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677 results for “time of use”
Fecal standing crop with real time correction using scat detection dogs to estimate population density
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Data from: An inexpensive and open-source method to study large terrestrial animal diet and behavior using time-lapse video and GPS
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Data from: Evaluating consumptive and nonconsumptive predator effects on prey density using field times series data
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Influences of temperature and time on habitat use patterns of a semi-aquatic turtle
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Divergence time estimation using ddRAD data and an isolation-with-migration model applied to water vole populations of Arvicola
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Exploring relationships between time of day and pollinator activity in the context of pesticide use - data
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Data from: Evolution of defence and herbivory in introduced plants - testing enemy release using a known source population, herbivore trials and time since introduction
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Mitigating ecosystem service tradeoffs in rangelands by using grazing duration and timing to manage water quality
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Simulated population time series used to build and test a model of accuracy for population-based global biodiversity indicators
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Insights from empirical analyses and simulations on using multiple fossil calibrations with relaxed clocks to estimate divergence times
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Data from: COPD screening using time–frequency features of self-recorded respiratory sounds
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Storm-Time Plasma Pressure Inferred from Multi-Mission Measurements and Its Validation using Van Allen Probes Particle Data
<p>Data associated with Space Weather Journal manuscript submission titled: "Storm-Time Plasma Pressure Inferred from Multi-Mission Measurements and Its Validation using Van Allen Probes Particle Data". This includes all the digital data that was used in constructing the Figures from the main text, along with files containing the fit set of coefficients and parameters for the model, and files describing the subset of magnetometer used for fitting the model. </p>
Data from: How do habitat amount and habitat fragmentation drive time-delayed responses of biodiversity to land-use change?
<p><span>Land-use change is a root cause of the extinction crisis, but links between habitat change and biodiversity loss are not fully understood. While there is evidence that habitat loss is an important extinction driver, the relevance of habitat fragmentation remains debated. Moreover, while time-delays of biodiversity responses to habitat transformation are well-documented, time-delayed effects have been ignored in the habitat loss vs. fragmentation debate. Here, using a hierarchical Bayesian multi- species occupancy framework, we systematically tested for time-delayed responses of bird and mammal communities to habitat loss and to habitat fragmentation. We focused on the Argentine Chaco, where deforestation has been widespread recently. We used an extensive field dataset on birds and mammals, along with a time series of annual woodland maps from 1985-2016 covering recent and historical habitat transformations. Contemporary habitat amount explained bird and mammal occupancy better than past habitat amount. However, occupancy was affected more by past rather than recent fragmentation, indicating a time-delayed response to fragmentation. Considering past landscape patterns is therefore crucial for understanding current biodiversity patterns. Not accounting for land-use history ignores the possibility of extinction debt and can thus obscure impacts of fragmentation, potentially explaining contrasting findings of habitat loss vs. fragmentation studies.</span></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: Phylogenetic relationships and timing of diversification in gonorynchiform fishes inferred using nuclear gene DNA sequences (Teleostei: Ostariophysi)
The Gonorynchiformes are the sister lineage of the species-rich Otophysi and provide important insights into the diversification of ostariophysan fishes. Phylogenies of gonorynchiforms inferred using morphological characters and mtDNA gene sequences provide differing resolutions with regard to the sister lineage of all other gonorynchiforms (Chanos vs. Gonorynchus) and support for monophyly of the two miniaturized lineages Cromeria and Grasseichthys. In this study the phylogeny and divergence times of gonorynchiforms are investigated with DNA sequences sampled from nine nuclear genes and a published morphological character matrix. Bayesian phylogenetic analyses reveal substantial congruence among individual gene trees with inferences from eight genes placing Gonorynchus as the sister lineage to all other gonorynchiforms. Seven gene trees resolve Cromeria and Grasseichthys as a clade, supporting previous inferences using morphological characters. Phylogenies resulting from either concatenating the nuclear genes, performing a multispecies coalescent species tree analysis, or combining the morphological and nuclear gene DNA sequences resolve Gonorynchus as the living sister lineage of all other gonorynchiforms, strongly support the monophyly of Cromeria and Grasseichthys, and resolve a clade containing Parakneria, Cromeria, and Grasseichthys. The morphological dataset, which includes 13 gonorynchiform fossil taxa that range in age from Early Cretaceous to Eocene, was analyzed in combination with DNA sequences from the nine nuclear genes and a relaxed molecular clock to estimate times of evolutionary divergence. This "tip dating" strategy accommodates uncertainty in the phylogenetic resolution of fossil taxa that provide calibration information in the relaxed molecular clock analysis. The estimated age of the most recent common ancestor (MRCA) of living gonorynchiforms is slightly older than estimates from previous node dating efforts, but the molecular tip dating estimated ages of Kneriinae (Kneria, Parakneria, Cromeria, and Grasseichthys) and the two paedomorphic lineages, Cromeria and Grasseichthys, are considerably younger.
Data from: Using time series analysis to characterize evolutionary and plastic responses to environmental change: a case study of a shift toward earlier migration date in sockeye salmon
Environmental change can shift the phenotype of an organism through either evolutionary or nongenetic processes. Despite abundant evidence of phenotypic change in response to recent climate change, we typically lack sufficient genetic data to identify the role of evolution. We present a method of using phenotypic data to characterize the hypothesized role of natural selection and environmentally driven phenotypic shifts (plasticity). We modeled historical selection and environmental predictors of interannual variation in mean population phenotype using a multivariate state-space model framework. Through model comparisons, we assessed the extent to which an estimated selection differential explained observed variation better than environmental factors alone. We applied the method to a 60-year trend toward earlier migration in Columbia River sockeye salmon Oncorhynchus nerka, producing estimates of annual selection differentials, average realized heritability, and relative cumulative effects of selection and plasticity. We found that an evolutionary response to thermal selection was capable of explaining up to two-thirds of the phenotypic trend. Adaptive plastic responses to June river flow explain most of the remainder. This method is applicable to other populations with time series data if selection differentials are available or can be reconstructed. This method thus augments our toolbox for predicting responses to environmental change.
Data from: Phylogenetic relationships within the lizard clade Xantusiidae: using trees and divergence times to address evolutionary questions at multiple levels
Xantusiidae (night lizards) is a clade of small-bodied, cryptic lizards endemic to the New World. The clade is characterized by several features that would benefit from interpretation in a phylogenetic context, including: (1) monophyletic status of extant taxa Cricosaura, Lepidophyma, and Xantusia; (2) a species endemic to Cuba (Cricosaura typica) of disputed age; (3) origins of the parthenogenetic species of Lepidophyma; (4) pronounced micro-habitat differences accompanied by distinct morphologies in both Xantusia and Lepidophyma; and (5) placement of Xantusia riversiana, the only vertebrate species endemic to the California Channel Islands, which is highly divergent from its mainland relatives. This study incorporates extensive new character data from multiple gene regions to investigate the phylogeny of Xantusiidae using the most comprehensive taxonomic sampling available to date. Parsimony and partitioned Bayesian analyses of more than 7 kb of mitochondrial and nuclear sequence data from 11 loci all confirm that Xantusiidae is monophyletic, and comprises three well-supported clades: Cricosaura, Xantusia, and Lepidophyma. The Cuban endemic Cricosaura typica is well supported as the sister to all other xantusiids. Estimates of divergence time indicate that Cricosaura diverged from the (Lepidophyma + Xantusia) clade ∼81 million years ago (Ma), a time frame consistent with the separation of the Antilles from North America. Our results also confirm and extend an earlier study suggesting that parthenogenesis has arisen at least twice within Lepidophyma without hybridization, that rock-crevice ecomorphs evolved numerous times (>9) within Xantusia and Lepidophyma, and that the large-bodied Channel Island endemic X. riversiana is a distinct, early lineage that may form the sister group to the small-bodied congeners of the mainland.
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: Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011
Detailed information on the spatiotemporal dynamic in surface water bodies is important for quantifying the effects of a drying climate, increased water abstraction and rapid urbanization on wetlands. The Swan Coastal Plain (SCP) with over 1500 wetlands is a global biodiversity hotspot located in the southwest of Western Australia, where more than 70% of the wetlands have been lost since European settlement. SCP is located in an area affected by recent climate change that also experiences rapid urban development and ground water abstraction. Landsat TM and ETM+ imagery from 1999 to 2011 has been used to automatically derive a spatially and temporally explicit time-series of surface water body extent on the SCP. A mapping method based on the Landsat data and a decision tree classification algorithm is described. Two generic classifiers were derived for the Landsat 5 and Landsat 7 data. Several landscape metrics were computed to summarize the intra and interannual patterns of surface water dynamic. Top of the atmosphere (TOA) reflectance of band 5 followed by TOA reflectance of bands 4 and 3 were the explanatory variables most important for mapping surface water bodies. Accuracy assessment yielded an overall classification accuracy of 96%, with 89% producer's accuracy and 93% user's accuracy of surface water bodies. The number, mean size, and total area of water bodies showed high seasonal variability with highest numbers in winter and lowest numbers in summer. The number of water bodies in winter increased until 2005 after which a decline can be noted. The lowest numbers occurred in 2010 which coincided with one of the years with the lowest rainfall in the area. Understanding the spatiotemporal dynamic of surface water bodies on the SCP constitutes the basis for understanding the effect of rainfall, water abstraction and urban development on water bodies in a spatially explicit way.
Data from: Use of auto-germ to model germination timing in the Sagebrush-steppe
Germination timing has a strong influence on direct seeding efforts, and therefore is a closely tracked demographic stage in a wide variety of wildland and agricultural settings. Predictive seed germination models, based on soil moisture and temperature data in the seed zone are an efficient method of estimating germination timing. We utilized Visual Basic for Applications (VBA) to create Auto-Germ, which is an Excel workbook that allows a user to estimate field germination timing based on wet-thermal accumulation models and field temperature and soil moisture data. To demonstrate the capabilities of Auto-Germ, we calculated various germination indices and modeled germination timing for 11 different species, across 6 years, and 10 Artemisia-steppe sites in the Great Basin of North America to identify the planting date required for 50% or more of the simulated population to germinate in spring (1 March or later), which is when conditions are predicted to be more conducive for plant establishment. Both between and within the species, germination models indicated that there was high temporal and spatial variability in the planting date required for spring germination to occur. However, some general trends were identified, with species falling roughly into three categories, where seeds could be planted on average in either fall (Artemisia tridentata ssp. wyomingensis and Leymus cinereus), early winter (Festuca idahoensis, Poa secunda, Elymus lanceolatus, Elymus elymoides, and Linum lewisii), or mid-winter (Achillea millefolium, Elymus wawawaiensis , and Pseudoroegneria spicata) and still not run the risk of germination during winter. These predictions made through Auto-Germ demonstrate that fall may not be an optimal time period for sowing seeds for most non-dormant species if the desired goal is to have seeds germinate in spring.
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.