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123 results for “conservation priority”
Figure 3 in Bats (Mammalia: Chiroptera) from two priority areas for biodiversity conservation in the Brazilian Amazon and range extension for Carollia benkeithi (Phyllostomidae)
Figure 3: Skull of Carollia benkeithi (MPEG 37664, female). Skull shown in (A) dorsal and (B) ventral views; (C) left lateral view of the skull, the arrow indicates the cingulum of the last maxillary premolar; and (D) left lateral mandible, the arrow indicates the pm2 greater than the m1. Scale bar: 5 mm.
Figure 2 in Bats (Mammalia: Chiroptera) from two priority areas for biodiversity conservation in the Brazilian Amazon and range extension for Carollia benkeithi (Phyllostomidae)
Figure 2: Geographic distribution of Carollia benkeithi (sensu McLellan and Koopman 2007) and new records (yellow stars), extending it ca. 590 km northwestward. Black dots are records recently published for eastern Pará state, Brazil (Lemos et al. 2020).
Figure 3 in Reviewing the status and demise of the Endangered Eld's deer and identifying priority sites and conservation actions in Cambodia
Figure 3: Minimum counts of Eld's deer recorded at Ang Trapeang Thmor and Siem Pang Wildlife Sanctuary.
Figure 2 in Reviewing the status and demise of the Endangered Eld's deer and identifying priority sites and conservation actions in Cambodia
Figure 2: Distribution of Eld's deer records in Cambodia up to 2020, divided into three regions: northern, eastern and central-western Cambodia. Management area boundaries, including protected areas, districts and communes, have been used to illustrate where records have occurred, and as such does not depict the actual extent of Eld's deer in each location. Svay Leu and Kaoh Nheaek Districts and Srayang Commune overlap with protected areas, however Eld's deer were recorded outside of the protected areas so only the proportion of the district/ commune outside of protected areas is shown. The historical distribution of Eld's deer prior to 2000 was outside the scope of the review, however we included any locations with pre-2000 records that appeared within our literature review. Therefore, this map is not an accurate reflection of Eld's deer historical distribution. The white area on the map is not necessarily lacking Eld's deer, given suitable habitat, but is unsurveyed.
Identifying hotspots and priority areas for xenarthran research and conservation
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Data from: Identifying conservation priorities for gorgonian forests in Italian coastal waters with multiple methods including citizen science and social media content analysis
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Prehistoric baseline reveals substantial decline of oyster reef condition in a Gulf of Mexico conservation priority area
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Data from: A comprehensive evaluation of flowering plant diversity and conservation priority for national park planning in China
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Data from: Remotely sensed data informs red list evaluations and conservation priorities in southeast Asia
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Data from: Landscape genetics informs mesohabitat preference and conservation priorities for a surrogate indicator species in a highly fragmented river system
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Data from: Multi-scale habitat modeling identifies spatial conservation priorities for mainland clouded leopards (Neofelis nebulosa)
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Data from: Conservation priorities for endangered coastal North African Pennisetum glaucum L. landrace populations as inferred from phylogenetic considerations and population structure analysis
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Data from: Identifying priority habitats for dung beetle conservation: Taxonomic and functional responses across a land-use disturbance gradient
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Data from: Conservation genetics of the Philippine tarsier: cryptic genetic variation restructures conservation priorities for an island archipelago primate
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Data from: Can patterns of habitat use by western Nearctic-Neotropical migratory landbirds in winter inform conservation priorities?
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High conservation priority of range-edge plant populations not matched by habitat protection or research effort
<p>Data and code for Caissy et al. 2020, Biological Conservation. Dataset excludes geographical data to avoid violating data sharing policies.</p>
Data from: Habitat suitability and connectivity modeling reveal priority areas for Indiana bat (Myotis sodalis) conservation in a complex habitat mosaic
Context <p>Conservation for the Indiana bat (<i>Myotis sodalis), </i>a federally endangered species in the United States of America, is typically focused on local maternity sites; however, the species is a regional migrant, interacting with the environment at multiple spatial scales. Hierarchical levels of management may be necessary, but we have limited knowledge of landscape-level ecology, distribution, and connectivity of suitable areas in complex landscapes.</p> Objectives <p>We sought to 1) identify factors influencing <i>M. sodalis </i>maternity colony distribution in a mosaic landscape, 2) map suitable maternity habitat, and 3) quantify connectivity importance of patches.</p> Methods <p>Using 3 decades of occurrence data, we tested <i>a priori</i>,<i> </i>hypothesis-driven<i> </i>habitat suitability models. We mapped suitable areas and quantified connectivity importance of habitat patches with probabilistic habitat availability metrics.</p> Results <p>Factors improving landscape-scale suitability included limited agriculture, more forest cover, forest edge, proximity to medium-sized water bodies, lower elevations, and limited urban development. Areas closer to hibernacula and rivers were suitable. Binary maps showed that thirty percent of the study area was suitable for <i>M. sodalis</i> and 29% was important for connectivity. Most suitable patches were important for intra-patch connectivity and far fewer contributed to inter-patch connectivity.</p> Conclusions <p>While simple models may be effective for small, homogenous landscapes, complex models are needed to explain habitat suitability in large, mixed landscapes. Suitability modeling identified factors that made sites attractive as maternity areas. Connectivity analysis improved our understanding of important areas for bats, identified suitable patches that may be isolated from the habitat network, and prioritized areas to target restoration.</p>
Global biogeographic synthesis and priority conservation regions of the relict tree family Juglandaceae
<p><span><b>Abstract</b></span></p> <p><span><b>Aim:</b> To establish a complete database of Juglandaceae at a spatiotemporal scale and develop a phylogeographic framework with which to elucidate the distributional patterns, diversity patterns, origins, evolution, and conservation priority regions of this family.</span></p> <p><span><b>Location:</b> Worldwide</span></p> <p><span><span><b>Methods: </b>Data on the distribution of all the extant and fossil species of Juglandaceae were collected, followed by analyses of its latitudinal distribution, elevational distribution, and species and generic diversity. Furthermore, based on all genera and 87% of the species, we reconstructed phylogenetic relationships, estimated divergence times, calculated phylogenetic diversity and inferred ancestral distributions.</span></span></p> <p><span><b>Results: </b>Extant Juglandaceae (10 genera and 60 species) are mainly distributed in eastern Asia and North America (principally between 20°N and 40°N). Tropical Juglandaceae mainly inhabit mountainous areas higher than 1000 m, especially in the New World. Southwest China and northern Vietnam are characterized by high species, generic, and phylogenetic diversity. The United States of America has only high species diversity. The area of origin of Juglandaceae was North America and Europe in the early Eocene, and its widespread dispersal mainly occurred between 13 and 26 Ma.</span></p> <p><span><b>Main conclusions: </b>The members of Juglandaceae inhabit areas with temperate climatic conditions. The diversification centre has shifted intercontinentally from North America and Europe to Southwest China and northern Vietnam, which are identified as conservation priority regions. The high-latitude cooling during the Oligocene followed by a long-term stable warmer climate in the early and middle Miocene drove the southward translocation of the family.</span></p>
Identifying conservation priorities in a defaunated tropical biodiversity hotspot
<p><b>Aim: </b>Unsustainable hunting is leading to widespread defaunation across the tropics. To mitigate against this threat with limited conservation resources, stakeholders must make decisions on where to focus anti-poaching activities. Identifying priority areas in a robust way allows decision-makers to target areas of conservation importance, therefore maximizing the impact of conservation interventions.</p> <p><b>Location: </b>Annamite mountains, Vietnam and Laos.</p> <p><b>Methods: </b>We conducted systematic landscape-scale surveys across five study sites (four protected areas, one unprotected area) using camera-trapping and leech-derived environmental DNA. We analyzed detections within a Bayesian multi-species occupancy framework to evaluate species responses to environmental and anthropogenic influences. Species responses were then used to predict occurrence to unsampled regions. We used predicted species richness maps and occurrence of endemic species to identify areas of conservation importance for targeted conservation interventions.</p> <p><b>Results: </b>Analyses showed that habitat-based covariates were uninformative. Our final model therefore incorporated three anthropogenic covariates as well as elevation, which reflects both ecological and anthropogenic factors. Conservation-priority species tended to found in areas that are more remote now or have been less accessible in the past, and at higher elevations. Predicted species richness was low and broadly similar across the sites, but slightly higher in the more remote site. Occupancy of the three endemic species showed a similar trend.</p> <p><b>Main conclusion: </b>Identifying spatial patterns of biodiversity in heavily-defaunated landscapes may require novel methodological and analytical approaches. Our results indicate to build robust prediction maps it is beneficial to sample over large spatial scales, use multiple detection methods to increase detections for rare species, include anthropogenic covariates that capture different aspects of hunting pressure, and analyze data within a Bayesian multi-species framework. Our models further suggest that more remote areas should be prioritized for anti-poaching efforts to prevent the loss of rare and endemic species.</p>
Lens genus SDM and conservation priorities - Data source file
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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
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.