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174 results for “structural size”
Economical routes to size-specific assembly of self-closing structures
<p>This data contains images related to a publication on the self-assembly of DNA origami particles (<a href="https://www.science.org/doi/10.1126/sciadv.ado5979">https://www.science.org/doi/10.1126/sciadv.ado5979</a>). In this work, we conduct self-assembly experiments with various unique subunit types that target two different diameters of tubule structures.</p> <p>We provide image data of tubules that are associated with the probability distributions reported across several figures in the main text. Images of tubules are in the ZIP archives and show the section of tubules we analyzed to produce the probability distributions in the manuscript. Each folder of images has an associated CSV file that relates an image name to the type of tubule that the image was identified as. Tubule types have "m" and "n" values.</p> <p>We provide full tomogram reconstruction data for the multicomponent tubules that are shown in Figure 2 of the main text. In the ZIP archive, each tubule image has two files associated with it: a REC file that contains the tomogram reconstruction data and an MDOC file that contains imaging metadata. REC files can be opened with the open-source software IMOD.</p> <p>We provide raw image data of pitch- and width-controlled tubules that have been labeled with gold nanoparticles. These accompany the representative images in Figure 4 in the main text. (Pitch Controlled 4-color with GNPs.zip, Width Controlled 4-color with GNPs.zip).</p> <p>We provide raw image data of length-controlled tubules. These images accompany Figure 5 in the main text. (Length Controlled Tubule Images.zip)</p> <p><strong>Associated publication citation:</strong></p> <div> <p><span>Thomas E. Videbæk <em>et al., </em></span><span>Economical routes to size-specific assembly of self-closing structures. </span><span><em>Sci. Adv. </em></span><span><strong>10</strong>, </span><span>eado5979 </span><span>(2024). </span><span>DOI:<a href="https://doi.org/10.1126/sciadv.ado5979">10.1126/sciadv.ado5979</a></span></p> </div>
Two decades of body length measurements in size-structured larval and juvenile fish populations in English rivers.
<p>Long term ecological datasets are valuable in providing context and understanding to complex ecological processes that occur over broad temporal scales, and provide a baseline for analysing change. Monitoring of fish populations in UK waterbodies and elsewhere is typically through measuring the length of individual fish caught in surveys. Through this method, the age structure of fish populations can be determined, as well as over winer survival rates and future recruitment success and cohort sizes can be predicted. The larval and juvenile period are when fish are considered most vulnerable to predation, competition, disease and environmental perturbations. </p> <p><br>This study presents the first long-term larval and juvenile fish lengths dataset for 67 survey sites over two decades (1999-2018) from the rivers Ancholme, Warwickshire Avon, Don, Trent, and Yorkshire Ouse (including the Swale, Ure, Nidd and Wharfe) in the United Kingdom. These rivers represent a range of topographical and biotopical characteristics. For the majority of this study, surveys were conducted on a monthly or fortnightly basis making both annual and seasonal analyses of size structure, growth and body length possible. Although there is some variation in the sampling frequency and some locations varied throughout the study according to requirements. In total, more than 380,000 larval or juvenile fish of 30 species were measured, likely representing one of the most comprehensive datasets of its type.</p> <p>Surveys were conducted in river margins, where the velocity was slowest and larval and juvenile fish tend to aggregate. Fish were captured using a 25 x 3 m micromesh (3 mm mesh size) seine net that was set in a rectangle parallel to the bank. This net capture fish as small as 5 mm and is the most appropriate method of catching larvae and juvenile fish, although occasionally some larger adult fish may have also been captured and measured as part of this dataset for completeness. All fish were identified to species and measured to standard length (mm) and released at the point of capture. The exception was the smallest larvae, which were euthanised with an overdose of methanesulphonate (MS-222) and preserved in 4% formalin solution for microscopic examination.</p> <p><br>The dataset contains 384,090 rows and 13 columns. Each row corresponds to a single fish that was measured at each site and date. Associated site information (site name, location, area fished (m<sup>2</sup>) and survey date) is reported for each row. When only a fraction of the catch was processed, the sub-sample size was reflected in the Count column (e.g. when half the sample was processed, the numbers of fish measured or only counted were multiplied by two). This enables accurate densities to be calculated as the total number of both measured and unmeasured fish is recorded.</p> <p>Description of columns found in the dataset:</p> <p> </p> <table> <tbody> <tr> <td> <p><strong>Column heading</strong></p> </td> <td> <p><strong>Column description</strong></p> </td> <td> <p><strong>Data type</strong></p> </td> <td> <p><strong>Units</strong></p> </td> </tr> <tr> <td> <p>Fish _Catchment</p> </td> <td> <p>The river catchment/basin location of each fish site</p> </td> <td> <p>Text</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Fish_River</p> </td> <td> <p>The river/watercourse location of each fish site.</p> </td> <td> <p>Text</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Fish_SiteName</p> </td> <td> <p>The name of each fish site</p> </td> <td> <p>Text</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Fish_Latitude</p> </td> <td> <p>The latitude of each fish site (WGS 1984)</p> </td> <td> <p>Integer</p> </td> <td> <p>Decimal degrees</p> </td> </tr> <tr> <td> <p>Fish_Longitude</p> </td> <td> <p>The longitude of each fish site (WGS 1984)</p> </td> <td> <p>Integer</p> </td> <td> <p>Decimal degrees</p> </td> </tr> <tr> <td> <p>Fish_Area</p> </td> <td> <p>Area of fish site surveyed</p> </td> <td> <p>Integer</p> </td> <td> <p>m<sup>-2</sup></p> </td> </tr> <tr> <td> <p>Fish_SurveyDate</p> </td> <td> <p>Date fish survey was carried out</p> </td> <td> <p>Integer</p> </td> <td> <p>dd/mm/yyyy</p> </td> </tr> <tr> <td> <p>Fish_Year</p> </td> <td> <p>Year fish survey was carried out</p> </td> <td> <p>Integer</p> </td> <td> <p>yyyy</p> </td> </tr> <tr> <td> <p>Common_Name</p> </td> <td> <p>The common/vernacular name of each fish taxon recorded in the dataset.</p> </td> <td> <p>Text</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Latin_Name</p> </td> <td> <p>The scientific name of each fish taxon recorded in the dataset</p> </td> <td> <p>Text</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Net_Number</p> </td> <td> <p>The net number the fish in a given survey were caught on</p> </td> <td> <p>Integer</p> </td> <td> <p>n/a</p> </td> </tr> <tr> <td> <p>Length_mm</p> </td> <td> <p>Length of individual fish caught</p> </td> <td> <p>Integer</p> </td> <td> <p>mm</p> </td> </tr> <tr> <td> <p>Count</p> </td> <td> <p>Count of fish caught accounting for sub- sampling</p> </td> <td> <p>Integer</p> </td> <td> <p>Number of fish</p> </td> </tr> </tbody> </table> <p> </p>
Data from: Flock size and structure influence reproductive success in four species of flamingo in 540 captive populations worldwide
<p><strong>Summary</strong></p> <p>This dataset accompanies the publication "<strong>Flock size and structure influence reproductive success in four species of flamingo in 540 captive populations worldwide</strong>" published in Zoo Biology. It contains anonymised data from 540 captive flamingo populations, and includes the four species: <em>Phoeniconaias minor, Phoenicopterus chilensis, Phoenicopterus roseus</em> and<em> Phoenicopterus ruber</em>. Data were sourced from the Zoological Information Management System (ZIMS), operated by Species360 (https://www.species360.org/). ZIMS is the largest real-time database of comprehensive and standardized information spanning more than 1,200 zoological collections globally, and provides the number of institutions currently managing each flamingo species and both their current and historic population sizes. These data were used to investigate the relationship between reproductive success and both flock size, and structure, on a global scale.</p> <p>This dataset also contains climatic data provided by WorldClim, which were used to assess the influence of climatic variables on captive flamingo reproductive success globally. The WorldClim database averages 19 different climatic variables derived from monthly temperature and rainfall values at a 1 km spatial resolution for the period 1970-2000. Using geographic coordinates (latitude and longitude) we calculated several climatic metrics for each institution. </p> <p> </p> <p><strong>Description of the Dataset</strong></p> <p>One file is provided for each species (<em>P. minor, P. chilensis, P. roseus </em>and <em>P. ruber</em>) as a csv file. Each file contains the following 15 columns:</p> <ul> <li><strong>Institution Code: </strong>An anonymous code used to identify individual zoological institutions. </li> <li><strong>Country: </strong>The country where the institution is located.</li> <li><strong>Year: </strong>Current year (<em>t</em>).</li> <li><strong>Flock Size:</strong> Flock size in year <em>t.</em></li> <li><strong>Males: </strong>The number of males in the flock in year <em>t.</em> </li> <li><strong>Females:</strong> The number of females in the flock in year <em>t.</em></li> <li><strong>Unsexed:</strong> The number of unsexed individuals in the flock in year <em>t.</em></li> <li><strong>Proportion of Females: </strong>The proportion of the flock made up of female individuals in year <em>t</em>. </li> <li><strong>Proportion of Unsexed:</strong> The proportion of the flock made up of unsexed individuals in year <em>t.</em></li> <li><strong>Hatches:</strong> Number of birds hatched in year <em>t.</em></li> <li><strong>Proportion of Additions:</strong> The proportion of the flock in year <em>t</em> made up of additions from year <em>t-1</em> (not including new birds hatched into the flock).</li> <li><strong>MAP: </strong>Mean annual precipitation (mm).</li> <li><strong>MAT: </strong>Mean annual temperature (°C).</li> <li><strong>MAP Var: </strong>Mean annual variation in precipitation (MAP coefficient of variation).</li> <li><strong>MAT Var: </strong>Mean annual variation in temperature (MAT standard deviation).</li> </ul> <p>Note: Mean Annual Temperature (MAT) is provided by WorldClim as °C multiplied by 10, and similarly mean annual variation in temperature as MAT standard deviation multiplied by 100. In the corresponding publication, both were divided (by 10 and 100 respectively) prior to modelling to avoid confusion in the units used.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>We acknowledge and thank all Species360 member institutions for their continued support and data input. The research which data refers to was funded by the Irish Research Council Laureate Awards 2017/2018 IRCLA/2017/60 to Y.M.B. Additionally, S.Q.S. received funding from the International Max Planck Research School for Organismal Biology. The Species360 Conservation Science Alliance would like to thank their sponsors: the World Association of Zoos and Aquariums, Wildlife Reserves of Singapore, and Copenhagen Zoo. </p> <p> </p> <p><strong>Disclaimer</strong></p> <p>Despite our best efforts at screening the data for errors and inconsistencies, some information could be erroneous. Similarly, data contained within ZIMS are based on submitted records from individual institutions, and are not subject to editorial verification, potentially permitting errors or failure to update species holdings etc. Despite this, ZIMS represents the only global database of zoo collection composition records, and as a result, is used by the IUCN, Convention on International Trade in Endangered Species (CITES), the Wildlife Trade Monitoring Network (TRAFFIC), United States Fish and Wildlife Service (USFWS) and Department for Environment, Food and Rural Affairs (DEFRA). </p> <p> </p> <p><strong>Credit</strong></p> <p>If you use this dataset, please cite the corresponding publication:</p> <p>Mooney, A., Teare, J. A., Staerk, J.,Smeele, S. Q., Rose, P., Edell, R. H., King, C. E., Conrad, L., & Buckley, Y. M. (2023). Flock size and structure influence reproductive success in four species of flamingo in 540 captive populations worldwide.<em> Zoo Biology</em>, 1–14. <a href="https://doi.org/10.1002/zoo.21753">https://doi.org/10.1002/zoo.21753</a></p> <p> </p> <p> </p>
Summer water chemistry, phytoplankton and zooplankton community composition, size structure, and biomass in a shallow, hypereutrophic reservoir in southwestern Iowa, USA (2019).
This data product contains data for Green Valley Lake, a hypereutrophic reservoir in southwest Iowa (USA) from the summer of 2019. We sampled and quantified zooplankton, phytoplankton, and nutrient concentrations (total N, total P, soluble reactive P, nitrate) in the lake weekly with the primary aim of assessing consumer nutrient cycling, specifically zooplankton nutrient cycling, in a hypereutrophic reservoir. Weekly plankton sampling included quantifying zooplankton and phytoplankton biomass, community composition, and size structure. Phytoplankton size was measured as the greatest axial linear distance which would be approached by a zooplankton grazer. Allometric equations from the literature were applied to the zooplankton size measurements to estimate zooplankton community excretion of N and P. We found that the estimated contribution of zooplankton excretion to the dissolved P pool was substantial in the spring. Further, we found evidence that zooplankton affected phytoplankton size distributions through selective grazing of smaller phytoplankton cells likely affecting nutrient uptake and storage by phytoplankton.
Effects of ribbed mussel aggregation size on marsh invertebrate community structure and multiple eocsystem functions
Ribbed mussels (Geukensia demissa) were added in aggregations containing 0, 1, 3, 5, 10, 20, 40 or 80 mussels (N=3 replicates per aggregation size) in Spring of 2012 in a high marsh platform at the Airport Marsh on Sapelo Island, GA. In summer of 2013, we measured the response of invertebrate communities and six ecosystem functions. Specifically, we counted the number of Littoraria irrorata, Sesarma reticulatum burrows, Uca pugnax burrows (those > and <5mm in diameter were counted separately), and mud crab (Eurythium limosum and Panopeus herbstii) in 50cm x 50cm sampling frames. And, we measured aboveground cordgrass biomass, benthic algae biomass, invertebrate biomass, decomposition rate, infiltration rate, and soil accretion in the same size sampling frames in August of 2013.
Experimental manipulation of predatory crab species identity (Panopeus obesus vs. Eurytium limosum) and size-structure and assessment of effects on invertebrate densities, sediment properties and plant biomass.
Predatory mud crabs (Panopeus obesus and Eurytium limosum) are two of the main resident infaunal predators in southeastern US salt marshes. Little is known, however, about their effects on important prey species, or their influences on sediment or plant properties. These influences are likely to be dependent on the identity of species and the size-stucture of the population. We therefore manipulated the species identity (Panopeus or Eurtium) and size-structure. The size-structure treatrment had four levels: small [9 individuals, each 18-22mm carapace diameter], medium [6 ind. 24 -28mm], large [3 ind. 32-36mm], mixed (3 small, 2 medium, 1 large, all within same cage). The numbers of crabs in each size-structure treatment were chosen to capture natural size-abundance relationships. The treatments were maintained in experimental cages (70 x 70 x 100 cm, length, width, height) in the mid-Spartina zone at Dean Creek, Sapelo Island, GA. We maintained the treatments over 4 months (July - October 2010), before assessing impacts on prey densitities (mud fiddler crabs, ribbed mussels and marsh periwinkles), and ecosystem properties (aboveground plant biomass, sediment redox potential, sediment water content).
Raw data for the article "Size-Dependent Structural Alterations in Ag Nanoparticles During CO2 Electrolysis in a Gas-Fed Zero-Gap Electrolyzer"
<p>In the article "Size-Dependent Structural Alterations in Ag Nanoparticles During CO2 Electrolysis in a Gas-Fed Zero-Gap Electrolyzer" we described our investigation on the size-dependent degradation behavior of Ag NPs (10, 40, and 100 nm in size) on GDE during CO<sub>2</sub> electrolysis. Here we present the dataset the work was based on. For each figure in the article and the supporting information we provide a set of raw and unprocessed data.</p>
UCSB SONGS Mitigation Monitoring: Wetland Survey - Spartina Size Structure
These data describe annual estimates of Spartina foliosa size structure collected as part of the SONGS San Dieguito Wetland Restoration mitigation monitoring program designed to evaluate compliance of the restoration project with conditions of the SONGS permit. Monitoring began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA. The height of Spartina stems were recorded along four transects at each wetland. Beginning in 2024, Tijuana Estuary was replaced with Mugu Lagoon in Ventura County, CA.
Figure 4 in Inter-oceanic comparison of planktonic copepod ecology (vertical distribution, abundance, community structure, population structure and body size) between the Okhotsk Sea and Oyashio region in autumn
Figure 4. Copepod species composition (centre) and copepodid stage structures of the dominant species (left: Oyashio region, right: Okhotsk Sea). All data are integrated means of a 0– 500 m water column based on the IONESS samples in the Oyashio region (St. 19) and Okhotsk Sea (St. OK24) from October to November 1996. Error bars for the copepodid stage indicate standard deviations of each daily duplicate.
Figure 3 in Inter-oceanic comparison of planktonic copepod ecology (vertical distribution, abundance, community structure, population structure and body size) between the Okhotsk Sea and Oyashio region in autumn
Figure 3. Vertical distribution of zooplankton biovolume in the Oyashio region (upper panels) and Okhotsk Sea (lower panels) from September to December in 1996–1998. Note that the biovolume axes are not the same between panels. Tc: thermocline.
Assessing size at sexual maturity and fine-scale population structure in a direct developing whelk (Buccinum undatum) in Southern Newfoundland, Canada
<p>R script file used to filter genotype data, estimate L50, and analyze patterns of population structure of <em>Buccinum undatum </em>in Southern Newfoundland, Canada. Also included are the following files required to run the script:</p> <p>populationsNWA.snps.vcf - Northwest Atlantic group output at the conclusion of the Stacks de novo pipeline<br>pop_map_NWA.txt - Population map for the Northwest Atlantic group<br>genlightNWAFullFilt.rds - Filtered genotype data for the Northwest Atlantic group<br>populations3Ps.snps.vcf - 3Ps group output at the conclusion of the Stacks de novo pipeline <br>pop_map_3Ps.txt - Population map for the 3Ps group<br>genlight3PsFullFilt.rds - Filtered genotype data for the 3Ps group<br>maturity_data.csv - Data set containing, shell length, sex, and maturity status for samples.<br>sample_site_coordinates_3Ps.csv - Data set containing coordinates of 3Ps sample sites</p> <p> </p>
Tree size, microhabitat diversity and landscape structure determine the value of isolated trees for bats in farmland
<p>Isolated trees are increasingly recognised as playing a vital role in supporting biodiversity in agricultural landscapes, yet their occurrence has declined substantially in recent decades. Most bats in Europe are tree-dependent species that rely on woody elements in order to persist in farmlands. However, isolated trees are rarely considered in conservation programs and landscape planning. Further investigations are therefore urgently required to identify which trees – based on both their intrinsic characteristics and their location in the landscape – are particularly important for bats. We acoustically surveyed 57 isolated trees for bats to determine the relative and interactive effects of size, tree-related microhabitat (TreM) diversity and surrounding landscape context on bat activity. Tall trees with large diameter at breast height and crown area positively influenced the activity of <em>Pipistrellus pipistrellus</em> and small Myotis bats (<em>Myotis</em> spp.) while smaller and thinner trees favoured <em>M. myotis</em> activity. The diversity of TreMs that can be used as roosts had a positive effect on (i) <em>Barbastella barbastellus</em> activity only when trees were relatively close (10% within 100 radius scale). The potential benefits of isolated trees for bats result from ecological mechanisms operating at both tree and landscape scales, underlining the crucial need for implementing a multi-scale approach in conservation programs. Maintaining the largest and most TreM-diversified trees located in the most heterogeneous agricultural landscapes will provide the greatest benefits.</p>
A Pelagic Size Structure database (PSSdb) to support biogeochemical modeling: third update to first release of PSSdb-bulk
<p>This dataset represents the third update to the first release of the Pelagic Size Structure database (PSSdb, <a href="https://pssdb.net">https://pssdb.net</a>) scientific project, investigating the global particle size distributions measured from multiple pelagicǂ imaging systems. These devices include the Imaging Flow Cytobot (Olson and Sosik 2007), benchtop scanners like the ZooScan (Gorsky et al. 2010), and the Underwater Vision Profiler (Picheral et al. 2010). The data sources originate from Ecotaxa (<a href="https://ecotaxa.obs-vlfr.fr/">https://ecotaxa.obs-vlfr.fr/</a>), Ecopart (<a href="https://ecopart.obs-vlfr.fr/">https://ecopart.obs-vlfr.fr/</a>), and Imaging FlowCytobot dashboards (<a href="https://ifcb.caloos.org/dashboard">https://ifcb.caloos.org/dashboard</a> and <a href="https://ifcb-data.whoi.edu/dashboard">https://ifcb-data.whoi.edu/dashboard</a>). Links to the PSSdb code and documentation are available on the PSSdb webpage (<a href="https://pssdb.net">https://pssdb.net</a>). </p> <p>This <em>updated version</em> includes the following changes: </p> <p>● Duplicate data entries and NaN values have been removed.<br>● Data products now include Normalized Biomass Size Spectra (NBSS), and Particle Size Distribution (PSD), two widely used methods to represent plankton and particles size distribution in marine ecology and biogeochemistry (Jonasz and Fournier 1996, San Martin et al. 2006).<br>● Linear regressions are now performed with log10 transformations of the normalized biovolume/abundance and the size classes.<br>● Inclusion of UVP6 and other benchtop plankton Scanner datasets from net tows, which expand the temporal and spatial coverage of the data products.<br>● Unbiased portion of the size spectra is selected by a new thresholding method that accounts for both uncertainties on particle sizes, limited by the camera resolution, and particle count (Schartau et al. 2010), so that only size classes with less than 20% uncertainty are retained, in addition to gaps in the size spectra.</p> <p>Added in this version (March, 2024):<br>● An error in the thresholding function (scripts/funcs_NBS.py) was corrected.<br>● A quality control function was implemented (scripts/funcs_NBS.py) to flag size spectra calculations in products 1a and 1b.</p> <p>Added in this version (April, 2024):</p> <p><span><span>●<span> </span></span></span><span>An error in the size classes defined in the <a href="https://github.com/jessluo/PSSdb/blob/main/ancillary/ecopart_size_bins.tsv"><span>ecopart_size_bins.tsv</span></a> used by the size binning function (<a href="https://github.com/jessluo/PSSdb/commit/9e3c52179b2d3333971028a4a023a06e48444283#diff-28c0193fe5dad62dccba0020363d6cc496a8921fccb723a5e4bf3608d3dd0879"><span>scripts/funcs_NBS.py</span></a>) was corrected, the size ratio between consecutive size bins is the same across all the size ranges now.</span></p> <p> </p> <p>This PSSdb dataset is composed of two products, specific to each imaging device: </p> <ul> <li><strong>Product </strong>1a includes the size distribution , computed from normalized biovolume, for NBSS, and normalized abundance, for PSD, of plankton and particles within a set of pre-defined size classes (expressed in both biovolume and equivalent circular diameter), averaged by year and month, and in 1-degree longitude/latitude grid cells.</li> <li><strong>Product 1b</strong> includes the results of NBSS and PSD regression fit parameters, slopes, intercept, and coefficient of determination (R2), averaged by year and month, and in 1-degree longitude/latitude grid cells. The regression parameters are defined using ordinary least squares linear regressions applied to a log10 transformed normalized biovolume/normalized abundance and biovolume/ diameter size class values.</li> </ul> <p>Size spectra parameters were averaged over a maximum of 16 spatial and temporal subsets (0.5°x0.5°x1 week) to avoid over-representation of repeated sampling events (e.g., time-series datasets) within a grid cell. Linear regressions were performed on the linear portion of the log10-transformed NBSS and PSD estimates, between the size classes with a size measurement or particle count uncertainty greater than 20% (Schartau et al. 2010) , and where the maximum NB/PSD is observed and the largest size class before three empty consecutive size classes.</p> <p><em> <strong> For additional information, please see the PDF documentation available below ...</strong></em></p> <p> </p>
PSSdb-Taxa: A Pelagic Size Structure database taxa-specific product to support biogeochemical modeling: Update to first release of taxa-specific products
<p>This dataset represents the first update to the first release of taxa-specific products from the Pelagic Size Structure database (PSSdb,<a href="https://pssdb.net/"> </a><a href="https://pssdb.net">https://pssdb.net</a>), a scientific project investigating the global particle size distributions measured from multiple pelagic imaging systems. These devices include the Imaging Flow Cytobot (Olson and Sosik 2007), benchtop scanners like the ZooScan (Gorsky et al. 2010), and the Underwater Vision Profiler (Picheral et al. 2010). The data sources originate from Ecotaxa (<a href="https://ecotaxa.obs-vlfr.fr/">https://ecotaxa.obs-vlfr.fr/</a>), Ecopart (<a href="https://ecopart.obs-vlfr.fr/">https://ecopart.obs-vlfr.fr/</a>), and Imaging FlowCytobot dashboards (<a href="https://ifcb.caloos.org/dashboard">https://ifcb.caloos.org/dashboard</a> and<a href="https://ifcb-data.whoi.edu/dashboard"> </a><a href="https://ifcb-data.whoi.edu/dashboard">https://ifcb-data.whoi.edu/dashboard</a>).</p> <p>Taxa-specific products were generated after standardization of the automated or manual taxonomic annotations assigned to individual particles following the recent guidelines of Neeley et al. (2021). We used the World Register of Marine Species (WoRMS, <a href="https://www.marinespecies.org/">https://www.marinespecies.org/</a>) to assign each particle its final taxonomic annotation, and published group-specific relationships linking biovolume to carbon biomass or dry weight.</p> <p>The herein taxa-specific products include both taxonomic class-specific data, obtained after grouping all particles in a given taxonomic class<strong><sup>§</sup></strong>, and broad plankton functional type (PFT) data<strong><sup>Ɨ</sup></strong>. Detrital materials were also separated based on common categories (marine snow, aggregate, fecal pellet) and known biovolume-to-biomass conversion factors (Durkin et al. 2021). Links to the PSSdb code (including the taxonomic and allometric look-up tables) and documentation are available on the PSSdb webpage (<a href="https://pssdb.net">https://pssdb.net</a>).</p> <p> </p> <p>This <em>updated version</em> includes the following changes (modified in April, 2024):</p> <p>● An error in the size classes defined in the <a href="https://github.com/jessluo/PSSdb/blob/main/ancillary/ecopart_size_bins.tsv">ecopart_size_bins.tsv</a> used by the script generating taxa-specific products (<a href="https://github.com/jessluo/PSSdb/commit/b5725df2f32f0300ab64b0a630136c7f5a6857c7">scripts/5_compute_taxa_NBSS.py</a>) was corrected, the size ratio between consecutive size bins is the same across all the size range.</p> <p> </p> <p><em><strong> For additional information, please see the PDF documentation available below ...</strong></em></p>
Рис. 2. Размерная структура G. lacustris в ΛитораΛьной зоне озера АрахΛей: 1 — июнь; 2 — август; 3 — октябрь Fig. 2. G. lacustris population size structure in the Lake Arakhley littoral zone: 1 — June, 2 — August, 3 — October in The life cycle of Gmelinoides fasciatus (Stebbing, 1899) and Gammarus lacustris (Sars, 1863) amphipods in the lake Arakhley littoral during the extreme low-water phase of the hydrological cycle
Рис. 2. Размерная структура G. lacustris в ΛитораΛьной зоне озера АрахΛей: 1 — июнь; 2 — август; 3 — октябрь Fig. 2. G. lacustris population size structure in the Lake Arakhley littoral zone: 1 — June, 2 — August, 3 — October
Рис. 1. Размерная структура Gm. fasciatus в ΛитораΛьной зоне озера АрахΛей: 1 — в июне; 2 — в августе; 3 — в октябре; 4 — в Αекабре 2017 г. и июне 2018 г. Fig. 1. Gm. fasciatus population size structure in the Lake Arakhley littoral zone: 1 — June; 2 — August; 3 — October; 4 — December, 2017 and June, 2018 in The life cycle of Gmelinoides fasciatus (Stebbing, 1899) and Gammarus lacustris (Sars, 1863) amphipods in the lake Arakhley littoral during the extreme low-water phase of the hydrological cycle
Рис. 1. Размерная структура Gm. fasciatus в ΛитораΛьной зоне озера АрахΛей: 1 — в июне; 2 — в августе; 3 — в октябре; 4 — в Αекабре 2017 г. и июне 2018 г. Fig. 1. Gm. fasciatus population size structure in the Lake Arakhley littoral zone: 1 — June; 2 — August; 3 — October; 4 — December, 2017 and June, 2018
Species-specific differences in bumblebee worker body size between elevations: Implications for pollinator community structure under climate change
<p>Code and dataset for manuscript titled "<span>Species-specific differences in bumblebee worker body size between elevations: Implications for pollinator community structure under climate change". Authors: Caterina Massa, Janneke Hille Ris Lambers, Sarah K. Richman. Manuscript accepted to Journal of Pollination Ecology in May 2024. All data collected and analyzed by the authors.<br></span></p>
Fig. 5 in The Body Size, Age Structure And Growth Pattern Of The Endemic Balkan Mosor Rock Lizard (Dinarolacerta Mosorensis Kolombatović, 1886)
Fig. 5. The growth curves of male and female Mosor rock lizards. Age was assessed by skeletochronology, while the growth curves were fitted to VON BERTALANFFY's equation
Fig. 2. A in The Body Size, Age Structure And Growth Pattern Of The Endemic Balkan Mosor Rock Lizard (Dinarolacerta Mosorensis Kolombatović, 1886)
Fig. 2. A cross-section of the femur diaphysis of an adult female Mosor rock lizard. Eight LAGs are shown (LAGs appear as thin dark lines); the first LAG is partly eroded, while the outer LAGs are closely spaced (decreasing intervals between them indicate a shift in a resource allocation after sex-
Fig. 1 in The Body Size, Age Structure And Growth Pattern Of The Endemic Balkan Mosor Rock Lizard (Dinarolacerta Mosorensis Kolombatović, 1886)
Fig. 1. The sample size and body length (SVL) distribution of Mosor rock lizard hatchlings, subadults and adults
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.