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22,549 results for “AND LTER”
SBC LTER: Effect of algal diet on consumption, growth, and gonad weight of the purple sea urchin (Strongylocentrotus pupuratus)
Data are for an experiment evaluating the effects of algal diet on consumption, growth, and gonad weight of an important kelp forest grazer, the purple sea urchin, Strongylocentrotus pupuratus over a 13 week period (November 2010 - February 2011). Four co-occurring species of macroalgae known to be part of its diet were offered: two kelps Macrocystis pyrifera and Pterygophora californica, and the red algae Chondracanthus corymbiferus and Rhodymenia californica. During 9 consectutive trials in a controlled laboratory setting, we measured consumption, test (exoskeleton) growth, jaw growth, change in whole body wet weight and gonad weight of urchins fed one of five experimental diets. The algae chosen represent a large proportion (> 75%) of the algal biomass in Santa Barbara Channel reefs (California, USA). Changes in the availability of these four species of macroalgae could have large implications for the performance of purple sea urchins and consequently, for the structure of subtidal reef communities. These data are presented in a paper describing the effects of five southern California macroalgal diets on the consumption, growth and gonad weight of the purple sea urchin: Matthew C. Foster, M., Byrnes, J. E. K., D. C. Reed. 2015. Effects of five southern California macroalgal diets on consumption, growth and gonad weight in the purple sea urchin, Strongylocentrotus purpuratus. PeerJ. DOI: 10.7717/peerj.719
SBC LTER: Kelp blade characteristics to support turnover dynamics of giant kelp, Macrocystis pyrifera in the Santa Barbara Channel
These data describe the age-specific changes in the size and related traits of giant kelp (Macrocystis pyrifera) blades in the Santa Barbara Channel (Isla Vista Reef) during the spring and summer of 2012-2013. Data are contained in three tables: 1) a time series of change in blade size with age due to growth and senescence for blades growing at different depths and locations in the kelp forest, 2) physical traits of blades (biomass density, nitrogen, chlorophyll a) of different ages collected at different depths and locations in the kelp forest, and 3) photosynthetic performance (Pmax, alpha) of blades of different ages collected at different depths and locations in the kelp forest. These data were used to test whether spatial variation in the turnover dynamics of giant kelp blades could be could be explained by leaf life span theory developed for higher plants. The data were also used in a mathematical model of frond growth and senescence to investigate the relative and absolute magnitude of blade senescence in a kelp forest, and to examine how these losses were affected by light availability. Analyses using these data were published in Rodriguez, G. E. 2014. Turnover dynamics of the giant kelp, Macrocystis pyrifera. Ph.D., University of California, Santa Barbara. ProQuest, UMI Dissertations Publishing, 2014. 3682967.
SBC LTER: Pore water constituents and residence times (Radon activity) from Santa Barbara beaches, 2012-2013
Constituents of beach pore water and parameters for calculating residence times are reported for two beaches in the Santa Barbara area, Isla Vista Beach and East Campus Beach, from July 2012 to June 2013. This dataset reports beach pore water concentrations of ammonium and nitrate, total dissolved Nitrogen and Carbon, particulate Nitrogen and Carbon, Radon, salinity, conductance, Oxygen and water temperature. Residence time ("Tau") can be calculated from Radon-222 activities in nearshore seawater, in pore water and at equilibrium, which are presented in a second table (also available in published paper). Results from these data were reported in: Goodridge, B. M. and J. M. Melack. 2014. Temporal evolution and variability of dissolved inorganic nitrogen in beach pore water revealed using radon residence times. Environmental Science and Technology, 48: 14211-14218. DOI:10.1021/es504017j
SEV-LTER Mean Variance Experiment Desert Shrubland Soil Moisture and Temperature
We designed novel field experimental infrastructure to resolve the relative importance of changes in the climate mean and variance in regulating the structure and function of dryland populations, communities, and ecosystem processes. The Mean x Variance Experiment (MVE) adds three novel elements to prior designs (Gherardi & Sala 2013) that have manipulated interannual variance in climate in the field by (i) determining interactive effects of mean and variance with a factorial design that crosses a drier mean with increased (more) variance, (ii) studying multiple dryland ecosystem types to compare their susceptibility to transition under interactive climate drivers, and (iii) adding stochasticity to our treatments to permit the antecedent effects that occur under natural climate variability. This new infrastructure enables direct experimental tests of the hypothesis that interactions between the mean and variance of precipitation will have larger ecological impacts than either the mean or variance in precipitation alone. A subset of plots have soil moisture and temperature sensors to evaluate treatment effectiveness by addressing, How do MVE manipulations alter the mean and variance in soil moisture and temperature? And, how does micro-environmental variation among plots influence how much MVE treatments alter soil moisture profiles over three soil depths? This data package includes soil moisture and temperature sensor data from the Mean x Variance Climate experiment in the Desert Shrubland ecosystem at the Sevilleta National Wildlife Refuge, Socorro, NM.
SEV-LTER Mean Variance Experiment Juniper Savanna Soil Moisture and Temperature
We designed novel field experimental infrastructure to resolve the relative importance of changes in the climate mean and variance in regulating the structure and function of dryland populations, communities, and ecosystem processes. The Mean x Variance Experiment (MVE) adds three novel elements to prior designs (Gherardi & Sala 2013) that have manipulated interannual variance in climate in the field by (i) determining interactive effects of mean and variance with a factorial design that crosses a drier mean with increased (more) variance, (ii) studying multiple dryland ecosystem types to compare their susceptibility to transition under interactive climate drivers, and (iii) adding stochasticity to our treatments to permit the antecedent effects that occur under natural climate variability. This new infrastructure enables direct experimental tests of the hypothesis that interactions between the mean and variance of precipitation will have larger ecological impacts than either the mean or variance in precipitation alone. A subset of plots have soil moisture and temperature sensors to evaluate treatment effectiveness by addressing, How do MVE manipulations alter the mean and variance in soil moisture and temperature? And, how does micro-environmental variation among plots influence how much MVE treatments alter soil moisture profiles over three soil depths? This data package includes soil moisture and temperature sensor data from the Mean x Variance Climate experiment in the Juniper Savanna ecosystem at the Sevilleta National Wildlife Refuge, Socorro, NM.
SEV-LTER Mean - Variance Experiment Quadrat Plant Species Cover and Height
We designed novel field experimental infrastructure to resolve the relative importance of changes in the climate mean and variance in regulating the structure and function of dryland populations, communities, and ecosystem processes. The Mean - Variance Climate Experiment (MVE) adds three novel elements to prior designs that have manipulated interannual variance in climate in the field (Gherardi & Sala, 2013) by (i) determining interactive effects of mean and variance with a factorial design that crosses reduced mean with increased variance, (ii) studying multiple dryland biomes to compare their susceptibility to transition under interactive climate drivers, and (iii) adding stochasticity to our treatments to permit the antecedent effects that occur under natural climate variability. This new infrastructure enables direct experimental tests of the hypothesis that interactions between the mean and variance of precipitation will have larger ecological impacts than either the mean or variance in precipitation alone. This dataset includes plant species cover and height data measured in 1 m x 1 m quadrats at all Mean - Variance experiment sites. Quadrat locations span five important ecosystems of the American southwest: blue grama-dominated Plains grassland (est. fall 2019), black grama-dominated Chihuahuan Desert grassland (est. fall 2020), creosotebush dominated Chihuahuan Desert shrubland (est. fall 2021), juniper savanna (est. fall 2022) and pinon-juniper woodland (est. fall 2023). Data on plant cover and height for each plant species are collected per individual plant or patch (for clonal plants) within 1 m x 1 m quadrats. These data inform population dynamics of foundational and rare plant species. The cover and height of individual plants or patches are sampled twice yearly (spring and fall) in permanent 1m x 1m plots within each site or experiment. This data package includes plant cover and height only -- for species biomass estimates per quad see package knb-lte
SEV-LTER Mean - Variance Experiment Seasonal Biomass Data at the Sevilleta National Wildlife Refuge, New Mexico
We designed novel field experimental infrastructure to resolve the relative importance of changes in the climate mean and variance in regulating the structure and function of dryland populations, communities, and ecosystem processes. The Mean - Variance Climate Experiment (MVE) adds three novel elements to prior designs that have manipulated interannual variance in climate in the field (Gherardi & Sala, 2013) by (i) determining interactive effects of mean and variance with a factorial design that crosses reduced mean with increased variance, (ii) studying multiple dryland biomes to compare their susceptibility to transition under interactive climate drivers, and (iii) adding stochasticity to our treatments to permit the antecedent effects that occur under natural climate variability. This new infrastructure enables direct experimental tests of the hypothesis that interactions between the mean and variance of precipitation will have larger ecological impacts than either the mean or variance in precipitation alone. This data package includes species-level plant cover and biomass data from the Mean - Variance Experiment at five sites comprising the major ecosystems of the Sevilleta National Wildlife Refuge: Chihuahuan Desert shrubland, Chihuahuan Desert grassland, Great Plains grassland, Juniper savanna, and pinon-juniper woodland. Species cover and volume in one-meter-squared quadrats are assessed twice-yearly in spring and fall, and regressions correlating biomass and volume constructed using seasonal harvest weights from SEV157, "Net Primary Productivity (NPP) Weight Data."
SEV-LTER Mean x Variance Experiment Pinon Juniper Soil Moisture and Temperature
We designed novel field experimental infrastructure to resolve the relative importance of changes in the climate mean and variance in regulating the structure and function of dryland populations, communities, and ecosystem processes. The Mean x Variance Experiment (MVE) adds three novel elements to prior designs (Gherardi & Sala 2013) that have manipulated interannual variance in climate in the field by (i) determining interactive effects of mean and variance with a factorial design that crosses a drier mean with increased (more) variance, (ii) studying multiple dryland ecosystem types to compare their susceptibility to transition under interactive climate drivers, and (iii) adding stochasticity to our treatments to permit the antecedent effects that occur under natural climate variability. This new infrastructure enables direct experimental tests of the hypothesis that interactions between the mean and variance of precipitation will have larger ecological impacts than either the mean or variance in precipitation alone. A subset of plots have soil moisture and temperature sensors to evaluate treatment effectiveness by addressing, How do MVE manipulations alter the mean and variance in soil moisture and temperature? And, how does micro-environmental variation among plots influence how much MVE treatments alter soil moisture profiles over three soil depths? This data package includes soil moisture and temperature sensor data from the Mean x Variance Climate experiment in the Pinon Juniper ecosystem at the Sevilleta National Wildlife Refuge, Socorro, NM.
SEV LTER: Tracking Vegetation Phenology Using PhenoCam Imagery at the Sevilleta National Wildlife Refuge, New Mexico, 2014-2024
As of 03/03/2024, the Sevilleta Long-Term Ecological Research Program is equipped with a total of 65 digital RGB cameras, or PhenoCams, across the Sevilleta National Wildlife Refuge. These cameras are installed on eddy covariance flux towers and at a number of precipitation manipulation experiments to track vegetation phenology and productivity across dryland ecotones. PhenoCams have been paired with eddy covariance flux tower data at the site since 2014, while some Mean-Variance Experiment PhenoCams were installed as recently as June 2023. For information on PhenoCam data processing and formatting, see Richardson et al., 2018, Scientific Data (https://doi.org/10.1038/sdata.2018.28), Seyednasrollah et al., 2019, Scientific Data (https://doi.org/10.1038/s41597-019-0229-9), and the PhenoCam Network web page (https://phenocam.nau.edu/webcam/). The PhenoCam Network uses imagery from digital cameras to track vegetation phenology and seasonal changes in vegetation activity in diverse ecosystems across North America and around the world. Imagery is uploaded to the PhenoCam server hosted at Northern Arizona University, where it is made publicly available in near-real time, every 30 minutes from sunrise to sunset, 365 days a year. The data are processed using simple image analysis tools to yield a measure of canopy greenness, from which phenological metrics are extracted, characterizing the start and end of the growing season. These transition dates have been shown to align well with on-the-ground observations at various research sites. Long-term PhenoCam data can be used to track the impact of climate variability and change on the rhythm of the seasons.
Virgina Coast Reserve LTER Externally-hosted Models and Data
This dataset contains a listing of models and data associated with Virginia Coast Reserve Long-Term Ecological Research that are not otherwise available in the VCR/LTER data archive. It includes links to models and data that have been made available by researchers that are not in the VCR/LTER archive because they are deposited in a specialized system specifically tailored to a specific type (e.g. models) or in another archive due to requirements and constraints imposed by funders and journals. It takes the form of a spreadsheet including for each item the type (i.e., model or data), Internet link, name, brief description and optionally a link to a publication that used the data.
LTER-Italy site Lago Maggiore figure
<p>Geographical representation of the LTER-Italy site Lago Maggiore - DEIMS-ID <a href="https://deims.org/f30007c4-8a6e-4f11-ab87-569db54638fe">https://deims.org/f30007c4-8a6e-4f11-ab87-569db54638fe</a></p>
Water chemistry of LTER-Europe research site Lake Paione Inferiore LTER_EU_IT_088 (1984-2013)
<p>This dataset provides information about water chemical parameters for Lake Paione Inferiore LTER_EU_IT_088: pH, Total alkalinity, conductivity, total nitrogen, major cations (calcium, magnesium, sodium, potassium), major anions (sulphate, nitrate, chloride) and silica for the period 1984-2013.</p> <p>Lake Paione Inferiore (LPI) is a high altitude Alpine lake, located at 2002 m a.s.l. in the Bognanco Valley, Province of Verbania, Piedmont Region, Italy. It has a surface area of 0.86 ha and a maximum depth of 13.5 m. The Lake, together with Lake Paione Superiore (LPS), is included in the monitoring sites of the UN-ECE Program ICP WATERS (International Cooperative Programme on Assessment and Monitoring of Acidification of Rivers and Lakes) for which the CNR Water Research Institute is the National Focal Centre for Italy.</p> <p>This dataset includes the following files: Metadata LTER_EU_IT_088.xls and per each parameter one xls file with data records. Dataset for water chemistry of LPI for the period 2014-2020 is available at <a href="https://doi.org/10.5281/zenodo.10519349">https://doi.org/10.5281/zenodo.10519349</a></p> <p>Detailed description of the site LPI is available at https://deims.org/c128d2f9-beb0-45ba-89bb-df9e12f95b0f</p>
Salinity, Turbidity, Wind from the S1-GB pylon at the LTER site Delta del Po and Costa Romagnola (2012-2021)
<p>The present database comprises observations spanning from 2012 to 2021, focusing on abiotic parameters collected from the S1-GB dynamic pylon, in the Northern Adriatic Sea (around 7 miles offshore within the Po Delta on a bottom depth of 22.5 m), Italy. Specifically, it encompasses measurements on atmospheric parameters above the water surface and measurements at a defined depth (https://vocab.nerc.ac.uk/collection/P01/current/ADEPZZ01/) of salinity (URI: https://vocab.nerc.ac.uk/collection/OD1/current/SAL/) in PSU (Practical Salinity Units), turbidity (URI: http://vocab.nerc.ac.uk/collection/P25/current/TURB/) in NTU (Nephelometric Turbidity Units; http://vocab.nerc.ac.uk/collection/P06/current/USTU/), wind speed (URI: http://vocab.nerc.ac.uk/collection/P25/current/WINDS/) in m/s (meters per second; http://vocab.nerc.ac.uk/collection/P06/current/PMPS/), and wind from direction (URI: http://vocab.nerc.ac.uk/standard_name/wind_from_direction/) in degrees (angular degrees, 0 represents the true north; http://vocab.nerc.ac.uk/collection/P06/current/UAAA/). The S1-GB pylon is situated at 44,74° N; 12,45° E (WGS-84 coordinate system) and is managed by the Institute of Marine Science of the National Research Council (ISMAR-CNR) in Bologna. The dataset relies on a Comma Separated Values (CSV) file and it is composed by 82391 records offering an invaluable insight into the dynamic characteristics of the marine environment over nearly a decade. The S1-GB pylon is part of the site “Delta del Po and Costa Romagnola”, which belongs to the Long Term Ecological Research national and international networks (LTER-Italy, LTER-Europe and ILTER) and eLTER-RI. The site contributes also to the DANUBIUS and JERICO Research Infrastructures.</p>
Salinity, Turbidity, Wind from the E1 buoy at the LTER site Delta del Po and Costa Romagnola (2012-2021)
<p>The present database comprises observations spanning from 2012 to 2021, focusing on abiotic parameters collected from the E1 meteo-oceanographic buoy in the Northern Adriatic Sea (north of Rimini city on a bottom depth of 10.5 m), Italy. Specifically, it encompasses measurements taken atmospheric parameters above the water surface and measurements at a defined nominal depth (https://vocab.nerc.ac.uk/collection/P01/current/ADEPZZ01/) of salinity (URI: https://vocab.nerc.ac.uk/collection/OD1/current/SAL/) in PSU (Practical Salinity Units), turbidity (URI: http://vocab.nerc.ac.uk/collection/P25/current/TURB/) in NTU (Nephelometric Turbidity Units; http://vocab.nerc.ac.uk/collection/P06/current/USTU/), wind speed (URI: http://vocab.nerc.ac.uk/collection/P25/current/WINDS/) in m/s (meters per second; http://vocab.nerc.ac.uk/collection/P06/current/PMPS/), and wind from direction (URI: http://vocab.nerc.ac.uk/standard_name/wind_from_direction/) in degrees (angular degrees, 0 represents the true north; http://vocab.nerc.ac.uk/collection/P06/current/UAAA/). The buoy is located at 44,14° N; 12,57° E (WGS-84 coordinate system) and is managed by the Institute of Marine Science of the National Research Council (ISMAR-CNR) in Bologna. The dataset relies on a Comma Separated Values (CSV) file and it is composed by 82391 records, offering an invaluable insight into the dynamic characteristics of the marine environment in this area over nearly a decade. The E1 buoy is part of the site “Delta del Po and Costa Romagnola”, which belongs to the Long Term Ecological Research national and international networks (LTER-Italy, LTER-Europe and ILTER) and eLTER-RI. </p>
CCE LTER P1908 Upwelling Filament Ocean Acidification Phytoplankton Iron Incubation Experiments
<p>Metatranscriptome assembly, read counts, and annotations from four sets of trace metal clean ocean acidification experimeints in the California Current Ecosystem. Experiments were conducted during August 2019 as part of the CCE LTER program. Samples were collected at the initial time point (T0), and three pCO<sub>2</sub> treatments (400, 800, and 1200 ppm) with two time points for each experiment. </p> <p>Poly-A selected mRNA was sequenced on an Illumina NovaSeq 6000 and then assembled with Trinity for each separate experiment. Proteins from the assembly were then predicted with Genemark S-T. Taxonomic annotation was performed with DIAMOND BLASTP searches against PhyloDB v1.076 and based on the Lineage Proability Index from the top hits. Functional annotation was similarly performed using KEGG with KEGG Orthology annotation based on KofamKOALA results. Read quantification was conducted with Bowtie2. </p> <p>Predicted proteins from each assembly is provided in fasta format. The read counts and annotations for each experiment are in tab-delimited files. </p>
Water chemistry of LTER-Europe research site Lake Paione Superiore LTER_EU_IT_089 (1984-2013)
<p>This dataset provides information about water chemical parameters for Lake Paione Superiore LTER_EU_IT_089: pH, Total alkalinity, conductivity, total nitrogen, major cations (calcium, magnesium, sodium, potassium), major anions (sulphate, nitrate, chloride) and silica for the period 1984-2013.</p> <p>Lake Paione Superiore (LPS) is a high altitude Alpine lake, located at 2269 m a.s.l. in the Bognanco Valley, Province of Verbania, Piedmont Region, Italy. It has a surface area of 0.68 ha and a maximum depth of 11.5 m. The Lake, together with Lake Paione Inferiore (LPI), is included in the monitoring sites of the UN-ECE Program ICP WATERS (International Cooperative Programme on Assessment and Monitoring of Acidification of Rivers and Lakes) for which the CNR Water Research Institute is the National Focal Centre for Italy.</p> <p>This dataset includes the following files: Metadata LTER_EU_IT_089.xls and per each parameter one xls file with data records.</p> <p>Detailed description of the site LPS is available at https://deims.org/7e5837a9-ee27-4e27-822a-f50e5217c313</p> <p>Dataset for water chemistry of LPS for the period 2014-2020 is available at https://doi.org/10.5281/zenodo.10519126</p>
Net primary production (NPP) and climate data from Sevilleta LTER core and control sites in desert grassland and shrubland ecosystems, 1999 - 2017
This dataset and R code were used to create the figures, tables and statistical analyses for the following publication: Rudgers, JA et al. 2018. Climate sensitivity functions and net primary production: A framework for incorporating climate mean and variability. Ecology. Data were collected by the Sevilleta LTER program, which is located in the Sevilleta National Wildlife Refuge (SNWR), New Mexico. These are long-term, continuing data sets. Data collection started in 1999 at the black grama grassland and creosote shrubland, and in 2002 for blue grama grassland. Meteorological stations started recording data as early as 1989. The study abstract from Rudgers et al. 2018 is: Understanding controls on net primary production (NPP) has been a long-standing goal in ecology. Climate is a well-known control on NPP, although the temporal differences among years within a site are often weaker than the spatial pattern of differences across sites. Climate sensitivity functions describe the relationship between an ecological response (e.g., NPP) and both the mean and variance of its climate driver (e.g., aridity index), providing a novel framework for understanding how climate trends in both mean and variance vary with NPP over time. Nonlinearities in these functions predict whether an increase in climate variance will have a positive effect (convex nonlinearity) or negative effect (concave nonlinearity) on NPP. The influence of climate variance may be particularly intense at ecosystem transition zones, if species reach physiological thresholds that create nonlinearities at these ecotones. Long-term data collected at the confluence of three dryland ecosystems in central New Mexico revealed that each ecosystem exhibited a unique climate sensitivity function that was consistent with long-term vegetation change occurring at their ecotones. Our analysis suggests that rising temperatures in drylands could alter the nonlinearities that determine the relative costs and benefits of varia
SBC LTER Darwin Core Archive: Kelp Forest Reef Fish Abundance
These data describe the abundance of reef fish as part of the Santa Barbara Coastal LTER program (SBC LTER) to track long-term patterns in kelp forest reef species abundance and diversity. The study began in 2000 in the Santa Barbara Channel, California, USA, and the time series is ongoing and updated approximately annually. Abundances of all taxa of resident kelp forest fish encountered along permanent transects are recorded at nine reef sites located along the mainland coast of the Santa Barbara Channel and at two sites on the north side of Santa Cruz Island. These sites reflect several oceanographic regimes in the channel and vary in distance from sources of terrestrial runoff. In these surveys, fish were counted in either a 40x2m benthic quadrat, or in the water parcel 0-2m off the bottom over the same area. This dataset is formatted as a Darwin Core Archive (DwC-A, occurrence core). All taxa are counted (using an open species list), and abundances are zero-filled for each taxon not encountered. This is a derived data product and less-processed data may be available. See http://sbc.lternet.edu for more information and source data, which may include additional measurements, and http://sbc.marinebon.edu for processing notes.
Long Term Ecological Research (LTER) Network Site Boundaries
This is a set of Long Term Ecological Research (LTER) site boundaries preserved as a shapefile. Note that for some sites “real” boundaries are included while others–particularly marine sites–use a simpler bounding box method. Each site is listed both with its three-letter abbreviation and its unabbreviated name. World Geodetic System 1984 (WGS84) is the coordinate reference system used (EPSG:4326). More information about any of the sites can be found on the LTER Site Profiles page on the LTER Network website (https://lternet.edu/site). This data product was made possible by the contributions of the Information Managers for the LTER sites, each of whom contributed their sites' boundaries. This version of the data includes the following changes from the prior version: - Arctic (ARC) updated - Cedar Creek (CDR) updated - Florida Coastal Everglades (FCE) updated - Harvard Forest (HFR) updated - Konza Prairie (KNZ) updated - McMurdo Dry Valleys (MCM) updated - Moorea Coral Reef (MCR) updated
North Temperate Lakes LTER: Crayfish Abundance 1981 - current (Reformatted to the ecocomDP Design Pattern)
This data package is formatted as an ecocomDP (Ecological Community Data Pattern). For more information on ecocomDP see https://github.com/EDIorg/ecocomDP. This Level 1 data package was derived from the Level 0 data package found here: https://pasta.lternet.edu/package/metadata/eml/knb-lter-ntl/3/29. The abstract below was extracted from the Level 0 data package and is included for context: Crayfish data include crayfish catch in cylindrical minnow traps baited with beef liver and occasional occurrence in other gear used to sample fish. Traps are placed at fyke net locations in nine study lakes (Allequash, Big Muskellunge, Crystal, Sparkling, Trout, Mendota, Monona, Wingra and Fish). Crayfish traps have been eliminated as gear in the Madison area lakes (Mendota, Monona, Wingra, and Fish) after 2003. Individuals are identified to species and counted. In Trout and Sparkling Lake more detailed surveys have been conducted during the summer on an ad hoc basis to track distribution and abundance of the invading species Orconectes rusticus. Additional data sets consist of pre-LTER sets (initiated in late June 1972) gathered by Capelli (Ph.D. dissertation) and Lorman (Ph.D. dissertation). Most of pre-LTER data is detailed distribution in Trout Lake, and community composition in other area lakes. Sampling Frequency: annually Number of sites: 9 Note that 2020 data does not exist due to insufficient sampling.
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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)
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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.