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Inter- and intra-annual temperature and precipitation variability (1950-2022) across the ranges of non-migratory birds and their association with generation length
While environmental variability is theorized to impact the life history characteristics of organisms, these hypotheses have not been thoroughly tested with empirical data. To fill this gap, we synthesized a global data set of environmental variability metrics and life history characteristics across the ranges of 7,477 non-migratory, non-marine avian species. These data are derived from the ERA5 climate reanalysis, AVONET, BirdTree, and BirdLife databases as well as previously published research. By extracting environmental variability values across individual species' ranges, this data set allows users to evaluate avian species' pace of life in response to environmental change.
Data in support of 'Mechanistic insights into plant community responses to environmental variables: genome size, cellular nutrient investments, and metabolic trade-offs.'
Data was collected to examine whether and how the plant genome size (GS) influences traits (stomata size, stomata density, cellular and tissue level carbon (C), nitrogen (N), and phosphorus (P) contents) and metabolic-tradeoffs (of photosynthesis, evapotranspiration, water-use, efficiency) of plants in treatment plots in which nothing, N, P, or NP had been annually added. Data was collected from ~500 plants from seven grassland sites that are all part of the Nutrient Network (https://nutnet.org), a globally distributed experiment in which plots have different nutrient amendment treatments that are administered identically to allow cross-site comparisons of the effects of nutrients on biodiversity patterning. The sites chosen varied along a North-South latitude, longitude, mean annual precipitation (MAP) and mean annual temperature (MAT) gradient.
Daily river metabolism using oxygen flux at 75 sites in Mongolia or the United States in steppe ecoregions
We obtained GIS data to indicate local geomorphology and watershed-scale values for land use, climate, slope, and elevation for each sampling site. We selected our sites using the GIS-based program RESonate (Williams et al., 2013) to represent replicates in multiple watersheds of different geomorphic patches or Functional Process Zones (FPZs). The FPZs are reoccurring longitudinal geomorphic patches that are hypothesized to control biocomplexity, including community composition and system productivity (Thorp et al., 2006). A detailed description of the FPZ delineation methodology we employed has been provided previously (Maasri et al., 2019a; Erdenee et al., 2021). We classified each study site hierarchically by country, ecoregion, river basin, upper (streams higher in the watershed) or lower (low slope rivers of lower elevations), and relatively constrained valley or wide valley. This approach allowed us to assess reach-scale properties that could directly influence the physiological controls most often collected alongside metabolism data. This provided a framework to evaluate how we may understand the determinants of metabolism at multiple scales. We studied three large-scale temperate steppe ecoregions (Terminal Basin, TB; Montane Steppe, MS; and Grassland Steppe, GS) as characterized by Olson et al. (2001) and updated by Dinerstein et al. (2017) in two countries (Mongolia and the United States, Fig. 2). We aggregated our large-scale ecoregions for the US as follows: TB = Great Basin shrub steppe and Sierra Nevada forest, MS = South Central Rockies forest and Wyoming Basin shrub steppe, GS = Nebraska Sand Hills mixed grasslands and Northern Shortgrass prairie. We aggregated our large-scale ecoregions for Mongolia as follows: TB = Altai mountains forest and forest steppe, Gobi Lakes Valley desert steppe, Great Lakes Basin desert steppe, and Khangai Mountains alpine meadows, MS = Selenge-Orkhon forest steppe and Syan Mountains conifer forests, GS = Daurian Forest s
Stanislaus River Steelhead Life Cycle Monitoring Program
The Stanislaus River Steelhead Life Cycle Monitoring Program is an ongoing survey starting in 2021 that aims to estimate the amount of steelhead (Onocorhynchus mykiss) present in the Stanislaus River by recording steelhead and redds observed. In addition to estimating the amount of steelhead, the survey aims to collect data relevant to steelhead spawning, documenting environmental conditions such as temperature and flow, and recording other fish activity present.
Monitoring adult Chinook salmon upstream passage on Yuba River
Adult salmonid data on the Yuba River is collected and managed by the Yuba Water Agency and the California Department of Water Resources. Upstream passage data is collected year-round at Daguerre Point Dam, 24 hours a day and 7 days a week. Data from this monitoring is modeled by Brian Poxon and Paul Bratovich to produce estimates of adult escapement (upstream passage) abundance. These data will also be used to inform the development of a juvenile production estimate (JPE) for spring-run Chinook salmon in the Sacramento River Watershed.
Gas exchange velocities (k600), gas exchange rates (K600), and hydraulic geometries for streams and rivers derived from the NEON Reaeration field and lab collection data product (DP1.20190.001)
This dataset contains estimates of gas exchange velocity, gas exchange rate, and hydraulic parameters for streams calculated from tracer-gas experiments and conservative tracer injections collected by the National Ecological Observatory Network (NEON). All input data were collected by NEON and is available on the NEON data portal at https://data.neonscience.org. Specifically, the NEON Reaeration field and lab collection data product (DP1.20190.001) was used to calculate these estimates. Gas exchange was estimated in two ways: first, following an unpooled frequentist approach and second, following a partially pooled Bayesian approach. In addition, a salt-correction was applied to gas exchange estimates for sites where it was possible and necessary. All estimates of gas exchange are included in the file gasExchange_ds.csv. A recommended selection of these estimates is included in the dataset (best_k600_mPerDay and best_K600_mPerDay). The stanfit objects used for the partially pooled Bayesian approach are also included as site-specific model objects for gas exchange velocities and rates. In addition, water velocity was calculated from conservative tracer injections, and mean water depth was calculated from these water velocity estimates and measurements of wetted width and water discharge. All hydraulic parameters are included in the file hydraulics_ds.csv. All processing code is available in the reaRates R package. NEON is sponsored by the National Science Foundation (NSF) and operated under cooperative agreement by Battelle. This material is based in part upon work supported by NSF through the NEON Program.
New Hampshire Soil Sensor Network: Soil CO2 Fluxes
The goal of the New Hampshire Soil Sensor Network is to examine spatial and temporal changes in soil properties and processes as the climate changes. Data collected can also calibrate and validate models that examine how ecosystems may respond to changing climate and land use. To determine how soil processes are affected by climate change and land management, this soil sensor network measures snow depth, air temperature, soil temperature, soil volumetric water content, and soil electrical conductivity, as well as soil CO2 fluxes. This data package includes air temperature, soil temperature at 5 cm, and soil volumetric water content at 5 cm, and soil CO2 flux at the time of sampling, as well as gap-filled soil CO2 fluxes using non-linear least squares regression. Data were collected at the following sites: BRT = Bartlett Experimental Forest, Bartlett, NH; BDF = Burley-Demmerit Farm, Lee, NH; DCF = Dowst Cate Forest, Deerfield, NH; HUB = Hubbard Brook Experimental Forest, Woodstock, NH; SBM = Saddleback Mountain, Deerfield, NH; THF = Thompson Farm, Durham, NH; and Trout Pond Brook, Strafford, NH.
Future hourly wet-bulb globe temperature dataset for 842 cities in Japan
We provide projected hourly wet-bulb globe temperature (WBGT) data for 842 cities in Japan for April to October in the period 2030-2100. The projection is generated by applying prediction models built by learning the relationship between historical hourly WBGT and the daily weather indices using a machine learning method called eXtreme Gradient Boosting, to a future climate scenario data for Japan area called NIES2020. Projection data for the historical period 1980-2014 are also available.
Daily rainfall series and rainfall erosivity in Mexico for three climatic normals (1968-1997, 1978-2007, and 1988-2017)
As in many countries around the world, there are some issues in the Mexican rainfall series, such as missing values, short measurement periods, and series homogeneity (breaks due to station relocation and measurement mistakes), which further compound the challenge of using climate data. Furthermore, it is necessary to develop a complete and helpful rainfall series database by following an imputing and homogenization process of the rainfall series. This research has compiled and systematized a national dataset with daily rainfall and rainfall erosivity for three climatic normals CN (1968-1997, 1978-2007, and 1988-2017). We have used the "climatol" package to fill the data. After, we calculated daily rainfall erosivity using a power law model. As a result, we obtained 1370, 1679, and 1683 rainfall series for the CNs 1968-1997, 1978-2007, and 1988-2017, respectively. The median values of the rainfall erosivity for the three CNs were 3245, 3070, and 3327 MJ mm/ ha h yr, respectively. We are making this database available for public consultation for researchers and students, technical assistants, decision-makers, and others interested in environmental studies in Mexico.
Distribution and habitat use of juvenile Feather River salmonids: 25 years and ongoing of snorkel surveys
Since 1999, the California Department of Water Resources (DWR) has conducted annual snorkel surveys to monitor juvenile salmon on the Feather River. The objective of this data collection effort is to determine the relative abundance and distribution of rearing juvenile Chinook salmon and steelhead. A secondary objective is to collect baseline data for future monitoring programs associated with habitat restoration projects. Crews survey units within 20 sampling sections on the high flow (HFC) and low flow channel (LFC) between January and September and collect information on species, fish size, substrate, cover, and habitat type. This dataset represents an extensive time series that could be used to identify habitat conditions where juvenile Chinook salmon and steelhead occur and how these conditions have changed over time. These data were published to support the Healthy Rivers and Landscapes Program.
White Cedar Ring Width Data from Michigan Upper Peninsula, 1869-2022
This project used tree cores to reconstruct growth over time and correlate that with climate variables including maximum monthly temperature, monthly precipitation, and vapor pressure deficit.
Water Monitoring of the Choptank River and Pocomoke River, Maryland, USA
Water monitoring at four locations on the Choptank River and four locations on the Pocomoke River in Maryland, U.S.A., was conducted from 2021 through 2023. Funding and scientific rationale were provided by the National Science Foundation grant 2049073 (“Resolving Sediment Connectivity between Rivers and Estuaries by Tracking Particles with their Microbial Genetic Signature”). The monitoring locations were chosen to measure estuary dynamics from the tidal freshwater zone through the mesohaline estuary. Parameters measured included water temperature, water level, water conductivity (reported as specific conductivity), water turbidity, and water velocity.
Monitoring juvenile Chinook salmon outmigration using rotary screw traps on Deer and Mill creeks 2023 to present
The California Department of Fish and Wildlife (CDFW) conducts juvenile salmonid emigration monitoring on Mill and Deer Creek (Tehama County, CA) annually from October through June using rotary screw traps (RSTs). Data from this monitoring is used to estimate juvenile spring-run Chinook salmon (Oncorhynchus tshawytscha) (spring-run) abundance and passage, identify yearling outmigration timing and alert resource agencies of juvenile spring-run presence in the lower Sacramento-San Joaquin Delta. This data will be included in the development of a juvenile production estimate (JPE) for spring-run Chinook salmon in the Sacramento River as required by Condition of Approval 7.5.2 of Incidental Take Permit No. 2081-2019-006-00 (ITP) issued by CDFW to California Department of Water Resources (DWR) for the long-term operation of the State Water Project. Salmonid data collected from the Mill and Deer RSTs, among other datasets, is also used by the Salmon Monitoring Team (SaMT) to understand the movement of juvenile salmon in the Sacramento River Watershed to estimate the number of winter-run and spring-run Chinook salmon that have entered the Sacramento-San Joaquin Delta (Delta). SaMT is a real-time operations monitoring team required by Condition of Approval 8.1.2 of the ITP which meets weekly from October through June, to provide advice for real-time management of SWP operations to DWR, CDFW, and the Water Operation Management Team (WOMT) to minimize take of winter-run and spring-run Chinook salmon in the Delta. This data package is complimentary to edi.1504 and represents current RST monitoring on Deer and Mill creeks. Data within the current year’s monitoring season are considered provisional.
IISD Experimental Lakes Area: Ice Phenology and Thickness, 1969-2025 (partial start/end years).
The IISD Experimental Lakes Area (IISD-ELA) Ice Phenology and Thickness data package provides two types of ice data from multiple lakes in northwestern Ontario, Canada. Ice phenology is the timing of when lakes freeze over in the fall and thaw out in the spring, as an ice-on and ice-off date each year, and the days of ice duration for each winter. Ice thickness data includes total ice thickness as well as the complex breakdown of individual layers (snow, slush, white ice, black ice). This data package includes both tabular data and metadata files for each type of ice data. The ice phenology table consists of a row for each ice-on date, ice-off date, and ice duration period for each lake, including the associated sampling method and any comments. The ice thickness table has a row for each measurement of a frozen lake on a specific date, including the total ice thickness and the thickness of individual layers as column values for each row. Metadata in this data package include a table of location coordinates and record counts, and an information sheet for ice phenology and one for ice thickness. The table of coordinates and counts is useful to know where the lakes and specific sampling sites are located and as an overview of data availability per lake (Lake 239 has the longest and most consistent data record, for both ice phenology and thickness). The two info sheets provide additional metadata details about the datasets, including background and uses of the datasets, a data dictionary, diagrams, lookup tables, descriptions of methods, and additional references. For data about lake depth, size, and volume, please consult the most recent version of our bathymetry data package: https://portal.edirepository.org/nis/revisionbrowse?scope=edi&identifier=1276 This data package is ongoing—updates will be provided as data are collected from these lakes in subsequent years. If data are not present for a lake you are interested in from IISD-ELA, please get in touch with us. The
Population persistence, phenotypic divergence and metabolic adaptation in yarrow (Achillea millefolium L.) along a climate gradient, CA, 1920 to 2023
This dataset provides insights into the persistence and adaptation of yarrow (Achillea millefolium L.) populations over a 100-year period of climate change. The data include plant height measurements and climatic variables (temperature and precipitation) from historical and resurveyed sites spanning a broad environmental gradient (1–3,200 m a.s.l.), alongside metabolic profiles obtained from a common-garden experiment. The dataset captures phenotypic changes in plant growth, metabolic diversity, and site-specific climatic shifts between 1920 and 2020. These data support analyses of how temperature and precipitation interact to shape plant responses over time and allow for exploring patterns of local adaptation in phenotypic and metabolic traits. This comprehensive dataset is valuable for understanding the ecological and evolutionary mechanisms underlying population persistence and can inform conservation strategies under future climate scenarios.
Species-level estimated abundances and zero counts of nighttime collected female mosquitoes 2014 - 2022 (Derived from NEON Mosquitoes sampled from CO2 traps (DP1.10043.001, RELEASE-2024))
This Level 2 data package contains species level estimated abundances, including zero counts, and estimated mean number of female mosquitoes per trap derived from the NEON Mosquitoes sampled from CO2 traps (DP1.10043.001), RELEASE-2024 Level 0 data (https://doi.org/10.48443/3cyq-6v47). The data set includes mosquito records of traps collecting mosquito samples at night, for up to 24 trap hours, across a total of 20 terrestrial core and 27 terrestrial gradient sites from 2014 to 2022. To ensure high confidence in abundance estimates, records were only included when at least 90% of collected individuals were identified to sex, and 90% of female specimens were identified to species. Information across multiple QC/QA fields within the NEON mosquito data was evaluated to identify and exclude records where confidence in estimated abundances may have been compromised. Species level zero counts were added for all species collected at least once within the sampling year and trap location. Additionally, species level zero counts were included for trap events where only male mosquitoes had been collected or where QC/QA remarks indicated traps were inactive due to cold temperatures. The data set provides an analysis ready time series of estimated abundances across NEON sites and plots. An R Markdown file that contains descriptions of the QC/QA and data filtering steps along with annotated code, as well as data tables used to filter active and inactive trap events based on QC/QA fields, are published with the data package. Any questions about this data package should be directed to Amely Bauer listed under contacts.
Rates and controls of nitrogen fixation in post-fire lodgepole pine forests, Greater Yellowstone Ecosystem, 2022
This dataset contains all the contents needed to reproduce the calculations and analyses done in the original paper associated with this dataset (Heumann et al. 2025 Ecology). The primary method used in this study was the Acetylene Reduction Assay (ARA) which measures the rate at which acetylene is reduced to ethylene in nitrogen-fixing organisms as a proxy for nitrogen fixation activity. We measured acetylene reduction rates in multiple cryptic niches (i.e., lichen, moss, pine litter, dead wood and mineral soil) in 34-year-old lodgepole pine stands in the Greater Yellowstone Ecosystem to explore the rates, temporal patterns, and climate controls on cryptic N fixation. Thus the foundation of this dataset is ethylene production rate measurements. All the data tables in this dataset contain either measured ethylene production rates or estimates of N fixation scaled from those ethylene production rates. Included with this are various physical measurements (e.g. dry mass, moisture content, incubation temperatures) that we included in our analyses in order to either scale up rates of N fixation using biomass estimates from field sites or explore temperature and moisture relationships with nitrogen fixation activity under controlled conditions. Included with this dataset are three R studio scripts used to run the calculations and analyses reported in the manuscript publication from this study.
IISD Experimental Lakes Area: Chemistry of LTER Lakes, 1968-2024
The IISD Experimental Lakes Area (IISD-ELA) Chemistry of LTER Lakes data package provides lake chemistry data from five reference lakes in northwestern Ontario, Canada for the years 1968-2024. This data package includes both tabular data and metadata files. The chemistry data includes the analysis of physical, nutrient, biological, inorganic, and organic parameters for long-term ecological research across lakes 114, 224, 239, 373, and 442. The dataset contains a row for each parameter measured at a specific date, lake, and depth (integrated layer or profile level). Metadata in this data package include a table of location coordinates and record counts and a PDF information sheet. The table of coordinates and counts is useful to know where the lakes and specific sampling sites are located and as an overview of data availability per lake (Lake 239 has the longest and most consistent data record). The info sheet provides additional metadata details about the dataset, including background and uses of the datasets, a data dictionary, diagrams, descriptions of methods and instruments, and additional references. The info sheet also contains a table that lists chemical parameter names and metadata used in this EDI repository alongside their equivalencies in the DataStream repository to help understand differences in naming conventions between the two parallel repository data packages. This data package is ongoing—updates will be provided as data are collected from these lakes in subsequent years. If data are not present here for a specific IISD-ELA lake that you are interested in, please get in touch with us. The data in this chemistry data package on EDI are also published in parallel at the Lake Winnipeg DataStream repository (https://doi.org/10.25976/fq3n-8207). The differences between the two are: the formatting of data and metadata (particularly how integrated sample information is organized across columns, and the differing chemical parameter names and metadata explai
Endurance swimming performance and physiology of juvenile sturgeon at different temperatures, 2022-2024
Endurance swimming trials were conducted on both Green Sturgeon (Acipenser medirostris) and White Sturgeon (Acipenser transmontanus) across multiple size classes to assess the effects of temperature and velocity on swimming performance. Fish were exposed to various water temperatures for at least 14 days and swam at fixed-water velocities (cm/s) in controlled swim tunnels. Data were collected on parameters such as species, size class, trial temperature, velocity, recovery time, time-to-fatigue, swim type classifications, and whether the trials were completed. Additional metadata included fish morphometrics such as fork length, total length, weight, and trial dates, enabling comparisons across species, size, and treatment conditions. Physiological responses were measured post-swimming to evaluate the impacts of endurance trials on the smallest size class of Green Sturgeon (5cm fork length): - In 2022, whole-body cortisol, glucose, and lactate concentrations were measured immediately following endurance trials (0 min recovery). - In 2023, recovery dynamics were incorporated, with physiological responses assessed at multiple time points (0 min, 15 min, 30 min, and 60 min post-trial). - In 2022 and 2023 the baseline physiological metrics (whole-body cortisol, glucose, and lactate concentrations) of control fish (not subjected to swimming trials) were measured across all temperatures, years, species, and size classes. This dataset provides information on sturgeon swimming performance under varied temperature conditions, as well as the associated physiological stress responses, offering valuable insights into their endurance capabilities and recovery processes. The findings can inform conservation strategies, habitat management, and aquaculture practices for these ecologically and economically important species.
State Water Project, Genetic Determination of Population of Origin 2011-2024
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
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.