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14,867 results for “determination”
Yield determinants of Kappaphycus alvarezii seaweed in South Sulawesi, Indonesia
<p>Experimental data for the paper "Yield determinants of Kappaphycus alvarezii seaweed in South Sulawesi, Indonesia" by van Oort et al.:</p> <ul> <li>seaweed biomasss monitored bi-weekly in 5 cycles of 6 weeks (42 days) in 2023 - 2024 in two locations in South Sulawesi, Indonesia</li> <li>era5 oceanographic data for the two locations in South Sulawesi, monthly, 2015 - 2024</li> <li>water quality data for the two locations in South Sulawesi, bi-weekly, cycles 4 & 5 in 2024</li> <li>temperature data for the two locations in South Sulawesi, hourly, cycles 4 & 5 in 2024</li> <li>location data (kml files)</li> </ul> <p>Plus r-scripts for visualisation and some metadata</p>
Assembled chromosomes of the blood fluke Schistosoma mansoni provide insight into the evolution of its ZW sex-determination system
<p><em>Schistosoma mansoni </em>has a diploid genome of approximately 380 MB, organized in 7 pairs of autosomes and 2 sex chromosomes. The original <em>Schistosoma mansoni </em>Genome Project was completed by the Wellcome Sanger Institute in collaboration with The Institute for Genome Research using a Whole Genome Shotgun sequencing strategy. The draft assembly was subsequently improved first by incorporating Illumina reads from a clonal (single-miracidial) infection and more recently by incorporating long PacBio reads, HiC, and optical mapping data.</p> <p>Associated manuscript can be found at https://www.biorxiv.org/content/10.1101/2021.08.13.456314v1</p>
17O-EPR determination of the structure and dynamics of copper single-metal sites in zeolites
<p><strong>Description of the dataset: </strong></p> <ul> <li><strong>Data type</strong>: Experimental spectroscopic measurements, computer simulation and analysis</li> <li>Files are with filename extensions: <strong>DSC</strong>, <strong>DAT</strong>, <strong>spc</strong>, <strong>par</strong>, <strong>m</strong>, <strong>f34</strong>,<strong> xyz</strong>, <strong>out</strong>, <strong>in</strong></li> <li>Information on <strong>origin of the data</strong>:</li> </ul> <ul> <li>EPR spectroscopic measurements with filename extensions <strong>DSC</strong>, <strong>DTA</strong>,<strong> spc </strong>and<strong> par.</strong></li> <li>EPR spectroscopic simulation and analyses with filename extension <strong>m</strong>.</li> <li>Periodic DFT computations with(out) filename extensions <strong>out</strong> and <strong>f34</strong> in ASCII format.</li> <li>Molecular cluster DFT computations with filename extensions <strong>in</strong> and <strong>out</strong> in ASCII format.</li> <li>Geometry information of cluster models is stored in <strong>xyz</strong> files in ASCII format.</li> </ul> <ul> <li>X-band CW-EPR spectroscopic measurements were generated by EMX spectrometer equipped with SHQ cavity produced by Bruker.</li> <li>Q-band and X-band Pulsed-EPR spectroscopic measurements were generated by ELEXYS 580 EPR spectrophotometer equipped with SHQ cavity and ER035 M NMR gaussmeter produced by Bruker.</li> <li>Periodic DFT computations were generated using distributed parallel version of CRYSTAL17 code.</li> <li>Molecular cluster DFT computations were generated using the ORCA (v4.2.1) code.</li> <li><strong>If t</strong> <ul> <li>Files in <strong>PARACAT_WP3_20210625_01_CW</strong> folder includes X-band CW-EPR spectroscopic measurements; original data are in DTA/DSC and spc/par formats.</li> <li>Files in <strong>PARACAT_WP3_20210625_02_HYSCORE</strong> folder includes HYSCORE spectroscopic measurements; original data are in DTA/DSC formats.</li> <li>Files in <strong>PARACAT_WP3_20210625_03_ESE</strong> folder includes ESE spectroscopic measurements; original data are in DTA/DSC formats.</li> <li>Files in <strong>PARACAT_WP3_20210625_04_ENDOR</strong> folder includes ENDOR spectroscopic measurements; original data are in DTA/DSC formats.</li> <li>Files in <strong>PARACAT_WP3_20210625_05_MATLAB</strong> folder includes computer simulations/analyses of the EPR measurements; data are in m formats.</li> <li>Files in <strong>PARACAT_WP3_20210625_06_DFT </strong>folder includes periodic and cluster DFT computation inputs, outputs and geometries in ASCII format.</li> </ul> </li> </ul> <ul> <li><strong>Information on</strong>: <ul> <li>specialized abbreviations: <strong>EPR</strong> – Electron Paramagnetic Resonance, <strong>CW</strong> – Continuous Wave EPR, <strong>ESE</strong> – Electron Spin Echo detected EPR, <strong>HYSCORE</strong> – HYperfine Sublevel CORrelation spectroscopy, <strong>ENDOR</strong> – Electron Nuclear DOuble Resonance spectroscopy, <strong>DFT </strong>– Density Functional Theory, <strong>CHA </strong>– Chabazite, zeolite topology.</li> <li>definitions of variables: <strong>Magnetic field, Temperature.</strong></li> <li>units of measurement: <strong>Gauss (G), K, degree (°), milliTesla (mT)</strong>.</li> <li>abbreviations: <strong>6MR, 8MR </strong>are the Cu docking sites; <strong>2Al-3NN</strong>, <strong>2Al-2NN</strong>, <strong>1Al</strong> are the different aluminium distributions analysed; <strong>1w</strong>, <strong>2w</strong>, <strong>3w, 4w</strong> indicates the number of water ligands considered in the models; <strong>eq</strong> and <strong>ax</strong> indicates equatorial and axial ligands. Periodic DFT computations with filename extension <strong>.f34</strong> include structural/symmetry information of optimized structure. Molecular cluster DFT computations with filename extension <strong>.in</strong>/<strong>.out</strong>/<strong>.xyz</strong> are inputs, outputs, and structure of cluster models.</li> </ul> </li> </ul>
Training data for neural network-based determination of nematic elastic constants
<p>Neural network training data packets (<strong><em>intensities_{i}.csv, K1K3_{i}.csv</em></strong>), each consisting of 1000 training data pairs, used in a machine learning-based method for determination of Frank elastic constants of nematic liquid crystals, experimental measurements of time-dependent light intensities (<strong><em>experimental_time</em></strong>_<strong><em>{i}.csv, experimental_intensity_{i}.csv</em></strong>), diode spectrum data (<strong><em>diode_lbd</em></strong><strong><em>.csv, diode_w.csv</em></strong>).</p> <p>These data sets are associated with the paper <a href="https://www.nature.com/articles/s41598-023-33134-x"><strong><em>[Zaplotnik et al. SciRep, 2023]</em></strong></a></p> <p>This is supplementary material for a Jupyter Notebook uploaded on <a href="https://zenodo.org/record/7368828">Zenodo</a>.</p>
Data set for publication: Determination of Virulence-Associated Genes and Antimicrobial Resistance Profiles in Brucella Isolates Recovered from Humans and Animals in Iran Using NGS Technology
<p>This dataset includes information on resistance profiling, as well as antimicrobial resistance (AMR) genes and virulence-related factors that were identified in <em>Brucella</em> isolates recovered from humans and animals in different regions of Iran using classical phenotyping and next-generation sequencing (NGS) technology.</p>
Experimental determination of the gadolinium L subshells fluorescence yields and Coster-Kronig transition probabilities
<p>Data associated with the two main tables of the publication "Experimental determination of the gadolinium L subshells fluorescence yields and Coster-Kronig transition probabilities". There are two .txt files containing tabulator-separated values:</p> <p><em>tabl01_ck.txt: </em>Data associated with Table 1 of the publication. This file contains the L subshell Coster-Kronig (CK) factors and their respective uncertainties.</p> <p><em>tabl02_fy.txt: </em>Data associated with Table 2 of the publication. This file contains the experimentally determined Gd L subshell fluorescence yields in comparison to available literature sources and their respective uncertainties.</p> <p>For more details see the original Open Access publication:</p> <p>Kayser, Y., Hönicke, P., Wansleben, M., Wählisch, A., Beckhoff, B., <em>X-Ray Spectrom</em> 2022, 1. <a href="https://doi.org/10.1002/xrs.3313">https://doi.org/10.1002/xrs.3313</a></p>
A novel and holistic approach for experimental X-ray fundamental parameter determination - the Ru L-shell
<p>This dataset contains the experimentally determined fundamental parameters for the ruthenium L-subshells from our paper with the title "A novel and holistic approach for experimental X-ray fundamental parameter determination - the Ru L-shell". The paper will be published soon in a peer-reviewd journal.</p> <p>This file contains L-subshell fluorescence yields, L-shell Coster-Kronig factors, L-shell Auger yields, <br> Mass attenuation coefficients in energy range from 2.41 keV to 8 keV, L-subshell photo ionization cross sections up to 8 keV and <br> L-subshell fluorescence prodution cross sections of Ru.</p>
Integrative structure determination of PTBP1-viral IRES complex in solution
<p>Ensemble structure model of the RNA-binding protein PTBP1 in complex with the internal ribosome entry site (IRES) of encephalomyocarditis virus (EMCV) RNA and data underlying these models.</p> <ul> <li>Main ensemble based on all restraints (corresponding to Figure 2 in the associated paper)</li> <li>Ensemble obtained with only DEER distance distribution restraints corresponding to Figure S7(A) in the Supplementary Material of the associated paper</li> <li>Validation ensemble obtained with all restraints after removing the conformers of the main ensemble from the raw ensemble corresponding to Figure S7(B) inthe Supplementary Material of the associated paper</li> <li>Ensemble obtianed with all restraints by fitting populations with a non-negative linear least squares (NNLLSQ) approach corresponding to Figure S8(A) in ths Supplementary Material of the associated paper</li> <li>Primary DEER-EPR data underlying site-to-site distance distributions for 35 spin-label pairs and corresponding distanace distributions</li> <li>Small-angle neutron scattering (SANS) curves a two detector distances with corresponding resolution files and a small-angle x-ray scattering (SAXS) curve</li> <li>Restraint file for the ensemble fit with MMMx software, specifying the mean distances and standrad deviations of distance distributions that were also used for specifying lower and upper distance bounds in CYANA generation of the raw ensemble</li> <li>Source data for the figures in the associated paper</li> <li>Source data for the tables in the associated paper</li> </ul> <p>All ensembles are ZIP files containing single PDB files for all conformers and an ensemble specification that reports populations for all conformers.</p>
Central Valley Project, Genetic Determination of Population of Origin 2011-2021
Central Valley Chinook Salmon populations differ in their Endangered Species Act listing status. It is often difficult to distinguish individuals from the different Evolutionarily Significant Units. As such, many of the salmon monitoring and evaluation efforts in the Central Valley and San Francisco Bay-Delta are hampered by uncertainty about population (stock) identification and proportional effects of management actions (Dekar et al. 2013; IEP 2019). Studies have identified that the current identification method (length-at-date models) of juvenile Chinook salmon (Fisher 1992) captured in the watershed vary in their accuracy, particularly for spring-run (NMFS 2013; Harvey et al. 2014; Merz et al. 2014). The inaccuracy of the size-based methods is likely due to differences in fish distribution during early rearing, habitat-specific growth rates, and inter-annual variability in temperatures and food availability that lead to overlap in size ranges among stocks. The primary objective of this project was the genetic classification (to race; Evolutionary Significant Unit) of Chinook Salmon captured from State Water Project and Central Valley Project fish protection facilities and Interagency Ecological Program monitoring programs. The population-of-origin was determined for sampled fish by comparing their genotypes to reference genetic baselines. Genetic methods, having less statistical uncertainty that size-based models for population identification, were intended to directly target (and reduce) one source of uncertainty in the estimation of loss (take) from water diversions (operations) and develop the information necessary for understanding stock-specific distribution, habitat utilization, abundance, and life history variation. This project supports recommendations from the Interagency Ecological Program’s Salmon and Sturgeon Assessment of Indicators by Life Stage and Interagency Ecological Program Science Agenda efforts to improve Central Valley salmonid monitoring
Knights Landing, California Department of Fish and Wildlife, Genetic Determination of Population of Origin 2017 through 2019
Central Valley Chinook Salmon populations differ in their Endangered Species Act listing status. It is often difficult to distinguish individuals from the different Evolutionarily Significant Units. As such, many of the salmon monitoring and evaluation efforts in the Central Valley and San Francisco Bay-Delta are hampered by uncertainty about population (stock) identification and proportional effects of management actions (Dekar et al. 2013; IEP 2019). Studies have identified that the current identification method (length-at-date models) of juvenile Chinook salmon (Fisher 1992) captured in the watershed vary in their accuracy, particularly for spring-run (NMFS 2013; Harvey et al. 2014; Merz et al. 2014). The inaccuracy of the size-based methods is likely due to differences in fish distribution during early rearing, habitat-specific growth rates, and inter-annual variability in temperatures and food availability that lead to overlap in size ranges among stocks. The primary objective of this project was the genetic classification (to race; Evolutionary Significant Unit) of Chinook Salmon captured from State Water Project and Central Valley Project fish protection facilities and Interagency Ecological Program monitoring programs. The population-of-origin was determined for sampled fish by comparing their genotypes to reference genetic baselines. Genetic methods, having less statistical uncertainty that size-based models for population identification, were intended to directly target (and reduce) one source of uncertainty in the estimation of loss (take) from water diversions (operations) and develop the information necessary for understanding stock-specific distribution, habitat utilization, abundance, and life history variation. This project supports recommendations from the Interagency Ecological Program’s Salmon and Sturgeon Assessment of Indicators by Life Stage and Interagency Ecological Program Science Agenda efforts to improve Central Valley salmonid monitoring
Sacramento trawl, Delta Juvenile Fish Monitoring Program, Genetic Determination of Population of Origin 2017-2021
Central Valley Chinook Salmon populations differ in their Endangered Species Act listing status. It is often difficult to distinguish individuals from the different Evolutionarily Significant Units. As such, many of the salmon monitoring and evaluation efforts in the Central Valley and San Francisco Bay-Delta are hampered by uncertainty about population (stock) identification and proportional effects of management actions (Dekar et al. 2013; IEP 2019). Studies have identified that the current identification method (length-at-date models) of juvenile Chinook salmon (Fisher 1992) captured in the watershed vary in their accuracy, particularly for spring-run (NMFS 2013; Harvey et al. 2014; Merz et al. 2014). The inaccuracy of the size-based methods is likely due to differences in fish distribution during early rearing, habitat-specific growth rates, and inter-annual variability in temperatures and food availability that lead to overlap in size ranges among stocks. The primary objective of this project was the genetic classification (to race; Evolutionary Significant Unit) of Chinook Salmon captured from State Water Project and Central Valley Project fish protection facilities and Interagency Ecological Program monitoring programs. The population-of-origin was determined for sampled fish by comparing their genotypes to reference genetic baselines. Genetic methods, having less statistical uncertainty that size-based models for population identification, were intended to directly target (and reduce) one source of uncertainty in the estimation of loss (take) from water diversions (operations) and develop the information necessary for understanding stock-specific distribution, habitat utilization, abundance, and life history variation. This project supports recommendations from the Interagency Ecological Program’s Salmon and Sturgeon Assessment of Indicators by Life Stage and Interagency Ecological Program Science Agenda efforts to improve Central Valley salmonid monitoring
Chipps Island trawl, Delta Juvenile Fish Monitoring Program, Genetic Determination of Population of Origin 2017-2021
Central Valley Chinook Salmon populations differ in their Endangered Species Act listing status. It is often difficult to distinguish individuals from the different Evolutionarily Significant Units. As such, many of the salmon monitoring and evaluation efforts in the Central Valley and San Francisco Bay-Delta are hampered by uncertainty about population (stock) identification and proportional effects of management actions (Dekar et al. 2013; IEP 2019). Studies have identified that the current identification method (length-at-date models) of juvenile Chinook salmon (Fisher 1992) captured in the watershed vary in their accuracy, particularly for spring-run (NMFS 2013; Harvey et al. 2014; Merz et al. 2014). The inaccuracy of the size-based methods is likely due to differences in fish distribution during early rearing, habitat-specific growth rates, and inter-annual variability in temperatures and food availability that lead to overlap in size ranges among stocks. The primary objective of this project was the genetic classification (to race; Evolutionary Significant Unit) of Chinook Salmon captured from State Water Project and Central Valley Project fish protection facilities and Interagency Ecological Program monitoring programs. The population-of-origin was determined for sampled fish by comparing their genotypes to reference genetic baselines. Genetic methods, having less statistical uncertainty that size-based models for population identification, were intended to directly target (and reduce) one source of uncertainty in the estimation of loss (take) from water diversions (operations) and develop the information necessary for understanding stock-specific distribution, habitat utilization, abundance, and life history variation. This project supports recommendations from the Interagency Ecological Program’s Salmon and Sturgeon Assessment of Indicators by Life Stage and Interagency Ecological Program Science Agenda efforts to improve Central Valley salmonid monitoring
Determinants of flammability in the critically imperiled pine rocklands of Long Pine Key, 2021-2023
The distribution of plant functional trait values across environmental gradients reflects species’ adaptations to local abiotic conditions. Here, we measured plant composition and plant functional traits in 272 1m2 plots across an elevational and hydrological gradient on Long Pine Key in Everglades National Park between 2021 to 2023. At each site we measured average water depth, elevation, burn frequency, and species richness. We also measured the specific leaf area (SLA), leaf dry matter content (LDMC), leaf area (LA), maximum burn temperature (Temp_C), time to ignition (Ignite) and its inverse (IgniteINV), burn duration (Time), and percent burned (Percent) of five individuals of each species found within our plots. We then used the plant functional trait values SLA, LDMC, and LA, to calculate the CSR value of each plant species found within our plots following the methodology outlined in Pierce et al. (2016). We used these data to determine the distribution of trait values across Long Pine Key and to test for correlations between classic plant functional traits and plant flammability traits. Pierce, S., D. Negreiros, B. E. Cerabolini, J. Kattge, S. Díaz, M. Kleyer, B. Shipley, S. W. Wright, N. A. Soudzilovskaia, V. G. Onipchenko, P. M. van Bodegom, C. Frenette-Dussault, E. Weiher, B. X. Pinho, J. H. C. Corelissen, J. P. Grime, K. Thompson, R. Hunt, P. J. Wilson, G. Buffa, O. C. Nyakunga, P. B. Reich, M. Caccianiga, F. Mangili, R. M. Ceriani, A. Luzzaro, G. Brusa, A. Siefert, N.P.U. Barbosa, F. S. Chapin III, W. K. Cornwell, J. Fang, G. W. Fernandes, E. Garnier, S. Le Stradic, J. Peñuelas, F. P. L. Melo, A. Slaviero, M. Tabarelli, D. Tampucci. 2017. “A global method for calculating plant CSR ecological strategies applied across biomes world‐wide.” Functional ecology 31: 444-457.
Salmonid habitat use monitoring used to determine effectiveness of habitat improvement projects in the Sacramento River, CA
Overview The Central Valley Project Improvement Act (CVPIA) funds habitat improvement work in the Central Valley of California to increase salmonid populations in furtherance of meeting CVPIA fish doubling goals. This data package contains five datasets. Enclosure Study – Growth Data This dataset covers enclosure studies that examined salmonid growth rates in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Data was collected in July and August 2019 from project sites, constructed habitat project sites, and control sites where no treatment is planned. Six enclosures with juvenile Fall Run Chinook salmon from Coleman National Fish Hatchery were placed in each habitat type. Fish growth was tracked for approximately 6.5 weeks. Annual reports summarize the survey findings. Enclosure Study – Gut Contents Data This dataset covers enclosure studies that examined salmonid growth rates in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Data was collected in July and August 2019 from project sites, constructed habitat project sites, and control sites where no treatment is planned. Six enclosures with juvenile Fall Run Chinook salmon from Coleman National Fish Hatchery were placed in each habitat type. Enclosures remained in the river for approximately 6.5 weeks. At the end of the study, fish were euthanized, and we dissected their guts and enumerated the taxa found. Annual reports summarize the survey findings. Microhabitat Use Data This dataset covers salmonid microhabitat use conducted in the Sacramento River and focused on assessing effectiveness of salmonid habitat improvement projects. Surveys are conducted roughly monthly and include pre-project sites, constructed habitat project sites, and control sites where no treatment is planned. Based upon habitat inventory data, annually identify which habitat units within each side channel will be selected for the collectio
Soil hydraulic and thermal properties determined in surface organic and mineral soils in the region near Toolik Lake on the North Slope of Alaska, 2016-2019
Soil cores of 5 cm diameter down to frozen soil were taken from a subset of sample sites for laboratory analysis. Determinations of hydraulic conductivity, thermal conductivity, porosity, and bulk density were made for each core. For a further subset of sites we developed soil moisture retention curves.
Stream nitrate concentrations and discharge, stream nitrate uptake, and results of stream network nitrate model to determine lateral nitrate load from land to stream in Oak Creek, Arizona, USA
Data package associated with Handler et al. (2024) "Nitrate loads from land to stream are balanced by in-stream nitrate uptake across season in a dryland stream". The study describes the nitrate dynamics in Oak Creek watershed. Data include measurements from four seasonal synoptic sampling campaigns, nine seasonal stream nitrate uptake experiments on the main stem and tributaries, and the results of a network model that estimates the lateral load of nitrate from surrounding landscape to the stream network as well as network-level stream nitrate uptake and retention.
Chlorophyll and phaeopigments measured from discrete bottle samples from CCE LTER process cruises in the California Current System, determined by extraction and bench fluorometry, 2006 - 2024 (ongoing).
Discrete bottle samples taken from various depths in the CCE region are filtered (known volumes) onto GF/F filters onboard the CCE Process cruises (since 2006, ongoing). The filters are placed into culture tubes containing 90% acetone, and the fluorescence of the samples is read on a fluorometer after 24 to 48 hours. The samples are then acidified to degrade the chlorophyll to phaeopigments (non-photosynthetic pigments) and a second reading is taken. The readings prior to and after acidification are used to calculate concentrations of both chlorophyll a and phaeopigments (i.e. phaeophytin).
Soil moisture determinations by Electrical Resistivity (ERT) Experiment at the Kellogg Biological Station, Hickory Corners, MI (2009)
Dataset AbstractLarge-scale conversion of croplands to perennial biofuel crops could substantially impact regional water, nutrient, and C cycles due to the longer growing seasons and differences in rooting systems compared with most annual crops. However, these differences in crop water use are not well known due to the limited tools available to nondestructively study the spatiotemporal patterns of root water uptake in situ at field scales. Geophysical imaging tools such as electrical resistivity (ER) reveal changes in water content in the soil profile. Data used in: https://doi.org/10.1002/vzj2.20124original data source http://lter.kbs.msu.edu/datasets/222
WAT02 Climate legacies determine grassland responses to future rainfall regimes
Climate variability and periodic droughts have complex effects on carbon (C) fluxes, with uncertain implications for ecosystem C balance under a changing climate. Responses to climate change can be modulated by persistent effects of climate history on plant communities, soil microbial activity, and nutrient cycling (i.e., legacies). To assess how legacies of past precipitation regimes influence tallgrass prairie C cycling under new precipitation regimes, we modified a long-term irrigation experiment that simulated a wetter climate for >25 years. We reversed irrigated and control (ambient precipitation) treatments in some plots and imposed an experimental drought in plots with a history of irrigation or ambient precipitation to assess how climate legacies affect aboveground net primary productivity (ANPP), soil respiration, and selected soil C pools. Legacy effects of elevated precipitation (irrigation) included higher C fluxes and altered labile soil C pools, and in some cases altered sensitivity to new climate treatments. Indeed, decades of irrigation reduced the sensitivity of both ANPP and soil respiration to drought compared with controls. Positive legacy effects of irrigation on ANPP persisted for at least 3 years following treatment reversal, were apparent in both wet and dry years, and were associated with altered plant functional composition. In contrast, legacy effects on soil respiration were comparatively short-lived and did not manifest under natural or experimentally-imposed “wet years,” suggesting that legacy effects on CO2 efflux are contingent on current conditions. Although total soil C remained similar across treatments, long-term irrigation increased labile soil C and the sensitivity of microbial biomass C to drought. Importantly, the magnitude of legacy effects for all response variables varied with topography, suggesting that landscape can modulate the strength and direction of climate legacies. Our results demonstrate the role of climate his
MCR LTER: Coral Reef: Early life stage bottleneck determines rates of coral recovery following severe disturbance; Data for Speare et al., 2024, Ecology
The data included in this data package were collected on the north shore of Moorea, French Polynesia, from 2011-2018 to evaluate drivers of different recovery rates of corals at two depths (10m and 17m). Data on juvenile coral densities, growth, and mortality, were collected from annual time series photoquadrats. Data from two experiments on coral settlement tiles were used to evaluate how exclusion of fishes influences the density of coral recruits, and the survival of coral recruits at 10 and 17m. These data were used for analyses in the manuscript entitled "Early life stage bottleneck determines rates of coral recovery following severe disturbance". These data are in support of a publication Speare et al. (2024) Ecology. This material uses data collected by the U.S. National Science Foundation's (NSF) Moorea Coral Reef Long Term Ecological Research (MCR LTER) site under Grant No. OCE 2224354 (and earlier awards). Additional financial support to the MCR LTER site was provided through a generous gift from the Gordon and Betty Moore Foundation. Research was completed under permits issued by the French Polynesian Government (Délégation à la Recherche) and the Haut-commissariat de la République en Polynésie Francaise (DTRT) (Protocole d'Accueil 2005-2024).
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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.