Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Related Publications
• Parameters
• Instruments
• Project Information
• Funding

The Neuse River Estuary Water Quality Dataset is a compilation of the biological, chemical and physical water quality data that was collected along the length of the Neuse River Estuary, NC from March 14, 1985 to February 15, 1989 and from January 24, 1994 to the present.  The primary purpose of this dataset was to provide long-term environmental information to supplement experimental, process-based research, including the Atlantic Coast Environmental Indicators Consortium (ACE-INC) project as well as other laboratory studies.  

The full YSI profile data related to this dataset can be found at Neuse River Estuary YSI Profile: https://www.bco-dmo.org/dataset/767641.

Bi-weekly water sampling and in situ measurements were performed at fixed sampling stations.  Water samples and in situ measurements were collected at the surface (approximately 0.2 meters) and at the bottom of the water column (approximately 0.5 meters from the sediment layer).  These data are included in the worksheet titled "NRE Dataset."  In situ measurements were also performed throughout the water column in 0.5 meter depth increments.  These data are included in the worksheet titled "NRE YSI Profiles."  Parameters measured include: temperature, salinity, specific conductivity, dissolved oxygen (DO), pH, chlorophyll fluorescence, photosynthetically active radiation (PAR), turbidity, barometric pressure, secchi depth, colored dissolved organic matter (CDOM), particulate organic carbon (POC) and nitrogen (PN), dissolved organic and inorganic carbon, dissolved inorganic nutrient concentrations (nitrate/nitrite, ammonium, total dissolved nitrogen, phosphate and silicic acid), chlorophyll a, primary productivity and diagnostic phytoplankton pigment concentrations (chlorophylls and carotenoids).  Calculated parameters include:  diffuse light attenuation coefficient (Kd), carbon to nitrogen molar ratio (C:N), dissolved inorganic nitrogen (DIN; nitrate/nitrite plus ammonium), dissolved organic nitrogen (DON; total dissolved nitrogen minus dissolved inroganic nitrogen) and the nitrogen to phosporus molar ratio (N:P).  

Methods
Water sampling was conducted bi-weekly. When collection was split over two days, a single date was used based on the upstream or majority stations.

Stations were selected to cover the entire length of the Neuse River Estuary from Streets Ferry Bridge (Station 0) to the mouth of the estuary where it flows into Pamlico Sound.  When possible, efforts were made to select locations with key stationary features (channel markers, buoys and land markers) to allow easy station identification in the field.

Surface water samples were collected by submerging 10 liter high-density polyethylene containers just below the water surface or by filling the containers with surface water collected from bucket casts.  Bottom water samples were collected with a horizontal plastic Van Dorn sampler. Starting December 2007, all samples collected with diaphragm pump and a weighted, marked hose. All containers were kept in dark coolers at ambient temperature during transport to the laboratory.  All filtration was done within a few hours of collection and when conditions permitted, on board the research vessel.

Prior to the 09/13/2000 sampling date, in situ measurements were performed at discrete depths using a Hydrolab Data Sonde 3 equipped with a multiprobe and SVR3 display logger.  Beginning on the 09/13/2000 sampling date, in situ measurements were performed at discrete depths on the sunlit side of the research vessel using a Yellow Springs Instruments (YSI Incoporated, Ohio) multiparameter sonde (Model 6600 or 6600 EDS-S Extended Deployment System) equipped with a YSI conductivity/temperature probe (Model 6560), a YSI chlorophyll probe (Model 6025), a YSI pH probe (Model 6561 or 6566), a YSI pulsed dissolved oxygen probe (Model 6562), a self cleaning YSI turbidity probe (Model 6026 or 6136), and beginning on the 07/30/2003 sampling date, a flat Li-Cor sensor (UWQ-PAR 6067).  The YSI sonde was coupled to a either a YSI 610 DM datalogger or a YSI 650 MDS Multi-parameter Display System datalogger.  In situ measurements were performed at the surface (approximately 0.2 meters) and at the bottom of the water column (approximately 0.5 meters from the sediment layer).  These data are included in the worksheet titled "NRE Dataset."  In situ measurements were also performed throughout the water column in 0.5 meter depth increments.  These data are included in the worksheet titled "NRE YSI Profiles."  The data were stored on the datalogger and downloaded to Ecowin software upon return to the laboratory.

The secchi disk was deployed off of the sunlit side of the research vessel.  The depth (in meters) at which the secchi disk was no longer visible by the naked eye was recorded as the secchi depth.

The diffuse light attenuation coefficient, Kd, was calculated from depth profiles of photosynthetically active radiation (PAR, 400-700 nm).  Prior to the 07/30/2003 sampling date, PAR measurements were performed with a spherical underwater quantum sensor (LI-COR LI-193SA) coupled to a LI-COR LI-1000 datalogger.  Beginning on the 07/30/2003 sampling date, a flat underwater quantum sensor (LI-COR LI-193SA) attached to a Yellow Springs Instruments YSI 6600 or YSI 6600 EDS-S sonde was used to measure PAR.  Measurements of PAR were performed on the sunlit side of the research vessel in 0.5 meter depth increments, beginning just below the water surface.  The diffuse attenuation coefficient is the slope of the linear regression between natural log transformed PAR data and depth. 

Colored dissolved organic matter (CDOM) was measured using a Turner Designs TD-700 fluorometer configured with a near-UV mercury vapour lamp, a 350 nm excitation filter, and a 410–600 nm emission filter. The fluorometer was calibrated to quinine sulfate (QS) solutions made up in 2 N sulfuric acid. Water samples were vacuum filtered (less than 25 kilopascal) using pre-combusted Whatman glass microfibre filters (GF/F) and the filtrate was stored in scintillation vials in the dark at 4 degrees Celsius until fluorometric analysis.  The official decision (3/2/2017) is that cdom results from 12/1/2003 through 4/25/2011 would be multiplied by a corrective factor of 2.0.  Results for sample date of 5/9/2011 and after do not need correcting.  It is believed the stock solution was made wrong, making a 1L recipe for 600 ug/L in a 500 ml flask equals 1200 ug/L stock solution.  Standards were still calibrated according to recipe, but were actually 2x as strong. 

 The official decision (3/2/2017) is that cdom results from 12/1/2003 through 4/25/2011 would be multiplied by a corrective factor of 2.0.  Results for sample date of 5/9/2011 and after do not need correcting.  It is believed the stock solution was made wrong, making a 1L recipe for 600 ug/L in a 500 ml flask equals 1200 ug/L stock solution.  Standards were still calibrated according to recipe, but were actually 2x as strong. 

Particulate organic carbon (POC) concentrations were determined by elemental analysis of material collected on pre-combusted Whatman GF/F glass fiber filters.  Carbonates were removed from the filters by vapor phase acidification using concentrated hydrochloric acid (HCl).  After drying at 60 0C, the filters were rolled in tin disks and injected into a PE 2400 Series II CHNS/O Analyzer calibrated with acetanilide ending in June 2014.  Starting on the Neuse River sample date of June 2, 2014, a Costech Analytical Technologies, Inc. Elemental Combustion System CHNS-O ECS 4010 was used for elemental analysis by "flash combustion/chromatographic separation and multi-detector techniques".  The Costech Instrument utilizes EAS Clarity Software.  Atropine standards are used to develop a calibration curve (C 70.56%, N 4.84%, and carbon response ratio of 0.025 +/-0.003).  NIST Buffalo River Sediment Reference Material 8704 (C 3.351% +/-0.017, N 0.20% +/-0.04) and/or Acetanilide Bypass (C 71.09%, N 10.36%, carbon response ratio of 0.055 +/- 0.003) may used for calibration or a check standard.

The molar ratio of particulate organic carbon (POC) to particulate nitrogen (PN), or C:N, was calculated by dividing POC by PN.  (Carbon ug/L /12.011)/(Nitrogen ug/L/14.007).

Dissolved organic carbon (DOC) concentration was measured using a Shimadzu TOC-5000A Analyzer:  Water samples were vacuum filtered (less than 25 kilopascal) using pre-combusted Whatman glass microfibre filters (GF/F).  The filtrate was stored in pre-combusted glass scintillation vials with Teflon closures and frozen at -20 degrees Celsius until analysis.  The Shimadzu TOC-5000A Analyzer uses high temperature catalytic oxidation followed by non-dispersive infrared analysis of the CO2 produced.  Samples were acidified to a pH less than 2 and sparged with air before they were analyzed for non-volatile organic carbon.  DOC values in 1996 were run from previously run nutrient samples. Starting February 2018, all stations were collected.  Prior to Feb. 2018 only NR 0, 30, 70, 100, 120, and 160 surface and bottom stations were measured.

Nitrate/nitrite (NO3- / NO2-) concentration was determined using a Lachat/Zellweger Analytics QuikChem 8000 flow injection autoanalyzer (Milwaukee, WI, USA) using method FIA 31-107-04-1-C:  Water samples were vacuum filtered (less than 25 kiloPascals) using pre-combusted Whatman glass microfibre filters (GF/F).  The filtrate was stored in high-density polyethylene bottles and frozen at -20 degrees Celsius until analysis.  Two replicates were run from the same bottle.  Method detection limits (MDL, µg L-1) were: before 4Nov02 = 1.06; beginning 4Nov02 = 3.68; beginning 11Jul06 = 0.6; beginning 1Dec09 = 0.27; beginning 13Feb12 = 0.36; beginning 18Feb15 = 0.71.  MDL was changed to 0.88 on a sample date of 8/21/2017.

Ammonium (NH4+) concentration was determined using a Lachat/Zellweger Analytics QuikChem 8000 flow injection autoanalyzer (Milwaukee, WI) using method FIA 31-107-06-1-A/B:  Water samples were vacuum filtered (less than 25 kiloPascals) using pre-combusted Whatman glass microfibre filters (GF/F).  The filtrate was stored in high-density polyethylene bottles and frozen (-20 degrees Celsius) until analysis.  Two replicates were run from the same bottle.   Method detection limits (MDL, µg L-1) were: before 4Nov02 = 4.69; beginning 4Nov02 = 4.31; beginning 11Jul06 = 2.55; beginning 1Dec09 = 3.98; beginning 13Feb12 = 2.87; beginning 18Feb15 = 3.34.  MDL was changed to 1.05 on sample date 8/21/2017.

Dissolved inorganic nitrogen (DIN) concentration was calculated by summing nitrate/nitrite (NO3- / NO2-) and ammonium (NH4+).  If either NO3- / NO2- or NH4+ were below the detection limit (-9999), they were taken to be zero for this calculation.

Total dissolved nitrogen (TDN) was measured by in-line digestion using the Lachat/Zellweger Analytics QuikChem 8000 flow injection autoanalyzer (Milwaukee, WI, USA) using method FIA 31-107-04-3-B for low total nitrogen for brackish/fresh waters (detection level: 0.1 - 5.0 milligrams nitrogen per liter):  Water samples were vacuum filtered (less than 25 kiloPascals) using pre-combusted Whatman glass microfibre filters (GF/F).  The filtrate was stored in high-density polyethylene bottles and frozen at -20 degrees Celsius until analysis.  Two replicates were run from the same bottle.  Total dissolved nitrogen by in-line digestion works by oxidizing all the nitrogen compounds to nitrate by heating to 100 degrees Celsius and adding energy via UV light.  The pH is dropped from 9.1 to 3 during the decomposition.  The entire digestion occurs prior to the injection valve.  The nitrate/nitrite concentration is then determined using standard colorimetric techniques similar to the strict nitrate/nitrite manifold. Method detection limits (MDL, µg L-1) were: beginning 1Nov04 = 78; beginning 11Jul06 = 35.4 beginning 1Dec09 = 25.6; beginning 13Feb12 = 36.9; beginning 14Jan13 = 19.6; beginning 18Feb15 = 10.5.  MDL changed to 7.30 on sample date of 8/21/2017 

Dissolved organic nitrogen (DON) was calculated by subtracting dissolved inorganic nitrogen (DIN) from total dissolved nitrogen (TDN).  If the DIN value used in the calculation was below the detection limit, it was taken to be zero for this calculation.  At one point DON was determined by high temperature oxidation using the Antek 7000N or Antek 7000V analyzer.

Orthophosphate (PO43-) was determined using a Lachat/Zellweger Analytics QuikChem 8000 flow injection autoanalyzer (Milwaukee, WI) using method FIA 31-115-01-1-F/G:  Water samples were vacuum filtered (less than 25 kiloPascals) using pre-combusted Whatman glass microfibre filters (GF/F).  The filtrate was stored in high-density polyethylene bottles and frozen at -20 degrees Celsius until analysis.  Two replicates were run from the same bottle.  Method detection limits (MDL, µg L-1) were: before 4Nov02 = 0.35; beginning 4Nov02 = 0.74; beginning 1Nov04 = 1.68; beginning 11Jul06 = 1.84; beginning 1Dec09 = 0.62; beginning 13Feb12 = 0.69; beginning 18Feb15 = 0.61.  MDL was changed to 1.80 on the sample date of 8/21/2017.

The molar ratio of nitrogen (N) to phosphorus (P), or N:P, was calculated by dividing dissolved inorganic nitrogen (DIN) by orthophosphate (PO43-) concentrations.

Silicic acid (SiO2) was measured after vacuum filtration (< 25 kPA) of the collected water samples through pre-combusted (3-4 hours at 450 0C) Whatman GF/F glass fiber filters.  The filtrate was stored in high-density polyethylene bottles and frozen (-20 0C) until analysis.  Two replicates were run from the same sample bottle.  Nitrate plus nitrite concentrations were determined using a Lachat QuikChem 8000 flow injection autoanalyzer (Milwaukee, WI, USA).  Method detection limits (MDL, µM) were: before 4Nov02 = 0.18; beginning 4Nov02 =1.24; beginning 1Nov04 = 1.86; beginning 11Jul06 = 0.75; beginning 1Dec09 = 0.75; beginning 13Feb12 = 0.09; beginning 18Feb15 = 0.08.  MDL was changed to 0.03 on sample date of 8/21/2017.

Chlorophyll a (Chl a) measurements prior to the 08/17/1999 sampling date were measured on a Shimadzu UV-160U spectrophotometer using the trichromatic equation following sonication (45-60 s) and overnight extraction of glass fiber filters in 90 % acetone.  Beginning on the 08/17/1999 sampling date, Chl a concentration was measured using the modified in vitro fluorescence technique in EPA Method 445.0 (Welshmeyer 1994, Arar et al.  1997): Fifty milliliters of each water sample was vacuum filtered (less than 25 kilopascals) in duplicate at low ambient light conditions using 25 mm Whatman glass microfibre filters (GF/F).  The filters were blotted dry, wrapped in foil and frozen immediately at -20 degrees Celsius until analysis.  Chlorophyll a was extracted from the filter using a tissue grinder and 10 mL of 90 percent reagent grade aqueous acetone (v/v with deionized water, Fisher Scientific NF/FCC Grade). The samples remained in the acetone overnight at -20 degrees Celsius.  The extracts were filter-clarified using a centrifuge and analyzed on a Turner Designs TD-700 fluorometer that was configured for the non-acidification method of Welschmeyer (1994).  The value reported is the average chlorophyll a concentration measured from the two filters.  The fluorometer was calibrated with a known concentration of pure Chl a that was determined using a Shimadzu UV-160U spectrophotometer and the extinction coefficients of Jeffrey and Humphrey (1975).  The calibration was checked daily against a solid secondary standard (Turner Designs, proprietary formula).  As of August 2010, fluorescence was also measured on a TurnerDesigns Trilogy fluorometer.  References: 1.  Welschmeyer, N.A. 1994. Fluorometric analysis of chlorophyll a in the presence of chlorophyll b and pheopigments. Limnol. Oceanogr. 39:1985-1992.  2.  Arar, E.J., W.L. Budde, and T.D. Behymer.  1997.  Methods for the determination of chemical substances in marine and environmental matrices.  EPA/600/R-97/072.  National Exposure Research Laboratory, U.S. Environmental Protection Agency, Cincinnati, Ohio.  3. Jeffrey, S.W., R.F.C. Mantoura, and S.W. Wright.  1997.  Phytoplankton pigments in oceanography:  Guidelines to modern methods.  UNESCO Publishing, Paris, France.

Spec was used to determine chla up until AUGUST 1999.  The spec results before Aug 1999 are corrected to correspond to the change in analysis with the Turner Designs fluorometer.  Figure 1 presents raw and log transformed regressions between the HPLC and SPEC determinations of chl a in the Neuse during calendar year 1998.  It appears that the SPEC method produces chl a values that are roughly 15 per cent higher than the HPLC method.  Figure 2 presents similar regressions between HPLC and FLUO determinations of chl a in the Neuse from August – December of 1999.  It appears that the FLUO method produces chl a values that are roughly 67 per cent higher than the HPLC method.  These figures suggest two important problems for utilizing existing chl a data in water quality modeling in the Neuse; (i) a decision must be made which analysis technique will be accepted as the standard for determining chl a, and (ii) a correction must be applied to equilibrate IMS chl a values determined by the SPEC and FLUO methods.

Primary Productivity rate was measured using an adaptation of Steeman Nielsen's (1952) 14C bicarbonate method (Paerl et al. 1998).  This method of measuring primary productivity allows direct measurement of carbon uptake and measures only net photosynthesis:  Water samples were stored in 10 Liter high density polyethylene containers overnight in the research pond, a flow through system that receives water from the adjacent Bogue Sound, thereby simulating ambient water temperatures.  The following morning the water samples were removed from the pond and transported to the laboratory for analysis.  Water samples (76 milliliters) were added to three clear plastic square bottles to determine light uptake of carbon in triplicate and to 1 dark bottle to determine dark uptake of carbon.  A solution of radioactive carbonate (300 microliters) was added to each bottle.  The bottles were incubated for 4 hours in the pond.  The light bottles were incubated underneath a field light simulator, while the dark bottles were incubated in a covered perforated bucket that was submerged in the pond.  The FLS was used to simulate the ambient light conditions that phytoplankton are exposed to in the estuary (mixing conditions).  The FLS is comprised of a rotating wheel with varying levels of screening.  During the incubation period, photosynthetically active radiation (PAR) measurements were performed using a 2 pi Li-Cor LI-192SA spherical quantum sensor attached to a Li-Cor data logger.  After the incubation period, the samples were returned to the laboratory, shaken and the entire contents were gently vacuum filtered (less than 25 kilopascals) using 25 mm Whatman glass microfibre filters (GF/F).  The filters were placed in wooden drying trays and treated with concentrated hydrochloric acid fumes for 40 minutes to an hour to remove inorganic 14C.  The filters were folded in half and placed in 7 milliliter plastic scintillation vials.  Five milliliters of liquid scintillation cocktail (ecolume or cytoscint) was added to the vials.  The vials were capped, shaken, stored in the dark for 3-24 hours and then assayed for radioactivity using a Beckman liquid scintillation counter.  In addition to the samples, triplicate voucher samples were used to quantify the radioactivity of the 14C added.  Voucher samples consisted of 100 microliter of 14C and 100 microliters of phenylethylamine.  These vials also received 5 milliliters of liquid scintillation cocktail.  A background vial and two 14C background standards were used.   The quantity of carbon fixed is proportional to the fraction of radioactive carbon assimilated.  (Paerl, H.W., J.L. Pinckney, J.M. Fear, and B.L. Peierls 1998. Ecosystem responses to internal and watershed organic matter loading: consequences for hypoxia in the eutrophying Neuse River Estuary, North Carolina, USA. Marine Ecology Progress Series 166: 17-25; Steemann Nielsen, E. 1952. The use of radio-active carbon (C14) for measuring organic production in the sea. Journal du Conseil permanent international pour L'Exploration de la Mer 18: 117-140)

Diagnostic phytoplankton photopigments were identified, separated and quantified by high performance liquid chromatography coupled to an in-line photodiode array spectrophotometer (Jeffrey et al.  1997):  Known volumes of water sample (500-1000 milliliters, enough to obtain color on the filter) were vacuum filtered (less than 25 kiloPascals) through 25 or 47 millimeter Whatman glass microfibre filters (GF/F) under reduced light conditions.  The filters were blotted dry, folded in half, wrapped in foil and then immediately frozen at -20 degrees Celsius until analysis.  The filters were placed in 15 milliliter centrifuge tubes containing 1.5-3.0 milliliters of 100% acetone (HPLC Grade), sonicated for 30-60 seconds using a Fisher Sonic Dismembrator 300 with microtip and extracted at -20 degrees Celsius for 12-24 hours.  After extraction the samples were centrifuged at 4500 rpm and the supernatant (i.e.- the combined extracted pigments) collected & filtered into amber glass autosampler vials using Millipex Millipore 0.45 micometer PTFE.  Two hundred microliters of extractant from each vial was injected into the HPLC system using a Spectra Physics (now Thermo Separations Products) AS3000 autosampler and SP8800 pump, running a non-linear, 55 minute, 2-solvent gradient adapted from Van Heukelem et.al. 1994 or 1995?.  The nonlinear, variable flow, binary gradient consisted of solvent A [80% methanol : 20% ammonium acetate (0.5 M adjusted to pH 7.2)] and B (80% methanol : 20% acetone).  The extractant was separated into individual pigments using a series of C18 reverse-phase columns to optimize photopigment separations:  The column order was a Rainin Microsorb guard column (0.46 x 1.5 centimeters, 3 micrometer packing) followed by a single monomeric reverse-phase C18 column (Rainin Microsorb-MV, 0.46 x 10 cm, 3 µm packing) followed by two polymeric reverse-phase C18 columns (Vydac 201TP5, 0.46 x 25 cm, 5 µm packing).  The columns were kept at a constant 52 degrees Celsius in an Alltech 330 column heater.  The separated pigments were then passed through an in line Shimadzu SPD-M10AV photodiode array detector which measured the absorbance of the sample/extractant, scanning the range of 350-800 nanometers every 2 seconds.  The data was collected and analyzed using Shimadzu's EZChrom software.  Individual pigments are identified using a combination of peak retention time and absorbance spectrum shape.  Retention times and absorbance spectra are identified for each pigment by analyzing known pigments (either as pure standards or pigments or isolated from algal cultures).  Pigments are quantified from their peak areas, calculated at 440nm. A calibration curve is generated by injecting various volumes of a mixed standard composed of known quantities of seven pure pigment standards (fucoxanthin, zeaxanthin, bacteriochlorophyll a, canthaxathin, chlorophyll b, chlorophyll a, echinenone and ß-carotene) and calculating the peak areas of those pigments   The peak areas are regressed against the known quantities of each pigment to calculate the slope (Response Factor) for that pigment.  Response factors for pigments we do not have reference standards for are calculated using the ratio of absorbance coefficients of each pigment to its closest structurally related reference pigment, multiplying the known pigment's response factor by that ratio. Pigments extracted from the samples are then quantified by multiplying the peak areas of a chromatogram at 440nm by the response factors. Pigment values listed as below detection were below the software threshold for peak detection or had spectra below a similarity of 0.9 compared to library spectra. Technician expert judgement was used in difficult cases.

The HPLC derived diagnostic photopigment concentrations were analyzed using the ChemTax matrix factorization program (Mackey 1996).  This program uses the steepest decent algorithm to determine the best fit based on an initial estimate of pigment ratios for algal classes.  The initial pigment ratio matrix used in the Chemtax analysis was derived from:  Mackey M.D., Mackey D.J., Higgins H.W., & Wright S.W.  1996.  CHEMTAX- a program for estimating class abundances from chemical markers: application to HPLC measurements of phytoplankton.  Marine Ecology Progress Series 144: 265-283, and consisted of nine photopigments (alloxanthin, antheraxanthin, chlorophyll b, total chlorophyll a (chlorophyll a + chlorophyllide a), fucoxanthin, lutein, peridinin, violaxanthin, and zeaxanthin) for five algal groups that constitute the bulk of the phytoplankton community in the Neuse River and Estuary (chlorophytes, cryptophytes, cyanobacteria, diatoms, and dinoflagellates).  In order to reduce the variation of pigment ratios due to large changes in phytoplankton species composition with depth, season, and salinity regime, homogenous data groupings of the HPLC pigment data were performed prior to running on Chemtax:  HPLC pigment data was grouped by Depth Level (surface or bottom) then by Season (winter, spring, summer and fall) then by Salinity regime (oligohaline: <5.0 ppt, mesohaline: 5.01 - 18.0 ppt, polyhaline: >18.01 ppt).  When there were less than 10 samples in a given homogenous grouping (Chemtax requires at least 10 samples per run), the data was grouped by oligohaline + mesohaline or mesohaline + polyhaline (This is indicated in the comments section).

Distance (in river kilometers) was calculated using ESRI ArcGIS software.  Distances were calculated using projected station locations (North Carolina State Plane 1983 meters projection).  Distances from station 0 through 30 (upper river stations) were measured along the main channel of the river. Distances from stations 30 to 180 were measured as straight lines between stations

BCO-DMO Processing Notes:
- added conventional header with dataset name, PI name, version date
- modified parameter names to conform with BCO-DMO naming conventions
- appended the AMS station coordinate information
- combined the various comments fields into one Comments field.

NSF Award Abstract:

Climatic perturbations by drought-flood cycles, tropical storms, and hurricanes are increasingly important in Mid-Atlantic estuaries, leading to ecosystem-scale responses of the plankton system with significant trophic implications. Recent observations support an emerging paradigm that climate dominates nutrient enrichment in these ecosystems, explaining seasonal and interannual variability of phytoplankton floral composition, biomass (chl-a), and primary production (PP). This project will evaluate this paradigm in the two largest estuaries in the United States, Chesapeake Bay (CB) and Albemarle-Pamlico Sound-Neuse River Estuary (APS-NRE) by quantifying responses to climatic perturbations. This project will: (1) resolve long-term trends of plankton biomass/production from high variability driven by climatic forcing, such as drought-flood cycles that generate significant departures from the norm; (2) quantify the role of episodic wind and precipitation events, such as those associated with frontal passages, tropical storms, and hurricanes, that evoke consequential spikes of biomass/production outside the resolution of traditional methods. The field program will focus on event-scale forcing of phytoplankton dynamics by collecting shipboard, aircraft remote sensing, and satellite (SeaWiFS, MODIS-A) data, analyzing extensive monitoring data for CB and APS-NRE to develop context, and quantifying effects of climatic perturbations on phytoplankton dynamics as departures from long-term averages. The rapid-response sampling will be paired with numerical simulations using coupled hydrodynamic biogeochemical models based on the Regional Ocean Modeling System (ROMS). This combination of observations and modeling will be used to explore mechanistic links and test empirical relationships obtained from field data.

Intellectual Merit. Drought-flood cycles, tropical storms, and hurricanes are occurring at increasing severity and frequency, exerting significant pressures on land margin ecosystems. Research and monitoring in these ecosystems has focused singularly on eutrophication for nearly five decades. Recognition of climatic perturbations as the underlying cause of phytoplankton variability represents a significant departure from this singular focus. This project will combine observations and modeling to significantly extend our knowledge of how climate regulates phytoplankton dynamics in estuaries. Progress in calibrating and validating hydrodynamic biogeochemical models with data collected in CB and APS-NRE by this project will lead to predictive capabilities thus far unattained, allowing us to evaluate the paradigm that climatic perturbations regulate phytoplankton dynamics in estuaries.

Broader Impacts: Addressing the effects of climatic perturbations on phytoplankton dynamics in estuaries with a combination of data collection, analysis, and mechanistic modeling has societal benefits for scientists and resource managers. Applications in addition to ?basic? science include the consideration of climatic forcing in designing effective nutrient management strategies. Specific impacts include: (1) quantifying the effects of climatic perturbations on planktonic processes for important estuarine-coastal ecosystems; (2) extending empirically-based water quality criteria forward by enabling predictions of floral composition, chl-a, and PP in changing climate conditions; (3) combining observations and mechanistic models to support scenario analysis, allowing us to distinguish long-term trends from variability imposed by climate. This project will offer a graduate course in physical transport processes and plankton productivity that will benefit from this research, support two Ph.D. students, and train undergraduates in NSF REU and minority outreach programs at HPL-UMCES and IMS-UNC. The main products will be peer-reviewed publications and presentations at scientific meetings. The three PIs maintain active web sites that will be used to distribute results and data.

NOTE:

Dr. Harding was the original Lead PI. Dr. Michael R. Roman was named as substitute PI when Dr. Harding served as a Program Director in the NSF Biological Oceanography Program for two years, and through his move to UCLA thereafter. Dr. Harding is responsible for the data holdings on this project and for coordinating their submittal to BCO-DMO.