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Fig. 1. A in Scientific Note Schooling behavior of Mugil curema (Perciformes: Mugilidae) in an estuary in southeastern Brazil
Fig. 1. A stationary school of Mugil curema, composed of small individuals in a shallow shoreline area (observed from the surface). In this situation, the fish are not polarized, and their arrangement resembles a chaotic image.
Fig. 3 in Growth of the Silverside Atherinella brasiliensis in Tramandaí Estuary, Southern Brazil (Actinopterygii: Atherinopsidae)
Fig. 3. Length frequency distributions of females of the silverside Atherinella brasiliensis in Tramandaí Estuary, Southern Brazil. Black bars represent small animals with no gender identification and equally distributed as males or females.
Fig. 1 in Growth of the Silverside Atherinella brasiliensis in Tramandaí Estuary, Southern Brazil (Actinopterygii: Atherinopsidae)
Fig. 1. Length/weight relationship of the silverside Atherinella brasiliensis in Tramandaí Estuary, Southern Brazil.
Fig. 1 in Diet composition and feeding strategy of the southern pipefish Syngnathus folletti in a Widgeon grass bed of the Patos Lagoon Estuary, RS, Brazil
Fig. 1. Relationship between mouth gape (a) and prey size (b) with total length (in mm) of female (open circles) and male (dots) individuals of the southern pipefish Syngnathus folletti.
Fig. 3 in Diet composition and feeding strategy of the southern pipefish Syngnathus folletti in a Widgeon grass bed of the Patos Lagoon Estuary, RS, Brazil
Fig. 3. Conceptual diagram showing the microhabitat distribution within the Widgeon grass bed of some benthic macroinvertebrates consumed by Syngnathus folletti. Gastropoda: 1. Heleobia australis; Tanaidacea: 2. Kalliapseudes schubartii, 3. Tanais stanfordi; Isopoda: 4. Dies fluminensis, 5. Uromunna peterseni; Amphipoda: 6. Mellita mangrovi.
Microbial 16S rRNA gene (DNA) and transcripts (cDNA) along a boreal soil-freshwater-estuary continuum
<p>This repository stores the processed files of the 16S rRNA sequencing reads (DNA and cDNA) of the La Romaine project, which were processed through the DADA2 pipeline. Files are '.rds' files and/or '.csv' files readable by the open statistical software R. The project is part of the Industrial Research Chair in Carbon Biogeochemistry in Boreal Aquatic systems (CarBBAS Chair) led by Paul A. del Giorgio.</p> <p>Samples were pooled by plate ID and season to be processed by DADA2. The number before each '*_seqtab.rds' file corresponds to a pool. ID details are in "splitdf_new.rds".</p> <p>Raw sequences can be found on SRA under the Bioproject number: PRJNA693020. Intermediate processing files are stored here. And scripts are available on <a href="https://github.com/CarBBAS/Paper_Stadler-delGiorgio_ISMEJ_2021">Github</a>.</p> <p>Files are being uploaded as manuscripts are published.</p> <p>Currently available files:</p> <ul> <li>2015-2017: 16S rRNA gene and transcripts (DNA and cDNA) in spring, summer, autumn (shallow sequencing) <ul> <li>Part of the manuscript: "Terrestrial connectivity, upstream aquatic history and seasonality shape bacterial community assembly within a large boreal aquatic network". The ISME Journal. 2021.</li> </ul> </li> </ul>
Observations of Autumnal Cooling in a Large Estuary: The Glider Data from Long Island Sound in 2014
<p>This data file is a component of the data used in a paper to appear in the Journal of Geophysical Research in 2023 entitled "Observations of Autumnal Cooling in a Large Estuary" by Amin Ilia, Grant McCardell, Kay Howard-Strobel, and James O'Donnell. The data file contains the measurements from a Slocum Glider (V1) from Webb Research used in the paper. The data is in a MATLAB binary (.mat) file as a structure variable with a field MetaData containing some notes, and data in <br> SampleTimeEST- the date and time of the sample (EST) in MATLAB's datenum() format<br> Pressure_dBar - the pressure (or equivalently depth in m) that the sample was acquired <br> Temperature_C - the water temperature in Celcius<br> PracticalSalinty - the practical salinty<br> LatitudeDeg- the latitude of the sampling location (deg)<br> LongitudeDeg - the longitude of the sampling location (deg east)</p> <p>The paper's abstract is: </p> <p>Long Island Sound (LIS) is a large estuary on the eastern United States coast. Seasonal variations <br> in solar insolation and wind create an annual water temperature cycle that impacts circulation <br> and biological processes. The waters warm from March-February until August-October and then <br> begins to cool. Ship surveys show that the vertical temperature structure becomes uniform during <br> this season when the area experiences low air temperatures and high winds. However, there have <br> been no observations that resolve the temporal evolution of the vertical structure of temperature <br> during these cooling periods because conditions inhibit ship operations. We report glider <br> measurements of the vertical structure of water temperatures and salinities from October 22 to <br> November 4, 2014, in eastern LIS. We find that 20m of water can cool at approximately 0.5 <br> C/day intervals of cold air and strong winds. We use the data to estimate heat content tendencies <br> and infer surface fluxes. We also estimate the surface heat fluxes using buoy-mounted <br> instruments and the COARE 3.0/3.5 formulae and show they are consistent. Using the buoy <br> fluxes and the products of an operation regional model, we show the agreement with the heat <br> budget fluxes is best when the closest buoy and the model results are used. This suggests that <br> resolving the temporally and spatially structure of the wind field is crucial to the accurate <br> simulation of the temperature variability in LIS. These intervals of very rapid cooling can lead to <br> significant density gradients between LIS and the shallow bays and marshes that surround it.</p>
Fig. 2 in Temporal variations in the diversity of true crabs (Crustacea: Brachyura) in the St Lucia Estuary, South Africa
Fig. 2. Distribution of Hymenosoma projectum (red), Paratylodiplax blephariskios (grey) and Neosarmatium africanum (blue) in 1948 and 2012.
Fig. 1 in Observations on the bloom-forming jellyfish Crambionella stuhlmanni (Chun, 1896) in the St Lucia Estuary, South Africa
Fig. 1. Large specimen (≈ 16 cm bell diameter) of Crambionella stuhlmanni in the shallows of Charter's Creek. (Photo Nicola K. Carrasco, 29 May 2008)
Fig. 4 in Observations on the bloom-forming jellyfish Crambionella stuhlmanni (Chun, 1896) in the St Lucia Estuary, South Africa
Fig. 4. Swarming Crambionella stuhlmanni washed up on the shore of Catalina Bay. (Photo Ricky H. Taylor, Dec. 2005)
Fig. 3 in Observations on the bloom-forming jellyfish Crambionella stuhlmanni (Chun, 1896) in the St Lucia Estuary, South Africa
Fig. 3. Salinity and relative abundance of Crambionella stuhlmanni recorded in the St Lucia Estuary from 1991 to 2000. Abundance: 0 – absent, 1 – present, 2 – abundant.
Using Monitoring and Mechanistic Modeling to Improve Understanding of Eutrophication in a Shallow New England Estuary
<p>This data repository contains the names and description of data files used in the “Using Monitoring and Mechanistic Modeling to Improve Understanding of Eutrophication in a Shallow New England Estuary” manuscript by Cashel et al (2023). These data files, formatted as .txt files, include simulated and observed data of various water quality components with time. Time is always provided as the Julian Day in the first column (left). The type of data in each file is indicated by a parameter code. Parameter codes are defined below.</p> <ul> <li>SAL = salinity (ppt)</li> <li>WT = water temperature (℃)</li> <li>PAR = photosynthetically active radiation (W/m<sup>2</sup>)</li> <li>TN = total nitrogen (mg/L as N)</li> <li>NH3 = ammonium (mg/L as N)</li> <li>NO3 = nitrate + nitrite (mg/L as N)</li> <li>TP = total phosphorus (mg/L as P)</li> <li>DIP = orthophosphate (mg/L as P)</li> <li>CBOD = carbonaceous biological oxygen demand (mg/L)</li> <li>CHL = phytoplankton as chlorophyll <em>a </em>(µg/L)</li> <li>MACRO = macroalgae biomass (gDW/m<sup>2</sup>)</li> <li>DO = dissolved oxygen (mg/L)</li> </ul> <p><strong><em>1 - Simulated Data</em></strong></p> <p>1.1 – PRE Model Data</p> <p> The primary simulated data for this study includes model output on an interval of 0.05 days. Columns two through eight contain the average concentration of each WASP Segment per each time step. Data presented in these columns from left to right are from WASP Segments 8, 9, 10, 12, 14, 16, and 17.</p> <ul> <li>WASP_SAL.txt </li> <li>WASP_WT.txt </li> <li>WASP_PAR.txt</li> <li>WASP_TN.txt</li> <li>WASP_NH3.txt</li> <li>WASP_NO3.txt</li> <li>WASP_TP.txt</li> <li>WASP_DIP.txt</li> <li>WASP_CBOD.txt</li> <li>WASP_CHL.txt</li> <li>WASP_MACRO.txt</li> <li>WASP_DO.txt</li> </ul> <p>1.2 – Macroalgae Scenario Data</p> <p> Simulated data files also include a model scenario evaluating the impact of macroalgae as a state variable. This set of model output comes from simulations with macroalgae removed as a state variable. These files have a model output of 0.05 days with time in the first column, and the second column contains the average concentration within WASP segment 17.</p> <ul> <li>MACRO_PAR.txt</li> <li>MACRO_NH3.txt</li> <li>MACRO_NO3.txt</li> <li>MACRO_DIP.txt</li> <li>MACRO_CBOD.txt</li> <li>MACRO_CHL.txt</li> </ul> <p>1.3 – Dissolved Oxygen Parameter Analysis Data</p> <p> Simulated data from model scenarios evaluating the impact of parameterization on dissolved oxygen concentrations are listed below. These model simulations have an output of 0.05 days. Rows two through ten contain average DO concentration (mg/L) for WASP Segments 9, 10, 11, 12, 13, 14, 15, 16, and 17. Files containing “1” indicate the high condition of each parameter analysis, and those with a “2” indicate the low condition.</p> <ul> <li>CBOD1_DO.txt</li> <li>CBOD2_DO.txt</li> <li>Phyto1_DO.txt</li> <li>Phyto2_DO.txt</li> <li>SOD1_DO.txt</li> <li>SOD2_DO.txt</li> </ul> <p>1.4 – Heatmap Simulations</p> <p> Simulated data for heatmaps presents average concentrations from noon of each day. The first row is time, and the following rows of two through nine have simulated data for WASP Segments 10, 11, 12, 13, 14, 15, 16, and 17.</p> <ul> <li>WASP_TN2.txt</li> <li>WASP_TP2.txt</li> <li>WASP_DO2.txt</li> <li>WASP_CHL2.txt</li> </ul> <p><strong><em>2 – Observed Data </em></strong></p> <p>2.1 – Sonde Data</p> <p> Observed sonde data is presented in .txt files from various years and location. Each data file has the first column of time, and the second column as concentration per each time step. File names begin with the site name, followed by an “S” or “B” (surface and bottom respectively, if applicable), the year, and the parameter code. Site names are: LNB (Little Narragansett Bay), Pawcatuck (Pawcatuck Point), Avondale (Avondale Marina), Greenhaven (Greenhaven Marina), WYC (Westerly Yacht Club), PR (Pawcatuck Rock), Viking (Viking Marina), and R1 (Route 1). File names per location are provided in the two tables below. Row 1 of each table has the site name, and the corresponding files are listed below.</p> <table align="center"> <tbody> <tr> <td> <p><strong>LNB</strong></p> </td> <td> <p><strong>Pawcatuck</strong></p> </td> <td> <p><strong>Avondale </strong></p> </td> <td> <p><strong>Greenhaven </strong></p> </td> </tr> <tr> <td> <p>LNB_SAL.txt</p> </td> <td> <p>Pawcatuck2018_ SAL.txt</p> </td> <td> <p>AvondaleS2019_SAL.txt</p> </td> <td> <p>GreenhavenS2018_SAL.txt</p> </td> </tr> <tr> <td> <p>LNB_WT.txt</p> </td> <td> <p>Pawcatuck2018_WT.txt</p> </td> <td> <p>AvondaleB2019_SAL.txt</p> </td> <td> <p>GreenhavenB2018_SAL.txt</p> </td> </tr> <tr> <td> <p>LNB_DO.txt</p> </td> <td> <p>Pawcatuck2018_DO.txt</p> </td> <td> <p>AvondaleS2019_WT.txt</p> </td> <td> <p>GreenhavenS2018_WT.txt</p> </td> </tr> <tr> <td> <p>LNB_CHL.txt</p> </td> <td> <p>Pawcatcuk2018_CHL.txt</p> </td> <td> <p>AvondaleB2019_WT.txt</p> </td> <td> <p>GreenhavenB2018_WT.txt</p> </td> </tr> <tr> <td> </td> <td> <p>Pawcatuck2019_SAL.txt</p> </td> <td> <p>AvondaleS2019_CHL.txt</p> </td> <td> <p>GreenhavenS2018_DO.txt</p> </td> </tr> <tr> <td> </td> <td> <p>Pawcatuck2019_WT.txt</p> </td> <td> <p>AvondaleB2019_CHL.txt</p> </td> <td> <p>GreenhavenB2018_DO.txt</p> </td> </tr> <tr> <td> </td> <td> <p>Pawcatuck2019_DO.txt</p> </td> <td> <p>AvondaleS2019_DO.txt</p> </td> <td> </td> </tr> <tr> <td> </td> <td> <p>Pawcatuck2019_CHL.txt</p> </td> <td> <p>AvondaleB2019_DO.txt</p> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> <p>AvondaleS2020_SAL.txt</p> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> <p>AvondaleB2020_SAL.txt</p> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> <p>AvondaleS2020_WT.txt</p> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> <p>AvondaleB2020_WT.txt</p> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> <p>AvondaleS2020_CHL.txt</p> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> <p>AvondaleB2020_CHL.txt</p> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> <p>AvondaleS2020_DO.txt</p> </td> <td> </td> </tr> <tr> <td> </td> <td> </td> <td> <p>AvondaleB2020_DO.txt</p> </td> <td> <p> </p> <p> </p> </td> </tr> </tbody> </table> <p> </p> <table align="center"> <tbody> <tr> <td> <p><strong>WYC</strong></p> </td> <td> <p><strong>PR</strong></p> </td> <td> <p><strong>Viking</strong></p> </td> <td> <p><strong>R1</strong></p> </td> </tr> <tr> <td> <p>WYC2018_SAL.txt</p> </td> <td> <p>PRS2018_SAL.txt</p> </td> <td> <p>Viking2018_SAL.txt</p> </td> <td> <p>R1S2018_SAL.txt</p> </td> </tr> <tr> <td> <p>WYC2018_WT.txt</p> </td> <td> <p>PRB2018_SAL.txt</p> </td> <td> <p>Viking2018_WT.txt</p> </td> <td> <p>R1B2018_SAL.txt</p> </td> </tr> <tr> <td> <p>WYC2018_CHL.txt</p> </td> <td> <p>PRS2018_WT.txt</p> </td> <td> <p>Viking2018_CHL.txt</p> </td> <td> <p>R1S2018_WT.txt</p> </td> </tr> <tr> <td> <p>WYC2018_DO.txt</p> </td> <td> <p>PRB2018_WT.txt</p> </td> <td> <p>Viking2018_DO.txt</p> </td> <td> <p>R1B2018_WT.txt</p> </td> </tr> <tr> <td> </td> <td> <p>PRS2018_DO.txt</p> </td> <td> <p>Viking2019_SAL.txt</p> </td> <td> <p>R1S2018_DO.txt</p> </td> </tr> <tr> <td> </td> <td> <p>PRB2018_DO.txt</p> </td> <td> <p>Viking2019_WT.txt</p> </td> <td> <p>R1B2018_DO.txt</p> </td> </tr> <tr> <td> </td> <td> <p>PRS2020_SAL.txt</p> </td> <td> <p>Viking2019_CHL.txt</p> </td> <td> <p>R1S2020_SAL.txt</p> </td> </tr> <tr> <td> </td> <td> <p>PRB2020_SALtxt</p> </td> <td> <p>Viking2019_DO.txt</p> </td> <td> <p>R1B2020_SAL.txt</p> </td> </tr> <tr> <td> </td> <td> <p>PRS2020_WT.txt</p> </td> <td> <p>Viking2020_SAL.txt</p> </td> <td> <p>R1S2020_WT.txt</p> </td> </tr> <tr> <td> </td> <td> <p>PRB2020_WT.txt</p> </td> <td> <p>Viking2020_WT.txt</p> </td> <td> <p>R1B2020_WT.txt</p> </td> </tr> <tr> <td> </td> <td> <p>PRS2020_DO.txt</p> </td> <td> <p>Viking2020_CHL.txt</p> </td> <td> <p>R1S2020_DO.txt</p> </td> </tr> <tr> <td> </td> <td> <p>PRB2020_DO.txt</p> </td> <td> <p>Viking2020_DO.txt</p> </td> <td> <p>R1B2020_DO.txt</p> </td> </tr> </tbody> </table>
Longitudinal transport of suspended sediment in the Modaomen Estuary of the Pearl River: effects of river, tide, and mouth bar: Datasets
<p><strong>This dataset supplements the article: Longitudinal transport of suspended sediment in the Modaomen </strong><strong>E</strong><strong>stuary of the Pearl River: effects of river, tide, and mouth bar, submitted to Marine Geology</strong></p> <p>Contact information: Dr. Liu, F., School of Ocean Engineering and Technology, Sun Yat-sen University, Guangzhou, 510275, China.</p> <p>Email: <a href="mailto:liuf53@mail.sysu.edu.cn">liuf53@mail.sysu.edu.cn</a> (Liu, Feng)</p> <p><strong><em>Brief view of the dataset</em></strong></p> <p>Hydrodynamics, suspended sediment concentration and salinity distribution were measured at three fixed stations along the longitudinal direction of the estuary. The stations were located at Guadingjiao (M1), inside the bar (M2), and outside the bar (M3), and sampling was simultaneously conducted at neap tide (NT) from July 31 to August 1 and spring tide (ST) from August 8 to August 9 in 2017. All observation data has been compiled to include data from the surface to the bottom six layers within 26 hours. This directory contains the following datasets.</p> <p><strong>M10731.xlsx: </strong>Current velocity, current direction, salinity and SSC during neap tide at Station M1 </p> <p><strong>M10808.xlsx: </strong>Current velocity, current direction, salinity and SSC during spring tide at Station M1 </p> <p><strong>M20731.xlsx: </strong>Current velocity, current direction, salinity and SSC during neap tide at Station M2</p> <p><strong>M20808.xlsx: </strong>Current velocity, current direction, salinity and SSC during spring tide at Station M2</p> <p><strong>M30731.xlsx: </strong>Current velocity, current direction, salinity and SSC during neap tide at Station M3</p> <p><strong>M30808.xlsx: </strong>Current velocity, current direction, salinity and SSC during spring tide at Station M3</p>
phoebe_gross_estuary_temp_mosaics_v1
<p>Temperature and bioenergetics data used in the paper "Complex temperature mosaics across space and time in estuaries: implications for current and future nursery function."</p>
Current velocity data from a quasi-continuous survey using ADCP in Satilla River Estuary, Georgia.
<p><strong>Title: </strong>Current velocity data from a quasi-continuous survey using ADCP in Satilla River Estuary, Georgia.</p> <p><strong>Author/Data Collector: </strong>Chunyan Li</p> <p><strong>Point of Contact, PI, Originator: </strong>Chunyan Li (cli@lsu.edu)</p> <p><strong>Description:</strong></p> <p>These are velocity profile data from vessel-towed ADCP obtained in the Satilla River Estuary during a survey conducted on 17–18 November 2004. The instrument was an RDI 600 KHz Workhorse ADCP. The survey was done mostly during daylight time along a 90-degree bend in the middle of the Satilla River Estuary. The observations covered nearly two semidiurnal tidal cycles with 15 repetitions and 33 hours in measurement time. The route is about 11 km in length and covers both the West and East sides of the bend of the channel. Note that tide in this area is essentially semidiurnal which makes 12-h observations sufficient to resolve the main tidal constituents.</p> <p>The ADCP was mounted on one side of the boat approximately 0.4 m below the surface. The vertical bins were 0.5 m. The surveys were conducted at an average cruise speed of about 2.5–3 m/s except at the turns when the vessel had to slow down and during CTD casts when the vessel had to stop for a few minutes. A Seabird Electronic SBE 19 plus CTD was used to measure the vertical profiles of water temperature, salinity, fluorescence, light attenuation, and dissolved oxygen at two to three locations during each survey. Note that only ADCP data are included in this dataset.</p> <p>The data are averaged at about 8-second intervals, excluding bad data. The data presented here are in ASCII with the generic format provided by the RDI’s software WinRiver II output. There are a total of seven data files. There are:</p> <p> </p> <p>ADCP_Nov17_2004_Satilla_River_000t.000</p> <p>ADCP_Nov17_2004a_Satilla_River_000t.000</p> <p>ADCP_Nov17_2004a_Satilla_River_001t.000</p> <p>ADCP_Nov17_2004a_Satilla_River_002t.000</p> <p>ADCP_Nov18_2004a_Satilla_River_000t.000</p> <p>ADCP_Nov18_2004a_Satilla_River_001t.000</p> <p>ADCP_Nov18_2004a_Satilla_River_002t.000</p> <p>Here is an example of the data –</p> <p> 50 25 42 124 10 20 1</p> <p>4 11 17 15 3 34 86 19 10 3.220 -0.410 331.714 17.460</p> <p>-50.84 11.65 -0.88 0.42 0.00 4.00 0.00 -21.08 7.38 7.38 7.52 7.31</p> <p>3.57 6.85 0.78 -3.48 3.57</p> <p>30.9708933 -81.5066250 -47.77 0.00 3.6</p> <p>-4.8 -1.0 -0.5 -12.5 10.0 -12.5 10.0 1.28 6.28</p> <p>30 cm BT dB 0.44 0.082</p> <p> 1.28 50.99 309.66 -39.3 32.5 -3.2 -3.9 99.7 101.2 102.8 101.7 100 -0.03</p> <p> 1.78 53.58 304.67 -44.1 30.5 -0.2 4.0 102.6 103.8 105.5 104.4 100 -0.04</p> <p> 2.28 43.23 318.41 -28.7 32.3 -1.7 -5.8 102.3 103.7 105.2 104.6 100 -0.02</p> <p> 2.78 53.59 320.14 -34.3 41.1 -2.3 8.6 101.3 103.0 105.1 104.3 90 -0.08</p> <p> 3.28 46.16 304.23 -38.2 26.0 -0.6 2.2 100.1 103.6 104.0 102.8 100 -0.06</p> <p> 3.78 55.55 309.19 -43.1 35.1 -1.2 -2.4 100.1 101.3 102.7 102.0 100 -0.09</p> <p> 4.28 47.84 308.45 -37.5 29.7 1.8 2.5 99.6 100.8 101.7 100.9 100 -0.02</p> <p> 4.78 47.27 311.81 -35.2 31.5 -2.4 5.7 98.5 101.7 102.0 100.8 100 -0.02</p> <p> 5.28 40.47 308.48 -31.7 25.2 0.5 0.1 98.1 101.0 101.4 100.8 100 -0.05</p> <p> 5.78 43.89 314.42 -31.3 30.7 -1.8 5.7 97.8 100.9 101.2 101.0 100 -0.11</p> <p> 6.28 44.51 317.27 -30.2 32.7 0.8 2.2 97.3 101.4 100.9 100.6 100 -0.00</p> <p> 6.78 38.19 315.72 -26.7 27.3 -3.2 35.8 107.0 104.9 101.9 112.0 50 2147483647</p> <p> 7.28 -32768 -32768 -32768 -32768 -32768 -32768 255 255 121.6 255 0 2147483647</p> <p> 7.78 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 8.28 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 8.78 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 9.28 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 9.78 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 10.28 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 10.78 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 11.28 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 11.78 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 12.28 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 12.78 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 13.28 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 13.78 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 14.28 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 14.78 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 15.28 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p> 15.78 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p>The data were used in Li et al. (2008).</p> <p><strong>References</strong></p> <p>Li, C., C. Chen, D. Guadagnoli, and I. Y. Georgiou (2008). Geometry-induced residual eddies in estuaries with curved channels: Observations and modeling studies, <em>Journal of Geophysical Research</em>, Vol. 113, C01005, doi:10.1029/2006JC004031.</p>
Current velocity data from a continuous survey using a towed ADCP in Wilmington River Estuary, Georgia, USA
<p><strong>Title: </strong>Current velocity data from a continuous survey using a towed ADCP in Wilmington River Estuary, Georgia, USA</p> <p><strong>Author/Data Collector: </strong>Chunyan Li</p> <p><strong>Point of Contact, PI, Originator: </strong>Chunyan Li (cli@lsu.edu)</p> <p><strong>Description:</strong></p> <p>These are velocity profile data from vessel towed ADCP obtained in the Wilmington River Estuary during a survey conducted on Sep. 29, 2004, for ~ 11.5 hours. The instrument was an RDI 600 KHz Workhorse ADCP.</p> <p>The ADCP was mounted on a sled towed by the boat. The vertical bins were 0.5 m. The surveys were conducted at an average cruise speed of about 2.5–3 m/s except at the turns when the vessel had to slow down and during CTD casts when the vessel had to stop for a few minutes. A Seabird Electronic SBE 19 plus CTD was used to measure the vertical profiles of water temperature, salinity, fluorescence, light attenuation, and dissolved oxygen during the survey. Note that only ADCP data are included in this dataset.</p> <p>The data are averaged at about 30-second intervals, excluding bad data. The data presented here are in ASCII with the generic format provided by the RDI’s software WinRiver II output. There are a total of two data files. There are:</p> <p>ADCP_Sep29_2004_WM_000_ASC.TXT</p> <p>ADCP_Sep29_2004_WM_001_ASC.TXT</p> <p>Here is an example of the data –</p> <p> 50 50 42 50 1 20 1</p> <p>4 9 29 11 32 26 57 468 60 2.361 -0.824 118.753 24.276</p> <p>49.04 93.15 -0.17 -0.46 0.00 6.00 0.00 3.08 6.63 6.64 6.68 6.59</p> <p>30.53 28.91 26.93 14.22 30.45</p> <p>32.00327167 -81.01664167 31.50 92.41 30.4</p> <p>-22.0 -7.2 -3.2 -11.2 10.0 -10.8 10.0 1.53 5.53</p> <p>50 cm BT dB 0.43 0.073</p> <p> 1.53 52.35 193.13 -11.9 -51.0 -0.3 3.5 92.1 94.8 94.6 95.6 100 -2.02</p> <p> 2.03 49.89 189.47 -8.2 -49.2 -0.1 -2.1 97.7 99.9 100.4 100.4 100 -2.28</p> <p> 2.53 52.68 187.22 -6.6 -52.3 0.7 4.0 99.0 101.3 101.7 101.2 98 -2.84</p> <p> 3.03 48.92 190.92 -9.3 -48.0 -0.2 5.1 99.2 101.3 101.9 101.6 100 -2.21</p> <p> 3.53 51.77 185.37 -4.8 -51.5 0.3 5.7 98.6 101.4 102.0 101.2 100 -2.99</p> <p> 4.03 48.03 186.14 -5.1 -47.8 1.0 1.2 98.5 101.1 101.9 101.0 100 -2.64</p> <p> 4.53 50.69 190.02 -8.8 -49.9 0.5 3.6 98.5 101.2 101.9 101.2 100 -2.32</p> <p> 5.03 43.70 186.57 -5.0 -43.4 0.7 4.4 98.3 101.2 101.9 101.2 100 -2.34</p> <p> 5.53 41.22 186.13 -4.4 -41.0 1.5 -0.3 98.5 101.6 102.0 101.4 83 -2.35</p> <p> 6.03 -32768 -32768 -32768 -32768 -32768 -32768 255 255 255 255 0 2147483647</p> <p>The ADCP data were used in Li et al. (2008).</p> <p><strong>Acknowledgements</strong></p> <p>I would like to thank Captain Harry Carter who assisted me by driving the boat for the whole day. He also assisted me with CTD casts, deployment, and retrieval of other CTDs. It was a great day working out with him.</p> <p><strong>References</strong></p> <p>Li, C., C. Chen, D. Guadagnoli, and I. Y. Georgiou (2008). Geometry-induced residual eddies in estuaries with curved channels: Observations and modeling studies, <em>Journal of Geophysical Research</em>, Vol. 113, C01005, doi:10.1029/2006JC004031.</p> <p> </p>
Fig. 1 in Diversity of bivalve molluscs in the St Lucia Estuary, with an annotated and illustrated checklist
Fig. 1. Map of the St Lucia Estuary, showing the sampling sites where bivalves were collected from 1925 to 2011; and its geographical position relative to South Africa (adapted from Carrasco et al. 2010).
Fig. 2. Barnea manilensis, a in Diversity of bivalve molluscs in the St Lucia Estuary, with an annotated and illustrated checklist
Fig. 2. Barnea manilensis, a large concentration of dead shells at False Bay, Lake St Lucia, in April 2011. (Photo: Lynette Perissinotto)
Figure 2 in Swimming depth and behaviour of newly recruiting post-larvae of Sicyopterus japonicus (Gobioidei: Sicydiinae) in the estuary of the Ota River, Wakayama, Japan
Figure 2. – Map of the study area the estuary of the Ota River, Wakayama, Japan with the closed and opened (river mouth) stars showing starting and end points of underwater observation. Observations were not conducted in the shaded area on the right side because larvae avoided those areas.
Tidewater goby and estuarine fish records from seining, qPCR and metabarcoding data for Southern California estuaries in 2023
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