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431 results for “areas of endemism”
Fig. 2. Area diagram depicting relationships among the 24 in Biogeography of freshwater fishes from the Northeastern Mata Atlântica freshwater ecoregion: distribution, endemism, and area relationships
Fig. 2. Area diagram depicting relationships among the 24 coastal drainages analyzed, obtained by parsimony analysis of endemicity based on freshwater fishes. The topology represents the strict consensus of five equally parsimonious trees obtained through a heuristic search (length= 71 steps, CI = 0.521, RI = 0.709).
Fig. 1 in Biogeography of freshwater fishes from the Northeastern Mata Atlântica freshwater ecoregion: distribution, endemism, and area relationships
Fig. 1. Map showing the Northeastern Mata Atlântica ecoregion, the rivers included in the PAE, and the groups recovered from the analysis. Adjacent freshwater ecoregions are: (327) São Francisco, (329) Paraíba do Sul, and (344) Upper Paraná.
Fig. 2 in Unexpected Echinococcus multilocularis infections in shepherd dogs and wolves in south-western Italian Alps: A new endemic area?
Fig. 2. Multiple alignment of partial mitochondrial cob (124bp) from three specimens identified as Echinococcus multilocularis analyzed in the present paper (the first three input sequences) with: (a) six E. multilocularis sequences retrieved from GenBank after comparison by Local Alignment Search Tool BLAST; (b) five sequences referred to Echinococcus granulosus (Eg, EgG1), E. ortleppi (EgG5), E. canadensis (EgG6-7) and Taenia hydatigena (Thy) retrieved from GenBank. (c) Multiple alignment of partial mitochondrial nad1 (139bp) from three specimens identified as Echinococcus ortleppi analyzed in the present paper (the first three input sequences) with sequences retrieved from GenBank belonging to other representatives of E. ortleppi, E. granulosus, E. canadensis, E. multilocularis, T. krabbei, T. ovis and T. hydatigena. Dots indicate identity with nucleotide of the first sequences listed.
Fig. 1 in Unexpected Echinococcus multilocularis infections in shepherd dogs and wolves in south-western Italian Alps: A new endemic area?
Fig. 1. Locations of wolf (blue dots) and dog (orange dots) fecal samples positive to Echinococcus multilocularis collected during a survey on Echinococcus spp. carried out from June to November 2017 in a mountainous area in the Alps of the Imperia Province, Italy. In the map are also reported the southernmost reports of Echinococcus multilocularis (E. multilocularis) to date in Europe (France, Drs. Boué and Umhang, pers. communication; North-Eastern Italian Alps, Croatia, as in (Beck et al., 2018)). Two dog fecal samples were collected from the same pasture and are represented by a single dot (noted as 2×). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Leishmania presence in bats in areas endemic for leishmaniasis in centralwest Brazil
Fig. 2. Agarose gel demonstrating kDNA PCR products (120bp). M: 100bp marker. 1–17: analyzed samples, of which 2–11, 13 and 16 were considered positive. PC: positive control of Leishmania spp., NC: negative control.
Fig. 4 in Leishmania presence in bats in areas endemic for leishmaniasis in centralwest Brazil
Fig. 4. Identification of Leishmania according to site of collect of the bats per city, Mato Grosso do Sul, Brazil; Grey area - municipal boundary; A – Campo Grande; B – Corumbá; C – Ivinhema; D – Brasilândia.
Fig. 3 in Leishmania presence in bats in areas endemic for leishmaniasis in centralwest Brazil
Fig. 3. Agarose gel demonstrating LnPCR products (350bp). M: 100bp marker, 1–17: analyzed samples, of which 2, 7, 10 and 14 were considered positive. PC: positive control of Leishmania spp., NC: negative control.
Fig. 1. Study area, showing November 2014 and 2016 in Chiggers (Acariformes: Trombiculoidea) do not increase rates of infection by Batrachochytrium dendrobatidis fungus in the endemic Dwarf Mexican Treefrog Tlalocohyla smithii (Anura: Hylidae)
Fig. 1. Study area, showing November 2014 and 2016 sampling sites. Gray and white circles show presence or absence of Batrachochytrium dendrobatidis. Sampling sites in 2010 and 2011 show fungus presence, reported by Cortes in 2014.
Fig. 6 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?
Fig. 6. Relationship between elevation and geographical range of Hybos spp. in Thailand. The number of 1° grids in which a species was recorded is plotted against the median elevation of all records. Line fitted by linear regression in PAST (r2=0.1026).
Fig. 5 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?
Fig. 5. EZPAE down-weighted against homoplasy, using altitudinally zoned mountain ranges as OGU, 'characters' made additive. Strict consensus tree of two equally parsimonious trees (CI = 0.716, RI = 0.534) produced by maximum parsimony analysis with weighted 'characters' and TBR branch swapping in TNT. Symmetrical resampling support is given under the nodes. Alphabetic codes of termini correspond with mountain ranges as abbreviated in Fig. 3; the suffixes 'low' & 'high' refer to low (<1,250m) and high (>1,250m) elevation sample data.
Fig. 4 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?
Fig. 4. EZPAE down-weighted against homoplasy, using altitudinally zoned mountain ranges as OGU, 'characters' made non-additive. Strict consensus tree of four equally parsimonious trees (CI = 0.674, 0.580) produced by maximum parsimony analysis with weighted 'characters' and TBR branch swapping in TNT. Symmetrical resampling support is given under the nodes. Alphabetic codes of termini correspond with mountain ranges as abbreviated in Fig. 3; the suffixes 'low' & 'high' refer to low (<1,250m) and high (>1,250m) sample data.
Fig. 2. PAE using 1 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?
Fig. 2. PAE using 1° grids as OGU. Strict consensus tree of 760 equally parsimonious trees (CI = 0.501, RI = 0.557) produced by maximum parsimony analysis with unweighted 'characters' and TBR branch swapping in TNT. Symmetrical resampling support is given under the nodes (see Fig 1A for explanation of alphabetic codes).
Fig. 3 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?
Fig. 3. PAE using mountain ranges as OGU. Strict consensus tree of nine equally parsimonious trees (CI = 0.745, RI = 0.722) produced by maximum parsimony analysis with weighted 'characters' and implicit enumeration in TNT. Symmetrical resampling support is given under the nodes. Abbreviations. – CM, Cardamom Mountains; DK, Dong Paya Yen – Khao Yai Forest Complex; DL, Daen Lao Range; LP, Luang Prabang Range; NST, Nakhon Si Thammarat Range; PM, Petchabun Mountains; PR, Phuket Range; PPR, Phu Pan Range; TH, Tenasserim Hills; TT, Thanon Thongchai Range. Grid-B and Grid-L refer to 1° grids (B and L in Fig. 1A) that were not assigned to any mountain range.
Fig. 1 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?
Fig. 1. Maps of Thailand showing: A, Grid of 1° of latitude and longitude denoted by single-letters A–W. Mountain ranges are indicated by two- or three letter codes (CD, DK, DL, LP, NST, PM, PPR, PR, TH & TT) and the grids that comprise each range are colour-coded. Grids B and L were not assigned to any mountain range; B, Species richness (number of species) of Hybos present in 1° grids; C, reciprocal weighted endemicity of Hybos spp. calculated for 1° grids.
Data from: mapping endemic freshwater fish richness to identify high priority areas for conservation: an ecoregion approach
<p>Freshwater ecosystems are experiencing accelerating global biodiversity loss. Thus, knowing where these unique ecosystems' species richness reaches a peak can facilitate their conservation planning. By hosting more than 290 freshwater fishes, Iran is a major freshwater fish hotspot in the Middle East. Considering the accelerating rate of biodiversity loss, there is an urgent need to identify species rich areas and understanding of the mechanisms driving biodiversity distribution. In this study, we gathered distribution records of all endemic freshwater fishes of Iran (85 species) to develop their richness map and determine the most critical drivers of their richness patterns from an ecoregion approach. We performed a generalized linear model (GLM) with quasi-Poisson distribution to identify contemporary and historical determinants of endemic freshwater fish richness. We also quantified endemic fish similarity among the 15 freshwater ecoregions of Iran. Results showed that endemic freshwater fish richness is highest in the Zagros Mountains while moderate level of richness was observed between Zagros and Alborz Mountains. High, moderate and low richness of endemic freshwater fish match with Upper Tigris & Euphrates, Namak, and Kavir & Lut Deserts ecoregions respectively. Kura - South Caspian Drainages and Caspian Highlands were the most similar ecoregions and Orumiyeh was the most unique ecoregion according to endemic fish presence. Precipitation and precipitation change velocity since the Last Glacial Maximum were the most important predictors of endemic freshwater fish richness. Areas identified to have the highest species richness have high priority for the conservation of freshwater fish in Iran, therefore, should be considered in future protected areas development.</p>
Data from: Sequential use of niche and occupancy models identifies conservation and research priority areas for two data-poor endemic birds from the Colombian Andes
<p>The lack of high-quality information on data-poor species can hinder efforts to inform conservation actions via spatial distribution modeling. This is particularly true for tropical birds of conservation concern, for which ecological studies and assessments of their conservation status have received limited funding. Here we use a cost- and time-efficient protocol for assessing the distribution of range-restricted taxa and to identify priority areas for their conservation based on a sequential application of Environmental Niche Models (ENMs) and Occupancy-Detection Models. This approach first uses available geographical information and niche-theory to prioritize potential study sites, which can later be surveyed to obtain high-quality presence-absence data to accurately model distributional ranges with limited resources. We apply this protocol to identify priority areas for two Neotropical birds of conservation concern endemic to the Colombian Andes: Yellow-headed Brush-finch (<i>Atlapetes flaviceps</i>) and Tolima Dove (<i>Leptotila conoveri</i>). We first fitted ENMs using spatially-filtered datasets containing all available records up to 2018. We then conducted field surveys across climatically suitable areas identified for both species, carrying out a total of 1750 counts to generate input data for the occupancy models. Overall, our results suggested more extended and more continuous distribution ranges for both species than previously reported, but also identified population strongholds that are not currently represented within the national protected areas system. Both species occupied a narrow elevational belt (~1300–2600) of the Central Andes of Colombia primarily on the slopes of the Magdalena River valley, with isolated populations in the Western and Eastern Andes; these areas have undergone some of the most marked landscape transformations in Colombia. This straightforward protocol maximizes available information and minimizes costs, while allowing for estimation of occurrence probabilities for range-restricted, data-poor taxa.</p>
Dataset: Habitat suitability models to make conservation decisions based on areas of high species richness and endemism
<p>This repository contains the files associated with the following article:</p> <p>Hernández-Quiroz NS, EI Badano, F Barragán-Torres, J Flores & C Pinedo-Álvarez. Habitat suitability models to make conservation decisions based on areas of high species richness and endemism. Biodiversity and Conservation, 27, pp. 3185-3200. <a href="https://doi.org/10.1007/s10531-018-1596-9">https://doi.org/10.1007/s10531-018-1596-9</a></p> <p>The Microsoft Excel file (SM 01-Oak occurrences.xlsx) contains the occurrence points used to calibrate the habitat suitability model of each oak species (59 species in total). This file indicates the name of the species (column A), latitude and longitude of each occurrence point (columns B and C; in geographic coordinates) and the full set of bioclimatic variables (columns D-V) and topographic variables (columns W-Z) associated to each point. These later data are provided as they were gathered from the bioclimatic layers of WorldClim and the topographic layers of the Mexican National Institute of Statistics and Geography. The repository also contains interactive maps indicating the predicted and observed distributions of the 59 Mexican oak species (SM 02-Estimated oak distribution ranges.kmz), and the probability-based and occurrence-based map of oak richness and endemic species (SM 03-Oak richness maps.kmz). These geographic projections are provided in KMZ format to make them easy to visualize in Google Earth (freely available at www.google.com/earth). Details about these KMZ files can be consulted by accessing the file properties after opening them in Google Earth.</p>
Data from: Ancestral area analyses reveal Pleistocene-influenced evolution in a clade of Coastal Plain endemic plants
<p><strong>AIM:</strong> The North American Coastal Plain is currently recognized as a global biodiversity hotspot. However, the mechanisms driving high levels of species richness in a region with relatively low topographic relief and homogeneous climate are unclear. We investigated the evolutionary processes driving ancestral area evolution and diversification in a biodiversity hotspot from both a systematic and biogeographic context using a clade endemic to the hotspot.</p> <p><strong>LOCATION</strong>: North American Coastal Plain</p> <p><strong>TAXON</strong>: The Scrub Mint clade comprises <em>Dicerandra</em>, <em>Conradina</em>, <em>Piloblephis</em>, <em>Stachydeoma</em>, and four species of <em>Clinopodium</em> (Mentheae; Lamiaceae), almost all of which are endemic to the North American Coastal Plain. </p> <p><strong>METHODS</strong>: We generated a dated phylogeny using a target enrichment/capture dataset and then calculated ancestral area using biogeographic models. We uncovered neo- and paleo-endemism hotspots and inferred ancestral potential ranges at each node based on ancestral niche reconstructions and paleoclimatic data to understand the geographic range evolution of subclades. </p> <p><strong>RESULTS</strong>: Ancestral area for the SMC was inferred to be the Florida Panhandle/Apalachicola River basin. A diversification event likely happened around the mid-Pleistocene Transition. Endemism hotspots were recovered in NE Florida, the Atlantic Coastal Ridge, and along the Lake Wales Ridge. Reconstructions of potential ranges support biogeographic findings, with the ancestor of the SMC likely located in the vicinity of the northeastern Gulf Coast during interglacial and glacial periods.</p> <p><strong>MAIN</strong> <strong>CONCLUSIONS</strong>: The timing of diversification events and colonization of new areas by ancestors of the SMC is consistent with the timing of major geological events in the region. The presence of multiple types of endemism highlights the complexity of evolutionary and ecological processes that foster the large number of endemic taxa found in this region. Efforts to identify hotspots in this region will be critical to preserving the remaining pockets of biodiversity threatened by global change.</p>
Reducing the Risk of P. Vivax After Falciparum Infections in Co-endemic Areas
ClinicalTrials.gov study NCT03916003. IPD Sharing: YES. Countries: 3. Publications: 2.
Prevalence of Hookworm Infection and Community Preparedness for Hookworm Vaccine Trials in Endemic Areas of Brazil
ClinicalTrials.gov study NCT00939198. IPD Sharing: Not stated. Countries: 1. Publications: 3.
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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.