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438
datasets available to search
ShareScore release 0.9.0
Dataset results
438 results for “space time”
Data from: The Bogert effect revisited: salamander regulatory behaviors are differently constrained by time and space
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Data from: Estimating the effective population size across space and time in the Critically Endangered western chimpanzee in Guinea-Bissau: Challenges and implications for conservation management
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Data from: Space-for-time substitution misleads projections of plant community and stand-structure development after disturbance in a slow-growing environment
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Data from: Top predators determine how biodiversity is partitioned across time and space
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Data from: Testing main Amazonian rivers as barriers across time and space within widespread taxa
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Behaviour across time and space–how large scale ‘trait-based’ approaches can shape behavioural ecology
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Data from: Consistent scaling of inbreeding depression in space and time in a house sparrow metapopulation
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Data for: Positive feedback on climate warming by stream microbial decomposers indicated by a global space-for-time substitution study
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Data from: Tracking shifts in forest structural complexity through space and time in human-modified tropical landscapes
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Quantifying within-species trait variation in space and time reveals limits to trait-mediated drought response
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Data from: The conservation status and population decline of the African penguin deconstructed in space and time
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Data from: Behavioral syndromes across time and space in a long-lived turtle
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Data from: Hierarchy in structuring of resource selection: Understanding elk selection across space, time, and movement strategies
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Code and data underlying "Interictal intracranial EEG for predicting surgical success: the importance of space and time"
<p>Code and data underlying our publication "Interictal intracranial EEG for predicting surgical success: the importance of space and time" in Epilepsia 2020</p>
Weekly depth to groundwater space-time maps for a shallow aquifer in rural Colombia
<p>The following dataset is related to the paper: Integrating community science research and space-time mapping to determine depth to groundwater in a remote rural region. It contains the results of the modeling approach that combines space-time depth to groundwater values with probabilistic depth to groundwater data. </p> <p> </p> <p><strong>Abstract [From the paper]:</strong></p> <p>We show how Community Science Research, an approach in which research projects are built with active community participation, added essential descriptive information to a statistical model to represent groundwater levels of a shallow aquifer located in Colombia. The community collected depth to groundwater during an extreme wet year and an average year in the watershed's middle-low-elevation areas. We used the data to map depth to groundwater using three statistical models, each with different configurations. Depth to groundwater is better represented by the model that incorporates qualitative data into quantitative observations. We map the probability of shallow depth to groundwater to identify how the aquifer responds to precipitation and show that in the wet year, the area of shallow depth to groundwater considerably increases compared to the average year. This difference implies that after the watershed receives an excess in precipitation, its flow regulation capacity can decrease, which is further threatened by local land-use activities. </p>
Unique genetic signatures of local adaptation over space and time for diapause, an ecologically relevant complex trait, in Drosophila melanogaster
<p>Organisms living in seasonally variable environments utilize cues such as light and temperature to induce plastic responses, enabling them to exploit favorable seasons and avoid unfavorable ones. Local adapation can result in variation in seasonal responses, but the genetic basis and evolutionary history of this variation remains elusive. Many insects, including <i>Drosophila melanogaster,</i> are able to undergo an arrest of reproductive development (diapause) in response to unfavorable conditions. In <i>D. melanogaster</i>, the ability to diapause is more common in high latitude populations, where flies endure harsher winters, and in the spring, reflecting differential survivorship of overwintering populations. Using a novel hybrid swarm-based genome wide association study, we examined the genetic basis and evolutionary history of ovarian diapause. We exposed outbred females to different temperatures and day lengths, characterized ovarian development for over 2800 flies, and reconstructed their full phased genomes. We found that diapause scored at two different developmental cutoffs has modest heritability, and we identified hundreds of SNPs associated with each of the two phenotypes. Alleles associated with one of the diapause phenotypes tend to be more common at higher latitudes, but these alleles do not show predictable seasonal variation. The collective signal of many small-effect, clinally varying SNPs can plausibly explain latitudinal phenotypic variation seen in North America. SNPs associated with diapause do not exhibit signs of recent selective sweeps, but most are segregating at relatively high frequencies in Africa, suggesting that variation in diapause relies on ancestral polymorphisms. Finally, we utilized outdoor mesocosms to track diapause under natural conditions. We found that hybrid swarms reared outdoors evolved increased propensity for diapause in late fall, whereas indoor control populations experienced no such change. Our results indicate that diapause is a complex, quantitative trait with different evolutionary patterns across time and space.</p>
Dispatches from the neighborhood watch: using citizen science and field survey data to document color morph frequency in space and time
<p>Heritable color polymorphisms have a long history of study in evolutionary biology, though they are less frequently examined today than in the past. These systems, where multiple discrete, visually identifiable color phenotypes co-occur in the same population, are valuable for tracking evolutionary change and ascertaining the relative importance of different evolutionary mechanisms. Here, we use a combination of citizen science data and field surveys in the Great Lakes region of North America to identify patterns of color morph frequencies in the eastern gray squirrel (<i>Sciurus carolinensis</i>). Using over 68,000 individual squirrel records from both large and small spatial scales, we identify the following patterns: (1) the melanistic (black) phenotype is often localized but nonetheless widespread throughout the Great Lakes region, occurring in all states and provinces sampled. (2) In Ohio, where intensive surveys were performed, there is a weak but significantly positive association between color morph frequency and geographic proximity of populations. Nonetheless, even nearby populations often had radically different frequencies of the melanistic morph, which ranged from 0 to 96%. These patterns were mosaic rather than clinal. (3) In the Wooster, Ohio population, which had over eight years of continuous data on color morph frequency representing nearly 40,000 records, we found that the frequency of the melanistic morph increased gradually over time on some survey routes but decreased or did not change over time on others. These differences were statistically significant and occurred at very small spatial scales (on the order of hundreds of meters). Together, these patterns are suggestive of genetic drift as an important mechanism of evolutionary change in this system. We argue that studies of color polymorphism are still quite valuable in advancing our understanding of fundamental evolutionary processes, especially when coupled with the growing availability of data from citizen science efforts.</p>
Data from: Can collective memories shape fish distributions? A test, linking space-time occurrence models and population demographics
Social learning can be fundamental to cohesive group living, and schooling fishes have proven ideal test subjects for recent work in this field. For many species, both demographic factors, and inter- (and intra-) generational information exchange are considered vital ingredients in how movement decisions are reached. Yet key information is often missing on the spatial outcomes of such decisions, and questions concerning how migratory traditions are influenced by collective memory, density-dependent and density-independent processes remain open. To explore these issues, we focused on Atlantic herring (Clupea harengus), a long-lived, dense-schooling species of high commercial importance, noted for its unpredictable shifts in winter distribution, and developed a series of Bayesian space-time occurrence models to investigate wintering dynamics over 23 years, using point-referenced fishery and survey records from Icelandic waters. We included covariates reflecting local-scale environmental factors, temporally-lagged prey biomass and recent fishing activity, and through an index capturing distributional persistence over time, derived two proxies for spatial memory of past wintering sites. The previous winter's occurrence pattern was a strong predictor of the present pattern, its influence increasing with adult population size. Although the mechanistic underpinnings of this result remain uncertain, we suggest that a 'wisdom of the crowd' dynamic may be at play, by which navigational accuracy towards traditional wintering sites improves in larger and/or denser, better synchronized schools. Wintering herring also preferred warmer, fresher, moderately stratified waters of lower velocity, close to hotspots of summer zooplankton biomass, our results indicative of heightened environmental sensitivity in younger cohorts. Incorporating spatiotemporal correlation structure and time-varying regression coefficients improved model performance, and validation tests on independent observations one-year ahead illustrate the potential of uniting demographic information and non-stationary models to quantify both the strength of collective memory in animal groups and its relevance for the spatial management of populations.
Data from: Genomic prediction accuracies in space and time for height and wood density of Douglas-fir using exome capture as the genotyping platform
Background Genomic selection (GS) can offer unprecedented gains, in terms of cost efficiency and generation turnover, to forest tree selective breeding; especially for late expressing and low heritability traits. Here, we used: 1) exome capture as a genotyping platform for 1372 Douglas-fir trees representing 37 full-sib families growing on three sites in British Columbia, Canada and 2) height growth and wood density (EBVs), and deregressed estimated breeding values (DEBVs) as phenotypes. Representing models with (EBVs) and without (DEBVs) pedigree structure. Ridge regression best linear unbiased predictor (RR-BLUP) and generalized ridge regression (GRR) were used to assess their predictive accuracies over space (within site, cross-sites, multi-site, and multi-site to single site) and time (age-age/ trait-trait). Results The RR-BLUP and GRR models produced similar predictive accuracies across the studied traits. Within-site GS prediction accuracies with models trained on EBVs were high (RR-BLUP: 0.79–0.91 and GRR: 0.80–0.91), and were generally similar to the multi-site (RR-BLUP: 0.83–0.91, GRR: 0.83–0.91) and multi-site to single-site predictive accuracies (RR-BLUP: 0.79–0.92, GRR: 0.79–0.92). Cross-site predictions were surprisingly high, with predictive accuracies within a similar range (RR-BLUP: 0.79–0.92, GRR: 0.78–0.91). Height at 12 years was deemed the earliest acceptable age at which accurate predictions can be made concerning future height (age-age) and wood density (trait-trait). Using DEBVs reduced the accuracies of all cross-validation procedures dramatically, indicating that the models were tracking pedigree (family means), rather than marker-QTL LD. Conclusions While GS models' prediction accuracies were high, the main driving force was the pedigree tracking rather than LD. It is likely that many more markers are needed to increase the chance of capturing the LD between causal genes and markers.
Data from: Microevolution in time and space: SNP analysis of historical DNA reveals dynamic signatures of selection in Atlantic cod
Little is known about how quickly natural populations adapt to changes in their environment and how temporal and spatial variation in selection pressures interact to shape patterns of genetic diversity. We here address these issues with a series of genome scans in four overfished populations of Atlantic cod (Gadus morhua) studied over an 80-year period. Screening of >1000 gene-associated single-nucleotide polymorphisms (SNPs) identified 77 loci that showed highly elevated levels of differentiation, likely as an effect of directional selection, in either time, space or both. Exploratory analysis suggested that temporal allele frequency shifts at certain loci may correlate with local temperature variation and with life history changes suggested to be fisheries induced. Interestingly, however, largely nonoverlapping sets of loci were temporal outliers in the different populations and outliers from the 1928 to 1960 period showed almost complete stability during later decades. The contrasting microevolutionary trajectories among populations resulted in sequential shifts in spatial outliers, with no locus maintaining elevated spatial differentiation throughout the study period. Simulations of migration coupled with observations of temporally stable spatial structure at neutral loci suggest that population replacement or gene flow alone could not explain all the observed allele frequency variation. Thus, the genetic changes are likely to at least partly be driven by highly dynamic temporally and spatially varying selection. These findings have important implications for our understanding of local adaptation and evolutionary potential in high gene flow organisms and underscore the need to carefully consider all dimensions of biocomplexity for evolutionarily sustainable management.
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.