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.
3,583
datasets available to search
ShareScore release 0.9.0
Dataset results
3,583 results for “elevations”
Figure 4 in The lycaenid butterfly fauna (Lepidoptera) of Cosñipata, Peru: annotated checklist, elevational patterns, and rarity
Figure 4. El Mirador (red marking), a site occupied by territorial males at 1,720m (image courtesy S. Kinyon).
High-resolution digital elevation model of Klados Gorge, Crete, Greece
<p>High-resolution digital elevation model constructed from photogrammetric processing of drone images taken at Klados Gorge, Crete, Greece in 2017. The authors used <em>Agisoft</em> PhotoScan for the photogrammetric processing and to generate 3D spatial data for further use.</p>
Figure 1 in Rediscovery of Cicindela scabrosa floridana Cartwright (Coleoptera: Cicindelidae) and its elevation to species level
Figure 1. Habitus photographs of typical representatives of the four species of the abdominalis group. A) C. floridana. B) C. scabrosa. C) C. abdominalis. D) C. highlandensis.
Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads. in Map of Guam
Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads.
MAP OF GUA:i\I Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads. in Map of Guam
MAP OF GUA:i\I Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads.
Figure 4 in Rediscovery of Cicindela scabrosa floridana Cartwright (Coleoptera: Cicindelidae) and its elevation to species level
Figure 4. Miami pine rockland habitat at Miami site with an extant population of C. floridana showing small open patches among dense vegetation.
MAP OF GUAM Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads. in Map of Guam
MAP OF GUAM Guam is about 30 miles long and 4 to 8 miles wide. The portion of the island northeast of Agana, the capital, is a limestone plateau 200 to 300 feet in elevation. The docks are at Piti, and a channel 2 miles long extends to the ship anchorage in the outer part of Apra Harbor. Heavy lines on the map are automobile roads, broken lines are trails, and heavy broken lines are poor roads.
Figure 3 in Rediscovery of Cicindela scabrosa floridana Cartwright (Coleoptera: Cicindelidae) and its elevation to species level
Figure 3. Close view of elytra showing differences in color and surface sculpturing of the four species of the abdominalis group. A) C. floridana. B) C. scabrosa. C) C. abdominalis. D) C. highlandensis.
Figure 2 in Rediscovery of Cicindela scabrosa floridana Cartwright (Coleoptera: Cicindelidae) and its elevation to species level
Figure 2. Comparison of elytra of the four species of the abdominalis group, left to right. A) C. floridana. B) C. scabrosa. C) C. abdominalis. D) C. highlandensis. Note the separate post median marginal spot in C. scabrosa and C. abdominalis.
Figures 1-6. Diactis spp. 1 in Tynommatidae, n. stat., a family of western North American millipeds: Hypotheses on origins and affinities; tribal elevations; rediagnoses of Diactis Loomis, 1937, and Florea and Caliactis, both Shelley, 1996; and description of D. hedini, n. sp. (Callipodida: Schizopetalidea)
Figures 1-6. Diactis spp. 1) D. hedini holotype, right gonopod, caudal view. 2) D. hedini holotype, right gonopod, telopodite of the same, medial view. 3) D. hedini holotype, right gonopod, the same, lateral view. 4) D. hedini holotype, right gonopod, distal extremity of the same, anterior view. 5) Telopodite of right gonopod of D. frondifera male from Los Angeles Co., California, lateral view. 6) Telopodite of right gonopod of D. triangula male from San Bernardino Co., California, anterior view. A, process 'A'; B, process 'B'; pfp, prefemoral process; s, solenomere; sb, solenomere branch; tt, tibiotarsus.
Figures 9-11 in Tynommatidae, n. stat., a family of western North American millipeds: Hypotheses on origins and affinities; tribal elevations; rediagnoses of Diactis Loomis, 1937, and Florea and Caliactis, both Shelley, 1996; and description of D. hedini, n. sp. (Callipodida: Schizopetalidea)
Figures 9-11. Colactidinae/Abacionidae comparison. 9) left gonopod of male of Colactis utorum from Utah, lateral view. 10) Adobe photoshop reconstruction of the same with telopodite bent>90° caudad. 11) left gonopod of Abacion tesselatum male from Ohio.
Midpoint attractor models resolve the mid-elevation peak in Himalayan plant species richness
<p>The midpoint attractor models (MPA) of species richness integrate a unimodal environmental favourability gradient and neutral effects forced by geometric constraints and thus extend ecologically neutral mid-domain model. However, both alternative MPA algorithms assume that underlying environmental favourability peaks within the modeling domain. Here, we used elevational distribution data for 1054 plant species occurring in NW Himalaya to explore species richness gradients and MPA performance in species groups defined by biogeography, taxonomy and life form. MPA models achieved an excellent fit, but the two MPA algorithms produced contrasting estimates of midpoint attractor location, especially for species groups with richness originating in lowlands. Therefore, we propose a modification of the MPA model accounting for the environmental favourability peak outside the study domain to reflect these situations. Biogeographic origin was more decisive for midpoint attractor location than taxonomic or life-form classification, indicating relatively low climatic niche conservatism in plants.</p>
Elevational range size patterns of vascular plants in Himalaya contradict Rapoport's rule
<p>1. Elevational range size patterns reflect ecological and evolutionary processes, but they are also affected by geometric constraints. The confounding effect of these constraints led to an ongoing controversy about the elevational Rapoport's rule, which postulates a positive association between the range size and elevation, and about the plausibility of the climate variability hypotheses as its causal explanation.</p> <p>2. Here we used an advanced null modelling approach to disentangle the interacting effects of geometric constraints and species richness gradients on the elevational range size of vascular plants. We collected extensive field data on elevational distribution for 728 vascular plant species occurring in the Ladakh region, Western Himalaya. We supplied these regional data with sub-continental elevational ranges extracted from the literature. Moreover, we used in-situ measured temperatures to quantify temperature variability along an elevational gradient to test the climate variability hypothesis.</p> <p>3. Observed range size patterns were sensitive to methods used to quantify the average range size. Range truncation disproportionately affected regional ranges of low-elevation species and resulted in spurious support of elevational Rapoport's rule. However, when the confounding effects of domain boundaries and richness gradient were controlled, our null models revealed only slight deviations from the random expectations of elevational range size patterns, contrasting with the prediction of the Rapoport's rule. In line with these findings, seasonal and diurnal temperature variability did not change with elevation.</p> <p>4. Synthesis: Geometric constraints combined with underlying species richness gradient create range size patterns seemingly supporting Rapoport´s elevational rule. However, null models accounting for these effects indicate that the range-size of vascular plants in the Himalayas does not increase with elevation. Given the universality of the geometric constraints and species richness gradient, our results suggest that these confounding factors must be controlled when testing Rapoport's rule. The null model approach described here provides an efficient tool to do that.</p>
Fig. 6 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand
Fig. 6. Variation in Equitability (J) and Berger-Parker dominance (DBP) of Diptera (A) and Auchenorrhyncha (B) during 12 months of sampling over six 500 m elevation zones at Doi Inthanon in 2014. Values of J (bars) and DBP (lines) were computed in PAST and 95% confidence intervals obtained by bootstrapping using 9999 random samples. In Kruskal-Wallis H-tests there was a significant difference between the medians for Berger-Parker dominance in Diptera (H = 26.7, p <0.01) and Auchenorrhyncha (H = 14.9, p <0.01). Equitability was significantly different for Diptera (H = 36.5, p <0.01) but not for Auchenorrhyncha (H = 10.7, p = 0.0582).
Fig. 10 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand
Fig. 10. Variation in Mean Monthly Turnover (βwM) of Diptera (A) and Auchenorrhyncha (B) during 12 months of sampling over six 500 m elevation zones at Doi Inthanon in 2014. The mean value of βwM in each elevation zone ± standard error is indicated. Note that the vertical axis does not extend to zero. In Kruskal-Wallis H-tests there was a significant difference between the medians for Diptera (H = 29.0, p <0.01) and Auchenorrhyncha (H = 22.1, p <0.01).
Fig. 2 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand
Fig. 2. Observed species richness (Sobs) of Diptera and Auchenorrhyncha trapped in six elevation zones over 12 months sampling at Doi Inthanon in 2014. Diptera, open circles; Auchenorrhyncha, closed circles.). In Kruskal-Wallis H-tests there was a significant difference between the medians for Diptera (H = 22.1, p <0.01) and Auchenorrhyncha (H = 14.3, p <0.05).
Fig. 1. Relative abundance, A in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand
Fig. 1. Relative abundance, A* (number of individuals caught. trap-1. month-1) of Diptera and Auchenorrhyncha trapped in six elevation zones over 12 months sampling at Doi Inthanon in 2014. Standard errors indicated. Note log10 scale. Data were fitted to a linear regression model in PAST; Diptera, open circles (r2 = 0.8567, p = 0.0081); Auchenorrhyncha, closed circles (r2 = 0.3182, p = 0.2434). In Kruskal-Wallis H-tests of untransformed data there was a significant difference between the medians for Diptera (H = 29.3, p <0.01) but not for Auchenorrhyncha (H = 3.3, p = 0.657).
Fig. 8 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand
Fig. 8. Variation in species turnover measured as βw of Diptera (a) and Auchenorrhyncha (b) during 12 months of sampling over six 500 m elevation zones at Doi Inthanon in 2014. Pairwise calculations of βw between each quadrat of a grid of elevation and month with the quadrat with maximum species richness (April/1,500–2,000 m quadrat for Diptera and June/500–1,000 m quadrat for Auchenorrhyncha) were mapped using the multiquadric gridding algorithm in the gridding module of PAST. Values of βw (indicated by colour scale bar) vary between 0 (complete identity) and 1.0 (complete non-identity). Data are not available for January and February at <500 m and 500–1,000 m.
Fig. 3. Relative abundance, A in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand
Fig. 3. Relative abundance, A* (number of individuals caught. trap-1. month-1) of Diptera and Auchenorrhyncha over 12 months sampling at Doi Inthanon in 2014. Standard errors indicated. Note log10 scale. In Kruskal-Wallis H-tests of untransformed data there was a significant difference between the medians for Diptera (H = 24.5, p <0.05) and Auchenorrhyncha (H = 34.3, p <0.01).
Fig. 9 in Spatiotemporal dynamics of insect diversity in tropical seasonal forests is linked to season and elevation, a case from northern Thailand
Fig. 9. Spatiotemporal variation in species turnover measured as Mean Local Turnover βwL of Diptera (A) and Auchenorrhyncha (B) trapped during 12 months of sampling over six 500 m elevation zones at Doi Inthanon in 2014. Data were plotted on a grid of elevation zone (vertical axis) and months (horizontal axis) and mapped using the multiquadric gridding algorithm in the gridding module of PAST. Values of βwL (indicated by colour scale bar) vary between 0 (complete identity) and 1.0 (complete non-identity). Data are not available for January and February at <500 m and 500–1,000 m.
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.