Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
11,177
datasets available to search
ShareScore release 0.9.0
Dataset results
11,177 results for “identify”
Identifying hotspots and priority areas for xenarthran research and conservation
<p><span><b>Aim: </b>Limited funds for conservation and research require the development of prioritization schemes. Traditionally, biodiversity metrics were used to delineate priority areas; however, a growing realization emphasizes that logistic factors should be also considered. Here, we combine species richness, past collection efforts, degree of habitat loss and accessibility to define priority areas and spatially orient fieldwork in a cost-effective manner for xenarthrans, one of the four main mammalian radiation.</span></p> <p><span><b>Location: </b>Neotropics.</span></p> <p><span><b>Methods: </b>We assessed spatial patterns of species richness in Xenarthra and identify diversity hotspots based on species distribution models. Spatial patterns and biases in the Xenarthra past collection efforts were analyzed using a comprehensive database including 33,464 individual records. Finally, we produced priority area indices relating species richness and collection efforts with levels of habitat loss and accessibility (roads and rivers network) to highlight important but neglected areas. </span></p> <p><span><b>Results:</b> Collection efforts were concentrated to a small portion of the Neotropics (central-southern Brazil, eastern Bolivia and north-western Argentina) and were biased toward access routes. Major xenarthran diversity hotspots include the Amazonian lowlands of Bolivia and the dry Chaco of Paraguay and Argentina. Priority areas for research varied depending on the metric analyzed. Amazon holds a high diversity that remains poorly explored. Central Argentina and northeastern Brazil are priority areas for research and conservation given the low sampling efforts, high diversity and endemic species, high levels of habitat loss and a dense road network.</span></p> <p><span><b>Main conclusions: </b>Most areas of the Neotropics lack a proper assessment of the xenarthran assemblage, reflecting extensive knowledge shortfalls. Overall, sites close to roads tend to be better sampled, but many areas with a dense road network are under-sampled, being good candidates for low-cost studies. There is an alarming spatial overlap between Xenarthra diversity hotspots and areas facing intense human modification. Some of the priority areas for research should also be viewed as priority areas for conservation.</span></p>
FIGURE. Flower characteristics comparison of A. P. charlesworthii var. lannaense, B. P. papilio-laoticus (photo. by W. Tongkham) and C. P. Little Trouble (P. charlesworthii x P. barbigerum) (photo. by R. Hella) in Paphiopedilum charlesworthii var. lannaense, a new slipper orchid from Northern Thailand identified by morphological and AFLP analyses
FIGURE. Flower characteristics comparison of A. P. charlesworthii var. lannaense, B. P. papilio-laoticus (photo. by W. Tongkham) and C. P. Little Trouble (P. charlesworthii x P. barbigerum) (photo. by R. Hella)
FIGURE. Some flower variation of Paphiopedilum charlesworthii var. lannaense, whole plant and flower. (photo. by W. Tongkham) in Paphiopedilum charlesworthii var. lannaense, a new slipper orchid from Northern Thailand identified by morphological and AFLP analyses
FIGURE. Some flower variation of Paphiopedilum charlesworthii var. lannaense, whole plant and flower. (photo. by W. Tongkham)
FIGURE. Paphiopedilum charlesworthii var. lannaense, whole plant and flower. A. Flowering plant, B. Flower front view, C. Flower side view and D. Flower back view (photo. by W. Tongkham) in Paphiopedilum charlesworthii var. lannaense, a new slipper orchid from Northern Thailand identified by morphological and AFLP analyses
FIGURE. Paphiopedilum charlesworthii var. lannaense, whole plant and flower. A. Flowering plant, B. Flower front view, C. Flower side view and D. Flower back view (photo. by W. Tongkham)
FIGURE. Dendrogram of P. charlesworthii var. lannaense and 10 other Paphiopedilum species in section Paphiopedilum by 7 AFLP primer combinations, 1= first main group, 2= second main group, 2.1= subgroup 2.1 and 2.2 = subgroup 2.2. in Paphiopedilum charlesworthii var. lannaense, a new slipper orchid from Northern Thailand identified by morphological and AFLP analyses
FIGURE. Dendrogram of P. charlesworthii var. lannaense and 10 other Paphiopedilum species in section Paphiopedilum by 7 AFLP primer combinations, 1= first main group, 2= second main group, 2.1= subgroup 2.1 and 2.2 = subgroup 2.2.
FIGURE. Flower and leaf characteristics comparison of A. P. charlesworthii var. lannaense, B. P. charlesworthii, C. P. vejvarutianum and D. P. barbigerum var. coccineum (photo. by W. Tongkham) in Paphiopedilum charlesworthii var. lannaense, a new slipper orchid from Northern Thailand identified by morphological and AFLP analyses
FIGURE. Flower and leaf characteristics comparison of A. P. charlesworthii var. lannaense, B. P. charlesworthii, C. P. vejvarutianum and D. P. barbigerum var. coccineum (photo. by W. Tongkham)
FIGURE. Dendrogram of P. charlesworthii var. lannaense and 49 other Paphiopedilum species by 6 AFLP primer combinations, 1= Brachypetalum, 2= Cochlopetalum, 3= Parvisepalum, 4= Polyantha, 5= Sigmatopetalum, 6= Paphiopedilum, 7= Laosianum, and 8= Megastaminodium. in Paphiopedilum charlesworthii var. lannaense, a new slipper orchid from Northern Thailand identified by morphological and AFLP analyses
FIGURE. Dendrogram of P. charlesworthii var. lannaense and 49 other Paphiopedilum species by 6 AFLP primer combinations, 1= Brachypetalum, 2= Cochlopetalum, 3= Parvisepalum, 4= Polyantha, 5= Sigmatopetalum, 6= Paphiopedilum, 7= Laosianum, and 8= Megastaminodium.
FIGURE. Flower and leaf characteristics of A. P. charlesworthii var. lannaense, B. P. charlesworthii, C. P. barbigerum var. coccineum and D. P. barbigerum var. sulivongii (photo. by W. Tongkham) in Paphiopedilum charlesworthii var. lannaense, a new slipper orchid from Northern Thailand identified by morphological and AFLP analyses
FIGURE. Flower and leaf characteristics of A. P. charlesworthii var. lannaense, B. P. charlesworthii, C. P. barbigerum var. coccineum and D. P. barbigerum var. sulivongii (photo. by W. Tongkham)
FIGURE. In situ photos of Paphiopedilum charlesworthii var. lannaense. A. limestone mountain at 1,100–1,200 m elevation, B. P. charlesworthii var. lannaense living on vertical cliffs of limestone, C. P. charlesworthii var. lannaense plant, D. flowering plant with flower bud, E., F. flowering plant (flower color was faded because these photos were taken toward the end of flowering period) (photo. By S. Somboonphon) in Paphiopedilum charlesworthii var. lannaense, a new slipper orchid from Northern Thailand identified by morphological and AFLP analyses
FIGURE. In situ photos of Paphiopedilum charlesworthii var. lannaense. A. limestone mountain at 1,100–1,200 m elevation, B. P. charlesworthii var. lannaense living on vertical cliffs of limestone, C. P. charlesworthii var. lannaense plant, D. flowering plant with flower bud, E., F. flowering plant (flower color was faded because these photos were taken toward the end of flowering period) (photo. By S. Somboonphon)
FIGURE. Illustration of Paphiopedilum charlesworthii var. lannaense W. Tongkham, S. Pumikong, N. Potapohn & W. Bundithya A. flower, B. dorsal sepal, C. synsepal, D. petal, E. labellum frontal view, F. labellum side view, G. labellum longitudinal section, H. pedicel, I. pedicel longitudinal section and transverse section, J. stigma and pollen, K. staminode, L. column side view, M. leaf, N. peduncle, bract and pedicel, and O. flowering plant. Drawn by W. Tongkham from S. Pumikong 021001 (holotype QBG! [no. 132572]). in Paphiopedilum charlesworthii var. lannaense, a new slipper orchid from Northern Thailand identified by morphological and AFLP analyses
FIGURE. Illustration of Paphiopedilum charlesworthii var. lannaense W. Tongkham, S. Pumikong, N. Potapohn & W. Bundithya A. flower, B. dorsal sepal, C. synsepal, D. petal, E. labellum frontal view, F. labellum side view, G. labellum longitudinal section, H. pedicel, I. pedicel longitudinal section and transverse section, J. stigma and pollen, K. staminode, L. column side view, M. leaf, N. peduncle, bract and pedicel, and O. flowering plant. Drawn by W. Tongkham from S. Pumikong 021001 (holotype QBG! [no. 132572]).
FIGURE. Distribution map of P. charlesworthii var. lannaense (star), P. charlesworthii (square), P. barbigerum var. coccineum (circle), P. papilio-laoticus (triangle), P. barbigerum var. sulivongii (semi-circle) and P. vejvarutianum (pentagon) (drawn by W. Tongkham) in Paphiopedilum charlesworthii var. lannaense, a new slipper orchid from Northern Thailand identified by morphological and AFLP analyses
FIGURE. Distribution map of P. charlesworthii var. lannaense (star), P. charlesworthii (square), P. barbigerum var. coccineum (circle), P. papilio-laoticus (triangle), P. barbigerum var. sulivongii (semi-circle) and P. vejvarutianum (pentagon) (drawn by W. Tongkham)
Spy in the sky: a method to identify pregnant small cetaceans
<p>Data on sex ratios, age classes, reproductive success and health status are key metrics to manage populations yet can be difficult to collect in wild cetacean populations. Long-term individual-based studies provide a unique opportunity to apply unoccupied aerial system (UAS) photogrammetry to non-invasively measure body morphometrics of individuals with known life history information. The aims of this study were 1) to compare length measurements from UAS photogrammetry with laser photogrammetry and 2) to explore whether UAS measurements of body width could be used to remotely determine pregnancy status, sex or age class in a well-studied bottlenose dolphin population in Scotland. We carried out five boat-based surveys in July and August 2017, with concurrent photo-identification, UAS, and laser photogrammetry. Photographs were measured using bespoke programmes, MorphMetriX for UAS photos and a Zooniverse project for laser photos. In total 64 dolphins were identified using photo-ID, 54 of which had concurrent UAS body length and 47 with laser body length measurements. We also measured body widths at 10% increments from 10-90% of body length for 48 individuals of known sex, age class and/or pregnancy status. There was no significant difference in the length of individuals measured with UAS and laser photogrammetry. Discriminant analyses of the body width-length ratios expected to change during pregnancy, correctly assigned pregnancy status for 14 of the 15 females of known pregnancy status. Only one pregnant female was incorrectly assigned as not pregnant. However, our results showed that length and body width cannot accurately allocate these bottlenose dolphins to sex or age class using photogrammetry techniques alone. The present study illustrates that UAS and laser photogrammetry measurements are comparable for small cetaceans and demonstrates that UAS measurements of body width-length ratio can accurately assign pregnancy status in bottlenose dolphins.</p>
Data from: A new lineage of Galapagos giant tortoises identified from museum samples
<p>The Galapagos Archipelago is recognized as a natural laboratory for studying evolutionary processes. San Cristóbal was one of the first islands colonized by tortoises, which radiated from there across the archipelago to inhabit 10 islands. Here, we sequenced the mitochondrial control region from six historical giant tortoises from San Cristóbal (five long deceased individuals found in a cave and one found alive during an expedition in 1906) and discovered that the five from the cave are from a clade that is distinct among known Galapagos giant tortoises but closely related to the species from Española and Pinta Islands. The haplotype individual collected alive in 1906 is in the same clade as the haplotype in the contemporary population. To search for traces of a second lineage in the contemporary population on San Cristóbal, we closely examined the population by sequencing the mitochondrial control region for 129 individuals and genotyping 70 of these for both 21 microsatellite loci and >12 000 genome-wide single nucleotide polymorphisms [SNPs]. The dataset archived here consists of a VCF file of the SNPs genotyped through ddRAD and a structure file of the 21 microsatellites with the genotypes for the same 64 individuals in each. Only a single mitochondrial haplotype was found, with no evidence to suggest substructure based on the nuclear markers.</p>
Sample of Digitised Books - Images identified as Embellishments. c. 1510 - c. 1900. JPG
<p>A subsample of Digitised Books - Images identified as Embellishments. c. 1510 - c. 1900. JPG https://bl.iro.bl.uk/concern/datasets/59d1aa35-c2d7-46e5-9475-9d0cd8df721e?locale=en</p>
Time-series transcriptome analysis identified differentially expressed genes in broiler chicken infected with mixed Eimeria species
<p>Coccidiosis caused by the <em>Eimeria</em> species is a highly problematic disease in the chicken industry. Here, we used RNA sequencing to observe the time-dependent host responses of <em>Eimeria</em>-infected chickens to examine the genes and biological functions associated with immunity to the parasite. Transcriptome analysis was performed at three time points: 4, 7, and 21 days post-infection (dpi). Based on the changes in gene expression patterns, we defined three groups of genes that showed differential expression. This enabled us to capture evidence of endoplasmic reticulum stress at the initial stage of <em>Eimeria</em> infection. Furthermore, we found that innate immune responses against the parasite were activated at the first exposure; they then showed gradual normalization. Although the cytokine-cytokine receptor interaction pathway was significantly operative at 4 dpi, its downregulation led to an anti-inflammatory effect. Additionally, the construction of gene co-expression networks enabled identification of immunoregulation hub genes and critical pattern recognition receptors after <em>Eimeria</em> infection. Our results provide a detailed understanding of the host-pathogen interaction between chicken and <em>Eimeria</em>. The clusters of genes defined in this study can be utilized to improve chickens for coccidiosis control.</p>
Differences in local immune cell landscape between Q fever and atherosclerotic abdominal aortic aneurysms identified by multiplex immunohistochemistry
<p><strong>Background:</strong> Chronic Q fever is a zoonosis caused by the bacterium <em>Coxiella burnetii</em> which can manifest as infection of an abdominal aortic aneurysm (AAA). Antibiotic therapy often fails, resulting in severe morbidity and high mortality. Whereas previous studies have focused on inflammatory processes in blood, the aim of this study was to investigate local inflammation in aortic tissue.</p> <p><strong>Methods:</strong> Multiplex immunohistochemistry was used to investigate local inflammation in Q fever AAAs compared to atherosclerotic AAAs in aorta tissue specimen. Two six-plex panels were used to study both the innate and adaptive immune system.</p> <p><strong>Results: </strong>Q fever AAAs and atherosclerotic AAAs contained similar numbers of CD68<sup>+</sup> macrophages and CD3<sup>+</sup> T cells. However, in Q fever AAAs the number of CD68<sup>+</sup>CD206<sup>+</sup> M2 macrophages was increased, while expression of GM-CSF was decreased compared to atherosclerotic AAAs. Furthermore, Q fever AAAs showed an increase in both the number of CD8<sup>+</sup> cytotoxic T cells and CD3<sup>+</sup>CD8<sup>-</sup>FoxP3<sup>+</sup> regulatory T cells. Lastly, Q fever AAAs did not contain any well-defined granulomas.</p> <p><strong>Conclusions:</strong> These findings demonstrate that despite the presence of pro-inflammatory effector cells, persistent local infection with <em>C. burnetii</em> is associated with an immune suppressed micro environment.</p> <p><strong>Funding:</strong> This work was supported by SCAN consortium: European Research Area - CardioVascualar Diseases (ERA-CVD) grant [JTC2017-044] and TTW-NWO open technology grant [STW-14716].</p>
Figure 6 in Wanted, tracked down and identified: Mesozoic non-biting midges of the subfamily Chironominae (Chironomidae, Diptera)
Figure 6. Palaeocentron krzeminskii, adult male, MP/4020 (ISEZ PAN); mid-Cretaceous, probably Albian–Cenomanian; Hukawng Valley, Kachin State, Myanmar. A–E, tibial apices of fore (A, B) mid- (C) and hindleg (D, E), with bristle fan magnified (E). F, G, thorn-like bristles on hindleg tibia: arrangement (F) and shape (G).
Figure 4 in Wanted, tracked down and identified: Mesozoic non-biting midges of the subfamily Chironominae (Chironomidae, Diptera)
Figure 4. Palaeocentron krzeminskii, adult male, MP/4020 (ISEZ PAN); mid-Cretaceous, probably Albian–Cenomanian; Hukawng Valley, Kachin State, Myanmar. A, inclusion in amber. B, Fourier transform infrared spectroscopy (attenuated total reflectance) spectrum no. 17497 IAA, obtained from amber piece with the examined inclusion.
Figure 3 in Wanted, tracked down and identified: Mesozoic non-biting midges of the subfamily Chironominae (Chironomidae, Diptera)
Figure 3. Pseudochironomini? incertae sedis, adult male, PIN 3130/223; Late Cretaceous, Santonian; Yantardakh, Taimyr Peninsula, Russia. A, inclusion in amber embedded in epoxy resin. B, habitus. C, D, wing, with RM vein area magnified (D). E, F, tibial armature of mid (E) and hindleg (F). G, H, hypopygium in dorsolateral (G) and ventrolateral aspect (H).
Figure 2 in Wanted, tracked down and identified: Mesozoic non-biting midges of the subfamily Chironominae (Chironomidae, Diptera)
Figure 2. Mesoacentron kaluginae, adult male, PIN 3130/224; Late Cretaceous, Santonian; Yantardakh, Taimyr Peninsula, Russia. A, B, wing, with anal lobe and squama magnified (B). C, D, tibial armature of mid (C) and hindleg (D). E, hypopygium, ventral aspect. F, anal point. G, H, hypopygial volsellae: superior (green), inferior (blue), digitus (yellow), pseudovolsella (red) and pars ventralis (purple) photographed (G) and drawn (H).
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.