.0 10.2 12.8 13.6 PEANUTS (lb/acre) 523 851 748 1110 SILAGE (tons green/acre) SOYBEANS (bu/acre) 11.1 TOBACCO (lb/acre 519 394 636 583 552 WHEAT (bu/acre) 6.7 8.2 6.7 8.8 10.3 1925 1930 1935 1940 1945 COTTON (lb/acre) 248 219 350 230 490 CORN (bu/acre) 16.8 19.7 18.0 21.6 22.1 HAY (tons dry/ac 0.84 0.75 0.77 0.92 1.22 OATS (bu/acre) 17.9 17.2 18.3 29.0 27.9 PEANUTS (lb/acre 924 1157 1237 1176 1196 SILAGE (tons gre 6.84 7.48 8.35 SOYBEANS (bu/acre) 9.0 6.1 6.0 3.9 TOBACCO (lb/acre 693 640 821 912 1045 WHEAT (bu/acre) 11.2 10.7 9.5 11.9 16.9 1950 1954 1959 1964 1969 COTTON (lb/acre) 338 403 423 502 327 CORN (bu/acre) 30.9 26.0 41.0 63.7 72.6 HAY (tons dry/ac 1.15 0.91 1.13 1.15 1.55 OATS (bu/acre) 28.1 34.8 38.4 58.6 62.5 PEANUTS (lb/acre 1163 1326 1595 1981 2115 SILAGE (tons gre 9.35 7.77 9.68 11.55 11.79 SOYBEANS (bu/acr 16.8 18.2 22.3 23.1 26.5 TOBACCO (lb/acre 1060 1151 1381 2179 1800 WHEAT (bu/acre) 17.5 23.8 9.5 30.7 45.0 1974 1978 1982 1987 COTTON (lb/acre) 461 598 597 496 CORN (bu/acre) 77.9 79.5 99.9 57.8 HAY (tons dry/ac 1.62 1.59 1.64 1.66 OATS (bu/acre) 53.4 54.3 60.6 62.3 PEANUTS (lb/acre 2413 3066 2722 2664 SILAGE (tons gre 13.54 13.32 14.89 9.37 SOYBEANS (bu/acr 24.4 23.8 26.3 24.0 TOBACCO (lb/acre 1883 1952 2026 2115 WHEAT (bu/acre) 36.0 30.5 33.7 42.6 VELSL 6VEGE V9GE:! 89Z9T LS6Gt, C89tZT TV-40'L 9sov 68L9 ETLE ZG8T VTOV 6ZIPET Tle-48leOD LESZZ SZ60T 99Z9 EETV 6L80T tPL9Zt asnaN 8TEZ 919E L89Z 81ZZ ZEOL 896TZ alel LOE8Z IL86 8TV9 T68S: TL98T SELZE 83[ouleo-d LTSTZ Mt, TOSt DILTZ T9ES L88ET ulemoq:) ZVS6T ZOS6T HSV6T OV6T SE6T ROM SAHXdflL 60VEOZ VETZ9Z TZOT6T 60666 09LC9T 09LE9T Tle-401 DIDIBZZ 89ZZE OE96T Z089 OT9LT OT9LT TV-48900 OLD,TPL 99Z90T 866L9 OEL6Z 8899C 898GE asnaN V889E OT8TG ZZ09E SEZOZ L8ZSZ L8ZGZ ael 66L9V C9809 6 ZD,9 D, 966TE SOPLS SOVLS 03[ouvo-d ZIDIZZ 8E60E zvolz GVTTT TLSLZ TLSLZ ulemolqo ZSZ6T OZ6T ZOT6T 006T 068T H0881 SAaxldflLL T9E8TVT VOTESET 6G8LEZT tZLLS6 ECOZ96 VSOTOL CGEOSOT Tle-401 06TT76T TZ9V8T 609t8T OT6LOT tIEL6 96869 LOST8 -re-4seoo LTSEES 6VZ9Zt, EMET, TE69ZE OLZSTE VZVVOZ E8L80E asneN 891ZZE SL9TVE SOZZEZ L9VELT OSSLST T,6E9ZI 6ozooz xej TOZSST VE668T E6999T LLEEET 9ZS6DT 9T9EET 909zzz 93(OUVO-d s;szclz VZ90TZ 699EZZ 6EO9TZ ZLEZEZ CZL99T 9tZLEZ UVIAotio L861 Z80T 8L6T VL6T 696T 1796T 6S6T HNIMS 69STOOT OOL606 LTZ69L EOLOTS ELVEZ9 Z6968S -Ele4ol ETLS8 OT88L 99TDL TS89V ZOO19 96LTL Tie-4sleoo 06TL9Z 6TZSVZ TEOL6T OULST 96E9ST 8TOEtPI asn9N L8Z69T 6696ST 8LIPLZT TOST6 88860T 96VE6 alej, Z8STTZ 6GZ96T Z9E9ST 990EZT 9ZZttT ULM 03[OUVOU 96LL9Z ET86ZZ 08TT70Z S9tT6 09STST T8S8ET uiemotio f,S6T OS6T Sf,6T OV6T SC6T OC6T HNIMS OT9969 890098 Lf,6ZLL L8ZL8L SOZIT9 ESEVLL -Ev-401 ISD,t,L E9ZO6 886PL ZTL89 T89D,9 9PEOL Tie4sleoo LZT9ST LBTLTZ VZEIZZ TLZITZ 968891 E919OZ asnam ZOES6 6GL9VT ECTOET E98ZET 9LVOOT c8tp8zl avii E6LZf,T VLLSOZ T0898T ZTEVIZ 898TST L880tZ 93jouleou 9C69ZT 9LO06T TOL6ST BZT091 V8ZS6 tLtp8ZT ULAoqo SUT ONT OUT 006T 068T 088T SNIMS u-rsles/-EleurTuV anjUA P;DILIIUIISQ S91BO[PUl 'uisLq ooilEuud-;)IjLEuaqlV aqj ui slumpe uuLj jo AloluaAul TC XIPUeddV UL sE)c)lpueddV 174 Appendices Appendix 3.7. Continued Animal/Basin Year TURKEYS 1959E 1964E 1969 1974 1978 1982 1987E chowan 4241 12359 40 30 143 40 68 Roanoke 11245 10567 1153 592 1421 716 1217 Tar 4812 26547 149 1726 384445 210164 357279 Neuse 17850 21765 64491 123743 612472 1006477 1711011 Coastal 12724 17827 2 41 0 0 0 Total 50871 89065 65834 126132 998480 1217397 2069575 SHEEP 1880 1890 1900 1910 1920 1925 Chowan 22798 25089 19014 14766 7665 5154 Roanoke 67916 62638 56381 50636 19130 18024 Tar 21433 18769 14146 8721 4588 2942 Neuse 32793 25000 16497 8159 3165 2398 coastal 10967 12390 12057 15587 10398 5406 Total 155907 143886 118095 97870 44946 33924 SHEEP 1930 1935 1940 1945 1950 1954 Chowan 9446 6328 4114 4063 4011 5518 Roanoke 34171 18572 12896 10393 12732 9781 Tar 4108 3755 2561 3039 2570 2665 Neuse 2954 2306 1731 1868 1879 1899 coastal 11856 8128 6177 6596 6114 4861 Total 62534 39089 27479 25960 27306 24724 SHEEP 1959 1964 1969 1974 1978 1982 1987E Chowan 5700 4218 3594 1759 2271 3107 3107 Roanoke 12075 7683 6467 5483 4716 4141 4141 Tar 2848 1440 640 325 66 149 149 Neuse 3077 1787 1613 1054 328 865 865 Coastal 3297 2701 1504 657 902 525 525 Total 26997 17829 13819 9277 8283 8786 8786 MULES 1880 1890 1900 1910 1920 1925 Chowan 5789 5674 7425 9905 26089 25321 Roanoke 15079 16212 17910 23645 42357 44583 Tar 8108 8768 10344 14462 26915 30100 Neuse 11385 13610 19212 25107 45625 46320 Coastal 2432 2362 2761 2998 6666 8412 Total 42793 46627 57652 76117 147654 154735 Appendices 175 Appendix 3.7. Continued Animal/Basin Year MULES 1930 1935 1940 1945 1950 1954 Chowan 27166 26612 28341 26372 23506 15614 Roanoke 52385 51350 57500 52596 52634 39347 Tar 37227 36208 38848 36516 40077 29871 Neuse 50469 50681 54213 52153 52364 35229 Coastal 9110 9689 8891 6793 3943 2050 Total 176356 174540 187793 174430 172523 122112 MULES 1959E 1964E 1969 1974 1978 1982 1987E Chowan 10699 5784 869 236 86 9 9 Roanoke 27702 16057 4412 1324 639 134 134 Tar 20817 11763 2709 488 208 42 42 Neuse 24003 12777 1551 217 115 9 9 Coastal 1378 706 33 1 1 0 0 Total 84600 47087 9574 2266 1049 194 194 HORSES 1880 1890 1900 1910 1920 1925 Chowan 14268 14313 21887 22308 20566 14696 Roanoke 39600 41003 54279 58562 59183 47397 Tar 11230 10630 16385 16995 17293 11416 Neuse 15208 13222 16704 18966 19236 12975 Coastal 6144 6919 8285 8927 8671 7137 Total 86450 86087 117541 125757 124949 93620 HORSES 1930 1935 1940 1945 1950 1954 Chowan 9728 6094 5881 6539 7043 3820 Roanoke 35106 23388 23173 24847 25460 17595 Tar 7127 3960 3552 3889 4628 3507 Neuse 8016 4776 3801 4649 5895 4485 Coastal 4642 3546 2997 2721 2440 1222 Total 64620 41764 39404 42646 45466 30629 HORSES 1959E 1964E 1969 1974 1978 1982 1987E Chowan 2751 1683 614 1434 1319 1555 1555 Roanoke 12603 7611 2619 5743 5407 6099 6099 Tar 2607 1707 806 1081 1213 1154 1154 Neuse 3364 2242 1121 2111 2459 2708 2708 Coastal 868 514 160 326 288 324 324 Total 22193 13757 5321 10694 10685 11841 11841 068VLV OLLLSE OLZTSE 68609Z 9MOC 09T60Z -[vqoL 6E9TZ ZTM 0688T MET 09ZST t6vzT lvqgTaoo VTOT8 889ts Z99LS TOZZt 86s9s SS9ZE esneN 69L69 6860v 9ZOEV S680E 8LZ6E TVZTZ .77al S16LEZ Z8T86T 6S6ZST E086ET 6VLZST 86VVTT G%ouleo-d ESSPL OOL6V EELSD, 09ZVE TSS6E ZLZ8Z uvmoqo D,96T OS6T 061 ot6T SE61 OC6T zrllLVD LVLLtZ T968TE OEME E6S9TE C98LTE 99SLSE Tv-40I SUPT OSZEZ ZTOLZ E9ELZ ZZSOE TLSTE. -Ev4svoo 8060V V9ZTS S668S VSEVS TSOSS OSLvL esnaN LZS8Z SZELE GLOP 666EV OTZTV 698LS aVI EEZ8ZT OOE8ST LZSPST S80SET LSLZET t6ZLET 63[ouleo-d C98SE 8188v TZSSS Z6LSS EMS 0809S upmoqo SUT OUT 0161 006T 06ST 088T SUM 8L6VVL8T L8S9EL9T EV966TST TtOSOVS 8E9E8SV OOT06ZV 898TZLV TV-401 TTELOVT SZ999ZT 800868 t,6LEST 99DI09T E6ZZCZ Et6lZC TV48VOD OVEZVOV ZEZ609E Z866S8V 6TZE19E 0869T6T E9ZL6VT 6VSVSVT asneN 66EL6Z9 LL9ZZ9S 6OE9ETE 6SE6V8T SZE868 TZP989 ZE6T9L aVI ZVSE09E 9TLLTZE 88EL8EE SSTSS6T 89ZSSZT t6E68ET 99SSZ9T 8:40uleO'd L8OV6EE PEVOEOE 9S6LT6Z VSVEE8 019ZSC OELV8V 888VSS UL*Aoqo HL86T Z86T 8L6T tL6T 696T 096T 6G6T SNZXDIHO 80VVVSV ZSZELEV OLLEVLS 8OLVE8E Z8tT6ZS TOME TV401 SS99LZ TLZVLZ 69VOOV 9E610C LE968t 8VSV6Z T94svOO L89EOVT 8VETZZT OT908ST 6SBEV6 SL89EZT OVLZES esnoN 896tTL OL86EL V06SP6 8LTS19 LT9TO8 STOLVS avL ZMtST VTEVZST L88ZTOZ 8VZ6StT OT6SELT LSTS6ET 95[OuvO-d 9L966S OStET9 006EO8 LSMS MLZOT 6L98SS uvmolqo tS6T OS6T MT Ot6T SE6T OE6T SNHXDIHO 9S6T80 THEM tSLETOE 60666ZZ ZSSME 90Z691 [leqol 9TELLE 99SZtE OSLOSZ 18TOZZ OTtStE 88T98T TVISVOO 8868tll Z98EZOT tZTSOL 08S99t 89SBES 99ETSE asnem 6MLL OT8OL9 OZEL9t 8080SE E86LZG 69t99Z aVj tT686LT T908tST 9896ZTT 689EL8 OtMT TES609 8310uvo-d 60EZ89 Z86LE9 MM OS98SE MM EUM uvmoqo SZ61 OZ61 OT6T 006T 0681 088T SNZXDIHO uTsvg/TlewTuY penulluo:D TC XIPUeddV sgolpueddV 9LI Appendices 177 Appendix 3.7. Continued Animal/Basin Year CATTLE 1959 1964 1969 1974 1978 1982 1987 Chowan 60893 65341 61632 72546 56612 61250 76640 Roanoke 220866 229758 245456 313944 257871 303281 356357 Tar 52409 59887 51059 63681 46568 44567 53464 Neuse 64633 74388 70624 78839 70559 71233 70686 Coastal 16617 21240 18266 18783 11102 8325 11092 Total 415418 450613 447037 547792 442712 488656 568239 BROILERS 1880E 1890E 1900E 1910E 1920E 1925E Chowan 0 6628 13255 19883 26511 29824 Roanoke 0 44999 89998 134998 179997 202496 Tar 0 48325 96650 144974 193299 217461 Neuse 0 119239 238477 357716 476954 536574 Coastal 0 232 463 695 926 1042 Total 0 219422 438843 658265 877687 987398 BROILERS 1930E 1935E 1940E 1945E 1950E 1954E Chowan 33138 36452 39766 43080 46394 49045 Roanoke 224996 247496 269995 292495 314994 332994 Tar 241624 265786 289949 314111 338273 357603 Neuse 596193 655812 715432 775051 834670 882366 Coastal 1158 1273 1389 1505 1621 1713 Total 1097109 1206820 1316530 1426241 1535952 1623721 BROILERS 1959E 1964E 1969 1974 1974 1982 1987E Chowan 52358 55672 58986 405246 2527410 2934388 3667985 Roanoke 355494 377993 400493 417427 2073553 2327470 2909337 Tar 381766 405928 430090 384696 1016318 2745128 3431410 Neuse 941985 1001604 1061223 1382506 1963347 3868738 4835922 Coastal 1829 1945 2061 78521 805238 1217358 1521697 Total 1733432 1843143 1952853 2668395 8385866 13093081 16366351 178 Appendices Appendix 3.8. Annual nitrogen and phosphorus production (kg/year) by farm animals in the Albemarle-Pamlico basin (1880-1987). Nutrient/Basin Year NITROGEN 1880 1890 1900 1910 1920 1925 Chowan 6302054 6228903 7108818 7265782 7944822 6071906 Roanoke 14879492 14540027 15308356 16804815 18221559 15269092 Tar 6378220 5152520 5951295 6364301 6689057 5437007 Neuse 8852011 7437139 8092455 9057791 9733398 8145700 Coastal 3414161 3412757 3257875 3409853 3548036 2776870 Total 39825938 36771346 39718799 42902541 46136873 37700574 NITROGEN 1930 1935 1940 1945 1950 1954 Chowan 5540085 6437336 5155960 7508731 7658501 9177731 Roanoke 14073506 15969026 14980296 18230935 19444816 21159331' Tar 4961073 6220553 5471179 6764858 7111455 7869522 Reuse 7242715 8962816 8043846 9806272 10090225 11276384 Coastal 2538904 2823247 2188981 2781296 2328735 2720594 Total 34356283 40412979 35840263 45092092 46633732 52203562 NITROGEN 1959 1964 1969 1974 1978 1982 1987 Chowan 7635426 6759978 6937741 7830546 8933804 9305266 10797441 Roanoke 19495283 18066928 18379813 22867892 21155313 24296835 27655762 Tar 7355499 6470679 5913871 7317532 8430494 11444897 12622176 Neuse 10226898 9067086 9893474 11685701 14013146 14601000 17430805 Coastal 2336814 2391444 2411419 2597154 3736367 3927342 4420564 Total 47049920 42756116 43536318 52298825 56269125 63575340 72926749 PHOSPHORUS 1880 1890 1900 1910 1920 1925 Chowan 1687262 1664229 1955084 2151673 2182893 1682618 Roanoke 3911243 3821383 4039684 4518506 4732874 4022536 Tar 1714675 1413390 1664164 1858726 '1873610 1553401 Neuse 2433313 2114302 2304296 2730436 2694946 2274100 Coastal 919114 926708 883378 969992 1012074 797343 Total 10623434 9818735 10643488 11442435 12418499 10092167 PHOSPHORUS 1930 1935 1940 1945 1950 1954 Chowan 1535994 1821381 1359372 2081977 2084575 2531156 Roanoke 3610253 4160759 3755277 4661720 4824546 5273977 Tar 1330043 1704605 1433532 1876072 1837216 2039961 Neuse 1970498 2452351 2153667 2692247 2611209 3000478 Coastal 727860 777248 579855 756408 658424 773717 Total 9194633 10770553 9428702 12089393 12570494 14031928 Appendices 179 Appendix 3.8. Continued Nutrient/Basin Year PHOSPHORUS 1959 1964 1969 1974 1978 1982 1987 Chowan 2117461 1852749 1983687 2200765 2582615 2653854 3024132 Roanoke 4896531 4521467 4624691 5715358 5428682 6191163 6953380 Tar 1964310 1731155 1666269 2089553 2588221 3561435 3877072 Neuse 2811170 2493617 2900085 3464430 4332556 4430399 5403074 Coastal 682272 679787 715638 772850 1188220 1251666 1387302 Total 12884382 11361302 11906450 14246302 16122645 18088517 20647094 86968T LLTLZL ESLZET 988809 LZLO8 ZSV60E 0 0 -[P-401 0 0 0 0 0 0 0 0 TleTa4snpui 8696ST LLTLZL ESLZET 98880S LZLO8 ZSV60E 0 0 IledToTunH qV1101 d/V MOOT S698E 8T9L IOZ6Z T06E SS6VT 0 0 Ile-4ol 0 0 0 0 0 0 0 0 Tie-p-4snpui V600T 9698C 819L TOZ6Z T06E SGOT 0 0 TiedTOTunK 7visvoo TS699 St99SZ 68tEV 60L99T 9699Z 9EEZOI 0 0 IR-401 0 0 0 0 0 0 0 0 TPTiqsnpui TS699 Gt99SZ 68tEt 60L99T 9699Z 9EEZOT 0 0 TedTOTunN asnam scost, EE9ZLI ZESOZ 90L8L 8TS8 TS9ZE 0 0 'p-461 0 0 0 0 0 0 0 0 Tv-rzr-4snpui SEOSV EE9ZLT ZESOZ 90M 8TS8 TG9ZE 0 0 TvdTDTunjj Z9T6S 68L9ZZ 86TLS 6SZ6TZ 9EPOV 90OSSI 0 0 -[Vqol 0 0 0 0 0 0 0 0 TieTaqsnpui Z9T6S 68L9ZZ 86TLS 6SZ6TZ 9EVOt 90OSST 0 0 liedTOTunN axoNvoll 9M EIVZE 916E ZIOST SLIT Vost 0 0 TV-401 0 0 0 0 0 0 0 0 TRT:r-4snpuj 9ST78 ETtZE 9T6E ZTOST SLIT Vost, 0 0 liedTOTunN NVMOHD A/f)Xcl A/f)XK A/!)Xcl A/E)XN A/!)Xcl A/f)XN A/!)Xcl A/f)XN 9dAL/UTsieS OT6T OT6T 006T 006T 068T 068T 08ST 088T a5utAas poluoijun ui juoA/uosjad/23j 1-1 puu juoA/uosiad/N 231 9-t, sQwnssV '9861-0881 IsSuipuol aoinos juiod pjuwijs3 .6-1@ xipueddV sao!pueddv 091 Appendices 181 Appendix 3.9. Continued 1920 1920 1930 1930 1940 1940 1950 1950 Basin/Type NKG/Y PKG/Y NKG/Y PKG/Y NKG/Y PKG/Y NKG/Y PKG/Y CHOWAN Municipal 40060 10450 58888 15362 110144 20907 143644 39646 Industrial 0 0 10000 2500 95000 25000 190000 50000 Total 40060 10450 68888 17862 205144 45907 333644 89646 ROANOKE municipal 495599 129287 680745 177586 817491 213258 1017891 265537 Industrial 0 0 100000 35000 336000 64000 336000 64000 Total 495599 129287 780745 212586 1153491 277258 1353891 329537 TAR Municipal 231679 60438 316969 82688 374602 97722 441187 115092 Industrial 0 0 0 0 0 0 0 0 Total 231679 60438 316969 82688 374602 97722 441187 115092 NEUSE municipal 430714 112360 596170 155523 826471 215601 1066754 278284 Industrial 0 0 0 0 0 0 500 0 Total 430714 112360 596170 155523 826471 215601 1067254 278284 COASTAL municipal 69860 18224 78375 20446 90781 23682 99921 26066 Industrial 0 0 0 0 0 0 0 0 Total 69860 18224 78375 20446 90781 23682 99921 26066 A?P TOTAL Municipal 1267913 330760 1731147 451604 2219489 571171 2769397 724625 Industrial 0 0 110000 37500 431000 89600 526500 114600 Total 1267913 330760 1841147 489104 2650489 660771 3295897 839225 182 Appendices Appendix 3.9. Continued 1960 1960 1970 1970 1980 1980 1986 1986 Basin/Type NKG/Y PKG/Y NKG/Y PKG/Y NKG/Y PKG/Y NKG/Y PKG/Y CHOWAN Municipal 174653 48969 151543 48363 144798 47731 148919 47895 Industrial 578000 88800 578000 88800 578000 88800 379000 88800 Total 752653 137769 729543 137163 722798 136531 527919 136695 ROANOKE Municipal 1189291 312130 826474 294070 844729 304012 857012 310711 Industrial 336000 64000 336000 64600 336000 64600 336000 64600 Total 1525291 376130 1162474 358670 1180729 368612 1193012 375311 TAR Municipal 401132 122638 382847 129738 427546 143756 490542 165046 Industrial 0 0 70000 400000 70000 535000 70000 391000 Total 401132 122638 452847 529738 497546 678756 560542 556046 NEUSE Municipal 1138754 335908 1067645 358045 1214426 415634 1490523 510820 Industrial 1000 1200 256229 22277 256200 22277 256200 22277 Total 1139754 337108 1323874 380322 1470626 437911 1746723 533097 COASTAL Municipal 107166 27956 73921 24141 79966 26155 87584 28610 industrial 0 0 0 0 0 0 0 0 Total 107166 27956 73921 24141 79966 26155 87584 28610 A/P TOTAL Municipal 3010996 847602 2502429 854356 2711465 937289 3074580 1063082 Industrial 915000 154600 1240229 575677 1240200 710677 1041200 566677 Total 3925996 1002202 3742658 1430033 3951665 1647966 4115780 1629759 Appendices 183 Appendix 4. 1. Pamlico River estuary sampling dates, parameters sampled, and data sources Abbreviations: ST Surface water temperature (OC) BT Bottom water temperature (OC) SS Surface water salinity (ppt) BS Bottom water salinity (ppt) SDO Surface water dissolved oxygen (mg/liter) BDO Bottom water dissolved oxygen (mg/liter) PH Surface water pH P04 Surface water orthophosphate phosphorus (uM) TDP Surface water total dissolved phosphorus (uM) TP Surface water total phosphorus (uM) PP Surface water particulate phosphorus (uM) N03 Surface water nitrate nitrogen (uM) NH4 Surface water ammonia nitrogen (uM) TDN Surface water total dissolved nitrogen (uM) TN Surface water total nitrogen (uM) PN Surface water particulate nitrogen (uM) CHL Surface water chlorophyll a (ugAiter) Key to data source references (see REFERENCES for full citations): 1. Hobbie (1970b) 2. Hobbie (1970a) 3. Hobbie et al. (1972) 4. Hobbie (1974) 5. Stephenson et al. (1975) 6. ICMR (1976) 7. ICMR (1977) 8. ICMR (1978) 9. ICMR (1980) 10. ICMR (1981) 11. ICMR (1982) 12. ICMR (1983) 13. Stanley (1984b) 14. Stanley (1986a) 15. Stanley (1986b) 16. Stanley (1987) 17. Davis et al. (1978) 18. Kuenzler et al. (1979) Note: The data from 23 October 1978 through 14 December 1978 are in none ofthe reports. I have access to the data however. (D.W.S.) 184 Appendices Appendix 4. 1. Continued Sample Parameters Sampled and Data Sources Date MO DA YR ST BT SS BS SDO BDO PH P04 TDP TP PP M03 NH4 TDN TN PN CHL 3 967 2 2 322 67 2 2 323 67 411 67 2 2 5 967 2 2 1 1 1 6 767 2 2 627 67 2 2 628 67 1 1 1 713 67 2 2 1 1 1 731 67 2 2 1 1 1 823 67 2 2 1 1 1 830 67 2 2 1 1 1 .9 20 67 2 2 1 1 1 10 367 2 2 10 467 1 1 1 10 17 67 2 2 1 1 1 10 30 67 2 2 1 1 1 11 14 67 2 2 1 1 1 11 28 67 2 2 1 1 1 12 19 67 2 2 1 1 1 1 868 2 2 1 1 1 129 68 2 2 1 1 1 213 68 2 2 214 68 1 1 1 226 68 2 2 1 1 1 629 68 2 2 2 2 1 1 1 716 68 2 2 2 2 1 1 1 8 668 2 2 2 2 1 1 1 823 68 2 2 2 2 1 1 1 9 668 2 2 2 2 1 1 1 930 68 2 2 2 2 1 1 1 10 11 68 2 2 2 2 1 1 1 11 21 68 2 2 2 2 1 1 1 12 13 68 2 2 2 2 2 2 1 669 2 2 2 2 2 2 2 669 2 2 2 2 2 2 1 1 1 226 69 2 2 2 2 2 2 1 1 1 4 169 2 2 2 2 2 2 1 1 1 415 69 2 2 2 2 2 2 1 1 1 5 269 2 2 2 2 1 2 1 1 1 6 369 2 2 2 2 2 2 1 1 1 619 69 2 2 2 2 2 2 1 1 1 7 469 2 2 2 2 2 2 1 1 1 Appendices 185 Appendix 4. 1. Continued Sample Parameters Sampled and Data Sources Date MO DA YR ST BT SS BS SDO BDO PH P04 TDP TP PP N03 NH4 TDN TN PN CHL 8 6 69 3 3 3 3 3 3 3 1 1 1 3 3 821 69 3 3 3 3 3 3 3 1 1 1 3 3 9 3 69 3 3 3 3 3 3 3 1 1 1 3 3 917 69 3 3 3 3 3 3 3 1 1 1 3 3 10 1 69 3 3 3 3 3 3 3 1 1 1 3 3 10 17 69 3 3 3 3 3 3 3 1 1 1 3 3 10 29 69 3 3 3 3 3 3 3 1 1 1 3 3 11 12 69 3 3 3 3 3 3 3 1 1 1 3 3 12 3 69 3 3 3 3 3 3 3 1 1 1 3 3 12 15 69 3 3 3 3 3 3 3 1 1 1 3 3 1 2 70 3 3 3 3 3 3 3 1 1 1 3 3 126 70 3 3 3 3 3 3 3 3 3 3 3 3 211 70 3 3 3 3 3 3 3 3 3 3 3 3 225 70 3 3 3 3 3 3 3 3 3 3 3 3 3 311 70 3 3 3 3 3 3 3 3 3 3 3 3 3 325 70 3 3 3 3 3 3 3 3 3 3 3 3 3 4 8 70 3 3 3 3 3 3 3 3 3 3 3 3 3 422 70 3 3 3 3 3 3 3 3 3 3 3 3 3 5 6 70 3 3 3 3 3 3 3 3 3 3 3 3 3 520 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 6 3 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 617 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 7 1 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 715 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 730 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 812 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 826 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 910 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 923 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 10 7 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 10 22 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 11 4 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 11 19 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 12 3 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 12 17 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 12 30 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 114 70 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2 5 71 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 218 71 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 5 71 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 331 71 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 416 71 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 428 71 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 186 Appendices Appendix 4, 1. Continued sample Parameters Sampled and Data Sources Date MO DA YR ST BT SS BS SDO BDO PH P04 TDP TP PP N03 NH4 TDN TN PN CHL 512 71 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 526 71 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 6 9 71 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 624 71 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 7 8 71 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 721 71 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 8 4 71 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 831 71 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 915 71 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 10 6 71 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 10 20 71 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 11 10 71 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 11 23 71 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 12 13 71 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 1 4 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 119 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 2 3 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 223 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 8 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 323 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 419 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 522 72 4 4A 4 4 4 4 4 4 4 4 4 4 4 4 614 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 719 72' 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 8 9 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 9 7 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 10 5 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 10 18 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 11 1 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 12 6 72 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 119 73 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 221 73 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 321 73 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 73 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 419 73 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 7 9 73 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 726 73 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 822 73 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 127 75 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 214 75 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 228 75 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 328 75 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 Appendices 187 Appendix 4. 1. Continued Sample Parameters Sampled and Data Sources Date MO DA YR ST BT SS BS SDO BDO PH P04 TDP TP PP N03 NH4 TDN TN PN CHL 4 17 75 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 19 75 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 30 75 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 18 75 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 6 24 75 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 7 11 75 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 21 75 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 8 275 17 17 8 575 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 8 16 75 17 17 8 19 75 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 9 275 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 9 675 17 17 17 9 18 75 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 10 675 17 17 17 10 10 75 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 10 19 75 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 10 21 75 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 11 575 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 11 575 17 17 17 11 975 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 12 575 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 12 775 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 12 975 17 17 17 12 14 75 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 12 15 75 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 12 17 75 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 1 12 76 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 1 15 76 17 17 17 2 24 76 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 2 26 76 17 17 17 2 27 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 3 11 76 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 3 24 76 16 6 6 6 6 6 6 6 6 6 6 6 6 6 6 3 25 76 17 17 17 4 376 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 4 476 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 4 676 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 4 21 76 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 576 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 5 11 76 17 17 17 6 776 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 23 76 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 188 Appendices Appendix 4. 1. Continued Sample Parameters Sampled and Data Sources Date MO DA YR ST BT SS BS SDO BDO PH P04 TDP TP PP N03 NH4 TDN TN PN CHL 6 23 76 17 17 17 7 6 76 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 19 76 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 7 25 76.18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 7 26 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 7 27 76 17 17 17 8 11 76 17 17 17 17 17 17 17 17 17 17 17 17 17 17 8 15 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 8 16 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 8 23 76 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 9 5 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 9 6 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 9 9 76 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 9 24 76 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 9 26 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 9 27 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 10 7 76 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 10 16 76 17 17 17 17 17 17 17 17 17 17 17 17 17 17 10 17 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 10 18 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 11 5 76 7 7 7 7 7 7 7 7 7 7 7 7 7 7 11 14 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 11 15 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 12 5 76 17 17 17 17 17 17 17 17 17 17 17 17 17 17 12 10 76 7 7 7 7 7 7 7 7 7 7 7 7 7 7 12 12 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 12 13 76 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 1 8 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 1 9 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 1 10 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 1 30 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 2 4 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 2 5 77 18 18 18 18 18 18 18 .18 18 18 18 18 18 18 18 18 2 9 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 2 19 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 2 20 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 3 2 77 17 18 17 18 17 18 17 17 17 17 17 17 17 17 17 17 17 3 2 77 18 18 18 18 18 18 18 18 18 18 18 18 18 3 10 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 3 12 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 3 13 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 3 30 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 4 2 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 Appendices 189 Appendix 4. 1. Confinued sample Parameters Sampled and Data Sources Date MO DA YR ST BT SS BS SDO BDO PH P04 TDP TP PP N03 NH4 TDN TN PN CHL 4 3 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 4 14 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 4 25 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 4 24 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 4 26 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 5 12 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 5 15 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 5 16 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 5 23 77 17 17 17 17 17 17 17 17 17 17 17 17 17 17 6 5 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 6 6 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 6 8 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 6 30 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 77 17 17 17 17 17 17 17 17 17 17 17 17 17 17 7 10 77 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 18 7 11 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 25 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 8 10 77 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 9 9 77 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 29 77 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 11 9 77 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 12 16 77 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 1 10 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 2 15 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 3 17 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 4 7 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 4 28 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 5 11 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 5 23 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 6 7 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 6 20 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 7 13 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 7 26 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 15 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 23 78 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 10 23 78 * * * * 11 9 78 * * * * 11 29 78 * * * * 12 14 78 * * * * 2 16 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 3 16 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 4 25 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 5 8 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 190 Appendices Appendix 4. 1. Continued Sample Parameters Sampled and Data Sources Date MO DA YR ST BT SS BS SDO BDO PH P04 TDP TP PP N03 NH4 TDN TN PN CHL 5 28 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 6 7 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 6 14 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 7 17 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 7 24 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 8 22 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 8 28 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 20 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 27 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 10 2 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 10 18 79 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 1 17 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 2 15 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 2 28 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 3 27 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 3 31 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 4 16 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 4 28 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 5 6 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 5 19 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 6 2 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 6 16 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 7 7 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 7 14 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 8 1 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 8 14 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 8 25 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 9 9 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 9 29 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 11 4 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 11 20 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 12 4 80 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 1 16 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 1 29 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 2 16 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 2 27 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 3 9 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 3 25 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 4 7 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 4 22 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 5 15 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 6 10 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 6 22 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 Appendices 191 Appendix 4. 1. Continued Sample Parameters Sampled and Data Sources Date MO DA YR ST BT SS BS SDO BDO PH P04 TDP TP PP N03 NH4 TDN TN PN CHL 7 7 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 716 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 729 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 825 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 910 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 918 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 10 1 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 10 9 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 10 22 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 3 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 12 4 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 12 23 81 11 11 11 11 11 11 11 11 11 11 11 11 11 11 11 1'7 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 220 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 211 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 224 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 3 9 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 319 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 4 2 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 5 3 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 511 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 524 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 610 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 625 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 716 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 722 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 8 5 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 819 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 9 1 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 916 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 10 8 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 10 21 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 10 29 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 11 10 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 11 30 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 15 82 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 1 6 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 125 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 2 9 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 216 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 222 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 310 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 4 1 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 192 Appendices Appendix 4. 1. Continued Sample Parameters Sampled and Data Sources Date MO DA YR ST BT SS BS SDO BDO PH P04 TDP TP PP N03 NH4 TDN TN PN CHL 412 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 422 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 5 583 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 5 683 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 6 283 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 613 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 630 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 712 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 727 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 8 883 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 831 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 9 883 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 923 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 10 483 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 11 383 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 11 17 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 11 22 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 12 29 83 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 1 684 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 126 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 2 284 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 215 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 3 884 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 316 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 327 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 420 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 427 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 5 984 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 523 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 6 884 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 621 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 7 584 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 720 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 8 284 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 815 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 829 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 921 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 926 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 10 10 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 10 24 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 11 14 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 11 27 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 12 13 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 Appendices 193 Appendix 4. 1. Continued sample Parameters Sampled and Data Sources Date MO DA YR ST BT SS BS SDO BDO PH P04 TDP TP PP N03 NH4 TDN TN PM CHL 12 19 84 14 14 14 14 14 14 14 14 14 14 14 14 14 14 14 2 6 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 2 21 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 3 28 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 4 12 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 4 24 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 4 30 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 5 7 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 5 21 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 5 31 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 6 11 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 6 20 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 7 9 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 7 17 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 8 1 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 8 6 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 8 19 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 8 28 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 9 19 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 9 30 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 10 14 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 11 15 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 11 26 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 12 9 85 15 15 15 15 15 15 15 15 15 15 15 15 15 15 15 1 15 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 2 4 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 2 18 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 3 26 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 4 2 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 4 17 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 5 1 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 5 8 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 5 22 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 6 4 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 6 19 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 7 10 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 7 16 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 7 30 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 8 13 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 8 27 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 9 10 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 9 24 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 10 8 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 194 Appendices Appendix 4. 1. Continued Sample Parameters Sampled and Data Sources Date MO DA YR ST BT SS BS SDO BDO PH P04 TDP TP PP N03 NH4 TDN TN PN CHL 10 30 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 11 7 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 12 9 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 12 27 86 16 16 16 16 16 16 16 16 16 16 16 16 16 16 16 Appendices 195 Appendix 4.2. Pamlico River estuary water quality sampling station locations Note 1. Sample station numbers are arranged by investigator (columns) and river segment (A-J) (rows). Note 2. Investigator codes: Hl = Hobbie (March 1967-February 1968) H2 = Hobbie (June 1968-July 1969) H3 = Hobbie (July 1969-July 1971) - H4 = Hobbie (August 1971-August 1973) Dl = Davis (August 1975-July 1976) D2 = Davis (August 1976-July 1977) K = Kuenzler (1975-1977) Il = ICMR (January 1975-June 1975) 12 = ICMR (July 1975-December 1986) Station 7 sampled 1/77-12/86 Station 2N sampled 7/75-7/77 Station 1A sampled 7/80-12/86 Note 3. The "location" notes below refer to geographic features named on National Ocean Survey Charts 11554 (13th. ed., 1981) and 11548 (31st. ed., 1985), published by the U.S. Department of Commerce, National Oceanic and Atmospheric Administration (NOAA), Washington, D.C. River Segment Investigator H1 H2 H3 H4 D1 D2 K Il 12 Latitude/Longitude/Location A 22 1 11 12 N35032 I 07"-W77002 155" Mid-river, RR bridge at Washington A 21 11 N35029151 "-W77001138" Mouth of Chocowinity Bay B 10 10 N35028155 "-W76059115 " Marker "12" off Camp Hardee B H17 H17 1 N35'28122 "-W76058,27 " Marker "10", mid-river off Hills Pt. 196 Appendices Appendix 4.2. Continued River Segment Investigator H1 H2 H3 H4 D1 D2 K Il 12 Latitude/Longitude/Location B 9S N350271 04 "-W76057 132 " South Blounts Bay B 9N N35028150 "-W76057 124 " Marker "1", mouth of Broad Ck. B H16 H16 2 20 2 1 N35027 142"-W76057 133" Marker "9", Blounts Bay B A5 N350281 00 "-W760581 00" West Blounts Bay C 3 N35027 1 27 "-W760561 11 Marker "8", NW of Maules Pt. C H11 H11 9 8 N350271 10"-W76055 1 10" Marker "7", NE of Maules Pt. C 4 19 N35026142 "-W76054 113 " Test Well "D" off Jack Ck. C 3 N35027 120"-W76053 135 " Off Mallard Ck., N side of river C 2 N35026148"-W76053137" Between Tripp Pt. and Mallard Ck. C 1 N350261 10"-W760531 40" Off Tripp Point, south side of river D H10 H10 5 18 2 8 N35026130"-W76052 1 22" Between Sparrow Bay and Duck Ck. D 4 N35026145 "-W76050145 Off Hawkins Landing, N side of river D H9 H9 16 7 N35025 I 50"-W76050130" Marker "5" off Core Pt. Appen.dices 197 Appendix 4.2. Continued River Segment Investigator Hl H2 H3 H4 Dl D2 K Il 12 Latitude/Longitude/Location D 6 N350261 03"-W760501 05 Mid-river between Core Pt. and Bath Ck. D 5 N350261 10"-W76050150" Between Hawkins Lndg. and Core Pt. D 6 N35025 143 "-W76050151 " off Core Pt., near s. shore of river D 7S N35024 1 04 "-W76049, 04 " Marker "2" at mouth of Durham Ck. D 17 7N N35027 103 "-W76049 115" Marker "1" at mouth of Bath Ck. D H8 H8 8 7 N35024 145 "-W76048,43 " Mid-river between TG and Bayview D SH8 SH8 9 15 N35024108 "-W76048140 " off mouth of Durham Creek D 3 3 N35025 115 "-W76048130" Mid-river between Durham Ck. & Bath Ck. D 7 N35023 145 "-W76047 152 " Off TG, near south shore D 10 14 M350251 55 "-W76047 140" Off Bayview, near north shore D 8 N35024 120"-W76047 145 " Off TG, near south shore D 9 N350251 05 "-W76047 145" Mid-river between TG and Bayview 198 Appendices Appendix 4.2. Continued River Segment Investigator Hl H2 H3 H4 Dl D2 K Il 12 Latitude/Longitude/Location D NH8 NH8 7 N3502513 0"-W7 604 613 6" off Mixon Creek, N side of river E 6 N35023112"-W76046107 " Off TG outfall E SH7 SH7 12 N35023128 "-W76046,20 " Marker "1" at TG barge canal E H7 H7 11 N350241 10 "-W76046103" Between Gum Pt. and TG barge canal E NH7 NH7 10 N35024147 "-W76045152 " Marker "4" off Gum Pt. E A3 14 N35023 157 "-W76044 139 Between St. Clair Ck. and Long Pt. E 14 11 5 5S N35023103"-W76044 139" Marker "1" at Ferry Landing E 12 N35024137 "-W76044125" Between Gaylord Bay and Ferry Lndg. E 12 4 6 5 N35024110"-W76044118" Between Gaylord Bay and Huddles Gut E A2 13 N35025 I 10"-W76044135" Off St. Clair Ck., N side of river E 13 N35024145"-W76044,35" off ferry landing, south side of river E 11 13 5N N35025119"-W76044110" Marker "i" in Gaylord Bay Appendices 199 Appendix 4.2. Continued River Segment Investigator H1 H2 H3 H4 Dl D2 K Il 12 Latitude/Longitude/Location E 15 N35022 103 "-W76041140 " Off Hickory Pt., south side of river E A4 15 N35023 I 00"-W76041140 " Off Long Pt., S side of river E 17 N35023 125 "-W76041, 10" Between Cousin Pt. and Hickory Pt. E 16 N35022 147 "-W76041122 Off Hickory Pt., S side of river E 18 N35024 I 03"-W76040,55 " Off Cousin Pt., N side of river E 19 N35024 140"-W760401 45" Off Cousin Pt., N side of river F 26 N35021122 "-W76041, 05 " Marker "5" off South Ck. F 25 H13 H13 32 4S N35021128"-W76040,37 " Marker "4" off South Ck. F H6 H6 17 N35023 145 "-W76040,16" Between Hickory Pt. & Cousin Pt. F NH6 NH6 16 4N N35024 146"-W760401 11 " Marker "1" at mouth of North Ck. F SH6 SH6 18 N35022 130"-W76040,29 " Between Hickory Pt. & Cousin Pt. F 24 10 N35021120 "-W76039135 " South of Indian island F 23 N35021155 "-W760391 00 " North of Indian Island 200 Appendices Appendix 4.2. Continued River Segment Investigator Hl H2 H3 H4 Dl D2 K Il 12 Latitude/Longitude/Location F 21 N35023103 "-W7603 8120 " North of Indian Island F 22 H5 H5 9 4 4 3 N35022123 "-W76038,47 " Marker "3", north of Indian Island F 20 8 N35023 140"-W760381 07 " North of Indian Island F H12 H12 N35021112 "-W76038,25 " Marker "2" south of Indian Island G SH4 SH4 20 N350211 10"-W76037 1 00" Off Reed Hammock G NH4 NH4 19 N35022 136"-W76036,06" Off Cousin Pt., north side of river G 35 N35020,36"-W76036,32" Off Reed Hammock, s. side of river G H4 H4 5 N35022 I 00"-W76036130" Between Reed Hammock and Adams Pt. 3 N3502114 0 " -W7 603 6119 " Mid-river between Wades Pt. & Goose Ck. G 34 N35021,02"-W76036,08" Between Reed Hammock and Wades Pt. G 5 2S N35020'22 "-W76035 147" Marker "1" at mouth of Goose Ck. Appendices 201 Appendix 4.2. Continued River Segment Investigator H1 H2 H3 H4 D1 D2 K 11 12 Latitude/Longitude/Location G 33 N35021124 "-W76035,48 Mid-river between Wades Pt. & Reed Ham. G 31 N35022124 "-W76035 1 00" Between Reed Hammock and Wades Pt. G 32 6 N35021152 "-W76035 124 " Between Reed Hammock and Wades Pt. G 30 7 N35022 154"-W76034 142" Off Wades Pt. G 21 N35022138 " -W76033124"' Marker "PR" at mouth of Pungo R. G 23 N35020118"-W76033 154 " Between Goose Ck. and Cedar Is. G 22 N35021124 "-W76033 133 " Mid-river south of mouth of Pungo R. H Al 31 2N N35023 136"-W76033 1 00" At mouth of Pungo River H SH3 SH3 26 N350201 00 "-W76032 1 06" North of Cedar Island H H3 H3 25 5 2 1A N35021120"-W76031,30 " Mid-river between Abel B. & Cedar Is. H NH3 NH3 24 N35023113 "-W76030130" S. of Indian Is. Marker "1" at Abel B. 1 38 N35020154 "-W76029114 " Between Marker "1" and Willow Pt. 202 Appendices Appendix 4.2. Continued River Segment Investigator H1 H2 H3 H4 D1 D2 K Il 12 Latitude/Longitude/Location 1 37 N35019152 "-W76029,12 Between Pamlico Pt. & Willow Pt. 1 39 NH2 NH2 27 2 N35021148 " -W76028150 " Marker at Willow Pt. shoal 1 36 SH2 SH2 29 4 N35019,00"-W76028158" Marker "i" at Pamlico Pt. I H2 H2 28 3 N35020130"-W76028 1 54 " Mid-river between Willow Pt. & Pam. Pt. 1 30 1 1 N35020106"-W76027136" Mid-river between Pam. Pt. & Rose Bay I Hl H1 1 6 6 N35018 147 "-W76027 120" Pamlico Pt. light 1 29 N350201 31 "-W76044 119" Marker "9" in South Creek i H15 H15 34 N350211 09"-W76043 143" Marker "8" in South Ck. J 28 N350211 03 "-W76042 120" off Old Field Pt., South Creek i H14 H14 33 12 4P N35021114"-W76042115" Marker "7", South Ck. J 27 N35020145"-W76041140" Marker "2", mouth of Bond Creek Appendix 4.3. Changes in sampling and analytical methods To the best of my knowledge, all the al. (1978) used a salinity-conductivity-tem- hydrographic and nutrient data reported perature (SCT) meter (Model 33) manu- by Hobbie for the period 1967-1973 were factured by Yellow Springs Instrument from analyses carried out by students and Company (YSI). Beginning in 1975, and research technicians at the Pamlico Estua- continuing to the present, the ICMR moni- rine Laboratory (PEL) near Aurora, NC. toring program at ECU has also made use After East Carolina University (ECU) took of the YSI SCT meter for temperature and over the monitoring program in 1975, the salinity measurements. There is no reason analyses continued to be performed at the to suspect that data from these two instru- PEL under the supervision of Mr. Dan ments are incomparable. All the data have Kornegay. In mid- 1980 the procedure was been reported in units of OC for tempera- changed so that samples were transported ture, and parts per thousand (ppt) for Sa- to the Institute for Coastal and Marine linity. Resources on the ECU campus in Greenville Dissolved oxygen measurements in for analysis. Finally, in March 1985 analy- the Pamlico studies have been made by sis of the Pamlico samples was shifted to two methods: 1) the classical Winkler titri- the ECU Biology Department's Central metric technique, and 2) oxygen sensing Environmental Laboratory, under the su- electrodes. The Winkler method was used pervision of Ms. Martha Jones. Samples for all the dissolved oxygen analyses re- collected by Davis et al. (1978) were also ported by Hobbie. Water samples were analyzed in the ECU Biology Department taken with a Kemmerer sampler, fixed in lab. Kuenzler et al. (1979) transported the field, and titrated in the laboratory. No their samples to the U.N.C. Chapel Hill other details of the procedure are given in campus foranalysis in the Limnology LabO- Hobbie's reports. Instead, the reader is ratory of the Department of Environmen- referred to Carpenter (1965), who described tal Sciences and Engineering. the method as "a modified ... Winkler determination", and he detailed the modi- Water Temperature, Salinity, Dis- fications, most of which involve the titra- solved Oxygen, and pH: Two kinds of tion equipment. Kuenzler at al. (1979) instruments have been used to measure used an "APHA-type" oxygen sampler to water temperature and salinity in the collect replicate D.O. samples from 0.5 in Pamlico studies. Hobbie used a conductiv- below the surface and 0.5 in above the ity bridge with built-in thermistor bottom. Samples were fixed by the addi- (Beckman RS5-3 induction salinometer) to tion of manganous sulfate and alkaline measure salinity and temperature in situ, iodide for Winkler analysis by procedures except for a few times in 1967 when hy- given in American Public Health Associa- drometers were used for salinity measure- tion (1975). Davis et al. (1978) and ICMR ment. Presumably a mercury thermom- both measured dissolved oxygen by means eter was used on these occasions to mea- of a Yellow Spring Instrument Company sure water temperature, although such is Model 51A oxygen meter and electrode. not stated in the report (Hobbie 1970b). All of the Hobbie dissolved oxygen data The induction salinometer was used also was reported as ml 02/liter. To permit by Kuenzler et al. (1979) in their Pamlico comparison with later data, I have con- samplingin 1975,1976 and 1977. Davis et verted the ml 02/liter values to mg02/liter, 204 Appendices by multiplying times 1.429 (Head 1985). was measured in the laboratory, but since Dissolved oxygen (DO) percent saturation then a portable instrument has been used values were included for some years in the to make measurements on freshly-drawn previous Pamlico reports, but the method samples in the field (Stanley 1987). ofealculation was not always given. There- fore, in order to have the data for all years Nitrogen and Phosphorus: Proce- and to insure consistency, I have recalcu- dures for the collection ofsamples, for nitro- lated percent saturations (DOPS) by the gen and phosphorus analyses have varied following formula: somewhat among the four studies. Hobbie I DOPS = (mgDO/liter * 100XDO Satu- stated simply that "surface samples were ration Value), taken at each station and returned to the where laboratory for analysis" (Hobbie 1970a, DO Saturation Value = (475 - (2.65 * page6). Davisetal. (1978) collected samples S)X33.3 + T). 0.5 m below the surface, immediately fil- S is salinity (ppt) and T is the tempera- tered aliquots for dissolved nutrients, and ture (OC). This is the same formula used by stored all the samples in the dark on ice for Hobbie (1970b) forsomeofthe earlyPamlico transport back to the laboratory. Kuenzler data. He indicated that it was developed et al. (1979) filled polyethylene carboys by Truesdale and Gameson (1957). with water from a depth of 0.5 m by means Of course, no percent saturation values of a Guzzler R Pump (Cole-Parmer Instru- could be calculated when there was not a ment Company) fitted with a plastic hose dissolved oxygen value. However, in those covered at the intake end with 153 um few cases where there was a DO value, but mesh nylon netting to exclude zooplank- no temperature and/or salinity data, I did ton. The samples were returned to the estimate the percent saturation. I did this Pamlico Estuarine Laboratory (PEL) by interpolating to give the missing salin- within a few hours for filtration, followed ity or temperature values needed for the by freezingand transport to Chapel Hill for calculation. later analysis. Finally, samples collected . I have not found in any of the Hobbie since 1975byICMR were taken by dipping reports a description of the method used 1-liter polyethylene bottles into the water for pH measurements. However, I believe just below the surface. The bottled samples that a pH meter with electrode (model were held on ice in the dark until they were unknown) was used, and that measure- returned to either the PEL or ECU (within ments were made on samples after they 6 hours of collection), where they were were returned to the Pamlico Estuarine filtered and frozen (e.g., ICMR 1982; Laboratory, usually within a few hours Stanley 1987). after collection. Davis et al. (1978) stored Other variables associated with the samples in the dark at mean ambient nutrient sample processing include the water temperature for up to 4 hours until type of filter used to separate dissolved and pH could be measured with a Corning particulate fractions, and the type and Model 10 meter. Kuenzler at al. (1979) also length of storage of samples between col- used a pH electrode, but I don't recall the lection and analysis. Hobbie used Gelman meter model; no reference to it is made in A glass fiber filters. Reactive phosphorus the project report. Since 1975 various pH was measured as soon as the samples were meters with electrodes (manufacturers and returned to the laboratory, but water (fil- models have varied) have been used for the tered and unfiltered) for the total phospho- ICMR pH measurements. Until 1985 pH rus, total dissolved phosphorus, and nitro- Appendices 205 gen fractions was frozen in plastic bags in 1969 that the calibration curve was not immediately after collection byplacingthe linear above 10 ug-at P/liter and the previ- bags onto dry ice (Hobbie et al. 1972). ous readings obtained were underesti- Similarly, Kuenzler et al. (1979) filtered mates. Therefore, the concentrations mea- samples through Whatman GF/C glass sured prior to 14 October 1969 are low and fiber filters and stored the filtered (or can be corrected by multiplying by a factor unfiltered) water frozen in polyethylene of 1.0 at 10 ug-at P/liter and 1.6 at 20 ug- until the nutrient analyses were run. at P/liter. Since this correction makes no Gelman type A/E glass fiber filters were difference to the conclusions of this report, used by Davis et al. (1978), and they also it was not applied to the data. It was also froze the samples pending analyses of nu- found that the curves for total (digested) trients. Since 1984 Whatman 934-AH and reactive (undigested) phosphate con- glass fiber filters have been used for the centrations versus extinction had different samples analyzed in the ICMR program. slopes. Again the differences are slight, There is no record of the kind of filters used but this correction and the correction for between 1975 and 1983. Both filtered and the differing factors at high concentrations unfiltered samples have been stored fro- of phosphorus will clear up most of the zen, for up to several months in some discrepancies of the data where the reac- instances, until the analyses were made. tive phosphorus is higher than the total 1. Phosphorus: Nearly all the samples phosphorus" (Copeland and Hobbie 1972, taken during these studies were analyzed pages 24-25). for at least three phosphorus fractions; Apparently the phosphorus methodol- total phosphorus (TP), total dissolved phos- ogy did not change between 1969 and phorus (TDP), and orthophosphate phos- August 1973 when Hobbie's sampling phorus (OK TP analyses were performed ended, since his 1974 report on the 1971- on unfiltered water samples, while the 1973 data states on page 12 that "details of other two measurements used filtered the phosphorus analysis are given in Hobbie water. All the TP and TDP samples were (1970a)", and the references he cites re- first digested by some variation of the garding methodology are the same ones persulfate oxidation method of Menzel and cited in the earlier report; i.e., Menzel and Corwin (1965). Subsequent analyses of Corwin (1965) for the persulfate digestion these digested samples, and undigested and Strickland and Parsons (1968) for the orthophosphate samples, was by manual use of the mixed reagent. The same spec- or automated colorimetric methods. All trophotometer that had been used earlier projects used the mixed reagent developed was used to read the sample color following by Murphy and Riley (1962), containing addition of the mixed reagent. ammonium molybdate, ascorbic acid, and Davis et al. (1979) seem to have used trivalent antimony. the same basic procedure as Hobbie, al- Copeland and Hobbie give further de- though they reported few details regard- tails on the methodology used between ing their phosphorus methodology. They 1967 and 1969: "The color development simply state that "phosphorus analyses was read in a Beckman DU II spectropho- involved conversion of phosphorus to or- tometer and the optical density calibrated thophosphate by persulfate digestion, and against standards. These standards proved subsequent colorimetric determination of to be constant and a factor of 5.0 multiplied soluble orthophosphate." They cite the by this spectrophotometer reading gave manual on water and wastewater chemi- the concentration. However, it was noted cal analyses published by the Environ- 206 Appendices mental Protection Agency (EPA) (1976) as the annual reports to Texasgulf (Stanley a reference to their procedures. The meth- 1986a, 198b, 1987). The most significant ods outlined in this document do indeed change in recent years came in 1985 when involve the use of persulfate digestion for the procedures were automated using a TDP and TP and the use of the three-part Scientific Instruments autoanalyzer simi- mixed reagent for phosphate determina- lar to the Technicon equipment used ear- tion. lier by Kuenzler et al. (1979). Details of the An earlier edition of the EPA manual autoanalyzer procedure are given in (1974) was referenced by Kuenzler et al. Stanley (1987). (1979) to describe the phosphorus method- On 28 March 1985 the total phospho- ology they used for Pamlico samples ana- rus analysis was dropped and particulate lyzed in their study between 1975 and phosphorus (PP) measurements were be- 1977. They used slightly different termi- gun. PP is the fraction of TP that remains nology to describe the phosphorus frac- on the filter pad following filtration. There- tions - "filterable reactive P" instead of fore, the total phosphorus data used in this orthophosphate phosphorus, and "total fil- study for the period 28 March 1985 through terable P" instead of total dissolved phos- December 1986 are not direct measure- phorus. The main difference between their ments, but rather the sums of the total procedure and that of Hobbie and Davis et dissolved phosphorus and PP values. al. was that they automated the analyses It has been determined recently that using Technicon Autoanalyzer equipment. all the total dissolved phosphorus (TDP) They state in their report that ". . . preci- data presented in the 1986 annual report sion was controlled in these analyses by (Stanley 1987) and part of the data in the runningall samples in duplicate. Accuracy 1985 report (Stanley 1986b) are in error. was checked in two ways. Where avail- This error arose duringthe transition from able, EPA controls were analyzed with manual to automated methods of analysis every run. Also approximately 10% of of TDP during 1985. The problem is that routine analysis time was spend [sic] de- the automated analysis gives erroneously termininarecoverv of known increments of high TDP results. The solution to this standar& (spike;) to samples. . . Stan- problem is described above in the Methods dards were routinely run at the beginning section of the report. and end of each sample run" (Kuenzler et 2. Nitrogen: From 1969 through 1973 al. 1979, pages 17-19). . Hobbie analyzed several nitrogen fractions, Finally, all ICMR samples from 1975 to including nitrate nitrogen, ammonia ni- the present have been analyzed for phos- trogen, total dissolved nitrogen (TDN), and phorus using the same basic chemistry total nitrogen (TN). The first three analy- described above; i.e., the mixed color re- ses were run on filtered samples, while the agent for OP and persulfate digestion to fourth (TN) used unfiltered water. Hobbie convert TP and TDP to OP. Notes provided (1974) referred to the total dissolved nitro- to me by the analyst who performed the gen as "total filtered nitrogen", and to the tests from 1975 through 1980 show that total nitrogen as "total unfiltered nitro- EPA (1974, 1976, 1979) procedures were gen". followed. A block digestor was used be- Hobbie's nitrogen analyses consisted of tween 1975 and sometime in 1977, when it various pre-treatments of a sample fol- was replaced by an autoclave. Since 1984 lowed by analysis as nitrite. The nitrite the methods for phosphorus analyses have was analyzed as an azo dye produced by been described in detail in appendices in sulphanilamide plus N-(l-napthyl)- Appendices 207 ethylenediamine. This diazotization tech- were automated using Technicon nique was adapted for sea water by Autoanalyzer equipment and EPA meth- Bendschneider and Robinson (1952), and ods. Cadmium reduction followed by ni- it is described in full in Strickland and trite analysis was the method they chose Parsons (1968), which is the reference cited for nitrate nitrogen determinations. They by Hobbie in his reports. The nitrate was cited EPA (1974) as their reference. Like analyzed as nitrite following reduction in a Davis et al., they also used the indophenol copper-cadmium column (Morris and Riley method for ammonia, and they cited EPA 1963). Ammonia also was analyzed as (1974) as the reference for the method. nitrite after oxidation of the sample with Their total dissolved nitrogen analyses alkaline hypochlorite, a method developed were by automated Kjeldahl methods (EPA by Richards and YJetch (1961). It really 1974). Total nitrogen was not measured. gives ammonia plus amino acids, For a brief period (January-June 1975) (Strickland and Parsons 1968), although the ICMR nitrate analyses were made the error is small, since amino acids are using the brucine colorimetric method, usually much less abundant than ammo- which is based on the formation ofa colored nia. Finally, the TN and TFN analyses complex between nitrate and brucine sul- were carried out using oxidation by strong fate in a 13 N sulfuric acid solution at a ultraviolet (UV) light to convert organic temperature of 1000C (EPA 1974). How- forms to a mixture of nitrate and nitrite ever, since July 1975 the ICMR samples (Armstrong et al. 1966; Strickland and have been analyzed by the cadmium re- Parsons 1968). duction method, which was automated in Davis et al. (1978) indicated that they mid-1985. used the UV spectrophotometric method From 1975 through 1979 the ICMR (APHA 1971) for nitrate determinations. ammonia analyses were made using an They analyzed ammonium nitrogen by the Orion Ammonia Probe (D. Kornegay, per- indophenol method, often referred to as the sonal communication). Unfortunately, this Solorzano (1969) method. Scheiner (1976) ion-selective electrode was not very sensi- modified the method slightly and Davis et tive. It could not detect concentrations al. cited this paper as their reference. In below 0.1 mg ammonia N/liter (7.14 uM), the indophenol method samples are treated so that most of the normal range in ammo- with sodium hypochlorite and phenol in an nia levels in the estuary was missed. Be- alkaline citrate medium. Sodium ginning in 1980, the indophenol method nitroprusside is used as a catalyst, and the was adopted (Solorzano 1969), and it has blue indophenol color formed with ammo- been used continuously since then, al- nia is measured spectrophotometrically though minor modifications have been (Parsons et al. 1984). Kjeldahl digestions made at various times. Details of the (EPA 1976) were used for the total nitro- procedure from 1984 onward, including gen and total dissolved nitrogen analyses. the switch to the automated procedure in This is one of the oldest and most widely- 1985, are given in the annual reports. used methods for TN and TDN. Organic Kjeldahl digestions were used for the matter is converted to ammonia by heat- ICMR total and total dissolved nitrogen ing with sulphuric acid, and the ammonia analyses beginning in January 1975. Be- determined spectrophotornetrically by one tween 1975 and the end of 1979, a block of the methods given above. digester was used and the ammonia pro- All of the nitrogen analyses performed duced in the reaction was measured by during the study by Kuenzler et al. (1979) means of the same Orion ammonia probe 208 Appendices used for the ammonia analyses. Beginning from 1975 through 1980, although no de- in 1980, the ammonia was determined by tails are certain for that time period. Since the indophenol blue method, modified 1980, this has been the method, with slight slightly at various times. When the analy- modifications, mostly involvingthe method ses were automated in 1985, a combined of extraction (e.g., grinding or no grinding nitrogen-phosphorus digestion reagent of filter pads), and the time allowed for came into use. (Stanley 1987). The ammo- extraction before the readings were made. nia produced by this digestion was ana- The chlorophyll data from part of 1985 are lyzed by the indophenol method. suspect because of a problem involving unequal dispersion ofthe pigment in tubes ChlorophyU a: Essentially the same following centrifugation to sediment the method has been used for chlorophyll a glass fiber filter fragments. It seems that analyses in all four of the Pamlico studies. mostofthe pigment was collecting near the Hobbie (1974) gave the following outline of bottom of the tube, so that when the sample the method: "Water samples were returned was decanted into the spectrophotometer to the laboratory ... and a part of the cell, erroneously low readings were ob- sample filtered through Gelman A glass tained. This problem was corrected in fiber filters for later chlorophyll analysis -early 1986. (filters were frozen)... Chlorophyll a was measured by grinding the filters, extract- Phytoplankton CeU Density and ing with 90% acetone, and estimating the Wet Weight Biomass: There have been pigment spectrophotometrically two major studies of phytoplankton spe- (Strickland and Parsons 1968). The spec- cies, numbers, and biomass in the Pamlico. trophotometric results were corrected for The first was by Hobbie (1971) for the time phaeophyton (Strickland and Parsons period August 1966 through April 1968. 1968)" (Hobbie 1974, page 12). It is impor- Two series of stations were sampled; one tant to note that all the chlorophyll results series from August 1966 to August 1967 from the other three studies were also and the other from March 1967 to Febru- corrected for phaeophyton. ary 1968. These were the same stations Davis etal. (1978) filtered their samples sampled for nutrients and hydrographic within 12 hours of collection (filter type not parameters during these time periods given), and the filters were stored frozen in (Hobbie 1970a, 1970b). The first series a dessicator. Analyses of chlorophyll were was sampled to examine the effects of the made within 30 days of sample collection. effluent from the phosphate slime (mining They cited Strickland and Parsons (1972) waste) pond located close to South Creek. as the reference for the procedure they When the effect could not be found, the used. Kuenzler et al. (1979) also froze the sampling was expanded to include most of filter pads (Whatman GF/C) and analyzed the estuary (Hobbie 1971). for chlorophyll a by means of the acetone Phytoplankton in the samples were extraction-spectrophotometric method, fol- identified and counted by the Utermohl lowing the procedure given in Lorenzen technique (Utermohl 1958). Briefly, the (1967). organisms were preserved in a Lugol's type ICMR analyses ofchlorophyll a, like all solution, settled into asmall countingcham- the others described above, were made by ber, the excess water removed, and the measuring the extinction of an acetone organisms counted with an inverted micro- extract of the pigment. The method prob- scope. Details are given in Hobbie's report. ably followed Strickland and Parsons (1972) The. most important advantage of this Appendices 209 method is that it enables counting of the identified and counted by D. Daniel. The flagellates and nannoplankton as well as membrane filtration method was used to less fragile, larger forms (Hobbie 1971). concentrate the Lugol's preserved algae The second Pamlico phytoplankton prior to counting at 40OX magnification study, sponsored by North Carolina Phos- (see Stanley and Daniel 1985a for details). phate Corporation, was made during the This method of concentrating the algae is period April 1982 through December 1985 more rigorous than the Utermohl settling (Stanley 1983, 1984a; Stanley and Daniel method usedbyHobbie in the earlierstudy, 1985a, 1985b, 1986). The objective was to but it apparently did not destroy the fragile collect baseline data for future impact as- flagellates and nannoplankton, so that sessment of increased phosphate mining results from the two studies are compa- in the area. There was a concern that rable. higher nutrient loads could trigger nui- In both of these phytoplankton studies, sance blooms of algae in the Pamlico like the algal biomass was calculated. Vol- those that had become common by this umes of representative individuals of each time in the Chowan River and the Neuse species were estimated by means of geo- River. Samples were collected approxi- metric formulae. These volumes were mately every other week from stations in multiplied by the species cell densities and the river and in South Creek, a tributary summed to give the total wet weight bio- near the mining sites. The River stations mass (ug/liter) for each sample. A specific were the same ones used for the Texasgulf gravity of unity was assumed (i.e., 1 ming nutrient and hydrography study. = 1 ing wet mass) (Hobbie 1971; Stanley Phytoplankton in the samples were and Daniel 1985a). 210 Appendices Appendix 4.4. Review of methods for analyzing water quality time series data The problem of testing water quality However, if the type of change is not known, monitoringdata fortrend intime has received a two-tailed test should be used. It should be increasing attention during the last decade, stressed that, when possible, the one-tailed primarily fortwo reasons (Hirsch et al. 1982). alternative should be chosen. First, there is interest in the question of In order to apply trend detection tech- changingwater quality arising from environ- niques, there can be only one data point for mental concern and activity. State and Fed- each time unit. This data preparation prob- eral legislation has resulted in the expendi- lem arises when numerous observations are ture of large sums of public and private located in the same time unit, yet one value is money for the purpose of water quality im- needed to represent that discrete time unit. provement, and there is naturally interest in Means or median values may be used as a evaluating the consequences of these expen- measure of central tendency to represent the ditures. Second, data sets covering a substan- time period. When dealing with multiple tial number of years are becoming increas- data sources, an important consideration is ingly common because of the establishment whether the data are mutually compatible. of monitoring programs in the early and mid- Similar sampling designs, sampling devices, 1970's. Many of the trend analyses have laboratory techniques and instruments may involved data from national water quality be a prerequisite to data merging; otherwise networks such as the U.S. Geological Survey's apparent trends may simply be an artifact of NASQAN network (e.g., Smith et al. 1982). a change in analytical methods. Under some Montgomery and Reckhow (1984) out- circumstances, the analyst may be able to lined a four-step trend detection method: 1) remove this analytical method effect from the hypothesis formulation - statement of the data series. problem to be tested, 2) data preparation - Once a hypothesis is formed and the data selection of water quality variables and data, are properly arranged (i.e., one datavalue per 3) exploratory data analysis, and 4) statistical unit time) the data are ready to be explored tests - tests for detecting trends. and analyzed. The data analysis step will Typically, the null hypothesis, H., is that provide the necessary information to deter- there is no change (notrend) in the population mine which statistical test should be used to of water quality values from which the data test the null hypothesis. Of particular interest were drawn. Consequently, the alternate are characteristics of the data related to fre- hypothesis, H1, may be either that a trend quently invoked assumptions. Montgomery does exist in the data (two-sided test) or that and Reckhow (1984) and Smith et al. (1982) a positive (or a negative) trend exists in the discuss these assumptions and corrective data (one-sided test). If it is known that a measures to deal with assumption violations. parameter either increased or decreased, a Some of the techniques available for the one-tail H, should be used. A one-tailed test exploratory data analysis include a graph of will maximize the probabilities of each out- the data against time, the five number sum- come by placing all the rejection region mary graph which Tukey (1977) calls the (alpha) at one tail ofthe outcome distribution. box-and-whisker plot, Tukey smoothing, and Appendices 211 the autocorrelation function (McLeod et al. any of these characteristics. The following 1983). Because no single method can clearly discussion, taken from Letterunaier et al. portray everything there is to learn about the (1982), describes these common features of data, it is advisable to use a number of water quality data which must be recognized exploratory techniques. before statistical methods can be selected. Hypothesis testing, the final step for trend 1. Seasonality: Most water quality vari- detection, consists of the following steps, as ables are affected directly or indirectly by summarized by Smith et al. (1982): seasonal climatic changes. For instance, 1. State the null hypothesis and back- water temperature responds directly to air ground assumptions for the test. temperature, although there is usually some 2. Calculate an appropriate test statistic lag which depends on the rate of heat transfer from the data. into and out of the ground and water. Water 3. Interpret the value of the statistic in temperature affects both the saturation con- light of the known probability distribution of centration of dissolved oxygen and the rates the statistic. of oxygen consumption and production by 4. If the value of the test statistic is within plants and animals in the water column and preselected limits on the distribution, accept sediments. Nutrient concentrations reflect the null hypothesis; or, both levels of biological activity and fresh- 5. If the value ofthe test statistic is outside water inflow to the estuary, both of which in the preselected limits, the null hypothesis turn may have large seasonal variability. cannot be accepted and a "statistically sig- Most trend analysis techniques require that nificant trend" is claimed. some procedure be employed to remove sea- The limits are calculated from a sonality. Montgomery and Reckhow (1984) preselected probability - typically denoted by reviewed some of these procedures. the Greek letter alpha - such that the probabil- 2. Nonnormal probability distributions: ity that the test statistic would fall outside the Most water quality variables are positively limits is (alpha) if the null hypothesis and all skewed, since they cannot be negative, but background assumptions were true. A typi- may occasionally take on large positive val- cal value selected for alpha is 0.1. Then one ues. Examples of variables from the Pamlico may say that a trend is, or is not, statistically data set exhibiting this characteristic include significant at the 10% level. That is, in 90% nutrients and chlorophyll a. On the other of the cases, one will correctly say there is no hand, some variables have small ranges and trend when such is true. One may also report often are nearly symetric, and if seasonal test results by a probability value (denote p). variations are removed, may be nearly nor- This is the probability that the test statistic mally distributed. Examples include tem- would depart from its expectation by at least perature, dissolved oxygen, and pH. the observed amount, under the null hypoth- Most parametric statistical tests require esis. that the data come from a population that is Most water quality data exhibit certain normally distributed. A combination of in- characteristics which can strongly influence tuitive knowledge, graphical methods, and the choice of an appropriate statistical trend statistical tests should be used to determine test. Thus it is very important that the data be whether or not to use parametric tests, or examined to determine whether they exhibit nonparametric tests, which do not require a 212 Appendices normal distribution of the parameter. Graphi- tion" (Montgomery and Reckhow 1984). cal techniques, involving visual compari- Positive correlation between samples arises sons, can be used to provide qualitative infor- because fluctuations from the mean tend to mation on the form of the underlying distri- continue for a period that is usually long bution. For larger samples (n>50), the compared to the sampling interval. Such Kolmogorow-Smirnov test (Sokal and Rohl f variations are, from a statistical standpoint, 1981) can be used to test statistically the "noise", and may obscure underlying trends. assumption of normality. This test, it should Persistence is usually not a major issue when be noted, determines only whether the data monthly sampling frequencies are used; for exhibit significant deviations from normality highersampling frequencies, such asbiweekly and not whether they are normal (i.e., sup- or weekly, it becomes increasingly impor- ports the alternative hypothesis and not the tant. Various tests for detecting null hypothesis) (Montgomery and Reckhow autocorrelation are discussed in Montgom- 1984). ery and Reckhow (1984), Kenkel (1975), and 3. Missing or nonuniformly sampleddata: Sen (1978,1979). Because of foul weather, equipment break- 5. Streamflow interaction: Some water down, analytical errors, and changing ideas quality variables display strong concentra- as to appropriate sampling strategies, long- tion gradients between freshwater and sea- term time series are likely to have missing water. For example, nitrate nitrogen is often data. There may be long periods when no 100-fold or more concentrated in rivers than samples were taken, and the intervals be- in in the ocean. Consequently, in a low- tween sampling dates are hardly ever uni- salinity estuary like the Pamlico Riverwhere form over a long period of time. Regardless there is a strong riverine influence, the con- of the cause, most traditional time series centration of nitrate depends largely on Tar techniques, which assume equal sample in- River flow, especially in the upper half of the tervals, are not appropriate to water quality estuary where most of the mixing occurs. data. Techniques exist to deal with a few 6. Censored data: Censored data are isolated data gaps (Lettenmaier 1976; those observations reported as being "less D'Astous and Hipel 1979) by estimating than" or "greater than" some specific value. values for the missing data. However,ifthere Examples include concentrations of nitrogen are a lot of missing values, or one or more and phosphorus which fall below the limits of long gaps exist, the effect of data interpola- detection (LD) of the analytical procedures. tion on the identification of the stochastic Where "less than LD" observations arise in process and the ultimate trend testing become the Pamlico data set, the LD values are used very problematic (Hirsch and Slack 1984). in the trend tests. This causes the distribution 4. Persistence: Water quality measure- of the data to deviate even farther from ments are not, in general, independent, but normality, and so parametric tests become are instead positively correlated (i.e., small less exact. However, provided that the LD values tend to be followed by small values does not change over the period of record, and large by large), and the correlation usu- nonparametric tests such as the one used in ally increases as the sampling interval de- this study (see below), may be used with no creases. This phenomenon is also sometimes difficulty (Hirsch and Slack 1984). termed "autocorrelation" or "serial coffela- Statistical tests used for trend analyses Appendices 213 fall under one of two categories: 1) classical, tions are present and not removed. or parametric or 2) distribution-free, or non- Another common parametric test for trend parametric (Bradley 1968). Classical tests, is based on linear regression of the variable of such as those used in regression, require the interest against time. The null hypothesis is estimation of one or more parameters (for that the variable and time are uncorrelated, example, the slope of the regression line) and the background assumptions are that the based on the observed values of the variable data are normal, independent, and identically and the distribution of the test statistic under distributed in time. If the slope of the regres- the null hypothesis follows from an assump- sion equation is found to be statistically sig- tion about the underlying probability distri- nificant, a trend is claimed. Unfortunately, bution of the random variable. several of the assumptions underlying the Distribution-free, or nonparametric, tests derivation of the necessary probability distri- typically ignore the magnitudes of the the bution to test for significance are violated by data in favor of the relative values or ranks of natural data. In general, water quality data the data. The major advantage of distribu- have seasonality, are skewed, and serially tion-free tests is that the underlying probabil- correlated. These features contradict the ity distribution of the random variable is assumptions of stationarity, normality, and immaterial. In fact, any strictly increasing independence of the random variable (the monotonic transformation - such as taking water-quality variable) required for comput- logarithms - changes the values of the data, ing the probability distribution of the test but does not affect the relative rankings. statistic in the regression test for trend. The However, because the magnitudes are ig- seasonality inflates thevariance used inthe t- nored, the test provides only a yes-or-no, not tests, the skewness increases the standard a how-much, answer. error in the estimated slope, and the serial The pros and cons of several parametric correlation raises the actual alpha level rela- and nonparametric tests for trend are dis- tive to the selected alpha level. Any one of cussed by Montgomery and Reckhow (1984), these defects may be sufficient to render the Hirsch and Slack(1984), Lettenmaier(1976), test invalid, especially since the amount by and Montgomery and Loftis (1987). Mont- which they are present - and therefore, the gomery and Loftis (1987) found that one of amount by which the test is being distorted - the most widely-used parametric tests, the t- cannot be known. test, is robust (i.e., is not appreciably affected The same or similar objections can be by a violation of a given underlying assump- raised against virtually every test for trend tion) for non-normal distributions if the dis- when applied to almost any water-quality tributions have the same shape (either symetric variable. Attempts have been made to alter or skewed) and sample sizes are equal. The (transform) the data to remove or reduce the Nest is also robust for unequal variances if undesirable features. To remove seasonality, the sample sizes are equal. The West appears one might fit a sine curve to the data (Steele not to be robust when 1) samples come from et al. 1974) and use the deviations from the two distributions ofdifferent shape, 2) samples curve as the random variable to be tested. But have unequal variances and unequal sample with the exception of a few variables such as sizes, 3) serial dependence in observations is water temperature, there is little reason to present, or 4) seasonal changes in concentra- believe that the form of seasonality is a pure 214 Appendices sine curve. The extent to which the cure works is largely unknowable. To eliminate skewness, one might use the logarithms of the data. Again, the extent to which this is proper is only a guess. Compensating for serial correlation is at best an art. Trying to do all three is extremely difficult, if not impossible. What is needed is a test that is largely unaf- fected by the three above-mentioned charac- teristics of the data. That is, the distribution of the test statistic is influenced little by these three characteristics of the data. Appendices 215 Appendix 4.5. The Seasonal Kendall Trend test for water qulalty data The distribution-free test which serves as identical. A complete specification of the the basis for trend testing in this study is Seasonal Kendall test is given below. Its Kendall's Tau (Kendall 1975). The null derivation is given by Hirsch et al. (1982). hypothesis for this test is that the random When all assumptions for the regression variable is independent of time. The only test are met, the regression test is the most necessary background assumption is that the powerful test for linear trend (Kendall and random variable is independent and identi- Stuart 1968). The Seasonal Kendall test is cally distributed (with any distribution). In almost as powerful, based on a series of tests this test, all possible pairs of data values are using generated random numbers (Hirsch et compared; if the later value (in time) is al. 1982). When skewness and seasonality higher, a plus is scored; if the later value is were introduced into the experiments, the lower, a minus is scored. If there is no trend Seasonal Kendall test performed better than in the data, the odds are 50-50 that a value is the test based on linear regression; and when higher (or lower) than one of its predecessors. serial correlation was introduced, it's effect In the absence of a trend, the number ofpluses on the Seasonal Kendall test was no more should be about the same as the number'of severe than it's effect on linear regression. minuses. If however, there are many more In addition to indicating whether a trend pluses than minuses, the values later in the exists, it may be desirable to estimate the series are more frequently higher than those trend rate, or slope. Hirsch et al. (1982) earlier in the series, and so an uptrend is defined the Seasonal Kendall Slope Estima- likely. Similarly, if there are many more tor to be the median of the differences (ex- minuses than pluses, a downtrend is likely. pressed as slopes) of the ordered pairs of data As discussed above, the one common values that are compared in the Seasonal pattern to water-quality variables is that they Kendall test. Instead of recording a plus or have a period of one year (other periodicities minus for each comparison, one simply may exist). Comparing, for example, a Janu- records the difference divided by the number ary value with a May value does not contrib- of years seperating the data points. The ute any information about the existence of a median of these differences is taken to be the trend, if aseasonal cycle of a 1-yearperiod change per year due to the trend. A math- exists. Thus, Hirsch et al. (1982) defined the ematical description of the Seasonal Kendall Seasonal Kendall test to be the Kendall's Tau Test is given inAppendix B, page 32 inSmith test restricted to those pairs of data which are et al. (1982). multiples of 12 months apart. Since compari- sons are made only between data from the the same month of the year, the problem of sea- sonality is avoided. The random variables may be nonidentically distributed, provided that the distributions 12 months apart are U.S. G.P.D.:1992-313-153:60516 I i i % @ @mmulimi@iim . 3 6668 00003 4860