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309 results for “Scale effects”
Simulated treatment effects on bird communities inform landscape‐scale dry conifer forest management
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Input data to model multiple effects of large-scale deployment of grass in crop-rotations at European scale
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Data for: Strong effects of food quality on host life history do not scale to impact parasitoid efficacy or life history
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Data from: An effective method for ecosystem-scale manipulation of bird abundance and species richness
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Scale-dependent effects of biodiversity and stability on marine ecosystem dynamics
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Data from: harnessing the power of regional baselines for broad-scale genetic stock identification: a multistage, integrated, and cost-effective approach
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Remarkable effects of microbial factors on soil phosphorus bioavailability: a country-scale study
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Habitat quality effects on the abundance of a coral-dwelling fish across spatial scales
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The effects of land-use history and the contemporary landscape on non-native plant invasion at local and regional scales in the French Broad Watersheds, 2007
Determining what factors explain the distribution of non-native invasive plants that can spread in forest-dominated landscapes could advance understanding of the invasion process and identify forest areas most susceptible to invasion. The researchers conducted roadside surveys to determine the presence and abundance of 15 non-native plant species known to invade forests in western North Carolina, USA. Prior to sampling, the researchers identified 15 non-native invasive plant species that were of concern in the study region. Generalized linear models were used to examine how contemporary and historic land use, landscape context, and topography influenced presence and abundance of the species at local and regional scales.
Data from: Effects of roads and land use on frog distributions across spatial scales and regions in the eastern and central United States
Aim: Understanding the scales over which land use affects animal populations is critical for conservation planning, and it can provide information about the mechanisms that underlie correlations between species distributions and land use. We used a citizen-science database of anuran surveys to examine the relationship between road density, land use, and the distribution of frogs and toads across spatial scales and regions of the United States. Location: Eastern and Central United States Methods: We compiled data on anuran occupancy collected from 1999-2013 across 13 states in the North American Amphibian Monitoring Program, a citizen science survey of calling frogs. These data were indexed to measures of land use within buffers ranging from 300 m to 10 km. Results: The negative effects of road density and development on anuran richness were strongest at the smallest scales (300 – 1000 m), and this pattern was consistent across regions. In contrast, the relationships of anuran richness to agriculture and forest cover were similar across local scales but varied among regions. Richness had a negative relationship with agriculture/ forest loss in the Midwest but a positive relationship with agriculture in the Northeast. Anuran richness was more closely related to primary/secondary road density than to rural road density, and the negative effects of larger roads increased at smaller scales. Individual species differed in the scales over which roads and development affected their distributions, but these differences were not closely related to either body size or movement ability. Main conclusions: This study further refines our understanding of the relationship between roads and amphibian populations and highlights the need for research into the specific mechanisms by which roads affect amphibians. Additionally, we find that relationships between land use and species richness can differ substantially across regions, demonstrating that one should use caution in generalizing from one region to another, even when species composition is similar.
STAVER: A Standardized Benchmark Dataset-Based Algorithm for Effective Variation Reduction in Large-Scale DIA-MS Data
<p>This project focuses on developing and applying STAVER, an innovative DIA algorithm designed to eliminate non-biological noise and variability from the large-scale DIA-MS study dataset analyses. STAVER is a flexible framework that utilizes prior knowledge regarding peptide separation coordinates (RT) and fragment ion intensities from the standard benchmark datasets, which effectively mitigates non-biological noise potential during library searches, enhancing spectrum identifications and protein quantification accuracy. Furthermore, the robustness and broad applicability of STAVER were validated in multiple large-scale DIA datasets from different platforms and laboratories, demonstrating significantly improved precision and reproducibility of protein quantification. It facilitates the comparative and integrative analysis of DIA datasets across different platforms and laboratories, enhancing the consistency and reliability of findings in clinical research. The project aims to promote the adoption of hybrid library search and improve the sensitivity and quality of DIA proteomics data through the open-source STAVER software package.</p>
Large-scale facilitative effects of Vachellia caven
<p>The importance of nurse plants structuring plant communities is well appreciated at local scales, yet the effect of a single nurse on large scales has been neglected in analyses. So far, studies only use environmental gradients within one type of ecosystem and tend to generalize the nurse effects. To assess how the effect of a single nurse species is modulated by different environmental settings, interactions between the shrub <em>Vachellia caven</em> and the surrounding plant communities were evaluated at 481 paired plots (outside vs underneath the plant crown), in 39 sites across two distribution ranges, the Mediterranean west and the mostly subtropical east of the Andes mountains (covering ca. 2x10 6 km<sup>2</sup>). Cover, abundance, and richness of perennial plants underneath and outside <em>V. caven </em>were used as response variables to estimate an index indicative of plant interactions (RII) and tested how this was affected by the rainfall gradient and distribution range.</p> <p>Overall, RII responses to rainfall gradients had low conditional R<sup>2</sup> (~0.25) at this large-scale of analysis, but were significantly different between ranges: the RII followed a quadratic trend across the rainfall gradient in the western range, while this relationship was positive and close to linear at the eastern range. Then, by projecting the RII models (i.e., for abundance, cover, and richness) spatially through a consensus map, we show that most positive effects of <em>V. caven</em> are geographically found in dissimilar areas: the central part of Chile (western range) and across the Paraná river (eastern range). When local fine-scale predictors (i.e., annual herbs cover and height, and herbivores feces cover), were used to model each response variable at the plot level (underneath or outside <em>V. caven</em>) similar trends were kept as when considering only large-scale predictors.</p> <p>Synthesis: Here, we show that the effect of the same nurse species on neighbouring plant communities can be very different depending on ranges of distribution, stressing that its ecological function cannot be generalized and not only depends on local factors but also is large-scale context-dependent. </p>
Disentangling effects of climate and land use on biodiversity and ecosystem services – a multi-scale experimental design
<p>1. Climate and land-use change are key drivers of environmental degradation in the Anthropocene, but too little is known about their interactive effects on biodiversity and ecosystem services. Long-term data on biodiversity trends are currently lacking. Furthermore, previous ecological studies have rarely considered climate and land use in a joint design, did not achieve variable independence or lost statistical power by not covering the full range of environmental gradients.</p> <p>2. Here, we introduce a multi-scale space-for-time study design to disentangle effects of climate and land use on biodiversity and ecosystem services. The site selection approach coupled extensive GIS-based exploration and correlation heatmaps with a crossed and nested design covering regional, landscape and local scales. Its implementation in Bavaria (Germany) resulted in a set of study plots that maximize the potential range and independence of environmental variables at different spatial scales.</p> <p>3. Stratifying the state of Bavaria into five climate zones (reference period 1981–2010) and three prevailing land-use types, i.e. near-natural, agriculture and urban, resulted in 60 study regions (5.8x5.8 km quadrants) covering a mean annual temperature gradient of 5.6–9.8 °C and a spatial extent of ~310x310 km. Within these regions, we nested 180 study plots located in contrasting local land-use types, i.e. forests, grasslands, arable land or settlement (local climate gradient 4.5–10 °C). This approach achieved low correlations between climate and land use (proportional cover) at the regional and landscape scale with |r≤0.33| and |r≤0.29|, respectively. Furthermore, using correlation heatmaps for local plot selection reduced potentially confounding relationships between landscape composition and configuration for plots located in forests, arable land and settlements.</p> <p>4. The suggested design expands upon previous research in covering a significant range of environmental gradients and including a diversity of dominant land-use types at different scales within different climatic contexts. It allows independent assessment of the relative contribution of multi-scale climate and land use on biodiversity and ecosystem services. Understanding potential interdependencies among global change drivers is essential to develop effective restoration and mitigation strategies against biodiversity decline, especially in expectation of future climatic changes. Importantly, this study also provides a baseline for long-term ecological monitoring programs.</p>
Data from: Scale-dependence of landscape heterogeneity effects on plant invasions
<p><span>Invasive alien species are amongst the most concerning threats to native biodiversity worldwide, and the level of landscape heterogeneity is considered to affect spatial patterns of their occurrence and spread. However, as previous studies on these associations report contrasting results, the role of landscape heterogeneity on its susceptibility to invasions remains poorly understood. Landscape heterogeneity is usually described by two measures: configuration and composition. Both measures may differently affect invasive species and these impacts may be additionally scale-dependent. Nevertheless, their relative contribution to invasion patterns is poorly known. We investigated the effect of two landscape heterogeneity components: configuration (edge density) and composition (number and evenness of land-cover types) measured at different spatial scales (from within 0.25 km to 5 km of the studied localities) on the local abundance of one of the most invasive alien plant species in Europe, the North American goldenrods (<em>Solidago canadensis</em> and <em>S. gigantea</em>). Using publicly available geospatial environmental data and a novel method based on remote analysis of Google Street View images, we collected and analyzed large dataset on goldenrod occurrence along 1347 roadside transects in agricultural landscapes of Poland. Both the compositional and configurational heterogeneity were positively associated with the local abundance of goldenrods, however the effect size of these relationships was dependent on spatial scale. While abundance-heterogeneity associations were most pronounced at the largest spatial scale for compositional heterogeneity, the pattern was the opposite for configurational heterogeneity. Landscape heterogeneity is a clear correlate of plant invasion potential, with occurrences of invasive plants generally higher in more heterogeneous landscapes. However, scale-dependence of this association means that researchers and practitioners may miss the association if only concentrating on a single spatial scale. While increasing heterogeneity of rural landscapes is widely introduced as a way to promote farmland biodiversity, we show that it may also support invasive plants and thus conflict with original goals of biodiversity-oriented strategies. Therefore, we suggest implementing regular management and eradication schemes in most heterogeneous landscapes. Finally, we demonstrate how remote analysis of plant invasions using existing imagery can advance our understanding of invasion biology.</span></p>
Simulation files to accompany the manuscript "Two-dimensional basin-scale seismic site effects in the Kitimat Valley, British Columbia, Canada: A practical example of using a fast hybrid FE/BE method"
<p>Simulation files to accompany the two-dimensional basin-scale seismic site effects investigation in the Kitimat valley, located in the northern coastal region of British Columbia, Canada.</p>
Effects of variations of SUSY breaking scale on neutrino parameters at low energy scale under radiative corrections
<p>The paper addresses the effects of the variations of the SUSY breaking scale $m_s$ in the range (2-14) TeV on the three neutrino masses and mixings, in running the renormalization group equations (RGEs) for different input values of high energy seesaw scale $M_R$, in both normal and inverted hierarchical neutrino mass models. The present investigation is a continuation of the earlier works based on the variation of $m_s$ scale. Two approaches are adopted one after another - bottom-up approach for running gauge and Yukawa couplings from low to high energy scale, followed by the top-down approach from high to low energy scale for running neutrino parameters defined at high energy scale, along with gauge and Yukawa couplings. A self-complementarity relation among three mixing angles is also employed in the analysis. Significant effect due to radiative corrections on neutrino parameters with the variation of SUSY breaking scale $m_s$, is observed.</p>
Orbital effect on millennial-scale East Asian summer monsoon variability during the Holocene
<p>Data for reproducing figures in journal article submitted to JGR: Atmospheres in June 2022.</p> <p>Data generated from hosing simulations of the 8.2 ka BP and 4.2 ka BP events using the CESM1.2.</p>
Scale-dependent environmental effects on phenotypic distributions in Heliconius butterflies
<p>Examining how environmental factors influence phenotypic distribution might provide valuable information about local adaptation, divergence, and speciation. The red-yellow Müllerian mimicry ring of <em>Heliconius</em> butterflies displays a wide range of color patterns across the Neotropics and is involved in several hybrid zones, making it an excellent system to study color phenotypic distribution. Using a multiscale distribution strategy, we studied whether different phenotypes of the distantly related species <em>H. erato</em> and <em>H. melpomene,</em> belonging to the red-yellow mimetic ring, are associated with different environmental conditions. We show that environmental gradients (particularly heat and precipitation factors) drive <em>Heliconius</em> phenotypic distributions, but that phenotype and environmental correlations vary with spatial scale. While co-mimics are frequently found in similar environments at a broad scale, patterns at the local level are not necessarily consistent (different variables are the best predictors of phenotypic occurrence in different areas) or congruent (co-mimic pairs show distinct associations with the environment). Thus, large-scale analysis may help to identify how environmental heterogeneity influences broad mimic phenotypic distributions, but local studies are needed to understand the context-dependent biotic, abiotic, and historical mechanisms that drive finer-scale phenotypic shifts.</p>
Combined effects of stream hydrology and land use on basin-scale hyporheic zone denitrification in the Columbia River Basin
<p><strong>This data includes inputs and outputs of a coupled carbon-nitrogen river corridor model (RCM) for the Columbia River Basin and sensitivity results with varying substrate concentrations, and random forest model results with key model inputs/watershed/stream variables. The detailed descriptions of the individual files are included in the readme.txt file. </strong></p>
Data for "Testing for variation in photoperiodic plasticity in a butterfly: inconsistent effects of circadian genes between geographic scales" (Ecology and Evolution, accepted manuscript)
<p>Raw data and analysis scripts belonging to <em>Testing for variation in photoperiodic plasticity in a butterfly: inconsistent effects of circadian genes between geographic scales</em> (Ecology and Evolution, accepted manuscript).</p> <p>Includes data from a photoperiodic assay with larvae of the speckled wood butterfly, <em>Pararge aegeria</em>, as well as a small bioinformatic analysis of SNP variation in two circadian candidate genes.</p> <p>List of files:</p> <table> <tbody> <tr> <td>statistics_and_figures.R</td> <td>Statistical analysis of phenotyping experiment; drawing figures</td> </tr> <tr> <td>variant_calling.sh</td> <td>Shell script for mapping sequencing reads; calling and tabulating SNPs</td> </tr> <tr> <td>experiment_diapause.txt</td> <td>Data from phenotyping experiment, for analysis of diapause induction</td> </tr> <tr> <td>experiment_larval</td> <td>Data from phenotyping experiment, for analysis of larval development</td> </tr> <tr> <td>snptable_timeless</td> <td>Tabulated allele frequencies for exonic SNPs in timeless</td> </tr> <tr> <td>snptable_period</td> <td>Tabulated allele frequencies for exonic SNPs in period</td> </tr> </tbody> </table>
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.