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156 results for “long-term dataset”
(12)-Pereyra2024A-DS0001--0009 – Nine Tribolium castaneum long-term live imaging datasets of embryonic development acquired with light sheet fluorescence microscopy
<p>(12)-Pereyra2024A-DS0001--0009 – Nine <em>Tribolium castaneum</em> long-term live imaging datasets of embryonic development acquired with light sheet fluorescence microscopy</p>
Data from: Long-term trends in the occupancy of ants revealed through use of multi-sourced datasets
<p><span>We combined participatory science data and museum records to understand long-term changes in occupancy for 29 ant species in Denmark over 119 years. Bayesian occupancy modelling indicated change in occupancy for 15 species: five increased, four declined and six showed fluctuating trends. We consider how trends may have been influenced by life-history and habitat changes. Our results build on an emerging picture that biodiversity change in insects is more complex than implied by the simple insect decline narrative.</span></p>
Dataset for "Long-term implications of reduced gas imports on the decarbonization of the European energy system"
<p>A dataset containing results for the paper "Long-term implications of reduced gas imports on the decarbonization of the European energy system". See also the associated Github repository: https://github.com/TimToernes/Reduced-gas-imports </p>
Long-term (2003-2020) hourly 0.25° global PM2.5 dataset (DeepCAMS) Part-1: 2003-2011
<p>This is part-I (2003-2011) of our DeepCAMS.</p> <p>Part-II can be found at https://doi.org/10.5281/zenodo.6969598</p> <p>Usage: The raw data -- (scaling factor: 0.1) --> the true PM2.5 concentration</p> <p>Paper title: Generating a Long-term (2003-2020) hourly 0.25° global PM2.5 dataset via spatiotemporal downscaling of CAMS with deep learning (DeepCAMS)</p> <p>Paper doi: <a href="https://doi.org/10.1016/j.scitotenv.2022.157747">https://doi.org/10.1016/j.scitotenv.2022.157747</a></p> <p>If you find our work helpful, please cite it, thank you very much!</p>
Long-term dataset of stable isotopes in rainfall at the North American monsoon region in southern Sonora, Mexico
<p>This is an original data set where rainwater samples were collected with a rain bucked prepared to avoid isotopic fractionation following the indication from the International Atomic Energy Agency (IAEA). We use a rainfall collector containing mineral oil, and samples from the collector were extracted within a maximum of 24 hours from the rain event and sometimes soon after precipitation ceased. Isotope analyses were carried with laser spectroscopy using working standards calibrated against the accepted Vienna Standard Meteoric Oceanic Water (VSMOW) for international reference and comparison. We analyzed the isotopic composition of 138 rain samples collected a permanent location with the aid of a rain bucket containing mineral oil. Samples were collected soon after every rainfall event between July 2014 and December 2021. Rainfall was collected at one permanent location at a residential area in Ciudad Obregon, Sonora Mexico within the Cajeme municipality (27.511850, -109.956316) in the transition zone between the urban and agricultural area in the northeastern edge of the city.</p>
Technoeconomic dataset for long-term energy systems modelling in Ghana (2015-2065)
<div> <p>Technoeconomic data and assumptions for energy systems modelling in Ghana, including capital cost, fixed cost, variable cost, power plants' characteristics (e.g. list of existing power plants in Ghana, operational life, efficiency, capacity factors), fuels' prices and emission intensities, power demand/consumption/generation, residual capacity, fossil fuels' reserves, and renewable energy potentials in 2015-2065. This document is complementary to CCG Starter Data Kit for Ghana (Allington et al., 2023) as it updates it to ensure the OSeMOSYS models are closer to the Ghanaian context.</p> </div>
(06)-He2019A-DS0001 – Tribolium castaneum foxQ2-5' line long-term live imaging dataset of embryonic development acquired with light sheet fluorescence microscopy
<p>(06)-He2019A-DS0001 – <em>Tribolium castaneum</em> foxQ2-5' line long-term live imaging dataset of embryonic development acquired with light sheet fluorescence microscopy</p>
Dataset for: Long-term soil warming decreases microbial phosphorus utilization by increasing abiotic phosphorus sorption and losses
<p><span>Phosphorus (P) is an essential and often limiting element that could play a crucial role in terrestrial ecosystem responses to climate warming. However, it has yet remained unclear how different P cycling processes are affected by warming. Here we investigated the response of soil P pools and P cycling processes in a mountain forest after 14 years of soil warming (+4°C). Long-term warming decreased soil total P pools, likely due to higher outputs of P from soils by increasing net plant P uptake and downward transportation of colloidal and particulate P. Warming increased the sorption strength to more recalcitrant soil P fractions (absorbed to iron oxyhydroxides and clays), thereby further reducing bioavailable P in soil solution. As a response, soil microbes enhanced the production of acid phosphatase, though this was not sufficient to avoid decreases of soil bioavailable P and microbial biomass P (and biotic phosphate immobilization). This study therefore highlights how long-term soil warming triggers changes in biotic and abiotic soil P pools and processes, which can potentially aggravate the P constraints of the trees and soil microbes and thereby negatively affect the C sequestration potential of these forests.</span></p>
Dataset for "A Double Dissociation between Savings and Long-Term Memory in Motor Learning"
<p>Data for "A Double Dissociation between Savings and Long-Term Memory in Motor Learning"<br> <br> For analysis code and any updates, please visit https://github.com/AlkisMH/Savings_vs_Long_Term_Memory<br> <br> For any questions, please contact Alkis Hadjiosif (alkis [at] seas [dot] harvard [dot] edu; ahadjiosif [at] gmail [dot] com)</p> <p>These .mat files contain data collected for Experiments 1-4 and S1, used to reproduce Figures 1-6 and S1 in the paper. Data for each experiment are in the form of a Matlab structure, with each field consisting of a [Num_trials x Num_participants] matrix.</p> <p>The fields are:</p> <p><strong>TN:</strong> Trial Number</p> <p><strong>VF:</strong> Whether visual feedback was given during the trial (1: online visual feedback; 2: no visual feedback)</p> <p><strong>Rotation:</strong> The visuomotor rotation imposed on each trial (in degrees). CCW is positive, CW is negative.</p> <p><strong>Wait:</strong> Whether, right before the trial, a wait time was imposed (1) or not (0). Trials immediately following breaks are indicated by (2).</p> <p><strong>Instruction:</strong> Whether an instruction was given for the trial (1) or not (0). Only present in Experiment 3. Note that Experiment 3 includes:</p> <p>-> Two specific instruction trials during learning and and two during relearning, before and after the 1-minute wait ("Move your hand to the center of the target","Move your hand to the far end of the target")</p> <p>-> Six random instruction trials before initial learning and six before relearning ("Move your hand to the left/right/near/far end of the target"), to familiarize participants with the instruction process</p> <p><strong>ITI:</strong> Time (in seconds) since the last trial (regardless of direction).</p> <p><strong>theta_target:</strong> Target direction (in degrees) relative to the 12 o'clock position. Only included for Experiment 4: target is always at 12 o'clock for Experiments 1-3.</p> <p><strong>theta:</strong> = reaching direction relative to theta_target, measured 150ms into the movement. Note that this is flipped based on the rotation sign so that adaptation towards the imposed visuomotor rotation is always positive.</p> <p><strong>theta_end:</strong> = reaching direction relative to theta_target, measured at the end of movement. Only included for Experiment 4: it is to be used for the no visual feedback blocks in Experiment 4.</p> <p>Note for <strong>Experiment 4</strong>: the last two blocks (last 114 trials) were done on day 2.</p>
Dataset from publication: Long-term changes in bloom dynamics of Southern and Central Baltic cold-water phytoplankton
<p>This data set contains the output of the numerical ocean model GETM used in the publication "Long-term changes in bloom dynamics of Southern and Central Baltic cold-water phytoplankton"</p>
Dataset for manuscript "Host-related and environmental factors influence long-term ectoparasite infestation dynamics of mouse lemurs in northwestern Madagascar" to be published in the American Journal of Primatology
<p>This Excel-file contains three datasets, corresponding to the initial raw dataset resulting from all ectoparasite inspections (n = 2,241), the merged dataset used for host-related and temporal modeling (n = 1940), and the even more condensed dataset with one datapoint per individual used for climatic modeling (n = 583), respectively.</p>
Dataset for "Seismic background level (SBL) growth can reveal slowly developing long-term eruption precursors"
<p>Ichihara M, Ohminato T, Konstantinou KI, Yamakawa K, Watanabe A, Takeo M (2023) Seismic background level (SBL) growth can reveal slowly developing long-term eruption precursors. Scientific Report (revised)</p> <p>Matlab fig files for Figures 1--6 and Figures in Supporting Information in the above manuscript.</p>
Data on the association between garlic mustard and the plant community from a long-term observational dataset in Illinois, U.S.A.
<p>The impact of a biological invasion on native communities is expected to be uneven across invaded landscapes due to differences in local abiotic conditions, invader abundance, and traits and composition of the native community. One way to improve predictive ability about the impact of an invasive species given variable conditions is to exploit known mechanisms driving invasive species' success. Invasive plants frequently exhibit allelopathic traits, which can be directly toxic to plants or indirectly impact them via disruption of root symbionts, including mycorrhizal fungi. The indirect mechanism – mutualism disruption – is predicted to impact plants that rely on mycorrhizas but not affect non-mycorrhizal plant species. To assess whether invader-driven mutualism disruption explains observed changes in native plant communities, we analyzed long-term (1998–2018) plant cover data from forest plots across the state of Illinois. We evaluated native plant communities experiencing a range of abundance of invasive allelopathic garlic mustard (<em>Alliaria</em> <em>petiolata</em>) and varying environmental conditions. Consistent with the mutualism disruption hypothesis, we showed that as garlic mustard abundance increased over time in 0.25 m<sup>2</sup> sampling quadrats, the abundance of mycorrhizal plant species decreased, but non-mycorrhizal plant species did not. Over space and time, garlic mustard abundance predicted plant abundances and diversity at the quadrat level, but this relationship was not present at a larger scale when quadrats were aggregated within sites. Garlic mustard's impact on the plant community was highly localized, yet it was as important as abiotic variables for predicting local plant diversity. We showed that garlic mustard abundance was a key predictor of patterns of plant diversity across invasion intensity and environmental heterogeneity in a way that is consistent with mutualism disruption. Our work indicates that the mutualism disruption hypothesis can provide generalizable predictions of the impacts of allelopathic invasive plants that are evident at a broad spatial scale.</p>
The Long-term, High-accuracy and Seamless Soil Moisture (LHS-SM) dataset over the Qinghai-Tibet Plateau: part 2 (2011-2020)
<p>Soil moisture (SM) is a vital variable in the water-energy cycle and characterizing its spatiotemporal dynamics is crucial for understanding the impacts of climate change. Although substantial efforts have been devoted to derive SM data at fine scale, there is still a research gap in obtaining the long-term, high-accuracy and high-resolution SM data over the Qinghai-Tibet Plateau (QTP) due to its complex topography. Therefore, this study generated the long-term, high-accuracy and seamless soil moisture (LHS-SM) dataset over the QTP during 2001-2020 using a two-step downscaling method. First the daily SM data from the Climate Change Initiative program of the European Space Agency (ESA CCI) was downscaled to 1km utilizing five machine learning approaches. Then a dynamic data merging method that considers the spatiotemporal nonstationary error was applied to derive the final LHS-SM data. Results indicated that LHS-SM data exhibited satisfying accuracy (mean R = 0.55, ubRMSE = 0.049 m³/m³) and certain improvement to the ESA CCI SM data both at station and network scales. The dataset can be used for various regional hydrology, meteorology, ecological analysis and modeling.</p>
Dataset for study Long-term changes in urban bird populations: correspondence of the trends between urban and rural areas
<p>Dataset used for a study "Long-term changes in urban bird populations: correspondence of the trends between urban and rural areas"</p> <p>Data structure:</p> <p>Type = type of environment (R - rural, U - urban)<br> POID = unique identifier of each census point across all transects<br> Transect = unique identifier of a transect (each contains 20 census points)<br> Point = unique identifier of a point within one transect<br> Year = year of the count<br> Species = scientific name of bird species<br> Count = number of birds counted</p> <p>Each species has its own datafile.</p>
Dataset for the transcriptome analysis of hippocampal subfields identifies gene expression profiles associated with long-term active place avoidance memory
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Dataset: Long-term changes in survival of Eurasian lynx in three reintroduced populations in Switzerland
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Dataset for: Long-term soil warming decreases microbial phosphorus utilization by increasing abiotic phosphorus sorption and losses
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Data from: Long-term trends in the occupancy of ants revealed through use of multi-sourced datasets
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Final eddy covariance dataset to support lessons from long-term monitoring of carbon gains and losses in cropping systems
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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.