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FIGURE 5 in The influence of landscape at multiple spatial scales of the river basins at the Eastern Amazon fish assemblage
FIGURE 5 | The dbRDA graph displays the distribution of fish data according to the most explanatory (local, macroscale, and land use) variables selected in the distLM model. Environmental variables were chosen by Forward and best model by AIC. Species code: Brachyhypopomus brevirostris (Pbre), Pyrrhulina capim (Pcap), Nannostomus trifasciatus (Ntri), Gymnorhamphichthys rondoni (Gron), Iguanodectes rachovii (Irac), Denticetopsis epa (Dent). Abbreviations: Local variables: EM: Average distance from excavated margins, MA: Average margin angle, SIN: Stretch sinuosity, SF: Smooth flow, LB: Substrate leaf bank, OM: Substrate organic matter, pH, RF: Rapids flow; TD: Average of thalweg depth; SSA: Stream sand. Macroscale variables: CLY: Catchment clay average, CSL: Catchment slope average, SDY: Catchment soil density, CSA: Catchment substrate sand; Land use: UR_S: Urbanization in 30m buffer, PAS_L: Pasture in 60m buffer, AGR_T: agriculture on catchment, PAS_S: Pasture in 30m buffer.
FIGURE 2 in The influence of landscape at multiple spatial scales of the river basins at the Eastern Amazon fish assemblage
FIGURE 2 | Scheme showing different spatial scales from which land use types were quantified in four catchments of the Eastern Amazon.
FIGURE 1 in The influence of landscape at multiple spatial scales of the river basins at the Eastern Amazon fish assemblage
FIGURE 1 | Study area containing 76 streams distributed in four Eastern Amazon basins and land use distribution. Land use: represents all uses (e.g., pasture, agriculture, and urbanization).
FIGURE 4 in Fish responses to multiple scales in coastal blackwater Atlantic Forest streams in Southeast Brazil
FIGURE 4 | Redundancy analysis (RDA) explaining the relationship between selected local, landscape, and spatial variables and fish species. Vector lines indicate the relationship of significant environmental variables to the ordination axis. TDS – Total Dissolved Solids; AR – Areas under Regeneration; PCNM1 – Spatial Component represented by the Principal Coordinates of Neighbor Matrices. Species are indicated by black dots. Acronyms according to Tab. 3
FIGURE 3 in Fish responses to multiple scales in coastal blackwater Atlantic Forest streams in Southeast Brazil
FIGURE 3 | Venn diagram showing the variance partition of local, regional and spatial variables in explaining the composition of fish communities. a = fraction of exclusive explanation of local variables; b = fraction of exclusive explanation of landscape variables; c = fraction of exclusive explanation of spatial variables; d = fraction of shared explanation between local and landscape variables; e = fraction of shared explanation between landscape and spatial variables; f = fraction of shared explanation between local and spatial variables; g = fraction of shared explanation among local, landscape and spatial variables.
FIGURE 1 in Fish responses to multiple scales in coastal blackwater Atlantic Forest streams in Southeast Brazil
FIGURE 1 | Location of the study area in the coastal region of the state of São Paulo, indicating the Baixada Santista and Northern Coast basins and the distribution of the sampling sites in the Itapanhaú (JP1, JP2, VA), Itaguaré (MP, PM, GU), Guaratuba (P1–P6), and Una (BB1, BB2) sub-basins (Adapted from Esteves et al., 2019). In detail, sites of the Guaratuba sub-basin and main landscape types.
FIGURE 2 in Fish responses to multiple scales in coastal blackwater Atlantic Forest streams in Southeast Brazil
FIGURE 2 | Nonmetric Multidimensional Scaling (NMDS) plot of Axis 1 and Axis 2 of the total fish density of 14 blackwater streams. Stream codes according to Tab. 1.
Input data to model multiple effects of large-scale deployment of grass in crop-rotations at European scale
<p>This is the input dataset to a Python script (<a href="https://github.com/oskeng/MF-bio-grass">https://github.com/oskeng/MF-bio-grass</a>) used to model the effects of widespread deployment of grass in rotations with annual crops to provide biomass while remediating soil organic carbon (SOC) losses and other environmental impacts.</p> <p>For more information about the dataset and the study, see the original article:</p> <p>Englund, O., Mola-Yudego, B., Börjesson, P., Cederberg, C., Dimitriou, I., Scarlat, N., Berndes, G. Large-scale deployment of grass in crop rotations as a multifunctional climate mitigation strategy. GCB Bioenergy</p>
Data from: Factors at multiple scales drive parasite community structure
<p>1. Understanding how ecological communities are assembled remains a key goal of ecosystem ecology. Because communities are hierarchical, factors acting at multiple scales can contribute to patterns of community structure. Parasites provide a natural system to explore this idea, as they exist as discrete communities within host individuals, which are themselves part of a community and metacommunity.</p> <p>2. We aimed to understand the relative contribution of multi-scale drivers in parasite community assembly and assess how patterns at one level may mask those occurring at another. Specifically, we wanted to disentangle patterns caused by passive sampling from those determined by ecological drivers, and how these vary with scale.</p> <p>3. We applied a Markov Random Fields model and assessed measures of β-diversity and nestedness for 420 replicate parasite infracommunities (parasite assemblages in host individuals) across two freshwater mussel host species, three sites and two time periods, comparing our results to simulations from four different ecologically relevant null models.</p> <p>4. We showed that β-diversity between sites (explaining 25% of variation in parasite distribution) and host species (41%) is greater than expected, and β-diversity between individual hosts is smaller than expected, even after accounting for parasite prevalence and characteristics of host individuals. Further, parasite communities were significantly less nested than expected once parasite prevalence and host characteristics were both accounted for, but more nested than expected otherwise, suggesting a degree of modularity at the within-host level that is masked if underlying host and parasite characteristics are not taken into account. The Markov Random Fields model provided evidence for possible competitive within-host parasite interactions, providing a mechanism for the observed infracommunity modularity.</p> <p>5. An integrative approach that examines factors at multiple scales is necessary to understand the composition of ecological communities. Further, patterns at one level can alter the interpretation of ecologically important drivers at another if variation at higher scales is not accounted for. </p>
Input data to model multiple effects of large-scale deployment of grass in crop-rotations at European scale
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Data from: Sex-specific resource strategies mediate home range sizes of an endangered carnivore across multiple scales
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The genomic landscapes of desert birds form over multiple time scales
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Data from: Factors at multiple scales drive parasite community structure
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Data from: Looking for compensation at multiple scales in a wetland bird community
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Supplementary Files to "Towards a global understanding of vegetation-climate dynamics at multiple time scales"
<p><strong>TimeSeriesPaper_main_processing.html</strong></p> <p>Html version of Jupyter notebook exemplifying main data analysis steps in "Towards a global understanding of vegetation-climate dynamics at multiple time scales" (doi:10.5194/bg-17-945-2020). Please see the publication for further details. Notebook written in Julia v0.6</p> <p><strong>Fig2_Co_Oscillation_Regimes.nc</strong></p> <p>Data underlying Fig. 2 in "Towards a global understanding of vegetation-climate dynamics at multiple time scales" (doi:10.5194/bg-17-945-2020).</p> <p>Classification of land surface by dominant scale of variability in Normalized Difference Vegetation Index (NDVI), air temperature, and precipitation. Dominant scale of variability was determined after Fourier decomposition, separately for each grid cell and summarized as unique combinations between variables (S - short-term, A - seasonal, L - longer-term, T - trend, listed in order NDVI, air temperature, precipitation). The semi-annual cycle is included in the seasonal band. Please see the publication for further details.</p>
Data from: Large-scale recovery of an endangered amphibian despite ongoing exposure to multiple stressors
Amphibians are one of the most threatened animal groups, with 32% of species at risk for extinction. Given this imperiled status, is the disappearance of a large fraction of the Earth's amphibians inevitable, or are some declining species more resilient than is generally assumed? We address this question in a species that is emblematic of many declining amphibians, the endangered Sierra Nevada yellow-legged frog (Rana sierrae). Based on >7,000 frog surveys conducted across Yosemite National Park over a 20-y period, we show that, after decades of decline and despite ongoing exposure to multiple stressors, including introduced fish, the recently emerged disease chytridiomycosis, and pesticides, R. sierrae abundance increased sevenfold during the study and at a rate of 11% per year. These increases occurred in hundreds of populations throughout Yosemite, providing a rare example of amphibian recovery at an ecologically relevant spatial scale. Results from a laboratory experiment indicate that these increases may be in part because of reduced frog susceptibility to chytridiomycosis. The disappearance of nonnative fish from numerous water bodies after cessation of stocking also contributed to the recovery. The large-scale increases in R. sierrae abundance that we document suggest that, when habitats are relatively intact and stressors are reduced in their importance by active management or species' adaptive responses, declines of some amphibians may be partially reversible, at least at a regional scale. Other studies conducted over similarly large temporal and spatial scales are critically needed to provide insight and generality about the reversibility of amphibian declines at a global scale.
Data from: Unmanned aerial systems measure structural habitat features for wildlife across multiple scales
1.Assessing habitat quality is a primary goal of ecologists. However, evaluating habitat features that relate strongly to habitat quality at fine-scale resolutions across broad-scale extents is challenging. Unmanned aerial systems (UAS) provide an avenue for bridging the gap between relatively high spatial resolution, low spatial extent field-based habitat quality measurements and lower spatial resolution, higher spatial extent satellite-based remote sensing. Our goal in this study was to evaluate the potential for UAS structure from motion (SfM) to estimate several dimensions of habitat quality that provide potential security from predators and forage for pygmy rabbits (Brachylagus idahoensis) in a sagebrush-steppe environment. 2.At the plant and patch scales, we compared UAS-derived estimates of vegetation height, volume (estimate of food availability), and canopy cover to estimates from ground-based terrestrial laser scanning (TLS), and field-based measurements. Then, we mapped habitat features across two sagebrush landscapes in Idaho, USA, using point clouds derived from UAS SfM. 3.At the individual plant scale, the UAS-derived estimates matched those from TLS for height (r2 = 0.85), volume (r2 = 0.94), and canopy cover (r2 = 0.68). However, there was less agreement with field-based measurements of height (r2 = 0.67), volume (r2 = 0.31), and canopy cover (r2 = 0.29). At the patch scale, UAS-derived estimates provided a better fit to field-based measurements (r2 = 0.51-0.78) than at the plant scale. Landscape-scale maps created from UAS were able to distinguish structural heterogeneity between key patch types. 4.Our work demonstrates that UAS was able to accurately estimate habitat heterogeneity for a key terrestrial vertebrate at multiple spatial scales. Given that many of the vegetation metrics we focus on are important for a wide variety of species, our work illustrates a general remote sensing approach for mapping and monitoring fine-resolution habitat quality across broad landscapes for use in studies of animal ecology, conservation, and land management.
Data from: Extreme insolation: climatic variation shapes the evolution of thermal tolerance at multiple scales
The climatic variability hypothesis (CVH) is a cornerstone of thermal ecology, predicting the evolution of wider organismal thermal tolerance ranges in more thermally variable environments. Thermal tolerance ranges depend on both upper and lower tolerance limits (critical thermal maxima [CTmax] and critical thermal minima [CTmin]), which may show different responses to environmental gradients. To delineate the relative effects of mean and extreme temperatures on thermal tolerances, we conducted a within-latitude comparative test of CVH predictions for army ants (Dorylinae) at multiple scales: across elevations, in seasonal versus aseasonal forests, and in subterranean versus surface microhabitats. Consistent with the CVH, thermally buffered subterranean species had narrower thermal tolerance ranges. Both CTmin and CTmax decreased with elevation for subterranean species. In contrast, aboveground species (those exposed to insolation) showed a decrease in CTmin but no change in CTmax across elevations. Furthermore, greater seasonal temperature variation in dry forests correlated with increased CTmax but not CTmin. These patterns suggest that CTmax and CTmin respond to different abiotic selective forces: habitat-specific exposure to extreme insolation corresponds to CTmax differences but not to CTmin variation. We predict that increasingly frequent heat spikes associated with climate change will have habitat-specific physiological consequences for ectothermic animals. Models predicting climate change impacts should account for species microhabitat uses and within-latitude differences in temperature seasonality.
Multiple Sclerosis: Cerebral Circulation Time is prolonged and not correlated with expanded disability status scale (EDSS). A study using digital subtracted angiography
<p>Dataset used to study the relationship between cerebral circulation time (CCT) and some clinical evidences, e.g. expand disability status scale (EDSS), disease duration, age at onset,... CCT was measured through the digital subtraction angiography (DSA) technique. </p> <p>Statistical Parametric Mapping software (SPM, Wellcome Department of Cognitive Neurology, Institute of Neurology, University College London; http://www.fil.ion.ucl.ac.uk/spm/) and ad-hoc scripts developed in the MATLAB scientific computing environment (http://www.mathworks.com, MathWorks, MA, USA) were applied to valuate the lesion volume and brain volume in MS patients.</p>
Tree diversity across multiple scales and environmental heterogeneity promote ecosystem multifunctionality in a large temperate forest region
<p><strong>Aim</strong>: Biodiversity across different scales provides multidimensional insurance for ecosystem functioning. Although the positive effects of local scale (α-diversity) biodiversity on ecosystem multifunctionality are widely accepted, species turnover across communities (β-diversity) which is often an important driver of ecosystem functioning did not receive the same attention. This study broadens the understanding of how multiple attributes of biodiversity maintain ecosystem multifunctionality from local to regional scales, across diverse environmental gradients.</p> <p><strong>Location</strong>: North-eastern China.</p> <p><strong>Time period</strong>: 2017.</p> <p><strong>Major taxa studied</strong>: Woody plants.</p> <p><strong>Methods</strong>: We estimate ecosystem multifunctionality using both averaging and modified multiple thresholds (50%, 70% and 90%) approaches. Multiple dimensions of biodiversity across varying spatial scales were measured within the framework of Hill‒Chao numbers. Linear and nonlinear models were used to evaluate the optimal patterns of multifunctionality and biodiversity along the latitude. Using variance decomposition, structural equation modeling and linear mixed models, we explored how multiple attributes of tree diversity at varying spatial scales affect multifunctionality, and how these relationships are modulated by environmental drivers.</p> <p><strong>Results</strong>: Our results show that multifunctionality decreased with increasing latitude, mirroring the pattern of tree diversity along latitudinal gradients. Phylogenetic β-diversity and species α-diversity emerged as crucial diversity indices for sustaining multifunctionality in these temperate forests. Soil and climatic conditions had either direct effects on multifunctionality, or indirect ones mediated by tree diversity. Environmental heterogeneity played a pivotal role in maintaining high levels of multifunctionality, exerting influence both directly and indirectly via phylogenetic β-diversity.</p> <p><strong>Main conclusions</strong>: This study underscores the positive effects of biodiversity on multifunctionality across multiple dimensions. Based on our findings, we conclude that any design of a forested landscape that is aimed at maximizing multifunctionality should consider maintaining high local diversity as well as forest community heterogeneity at varying scales.</p>
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.