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309 results for “Scale effects”
Data from: Ecological effects on metabolic scaling amphipod responses to fish predators in freshwater springs
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Data from: Gauging scale effects and biogeographical signals in similarity distance decay analyses: an Early Jurassic ammonite case study
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Data from: Short-term climate change manipulation effects do not scale up to long-term legacies: effects of an absent snow cover on boreal forest plants
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Long-term monitoring in endangered woodlands shows effects of multi-scale drivers on bird occupancy
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Effect of ecological factors on fine-scale patterns of social structure in African lions
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Data from: Which landscape size best predicts the influence of forest cover on restoration success? – A global meta-analysis on the scale of effect
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Data from: Landscape genetic analyses reveal fine-scale effects of forest fragmentation in an insular tropical bird
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Data from: Hidden founder effects: small-scale spatial genetic structure in recently established populations of the grassland specialist plant Anthyllis vulneraria
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Data from: Hurricane effects on Neotropical lizards span geographic and phylogenetic scales
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Data from: Scale-dependent effects of forest restoration on Neotropical fruit bats
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Predictive multi-scale occupancy models at range-wide extents: effects of habitat and human disturbance on distributions of wetland birds
<p><span><i>Aim:</i> Predicting distributions is fundamental to ecology, yet hindered by spatially-restricted sampling, scale-dependent relationships, and detection error associated with field surveys. Predictive species distribution models (SDMs) are nonetheless vital for conservation of many species. We developed a framework for building predictive SDMs with multi-scale data, and used it to develop range-wide breeding-season SDMs for 14 marsh bird species of concern.</span></p> <p><span><i>Location: </i>USA.</span></p> <p><span><i>Methods: </i>We built SDMs using data from range-wide surveys conducted over 14 years, and habitat and disturbance covariates measured at multiple spatial scales. We built hierarchical occupancy models that included heterogeneity in detectability during sampling, and used Bayesian model selection to regulate model complexity (covariates and scales) based explicitly on spatial predictive abilities. We thus integrated model selection for optimizing out-of-sample prediction, range-wide sampling over broad conditions, multi-scale analyses and scale-optimization, and species-specific detectability for a suite of wide-ranging species. </span></p> <p><span><i>Results: </i>Distributions of marsh birds were affected by local wetland conditions, but also by agricultural, urban, and hydrologic disturbances operating from local scales (100 – 500 m) to the watershed level. Variables measuring human disturbances improved prediction for most species, and every species was affected by attributes at > 1 scale. Five species showed evidence for continental-scale range contraction during the study.</span></p> <p><span><i>Main conclusions: </i>We demonstrate how hierarchical occupancy models can be optimized for prediction across a species' range at the extent of a continent while also accounting for imperfect detection, and thus describe a generalizable approach that can be used for any species. We provide the first data-driven, empirical SDMs built at the range-wide extent for most of our 14 study species and demonstrate that previous studies focused on local distributions and the effects of fine-scale wetland vegetation missed important broad-scale drivers of occupancy for marsh birds. </span></p>
A Large Scale Study On the Effectiveness of Manual and Automatic Unit Test Generation
<p>Recently, an increasingly large amount of effort has been devoted to implementing tools to generate unit test suites automatically. Previous studies have investigated the effectiveness of these tools by comparing automatically generated test suites (ATSs) to manually written test suites (MTSs). Most of these studies report that ATSs can achieve higher code coverage, or even mutation coverage, than MTSs, particularly when suites are generated from defective code. However, these studies usually consider a limited amount of classes or subject programs, while the adoption of such tools in the industry is still low. This work aims to compare the effectiveness of ATSs and MTSs when applied as regression test suites. We conduct an empirical study, using ten programs (1368 classes), written in Java, that already have MTSs and apply two sophisticated tools that automatically generate test cases: Randoop and EvoSuite. To evaluate the test suites’ effectiveness, we use line and mutation coverage. Our results indicate that MTSs are, in general, more effective than ATSs regarding the investigated metrics. Moreover, the number of generated test cases may not indicate test suites’ effectiveness. Furthermore, there are situations when ATSs are more effective, and even when ATSs and MTSs can be complementary.</p>
Supplementary material 3 from: Manjarrés-Hernández A, Guisande C, García-Roselló E, Heine J, Pelayo-Villamil P, Pérez-Costas E, González-Vilas L, González-Dacosta J, R. Duque S, Granado-Lorencio C, Lobo JM (2021) Predicting the effects of climate change on future freshwater fish diversity at global scale. Nature Conservation 43: 1-24. https://doi.org/10.3897/natureconservation.43.58997
Appendix 2
Supplementary material 4 from: Manjarrés-Hernández A, Guisande C, García-Roselló E, Heine J, Pelayo-Villamil P, Pérez-Costas E, González-Vilas L, González-Dacosta J, R. Duque S, Granado-Lorencio C, Lobo JM (2021) Predicting the effects of climate change on future freshwater fish diversity at global scale. Nature Conservation 43: 1-24. https://doi.org/10.3897/natureconservation.43.58997
Appendix 3
Supplementary material 1 from: Manjarrés-Hernández A, Guisande C, García-Roselló E, Heine J, Pelayo-Villamil P, Pérez-Costas E, González-Vilas L, González-Dacosta J, R. Duque S, Granado-Lorencio C, Lobo JM (2021) Predicting the effects of climate change on future freshwater fish diversity at global scale. Nature Conservation 43: 1-24. https://doi.org/10.3897/natureconservation.43.58997
Appendix 1
Supplementary material 2 from: Manjarrés-Hernández A, Guisande C, García-Roselló E, Heine J, Pelayo-Villamil P, Pérez-Costas E, González-Vilas L, González-Dacosta J, R. Duque S, Granado-Lorencio C, Lobo JM (2021) Predicting the effects of climate change on future freshwater fish diversity at global scale. Nature Conservation 43: 1-24. https://doi.org/10.3897/natureconservation.43.58997
Table S1
Data from: Testing the scaling effects and mechanisms of N-induced biodiversity loss: evidence from a decade-long grassland experiment
Although extensive studies demonstrate that nitrogen (N) enrichment frequently reduces plant diversity within small quadrats (0.5 –4 m2), only a few studies have evaluated N effects on biodiversity across different spatial scales. We conducted the first experimental test of the scale dependence of N effects on species richness from a 10-year N treatment (1.75- 28 g N m−2 yr−1) in a typical steppe. We used species area relationship (SAR) to analyze the scale dependence of species loss with power model S = cAz (S is species number, A is area, c is intercept, and z is slope). Absolute species loss decreased at sampling area > 8 m2. Proportional species loss (compared to control) decreased and critical threshold (Ncrit) for biodiversity losses increased with sampling areas. These scale dependences were quantified as increasing slope (z-value) of SAR with N addition. Through SAR decomposition, we found that this overall positive effect was in response to positive effects of changes to the species abundance distribution over negative effects of overall species richness losses. Synthesis. As nitrogen (N) enrichment typically occurs at scales much larger than individual plots, understanding how N enrichment affects the scaling patterns of biodiversity is necessary for biodiversity conservation and ecosystem management in response to anthropogenic N deposition.
Data from: Direct and indirect genetic and fine-scale location effects on breeding date in song sparrows
Quantifying direct and indirect genetic effects of interacting females and males on variation in jointly expressed life-history traits is central to predicting microevolutionary dynamics. However, accurately estimating sex-specific additive genetic variances in such traits remains difficult in wild populations, especially if related individuals inhabit similar fine-scale environments. Breeding date is a key life-history trait that responds to environmental phenology and mediates individual and population responses to environmental change. However, no studies have estimated female (direct) and male (indirect) additive genetic and inbreeding effects on breeding date, and estimated the cross-sex genetic correlation, while simultaneously accounting for fine-scale environmental effects of breeding locations, impeding prediction of microevolutionary dynamics. We fitted animal models to 38 years of song sparrow (Melospiza melodia) phenology and pedigree data to estimate sex-specific additive genetic variances in breeding date, and the cross-sex genetic correlation, thereby estimating the total additive genetic variance while simultaneously estimating sex-specific inbreeding depression. We further fitted three forms of spatial animal model to explicitly estimate variance in breeding date attributable to breeding location, overlap among breeding locations and spatial autocorrelation. We thereby quantified fine-scale location variances in breeding date and quantified the degree to which estimating such variances affected the estimated additive genetic variances. The non-spatial animal model estimated nonzero female and male additive genetic variances in breeding date (sex-specific heritabilities: 0·07 and 0·02, respectively) and a strong, positive cross-sex genetic correlation (0·99), creating substantial total additive genetic variance (0·18). Breeding date varied with female, but not male inbreeding coefficient, revealing direct, but not indirect, inbreeding depression. All three spatial animal models estimated small location variance in breeding date, but because relatedness and breeding location were virtually uncorrelated, modelling location variance did not alter the estimated additive genetic variances. Our results show that sex-specific additive genetic effects on breeding date can be strongly positively correlated, which would affect any predicted rates of microevolutionary change in response to sexually antagonistic or congruent selection. Further, we show that inbreeding effects on breeding date can also be sex specific and that genetic effects can exceed phenotypic variation stemming from fine-scale location-based variation within a wild population.
Data from: Invasive plants have scale-dependent effects on diversity by altering species-area relationships
Although invasive plant species often reduce diversity, they rarely cause plant extinctions. We surveyed paired invaded and uninvaded plant communities from three biomes. We reconcile the discrepancy in diversity loss from invaders by showing that invaded communities have lower local richness but steeper species accumulation with area than that of uninvaded communities, leading to proportionately fewer species loss at broader spatial scales. We show that invaders drive scale-dependent biodiversity loss through strong neutral sampling effects on the number of individuals in a community. We also show that nonneutral species extirpations are due to a proportionately larger effect of invaders on common species, suggesting that rare species are buffered against extinction. Our study provides a synthetic perspective on the threat of invasions to biodiversity loss across spatial scales.
Few species, higher abundance or many species and lower abundance of birds of prey: effects of land use changes at different spatial scales
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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.