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428 results for “zooplankton”
Zooplankton density for all samples collected from Toolik Lake and lakes near the Toolik Field Station, Arctic LTER 2003 - 2017 (Reformatted to a Darwin Core Archive)
This data package is formatted as a Darwin Core Archive (DwC-A, event core). For more information on Darwin Core see https://www.tdwg.org/standards/dwc/. This Level 2 data package was derived from the Level 1 data package found here: https://pasta.lternet.edu/package/metadata/eml/edi/262/2, which was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-arc/10272/5. The abstract below was extracted from the Level 0 data package and is included for context: Zooplankton density,were taken with a 30 cm diameter plankton net with 156 um mesh plankton netting, for all samples collected from Toolik Lake and lakes near the Toolik Field Station, Arctic LTER from 2003 - 2017. The Arctic is one of the most rapidly warming regions on Earth. Responses to this warming involve acceleration of processes common to other ecosystems around the world (e.g., shifts in plant community composition) and changes to processes unique to the Arctic (e.g., carbon loss from permafrost thaw). The objectives of the Arctic Long-Term Ecological Research (LTER) Project for 2017-2023 are to use the concepts of biogeochemical and community “openness” and “connectivity” to understand the responses of arctic terrestrial and freshwater ecosystems to climate change and disturbance. These objectives will be met through continued long-term monitoring of changes in undisturbed terrestrial, stream, and lake ecosystems in the vicinity of Toolik Lake, Alaska, observations of the recovery of these ecosystems from natural and imposed disturbances, maintenance of existing long-term experiments, and initiation of new experimental manipulations. Based on these data, carbon and nutrient budgets and indices of species composition will be compiled for each component of the arctic landscape to compare the biogeochemistry and community dynamics of each ecosystem in relation to their responses to climate change and disturbance and to the propagation of those responses ac
Zooplankton density for lake samples collected near Toolik Lake Arctic LTER in the summers between 1993-2002.
Zooplankton density, in number per liter, was taken with a 30 cm diameter plankton net with a 335 um mesh plankton netting. All samples were collected from Toolik Lake and the lakes near the Toolik Field Station, Arctic LTER from 1993-2002. NOTE: In versions pervious to 3 the dates for 1994 and 1995 were WRONG.
Zooplankton and micronekton abundance using an Isaacs-Kidd Midwater trawl on Northeast U.S. Shelf Long Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2023
During Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, acoustic backscattering layers were identified using multifrequency echosounders and were targeted for collection of zooplankton and micronekton using an Isaacs-Kidd Midwater Trawl. On each cruise, trawling was conducted at at least three stations, including the one at the shelfbreak front, one inshore of the front, and one offshore of the front. The catches from the trawls were preserved on ship and later identified to the lowest possible taxonomic level using a dissecting microscope. Each identified taxon was counted to provide net total abundance by taxon. Trawling was initiated in spring 2023 and is ongoing.
North Temperate Lakes LTER: Zooplankton - Trout Lake Area 1982 - current
Zooplankton samples are collected from the seven primary northern lakes (Allequash, Big Muskellunge, Crystal, Sparkling, and Trout lakes and bog lakes 27-02 [Crystal Bog], and 12-15 [Trout Bog]) at two to nine depths using a 2m long Schindler Patalas trap (53um mesh) and with vertical tows using a Wisconsin net (20cm diameter, 80um mesh). Zooplankton samples are preserved in buffered formalin (until 2001) or 95% ethanol (2001 onwards). Subsamples of the individual Schindler trap samples are combined to create a hypsometrically pooled sample which is counted for copepods, cladocerans, and rotifers. Data are summed over sex and stage to provide a lake-wide estimate of organisms per liter for each species. A minimum of 5 samples per lake-year are counted. The data set also contains length measurements for copepods and cladocerans. The Wisconsin net sample and the pooled sample are archived in the UW Zoology museum. Each year one complete set of Schindler Patalas depth samples collected in August is also archived. From 1981 to August 1986 - used a 0.5m high Schindler Patalas trap. Sampling Frequency: every two weeks during ice-free season, every 5 weeks during ice-cover. Number of sites: 7
North Temperate Lakes LTER: Zooplankton - Madison Lakes Area 1997 - current
Zooplankton samples for the 4 southern Wisconsin LTER lakes (Mendota, Monona, Wingra, Fish) have been collected for analysis by LTER since 1995 (1996 Wingra, Fish) when the southern Wisconsin lakes were added to the North Temperate Lakes LTER project. Samples are collected as a vertical tow using an 80-micron mesh conical net with a 30-cm diameter opening (net mouth: net length ratio = 1:3) consistent with sampling conducted by the Wisconsin Dept. Natural Resources in prior years. Zooplankton tows are taken in the deep hole region of each lake at the same time and location as other limnological sampling; zooplankton samples are preserved in 70% ethanol for later processing. Samples are usually collected with standard tow depths on most dates (e.g., 20 meters for Lake Mendota) but not always, so tow depth is recorded as a variate in the database. Crustacean species are identified and counted for Mendota and Monona and body lengths are recorded for a portion of each species identified (see data protocol for counting procedure); samples for Wingra and Fish lakes are archived but not routinely counted. Numerical densities for Mendota and Monona zooplankton samples are reported in the database as number or organisms per square meter without correcting for net efficiency. [Net efficiency varies from a maximum of about 70% under clear water conditions; net efficiency declines when algal blooms are dense (Lathrop, R.C. 1998. Water clarity responses to phosphorus and Daphnia in Lake Mendota. Ph.D. Thesis, University of Wisconsin-Madison.)] Organism densities in number per cubic meter can be obtained by dividing the reported square-meter density by the tow depth, although adjustments for the oxygenated depth zone during the summer and early fall stratified season is required to obtain realistic zooplankton volumetric densities in the lake's surface waters. Biomass densities can be calculated using literature formulas for converting organism body lengths reported in the databa
Size-fractionated zooplankton dry weight 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 density of zooplankton dry weight for five size fractions 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. One-half of the catch was size-fractionated with nested sieves into the following five size classes for biomass analysis: 0.2−0.5, 0.5−1, 1−2, 2−5, and >5 mm. Individual size fractions were concentrated on preweighed 200 μm mesh filters and frozen at −20°C until analysis. Samples were thawed, weighed to determine wet biomass, dried at 60°C for at least 24 h, and weighed again to determine dry biomass. Zooplankton density varies across size groups, seasonally, among years, and between sampling stations. Units of biomass density are milligrams dry weight per cubic meter.
PIE LTER zooplankton surveys using plankton tows along transects in the Plum Island Sound estuary, Massachusetts
Zooplankton were collected in spring and late summer/fall at four stations representing the salinity gradient in the Parker River-Plum Island Sound estuary. Two size classes, greater than 335 micron and greater than 150 micron, were collected by net tows. Conductivity or salinty and temperature were recorded for each sample. Samples were concentrated to less than 250 mls and preserved in 70 percent EtOH. For taxonomy, sample splits were taken such that a minimum of 250 individuals were present, and counted under a dissecting microscope. Individuals were identified to the lowest taxonomic level possible, generally to species. Adult copepods were additionally characterized by sex.
Nutrient, phytoplankton and zooplankton data, 20 year surface biomass from Darwin
<p>Nutrient, phytoplankton and zooplankton data to accompany Sonnewald et al. : Elucidating Ecological Complexity: Unsupervised Learning determines global marine eco-provinces.</p> <p>Note: We discard the areas (gridcells) with biomass <10-4</p> <p> </p>
Quantifying wind-driven dispersal of zooplankton in a Mediterranean pond
<p>Dispersal is an essential component in the life history of organisms and has strong ecological implications. Although it has been assumed that small organisms have very high dispersal rates, quantitative data supporting this claim remains scarce. In the context of zooplankton, wind stands out as a primary vector facilitating passive dispersal. We quantified short-distance wind-driven dispersal of propagules across various zooplankton taxa in a Spanish Mediterranean coastal temporary pond. We have also studied dispersal patterns in relation to the wind regime (intensity, steadiness and gust direction), source pond status (volume of water) and demographic dynamics (the abundance of individuals in water column populations). Further, we related propagules size merurements (surface, L2 and volume, L3) with dispersal distances. Additionally, we have performed measurements of the dispersed propagules and investigated the relationship between their dimensions and the dispersive distance on a local scale. Here, we present the raw data gathered during research.</p>
Warming drives phenological changes in coastal zooplankton
<p>This repository contains zooplankton observations and model data used in the article Forsblom, Stoffers, Lindén, Lehtiniemi and Engstöm-Öst (2024) Warming drives phenological changes in coastal zooplankton. Marine Biology (in press).</p>
Sub-fossil crustacean zooplankton relative abundances from 101 lakes across Canada
<p>This data set contains cladoceran sub-fossil relative abundances for 101 lakes across Canada sampled as part of the NSERC Canadian Lake Pulse Network project. Lakes were sampled once, over three summers (2017-2018-2019). Cores were collected using a gravity corer in the deepest point of each lake and were sectioned on site with a vertical extruder. Each lake was sampled for a “top” sediment sample, represented by the first centimeter of the surface of the sediment core, and a “bottom” sediment sample, corresponding to the 1 cm of sediment located between 3 and 4 cm from the base of the core. Cladoceran extraction and preparation followed the protocol from Korhola and Rautio (2001). Cladocerans were identified using DM 2500 Leica compound inverted microscope under 200X-400X magnification with a minimal count size of 100 individuals. Identification at the species, genus, or species complex level followed Szeroczynska and Sarmaja-Korjonen (2007) and Korosi and Smol (2012a; b).</p> <p>Sites are identified with Lake ID number, followed by “T” for top samples and “B” for bottom samples. Lakes IDs with respective locations (longitude and latitude coordinates) and Continental Basin allocations can be found here: <a href="https://doi.org/10.5281/zenodo.4701262">https://doi.org/10.5281/zenodo.4701262</a></p> <p>References</p> <p>Korhola, A., and M. Rautio. 2001. Cladocera and other branchiopod crustaceans, p. 225–234. <em>In</em> J.P. Smol, H.J.B. Birks, and W.M. Last [eds.], Tracking Environmental Change Using Lake Sediments. Springer.</p> <p>Korosi, J. B., and J. P. Smol. 2012a. An illustrated guide to the identification of cladoceran subfossils from lake sediments in northeastern North America: Part 1-the Daphniidae, Leptodoridae, Bosminidae, Polyphemidae, Holopedidae, Sididae, and Macrothricidae. J. Paleolimnol. <strong>48</strong>: 571–586. doi:10.1007/S10933-012-9632-3</p> <p>Korosi, J. B., and J. P. Smol. 2012b. An illustrated guide to the identification of cladoceran subfossils from lake sediments in northeastern North America: Part 2-the Chydoridae. J. Paleolimnol. <strong>48</strong>: 587–622.</p> <p>Szeroczyfiska, K., and K. Sarmaja-Korjonen. 2007. Atlas of Subfossil Cladocera from Central and Northern Europe, Friends of the Lower Vistula Society, Warsaw, Pol.</p>
Water quality, phytoplankton, and zooplankton in the Sacramento Deep Water Ship Channel, CA
Drivers of phytoplankton and zooplankton dynamics vary spatially and temporally in estuaries due to variation in hydrodynamic exchange and residence time, complicating efforts to understand controls on food web productivity. We conducted approximately monthly (2012 – 2019; n = 74) longitudinal sampling at ten fixed stations along a freshwater tidal terminal channel in the San Francisco Estuary, California, characterized by seaward to landward gradients in water residence time, turbidity, nutrient concentrations, and plankton community composition. We used multivariate autoregressive state space (MARSS) models to quantify environmental (abiotic) and biotic controls on phytoplankton and mesozooplankton biomass. The importance of specific abiotic drivers (e.g. water temperature, turbidity, nutrients) and trophic interactions differed significantly among hydrodynamic exchange zones with different mean residence times. Abiotic drivers explained more variation in phytoplankton and zooplankton dynamics than a model including only trophic interactions, but individual phytoplankton-zooplankton interactions explained more variation than individual abiotic drivers. Interactions between zooplankton and phytoplankton were strongest in landward reaches with the longest residence times and the highest zooplankton biomass. Interactions between cryptophytes and both copepods and cladocerans were stronger than interactions between bacillariophytes (diatoms) and zooplankton taxa, despite contributing less biovolume in all but the most landward reaches. Our results demonstrate that trophic interactions and their relative strengths vary in a hydrodynamic context, contributing to food web heterogeneity within estuaries at spatial scales smaller than the freshwater to marine transition.
Selected trait data for the most abundant phytoplankton, zooplankton, benthic invertebrates, and fishes of the Upper San Francisco Estuary
This data set includes selected trait data from published literature and online databases for the most common phytoplankton, zooplankton, benthic invertebrate, and fish taxa at long term monitoring stations in the Upper San Francisco Estuary, which includes the Sacramento-San Joaquin River Delta, Suisun Bay, and Grizzly Bay.
Zooplankton Data for North Inlet Estuary, South Carolina, from 1981 to 1992, North Inlet LTER (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-nin/2/1. The abstract below was extracted from the Level 0 data package and is included for context: This data package consists of Zooplankton Data for North Inlet Estuary, South Carolina, from 1981 to 1992, North Inlet LTER. The purpose of the long term monitoring of zooplankton was to characterize the fauna in the water column larger than or equal to 153 microns and to obtain some basic information on each of the taxa encountered there. A sampling regime of collections made at regular biweekly intervals was implemented to provide the best quantitative assessment of long term changes in the zooplankton population dynamics.
Interacting temperature, nutrients and zooplankton grazing control phytoplankton size-abundance relationships in eight Swiss lakes
<p>lake data set for the study "Interacting temperature, nutrients and zooplankton grazing control phytoplankton size-abundance relationships in eight Swiss lakes".</p> <p>Abstract: Biomass distribution among size classes follows a power law where the Log-abundance of taxa scales to Log-size with a slope that responds to environmental abiotic and biotic conditions. The interactions between ecological mechanisms controlling the slope of locally realized size-abundance relationships are however not well understood. Here we tested how warming, nutrient levels, and grazing affect the slope of phytoplankton community size-abundance relationships in decadal time-series from eight Swiss lakes of the peri-alpine region, which underwent environmental forcing due to climate change and oligotrophication. We expected rising temperature to have a negative effect on slope (favoring small phytoplankton), and increasing nutrient levels and grazing pressure to have a positive effect (benefitting large phytoplankton). Using a random forest approach to extract robust patterns from the noisy data, we found that the effects of temperature (direct and indirect through water column stability), nutrient availability (phosphorus and total biomass), and large herbivore (copepods and daphnids) grazing and selectivity on slope were non-linear and interactive. Increasing water temperature or total grazing pressure, and decreasing phosphorus levels, had a positive effect on slope (favoring large phytoplankton, which are predominantly mixotrophic in the lake dataset). Our results therefore showed patterns that were opposite to the expected long-term effects of temperature and nutrient levels, and support a paradigm in which i) small phototrophic phytoplankton appear to be favored under high nutrients levels, low temperature and low grazing, and ii) large mixotrophic algae are favored under oligotrophic conditions when temperature and grazing pressure are high. The effects of temperature were stronger under nutrient limitation, and the effects of nutrients and grazing were stronger at high temperature. Our study shows that the phytoplankton local size-abundance relationships in lakes respond to both the independent and the interactive effects of resources, grazing and water temperature in a complex, unexpected way, and observations from long-term studies can deviate significantly from general theoretical expectations.</p>
Illuminating the planktonic stages of salmon lice: a unique fluorescence signal for rapid identification of a rare copepod in zooplankton assemblages.
<p>The Excitation Emission Matrix (EEM) measurements were taken with Shimadzu's proprietary software ‘LabSolutions RF’. All files are in the exported csv format with columns representing the excitation wavelengths and rows the emission wavelengths. Wavelengths range from 200-600 nm with a 2 nm increment. Fluorescence intensity was influenced by the fluctuating number of animals in the path of the excitation beam during the 5 minute measurement. We compensated for this artefact by repeating measurements of each sample five times, calculating the mean, and applying a smoothing function which found the median value within 10 nm. The fluorescence intensity was further normalized on a 0 to 1 scale by dividing intensity by the maximum fluorescence within each EEM measurement.</p> <p>Supplemental Table 1. The metadata of EEM measurements. The measurements were used for the spectrum section analysis and correspond to those depicted in Figures 2, 3, 4, & 5. See sections 3.1, 3.1.1, & 3.1.2. The Sample column indicates which lab culture cohort the sea lice came from (BGO*), which wild caught fish sample they came from (WC*), or the sampling date of non-target copepods (DDMMYY). The filename of each mean measurement is listed and indicates the first of 5 repeated measurements. Corresponding files can be found in the deposited.csv files at Zendo. In those files, data columns represent the excitation wavelengths, 200nm to 600nm increasing in 2 nm increments. Likewise, the rows represent the emission wavelengths. NaN’s are present where scattering layers were removed. All fluorescence intensity values are normalized to the maximum within each EEM.</p>
Fig. 1 in The Composition, Diversity And Community Dynamics Of Limnetic Zooplankton In A Tropical Caldera Lake (Lake Taal, Philippines)
Fig. 1. Map of Lake Taal with the six sampling sites (NB – North Basin, SB – South Basin). The insert shows the location of Lake Taal and the other lakes mentioned in the text (P – Lake Paoay, Lb – Lake Laguna de Bay, N – Lake Naujan and Ln – Lake Lanao).
Fig. 4 in The Composition, Diversity And Community Dynamics Of Limnetic Zooplankton In A Tropical Caldera Lake (Lake Taal, Philippines)
Fig. 4. Monthly variations in Shannon-Wiener Diversity (H') Index values of rotifers and cladocerans in the north and south basins of Lake Taal.
Fig. 3 in The Composition, Diversity And Community Dynamics Of Limnetic Zooplankton In A Tropical Caldera Lake (Lake Taal, Philippines)
Fig. 3. Mean monthly biomass (μg / l) of common zooplankton species from the north and south basins of Lake Taal for the year 2008.
Data from: The role of fish predators and their foraging traits in shaping zooplankton community structure
<p><span>Differentiation of foraging traits among predator populations may help explain observed variation in the structure of prey communities. However, few studies have investigated the phenotypic effects of predators on their prey in natural communities. Here, we use a comparative analysis of 78 Greenlandic lakes to examine how foraging trait variation among threespine stickleback populations can help explain variation in zooplankton community composition among lakes. We find that landscape-scale variation in zooplankton composition was jointly explained by lake properties, such as size and water chemistry, and the presence and absence of both stickleback and arctic char. </span><span>Additional variation in zooplankton community structure can be explained by stickleback jaw protrusion, a trait with known utility for foraging on zooplankton, but only in lakes where stickleback co-occur with arctic char. Overall, our results illustrate how trait variation of consumers, alongside other ecosystem properties, can influence the composition of prey communities in nature.</span></p>
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