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190 results for “multiple scales”
Data and code to reproduce analyses in Heinken et al, "A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites"
<p>This datasets archives the GitHub version found at https://github.com/ThieleLab/CodeBase to reproduce simulations for the article Heinken et al, "A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites", Cell Systems, in press.</p>
SPREAD: A Large-scale, High-fidelity Synthetic Dataset for Multiple Forest Vision Tasks (Part I)
<p><strong>This page only provides the ground-level image dataset. </strong></p> <ul> <li><strong>For the drone-view image dataset, please visit <a href="https://zenodo.org/records/13955516" target="_blank" rel="noopener"><em>SPREAD: A Large-scale, High-fidelity Synthetic Dataset for Multiple Forest Vision Tasks (Part II)</em></a>.</strong></li> <li><strong>For the point clouds, please visit <em><a href="https://zenodo.org/records/14228467" target="_blank" rel="noopener">SPREAD: A Large-scale, High-fidelity Synthetic Dataset for Multiple Forest Vision Tasks (Part III)</a>.</em></strong></li> </ul> <p>The dataset contains ground-level RGB images, depth maps, semantic segmentation labels, and instance segmentation labels collected from different scenes. Data from each scene is stored in a separate .7z file, along with a <code>color_palette.xlsx</code> file, which contains the RGB_id and corresponding RGB values.</p> <p>All files follow the naming convention: <code>{central_tree_id}_{timestamp}</code>, where <code>{central_tree_id}</code> represents the ID of the tree centered in the image, which is typically in a prominent position, and <code>timestamp</code> indicates the time when the data was collected.</p> <p>Specifically, each 7z file includes the following folders:</p> <ul> <li> <p><strong>rgb</strong>: This folder contains the RGB images (PNG) of the scenes and their metadata (TXT). The metadata describes the weather conditions and the world time when the image was captured. An example metadata entry is: <code>Weather:Snow_Blizzard,Hour:10,Minute:56,Second:36</code>.</p> </li> <li> <p><strong>depth_pfm</strong>: This folder contains absolute depth information of the scenes, which can be used to reconstruct the point cloud of the scene through reprojection.</p> </li> <li> <p><strong>semantic_segmentation</strong>: This folder contains grayscale images representing semantic segmentation labels, where 1 indicates tree trunks and 0 represents other elements.</p> </li> <li> <p><strong>instance_segmentation</strong>: This folder stores instance segmentation labels (PNG) for each tree in the scene, along with metadata (TXT) that maps <code>tree_id</code> to <code>RGB_id</code>. The <code>tree_id</code> can be used to look up detailed information about each tree in <code>obj_info_final.xlsx</code>, while the <code>RGB_id</code> can be matched to the corresponding RGB values in <code>color_palette.xlsx</code>. This mapping allows for identifying which tree corresponds to a specific color in the segmentation image.</p> </li> <li> <p><strong>obj_info_final.xlsx</strong>: This file contains detailed information about each tree in the scene, such as position, scale, species, and various parameters, including trunk diameter (in cm), tree height (in cm), and canopy diameter (in cm).</p> </li> <li> <p><strong>landscape_info.txt</strong>: This file contains the ground location information within the scene, sampled every 0.5 meters.</p> </li> </ul> <p>For forest datasets: birch_forest, broadleaf_forest, burned_forest, rainforest and redwood_forest, there's an additional folder called <strong>coco_annotation</strong> where we generated the COCO-format annotation files (.json) for each image.</p> <p>⚠️: 7z files that begin with "<strong>!</strong>" indicate that the RGB values in the images within the <code>instance_segmentation</code> folder cannot be found in <code>color_palette.xlsx</code>. Consequently, this prevents matching the trees in the segmentation images to their corresponding tree information, which may hinder the application of the dataset to certain tasks. This issue is related to a bug in Colossium/AirSim, which has been reported in <a href="https://github.com/microsoft/AirSim/issues/3423" target="_blank" rel="noopener">link1</a> and <a href="https://github.com/microsoft/AirSim/issues/1852" target="_blank" rel="noopener">link2</a>.</p>
SPREAD: A Large-scale, High-fidelity Synthetic Dataset for Multiple Forest Vision Tasks (Part III)
<p><strong>This page only provides point clouds. </strong></p> <ul> <li><strong>For the ground-level image dataset, please visit <a href="https://zenodo.org/records/13570934" target="_blank" rel="noopener"><em>SPREAD: A Large-scale, High-fidelity Synthetic Dataset for Multiple Forest Vision Tasks (Part I)</em></a>.</strong></li> <li><strong>For the drone-view image dataset, please visit <a href="https://zenodo.org/records/13955516" target="_blank" rel="noopener"><em>SPREAD: A Large-scale, High-fidelity Synthetic Dataset for Multiple Forest Vision Tasks (Part II)</em></a>.</strong></li> </ul> <p>This dataset contains point clouds collected from different virtual forest scenes. Data from each scene is stored in a separate .7z file, along with a <code>point_cloud_color_palette.txt</code>file, which contains the Tree_id and corresponding RGB values.</p> <p>Specifically, each 7z file includes the following folders:</p> <ul> <li> <p><strong>tree</strong>: This folder contains the point cloud data of every single tree within the forest scene. Each tree is stored separately in a <code>.ply</code> file including both location and color infomation. For performance reasons, the maximum number of point clouds for each tree is limited to 10,000.</p> </li> <li> <p><strong>ground</strong>: This folder contains a <code>landscape.ply</code> describing the ground information. The color of the point cloud is set to [0,0,0].</p> </li> </ul> <p><strong>The unit of the point cloud is meters (m).</strong></p>
Large scale eDNA monitoring of multiple aquatic pathogens as a tool to provide risk maps for wildlife diseases
<p>Multiple parasites and pathogens cause disease in aquatic wildlife and in aquaculture species, generating a need for monitoring and management. Conventional disease monitoring methods involve laborious, costly and invasive capture and examination of host species, and require specialised expertise for every host and pathogen of interest. These restrictions could be alleviated by using pathogen detection techniques based on environmental DNA that provide simultaneous surveys of multiple aquatic pathogens across different host taxa. This would also be valuable for approaches employing parasite diversity as bioindicators of ecosystem disturbance, which suffer from similar restrictions. Here, we tested the potential for simultaneous detection of four wildlife pathogens in water samples from 280, mainly riverine, sites across Switzerland. We targeted the crayfish pathogen <em>Aphanomyces astaci, </em>the amphibian pathogen <em>Batrachochytrium dendrobatidis, </em>and the fish pathogens <em>Saprolegnia parasitica</em> and <em>Tetracapsuloides bryosalmonae</em>. The eDNA detection showed a widespread distribution of <em>A. astaci</em>, <em>S. parasitica</em> and <em>T. bryosalmonae</em>, although <em>A. astaci </em>and <em>T. bryosalmonae</em> were not detected in some alpine river catchments. <em>B. dendrobatidis</em> was detected only rarely, which was expected since the sampling did not target amphibian breeding sites. Co-detection rates were higher in rivers than in lakes, likely reflecting the habitat preferences and distributions of the host species. We discuss the advantages and limitations of eDNA-based pathogen monitoring and list a set of recommendations for managers. Our study illustrates how eDNA-based techniques can monitor several pathogen species concurrently, thus facilitating more comprehensive disease monitoring schemes. Combined with metabarcoding approaches in the future, eDNA based sampling and detection can facilitate the incorporation of parasite and pathogen occurrence and diversity as an indicator for aquatic ecosystem health, and for revealing the hidden biodiversity and structure of parasite communities.</p>
Data and codes to replicate the analysis in: The spatial ecology of conflicts: Unravelling patterns of wildlife damage at multiple scales
<p><span><span>Human encroachment into natural habitats is typically followed by conflicts derived from wildlife damages to agriculture and livestock. Spatial risk modelling is a useful tool to gain understanding of wildlife damage and mitigate conflicts. Although resource selection is a hierarchical process operating at multiple scales, risk models usually fail to address more than one scale, which can result in the misidentification of the underlying processes. Here, we addressed the multi-scale nature of wildlife damage occurrence by considering ecological and management correlates interacting from household to landscape scales. We studied brown bear (<i>Ursus arctos</i>) damage to apiaries in the North-eastern Carpathians as our model system. Using generalized additive models, we found that brown bear tendency to avoid humans and the habitat preferences of bears and beekeepers determine the risk of bear damage at multiple scales. Damage risk at fine scales increased when the broad landscape context also favoured damages. Furthermore, integrated-scale risk maps resulted in more accurate predictions than single-scale models. Our results suggest that principles of resource selection by animals can be used to understand the occurrence of damages and help mitigate conflicts in a proactive and preventive manner. </span></span></p>
Behavioral responses of a large, heat-sensitive mammal to climatic variation at multiple spatial scales
<p>1. Climate warming creates energetic challenges for endothermic species by increasing metabolic and hydric costs of thermoregulation. Although endotherms can invoke an array of behavioral and physiological strategies for maintaining homeostasis, the relative effectiveness of those strategies in a climate that is becoming both warmer and drier is not well understood.</p> <p>2. In accordance with the heat dissipation limit theory, which suggests that allocation of energy to growth and reproduction by endotherms is constrained by the ability to dissipate heat, we expected that patterns of habitat use by large, heat-sensitive mammals across multiple scales are critical for behavioral thermoregulation during periods of potential heat stress and that they must invest a large portion of time to maintain heat balance.</p> <p>3. To test our predictions, we evaluated mechanisms underpinning the effectiveness of bed sites for ameliorating daytime heat loads and potential heat stress across the landscape while accounting for other factors known to affect behavior. We integrated detailed data on microclimate and animal attributes of moose <em>Alces</em> <em>alces</em>, into a biophysical model to quantify costs of thermoregulation at fine and coarse spatial scales.</p> <p>4. During summer, moose spent an average of 67.8% of daylight hours bedded, and selected bed sites and home ranges that reduced risk of experiencing heat stress. For most of the day, shade could effectively mitigate the risk of experiencing heat stress up to 10°C, but at warmer temperatures (up to 20℃) wet soil was necessary to maintain homeostasis via conductive heat loss. Consistent selection across spatial scales for locations that reduced heat load underscores the importance of the thermal environment as a driver of behavior in this heat-sensitive mammal.</p> <p>5. Moose in North America have long been characterized as riparian-obligate species because of their dependence on woody plant species for food. Nevertheless, the importance of dissipating endogenous heat loads conductively through wet soil suggests riparian habitats also are critical thermal refuges for moose. Such refuges may be especially important in the face of a warming climate in which both high environmental temperatures and drier conditions will likely exacerbate limits to heat dissipation, especially for large, heat-sensitive animals.</p>
Data from: Dominant species determine grazing effects on the stability of herbaceous community production at multiple scales in drylands
<p><span>Sustainable provision of critical ecosystem services in drylands is reliant on their stability under anthropogenic disturbances. Livestock grazing and shrub encroachment are the primary drivers of disturbance that impact their biodiversity and production dynamics. However, the effects of grazing on the stability at multiple scales, particularly following the transition from grass-dominated to shrub-encroached drylands, is still largely unexplored</span><span>.</span></p> <p><span>Here, we conducted comparable sheep-grazing experiments in two types of drylands (grass-dominated vs. shrub-encroached grasslands) on the Mongolia Plateau to explore the effects of grazing and shrub encroachment on biodiversity and stability at multiple scales. We examined how grazing affected the temporal stability of aboveground biomass in herbaceous communities in both grass-dominated and shrub-encroached grasslands, through two potential mechanisms: insurance effects and changes in the population-level stability of individual species.</span></p> <p><span>We found that an increase in sheep grazing intensity had significant and negative effects on insurance effects by decreasing both species asynchrony and spatial asynchrony but it had no effects on population stability, consequently leading to reductions in herbaceous community stability of the grasslands. However, grazing-increased insurance effects canceled out grazing-decreased population stability, contributing to no changes in the community stability of shrub-encroached grasslands. Likely, because grazing-induced reductions in the relative abundance of the dominant species were more noticeable in shrub-encroached grasslands than that of in grasslands. Moreover, the grazing-decreased abundance of dominant species was directly correlated to increases in insurance effects in shrub-encroached grasslands but not in grasslands, despite the positive relationships between population stability and the relative abundance of the dominant species in both grass-dominated and shrub-encroached drylands. </span></p> <p><em><span>Synthesis and applications.</span></em><span> Our results indicate that grazing can decrease the stability of herbaceous production in drylands, but this negative effect is attenuated with the transition from grasslands to shrub-encroached grasslands, suggesting that grazing effects on herbaceous community stability can be altered by shrub encroachment in drylands. Furthermore, the stability of dominant grasses plays a crucial role in stabilizing herbaceous communities, and should be considered in promoting sustainable ecosystem functioning and services in drylands.</span></p>
Data from: Philopatry influences the genetic population structure of the blacktip shark (Carcharhinus limbatus) at multiple spatial scales
<p>Understanding how interactions among microevolutionary forces generate genetic population structure of exploited species is vital to the implementation of management policies that facilitate population persistence. Philopatry displayed by many coastal shark species can impact gene flow and facilitate selection, and thus has direct implications for the spatial scales of management plans. Here, genetic structure of the blacktip shark (Carcharhinus limbatus) was examined using a mixed-marker approach based on mitochondrial control region sequences and 4,339 SNP-containing loci generated using ddRAD-Seq. Genetic variation was assessed among young-of-the-year sampled in 11 sites in waters of the United States in the western North Atlantic Ocean, including the Gulf of Mexico. Spatial and environmental analyses detected 68 nuclear loci putatively under selection, enabling separate assessments of neutral and adaptive genetic structure. Both mitochondrial and neutral SNP data indicated three genetically distinct units – the Atlantic, eastern Gulf, and western Gulf – that align with regional stocks and suggest regional philopatry by males and females. Heterogeneity at loci putatively under selection, associated with temperature and salinity, was observed among sites within Gulf units, suggesting local adaptation. Furthermore, five pairs of siblings were identified in the same site across timescales corresponding with female reproductive cycles. This indicates that females re-used a site for parturition, which has the potential to facilitate the sorting of adaptive variation among neighboring sites. The results demonstrate differential impacts of microevolutionary forces at varying spatial scales and highlight the importance of conserving essential habitats to maintain sources of adaptive variation that may buffer species against environmental change.</p>
Tidal Effects on Dynamics and Freshwater Transport of a Medium-scale River Plume with Multiple Outlets
<p>Data for submitted paper "Tidal Effects on Dynamics and Freshwater Transport of a Medium-scale River Plume with Multiple Outlets"</p>
Early life telomeres are influenced by environments acting at multiple temporal and spatial scales
<p><span>An individual's telomere length early in life may reflect or contribute to key life history processes sensitive to environmental variation. Yet, the relative importance of genetic and</span><span> environmental factors in shaping early life telomere length is not well understood as it requires samples collected from multiple generations with known developmental histories. We used a confirmed pedigree and conducted an animal model analysis of telomere lengths obtained from nestling house sparrows (<em>Passer domesticus</em>) sampled over a span of 22 years. We found significant additive genetic variation for early life telomere length, but it comprised a relatively small proportion (9%) of the total biological variation. Three sources of environmental variation were important: among cohorts, among breeding attempts within years and families, and among nestmates. The magnitude of variation among breeding attempts and among nestmates also differed by cohort, suggesting that interactive effects of environmental factors across time or spatial scales were important, yet we were unable to identify the specific causes of these interactions. The mean amount of precipitation during the breeding season positively predicted telomere length, but neither weather during a given breeding attempt nor date in the breeding season contributed to an offspring's telomere length. At the residual level, level of individual nestlings, offspring sex, size, and mass at 10 days of age also did not predict telomere length. Environmental effects appear especially important in shaping early life telomere length in some species, and an array of complex more focus on how environmental factors that interactions across scales may help to explain some of the variation observed among studies.</span></p>
Early life telomeres are influenced by environments acting at multiple temporal and spatial scales
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Data from: Multiple global change factors alter the scaling of nitrogen to phosphorus in alpine plants
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Evolutionary trajectories of multiple defense traits across phylogenetic and geographic scales in Vitis
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Large scale eDNA monitoring of multiple aquatic pathogens as a tool to provide risk maps for wildlife diseases
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Behavioral responses of a large, heat-sensitive mammal to climatic variation at multiple spatial scales
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Data from: Unmanned aerial systems measure structural habitat features for wildlife across multiple scales
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Data from: The interplay of multiple spatial scales influences plant–herbivore interactions
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Tree diversity across multiple scales and environmental heterogeneity promote ecosystem multifunctionality in a large temperate forest region
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Data from: Generalist-pollinated <em>Arabis alpina</em> exhibits floral scent variation at multiple scales
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Opposing effects of Ceanothus velutinus phytochemistry on herbivore communities at multiple scales
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ScienceDex guides
Understand access before you commit
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.