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373 results for “potential distribution”
DATASET: Electric Potential Distribution Inside the Electrolyte During High Voltage Electrolysis
<p>This project contains all the data shown in the figures of the manuscript (and the supporting information) entitled:<br> 'Electric Potential Distribution Inside the Electrolyte During High Voltage Electrolysis'<br> (doi:10.26434/chemrxiv-2022-nw4sp).</p> <p>The data to each figure is provided in a subfolder with further information.</p>
Potential current and future distribution of the Andean toad Rhinella spinulosa (ANURA: BUFONIDAE): basis for conservation.
<p>Data and script for ecological niche model. Layers are included for. the present and future</p>
F I G U R E 6 in Current and future potential geographical distribution of Bactericera cockerelli: an invasive pest of increasing global importance
F I G U R E 6 Predicted future climatic suitability for tomato potato psyllid (TPP; Bactericera cockerelli) in (a) its native range in North America, and (b) its invasive regions in Australia under a future climate change scenario predicted to the year 2090 in CLIMEX using the general circular model (GCM) CSIRO Mark 3.0, run with the A1B emissions scenario the known global distributions denoted by green colour dots.
F I G U R E 5 in Current and future potential geographical distribution of Bactericera cockerelli: an invasive pest of increasing global importance
F I G U R E 5 Predicted global climatic suitability for tomato potato psyllid (TPP; Bactericera cockerelli) under a future climate change scenario predicted to the year 2090 in CLIMEX using the general circular model (GCM) CSIRO Mark 3.0, run with the A1B emissions scenario.
F I G U R E 2 in Current and future potential geographical distribution of Bactericera cockerelli: an invasive pest of increasing global importance
F I G U R E 2 Predicted global climatic suitability for tomato potato psyllid (TPP; Bactericera cockerelli) under current climatic conditions in its native region in North America. The known global distributions are denoted by green colour dots.
F I G U R E 4 in Current and future potential geographical distribution of Bactericera cockerelli: an invasive pest of increasing global importance
F I G U R E 4 Predicted climatic suitability for tomato potato psyllid (TPP; Bactericera cockerelli) under current climatic conditions in New Zealand under current climatic conditions. The known global distributions are denoted by green colour dots.
F I G U R E 1 in Current and future potential geographical distribution of Bactericera cockerelli: an invasive pest of increasing global importance
F I G U R E 1 Predicted global climatic suitability (ecoclimatic index) for tomato potato psyllid (TPP; Bactericera cockerelli under current climatic conditions using the adjusted parameters given in Table 1 under (a) natural rainfall and (b) as composite of natural rainfall and irrigation based on areas identified by Siebert et al. (2013). The known global distributions are denoted by green colour dots.
F I G U R E 3 in Current and future potential geographical distribution of Bactericera cockerelli: an invasive pest of increasing global importance
F I G U R E 3 Predicted climatic suitability for tomato potato psyllid (TPP; Bactericera cockerelli) under current climatic conditions in Australia current climatic conditions. The known global distributions are denoted by green colour dots.
F I G U R E 7 in Current and future potential geographical distribution of Bactericera cockerelli: an invasive pest of increasing global importance
F I G U R E 7 Predicted future climatic suitability for tomato potato psyllid (TPP; Bactericera cockerelli) in New Zealand under a future climate change scenario predicted to the year 2090 in CLIMEX using the general circular model (GCM) CSIRO Mark 3.0, run with the A1B emissions scenario. The known global distributions denoted by green colour dots.
Using species distribution models and decision tools to direct surveys and identify potential translocation sites for a critically endangered species
<p>Aim: Occurrence records for cryptic species are typically limited or highly uncertain, leaving their distributions poorly resolved and hampering conservation. This can apply to well‐studied species, and increased survey effort and/or novel methods are required to improve distribution data. Here, we paired species distribution modelling (SDM) with decision tools to direct surveys for the critically endangered Leadbeater's possum (Gymnobelideus leadbeateri) outside its current restricted range. We also assessed survey areas for their suitability to host translocations.</p> <p>Location: Victoria, Australia.</p> <p>Method: We used both recent and historic records (now out of range and spatially uncertain) of Leadbeater's possum to build SDMs using MaxEnt. The SDMs informed an initial multi‐criteria decision analysis (MCDA) that enabled prioritization of 80 survey sites across seven forest patches (13–145 km outside the known range), which we surveyed using camera traps. Site and vegetation data were used in a post‐survey MCDA to rank their potential translocation suitability.</p> <p>Results: The SDM predictions were consistent with the species' ecology, identifying cold areas with high rainfall that had not recently burnt as suitable. The spatial uncertainty of records did not exert a strong influence on either model predictions or the ranking of patches for surveys. Camera trap surveys yielded records of 19 native species, with Leadbeater's possum detected in only one survey patch, 13 km outside of its previously known range. The post‐survey MCDA identified three forest patches as potentially suitable for conservation translocations, and these priorities were not sensitive to the decision criteria used.</p> <p>Main conclusions: The approach outlined here prioritized survey effort over a large area, resulting in detection of Leadbeater's possum in one new patch. The potential translocation sites identified could present an important risk‐spreading measure for the species given the threat posed by bushfire. Combining SDMs and decision tools can help target surveys and guide subsequent conservation strategies.</p>
Fig. 1. The potential distribution map for B in Long-Term Bioclimatic Modelling The Distribution Of The Fire-Bellied Toad, Bombina Bombina (Anura, Bombinatoridae), Under The Influence Of Global Climate Change
Fig. 1. The potential distribution map for B. bombina under contemporary climatic conditions. The colour gradient represents high (red) to low (green) habitat suitability for the species.
Fig. 4. The potential distribution map for B. bombina under projected 2050 in Long-Term Bioclimatic Modelling The Distribution Of The Fire-Bellied Toad, Bombina Bombina (Anura, Bombinatoridae), Under The Influence Of Global Climate Change
Fig. 4. The potential distribution map for B. bombina under projected 2050 climatic conditions. The colour gradient represents high (red) to low (green) habitat suitability for the species.
Fig. 5. The potential distribution map for F in Distribution Of The Freshwater Snail Species Fagotia (Gastropoda, Melanopsidae) In Ukraine According To Climatic Factors. I. Fagotia Esperi
Fig. 5. The potential distribution map for F. esperi in Ukraine under climatic conditions projected for 2050. Captions as in fig. 4, Bu — "Southern Buh".
Fig. 4. The potential distribution map for F in Distribution Of The Freshwater Snail Species Fagotia (Gastropoda, Melanopsidae) In Ukraine According To Climatic Factors. I. Fagotia Esperi
Fig. 4. The potential distribution map for F. esperi in Ukraine under contemporary climatic conditions (black squares represent pixels of 10-minute resolution, predicted to be suitable for the species). Convex polygons are drawn around assumed clusters: N — "northern", Ds — "Dnister", Du — "Danube", Dn — "Dnipro".
Potential distribution of invasive boxwood blight pathogen (Calonectria pseudonaviculata) as predicted by process-based and correlative models
<p>R project, R scripts, and data files for reproducing most of the analyses presented in a climatic suitability study for boxwood blight. The README. md file describes how to run the scripts and provides details on data inputs.</p> <p><strong>Abstract: </strong>Boxwood blight caused by <em>Cps</em> is an emerging disease that has had devastating impacts on <em>Buxus</em> spp. in the horticultural sector, landscapes, and native ecosystems. In this study, we produced a process-based climatic suitability model in the CLIMEX program and combined outputs of four different correlative modeling algorithms to generate an ensemble correlative model. All models were fit and validated using a presence record dataset comprised of <em>Cps</em> detections across its entire known invaded range. Evaluations of model performance provided validation of good model fit for all models. A consensus map of CLIMEX and ensemble correlative model predictions indicated that not-yet-invaded areas in eastern and southern Europe and in the southeastern, midwestern, and Pacific coast regions of North America are climatically suitable for <em>Cps</em> establishment. Most regions of the world where<em> Buxus</em> and its congeners are native are also at risk of establishment. These findings provide the first insights into <em>Cps</em> global invasion threat, suggesting that this invasive pathogen has the potential to significantly expand its range.</p>
Predicting potential distributions of large carnivores in Kenya: An occupancy study to guide conservation
<p><span><strong>Aim</strong>:</span><span> Species distribution maps are frequently the foundation upon which species-specific conservation strategies are developed, however, mapping species distribution is challenging, especially across large spatial extents. Our aim was to use a novel empirical approach to predict the national distribution for all six large carnivore species </span><span>found in Kenya to guide conservation and management decisions by identifying knowledge and conservation gaps.</span></p> <p><span><strong>Location</strong>:</span><span> Kenya</span></p> <p><span><strong>Methods</strong>:</span><span> Data on carnivore presence and absence were collected through questionnaires and sightings-based surveys. These data were combined and analysed using single-season false-positive occupancy models, which account for imperfect detections and false positives. </span><span>To inform conservation strategies, </span><span>we used the occupancy outputs to make predictions for unsampled areas and create occupancy-based distribution </span><span>maps, where ψ>0.50, </span><span>to</span><span> (1) quantify differences with IUCN Red List range maps, (2) quantify overlap with wildlife areas and (3) </span><span>identify areas of high carnivore richness</span><span>.</span></p> <p><span><strong>Results</strong>:</span><span> Large carnivore occupancy was associated with land conversion, habitat, and prey availability. Our results suggest that all six species are widely distributed across Kenya and reveal substantial differences in distribution maps compiled by the IUCN Red List. </span><span>More specifically, our occupancy-based distribution maps predict a </span><span>much larger distribution for African wild dog (5.09X), lion (4.77X), and leopard (1.46X), similar distribution for cheetah, and smaller distribution for spotted hyaena (0.84X) and striped hyaena (0.65X). For all large carnivores, the vast majority (~80%) of their predicted distribution falls outside wildlife areas and northern Kenya is predicted to have the highest large carnivore richness.</span></p> <p><span><strong>Main conclusions</strong>:</span> <span>Our results are encouraging as large carnivores may be widely distributed across Kenya, in some cases potentially more so than previously acknowledged. However, much of this range lies outside wildlife areas and represents areas of concern both for conservation and human livelihoods illustrating the challenges of conserving large carnivores across their range.</span></p>
Fig. 4 in An assessment of potential distribution and climate change impacts on a critically endangered primate, the Delacour's langur
Fig. 4. Occurrence records of the Trachypithecus francoisi group based on previous research studies (Nadler et al., 2003; Workman, 2010a; Ebenau et al., 2011; Hendershott et al., 2016; Blair et al., 2021).
Fig. 3 in An assessment of potential distribution and climate change impacts on a critically endangered primate, the Delacour's langur
Fig. 3. Predicted distribution of climatically suitable habitat for the Delacour's langur under a range of different future climate change scenarios: A, MIROC6 models; B, CNRM-ESM2-1 models; C, IPSL-CM6A-LR models.
Fig. 2 in An assessment of potential distribution and climate change impacts on a critically endangered primate, the Delacour's langur
Fig. 2. Potential current distribution of the Delacour's langur generated from Maxent based on eight uncorrelated WorldClim bioclimatic variables.
Fig. 1 in An assessment of potential distribution and climate change impacts on a critically endangered primate, the Delacour's langur
Fig. 1. Occurrence records of the Delacour's langur derived from previous research studies (Nadler & Long, 2001; Nadler et al., 2003; Workman, 2010b; Ebenau et al., 2011; Wojciechowski, 2013; Nadler, 2015; Hoang & Dung, 2016; Linh et al., 2019; Nguyen et al., in press) and our field surveys.
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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)
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.