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40 results for “habitat risk”
MCR LTER: Coral Reef: Growth-predation risk trade-offs constrain the local distribution of a thicket-forming staghorn coral to marginal reef habitats; Data for Ladd et al., 2025, Scientific Reports.
This dataset is in support of the manuscript: Growth-predation risk tradeoffs constrain the local distribution of a thicket-forming staghorn coral to marginal reef habitats. These data were collected to 1) document how Acropora pulchra is distributed around the island of Moorea, and 2) to better understand the ecological processes that shape that distribution. Data include 1) results from surveys around the island of Moorea documenting the presence and size distribution of Acropora pulchra thickets, 2) results from an experiment measuring the growth and survivorship of Acropora pulchra fragments in the presence and absence of fish predators at nearshore fringing reef sites and adjacent sites in the mid lagoon (n = 20 sites in total), and 3) ancillary data on nitrogen content and dN15 in the tissue of the macroalgae Turbinaria ornata, sediment accumulation, and corallivore biomass at the experimental sites. All data were collected in 2016 and 2017.
Row sequcenes data for assessing the risks of potential pathogens and antibiotic resistance genes among heterogeneous habitats in a temperate estuary wetland
<p>The study included 118 usable samples within three different habitats (water, soil, and sediment) across the Liaohe River basin to the Red Beach wetland collected from seven papers, and all of the sequence files were uploaded for availability.</p>
Fig. 1 in Sleeping site selection in two Asian viverrids: effects of predation risk, resource access and habitat characteristics
Fig. 1. Home ranges, core areas and sleeping sites of binturongs (Arctictis binturong) and masked palm civets (Paguma larvata). Home ranges (minimum convex polygon [MCP] 95%) and core areas (MCP 50%) with sleeping sites overlaid of (a) three masked palm civets and a female binturong at Tikong, (b) a male binturong at Sesawo, and (c) location of study sites (Sesawo and Tikong) within the study area (Thung Yai Naresuan Wildlife Sanctuary – West). Different gray shades within home ranges represent core areas of each animal.
Fig. 4 in Sleeping site selection in two Asian viverrids: effects of predation risk, resource access and habitat characteristics
Fig. 4. Use and reuse of sleeping sites. Cumulative number of unique sleeping sites in relation to the total number of sites observed for two binturongs (Arctictis binturong) and three masked palm civets (Paguma larvata). Numbers of unique sleeping sites (sites that are not re-used) versus total sleeping sites observed and study areas are indicated in parenthesis.
Fig. 3 in Sleeping site selection in two Asian viverrids: effects of predation risk, resource access and habitat characteristics
Fig. 3. Use of sleeping sites within different forest types. Percentage of different forest types used (denoted as U) for sleeping sites versus forest types available (A) for two binturongs (Arctictis binturong) and three masked palm civets (Paguma larvata). Forest types are: semi-evergreen forest (SEF), mixed deciduous forest (MDF), and dry dipterocarp forest (DDF). Numbers in parenthesis after individual animals represent the number of sleeping sites used in the analysis, excluding reused sites.
Fig. 2 in Sleeping site selection in two Asian viverrids: effects of predation risk, resource access and habitat characteristics
Fig. 2. Use of vertical strata for sleeping sites. Percentage use of different vertical strata of sleeping sites by five radio-collared viverrids (two binturongs Arctictis binturong and three masked palm civets Paguma larvata). Strata are: Above canopy, Canopy, and Sub-canopy. Numbers in parenthesis represent number of sleeping sites where animals were directly observed, excluding reused sites.
Data from: Habitat fragmentation drives pest termite risk in humid but not arid biomes
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Data from: Movement-integrated habitat selection reveals wolves balance ease of travel with human avoidance in a risk-reward trade-off
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Increasing agricultural habitat reduces solitary bee offspring number and weight in apple orchards through reduced floral diet diversity and increased fungicide risk
<p>1. Threats to bee pollinators such as land use change, high pesticide risk, and reduced floral diet diversity are usually assessed independently, even though they often co-occur to impact bees in agroecosystems.</p> <p>2. We established populations of the non-native mason bee O. cornifrons at 17 NY apple orchards varying in proportion of surrounding agriculture and measured floral diet diversity and pesticide risk levels in the pollen provisions they produced. We used path analysis to test the direct and indirect effects of different habitats, diet diversity, and pesticide risk on emergent female offspring number and weight.</p> <p>3. Our results showed that high proportions of agricultural habitat surrounding bee nests indirectly reduced the number of female offspring produced, by reducing floral diet diversity in pollen.</p> <p>4. When proportion agriculture surrounding bee nests was high, bees collected increased proportions of Rosaceae in their pollen provisions, which marginally (0.05<p<0.1) increased fungicide risk levels in pollen, which, in turn, marginally reduced female offspring weight. In contrast, female offspring weight increased as proportion surrounding open habitat (wildflowers, grassland, pasture) increased, but this effect was not influenced by proportion Rosaceae or fungicide risk levels in pollen.</p> <p>5. Synthesis and Applications: To promote healthy O. cornifrons populations in apple, we must maintain floral resource diversity and open habitats, while reducing fungicide risk levels and agricultural habitats. More broadly, our results show that land use change, in the form of increasing agricultural habitat, can negatively impact bee populations in agroecosystems indirectly through multiple, simultaneous threats. We must strive to understand these complex interactions between simultaneous threats to maintain healthy bee populations in agroecosystems, where we rely on them for pollination.</p>
Data from: Prioritizing global land protection for population persistence can double the efficiency of habitat protection for reducing mammal extinction risk
<p>Halting the alarming rate of species extinction, driven primarily by habitat destruction, motivated the international community to adopt (2022) the Global Biodiversity Framework and it’s 23 targets aimed at reversing habitat and species loss. Due to urgency and resource constraints, a key challenge is meeting targets effectively and efficiently. Here we conduct a global prioritization linking 70,492 unique population maps and life history characteristics for 861 threatened terrestrial mammal species. Incorporating individual population data boosted viability for 84% more populations compared to using a more typical approach that uses species distributions alone, nearly doubling the security of long-term species persistence. We map and rank global mammal persistence priority areas and assess how well the current protected areas (PA) system captures these important regions. Our results will provide conservation actors a more direct and quantifiable linkage between conservation action and extinction risk than has previously been possible at a global scale.</p>
Data associated with: Applying remote sensing for large-landscape problems: Inventorying and tracking habitat recovery for a broadly distributed Species At Risk
<ol> <li> <p><span>Anthropogenic habitat alteration is leading to the reduction of global biodiversity. Consequently, there is an imminent need to understand the state and trend of habitat alteration across broad areas. In North America, habitat alteration has been linked to the decline of threatened woodland caribou. As such, habitat protection and restoration are critical measures to support recovery of self-sustaining caribou populations. Broad estimates of habitat change through time have set the stage for understanding the status of caribou habitat. However, the lack of updated and detailed data on post-disturbance vegetation recovery is an impediment to recovery planning and monitoring restoration effectiveness. Advances in remote sensing tools to collect high-resolution data at large spatial scales are beginning to enable ecological studies in new ways to support ecosystem-based and species-based management.</span></p> </li> <li> <p><span>We used semi-automated and manual methodologies to fuse photogrammetry point clouds (PPC) from high-resolution aerial imagery with wide-area Light Detection and Ranging (LiDAR) data to quantify vegetation structure (height, density, class) on disturbances associated with caribou declines. We also compared vegetation heights estimated from the semi-automated PPC-LiDAR fusion to heights estimated in the field, using stereoscopic interpretation, and using multi-channel TiTAN LiDAR.</span></p> </li> <li> <p><span>Vegetation regrowth was occurring on many of the disturbance types, though there was local variability in the type, height, and density of vegetation. Heights estimated using PPC-LiDAR fusion were highly correlated (r ≥ 0.87 in all cases) with heights estimated using stereomodels, TiTAN multi-channel LiDAR, and field measurements. </span></p> </li> <li> <p>We demonstrated that PPC-LiDAR fusion can be operationalized over large areas to collect comprehensive and consistent vegetation data across landscape levels, providing opportunities to link fine-resolution remote sensing to landscape-scale ecological studies. Crucially, these data can be used to estimate rates of habitat recovery at resolutions that are not feasible using more commonly used satellite-based sensors, bridging the gap between resolution and extent. Such data are needed to achieve effective and efficient habitat monitoring to support caribou recovery efforts, as well as a myriad of additional forest management needs.</p> </li> </ol>
Increasing agricultural habitat reduces solitary bee offspring number and weight in apple orchards through reduced floral diet diversity and increased fungicide risk
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Evaluation of federal habitat stewardship projects for aquatic species at risk in Canada: The province of Ontario as a case study
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Data from: Navigating a landscape of contrasting hunting regimes and habitats: Red deer responses to risk and resources
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Data associated with: Applying remote sensing for large-landscape problems: Inventorying and tracking habitat recovery for a broadly distributed Species At Risk
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Activity-pressure-habitat linkage matrix: Identifying impact chains to assess impact risk to tropical marine ecosystems from human activities in four Southeast Asian case studies Version 1.0
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Ungrazed seminatural habitats around farms benefit bird conservation without enhancing infectious disease risks
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Data from: Temporal scale of habitat selection for large carnivores: Balancing energetics, risk and finding prey
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Data from: Abiotic and habitat drivers of tick vector abundance, diversity, phenology and human encounter risk in southern California
The distribution, abundance and seasonal activity of vector species, such as ticks and mosquitoes, are key determinants of vector-borne disease risk, and are strongly influenced by abiotic and habitat conditions. Despite the numerous species of tick vectors in the heavily populated North American West Coast, all but Ixodes pacificus, the primary vector of the Lyme disease spirochete, is poorly characterized with regard to seasonal activity patterns and fine scale drivers of distribution and abundance, particularly in heavily populated regions of southern California. This lack of knowledge inhibits both scientific understanding and public health efforts to minimize vector exposure and risk of pathogen transmission to humans. Here we address this gap by characterizing the abiotic and habitat drivers of the distribution, abundance, and diversity of the vector tick community using fine scale temporal surveys over two seasons (2014 and 2015) across coastal and inland regions of Santa Barbara County, CA. We also characterize patterns of seasonal activity of the more common vector species to understand seasonality in risk of vector exposure, and specifically focus on human encounter risk using standardized tick drags as our method of collection. Leveraging plot-level habitat and abiotic variables in partial least squares regression analysis, we find the seven different vector species collected in this study have divergent drivers of activity and abundance. For example, I. pacificus is strongly associated with dense forest habitats and cool and moist microclimates, while Dermacentor occidentalis and Dermacentor variabilis, competent vectors of Rocky Mountain Spotted Fever, were found to be more tolerant of higher average temperatures and more open habitats. These results suggest that I. pacificus may be expected to experience reductions in geographic distribution and seasonal activity under projected land cover and climate change in coastal southern California, while D. occidentalis may experience more limited effects. We discuss implications for changing tick-borne disease risk associated with pathogens transmitted by Ixodes as well as Dermacentor species ticks in the western US, and contrast these predictions with eastern North America.
Data from: Habitat risk assessment for regional ocean planning in the U.S. Northeast and Mid-Atlantic
Coastal habitats provide important benefits to people, including habitat for species targeted by fisheries and opportunities for tourism and recreation. Yet, such human activities also can imperil these habitats and undermine the ecosystem services they provide to people. Cumulative risk assessment provides an analytical framework for synthesizing the influence of multiple stressors across habitats and decision-support for balancing human uses and ecosystem health. To explore cumulative risk to habitats in the U.S. Northeast and Mid-Atlantic Ocean Planning regions, we apply the open-source InVEST Habitat Risk Assessment model to 13 habitats and 31 stressors in an exposure-consequence framework. In doing so, we advance the science priorities of EBM and both regional planning bodies by synthesizing the wealth of available data to improve our understanding of human uses and how they affect marine resources. We find that risk to ecosystems is greatest first, along the coast, where a large number of stressors occur in close proximity and secondly, along the continental shelf, where fewer, higher consequence activities occur. Habitats at greatest risk include soft and hard-bottom nearshore areas, tidal flats, soft-bottom shelf habitat, and rocky intertidal zones—with the degree of risk varying spatially. Across all habitats, our results indicate that rising sea surface temperatures, commercial fishing, and shipping consistently and disproportionally contribute to risk. Further, our findings suggest that management in the nearshore will require simultaneously addressing the temporal and spatial overlap as well as intensity of multiple human activities and that management in the offshore requires more targeted efforts to reduce exposure from specific threats. We offer a transparent, generalizable approach to evaluating cumulative risk to multiple habitats and illustrate the spatially heterogeneous nature of impacts along the eastern Atlantic coast and the importance of spatial scale in estimating such impacts. These results offer a valuable decision-support tool by helping to constrain the decision space, focus attention on habitats and locations at the greatest risk, and highlight effect management strategies.
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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)
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DANDI Archive for NWB datasets
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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.