Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
221
datasets available to search
ShareScore release 0.9.0
Dataset results
221 results for “multi-scale”
Figure 3 in Multi-scale patterns in the host specificity of plant-dwelling arthropods: the influence of host plant and temporal variation on species richness and assemblage composition of true bugs (Hemiptera)
Figure 3. Mean number of individuals (from SIMPER analysis) of dominant hemipteran species, during each sampling period, for most plant species.
Figure 1 in Multi-scale patterns in the host specificity of plant-dwelling arthropods: the influence of host plant and temporal variation on species richness and assemblage composition of true bugs (Hemiptera)
Figure 1. Interactions between plant species sampled and sampling period for (A) abundance (number of individuals) per plant and (B) species richness per plant (standard error bars are shown).
Figure 6 in Multi-scale patterns in the host specificity of plant-dwelling arthropods: the influence of host plant and temporal variation on species richness and assemblage composition of true bugs (Hemiptera)
Figure 6. Relationship between the effectively specialized fauna (squares) and singleton species (circles) for the number of hemipteran species from each sampling period and for the entire collection. An exponential decay equation is fitted for effectively specialized fauna, y = 2.973∗ exp (−0.00575∗ x) + (−1.478), R2 = 0.7598, and for singleton species, y = 22.53∗exp (−0.08466∗x) + 0.2614, R2 = 0.9873.
Multi-scale full waveform inversion based on a convolutional neural network
<p>The research data from this paper are uploaded here and are available for download.</p>
Trait-based and multi-scale approach provides insight on responses of freshwater mussels to environmental heterogeneity
<p>Our understanding of the factors driving the distribution of metacommunities at different scales can be obscured by high variation in species composition between sites and a lack of fine-scale distribution data. Trait-based approaches have long been used to better identify and examine ecological patterns. Most recent studies of riverine metacommunities examining trait-based patterns have focused on shorter-lived organisms. Here we focused on a group of longer-lived, sedentary riverine organisms, unionid freshwater mussels. The objective of this study was to examine how (1) the distribution of mussels with different life history strategies (trait-based approach) and (2) the relative importance of environmental and spatial factors (as a proxy for dispersal) would differ with spatial scale and position in the river; and to (3) further compare this with patterns derived from a taxonomic approach. Fine-scale distribution data of mussels and environmental factors were collected every 100 m in spatially extensive surveys in an up- and downstream segment (200 sites/20 km-segment) of a semi-arid river, making them some of the most spatially intensive surveys documented to date. A combination of redundancy analysis, asymmetric eigenvector mapping, and variation partitioning analyses revealed that more variation was explained by environmental factors where more environmental differences occur between sites. Where environmental heterogeneity was lower the amount of variation explained by smaller-scale spatial factors was higher, likely mostly associated with stochastic rather than dispersal processes. A higher amount of unexplained variation at the taxonomic level suggests that stochasticity may also play an important role in determining species composition. In contrast, different life history groups had a highly predictable distribution pattern driven by environmental heterogeneity, especially between river segments and mesohabitat, which was associated with different flow conditions. The role we predict for environmental heterogeneity and stochasticity in shaping the distribution of mussels in our study river likely also applies to other taxa and ecosystems at a spatial scale at which neither dispersal limitation nor mass effects occur. Thus, understanding the magnitude and extent of dispersal relative to the amount of environmental heterogeneity may be key for predicting metacommunity structure and dynamics for different organisms.</p>
Data produced by the study "Application of the Multi-Scale Infrastructure for Chemistry and Aerosols version 0 (MUSICAv0) for air quality in Africa".
<p>This is the processed data used in the manuscript entitled "Application of the Multi-Scale Infrastructure for Chemistry and Aerosols version 0 (MUSICAv0) for air quality in Africa".</p> <p> </p>
SPEI-GD: The first global multi-scale daily SPEI dataset for 1983-2020
<p>The global daily SPEI dataset (SEPI-GD) at 0.25° spatial resolution form 1982 to 2021. This depository includes the five files of the daily SPEI data with five time scales (5, 30, 90, 180, and 360 days). The calculation based on ERA5's precipitation and Singer's potential evapotranspiration. All data are geographic latitude-longitude projection and NetCDF format. See paper for detailed explanation: Liu X, Yu S, Yang Z, et al. The first global multi-timescale daily SPEI dataset from 1982 to 2021[J]. Scientific Data, 2024, 11(1): 223.</p>
Data for: Multi-scale relationships in thermal limits within and between two cold-water frog species uncover different trends in physiological vulnerability
<ol> <li>Critical thermal limits represent an important component of an organism's capacity to cope with future temperature changes. Understanding the drivers of variation in these traits may uncover patterns in physiological vulnerability to climate change. Local temperature extremes have emerged as a major driver of thermal limits, although their effects can be mediated by the exploitation of fine-scale spatial variation in temperature through behavioral thermoregulation.</li> <li>Here, we investigated thermal limits along elevation gradients within and between two cold-water frog species (<em>Ascaphus</em> spp.), one with a coastal distribution (<em>A. truei</em>) and the other with a continental range (<em>A. montanus</em>). We quantified thermal limits for over 700 tadpoles, representing multiple populations from each species. We combined local temporal and fine-scale spatial temperature data to quantify local thermal landscapes (i.e., thermalscapes), including the opportunity for behavioral thermoregulation.</li> <li>Lower thermal limits for either species could not be reached experimentally reached without the water freezing, suggesting that cold tolerance is <0.3℃. In contrast, upper thermal limits varied among populations, but this variation only reflected local temperature extremes in <em>A. montanus</em>, perhaps due to greater variation in stream temperatures across its range. Lastly, we found minimal fine-scale spatial variability in temperature, suggesting limited opportunity for behavioral thermoregulation and thus increased vulnerability to warming for all populations.</li> <li>By quantifying local thermalscapes, we uncovered different trends in the relative vulnerability of populations across elevation for each species. In <em>A. truei</em>, physiological vulnerability decreased with elevation, whereas in <em>A. montanus</em>, all populations were equally physiologically vulnerable. These results highlight how similar environments can differentially shape physiological tolerance and patterns of vulnerability of species, and in turn, impact their vulnerability to future warming. </li> </ol>
Physicochemical habitat data and multi-scale occupancy data for spring-associated fishes in Oklahoma streams
<p class="vC7TJ allowTextSelection">Spring-associated fishes occupy thermally unique habitats in groundwater-dominated streams that are often of high quality. However, outside of water temperature, little else is known about the physicochemical habitat requirements for many of these species. With human effects on streams increasing, it is important to conservation and management to characterize spring habitats and the species that occupy them. Our study objective was to determine the physicochemical factors related to occupancy of four spring-associated species in the Arbuckle Uplift and Ozark Highlands ecoregions, Oklahoma USA. We used a hierarchal approach to identify habitat relationships at multiple spatial scales. We collected detection and non-detection data using both snorkeling and seining methods. We examined the physicochemical relationships related to detection and occupancy for four spring-associated fishes. Data were analyzed using occupancy modeling in a Bayesian framework. Our results indicated water depth and water clarity were important factors affecting detection of spring-associated fishes. Occupancy of our target species differed by ecoregion, with least darter being less common in the Ozark Highlands ecoregion and subadult smallmouth bass being more common in the Ozark Highlands. Interestingly, we found water temperature occupancy relationship for only least darter and southern redbelly dace, whereas redspot chub and smallmouth bass were more likely to occur at sites with deeper pool habitats of larger streams. We documented both spatial and temporal differences in occurrence probabilities at ecoregion, reach, and riffle-run-pool complex scale. Furthermore, our results indicate snorkeling was a superior sampling method compared to seining for detecting most fishes in clear warmwater streams even at relatively low visibilities. Lastly, we demonstrate the importance of using multi-scale studies when developing conservation plans for warmwater fishes.</p>
Multi-scale Modeling of Sleep Behaviors in Social Networks
ClinicalTrials.gov study NCT02846077. IPD Sharing: UNDECIDED. Countries: 1. Publications: 4.
Multi-scale Modeling of Breast Conserving Therapy
ClinicalTrials.gov study NCT02310711. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Differing, multi-scale landscape effects on genetic diversity and differentiation in eastern chipmunks
Open the record for dataset details and reuse information.
Data from: A multi-scale analysis of gene flow for the New England cottontail, an imperiled habitat specialist in a fragmented landscape
Open the record for dataset details and reuse information.
Data from: Multi-scale resistant kernel surfaces derived from inferred gene flow: An application with vernal pool breeding salamanders
Open the record for dataset details and reuse information.
Data from: Multi-scale drivers of community diversity and composition across tidal heights: an example on temperate seaweed communities
Open the record for dataset details and reuse information.
Data from: Multi-scale temporal patterns in fish presence in a high-velocity tidal channel
Open the record for dataset details and reuse information.
Data from: Very high resolution digital elevation models: are multi-scale derived variables ecologically relevant?
Open the record for dataset details and reuse information.
Data from: Multi-scale quantification of tissue behavior during amniote embryo axis elongation
Open the record for dataset details and reuse information.
Data from: Multi-scale landscape and wetland drivers of lake total phosphorus and water color
Open the record for dataset details and reuse information.
Why are there so many flowering plants? A multi-scale analysis of plant diversification
Open the record for dataset details and reuse information.
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.