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29 results for “Mesozooplankton”
Mesozooplankton taxonomic density collected using a 1-m diameter ring net with 200-μm mesh at Palmer Station, Antarctica during Palmer LTER field seasons, 2017-2020
Zooplankton are a morphologically and taxonomically diverse group of animals. Many zooplankton feed on phytoplankton in surface waters and thus provide a link between primary producers and higher trophic levels. The numerical density of common mesozooplankton taxa was determined at Palmer LTER Stations B and E. Samples were collected with a 1-m diameter, 200-μm mesh ring net towed obliquely from the surface to a target depth of 50 m and back. Tows were conducted during daytime, and sampling frequency was nominally twice weekly while personnel were at Palmer Station between the months of November and March. The preserved samples were size-fractionated with nested sieves into five size classes (0.2−0.5, 0.5−1, 1−2, 2−5, and >5 mm) prior to microscopic enumeration. Data are provided for the following taxa: copepods Oithona spp., Calanoides acutus (>1 mm only), Calanus propinquus (>1 mm only), Rhincalanus gigas (>1 mm only), and small calanoids (0.2−1 mm), chaetognaths, asteroid larvae, nemertean larvae, and foraminifera (not quantified in all years). Individual size fractions were split and subsampled such that at least 100 individuals of the most abundant taxon were present. Density varies across taxa, seasonally, among years, and between sampling stations. Units of density are individuals per cubic meter.
Drivers of spatial and temporal micro- and mesozooplankton dynamics in an estuary under strong anthropogenic influences (The Eastern Scheldt, Netherlands)
<p>Supplement to: Horn, H.G., van Rijswijk, P., Soetaert, K., van Oevelen, D. (2023): Drivers of spatial and temporal micro- and mesozooplankton dynamics in an estuary under strong anthropogenic influences (The Eastern Scheldt, Netherlands). J Sea Res. <a href="https://doi.org/10.1016/j.seares.2023.102357">https://doi.org/10.1016/j.seares.2023.102357</a></p> <p>This data set contains mesozooplankton and microzooplankton abundances, temperature, salinity, O2, DOC, Chl.a, SPM, and nutrient concentrations from eight stations in the Eastern Scheldt sampled in 2018. Phytoplankton growth and microzooplankton grazing rates from dilution experiments are also provided.</p>
Gut Fluorescence measurements of mesozooplankton grazing on autotrophic prey. Samples collected in the CCE-LTER region on Process Cruises from 2006 to the present. Summaries for each Lagrangian Cycle.
Mesozooplankton are collected with plankton nets (typically a 71-cm diameter, 202-um mesh Bongo net) and samples flash frozen at sea in liquid N2 for subsequent shore-based measurements of ingested phytoplankton chlorophyll-a. Measurements of mesozooplankton gut fluorescence are done by fluorometric analysis on a Turner Designs fluorometer of gut pigments extracted in 90% acetone. Analyses are done on mesozooplankton size-fractionated into 5 different categories on Nitex mesh (> 0.2 mm, 0.5 mm, 1.0 mm, 2.0 mm, 5.0 mm). The pigment content (as Chl-a and phaeopigments) is then expressed as mass of pigment ingested per m3 of water filtered, or divided by the dry weight biomass of the mesozooplankton in the same sample in order to obtain mass-specific ingestion per m3 of water. Application of published values of the temperature-dependent gut passage time are used to estimate the mesozooplankton grazing rate, as pigments ingested per m3 per unit time, or the corresponding mass-specific rate of ingestion. Samples for gut fluorescence assays have been collected on CCE-LTER Process Cruises since 2006 and these collections are ongoing.
Dry weight biomass measurements of net-collected mesozooplankton. Samples collected in the CCE-LTER region on Process Cruises from 2006 to the present. Summaries for each Lagrangian Cycle.
Mesozooplankton are collected with plankton nets (typically a 71-cm diameter, 202-um mesh Bongo net) and samples flash frozen at sea in liquid N2 for subsequent shore-based measurements of dry weight biomass. Measurements are made by weighing pre-tared Nitex mesh on an analytical balance, for mesozooplankton size-fractionated into 5 different categories (> 0.2 mm, 0.5 mm, 1.0 mm, 2.0 mm, 5.0 mm). Biomass is expressed as dry mass of zooplankton per m3 of water filtered, or when multiplied by the maximum depth of the tow, as integrated dry mass of zooplankton per m2 of sea surface. Samples for dry weight biomass have been collected on CCE-LTER Process Cruises since 2006 and these collections are ongoing.
Figure 4 in Seasonal variation and taxonomic composition of mesozooplankton in the southern Black Sea (off Sinop) between 2005 and 2009
Figure 4. Percentage composition of the main mesozooplankton groups in terms of abundance and biomass off Sinop for 2005–2009.
Figure 5 in Interactions between environmental factors and the mesozooplankton community from the Romanian Black Sea waters
Figure 5. Analysis of the main components (PCA) for the environmental factors from the Romanian Black Sea, by sector and season, 2013–2020.
Figure 6 in Interactions between environmental factors and the mesozooplankton community from the Romanian Black Sea waters
Figure 6. Statistically significant correlation (p <0.05) between the mesozooplankton groups and environmental factors grouped by isobaths, 2013–2020.
Linked collectors and determiners for: Mesozooplankton Ramfjord.
Natural history specimen data linked to collectors and determiners held within, "Mesozooplankton Ramfjord". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/b4804f19-8a8a-49e7-8dc2-79b528635696">https://bionomia.net/dataset/b4804f19-8a8a-49e7-8dc2-79b528635696</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/b4804f19-8a8a-49e7-8dc2-79b528635696">https://gbif.org/dataset/b4804f19-8a8a-49e7-8dc2-79b528635696</a>. Formatted as a Frictionless Data package.
Supplementary materials for "Effects of mesozooplankton growth and reproduction on plankton and organic carbon dynamics in a marine biogeochemical model"
<h2>Overview</h2> <p>This folder contains supplementary materials corresponding to the analysis conducted for "Effects of mesozooplankton growth and reproduction on plankton and organic carbon dynamics in a marine biogeochemical model". The folder is structured into two .zip files. <a href="../api/records/10720907/draft/files/ZENODO_PISCES_MLC.zip/content" target="_blank" rel="noopener noreferrer">ZENODO_PISCES_MLC.zip</a> contains the analysis presented in the paper. BDM-MAREDAT-ZENODO.zip contains the outputs from the Biomass Distribution Models pipeline developped by Nielja Knecht (<a href="../doi/10.5281/zenodo.7888451">10.5281/zenodo.7888451</a>) applied to the MAREDAT mesozooplankton product. </p> <h2>ZENODO_PISCES_MLC Folder Structure</h2> <h3>BDM</h3> <ul> <li><strong>MAREDAT_TUNED_SDM.csv</strong>: This file contains the BDM mesozooplankton biomass monthly climatology from MAREDAT data.</li> </ul> <h3>CODE</h3> <p>This directory contains Jupyter Notebook files (<code>.ipynb</code>) and related Python scripts used for data analysis and visualization. Below is a list of the files:</p> <ul> <li><strong>Code_Fig3_FigA8_FigA17.ipynb</strong>: Jupyter Notebook for generating figures 3, A8, and A17.</li> <li><strong>Code_Fig4.ipynb</strong>: Jupyter Notebook for generating figure 4.</li> <li><strong>Code_Fig5_FigA12_FigA13.ipynb</strong>: Jupyter Notebook for generating figures 5, A12, and A13.</li> <li><strong>Code_Fig6.ipynb</strong>: Jupyter Notebook for generating figure 6.</li> <li><strong>Code_Fig7.ipynb</strong>: Jupyter Notebook for generating figure 7.</li> <li><strong>Code_FigA10.ipynb</strong>: Jupyter Notebook for generating figure A10.</li> <li><strong>Code_FigA11.ipynb</strong>: Jupyter Notebook for generating figure A11.</li> <li><strong>Code_FigA14.ipynb</strong>: Jupyter Notebook for generating figure A14.</li> <li><strong>Code_FigA15.ipynb</strong>: Jupyter Notebook for generating figure A15.</li> <li><strong>Code_FigA16.ipynb</strong>: Jupyter Notebook for generating figure A16.</li> <li><strong>Code_FigA1.ipynb</strong>: Jupyter Notebook for generating figure A1.</li> <li><strong>Code_FigA2.ipynb</strong>: Jupyter Notebook for generating figure A2.</li> <li><strong>Code_FigA6_FigA7.ipynb</strong>: Jupyter Notebook for generating figures A6 and A7.</li> <li><strong>Code_FigA9.ipynb</strong>: Jupyter Notebook for generating figure A9.</li> <li><strong>Code_POC_metrics_not_in_the_paper.ipynb</strong>: Jupyter Notebook containing metrics related to particulate organic carbon (POC) not included in the paper.</li> <li><strong>Code_Table3.ipynb</strong>: Jupyter Notebook for generating table 3.</li> <li><strong>Code_Table4.ipynb</strong>: Jupyter Notebook for generating table 4.</li> <li><strong>Code_Table5.ipynb</strong>: Jupyter Notebook for generating table 5.</li> <li><strong>GlobalEstimatesAbstract.ipynb</strong>: Jupyter Notebook containing global estimates abstract.</li> <li><strong>mlctools</strong>: Python package containing utility functions for the analysis.</li> </ul> <h3>OBS</h3> <p>This directory contains observed data used in the analysis:</p> <ul> <li><strong>BATS_zooplankton.csv</strong>: Zooplankton data from the Bermuda Atlantic Time-series Study (BATS).</li> <li><strong>CHL2.nc</strong>: Chlorophyll data in NetCDF format.</li> <li><strong>climatology_n_0_5.nc</strong>: Climatological data in NetCDF format.</li> <li><strong>HOTS_zooplankton.csv</strong>: Zooplankton data from the Hawaii Ocean Time-series (HOTS).</li> </ul> <h3>OUTPUT</h3> <p>This directory contains output files from PISCES simulations (yearly, monthly and 5-day-average outputs). </p> <ul> <li><strong>0class</strong>: Output files for the '0class' classification corresponding to PISCES-v2.</li> <li><strong>0classregrid</strong>: Regridded output files for the '0class' classification corresponding to PISCES-v2.</li> <li><strong>10classes</strong>: Output files for the '10classes' classification corresponding to PISCES-MOG.</li> <li><strong>10classesregrid</strong>: Regridded output files from PISCES-MOG.</li> <li><strong>2classes</strong>: Output files from PISCES-MOG-2LS.</li> <li><strong>2classesregrid</strong>: Regridded output files from PISCES-MOG-2LS.</li> <li><strong>NOALLOregrid</strong>: Regridded output files from PISCES-MOG-NA.</li> </ul> <h3>PLOT</h3> <p>This directory contains plots generated during the analysis:</p> <h3>TEMP</h3> <p>This directory contains temporary files used during the analysis, including data files and matrices.</p> <h2>BDM-MAREDAT-ZENODO Folder </h2> <p>BDM-MAREDAT-ZENODO.zip contains the outputs from the Biomass Distribution Models pipeline developped by Nielja Knecht (<a href="../doi/10.5281/zenodo.7888451">10.5281/zenodo.7888451</a>) applied to the MAREDAT mesozooplankton product. </p> <p>For any inquiries or data access requests, please contact corentin.clerc -at- usys.ethz.ch</p>
Figure 6 in Biological diversity and seasonal variation of mesozooplankton in the southeastern Black Sea coastal ecosystem
Figure 6. Anchovy production during the sampling period.
Figure 1 in Seasonal variation and taxonomic composition of mesozooplankton in the southern Black Sea (off Sinop) between 2005 and 2009
Figure 1. Study area and sampling station location.
Figure 1 in Interactions between environmental factors and the mesozooplankton community from the Romanian Black Sea waters
Figure 1. Map of sampling stations during 2013–2020 in the Romanian Black Sea area.
Figure 3 in Interactions between environmental factors and the mesozooplankton community from the Romanian Black Sea waters
Figure 3. Black Sea temperature, salinity, and oxygen box plot by sector and season, 2013–2020.
Figure 2 in Interactions between environmental factors and the mesozooplankton community from the Romanian Black Sea waters
Figure 2. Matrix of mesozooplankton abundance and biomass in 2013–2020, by seasons.
Figure 4 in Interactions between environmental factors and the mesozooplankton community from the Romanian Black Sea waters
Figure 4. Black Sea nutrients box plot by sector and season, 2013–2020.
Supplement table of mesozooplankton taxa obtained using long-read and short-read metabarcoding
<p>Supplement tables containing information about publications on mesozooplankton taxa in the Ross Sea using two metabarcoding analyses</p>
Mesozooplankton data of NEREA Augmented Observatory
<p>Mesozooplankton was collected with double WP2, which has a mouth area of 0.25 m2 and mesh aperture width of 200 μm. The net, ballasted with a 3 kg weight, was towed vertically to the surface at low speed (0.7-1.0 m s-1). </p>
Bulk and amino acid nitrogen specific isotope data from particulate organic matter and mesozooplankton (1000-2000 µm) from the Mekong River plume and southern South China Sea
<p><strong><span><span>The mean trophic position (TP) of mesozooplankton largely determines how much mass and energy is available for higher trophic levels like fish. Unfortunately, the ratio of herbivores to carnivores in mesozooplankton is difficult to identify in field samples. Here we investigated changes in the mean TP of mesozooplankton in a highly dynamic environment encompassing four distinct habitats in </span></span></strong>the southern South China Sea:<strong> </strong><span>the </span>Mekong River plume, coastal upwelling region, shelf waters, and offshore oceanic waters<strong><span>. </span></strong><span>We used a set of parameters derived from bulk and amino acid nitrogen stable isotopes from particulate organic matter (POM) and four mesozooplankton size fractions to identify changes in the nitrogen source and structure of the planktonic food web across these habitats.</span> We found clear indications of a shift in N sources for biological production from nitrate in near-coastal waters towards an increase in diazotroph-N inputs in oceanic waters where diazotrophs shaped the phytoplankton community. The shift in N source was accompanied by a lengthening of the food chain (increase in the TP), which may provide further support for the connection between diazotrophy and the indirect routing of N through the marine food web. Our combined bulk and amino acid δ<sup>15</sup>N approach also allowed us to estimate the trophic enrichment (TE) of mesozooplankton across the entire regional ecosystem. When put in the context of literature values, our high TE of 5.1‰ suggested a link between ecosystem heterogeneity and the less efficient transfer of mass and energy across trophic levels.</p>
Figure 3 in Structure of mesozooplankton community in the Barents Sea and adjacent waters in August 2009
Figure 3. Temperature–salinity diagram for all top-to-bottom/100 m CTD data in the Barents Sea and adjacent waters in August 2009.
Figure 2 in Structure of mesozooplankton community in the Barents Sea and adjacent waters in August 2009
Figure 2. Vertical profiles of temperature and salinity in the upper layer at the five water masses in the Barents Sea and adjacent waters in August 2009.
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