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99 results for “scale-dependency”
Scale-dependent diversity-biomass relationships can be driven by tree mycorrhizal association and soil fertility
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Scale-dependent effects of biodiversity and stability on marine ecosystem dynamics
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Data and R code from: Relics of beavers past: time and population density drive scale-dependent patterns of ecosystem engineering
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Data from: Mesocosm experiment reveals scale-dependence of movement tendencies in sticklebacks
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Data from: Pattern and process in hominin brain size evolution are scale-dependent
A large brain is a defining feature of modern humans, yet there is no consensus regarding the patterns, rates, and processes involved in hominin brain size evolution. We use a reliable proxy for brain size in fossils, endocranial volume (ECV), to better understand how brain size evolved at both clade- and lineage-level scales. For the hominin clade overall, the dominant signal is consistent with a gradual increase in brain size. This gradual trend appears to have been generated primarily by processes operating within hypothesized lineages – 64% or 88% depending on whether one uses a more or less speciose taxonomy, respectively. These processes were supplemented by the appearance in the fossil record of larger-brained Homo species and the subsequent disappearance of smaller-brained Australopithecus and Paranthropus taxa. When the estimated rate of within-lineage ECV increase is compared to an exponential model that operationalizes generation-scale evolutionary processes, it suggests that the observed data were the result of episodes of directional selection interspersed with periods of stasis and/or drift; all of this occurs on too fine a time scale to be resolved by the current human fossil record, thus producing apparent gradual trends within lineages. Our findings provide a quantitative basis for developing and testing scale-explicit hypotheses about the factors that led brain size to increase during hominin evolution.
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>
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>
Figure 15 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model
Figure 15. Species accumulation curve for tintinnid ciliates diversity in the Arctic Ocean.
Figure 7 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model
Figure 7. Species accumulation curve for tintinnid ciliates diversity in the Mediterranean Sea.
Figure 19 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model
Figure 19. Species accumulation curve for tintinnid ciliates diversity in global ocean.
Figure 22 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model
Figure 22. The Whittaker index dependence on the distance (power function).
Figure 21 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model
Figure 21. The Whittaker index values in different water areas.
Figure 17 in Biogeography of marine tintinnid ciliates (Ciliophora, Tintinnida): a Scale-Dependent Model
Figure 17. Species accumulation curve for tintinnid ciliates diversity in the Southern Ocean.
Biodiversity scale-dependence and opposing multi-level correlations underlie differences among taxonomic, phylogenetic, and functional diversity
<p><b>Aim:</b> Biodiversity is a multi-dimensional property of biological communities that represents different information depending on how it is measured, but how dimensions relate to one another and under what conditions is not well understood. We explore how taxonomic, phylogenetic, and functional diversity can differ in scale-of-effect dependence and habitat-biodiversity relationships, and subsequently how spatial differences among biodiversity dimensions may arise.</p> <p><b>Location:</b> Nebraska, United States</p> <p><b>Time period:</b> May-July 2016, 2017</p> <p><b>Major taxa studied:</b> Birds</p> <p><b>Methods:</b> Across 2016 and 2017, we conducted 2,641 point counts at 781 sites. We modeled the occupancy of 141 species using Bayesian Bernoulli-Bernoulli hierarchical logistic regressions. We calculated species richness (SR), phylogenetic diversity (PD), and functional diversity (FD) for each site and year based on predicted occupancy, accounting for imperfect detection. Using Bayesian latent indicator scale selection and multivariate modeling, we quantified the spatial scales-of-effect that best explained the relationships between environmental characteristics and SR, PD, and FD. Additionally, we decomposed the residual between- and within-site biodiversity correlations using our repeated measures design.</p> <p><b>Results:</b> We demonstrate spatial differences among biodiversity predictions, arising from scale-dependence in habitat-biodiversity relationships and variation in correlation structure among biodiversity dimensions. Although relationships between specific land cover types and SR, PD and FD were qualitatively similar, the spatial scales at which these variables were important in explaining biodiversity differed among dimensions. Between-site residual biodiversity correlations were negative, yet within-site biodiversity residual correlations were positive.</p> <p><b>Main conclusions:</b> Our results demonstrate how spatial differences among biodiversity dimensions may arise from biodiversity-specific scale-dependent habitat relationships, low shared environmental correlations and opposing residual correlations between dimensions, which suggest that single-scale and single-dimension analyses are not entirely appropriate for quantifying habitat-biodiversity relationships. After accounting for shared habitat relationships, we found positive within-site residual correlations between taxonomic, phylogenetic, and functional diversity, suggesting that habitat change over time influenced all biodiversity dimensions relatively similarly. However, negative between-site residual correlation among biodiversity dimensions may indicate trade-offs in achieving maximum biodiversity across multiple biodiversity dimensions at any given location. Although habitat management can to a limited degree improve biodiversity relatively across all metrics, other environmental effects may ensure that not all facets of biodiversity can be maximized at once. If maximizing a specific biodiversity dimension is the goal, then care should be taken to consider these within-site residual correlations.</p>
Data from: Scale-dependent effects of landscape structure on pollinator traits, species interactions and pollination success
<p>Data: Plant-pollinator interactions, pollinator body size (inter-tegular distance, ITD) and plant reproductive success (number of seeds produced).<br><br>Data collected by Christie J. Webber. <br><br>Data collected in 14 experimental flowering plant patches during December 2012–February 2013. Patches were located in a 105 hectare sheep farm pasture in Oxford, North Canterbury, New Zealand (43°19'21"S 172°12'25"E).</p> <p>Files:</p> <ul> <li>Data_S1: contains plant-pollinator interactions sampled and pollinator inter-tegular distance (ITD). Data_S1 columns: patch ID where the interaction was recorded, plant species, pollinator ITD (mm), and pollinator family, genus and species.</li> <li>Data_S2: contains the number of seeds produced by each of the five flowers of each plant individual from each plant species on each patch. Data_S2 columns: patch ID where the measurement was taken, plant species, plant number (individual sampled), number of seeds.</li> </ul> <p>Dataset used in "Scale-dependent effects of landscape structure on pollinator traits, species interactions and pollination success" by G. Peralta, C.J. Webber, G.L.W. Perry, D.B. Stouffer, D.P. Vázquez and J.M. Tylianakis.</p>
Data for: Fear before food: Scale-dependence in elk habitat selection
<ol> <li>Habitat selection is a critical aspect of a species' ecology requiring complex decision-making that is both hierarchical and scale-dependent, since factors that influence selection may be nested or unequal across scales.</li> <li>Elk (<em>Cervus</em> <em>canadensis</em>) ranged widely across diverse habitats in North America prior to European settlement and subsequent eastern extirpation. Most habitat studies have occurred within their contemporary western range, even after eastern elk reintroductions began. As habitat selection can vary by geographic location, available cover, season, and diel period, it is important to understand how a non-migratory, reintroduced population in northern Wisconsin, USA is limited by the lack of variation in topography, elevation, and vegetation.</li> <li>We tested scale-dependent habitat selection on 79 adult elk from 2017–2020. We used resource selection functions across both temporal and spatial scales to understand differences in selection of topographic and environmental features.</li> <li>We found that selection varied both spatially and temporally and elk selected areas with the greatest potential to influence fitness at larger scales (i.e., landscape scale), meaning elk selected areas closer to escape cover and further from "risky" features (e.g., wolf territory centers, county roads and highways). We found stronger avoidance to wolf territory centers during spring, suggesting elk were selecting safer habitats during calving season. We found elk selected habitats with less canopy cover across both spatial scales and all seasons, suggesting that elk selected these areas for better access to forage as forest stands in early seral stages have greater nutritional value and forage biomass than closed-canopy forests and direct solar radiation to provide warmth in the cooler seasons.</li> <li>This study highlights how processes at different spatial and temporal scales influence species' decision-making. It provides insight into the complexity of making informed decisions in which an individual is responding to their immediate environment while simultaneously making decisions in the context of the larger landscape. Scale-dependent behavior is crucial to understand within specific geographic regions as these decisions scale up to influence population dynamics. </li> </ol>
Scale-dependence of ecological assembly rules: insights from empirical datasets and joint species distribution modelling
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Data from: Scale-dependent effects of landscape structure on pollinator traits, species interactions and pollination success
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Biodiversity scale-dependence and opposing multi-level correlations underlie differences among taxonomic, phylogenetic, and functional diversity
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Data from: Pattern and process in hominin brain size evolution are scale-dependent
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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.