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15,542 results for “How long”
State-dependent mortality, not behavior, fragments population distribution of a long-lived mammal after ecological disturbance
<p>Data and code used to produce figures and analyses for the peer-reviewed paper "State-dependent mortality, not behavior, fragments population distribution of a long-lived mammal after ecological disturbance". All demographic and GPS data were collected by the authors as part of the Wyoming Range Mule Deer Project, and spatial data were derived from publicly available GIS platforms. </p> <p>Questions about data and code can be directed to rraffer1@uwyo.edu and tlasharr@uwyo.edu.</p> <p> </p>
Replication package of the Paper "On the Relationships between the Initial Ecology Indicators of OSS Projects and Their Long-Term Popularity: An Exploratory Study on GitHub"
<p>The dataset is collected from GitHub API and GitHub GHTorrent dataset. A brief description of each folder is provided below:</p> <p><strong>1. "Dataset_and_Code" folder</strong></p> <p>Contains the final dataset and algorithms</p> <p><strong>2. "Test_parameters" folders </strong></p> <p>Includes datasets under different parameters and the corresponding reproduction code, which corresponds to the first experiment of RQ1</p> <p><strong>3. "Compare_baseline"folder</strong></p> <p>Includes the dataset used by our method, the dataset used by the baseline method, and the reproduction code, corresponding to the second experiment of RQ1</p> <p><strong>4. "PLS" folder</strong></p> <p>Includes the dataset used by PLS and the corresponding reproduction code, which corresponds to experiment of RQ2</p> <p><strong>5. " Indicator_Calculation " folder</strong><br>It contains the calculation methods for various metrics in the paper, as well as the corresponding key files. </p> <p><span><strong>6. " Appendix " folder</strong><br></span><span>It includes supplementary materials such as the methodology for metric calculations to address the reviewers' questions.</span> </p> <p><strong>Note</strong></p> <p>We have provided a corresponding README file in each folder to help others reproduce our results</p>
A Network-Based Phase-Gradient Stacking Method for Resolving Long-wavelength deformation from low-coherence SAR interferograms
<p><span><span><strong>This dataset includes the key results, primary </strong></span></span><strong>InSAR and GNS observatons </strong><strong> in our study. </strong></p>
High-spatial-resolution (0.0083° × 0.0083°) and long-term (1982 to 2010) monthly gridded wetland CH4 flux product for the Southeastern United States
<p>This dataset presents monthly gridded methane emissions from subtropical freshwater wetlands across the Southeastern United States spanning from 1982 to 2010, measured in nmol m-2 s-1. Each grid cell's methane flux prediction was adjusted based on the fractional wetland extent within that cell, utilizing data from the National Wetland Inventory (NWI) and the Wetland Area and Dynamics for Methane Modeling (WAD2M) product. The dataset includes mean monthly fluxes with no adjustment for wetland area (i.e., fluxes assuming hypothetical 100% wetland cover), as well as mean monthly fluxes adjusted for wetland area based on NWI or WAD2M, along with their respective standard deviations of the daily emissions for each month. Data are provided in NetCDF4 format.</p> <p>Lat: 25-40°N</p> <p>Lon: 95-75°W</p> <p>Period: 198201-201012 (for "CH4_Monthly_SEUS_unweighted.nc" and "CH4_Monthly_SEUS_NWI.nc") and 200001-201012 (for "CH4_Monthly_SEUS_WAD2M.nc")</p> <p>Temporal resolution: Monthly</p> <p>Spatial resolution: 0.0083° × 0.0083° (~1 km × 1 km)</p> <p>Unit: nmol m-2 s-1</p> <p>Fill value: -9999</p>
Artifact from "A Little Goes a Long Way: Tuning Configuration Selection for Continuous Kernel Fuzzing"
<p>Artifact from "A Little Goes a Long Way: Tuning Configuration Selection for Continuous Kernel Fuzzing"</p>
Dataset: The role of long-term hydrodynamic evolution in the accumulation and preservation of organic carbon-rich deposits in the shelf seas
<p>Output files from harmonic analysis of regional tidal model, glacial isostatic adjustment model input and output (relative sea level and ice sheet extent datasets), and scripts for figure generation.</p> <p>If using these data, please cite: </p> <p><strong>Ward, S.L., Bradley, S.L., Roseby, Z.A., Wilmes, S.B., Vosper, D.F., Roberts, C.M. and Scourse, J.D., 2025. The role of long‐term hydrodynamic evolution in the accumulation and preservation of organic carbon‐rich shelf sea deposits. <em>Journal of Geophysical Research: Oceans</em>, <em>130</em>(4), p.e2024JC022092. <a href="https://doi.org/10.1029/2024JC022092">https://doi.org/10.1029/2024JC022092</a></strong></p> <p> </p>
Reproduction package for the paper "Analyzing long-term maintenance releases of the Linux kernel"
<p>This is the reproduction package of the paper "Analyzing long-term maintenance releases of the Linux kernel". This package includes the datasets and the software for methods presented in the paper.</p>
Dittmann S., Kiessling T., Knickmeier K., Schönberg J., Brennecke D., Hinzmann M., Knoblauch D., Thiel M., 2024. Temporal variability of litter pollution of rivers in Germany - a long-term assessment by schoolchildren as citizen scientists.
<p>Research data to the manuscript "Temporal variability of litter pollution of rivers in Germany - a long-term assessment by schoolchildren as citizen scientists" by Dittmann et al. 2024.</p> <p> </p> <div> </div>
FIGURES 5–9 in New long-horned caddisfly genus and species of Leptoceridae (Insecta: Trichoptera) from Brazil
FIGURES 5–9. Ibyacerina caparao gen. nov. et sp. nov., male genitalia. 5, genital capsule, left lateral; 6, genital capsule, dorsal; 7, genital capsule, ventral; 8, phallic apparatus, ventral; 9, phallic apparatus, left lateral.
FIGURE 10 in New long-horned caddisfly genus and species of Leptoceridae (Insecta: Trichoptera) from Brazil
FIGURE 10. First order tributary of Rio José Pedro, Parque Nacional do Caparaó, Minas Gerais State, Brazil; type locality of Ibyacerina caparao gen. nov. et sp. nov. 10A, Malaise trap over stream; 10B, view of water running down the wall behind Malaise trap; 10C, downstream view from Malaise trap.
FIGURE 2 in New long-horned caddisfly genus and species of Leptoceridae (Insecta: Trichoptera) from Brazil
FIGURE 2. Ibyacerina caparao gen. nov. et sp. nov., male holotype. Head, pronotum, and mesonotum, in dorsal view. Abbreviations: ad.s.w. = anterodorsal setal wart; d.s.w. = dorsal setal wart; pd.s.w. = posterodorsal setal wart; pl.s.w. = posterolateral setal wart; p.s.w. = postoccipital setal wart; pn.s.w. = pronotal setal wart.
FIGURE 1 in New long-horned caddisfly genus and species of Leptoceridae (Insecta: Trichoptera) from Brazil
FIGURE 1. Maximum likelihood tree of Leptoceridae based on COI and CAD nucleotide sequences (lnL= -39834.3628, 1,503 bp). Thicker branches refer to those also recovered in the Bayesian inference consensus. Numbers above branches are SH-aLRT support (%) / ultrafast bootstrap support (%) and below are posterior probabilities. Values below 80% in SH-aLRT support, 95% in ultrafast bootstrap support, and 0.90 in Bayesian posterior probabilities are not shown, except for clade containing Ibyacerina caparao gen. et sp. nov. Taxa and branches are color coded according to subfamily and tribal classification following Malm & Johanson (2011).
Stoichiometric traits (N:P) of understory plants contribute to reductions in plant diversity following long-term nitrogen addition in subtropical forest
<p>Nitrogen enrichment is pervasive in forest ecosystems, but its influence on understory plant communities and their stoichiometric characteristics is poorly understood. We hypothesize that when forest is enriched with nitrogen (N), the stoichiometric characteristics of plant species explains changes in understory plant diversity. A 13 year field experiment was conducted to explore the effects of N addition on foliar carbon (C): N: phosphorus (P) stoichiometry and understory plant species richness in a subtropical Chinese fir forest. Four levels of N addition were applied: 0, 6, 12, and 24 g m<sup>-2</sup> yr<sup>-1</sup>. Individual plant species were categorized into resistant plants, intermediate resistant plants, and sensitive plants based on their response to nitrogen addition. Results showed that N addition significantly decreased the number of species, genera and families of herbaceous plants. Foliar N:P ratios were greater in sensitive plants than resistant or intermediate resistance plants, while intrinsic water use efficiency showed an opposite trend. However, no relationship was detected between soil available N and foliar N, and soil N:P and foliar N:P ratios. Our results indicated that long-term N addition decreased the diversity of understory plants in a subtropical forest. Through regulating water use efficiency with N addition, sensitive plants change their N:P stoichiometry and have a higher risk of mortality, while resistant plants maintain a stable N:P stoichiometry, which contributes to their survival. These findings suggest that plant N:P stoichiometry plays an important role in understory plant performance in response to environmental change of N.</p>
Data from: Resource predictability drives inter-annual variation in migratory behaviour in a long-lived bird
<p><span><span><span><span><span><span><span><span><span><span><span>There is a growing awareness that experience may play a major role in migratory decisions, especially in long-lived species. However, empirical support remains to date scarce. Here, we use multi-year GPS-tracking data on 28 adult Lesser Black-backed Gulls (<i>Larus fuscus</i>), a long-lived species for which migratory strategies typically consist of a series of long stopovers, to assess how experience affects interannual variation in stopover selection. We expect that food source reliability should play a pivotal role, as it both reduces the uncertainty on food availability across years, and enables for more efficient foraging during stopovers by reducing searching efforts. We found that during stopovers gulls indeed developed high fidelity to particular foraging locations, which strongly reduced the daily distance travelled for foraging. When revisiting stopovers in consecutive years, birds used over 80% of foraging locations from the previous year. Although the average fidelity to stopovers across years was a high as 85%, stopovers where birds showed high foraging site fidelity were up to 60% more likely to be revisited compared to stopover with low foraging site fidelity. Accordingly, birds using more stopovers with reliable foraging opportunities showed significantly less interannual variation in their stopover use than birds using stopovers with less reliable foraging opportunities. Our results thus highlight the need to further deepen our understanding of the role of cognitive processes in individual variation in migratory behaviour.</span></span></span></span></span></span></span></span></span></span></span></p>
A long-term 250-m resolution Normalized Difference Vegetation Index (NDVI) product for 1982–2020 in Idaho
<ol> <li>We developed a novel spatio-temporal fusion method to downscale the AVHRR NDVI products to the Moderate-resolution Imaging Spectroradiometer (MODIS) resolution. The algorithm effectively combines the high spatial variability of the MODIS NDVI data and the long-term temporal information of the AVHRR NDVI data. Finally, we successfully generated a monthly global long-term (since 1982) and high-resolution (250m) NDVI database.</li> <li>Here we provide the downscaled NDVI dataset of Idaho from 1982 to 2020.</li> <li>Datasets for other regions can be easily produced by the GEE platform with the code provided in the github (https://github.com/babyfoal/downsclaed_NDVI/tree/main).</li> <li>The spatial distribution and temporal variation of this dataset have been both well validated by the simulated and real-data experiments. </li> </ol>
Supplementary Data and Codes for "Machine Learning Based Long-term Water Quality in the Turbid Pearl River Estuary, China"
<p>The file "Ma_AGUSupplementary.xlsx" contains the in situ data used to develop the ANN model.</p> <p>The files "example_Chla.zip" and "example_TSS.zip" contain codes for retrieving the concentration of Chl-a and TSS on the sea surface of the Pearl River Estuary.</p> <p> </p>
Insights into short and long-term crop-foraging strategies in a chacma baboon (Papio ursinus) from GPS and accelerometer data
<p>Crop-foraging by animals is a leading cause of human-wildlife 'conflict' globally, affecting farmers and resulting in the death of many animals in retaliation, including primates. Despite significant research into crop-foraging by primates, relatively little is understood about the behaviour and movements of primates in and around crop fields, largely due to the limitations of traditional observational methods. Crop-foraging by primates in large scale agriculture has also received little attention. We used GPS and accelerometer bio-loggers, along with environmental data, to gain an understanding of the spatial and temporal patterns of activity for a female in a crop-foraging baboon group in and around commercial farms in South Africa over one year. Crop fields were avoided for most of the year, suggesting that fields are perceived as a high-risk habitat. When field visits did occur, this was generally when plant primary productivity was low, suggesting that crops were a 'fallback food'. All recorded field visits were at or before 15:00. Activity was significantly higher in crop fields than in the landscape in general, evidence that crop-foraging is an energetically costly strategy and that fields are perceived as a risky habitat. In contrast, activity was significantly lower within 100m of the field edge than in the rest of the landscape, suggesting that baboons wait near the field edge to assess risks before crop-foraging. Together this understanding of the spatiotemporal dynamics of crop-foraging can help to inform crop protection strategies and reduce conflict between humans and baboons in South Africa.</p>
Transcriptional kinetics and molecular functions of long non-coding RNAs
<p>R code, R markdowns and data (count tables) for the analysis described in 'Transcriptional kinetics and molecular functions of long non-coding RNAs'. Code and data is also available at https://github.com/sandberg-lab/lncRNAs_bursting.</p>
Datasets for "Discourse-Aware Unsupervised Summarization for Long Scientific Documents"
<p>Datasets used in <a href="https://aclanthology.org/2021.eacl-main.93.pdf">Discourse-Aware Unsupervised Summarization for Long Scientific Documents</a></p>
FIGURES 15–16 in Parasitylenchus myiophagus n. sp. (Nematoda: Parasitylenchidae), a tylenchid nematode parasite of long-legged flies (Diptera: Dolichopodidae)
FIGURES 15–16. Microsporidian infections of secondary generation females of Parasitylenchus myiophagus n. sp. 15. Head area showing clusters of developing spores (arrowheads). 16. Head area showing spores adjacent to swollen excretory pore area (arrowhead). Scale bars: 15 = 17 µm; 16 = 13 µm.
ScienceDex guides
Understand access before you commit
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.