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Figure 2 in Factors influencing spatial and temporal structure of frog assemblages at ponds in southeastern Brazil
Figure 2. Distribution of adult individuals of 22 anuran species at Santuário do Caraça, southeastern Brazil, according to variables used to describe microhabitat use and activity periods, in the first three axes of the discriminant function. Centroids for each species are shown on the right.
Fig. 4 in Diet seasonality and food overlap of the fish assemblage in a pantanal pond
Fig. 4. Niche breadth values to fish assemblage in the Sinhá Mariana pond (Mato Grosso State, Brazil) using Levin's stan- dardized index, during rainy and dry seasons.
Fig. 5 in Diet seasonality and food overlap of the fish assemblage in a pantanal pond
Fig. 5. Values of trophic niche breadth (mean ± standard error) of fish species in the Sinhá Mariana pond (Mato Grosso State, Brazil) during rainy and dry seasons.
Fig. 3 in Diet seasonality and food overlap of the fish assemblage in a pantanal pond
Fig. 3. Dendrogram of diet similarity of the fish assemblage in the Sinhá Mariana pond (Mato Grosso State, Brazil) showing the trophic guilds during rainy (A) and dry (B) seasons. Abbreviations of the species names are showing in table 1.
Fig. 2 in Diet seasonality and food overlap of the fish assemblage in a pantanal pond
Fig. 2. Water level in the in the studied region, Sinhá Mariana pond, Mato Grosso State, Brazil, from March/2000 to February/2001, showing the wet and dry seasons. These dates were provided by Agência Nacional de Águas (ANA).
Diel variation in insect-dominated temperate pond soundscapes and guidelines for survey design
<p>The data and code accompanying 'Diel variation in insect-dominated temperate pond soundscapes and guidelines for survey design' published in Freshwater Biology. </p>
Pond bat capture and diet data from the Netherlands
<p>The goal of this study was to describe the spatial segregation and diet of Pond bats (<em>Myotis dasycneme</em>). A wide range of water-bound habitats throughout the Netherlands was sampled, including marshes, lakes, rivers, wetlands and waterways. For all the locations water depth and soil type were determined. Life animals were captured during 471 nights using a mist net. No Pond bats were captured during 134 of those nights. Water depth and soil type was based on top 10 vector maps (www.pdok.nl/geo-services) with information about both variables. Each captured individual was placed in a separate cotton holding bag until it was weighted, sexed, and the reproductive status and age were assessed by observation of external characteristics. Before dissecting, the dry weight of each faecal pellet was measured with an electronic scale. All samples were dissected under a Carl Zeiss Discovery V20 stereomicroscope. All identifiable fragments were photographed and stored for later use. </p> <p>Genetic analysis: The pellets were ground to a fine powder in liquid nitrogen with a mortar and pestle using the protocol of the commercial Qiagen QIAamp DNA Stool Mini Kit in a special Ancient DNA facility dedicated to work with samples with degraded DNA and following established protocols to avoid contamination such as the inclusion of extraction blanks. Subsequently, aliquots of each extraction were further purified using Promega PCR purification columns. Amplifications of the ~313 bp long mitochondrial COI mini-barcoding marker were performed using forward primer ZBJ-ArtF1c 5’-AGATATTGGAACWTTATATTTTATTTTTGG-3’ and reverse primer ZBJ-ArtR2c 5’- WACTAATCAATTWCCAAATCCTCC-3’. The ~157 bp long mitochondrial 16S barcoding marker was amplified using the forward primer P7_FO-16S 5’- RGACGAGAAGACCCTATARA-3’ and P7_R0-16S 5’-ACGCTGTTATCCCTAARGTA-3’. Primers were labelled for DNA metabarcoding with IonExpress labels. The PCR was carried out in 30 microliter reactions containing 0.20 µl Qiagen taq 5u/µl, 3 µl 10x Qiagen buffer, 2 µl 2,5mM dNTP’s, 0,5 µl 10 µM forward primer, 0,5 µl 10 µM reverse primer, 1,5 µl 25mM MgCl<sub>2, </sub>0,5 µl 10 mg/ml BSA, 19.80 µl MiliQ and 2 µl template. Amplifications were performed using the following PCR programme: 5 min denaturation at 95°C followed by 40 cycles of 20 seconds denaturation at 95°C, 20 seconds annealing at 50°C and 1-minute elongation at 72°C. Final elongation was conducted at 72°C for 7 minutes on a C1000 Biorad PCR machine. Primer dimer and other contaminants were removed by using 0.9x Ampure XP beads (Agencourt) to which the PCR products were bound. The beads were washed with 150 microliter 70% EtOH twice and resuspended in 20 microliter TE buffer. Cleaned PCR products were quantified using an Agilent 2100 Bioanalyzer DNA High sensitivity chip. An equimolar pool was prepared of the amplicon libraries at the highest possible concentration. This equimolar pool was diluted according to the calculated template dilution factor to target 10-30% of all positive Ion Sphere Particles. Template preparation and enrichment was carried out with the Ion One Touch 200 Template kit with use of the Ion One Touch System, according to the manufacturer's protocol. The quality control of the Ion One Touch 200 Ion Sphere Particles was done with the Ion Sphere Quality Control kit using a Life Qubit 2.0. The enriched Ion Spheres were prepared for sequencing on a Personal Genome Machine (PGM) with the Ion PGM 200 Sequencing kit as described in the protocol and deposited on an Ion-314 chip (520 cycles per run) in three consecutive sequencing runs. Reads obtained from Ion Torrent sequencing were automatically sorted into separate sequence files based on the MID labels by the Ion Torrent software. The reads were further processed with PRINSEQ (version 0.20.3) with the following settings: a minimum read length of 100 bp, trimming to 140 bp, minimum mean quality of Q24 per read, additional trimming of '3 end bases with a Q lower than 24 and removal of full duplicate sequences. Filtered reads were clustered into Operational Taxonomic Units (OTUs) defined by a sequence similarity of at least 97% using CD-HIT-EST. Singletons were omitted. For each cluster the representative sequences were BLASTed with the NCBI-blast+ software package (version 2.2.28+) against either the NCBI GenBank nucleotide database or a custom database containing all Arthropod sequences located on the Barcode of Life Database. BLAST hits were filtered according to the following criteria: minimum hit length of a 100 bp, minimum hit similarity of 97% and a maximum e-value of 0.05. Reference databases of Dutch species such as http://www.nederlandsesoorten.nl/ were used to check if a species had been recorded for the Netherlands. All species not (yet) known for The Netherlands were reduced to genus level or to the family level if the genus is also unknown to occur.</p> <p> </p> <p>Description of the data files:</p> <p> </p> <p><strong>pelletsMicroscopy.csv</strong></p> <p>Details of individual faecal pellets with prey remains analysed using microscopic analysis.</p> <p>ID: pellet ID</p> <p>sex: sex of the caught Pond bat individual</p> <p>age: age class of the bat</p> <p>date: capture night</p> <p>province: province in which the bat was captured</p> <p>x and y: spatial coordinates within the Netherlands</p> <p>waterDepth: water depth in meters at the capture location</p> <p>pelletWeight: weight of the pellet in grams</p> <p>year: capture year</p> <p>dayOfYear: day of the year, since January 1</p> <p>period: I: end of hibernation till May 20, II May 21- June 29, III: June 30- July 30 and IV: July 31 till hibernation</p> <p>meanPreyWeight: average weight of prey in mg</p> <p>peat: whether the capture site was located in peatland or not</p> <p>propPupae: the proportion of pupae of chironomids: the number of pupae divided by the total number of organisms of all species in a pellet</p> <p>evenness: Pielou’s evenness of the abundance of prey items in a pellet</p> <p>shannon: Shannon index of the diversity of prey items in a pellet</p> <p>saFemale and saMale: sexual activity status of females and males at the time of capture</p> <p>temp: mean temperature (in 0.1 degrees Celsius) during the first two hours after sunset during the capture night</p> <p>wind: mean wind speed (in 0.1 m/s) during the first two hours after sunset during the capture night</p> <p>nPupae: number of Chironomidae pupae found in a pellet</p> <p>nPrey: total number of prey items found in a pellet</p> <p> </p> <p><strong>pelletsMetabarcoding.csv</strong></p> <p>Details of individual faecal pellets analysed using metabarcoding. </p> <p>ID: pellet ID</p> <p>sex: sex of the caught Pond bat individual</p> <p>reproductiveState: reproductive status of the bat</p> <p>age: age class of the bat</p> <p>mature: sexually mature (1) or not (0)</p> <p>date: capture night</p> <p>peat: whether the capture site was located in peatland or not</p> <p>province: province in which the bat was captured</p> <p>x and y: spatial coordinates within the Netherlands</p> <p>waterDepth: water depth in meters at the capture location</p> <p>pelletWeight: weight of the pellet in grams</p> <p> </p> <p><strong>preyWeight.csv</strong></p> <p>Mean weight (milligram) of taxonomic and developmental prey groups, including information on length (mm) and width (mm) of each group.</p> <p> </p> <p><strong>orderPellet.csv</strong></p> <p>Number of pellets in which at least 1 prey of a certain taxon is found, separately per sex of the bat and per analysis method (microscopy or metabarcoding). Total number of analyzed pellets was 365 for females – microscopy, 170 for males – microscopy, 95 for females – metabarcoding, and 65 for males – metabarcoding. </p> <p> </p> <p><strong>taxaCountsMicroscopy.csv</strong></p> <p>Number of prey individuals per taxonomic group found by using morphological analyses (microscopy) of faecal pellets of Pond bats. For each group the number of observations are given separately for male and female bats.</p> <p> </p> <p><strong>taxaCountsMetabarcoding.csv</strong></p> <p>Number of prey individuals per taxonomic group found by using metabarcoding of faecal pellets of Pond bats. For each group the number of observations are given for both male and female bats.</p>
Campus Pond (Buffalo Creek Watershed) Data from 2022-07-08 to 2022-09-01
<p>General Metadata for Campus Pond Sampling Station</p> <p>Files</p> <p>Specific metadata for each deployment and sensor can be found as text files with the file format of:</p> <pre><code>BC_CampusPond_YYYY-MM-DD_YYYY-MM-DD_metadata.txt</code></pre> <p>Where YYYY-MM-DD_YYYY-MM-DD is the date range of the sampling period.</p> <p>NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab <a href="https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts">https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts</a>.</p> <p>File Created</p> <ul> <li>2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md</li> </ul> <p>File Modified</p> <p>Description</p> <p>These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702).</p> <p>All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a></p> <p>Station Specifics</p> <p>The specific sensors at the site are:</p> <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> <p>The sensors are sampled every 15 minutes</p> <p>Measurement Parameters, units, and Variable Names</p> <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT - the temperature (dC) from the DO or conductivity. * WaterTemp - the water temperature measured from the pressure transducer in the water (dC). * AirTemp - the air temperature measured from the pressure transducer (BP sensor) in the air (dC). * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
Campus Pond (Buffalo Creek Watershed) Data from 2022-06-13 to 2022-07-08
<p>General Metadata for Campus Pond Sampling Station</p> <p>Files</p> <p>Specific metadata for each deployment and sensor can be found as text files with the file format of:</p> <pre><code>BC_CampusPond_YYYY-MM-DD_YYYY-MM-DD_metadata.txt</code></pre> <p>Where YYYY-MM-DD_YYYY-MM-DD is the date range of the sampling period.</p> <p>NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab <a href="https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts">https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts</a>.</p> <p>File Created</p> <ul> <li>2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md</li> </ul> <p>File Modified</p> <p>Description</p> <p>These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702).</p> <p>All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a></p> <p>Station Specifics</p> <p>The specific sensors at the site are:</p> <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> <p>The sensors are sampled every 15 minutes</p> <p>Measurement Parameters, units, and Variable Names</p> <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT - the temperature (dC) from the DO or conductivity. * WaterTemp - the water temperature measured from the pressure transducer in the water (dC). * AirTemp - the air temperature measured from the pressure transducer (BP sensor) in the air (dC). * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
Campus Pond (Buffalo Creek Watershed) Data from 2022-05-11 to 2022-06-13
<p>General Metadata for Campus Pond Sampling Station</p> <p>Files</p> <p>Specific metadata for each deployment and sensor can be found as text files with the file format of:</p> <pre><code>BC_CampusPond_YYYY-MM-DD_YYYY-MM-DD_metadata.txt</code></pre> <p>Where YYYY-MM-DD_YYYY-MM-DD is the date range of the sampling period.</p> <p>NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab <a href="https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts">https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts</a>.</p> <p>File Created</p> <ul> <li>2021-11-10 by KF - copied and modified from HS_wetland_general_metadata.md</li> </ul> <p>File Modified</p> <p>Description</p> <p>These data are from the sampling station in Campus Pond on the Longwood University Campus. The sensors are along the S shoreline of the pond (37.296813, -78.397702).</p> <p>All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a></p> <p>Station Specifics</p> <p>The specific sensors at the site are:</p> <pre><code>* Water Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Water Temperature (dC) and Water Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Water Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger * Air Temperature (dC) and Barometric Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger mounted in the air next to the wetland.</code></pre> <p>The sensors are sampled every 15 minutes</p> <p>Measurement Parameters, units, and Variable Names</p> <pre><code>* date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * observation.DO, .CT, .press, or .BP - the incremental number of each observation from the DO, conductivity, water pressure, or barometric pressure sensor. * timestamp.DO, .CT, .press, or .BP - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) from the DO, conductivity, water pressure, or barometric pressure sensor. * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp.DO, .CT - the temperature (dC) from the DO or conductivity. * WaterTemp - the water temperature measured from the pressure transducer in the water (dC). * AirTemp - the air temperature measured from the pressure transducer (BP sensor) in the air (dC). * Pressure.press or .BP - the pressure recorded by the pressure transducer (kPa) on the water pressure or barometric pressure sensor. * Z - the depth of the water (cm). * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) * press.g.cm2 - the pressure from the water pressure sensor (g/cm^2) * BP.g.cm2 - the barometric pressure from the barometric pressure sensor (g/cm^2)</code></pre>
Plants metacommunity from temporary ponds
<p>The database comprises a long-term survey of a plant metacommunity of temporary ponds. The metacommunity is <span><span>located in a flat landscape surrounded by hills, where a maximum of 61 ponds, every year</span><span>,</span><span> are filled with water in winter and dry out in summer in the same spatial locations. Information on species occurrences at the sampling unit level was recorded since 2005 (until 2022 and continuous). </span></span></p> <p><span>The database includes: </span></p> <ol> <li><span>Species occurrences at the sampling unit level for 61 temporary ponds along 14 years (to be periodically updated). </span></li> <li><span>Species traits database and functional description of traits. </span></li> <li><span>Environmental information of each pond including connectivity, area, heterogeneity and hydroperiod.</span></li> </ol>
Mysterious microsporidians: springtime outbreaks of disease in Daphnia communities in shallow pond ecosystems
<p>Parasites can play key roles in ecosystems, especially when they infect common hosts that play important ecological roles. <em>Daphnia</em> are critical grazers in many lentic freshwater ecosystems and typically reach peak densities in early spring. <em>Daphnia</em> have also become prominent model host organisms for the field of disease ecology, although most well-studied parasites infect them in summer or fall. Here, we report field patterns of virulent microsporidian parasites that consistently infect <em>Daphnia</em> in springtime, in a set of seven shallow ponds in Georgia, USA, sampled every 3–4 weeks for 18 months. We detected two distinct parasite taxa, closely matching sequences of <em>Pseudoberwaldia</em> <em>daphniae</em> and <em>Conglomerata</em> <em>obtusa</em>, both infecting all three resident species of <em>Daphnia</em>: <em>D. ambigua, D. laevis, </em>and<em> D. parvula</em>. To our knowledge, neither parasite has been previously reported in any of these host species or anywhere in North America. Infection prevalence peaked consistently in February-May, but the severity of these outbreaks differed substantially among ponds. Moreover, host species differed markedly in terms of their maximum infection prevalence (5% [<em>D. parvula</em>] to 72% [<em>D. laevis</em>]), mean reduction of fecundity when infected (70.6% [<em>D. ambigua</em>] to 99.8% [<em>D. laevis</em>]), mean spore yield (62,000 [<em>D. parvula</em>] to 377,000 [<em>D. laevis</em>] per host), and likelihood of being infected by each parasite. The timing and severity of the outbreaks suggest that these parasites could be impactful members of these shallow freshwater ecosystems and that the strength of their effects is likely to hinge on the composition of ponds' zooplankton communities.</p>
Reconstructed and measured bathymetry of the Brandka Pond (Bytom, S Poland) - database
<p>The Brandka Pond belongs to anthropogenic lakes, one of many within the Upper Silesian Anthropogenic Lake District. It developed in the early 1990s in Bytom (Southern Poland) due to land subsidence and a permanent change in the area's water conditions. The database contains material on the reconstruction of the bottom relief of the Brandka Pond in Bytom based on the rate of land subsidence after coal mining. It also includes changes in the extent of the reservoir in 1993-2019 and land use between 1881 and 2019.</p>
Tropical origin, global diversification and dispersal in the pond damselflies (Coenagrionoidea) revealed by a new molecular phylogeny
<p class="western">The processes responsible for the formation of Earth's most conspicuous diversity pattern, the latitudinal diversity gradient (LDG), remain unexplored for many clades in the Tree of Life. Here, we present a densely-sampled and dated molecular phylogeny for the most speciose clade of damselflies worldwide (Odonata: Coenagrionoidea), and investigate the role of time, macroevolutionary processes and biome-shift dynamics in shaping the LDG in this ancient insect superfamily. We used process-based biogeographic models to jointly infer ancestral ranges and speciation times, and to characterise within-biome dispersal and biome-shift dynamics across the cosmopolitan distribution of Coenagrionoidea. We also investigated temporal and biome-dependent variation in diversification rates. Our results uncover a tropical origin of pond damselflies and featherlegs ~ 105 Ma, while highligthing uncertainty of ancestral ranges within the tropics in deep time. Even though diversification rates have declined since the origin of this clade, global climate change and biome-shifts have slowly increased diversity in warm- and cold-temperate areas, where lineage turnover rates have been relatively higher. This study underscores the importance of biogeographic origin and time to diversify as important drivers of the LDG in pond damselflies and their relatives, while diversification dynamics have instead resulted in the formation of ephemeral species in temperate regions. Biome-shifts, although limited by tropical niche conservatism, have been the main factor reducing the steepness of the LDG in the last 30 Myr. With ongoing climate change and increasing northward range expansions of many damselfly taxa, the LDG may become less pronounced. Our results support recent calls to unify biogeographic and macroevolutionary approaches to increase our understanding of how latitudinal diversity gradients are formed and why they vary across time and among taxa.</p>
NOAA GML Kettle Ponds Surface Radiation Budget and Near-Surface Meteorology Data for SPLASH
<p>These files contain Surface Energy Balance data at the Kettle Ponds (CKP) site as part of NOAA’s Global Monitoring Laboratory’s deployment in the Sail-SPLASH Campaign between October 2021 through August 2023.</p>
Plants metacommunity from temporary ponds
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Animal metacommunities of temporary ponds in a flat grassland landscape of Uruguay
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Tropical origin, global diversification and dispersal in the pond damselflies (Coenagrionoidea) revealed by a new molecular phylogeny
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Restored off-channel pond habitats create thermal regime diversity and refuges within a Mediterranean-climate watershed
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Data from: Persistence of the ecological niche in pond damselflies underlies a stable adaptive zone despite varying selection
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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.