Contributors | Affiliation | Role |
---|---|---|
Frischer, Marc E. | Skidaway Institute of Oceanography (SkIO) | Principal Investigator |
Berger, Stella | Skidaway Institute of Oceanography (SkIO) | Project Coordinator, Contact |
Gegg, Stephen R. | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
The Skidaway River Monitoring Program (SRiMP) was initiated in 1986 and includes time series observations of hydrography, nutrients, auto- and heterotrophic microbial communities, phytoplankton, micro- and mesozooplankton, representative gelatinous zooplankton, and dissolved oxygen in a weekly to monthly resolution.
References:
Clesceri, L.S., A.E. Greenberg, A.D. Eaton. 1998. Standard Methods for the Examination of Water and Wastewater, 20th edition. Washington, DC. APHA, AWWA, WEF.
Gilbert, P.M., and T.C. Loder. 1977. Automated Analysis of nutrients in Seawater: a manual of techniques. Woods Hole Oceanographic Institute Technical Report WHOI-77-47.
Hansen, H.P., Determination of Oxygen. 1999. p. 75-89. In: K. Grasshoff, K. Kremling, and M. Ehrhardt (eds.). Methods of Seawater Analysis, 3rd edition, Wiley, Weinheim, New York.1999
Nejstgaard, J.C., M.E. Frischer, P.G. Verity, J.T. Anderson, A. Jacobsen, M.J. Zirbel, A. Larsen, J. Martínez-Martínez, A.F. Sazhin, T. Walters, D.A. Bronk, S.J. Whipple, S.R. Borett, B.C. Patten, J.D. Long. 2006. Plankton development and trophic transfer in seawater enclosures with nutrients and Phaeocystis pouchetii added. Marine Ecololy Progress Series 321:99-121.
Parsons, T.R.Y. Maita, and C.M. Lalli. 1984. Manual of Chemical and Biological Methods for Seawater Analysis, 3rd edition. Pergammon Press, New York.
Porter, K.G. and Y.S. Feig. 1980. The use of DAPI for identifying and counting aquatic microflora. Limnology and Oceanography 25: 943-948.
Shopov, A., S.C. Williams, and P.G. Verity 2000. Image analysis to discriminate and enumerate bacteria and viruses in aquatic samples. Aquatic Microbial Ecology 22: 103-110.
Solarzano, L., and J.H. Sharp 1980. Determination of total dissolved nitrogen in natural waters. Limnology and Oceanography 25: 751-754.
Utermöhl, H. 1958. Zur Vervollkommnung der quantitativen Phytoplankton-Methodik: Aus der Hydrobiologischen Anstalt der Max-Planck Gesellschft, Plön in Holstein. Mitteilungen der Internationalen Vereinigung für Theoretische und Angewandte Limnologie 9: 1-38.
Valderrama, J.C. 1981. The simultaneous analysis of total nitrogen and total phosphorus in natural waters. Marine Chemistry 10: 109-122.
Verity, P.G., J.A. Yoder, S.S. Bishop, J.R. Nelson, D.B. Craven, J.O. Blanton, C.Y. Robertson, and C.R. Tronzo. 1993. Composition, productivity, and nutrient chemistry of a coastal ocean planktonic food web. Continental Shelf Research 13: 741-776.
Verity, P.G. 2002a. A decade of change in the Skidaway River estuary. I. Hydrography and nutrients. Estuaries 25: 944-960.
Verity, P.G. 2002b. A decade of change in the Skidaway River estuary. II. Particulate organic carbon, nitrogen, and chlorophyll a. Estuaries 25: 961-975.
Verity, P.G., M.L. Alber, and S. B. Bricker. 2006. Development of hypoxia in well-mixed estuaries in the southeastern USA. Estuaries and Coasts 29: 665-673.
Verity, P.G., and D.G. Borkman. 2010. A Decade of Change in the Skidaway River Estuary. III.Plankton. Estuaries and Coasts 33: 513-540.
Williams, S.C., Y. Hong, D.C.A. Danaval, M.H. Howard-Jones, MH, D. Gibson, M.E. Frischer, and P.G. Verity. 1998. Distinguishing between living and nonliving bacteria: Evaluation of the vital stain propidium iodide and its combined use with molecular probes in aquatic samples. Journal of Microbiological Methods 32: 225-236.
Meteorological data are being continuously recorded by the SKiO weather station (http://weather.skio.usg.edu) which is located ~250 meters from the SRiMP sampling site. Actual meteorological data that include temperature, dew point, heat index, wind chill factor, relative humidity, barometric pressure, rainfall since midnight, wind direction, wind speed, peak wind gust, solar radiation, highest and lowest temperature since midnight, sunrise, sunset are utilized from the SKIO weather station using the SKIO Metric Mobile Weather application (weather.skio.usg.edu/metric/mini.html). In addition, historic meteorological data from an underground weather web page (http://www.wunderground.com/weatherstation/WXDailyHistory.asp?ID=KGASAVAN23) is included for a broader dataset.
Tidal stage (high, low and mid tide) and time determination has been extrapolated to local tide predictions by adding + 38 minutes to the data for the Tybee Lighthouse, Savannah River Entrance (station ID 8670892; 32.0333° N; 80.9017° W), which is located about 10 km from the SRiMP site. Corresponding heights of tidal stage are now recorded from Isle of Hope, Skidaway River (31.9833° N; 81.0500° W), located ca. 1.5 km from the SRiMP sampling site (http://tides.mobilegeographics.com/locations/2824.html).
Surface water temperature was measured weekly using a standard mercury thermometer (+- 0.1 ° C) as was surface salinity which used an AGE model 2100 salinometer from 1986 to 1996. From February 2004 until July 2011, water temperature, salinity, and dissolved oxygen (DO) were measured using a YSI Model 556 multi-probe system. From September 2011 until present, a multi-probe MANTA-2 (EUREKA Environmental Engineering, Austin, TX, USA) has been included to measure depths profiles of temperature, salinity, pH, conductivity, turbidity, in situ chlorophyll fluorescence and DO. The oxygen probe measurements are regularly (at least monthly) compared and calibrated (if necessary) against the high-precision Winkler titrations using a (Parsons et al., 1984; Hansen, 1999) and a Brinkmann Metrohm titrator. Also, monthly manual measurement of water surface temperature (standard mercury thermometer precision +- 0.1 °C), surface salinity (American Optical Refractometer; +- 0.2 psu or ppt), pH, and electrical conductivity (Hi 2550 pH/ORP & EC/TDS Meter, HANNA instruments, Smithfield, RI, USA) are standard protocol. Since early 2011, we have included weekly Secchi depth measurements in the SRiMP program.
From 1986 to 2011 the surface waters adjacent to the main dock of the Skidaway Institute of Oceanography were sampled using an acid cleaned bucket or a Niskin bottle at connective slack high and low waters on the same day. From 2011, water sampling of the Skidaway River Estuary is been performed at high tide in 1m depth using a Niskin bottle. Ctenophores are sampled at mid-tide the same day (method see below).
Sample water for the analyses of inorganic nutrients (PO4, Si(OH)4, NH4, NO3, NO2) is filtered through acid washed and pre-rinsed GFF filters using acid cleaned plastic syringes, and either analyzed fresh or stored at -20 °C in acid cleaned PE-bottles. Nutrient analyses were performed on automated procedures using a Technicon Auto Analyzer II; 0.1 µM precision (Gilbert and Loder 1977, Verity et al. 1993) while TDN was determined using persulfite digestion. DON was calculated as the difference between TDN and summed inorganic nitrogen (Solarzano and Sharp 1980, Valderrama 1981).
From 2011, dissolved nutrient concentrations [NO2/NO3, NH4, DON, PO4, Si(OH)4] are determined by contract with the nutrient analysis laboratory overseen by Dr. S. Joyce at the University of Georgia, Athens, GA. Continuing from mid 2011 to present, water samples for DIC and delta 13/12 C isotope ratios of 0.02 nylon filtered water samples is analyzed inhouse using a Mass Spectrometer (Thermo Scientific) in the lab of Dr. Jay Brandes (Skidaway Island Scientific Stable Isotope Laboratory, SISSIL). TDN and DOC concentrations of 0.2 µm filtered water samples are processed at SkIO by the lab of Dr. Aron Stubbins using a Total Organic Carbon Analyzer with a Total Nitrogen Measuring Unit (TOC-V and TNM-I, Shimadzu Scientific Instruments, Columbia, ML, USA).
Samples to determine the organic particulate fractions of carbon and nitrogen, i.e. POC and PON are filtered at low vacuum pressure (10 cm Hg) onto pre-combusted (450 °C for 4 h) 25 mm GF/F filters (Whatman). These filters are transferred to pre-combusted foil sheets and stored frozen at - 20 °C until analysis. In the past, filter samples were freeze-dried and combusted using a Fisons NA1500 NCS Series 2 CHNS analyzer and 2.5-Bis (5tert-butyl-2-benzo-oxazol-2-yl) thiophene (BBOT) standards (Verity 2002). Presently, POC and PON amounts and delta 13/12 C and 15/14 N isotope ratios are measured in house using a FLASH 2000 series CHNS/O elemental analyzer (Thermo Scientific) purchased in 2009.
Total viral abundance is determined by direct epifluorescence microscopic counting and quasi-automated image analysis (Shopov et a. 2000) using custom Skipper software (http://www.skipperimaging.com). Water samples are pre-filtered through 0.2 µm PC and then filtered onto 0.02 µm Anodisc filter and stained with SYBR Gold (Nobel and Fuhrman 1998).
Total bacteria abundance is determined by direct epifluorescence microscopic counting after staining with the DNA-specific fluorochrome DAPI following standard procedures (Porter and Feig 1980; Williams et al. 1998). Counting is facilitated by Bacteria data represent DAPI stained cells enumerated using epifluorescence microscopy, semiquasi-automated image analysis (Shopov et al. 2000) and custom Skipper software (http://www.skipperimaging.com) (Verity et al. 2006).
Total and fecal coliform bacteria concentration is determined using standard total coliform (method 9221B) and fecal coliform (method 9221E) procedures (Clesceri et al. 1998). Enterococci concentrations are determined using EPA method 1600.
Total and size fractionated (less and greater than 8 µm) phytoplankton chlorophyll-a concentrations are determined fluorometrically in house (lab of Dr. Jim Nelson) following the acetone extraction method as described by Parsons et al. (1984). From 2011, 0.2 µm and 8 µm PC filters are used for total and > 8µm fractions of chl-a analyses, respectively, following the acetone extraction overnight method as described for cellulose acetate filters in Nejstgaard et al. (2006) and compared to the chl-a in situ fluorescence readings of the MANTA-2 multiprobe.
Abundance and biomass of nanoplankton taxonomic groups are determined using true-color epifluorescence image analyzed microscopy. Water samples are fixed with glutaraldehyde and stained with proflavine-DAPI (Verity and Sieracki, 1993; Shopov et al., 2000). This protocol has been used since 1986 with the custom Skipper software (www.skio.usg.edu/?p=research/bio/veritylab/ip); (Verity and Borkman 2010). Since 2011, the program Image Pro-Plus (Media Cybernetics) is utilized to determine auto- and heterotrophic organisms. In addition, a detailed assessment of the microplanktonic community composition (including ciliates) is mapped four times per year using classical microscopic sedimentation techniques (Utermöhl 1958) after Lugol's fixation. Currently, emphasis is focused on flagellates vs. diatoms as indicators of environmental quality, with attention to potential harmful algal groups.
Since 2012, a variety of flow cytometric instruments are utilized to quantify picoplankton and larger microplankton including diatoms and dinoflagellates in our SRiMP program. Picoplankton analysis is performed by Dr. Liz Mann using a FacsCalibur (BD Biosciences, San Jose, CA, USA) in house. Additionally, we employ a state of the art CytoSense benchtop flow cytometer equipped with an imaging system and wide (1.5 mm) flow-cell uniquely capable of rapid analysis of live cells including large and chain-forming species (up to 4 mm long) such as diatoms and dinoflagellates (CytoBouy b.v., Woerden, the Netherlands, http://www.cytobuoy.com) performed in house by Dr. Jens Nejstgaard.
During the first decade, dominant copepods (Acartia spp.) were collected at the same sample site in approximately 6 week intervals by net tows (153 µm nylon mesh net, diameter 30 cm, length 150 cm). The net was towed for 15 minutes during maximum flood tide and again during ebb tide. Volume filtered for each tow was calculated from a flowmeter (General Oceanics) mounted in the mouth of the net. The content of the cod end was preserved in 3 % buffered formalin and stored at room temperature until counting under a dissecting microscope. Since 2011, net tows (65 µm mesh size, diameter 30 cm, length 100 cm) are collected at the same sample site in weekly intervals to determine copepods + eggs (mainly Acartia tonsa) abundances. The net is towed from 5 m to the surface during maximum flood tide. The sample is preserved in 3 % formalin and stored in the refrigerator (4 °C) until counting under a dissecting microscope.
Ctenophores (Mnemiopsis leidyi and Beroe sp.) are quantified weekly to monthly. Samples are collected using a 0.5 m zooplankton net (153 μm) fitted with a TSK flowmeter for ctenophores and jellies, and hauled obliquely from near-bottom to the surface for 5 minutes repeated trips through the water column. Ctenophore/jelly samples are sorted live in the lab immediately. Depending on taxa, various morphometric and volumetric measurements are recorded. Morphometric measurements are facilitated using a zoom stereoscope, e.g. trunk length, lobe or bell diameter, body width.
Aside from Quality Control and Quality Assurance (QA/QC) the SRiMP dataset has not been processed post analytical collection. Quarterly, all data entered into the SRiMP dataset is independently reviewed by a qualified technician or PI to assure that data is within expected ranges defined by historical values of a particular value. If individual data entries are out of range the data is scrutinized for obvious errors associated with the analytical process and/or data entry errors. If no obvious problems with the data are discovered the data is left in the dataset.
Parameter | Description | Units |
Year | year of sampling | YYYY |
Sample_ID | Sample ID | text |
Date | date of sampling | YYYYMMDD |
Time | Time as HHMMSS | HHMMSS |
Tide | Tidal Stage: | text |
Tide_Height | Predicted sea level at high and low tide | mm |
Day_of_the_week | Day of the week | text |
Time_AmPm | Time as HH:MM:SS AM or PM | HH:MM:SS AM or PM |
Day_Number | Day number (day 0 = 8/26/1986) | integer |
Location | Sampling location: main dock fuel dock MECA dock MECA Boat | text |
Lat | Sample Station Latitude (South is negative) | decimal degrees |
Lon | Sample Station Longitude (West is negative) | decimal degrees |
Collection_Type | Collection type: Water sample appendicularians ctenophores | text |
Comments | Comments | text |
Weather | Weather description | text |
Air_Temp | Air Temperature | degrees Celsius |
Dew_Point | Dew Point | degrees Celsius |
Heat_Index | Heat Index | degrees Celsius |
Wind_Chill | Wind Chill Factor | degrees Celsius |
Rel_Humidity | Relative Humidity | percentage |
Bar_Pressure | Barometric Pressure | kPa |
Rainfall | Rainfall since Midnight | mm |
Wind_Direction | Wind Direction (N W S E) | text |
Wind_Speed | Wind Speed | km/h |
Peak_Wind_Gust | Peak Wind Gust | km/h |
Solar_Radiation | Solar Radiation | W/m2 |
High_Temp | Highest Temperature since Midnight | degrees Celsius |
Low_Temp | Highest Temperature since Midnight | degrees Celsius |
Sunrise | Sunrise | HH:MM:SS AM or PM |
Sunset | Sunset | HH:MM:SS AM or PM |
Irradiance | Irradiance at 1m depth in percent of incident irradiance Io | perentage Io |
Sampling_Depth | Sampling Depth | meters |
Secchi_Depth | Secchi depth | meters |
Turbidity_MANTA_2 | Turbidity MANTA-2 (EUREKA Environmental) | NTU |
Rainfall_Actual | actual rainfall | inches |
Precipitation_week | Precipitation per previous week | mm/week |
Ogeechee_River_Discharge | Ogeechee River Discharge | m3/s |
pH_lab_115 | pH laboratory 115 | number |
pH_MANTA_2 | pH MANTA-2 (EUREKA Environmental) | number |
Salinity | Salinity using a refractometer | ppt |
Salinity_MANTA_2 | Salinity measured with MANTA-2 | ppt |
Specific_Conductance | Specific Conductance | mS/cm |
Specific_Conductance_MANTA_2 | Specific Conductance MANTA-2 | mS/cm |
Water_Temperature | Water Temperature measured with a mercury thermometer | degrees Celsius |
Water_Temperature_MANTA_2 | Water Temperature measured with MANTA-2 | degrees Celsius |
DO_YSI_556__MANTA_2 | Dissolved Oxygen concentration (YSI-556 or MANTA-2) | mg/l |
DO_percent_sat_YSI_556__MANTA_2 | Saturated Dissolved Oxygen (YSI-556 or MANTA-2) in percent | percentage |
DO_YSI_for_Winklers | Dissolved Oxygen concentration using YSI-556 for intercalibration with Winklers | mg/l |
DO_Winkler | Dissolved Oxygen using Winkler Method | mg/l |
DON | Dissolved Organic Nitrogen | umol N/l |
TDN | Total Dissolved Nitrogen | umol N/l |
TDN_StdDev | Total Dissolved Nitrogen Standard Deviation | umol N/l |
NO3 | Nitrate | umol N/l |
NO3_StdDev | Nitrate Standard Deviation | umol N/l |
NO2 | Nitrite | umol N/l |
NO2_StdDev | Nitrite Standard Deviation | umol N/l |
NOx | Nitrate +Nitrite | umol N/l |
NH4 | Ammonium | umol N/l |
NH4_StdDev | Ammonium Standard Deviation | umol N/l |
T_DIN | Total Dissolved Inorganic Nitrogen (NOx + NH4) | umol N/l |
Si_OH_4 | Silicate | umol Si/l |
Si_StdDev | Silicate Standard Deviation | umol Si/l |
PO4 | Phosphate | umol P/l |
PO4_StdDev | Phosphate Standard Deviation | umol P/l |
DIC | Dissolved Inorganic Carbon | mmol C/l |
DIC_StdDev | Dissolved Inorganic Carbon Standard Deviation | mmol C/l |
delta_13C_DIC | Delta Carbon-13 Isotope of DIC | percentage |
StdDev_13C_DIC | Delta Carbon-13 Isotope of DIC Standard Deviation | percentage |
Deut_Hydro | Deuterium to Hydrogen ratio | percentage |
Oxygen_18O | Delta Oxygen-18 isotope | percentage |
DOC | Dissolved Organic Carbon | umol C /l |
POC | Particulate Organic Carbon | ug /l |
delta_13C_POC | Delta Carbon-13 Isotope of POC | percentage |
PON | Particulate Organic Nitrogen | ug /l |
delta_15N_PON | Delta Nitrogen-15 Isotope of PON | percentage |
DIN_PO4 | Dissolved inorganic Nitrogen to Phosphate mass ratio | mol/mol |
DIN_Si | Dissolved Inorganic Nitrogen to Si(OH)4 mass ratio | mol/mol |
TDN_PO4 | Total Dissolved Nitrogen to Phosphate mass ratio | mol/mol |
TDN_Si | Total Dissolved Nitrogen to Si(OH)4 mass ratio | mol/mol |
Chla_total_MANTA_2 | Total Chlorophyll-a concentration using MANTA-2 | ug/l |
Chla_total_GFF | Total Chlorophyll-a filtered on GFF | ug/l |
Chla_total_GFF_StdDev | Toyal Chlorophyll-a filtered on GFF Standard Deviation | ug/l |
Chla_total_PC | Total Chlorophyll-a filtered on Polycarbonate filters 0.2 um | ug/l |
Chla_total_PC_StdDev | Total Chlorophyll-a filtered on PC 0.2 um Standard Deviation | ug/l |
Phaeo_total | Total Phaeophytin filtered on GFF | µg/l |
Phaeo_StdDev | Total Phaeophytin filtered on GFF Standard Deviation | ug/l |
Phaeo_PC_total | Phaeophytin total filtered on PC 0.2 um | ug/l |
Phaeo_PC_StdDev | Phaeophytin total filtered on PC 0.2 um Standard Deviation | ug/l |
Chla_gt8 | Chlorphyll-a greater than 8 um GFF (calculated) | ug/l |
Chla_lt8 | Chlorphyll-a less than 8 um GFF (measured) | ug/l |
Chla_gt8_PC | Chlorphyll-a greater than 8 um PC (measured) | ug/l |
Chla_gt8_PC_StdDev | Chlorphyll-a greater than 8 um PC (measured) Standard Deviation | ug/l |
Phaeo_gt8_PC | Phaeophytin greater than 8 um PC (measured) | ug/l |
Phaeo_gt8_PC_StdDev | Phaeophytin greater than 8 um PC (measured) Standard Deviation | ug/l |
Chla_lt8_PC | Chlorphyll-a less than 8 um PC (calculated) | ug/l |
Chla_lt8_PC_StdDev | Chlorphyll-a less than 8 um PC (calculated) Standard Deviation | ug/l |
Phaeo_lt8_PC | Phaeophytin less than 8 um PC (calculated) | ug/l |
Phaeo_lt8_PC_StdDev | Phaeophytin less than 8 um PC (calculated) Standard Deviation | ug/l |
Chla_gt8_to_total | Ratio of Chlorphyll-a less than 8 um to total Chl-a | ug/ug |
Chla_lt8_to_total | Ratio of Chlorphyll-a greater than 8 um to total Chl-a | ug/ug |
C_N_mass | POCC to PON mass ratio | ug/ug |
C_N_molar | POC to PON molar mass ratio | mol/mol |
C_Chla | Carbon to Chlorophyll-a mass ratio | ug/ug |
N_Chla | Nitrogen to Chlorophyll-a mass ratio | ug|ug |
Viruses | Viruses abundance | viruses/ml |
Viruses_StDev | Viruses abundance standard deviaton | viruses/ml |
Bacteria | Bacteria abundance | 10^6 cells/ml |
Bacteria_DAPI_Autocount | Bacteria abundance using DAPI Autocount | 10^6 cells/ml |
Bacteria_DAPI_Autocount_SD | Bacteria DAPI Autocount Std Dev | 10^6 cells/ml |
Pnano | Photosynthetic Nanoplankton abundance | 10^3 cells/ml |
Hnano | Heterotrophic Nanoplankton abundance | 10^3 cells/ml |
Hdino | Heterotrophic Dinoflagellates abundance | cells/ml |
Cyano | Cyanobacteria | cells/ml |
Diatoms | Diatom abundance | cells/ml |
Ciliates | Ciliate abundance | cells/ml |
Acartia_tonsa | Acartia tonsa abundance | individuals/l |
Pn_plus_Hn | Phototrophic plus Heterotrophic Nanoplankton | 10^3 cells/ml |
Hnano_Bac | Ratio of Heterotrophic Nanoplankton to Bacteria | 10^3 cells/10^6 cells |
Cil_Pnano | Ratio to Ciliate to Photosynthetic Nanoplankton | cells/10^3 cells |
Acartia_Ciliates | Ratio of Acartia to Ciliate (x10^-3) abundance | individuals/inividuals x10^3 |
Acartia_to_Total_Chla | Ratio of Acartia to Total Chloriphyll-a | inividuals/ug |
Cil_to__Pn_plus_Hn | Ratio of Ciliates to Phototrophic plus Heterotrophic Nanoplankton | cells/10^3 cells |
Cil_Bac | Ratio of Ciliates to Bacteria | cells/10^6 cells |
Cil__Pn_plus_Hn_plus_Bac | Ratio of ciliates to Phototrophic plus Heterotrophic Nanoplankton plus Bacteria | Cells/10^3 10^6 cells |
Acartia_to_Chla_gt8 | Ratio of Acartia to Chloriphyll-a greater than 8 um | inividuals/ug |
Pnana_to_Chla_lt8 | Ratio of Phtottrophic Nanoflagellates to Chlorphyll-a greater than 8 um | cellsx10^3/ug |
Chlagt8_Chlatotal__Chlalt8_chlatotal_xChlatotal | Ratio of Chlorphyll-a greater than 8 um to total Chl-a divided by ratio of Chlorphyll-a less than 8 um to total Chl-a multiplied by total Chl-a | ug/l |
Appendicularians | Appendicularian abundance | individuals/m3 |
Appendicularians_StdDev | Appendicularian abundance Standard Deviation | individuals/m3 |
Appendicularia_trunk_length | Appendicularia trunk length | mm |
Appendicularia_trunk_length_StdDev | Appendicularia trunk length Standard Deviation | mm |
Appendicularian_trunk_and_tail_length | Appendicularian trunk and tail length | mm |
Appendicularian_trunk_and_tail_length_StdDev | Appendicularian trunk and tail length Standard Deviation | mm |
Total_Mnemiopsis | Total Mnemiopsis abundance | individuals/m3 |
Total_Mnemiopsis_StdDev | Total Mnemiopsis abundance Standard Deviation | individuals/m3 |
Mnemiopsis_0_to_1cm | Mnemiopsis 0 to 1 cm long | individuals/m3 |
Mnemiopsis_0_to_1cm_StdDev | Mnemiopsis 0 to 1 cm long Standard Deviation | individuals/m3 |
Mnemiopsis_1point1_to_2cm | Mnemiopsis 1.1 to 2 cm long | individuals/m3 |
Mnemiopsis_1point1_to_2cm_StdDev | Mnemiopsis 1.1 to 2 cm long Standard Deviation | individuals/m3 |
Mnemiopsis_2point1_to_3cm | Mnemiopsis 2.1 to 3 cm long | individuals/m3 |
Mnemiopsis_2point1_to_3cm_StdDev | Mnemiopsis 2.1 to 3 cm long Standard Deviation | individuals/m3 |
Mnemiopsis_3point1_to_4cm | Mnemiopsis 3.1 to 4 cm long | individuals/m3 |
Mnemiopsis_3point1_to_4cm_StdDev | Mnemiopsis 3.1 to 4 cm long Standard Deviation | individuals/m3 |
Mnemiopsis_4point1_to_5cm | Mnemiopsis 4.1 to 5 cm long | individuals/m3 |
Mnemiopsis_4point1_to_5cm_StdDev | Mnemiopsis 4.1 to 5 cm long Standard Deviation | individuals/m3 |
Mnemiopsis_5point1_to_6cm | Mnemiopsis 5.1 to 6 cm long | individuals/m3 |
Mnemiopsis_5point1_to_6cm_StdDev | Mnemiopsis 5.1 to 6 cm long Standard Deviation | individuals/m3 |
Mnemiopsis_6point1_to_7cm | Mnemiopsis 6.1 to 7 cm long | individuals/m3 |
Mnemiopsis_6point1_to_7cm_StdDev | Mnemiopsis 6.1 to 7 cm long Standard Deviation | individuals/m3 |
Mnemiopsis_7point1_to_8cm | Mnemiopsis 7.1 to 8 cm long | individuals/m3 |
Mnemiopsis_7point1_to_8cm_StdDev | Mnemiopsis 7.1 to 8 cm long Standard Deviation | individuals/m3 |
Mnemiopsis_8point1_to_9cm | Mnemiopsis 8.1 to 9 cm long | individuals/m3 |
Mnemiopsis_8point1_to_9cm_StdDev | Mnemiopsis 8.1 to 9 cm long Standard Deviation | individuals/m3 |
Mnemiopsis_9point1_to_10cm | Mnemiopsis 9.1 to 10 cm long | individuals/m3 |
Mnemiopsis_9point1_to_10cm_StdDev | Mnemiopsis 9.1 to 10 cm long Standard Deviation | individuals/m3 |
Mnemiopsis_10point1_to_11cm | Mnemiopsis 10.1 to 11 cm long | individuals/m3 |
Mnemiopsis_10point1_to_11cm_StdDev | Mnemiopsis 10.1 to 11 cm long Standard Deviation | individuals/m3 |
Total_Beroe | Total Beroe abundance | individuals/m3 |
Total_Beroe_StdDev | Total Beroe abundance Standard Deviation | individuals/m3 |
Beroe_0_to_1cm | Beroe 0 to 1 cm long | individuals/m3 |
Beroe_0_to_1cm_StdDev | Beroe 0 to 1 cm long Standard Deviation | individuals/m3 |
Beroe_1point1_to_2cm | Beroe 1.1 to 2 cm long | individuals/m3 |
Beroe_1point1_to_2cm_StdDev | Beroe 1.1 to 2 cm long Standard Deviation | individuals/m3 |
Beroe_2point1_to_3cm | Beroe 2.1 to 3 cm long | individuals/m3 |
Beroe_2point1_to_3cm_StdDev | Beroe 2.1 to 3 cm long Standard Deviation | individuals/m3 |
Beroe_3point1_to_4cm | Beroe 3.1 to 4 cm long | individuals/m3 |
Beroe_3point1_to_4cm_StdDev | Beroe 3.1 to 4 cm long Standard Deviation | individuals/m3 |
Beroe_4point1_to_5cm | Beroe 4.1 to 5 cm long | individuals/m3 |
Beroe_4point1_to_5cm_StdDev | Beroe 4.1 to 5 cm long Standard Deviation | individuals/m3 |
Beroe_5point1_to_6cm | Beroe 5.1 to 6 cm long | individuals/m3 |
Beroe_5point1_to_6cm_StdDev | Beroe 5.1 to 6 cm long Standard Deviation | individuals/m3 |
Beroe_6point1_to_7cm | Beroe 6.1 to 7 cm long | individuals/m3 |
Beroe_6point1_to_7cm_StdDev | Beroe 6.1 to 7 cm long Standard Deviation | individuals/m3 |
Beroe_7point1_to_8cm | Beroe 7.1 to 8 cm long | individuals/m3 |
Beroe_7point1_to_8cm_StdDev | Beroe 7.1 to 8 cm long Standard Deviation | individuals/m3 |
Beroe_8point1_to_9cm | Beroe 8.1 to 9 cm long | individuals/m3 |
Beroe_8point1_to_9cm_StdDev | Beroe 8.1 to 9 cm long Standard Deviation | individuals/m3 |
Beroe_9point1_to_10cm | Beroe 9.1 to 10 cm long | individuals/m3 |
Beroe_9point1_to_10cm_StdDev | Beroe 9.1 to 10 cm long Standard Deviation | individuals/m3 |
Beroe_10point1_to_11cm | Beroe 10.1 to 11 cm long | individuals/m3 |
Beroe_10point1_to_11cm_StdDev | Beroe 10.1 to 11 cm long Standard Deviation | individuals/m3 |
Dataset-specific Instrument Name | SKiO Weather Station |
Generic Instrument Name | Automated Weather Station |
Dataset-specific Description | SKiO Weather Station |
Generic Instrument Description | Land-based AWS systems are designed to record meteorological information. |
Dataset-specific Instrument Name | BD FACSCalibur flow cytometer |
Generic Instrument Name | BD FACSCalibur Flow Cytometer |
Dataset-specific Description | BD FACSCalibur flow cytometer
Since 2012, a variety of flow cytometric instruments are utilized to quantify picoplankton and larger microplankton including diatoms and dinoflagellates in our SRiMP program. Picoplankton analysis is performed by Dr. Liz Mann using a FacsCalibur (BD Biosciences, San Jose, CA, USA) in house. Additionally, we employ a state of the art CytoSense benchtop flow cytometer equipped with an imaging system and wide (1.5 mm) flow-cell uniquely capable of rapid analysis of live cells including large and chain-forming species (up to 4 mm long) such as diatoms and dinoflagellates (CytoBouy b.v., Woerden, the Netherlands, http://www.cytobuoy.com) performed in house by Dr. Jens Nejstgaard. |
Generic Instrument Description | The FACSCalibur flow cytometer is an autonomous benchtop flow cytometer designed for routine cell analysis, assay development, verification and identification of cellular populations. It is equipped with a blue (488 nm) air-cooled argon laser and a red (635 nm) diode laser. For each particle (cell), five optical parameters can be recorded from the 488 nm laser beam excitation: two light scatter signals, namely forward and right angle, and three fluorescences corresponding to emissions in green (530/30 nm BP), orange (585/42 nm BP) and red (670 nm LP) wavelength ranges. A far red fluorescence (661/16 nm BP) induced by the red diode can also be recorded. Data are analysed using BD Biosciences CellQuest software. Optional features include a cell sorting option, allowing users to identify and isolate a population of interest and a HTS option (High-throughput (HT) or Standard (STD) mode), where sample volumes range from 2-10 microlitres in HT mode and 2-200 microlitres in STD mode. An optional BD FACS Loader tube-lifter can be used to verify tube position and rack identification. The instrument has a capture rate of 300 cells per second, supports 40 (12 x 75 mm) tubes per rack, and has an operating temperature ranging from 16-29 degC.
|
Dataset-specific Instrument Name | bucket |
Generic Instrument Name | bucket |
Dataset-specific Description | From 1986 to 2011 the surface waters adjacent to the main dock of the Skidaway Institute of Oceanography were sampled using an acid cleaned bucket or a Niskin bottle |
Generic Instrument Description | A bucket used to collect surface sea water samples. |
Dataset-specific Instrument Name | Thermo Scientific FLASH 2000 series CHNS/O elemental analyzer |
Generic Instrument Name | CHN Elemental Analyzer |
Dataset-specific Description | Thermo Scientific FLASH 2000 series CHNS/O elemental analyzer
Presently, POC and PON amounts and delta 13/12 C and 15/14 N isotope ratios are measured in house using a FLASH 2000 series CHNS/O elemental analyzer (Thermo Scientific) purchased in 2009 |
Generic Instrument Description | A CHN Elemental Analyzer is used for the determination of carbon, hydrogen, and nitrogen content in organic and other types of materials, including solids, liquids, volatile, and viscous samples. |
Dataset-specific Instrument Name | CytoSense benchtop flow cytometer |
Generic Instrument Name | CytoSense flow cytometer |
Dataset-specific Description | CytoSense benchtop flow cytometer
Since 2012, a variety of flow cytometric instruments are utilized to quantify picoplankton and larger microplankton including diatoms and dinoflagellates in our SRiMP program. Picoplankton analysis is performed by Dr. Liz Mann using a FacsCalibur (BD Biosciences, San Jose, CA, USA) in house. Additionally, we employ a state of the art CytoSense benchtop flow cytometer equipped with an imaging system and wide (1.5 mm) flow-cell uniquely capable of rapid analysis of live cells including large and chain-forming species (up to 4 mm long) such as diatoms and dinoflagellates (CytoBouy b.v., Woerden, the Netherlands, http://www.cytobuoy.com) performed in house by Dr. Jens Nejstgaard. |
Generic Instrument Description | The CytoSense is a portable, benchtop autonomous flow cytometer designed for phytoplankton species classification and analysis of filamentous algae. It can also be used in situ to reveal temporal and spatial phytoplankton variability. It can be remotely controlled, and has been specifically designed to record the optical pulse shapes of suspended particles between |
Dataset-specific Instrument Name | TSK flowmeter |
Generic Instrument Name | Flow Meter |
Dataset-specific Description | TSK flowmeter
Samples are collected using a 0.5 m zooplankton net (153 μm) fitted with a TSK flowmeter for ctenophores and jellies |
Generic Instrument Description | General term for a sensor that quantifies the rate at which fluids (e.g. water or air) pass through sensor packages, instruments, or sampling devices. A flow meter may be mechanical, optical, electromagnetic, etc. |
Dataset-specific Instrument Name | General Oceanics Flow Meter |
Generic Instrument Name | Flow Meter |
Dataset-specific Description | General Oceanics Flow Meter
Volume filtered for each tow was calculated from a flowmeter (General Oceanics) mounted in the mouth of the net |
Generic Instrument Description | General term for a sensor that quantifies the rate at which fluids (e.g. water or air) pass through sensor packages, instruments, or sampling devices. A flow meter may be mechanical, optical, electromagnetic, etc. |
Dataset-specific Instrument Name | Thermo Scientific Mass Spectrometer |
Generic Instrument Name | Isotope-ratio Mass Spectrometer |
Dataset-specific Description | Continuing from mid 2011 to present, water samples for DIC and delta 13/12 C isotope ratios of 0.02 nylon filtered water samples is analyzed inhouse using a Mass Spectrometer (Thermo Scientific) in the lab of Dr. Jay Brandes (Skidaway Island Scientific Stable Isotope Laboratory, SISSIL) |
Generic Instrument Description | The Isotope-ratio Mass Spectrometer is a particular type of mass spectrometer used to measure the relative abundance of isotopes in a given sample (e.g. VG Prism II Isotope Ratio Mass-Spectrometer). |
Dataset-specific Instrument Name | Hi 2550 pH/ORP & EC/TDS Meter |
Generic Instrument Name | Multi Parameter Bench Meter |
Dataset-specific Description | Hi 2550 pH/ORP & EC/TDS Meter |
Generic Instrument Description | An analytical instrument that can measure multiple parameters, such as pH, EC, TDS, DO and Temperature with one device. |
Dataset-specific Instrument Name | Niskin bottle |
Generic Instrument Name | Niskin bottle |
Dataset-specific Description | From 1986 to 2011 the surface waters adjacent to the main dock of the Skidaway Institute of Oceanography were sampled using an acid cleaned bucket or a Niskin bottle |
Generic Instrument Description | A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends. The bottles can be attached individually on a hydrowire or deployed in 12, 24, or 36 bottle Rosette systems mounted on a frame and combined with a CTD. Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc. |
Dataset-specific Instrument Name | Technicon Auto Analyzer II |
Generic Instrument Name | Nutrient Autoanalyzer |
Dataset-specific Description | Technicon Auto Analyzer II
Nutrient analyses were performed on automated procedures using a Technicon Auto Analyzer II; 0.1 µM precision |
Generic Instrument Description | Nutrient Autoanalyzer is a generic term used when specific type, make and model were not specified. In general, a Nutrient Autoanalyzer is an automated flow-thru system for doing nutrient analysis (nitrate, ammonium, orthophosphate, and silicate) on seawater samples. |
Dataset-specific Instrument Name | Phytoplankton Net |
Generic Instrument Name | Phytoplankton Net |
Dataset-specific Description | During the first decade, dominant copepods (Acartia spp.) were collected at the same sample site in approximately 6 week intervals by net tows (153 µm nylon mesh net, diameter 30 cm, length 150 cm
Samples are collected using a 0.5 m zooplankton net (153 μm) fitted with a TSK flowmeter for ctenophores and jellies |
Generic Instrument Description | A Phytoplankton Net is a generic term for a sampling net having mesh size of 150 microns or less that is used to collect phytoplankton. It is used only when detailed instrument documentation is not available. |
Dataset-specific Instrument Name | American Optical Refractometer |
Generic Instrument Name | Refractometer |
Dataset-specific Description | American Optical Refractometer; +- 0.2 psu or ppt |
Generic Instrument Description | A refractometer is a laboratory or field device for the measurement of an index of refraction (refractometry). The index of refraction is calculated from Snell's law and can be calculated from the composition of the material using the Gladstone-Dale relation.
In optics the refractive index (or index of refraction) n of a substance (optical medium) is a dimensionless number that describes how light, or any other radiation, propagates through that medium. |
Dataset-specific Instrument Name | AGE Model 2100 Salinometer |
Generic Instrument Name | Salinometer |
Dataset-specific Description | Surface salinity was measured with an AGE model 2100 salinometer from 1986 to 1996 |
Generic Instrument Description | A salinometer is a device designed to measure the salinity, or dissolved salt content, of a solution. |
Dataset-specific Instrument Name | Secchi Disc |
Generic Instrument Name | Secchi Disc |
Dataset-specific Description | Since early 2011, weekly Secchi depth measurements were included in the SRiMP program |
Generic Instrument Description | Typically, a 16 inch diameter white/black quadrant disc used to measure water optical clarity |
Dataset-specific Instrument Name | Shimadzu TNM-I Total Nitrogen Analyzer |
Generic Instrument Name | Total Nitrogen Analyzer |
Dataset-specific Description | TDN and DOC concentrations of 0.2 µm filtered water samples are processed at SkIO by the lab of Dr. Aron Stubbins using a Total Organic Carbon Analyzer with a Total Nitrogen Measuring Unit (TOC-V and TNM-I, Shimadzu Scientific Instruments, Columbia, ML, USA) |
Generic Instrument Description | A unit that accurately determines the nitrogen concentrations of organic compounds typically by detecting and measuring its combustion product (NO). See description document at: http://bcodata.whoi.edu/LaurentianGreatLakes_Chemistry/totalnit.pdf |
Dataset-specific Instrument Name | Shimadzu TOC-V Analyzer |
Generic Instrument Name | Total Organic Carbon Analyzer |
Dataset-specific Description | TDN and DOC concentrations of 0.2 µm filtered water samples are processed at SkIO by the lab of Dr. Aron Stubbins using a Total Organic Carbon Analyzer with a Total Nitrogen Measuring Unit (TOC-V and TNM-I, Shimadzu Scientific Instruments, Columbia, ML, USA) |
Generic Instrument Description | A unit that accurately determines the carbon concentrations of organic compounds typically by detecting and measuring its combustion product (CO2). See description document at: http://bcodata.whoi.edu/LaurentianGreatLakes_Chemistry/bs116.pdf |
Dataset-specific Instrument Name | Multi-Probe MANTA-2 |
Generic Instrument Name | Water Quality Multiprobe |
Dataset-specific Description | Multi-Probe MANTA-2
From September 2011 until present, a multi-probe MANTA-2 (EUREKA Environmental Engineering, Austin, TX, USA) has been included to measure depths profiles of temperature, salinity, pH, conductivity, turbidity, in situ chlorophyll fluorescence and DO. |
Generic Instrument Description | An instrument which measures multiple water quality parameters based on the sensor configuration. |
Dataset-specific Instrument Name | Standard Mercury Thermometer |
Generic Instrument Name | Water Temperature Sensor |
Dataset-specific Description | 1986 to 1996
Surface water temperature was measured weekly using a standard mercury thermometer (+- 0.1 ° C) |
Generic Instrument Description | General term for an instrument that measures the temperature of the water with which it is in contact (thermometer). |
Dataset-specific Instrument Name | Winkler Oxygen Titrator |
Generic Instrument Name | Winkler Oxygen Titrator |
Dataset-specific Description | The oxygen probe measurements are regularly (at least monthly) compared and calibrated (if necessary) against the high-precision Winkler titrations using a (Parsons et al., 1984; Hansen, 1999) and a Brinkmann Metrohm titrator |
Generic Instrument Description | A Winkler Oxygen Titration system is used for determining concentration of dissolved oxygen in seawater. |
Dataset-specific Instrument Name | YSI Model 556 multi-probe system |
Generic Instrument Name | YSI Professional Plus Multi-Parameter Probe |
Dataset-specific Description | From February 2004 until July 2011, water temperature, salinity, and dissolved oxygen (DO) were measured using a YSI Model 556 multi-probe system
YSI Model 556 multi-probe system |
Generic Instrument Description | The YSI Professional Plus handheld multiparameter meter provides for the measurement of a variety of combinations for dissolved oxygen, conductivity, specific conductance, salinity, resistivity, total dissolved solids (TDS), pH, ORP, pH/ORP combination, ammonium (ammonia), nitrate, chloride and temperature. More information from the manufacturer. |
Website | |
Platform | Skidaway Institute for Oceanography Main Dock |
Start Date | 1986-08-26 |
End Date | 2011-12-19 |
Description | /*-->*/
/*-->*/
Skidaway River Estuary, from the main dock of Skidaway Institute of Oceanography (SkIO), Georgia, USA
Skidaway River Estuary is a well mixed, warm, tidal influenced estuary located at the southeastern Atlantic coast of Georgia, USA, 31 59 N; 81 01 W. Water samples were taken at the surface in a depth of 0-1m.
Skidaway Institute for Oceanography - Sampling Locations: Main Dock, Fuel Dock, MECA Dock and the MECA Boat.
Most of the sampling is, and has been done, at the Main Dock: 31°59'23.96"N, 81°01' 21.09"W
Some sampling has been performed at the:
Fuel Dock: 31°59'25.19"N, 81°01' 17.40"W
MECA Dock: 31°59'21.48"N, 81°01' 26.62"
MECA Boat: 31°59'27.66"N, 81°01' 31.93"W to 31°59'30.68"N, 81°01'13.05"
Image of Sampling Locations |
In estuaries of the South Atlantic Bight, one of the longest and most extensive datasets of plankton and bacteria biomass and composition is from the Skidaway River and the associated Wassaw Sound estuarine system in Georgia. Wassaw Sound is a tidally dominated, bar-built estuary surrounded by extensive stands of salt marsh. Although pristine compared to industrially impacted waterways such as the Savannah River and Charleston Harbor, residential development and population density around the Wassaw Sound system have been increasing rapidly.
Since 1986 the Skidaway River Monitoring Program (SRiMP) has maintained a time series observation dataset of hydrography, nutrients, phytoplankton, heterotrophic microbial communities, mesozooplankton, representative gelatinous nekton, and dissolved oxygen. Samples have been collected approximately weekly from the main dock at the Skidaway Institute of Oceanography. The start of the program was coincident with the rapid development of Skidaway Island, Georiga USA that has transformed a marsh and maritime forest covered ancient barrier island to an island dominated by a residential luxury golf course community. Population growth in the 1980's was as high as 25% annually, but has since declined to <3% annually as island development has neared completion. Evidence from the SRiMP study support the hypothesis of causative linkages between human population growth, nutrient loading, and ecosystem alteration.
The long-term goal of this project is to understand how warm, well-mixed, subtropical estuaries vary their plankton community structure, function, and net ecosystem metabolism in response to increasing anthropogenic nutrient loading and natural environmental forcing. The approach is to continue a unique, long-term (19 years), temporally intensive (sampling twice per week) record in the Skidaway River estuary (Georgia, USA) of hydrography, nutrients, plankton and microbial communities, dissolved oxygen, and important living and non-living components of particulate matter. The record to date documents changes caused by cultural eutrophication throughout the food web from bacteria to copepods; independently collected evidence shows major declines in commercial catches of fin- and shellfish. Commonly accepted conceptual models and limited local evidence support the notion that gelatinous predators may benefit from the enhanced microbial food web and from decreased competition from vertebrates and invertebrates. These data will be used to evaluate estuarine biological and chemical responses to, and potential recovery from, the by-products of increasing human occupation of the coast, as well as chronic (long-term warming, rising sea level, extended drought or wet periods) and stochastic (tropical storms) patterns in natural phenomena. Questions to be addressed fall into two basic categories: (a) how do plankton communities (individual taxa and bulk properties) respond in structure and function to early stages of eutrophication that include changes in concentrations and ratios of all major inorganic and organic nutrients, and (b) are such changes consonant with accepted ecological theory for estuarine ecosystems?
The working hypothesis is that changes in nutrient loading have altered the competitive balance among phytoplankton, bacteria, and associated microbial communities, thus impacting higher trophic levels. A major corollary is that changes in food web structure at the lower levels are driving a long-term shift from oxic towards hypoxic conditions, i.e. from autotrophy to net heterotrophy. These lower oxygen concentrations may facilitate the development of gelatinous predators communities to fill the void caused by declines in fin- and shellfish. This study aims to provide sound scientific data on historic and contemporary patterns in plankton community structure, ecosystem function, and relationships to environmental variables, including trends in dissolved oxygen, as well as the quantitative basis to evaluate basic ecological hypotheses regarding estuarine ecosystems.
Skidaway Institute for Oceanography - Sampling Locations - Main Dock, Fuel Dock, MECA Dock and the MECA Boat.
Most of the sampling is, and has been done, at the Main Dock: 31°59'23.96"N, 81°01' 21.09"W
Some sampling has been performed at the:
Fuel Dock: 31°59'25.19"N, 81°01' 17.40"W
MECA Dock: 31°59'21.48"N, 81°01' 26.62"
MECA Boat: 31°59'27.66"N, 81°01' 31.93"W to 31°59'30.68"N, 81°01'13.05"
Funded as NSF-OCE Award #0545312: Patterns of Ecosystem Function and Trophic Status in Well-mixed Subtropical Estuaries Undergoing Anthropogenic Modification
Funding Source | Award |
---|---|
NSF Division of Ocean Sciences (NSF OCE) |