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Dataset results
12 results for “data-poor”
Figure 1 in Why we should develop guidelines and quantitative standards for using genetic data to delimit subspecies for data-poor organisms like cetaceans
Figure 1. Depiction of the divergence of lineages with four times (T1–T4) chosen to illustrate different levels of biological organization. At T1 the yellow lineage is found across the distribution and although there are likely Demographically Independent Populations (DIPs) that differ in frequencies of the blue, yellow, and red lineages, there are no discontinuities. At T2 some lineages may be diagnosable but likely do not yet appear to be separate lineages. At T3 three groups (the blue/green, yellow, and orange/red lineages) meet the subspecies definition (they are diagnosable and appear to be diverging separately). The divergence level is not sufficient that reconvergence can be ruled out. Between T3 and T4, barriers to gene flow change such that the yellow lineage comes into contact with the blue/green and red-dominated lineages. Blue has diverged in a manner by which gene flow does not resume and the green/yellow lineage dies out. The yellow lineage reconverges and persists alongside the red lineage with a small level of gene flow (orange). At T4 the blue lineage is a species evolving separately from the yellow/red species. The yellow/red species has two subspecies that are both diagnosable and partially diverged.
Data for: An integrated population model and population viability assessment for the southern population of a data-poor species
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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>
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
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Data from: The challenge of modeling niches and distributions for data-poor species: a comprehensive approach to model complexity
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Reconstructing Blood Flow in Data-Poor Regimes: A Vasculature Network Kernel for Gaussian Process Regression
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Local ecological knowledge of fisheries charts decline of sharks in data-poor regions
<p>Scientific knowledge is lacking on marine species of economic and conservation importance, hindering their sustainable management. Local Ecological Knowledge (LEK) has the potential to provide valuable insights on large (spatial and temporal) scales, by drawing on the collective experiences of those who work closely with the taxa of interest. This study explored the status of shark population over time in four countries across eastern and southern Arabia (i.e. Kuwait, Bahrain, Oman and Yemen). Results indicate strong declines, with highly experienced fishermen reporting greater perceived declines (80%) in the abundance of sharks (in general), with mean year of perceived decline starting in the late 1990s to early 2000s. For three specific taxa investigated, hammerhead sharks (e.g. Sphyrna mokarran) had the greatest mean perceived decline (80%), while even the group with the least decline (small carcharhinids) had mean perceived declines of 50%. Management measures are urgently required in the region to ensure sustainability of historic shark fisheries that provide food security and coastal livelihoods (e.g. Yemen and Oman), and to prevent regional extinctions (e.g. hammerhead sharks). Older and more experienced fishermen who are both; witness to the greatest declines and may have local standing and influence could be valuable resources in developing more community-based sustainable fisheries, especially given the apparent lack of success of formal management measures.</p>
Local ecological knowledge of fisheries charts decline of sharks in data-poor regions
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In vitro transcriptomic analyses reveal pathway perturbations, estrogenic activities, and potencies of data-poor BPA alternative chemicals
GEO Series GSE211183. Homo sapiens; synthetic construct. 768 samples. Type: Expression profiling by high throughput sequencing.
High-Throughput Transcriptomics Toxicity Assessment of Eleven Data-Poor Bisphenol A Alternatives
GEO Series GSE271332. Homo sapiens. 286 samples. Type: Expression profiling by high throughput sequencing.
Application of a New Approach Methodology (NAM)-based Strategy for Genotoxicity Assessment of Data-poor Compounds
GEO Series GSE213454. Homo sapiens. 276 samples. Type: Expression profiling by high throughput sequencing.
Using genomics and morphometrics to monitor data-poor and commercially exploited octopod populations
<p>Raw demultiplexed data as fastq.gz files</p> <p>Processed files for each species dataset (Neutral, Selection, Autosomal)</p> <p>Mastersheet containing sample information, GenBank accession numbers, morphological raw data, haplotype number, and whether samples were used in the SNP analyses</p> <p>Codes for morphological and SNP analyses</p> <p>Metadata</p>
ScienceDex guides
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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.