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October 2001 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites

Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in October, 2001. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.

November 2001 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites

Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in November, 2001. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.

March 2002 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites

Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in March, 2002. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.

September 2002 surface water bacterial productivity at ten Georgia Coastal Ecosystems LTER sampling sites

Surface water samples were collected during low tide survays near ten Georgia Coastal Ecosystem LTER sampling sites in September, 2002. The incorporation of tritiated leucine in unfiltered samples during one hour incubations was measured using a standard microcentrifuge method to estimate bacterial productivity in each sample. This study was part of the GCE-LTER hydrographic monitoring program, and will be repeated quarterly.

openCC (other)Dec 2025View details →

Chemistry of coastal stream and lagoon water from Puerto Rico - 2021-2024

Water samples were collected from coastal streams and lagoons in Puerto Rico from February 2021 to March 2024 as part of ongoing coastal ecosystem monitoring. These samples were analyzed at the University of New Hampshire Water Quality Analysis Laboratory for comprehensive water chemistry including field parameters, major ions, nutrients, dissolved gases, and trace metals. Sampling sites included Quebrada Fajardo (QFJO) at multiple depths and distances upstream, Quebrada Pitahaya (Qpaya), Laguna Pitahaya (LPYHA), Luquillo streams (LUQA, LUQB), and Laguna Cartagena (LCART). Field measurements included pH, conductivity, dissolved oxygen, temperature, turbidity, and atmospheric pressure. Laboratory analyses encompassed dissolved organic carbon (DOC), total dissolved nitrogen (TDN), nutrients (NH4-N, PO4-P, NO3-N), major ions (Cl, SO4, Na, K, Mg, Ca), dissolved gases (CH4, CO2, N2O), and trace metals by Inductively Coupled Plasma (ICP) analysis. The ICP analysis provided enhanced detection capabilities for cations and metals including calcium, iron, manganese, silicon, strontium, sulfur, sodium, magnesium and potassium. Samples were collected as grab samples from the water surface. All samples were filtered through pre-combusted Whatman GF/F for nutrients and organic matter and Whatman WCN Cellulose Nitrate Membranes for metals. Values below detection limits are recorded as 1/2 the detection limit. This dataset provides comprehensive water quality data for Puerto Rican coastal watersheds, with particular focus on stratified sampling in Quebrada Fajardo to understand vertical water column structure and biogeochemical processes in coastal environments influenced by both terrestrial and marine inputs. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecol

openCC (other)Sep 2024View details →

Dissolved inorganic nutrients from the Martha's Vineyard Coastal Observatory (MVCO), including 4 macro-nutrients from water column bottle samples, ongoing since 2003 (NES-LTER since 2017)

Dissolved inorganic nutrients including nitrate + nitrite, ammonium, silicate, and phosphate are measured from water column bottle and bucket samples taken on NES-LTER day cruises in the vicinity of the Martha's Vineyard Coastal Observatory (MVCO). Sampling frequency near MVCO is approximately monthly, ongoing since 2003. Samples were filtered, frozen, then processed at the Woods Hole Oceanographic Institution's Nutrient Analytical Facility. These macro-nutrients are analyzed in seawater using a colorimetric assay in which light absorbance is measured versus known standards, and final concentrations are calculated (in micromole per liter). Each sample may have up to 3 replicates.

zenodo44/100

Supplementary dataset to the publication "Bi, S., and Hieronymi, M. (2024). Holistic optical water type classification for ocean, coastal, and inland waters. Limnology & Oceanography"

<p>The NetCDF data files contain the training dataset used to develop the Optical Water Type (OWT) framework proposed by Bi and Hieronymi (2024). The dataset is available in two spectral versions:</p> <p>    1.    <code>owt_BH2024_training_data_hyper.nc</code>: This file includes training data with a spectral resolution of 2 nm, ranging from 400 to 900 nm.<br>    2.    <code>owt_BH2024_training_data_olci.nc</code>: This file contains data formatted similarly to the hyperspectral version but aligned with the nominal Sentinel-3 OLCI wavebands.</p> <h2>Contents of the Dataset</h2> <p>For each version, the dataset includes spectral inherent and apparent optical properties such as:</p> <p>    •    Remote Sensing Reflectance (Rrs)<br>    •    Pure Water Absorption (aw)<br>    •    Absorption Coefficient of Detritus (ad)<br>    •    Total Absorption Coefficient without Pure Water (agp)<br>    •    Absorption Coefficient of Phytoplankton (aph)<br>    •    Backscattering Coefficient of Total Particulate Matter (bbp)<br>    •    Scattering Coefficient of Total Particulate Matter (bp)<br>    •    Scattering Coefficient of Pure Water (bw)</p> <p>Additionally, the dataset includes various environmental and biological parameters:</p> <p>    •    Chlorophyll a Concentration (Chl)<br>    •    Inorganic Suspended Matter Concentration (ISM)<br>    •    Colored Dissolved Organic Matter Absorption at 440 nm (ag440)<br>    •    Single-Scattering Albedo of Detritus at 550 nm (A_d)<br>    •    Power Law Exponent of Detritus Attenuation (G_d)<br>    •    Water Salinity (Sal)<br>    •    Water Temperature (Temp)<br>    •    Fraction for Diminished Coccolithophore Absorption (a_frac)<br>    •    Fraction of Coccolithophore Group (cocco_frac)</p> <h2>Optical Water Types</h2> <p>The training dataset includes 10 pre-defined optical water types, with 10,000 samples for each type. Detailed descriptions of these water types can be found in Table 1 of Bi and Hieronymi (2024) or as follows,</p> <table> <tbody> <tr> <td>OWT</td> <td>Desciption</td> </tr> <tr> <td>1</td> <td>Extremely clear and oligotrophic indigo-blue waters with high reflectance in the short visible wavelengths.</td> </tr> <tr> <td>2</td> <td>Blue waters with similar biomass level as OWT 1 but with slightly higher detritus and CDOM content.</td> </tr> <tr> <td>3a</td> <td>Turquoise waters with slightly higher phytoplankton, detritus, and CDOM compared to the first two types.</td> </tr> <tr> <td>3b</td> <td>A special case of OWT 3a with similar detritus and CDOM distribution but with strong scattering and little absorbing particles like in the case of Coccolithophore blooms. This type usually appears brighter and exhibits a remarkable ~490 nm reflectance peak.</td> </tr> <tr> <td>4a</td> <td>Greenish water found in coastal and inland environments, with higher biomass compared to the previous water types. Reflectance in short wavelengths is usually depressed by the absorption of particles and CDOM.</td> </tr> <tr> <td>4b</td> <td>A special case of OWT 4a, sharing similar detritus and CDOM distribution, exhibiting phytoplankton blooms with higher scattering coefficients, e.g., Coccolithophore bloom. The color of this type shows a very bright green.</td> </tr> <tr> <td>5a</td> <td>Green eutrophic water, with significantly higher phytoplankton biomass, exhibiting a bimodal reflectance shape with typical peaks at ~560 and ~709 nm.</td> </tr> <tr> <td>5b</td> <td>Green hyper-eutrophic water, with even higher biomass than that of OWT 5a (over several orders of magnitude), displaying a reflectance plateau in the Near Infrared Region, NIR (vegetation-like spectrum).</td> </tr> <tr> <td>6</td> <td>Bright brown water with high detritus concentrations, which has a high reflectance determined by scattering.</td> </tr> <tr> <td>7</td> <td>Dark brown to black water with very high CDOM concentration, which has low reflectance in the entire visible range and is dominated by absorption.</td> </tr> </tbody> </table> <h2>Additional Information</h2> <p>The detailed description of the data simulation can be found in the supporting information of Bi and Hieronymi (2024). The models used for simulating the data are available on GitHub:</p> <p>    •    Component IOP Model: <a href="https://github.com/bishun945/IOPmodel" target="_blank" rel="noopener">Bio-geo-optical modelling of natural waters by Bi, Hieronymi, and Röttgers (2023)</a><br>    •    OWT Package: <a href="https://github.com/bishun945/pyOWT" target="_blank" rel="noopener">pyOWT</a></p> <h2>References</h2> <p>    1.    OWT Framework: Bi, S., and Hieronymi, M. (2024). Holistic optical water type classification for ocean, coastal, and inland waters. Limnology & Oceanography, lno.12606. doi: 10.1002/lno.12606<br>    2.    Component IOP Model: Bi, S., Hieronymi, M., and Röttgers, R. (2023). Bio-geo-optical modelling of natural waters. Front. Mar. Sci. 10, 1196352. doi: 10.3389/fmars.2023.1196352<br>    3.    Pure Water IOP Model: Röttgers, R., Doerffer, R., McKee, D., and Schönfeld, W. (2016). The Water Optical Properties Processor (WOPP): Pure Water Spectral Absorption, Scattering and Real Part of Refractive Index Model. Technical Report No WOPP-ATBD/WRD6. Available at: https://calvalportal.ceos.org/tools<br>    4.    Rrs Model: Lee, Z., Du, K., Voss, K. J., Zibordi, G., Lubac, B., Arnone, R., et al. (2011). An inherent-optical-property-centered approach to correct the angular effects in water-leaving radiance. Appl. Opt. 50, 3155. doi: 10.1364/AO.50.003155</p> <h2>Authors and Contact</h2> <p>    •    Author: Shun Bi, Martin Hieronymi, Rüdiger Röttgers<br>    •    Creator: Shun Bi, Shun.Bi@hereon.de</p> <h2>Example Python Code to Read Data</h2> <p>Here is an example of how to read the NetCDF data using Python and the <code>xarray</code> library:</p> <pre><code>import xarray as xr # Load the dataset data_hyper = xr.open_dataset("path_to_your_file/owt_BH2024_training_data_hyper.nc") # Print the dataset to see its structure print(data_hyper) # Access a specific variable, e.g., remote sensing reflectance (Rrs) rrs = data_hyper['Rrs'] # Plot a sample of Rrs import matplotlib.pyplot as plt # Select a sample ID, for example the first sample sample_id = 0 plt.plot(data_hyper['wavelen'], rrs[sample_id, :]) plt.xlabel('Wavelength (nm)') plt.ylabel('Rrs (1/sr)') plt.title(f'Remote Sensing Reflectance for Sample ID {sample_id}') plt.show()</code></pre>

opencc-by-4.0Jul 2024View details →

zenodo44/100

Input data for: Reconstruction of hourly coastal water levels and counterfactuals without sea level rise for impact attribution

<p>This Zenodo archive contains essential input datasets utilized in our <a href="https://doi.org/10.5194/essd-2023-112">research study</a> titled "Reconstruction of hourly coastal water levels and counterfactuals without sea level rise for impact attribution". </p><p>This archive contains only input data. The Hourly Coastal water levels with Counterfactual (HCC) dataset is published in the <a href="https://doi.org/10.48364/ISIMIP.749905">ISIMIP repository</a>.</p><p><strong>Datasets Included</strong>:</p><p><strong>CoDEC (Coastal Dataset for the Evaluation of Climate Impact)</strong>:</p><ul><li>This dataset is described in<a href="https://doi.org/10.3389/fmars.2020.00263"> Muis et al. (2020)</a></li><li><strong>cf_esl folder</strong>: Contains data representing total CoDEC water levels. Individual NetCDF files store data for each grid point.</li><li><strong>cf_tides folder</strong>: This folder holds data related to tidal elevation.</li><li><strong>coor_coastal.nc</strong>: A NetCDF file featuring the spatial grid utilized in CoDEC. This dataset comprises only coastal grid points.</li></ul><ol><li><strong>HR (Hybrid Reconstructions)</strong>:<ul><li><strong>HybridRec_Upd0422.mat</strong>: This file contains data from the Hybrid Reconstructions dataset (<a href="https://doi.org/10.1038/s41558-019-0531-8">Dangendorf et al 2019</a>), aligned to the CoDEC grid, and includes satellite altimetry integral to producing the Hybrid Reconstructions dataset. Each row corresponds to one grid point on the CoDEC grid. For ease of use in our applications, we offer a preprocessing script in our <a href="https://doi.org/10.5281/zenodo.7771501">source code</a> named split_hr_dataset_to_stations.py.</li></ul></li></ol><p>We here provide the specific versions of HR and CoDEC that are used in our study to ensure accurate replication.</p>

opencc-by-4.0Sep 2023View details →

edi44/100

Lagrangian Water Age trajectories initiated from the coastal 500m isobath and derived from surface velocities obtained from satellite observations

We conduct a Lagrangian particle trajectory analysis of surface velocities. We define an “offshore water age” as the time taken by a water parcel to be advected backward in time from its current position along its trajectory until it crosses the 500 m isobath. The rationale of this diagnostic is to detect filaments of coastal water advected offshore by horizontal transport and to estimate the time for water parcels in the filament o leave the coastal area. For example, a value of “20 days” assigned to a pixel means that the water parcel in that area was in the coastal area approximately 20 days before, where it was likely enriched in nutrients.

openCC (other)Aug 2021View details →

edi44/100

November 2001 to March 2003 water column chlorophyll and phaeopigment concentrations for Georgia Coastal Ecosystems LTER sampling sites

Water samples were collected from the surface and the bottom of the water column at ten GCE-LTER sampling sites and from the surface of the water column during a low water transect along the Altamaha River in November 2001, March 2002, June 2002, September 2002, December 2002, and March 2003 . Samples were taken at various times of day and under various tidal conditions. The particulate matter was separated by filtration and analyzed for chlorophyll and phaeopigment content by flourometric analysis. This study was part of the GCE-LTER hydrographic monitoring program, and is repeated quarterly.

openCustomFeb 2008View details →

edi44/100

Water Quality of Virginia Coastal Bays- Nutrients, 1992-2008

This dataset has been superceded by: VCR15243 Water Quality Sampling - integrated measurements for the Virginia Coast, 1992- Please see that dataset for updated data. This dataset contains information on nutrient concentrations a the Virginia Coast Reserve Long-Term Ecological Research Project.

Fig. 7. Serpulids from United States fouling plates. Pomatostegus stellatus. A in The fouling serpulids (Polychaeta: Serpulidae) from United States coastal waters: an overview

Fig. 7. Serpulids from United States fouling plates. Pomatostegus stellatus. A. Operculum, from Biscayne Bay, Florida (SERC-118825). – Protula balboensis. B–D. Tube, body and branchial crown, white arrow shows detail of rounded processes, Biscayne Bay, Florida (SERC-118825). E. Body of live adult from Smithsonian Institution station in Bocas del Toro, Panama (photo by Betel Martínez- Guerrero). – Pseudochitinopoma occidentalis. F. Operculum, Puget Sound, Washington (SERC- 33385R). – Pseudovermilia occidentalis. G. Operculum, Biscayne Bay, Florida (SERC-118450). – Salmacina huxleyi. H–I. Tubes, body and collar chaetae, Biscayne Bay, Florida (SERC-118449). – S. tribranchiata. J. Body, Galapagos Island (SERC-233687).

Fig. 4. Serpulids from United States fouling plates. Hydroides bispinosa. A in The fouling serpulids (Polychaeta: Serpulidae) from United States coastal waters: an overview

Fig. 4. Serpulids from United States fouling plates. Hydroides bispinosa. A. Operculum, from Biscayne Bay, Florida (SERC-118756). – H. cf. brachyacantha. B. Operculum, Pensacola Bay, Florida (SERC- 92415). – H. dianthus. C. Operculum, Corpus Christi, Texas (SERC-87878RB). – H. dirampha. D. Operculum, Biscayne Bay, Florida (SERC-118709). – H. elegans. E. Operculum, San Diego, California (SERC-04075R). – H. floridana. F. Operculum, Corpus Christi, Texas (SERC-87968). – H. gracilis. G. Operculum, San Diego, California (SERC-34585R). – H. longispinosa. H. Operculum, Oahu, Hawaii (SERC-19654). – H. parva. I. Operculum, Biscayne Bay, Florida (SERC-118709). – H. sanctaecrucis. J. Operculum, Tampa Bay, Florida (SERC-66920R).

Fig. 10 in The fouling serpulids (Polychaeta: Serpulidae) from United States coastal waters: an overview

Fig. 10. Distribution of serpulids (Salmacina, Serpula and Spirobranchus spp.) from United States fouling plates (closed symbols) and literature records (open symbols).

Fig. 3 in The fouling serpulids (Polychaeta: Serpulidae) from United States coastal waters: an overview

Fig. 3. Distribution of serpulids (Crucigera and Ficopomatus spp.) from United States fouling plates (closed symbols) and literature records (open symbols).

Fig. 2. Serpulids from United States fouling plates. Crucigera websteri. A in The fouling serpulids (Polychaeta: Serpulidae) from United States coastal waters: an overview

Fig. 2. Serpulids from United States fouling plates. Crucigera websteri. A. Operculum, juvenile from Humboldt Bay, California. B. Operculum, adult from San Pedro, California (LACMNH-N8819). – C. zygophora. C. Operculum, juvenile from Alaska (SERC). D. Operculum, adult from Canoe Bay, Alaska (LACMNH-N2128). – Ficopomatus enigmaticus. E. Tubes from Lake Merritt, California (LACMNH-N5141). F. Body, from Chesapeake Bay, Virginia (SERC-59327). G. Operculum, from Chesapeake Bay, Virginia (SERC-60530R). H. Colonies in Long Beach, California (photo by Bruno Pernet). – F. miamiensis. I. Tubes, from Chetumal Bay, Mexican Caribbean (ECOSUR). J–K. Operculum, from Galveston Bay, Texas (SERC-88344RF). – F. uschakovi. L. Tube, from Corpus Christi, Texas (SERC-88883). M. Thorax and operculum, from Galveston Bay, Texas (SERC-86995). N. Operculum, from La Encrucijada, Chiapas (UMAR-Poly 113). O. Thorax and operculum, from Corpus Christi, Texas (SERC-88883).

Fig. 1 in The fouling serpulids (Polychaeta: Serpulidae) from United States coastal waters: an overview

Fig. 1. Study area. Site abbreviations following decreasing latitude from east to west coasts: RI = Narragansett Bay, Rhode Island; CB = Chesapeake Bay, Virginia; CH = Charleston, South Carolina; Florida: JX = Jacksonville, IR = Indian River, BB = Biscayne Bay, TB = Tampa Bay and PB = Pensacola Bay; GB = Galveston Bay and CC = Corpus Christi, Texas; Alaska: DH = Dutch Harbor, KD = Kodiak, AK = Kechamak Bay, AV = Valdez, PW = Prince William Sound, ST = Sitka and KT = Ketchikan; WA = Puget Sound, Washington; OR = Coos Bay, Oregon; California: HB = Humboldt Bay, SF = San Francisco, MO = Morro Bay, LB = Long Beach, MI = Mission Bay and SD = San Diego; HI = Oahu, Hawaii.

Fig. 6 in The fouling serpulids (Polychaeta: Serpulidae) from United States coastal waters: an overview

Fig. 6. Distribution of serpulids (Hydroides spp.) from United States fouling plates (closed symbols) and literature records (open symbols).

Fig. 5 in The fouling serpulids (Polychaeta: Serpulidae) from United States coastal waters: an overview

Fig. 5. Distribution of serpulids (Hydroides spp.) from United States fouling plates (closed symbols) and literature records (open symbols).

Fig. 8 in The fouling serpulids (Polychaeta: Serpulidae) from United States coastal waters: an overview

Fig. 8. Distribution of serpulids (Pomatostegus, Protula, Pseudochitinopoma and Pseudovermilia spp.) from United States fouling plates (closed symbols) and literature records (open symbols).