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1,936 results for “environmental data”
Temporal study of Santa Cruz Mountain bats using environmental DNA and acoustic data
<p>Data and R scripts for a study of niche partitioning in a bat community in California's Santa Cruz Mountains using environmental DNA and bioacoustic data collected over a roosting season.</p> <p>Associated with the publication "Temporal study of environmental DNA and acoustic data reveals coexistence of sympatric bat species in a North American ecosystem" in <em>Environmental DNA. </em></p>
Environmental and AIS data collected during the EUMarineRobots Trans-National Access activities experiments using the NATO STO-CMRE Littoral Ocean Observatory Network testbed
<p>Environmental and AIS data collected during the H2020 project EUMarineRobots Trans-National Access activities experiments using the NATO STO-CMRE Littoral Ocean Observatory Network (LOON) testbed. Environmental data consists of temperature measured across the water column; sound velocity measured close to the surface and close to the sea bottom; meteorological data at the surface (i.e., pressure, temperature, wind speed and direction, humidity and rain). The environmental dataset is complemented with Automatic Identification System (AIS) data for the ships transiting close to the LOON area (Gulf of La Spezia, Italy)</p> <p>Temperature measured across the water column in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for:<br> i) Nov 12, 19-20, 23-24 - 2020<br> ii) Dec 1-4, 14-20 - 2020<br> iii) Jan 12-13, 15, 18-24, 27-28 - 2021</p> <p><br> Meteorological data at the surface (i.e., pressure, temperature, wind speed and direction, humidity and rain) in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for:<br> i) Nov 12, 19-20, 23-24 - 2020<br> ii) Dec 1-4, 14-20 - 2020<br> iii) Jan 12-13, 15, 18-24, 27-28 - 2021</p> <p><br> Sound velocity measured close to the surface (SVP1) and close to the sea bottom (SVP2) in the LOON area (Gulf of La Spezia, Italy). The dataset includes measurements for:<br> i) Nov 12, 19-20, 23-24 - 2020<br> ii) Dec 1-4, 14-20 - 2020<br> iii) Jan 12-13, 15, 18-24, 27-28 - 2021</p> <p>SVP2 data missing for Dec 14-20 (2020) and Jan 24, 27-28 (2021).</p> <p>Automatic Identification System (AIS) data for the ships transiting close to the LOON area (Gulf of La Spezia, Italy). The dataset includes AIS data for:<br> i) Nov 12, 19-20, 23-24 - 2020<br> ii) Dec 1-4, 14-20 - 2020<br> iii) Jan 12-13, 15, 18-24, 27-28 - 2021<br> </p> <p>For reference, see: "Environmental data collected on the CMRE LOON tested during the EUMR project: dataset description", Petroccia, Roberto; Zappa, Giovanni; Cimino, Giampaolo; Grati, Alberto; Alves, João. CMRE-DA-2021-001. July 2021, available at https://www.cmre.nato.int/research/publications/latest-techreports/1638-cmre-da-2021-001</p>
Data for "Microstructural mapping of A. islandica shells reveals environmental and physiological controls on biomineral size"
<p>This data contains the image segmentation workflow, data processing procedure and all data generated for the publication "Microstructural mapping of A. islandica shells reveals environmental and physiological controls on biomineral size" currently under review.</p>
Data for: Machine learning for predicting environmental mobility based on retention behaviour
<p>This repository contains the data and supplementary information for the paper: "Machine learning for predicting environmental mobility based on retention behaviour".</p>
Data for: Luo et al., Expiratory aerosol pH: the overlooked driver of airborne virus inactivation, Environmental Science and Technology, 10.1021/acs.est.2c05777
<p><strong>Experimental data </strong></p> <p>This folder contains the experimental data to the figures shown in the main manuscript and Supporting Information.</p> <p>Figures 1 and S3 (inactivation curves for IAV, SARS-CoV-2 and HCoV-229E)</p> <p>Figure 1 (rate constants)</p> <p>Figure 2 (EDB analysis of SLF)</p> <p>Figure S1A (zetasizer analysis to measure virus aggregation)</p> <p>Figure S1B (renilla and plaque assay data for viruses exposed to pH 5, 6 and 7)</p> <p>Figure S4A (EDB analysis of different SLF samples; raw data)</p> <p>Figure S4Amean (EDB analysis of different SLF samples; mean values)</p> <p>Figure S5 (EDB analysis of nasal mucus)</p> <p>Figure S8 (EDB analysis of slow crystal growth stage of SLF and nasal mucus)</p> <p>Figure S13 and S14 (literature data on inactivation of IAV and SARS-CoV-2 in aerosol particles)</p> <p> </p> <p> </p>
The raw data of Souma, Katano, Doi et al. "Comparing environmental DNA with whole pond survey to estimate the total biomass of fish species in ponds" in Freshwater Biology
<p>The raw data of Souma, Katano, Doi, Takahara, and Minamoto. "Comparing environmental DNA with whole pond survey to estimate the total biomass of fish species in ponds" in Freshwater Biology.</p>
Raw data from: "Thermal mismatches explain consumer-resource dynamics in response to environmental warming".
<p>Data from:</p> <p>Álvarez-Codesal, S, Faillace CA, Garreau, A, Bestion, E, Synodinos, AD, & Montoya, JM. 2023. Thermal mismatches explain consumer-resource dynamics in response to environmental warming. Ecology and Evolution.<br> </p> <p>Composed of seven associated datasets:</p> <p>- Algae_Net_Photosynthesis.csv</p> <p>- Daphnia_Ingestion.csv</p> <p>- Algae_Respiration.csv</p> <p>- Daphnia_Ingestion.csv</p> <p>- Daphnia_respiration.csv</p> <p>- Interaction_Strength.csv</p> <p>- Energy_Balance_Ratios_dataset.csv</p> <p> </p> <p>A detailed explanation of the methods is provided in the related Alvarez-Codesal et al. 2023 article, please refer to it for a full understanding of the methods and results.</p> <p>Briefly: our aim was to quantify the impact of warming on consumer-resource interactions, using as consumer <em>Daphnia pulex</em>, and as resources two algae species, <em>Chlamydomonas reinhardtii</em> and <em>Desmodesmus</em> sp.</p> <p>First, we measured thermal dependencies of physiological rates related to energy gain (i.e., ingestion, net photosynthesis) and loss (i.e., respiration) for <em>Daphnia</em> and the algae in basal conditions at eight temperatures. From these, we calculated species energetic balances as net photosynthesis-to-respiration ratio (P/R<sub>r</sub>) for resources, or as ingestion-to-respiration ratio (I/R<sub>c</sub>) for consumers, using predicted values of each (per capita) rate from the models. We used energetic balances as an indicator of how species respond to increasing temperatures, defining intraspecific energetic mismatches when the energetic balance decreases.</p> <p>Second, we inferred interspecific thermal mismatches (inter-TM) by comparing individual energetic balances for both consumer-resource pairs, and identified the thermal mismatch regions, where: 1) trends of energetic balances contrast between the interacting species; and 2) both species reduce their energetic balance with increasing temperature. The inter-TMs were used to increase our qualitative understanding on the outcomes of thermal dependencies of interaction strength.</p> <p>Third, we calculated the natural logarithm of the consumer-resource energetic balance for each interacting pair as the ratio between consumer energetic balance and the resource energetic balance to get qualitative predictions on the trends of interaction strength with temperature.</p> <p>Finally, we measured experimentally thermal dependencies of interaction strength for each consumer-resource pair and verified if our predictions using the thermal mismatches fitted the trends of interaction strengths across temperatures.</p>
Code and data for manuscript: Incorporating environmental heterogeneity and observation effort to predict host distribution and viral spillover from a bat reservoir.
<p>This is the source code and data required to reproduce data analysis and figures from the manuscript, "Incorporating environmental heterogeneity and observation effort to predict host distribution and viral spillover from a bat reservoir". </p>
Data on specialist and generalist herbivory, environmental variation, and phytochemical similarity from the Atlantic Rainforest of Brazil: 2013-2014
What: These are data on specialist and generalist herbivory from naturally occurring Piper plants as well as environmental data collected in 10 m diameter plots across sites in the Atlantic Rainforest of Brazil. Data also include chemical similarity calculated as the Morisita similarity index for species in a given plot and chemical modules that demonstrate classes of compounds that group together and influence herbivory. Why: Data were collected to understand factors that influence herbivory and tropical forest richness with a particular focus on secondary chemistry metabolomics. Where: Field sites include São Bento de Sapucaí (-22.8758, -45.8581), Parque Nacional de Itatiaia (-22.3698, -44.6285), Parque Estadual de Intervales (-24.3088, -48.2736), and Parque Estadual de Serra do Mar - Núcleo Pincinguaba (-23.6200, -46.7222). When: Data were collected in the field from Dec 2013 – May 2014. How: Field data were collected in 10 m diameter plots centered on randomly located Piper plants. Chemical data come from 1H-NMR metabolomics.
Environmental and taxonomic data along the Thames River - Lake St. Clair continuum in Ontario, August 2020 to September 2023.
Data for this research were collected from water samples obtained along the Thames River- Lake St. Clair continuum to determine differences in water quality and biodiversity between river and lake sites. Sampling began in Lake St. Clair in August of 2020 in Stoney Point Ontario. Samples were taken from the intake well of the water treatment plant. The intake pipe is located approximately 1km off-shore, at a depth of 1.9m. To address spatial differences, a second site was added in Lake St. Clair in Belle River, Ontario and a river site was added in Chatham, Ontario. Belle River samples were collected from the intake well at the water treatment plant, with the intake pipe located approximately 1km off-shore and at a depth of 3.1m. Chatham samples were collected from the surface of the Thames River as grab samples. Samples from both locations were collected weekly to monthly throughout June to October, 2021. To further increase spatial resolution, samples were collected from the mouth of the Thames River in Lighthouse Cove, Ontario, from June to October 2022, and from this site and another river site in Prairie Siding, Ontario, from June to October 2023. They were collected as grab samples from the surface of the water. Each site was sampled weekly to monthly.
Lake ice surveys, 1874-2022, Adirondack Long-Term Ecological Monitoring Program Project No. 8 by Adirondack Ecological Center of the State University of New York College of Environmental Science and Forestry, Newcomb, New York. Environmental Data Initiative.
The objective of this dataset is to document ice-in and ice-out dates on several lakes on the State University of New York College of Environmental Science and Forestry's Huntington Wildlife Forest (HWF). Lakes include: Arbutus, Catlin, Deer, Military, Rich, Wolf and Lodo Pond; some records exist for Long Pond and other water bodies but they are not included here except in some comment fields.
Return on Investment Metrics for Data Repositories in Earth and Environmental Sciences
Despite a growing recognition of the importance of data to the economy and to science, investment in repositories to manage and disseminate that data in easily accessible and understandable ways is scarce. Keeping repository services active and up-to-date for a long time period is difficult due to this funding situation. As a result, repositories must continually provide proof of their value, their Return on Investment (ROI) to their sponsors; yet doing so has always been difficult, problematic and not always successful. In this work, an analysis of approaches for assessing the ROI of several scientific data repositories has identified various techniques that repositories use to report on the impact and value of their data products and services. A survey of selected repositories rated the set of metrics identified and rated each by its importance as well as the ease with which the metric could be measured. The discussion is broken down into considerations for calculating costs, perceived value of repositories and suggested metrics that would allow a repository to calculate an ROI. The authors, representatives of environmental data repositories, concluded that easily obtainable data use metrics, such as data downloads, etc., have limited value while more informative analyses would require additional resources.
Water quality data collected by the Citizen-Led Environmental Observatory (CLEO) from multiple nearshore sites in Lake Lillinonah, Connecticut, USA, 2010-current
Included in this data package are water quality data from the Citizen-Led Environmental, a Observatory (CLEO) volunteer water quality monitoring program run by Friends of the Lake (FOTL) and Fairfield University at Lake Lillinonah, Connecticut, USA. The program has been operational since 2008 (data available 2010-current). Trained volunteer monitors collect data from dock locations across the lake on water temperature, Secchi disk depth, water color, presence of floating woody debris, recreation potential, trash, particle type and surface scum. Volunteers collect data between 3:00 and 7:00 PM three times per week from Memorial Day through Labor Day. In addition to the variables listed above, CLEO volunteers collect routine water samples on a biweekly basis, as well as any time there is a notable algal bloom. The routine samples are analyzed for nutrient (total nitrogen and total phosphorus) concentrations as well as concentrations of the cyanobacterial toxin microcystin. The blooms samples are analyzed for microcystin only. These data are available in EDI packages EDI568 (nutrients) and EDI569 (toxins).
CO2, CH4, and H2O flux data and associated environmental variables for the BBC collapse scar for 2004
This data set contains flux measurements for the transect from the center of the BBC collapse scar (0m) into the surrounding fire scar (30m) of the Survey Line Fire (burned in June-July 2001). We measured CO2, H2O and CH4 fluxes every one to two weeks throughout the growing season of 2004. We measured fluxes at permanent plots established from the center of the bog into the surrounding burn at 0, 6, 12, 18, 24, and 30 m on the east and west side of the transect. Flux measurements on either side of the transect were treated as replicates. CO2 and H2O fluxes were measured using a Li-840 infrared gas analyzer (Licor Inc., Lincoln, NB, USA). The IRGA was calibrated before each trip to the field using a span of 400 ppm and a zero of N2 gas. We logged data every 0.5 seconds for 2 min. To account for measurement variability, we conducted two measurements in succession at each location, after flushing the chamber for accumulated CO2 and H2O. For the flux measurements, we built plexiglass chambers with pipe insulation bases with dimensions of 61 x 61 x 30.5 cm, 61 x 61 x 61 cm, or 61 x 61 x 122 cm. The shorter chambers were used in the collapse portion of the transect. Chambers included fans for air circulation, inlet and outlet ports for CO2 measurements, or just outlet ports for CH4 measurements (Carroll and Crill 1997). We placed chambers directly on the soil surface and used pipe insulation and plastic sheeting to make a solid seal during the measurement. To estimate the volume for each chamber measurement, we measured the distance to the soil surface from a 6 cm grid suspended 30 cm above each plot, the surface area was then used to calculate the chamber volume for each measurement. Dark measurements were used to determine CO2 derived from soil and root respiration (ecosystem respiration) using a two-layer cloth shroud with a reflective surface to exclude solar radiation. To estimate net ecosystem exchange (NEE) of CO2, we conducted chamber measurements of plant and soi
Site, environmental and stand data across an age since fire range of 6-338 years for 30 sites in northern Yukon and central Alaska
This dataset describes site level environmental and stand attributes of 30 black spruce stands across northern Yukon and central Alaska. Sites were selected to cover a broad age range since fire (6 to 338 years). Site level descriptions include: latitude, longitude, elevation, slope, aspect, soil characteristics (organic layer depth, pH, active layer depth, moisture classification, texture), average tree age, density and stand basal area. <br><br> **In Prep Puplication** Viglas, Jayme, Carissa Brown, and Jill Johnstone. Stand age effects on seed productivity of north
Alaska Peatland Experiment: Biweekly flux data and environmental measurements (soil temperature, soil moisture, seasonal thaw depth, water table depth)
This dataset contains ecosystem respiration data measured biweekly at the Alaska Peatland Experiment (APEX) gradient plots. Five plots encompass the gradient all changing in dominant vegetation type. Plot labels are as follows: BS (Black Spruce), WB (Shrub), TG (Grass), EC (Sedge/forb), Control (Rich fen). Data set also includes environmental data (soil temperature, soil moisture, seasonal thaw depth, water table depth) taken at the same time as each flux.
Yukon River Basin Fire and Permafrost Study: Site description and summary of environmental data (2009-2012)
This study was designed to examine the effects of fire on permafrost across three soil landscapes in interior Alaska: rocky uplands, silty uplands, and sandy lowlands. This dataset provides a description of each intensive study site and summarizes soils data, including soil texture, moisture, water stocks, surface organic thickness, thaw depth, and net seasonal heat input. Associated datasets include soil temperature data, plant species data, and detailed soil information by soil layer.
Environmental and stand data for 88 sites located in the 2004 burns off the Steese, Taylor, and Dalton Highways, and for the 2005 burn near Eagle Plains, Yukon.
This dataset contains environmental variables collected at the site level (latitude, slope, aspect, moisture, etc.), pre-fire stand characteristics (tree density and basal area by species), and postfire regeneration (seedling density by species).
KEE01 Prairie phenology data from Konza Environmental Education Program (KEEP) since 2001
This data represents the "phenology" or timing of observable biological processes, e.g. first day of blooming, first sighting of a migratory species, etc... as reported by volunteers with the Konza Environmental Education Program. The reports do not follow a specific experimental design and are based on the individual's knowledge and skills. Data is also available on the KEEP website (https://keep.konza.k-state.edu/prairieecology/index.html).
Data from: Genetic and environmental canalization are not correlated among altitudinally varying populations of Drosophila melanogaster
<p>Organisms are exposed to environmental and mutational effects influencing both mean and variance of phenotypes. Potentially deleterious effects arising from this variation can be reduced by the evolution of buffering (canalizing) mechanisms, ultimately reducing phenotypic variability. There has been interest regarding the conditions enabling the evolution of canalization. Under some models, the circumstances under which genetic canalization evolves is limited, despite apparent empirical evidence for it. It has been argued that genetic canalization evolves as a correlated response to environmental canalization (congruence model). Yet, empirical evidence has not consistently supported predictions of a correlation between genetic and environmental canalization. In a recent study, a population of <em>Drosophila </em>adapted to high altitude showed evidence of genetic decanalization relative to those from low altitudes. Using strains derived from these populations, we tested if they varied for multiple aspects of environmental canalization We observed the expected differences in wing size, shape, cell (trichome) density and mutational defects between high- and low-altitude populations. However, we observed little evidence for a relationship between measures of environmental canalization with population or with defect frequency. Our results do not support the predicted association between genetic and environmental canalization.</p>
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.