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3,583 results for “elevations”
Multi-temporal elevation changes of Fedchenko Glacier (Tajikistan) from 1928 to 2021
<p>This dataset contains rasters of elevation changes on and around Fedchenko Glacier. All the elevation change maps are provided relatively to a Pléiades DEM acquired on 2021-09-20. Rasters are georeferenced in UTM43, and are provided in the form of *.tif files.</p> <p>For methodological details, please refer to the final publication of the article "Multi-temporal elevation changes of Fedchenko Glacier (Tajikistan) from 1928 to 2021" by Brun and others, or refer to the pre-print available at <a href="https://doi.org/10.31223/X5CX1H">https://doi.org/10.31223/X5CX1H</a></p>
Data from: Environmental variation associated with topography explains butterfly diversity along a tropical elevation gradient
<p>Few studies have evaluated the role of topography on the diversity patterns of biological communities along elevation gradients. We evaluated the influence of microclimate and vegetation structure associated with topographic variation on the richness and composition of species of different families of butterflies on a mountain located in a dry enclave (Chicamocha River Canyon) in the northern Andes, Colombia. We captured butterflies over four months at 18 elevations (300 to 1500 m a.s.l.) in two topographic positions (riverbed and hillslope) using an entomological net and traps baited with fermented fruit. In general, butterfly richness increased with elevation in both topographic positions. However, the richness-elevation relationship changed with butterfly family. The riverbed and hillslope sites host different assemblages of butterflies, and this pattern that was consistent for most families. In the riverbed, two sets of species are recognized along the elevation gradient (one below 700 m a.s.l. and the other above 1000 m a.s.l.), mainly owing to species replacement. On the hillslopes there was no clear pattern of grouping associated with elevation. Microclimate differences between the riverbed and hillslope sites along the elevation gradient were related to the vegetation structure and explained the variation in butterfly species composition. Our results highlight the role of topography not only by explaining the response of species richness and composition to environmental variation determined by elevation, but also as a factor that must be considered in the planning and management of biodiversity conservation in the mountains.</p>
Fig. 14. – Panicum spergulifolium A. Camus, low elevation morphotype. A in Revision of the group previously known as Panicum L. (Poaceae: Panicoideae) in Madagascar
Fig. 14. – Panicum spergulifolium A. Camus, low elevation morphotype. A. Habit; B. Leaf; C. Ligule area; D. Panicle branch; E. Spikelet; F. Lower glume; G. Upper glume; H. Spikelet with glumes removed; I. Lower lemma, dorsal view; J. Lower lemma, ventral view; K. Spikelet with glumes and lower lemma removed; L. Upper lemma, ventral view; M. Upper floret, lateral view; N. Upper lemma, ventral view; O. Upper palea, ventral view; P. Upper palea, dorsal view. [Nanjarisoa et al. 74, K] [Drawing: Lucy T. Smith]
Fig. 15. – Panicum spergulifolium A. Camus, high elevation morphotype. A in Revision of the group previously known as Panicum L. (Poaceae: Panicoideae) in Madagascar
Fig. 15. – Panicum spergulifolium A. Camus, high elevation morphotype. A. Habit; B. Ligule; C. Panicle branch; D. Lower glume, dorsal view; E. Lower glume, ventral view; F. Upper glume, dorsal view; G. Upper glume, ventral view; H. Lower lemma, dorsal view; I. Lower lemma, ventral view; J. Lower palea; K. Upper lemma, dorsal view; L. Upper lemma, ventral view; M. Upper palea, dorsal view; N. Upper floret, the lemma removed. [Vorontsova et al. 1218, K] [Drawing: Lucy T. Smith]
Fig. 20 in Elevation of Pilisaprinus to full generic status with notes on the evolution of termitoxeny in the Saprininae (Coleoptera: Histeridae)
Fig. 20. Excerpt from the unpublished phylogenetic analysis of the Saprininae (Lackner, unpubl. data) showing the position of Pilisaprinus verschureni, Saprinus (Phaonius) pharao Marseul, 1855 and Saprinus (s.str.) semistriatus (Scriba, 1790). Synapomorphies relevant for the phylogenetic placement of Pilisaprinus are numbered: 1 – apical third of 8th sternite of male terminalia with dense setae; 2 – majority of antennal club glabrous apart from large oval or slit-like sensory areas situated on ventral side of club which are densely covered with sensilla (see also Fig. 3); 3 – sensory areas of the antennal club complemented with an apical sensory cap (see also Fig. 3); 4 – pronotal hypomeron setose; 5 – prosternal foveae absent; 6 – metepisternum setose; 7 – antennal annuli present; 8 – sensory structures of the antennal club in a form of slit-like pits not surrounded by sensilla; 9 – inner subhumeral stria absent.
Figs 10–12 in Elevation of Pilisaprinus to full generic status with notes on the evolution of termitoxeny in the Saprininae (Coleoptera: Histeridae)
Figs 10–12. Mouthparts and sensory structures of the antenna of Pilisaprinus verschureni (Thérond, 1959). 10 – mandibles, dorsal view; 11 – labrum, left half showing dorsal view; right half showing ventral view; 12 – antennal club showing sensory structures of the antenna.
Figs 1–9 in Elevation of Pilisaprinus to full generic status with notes on the evolution of termitoxeny in the Saprininae (Coleoptera: Histeridae)
Figs 1–9. External morphology of Pilisaprinus verschureni (Thérond, 1959). 1 – habitus, dorsal view; 2 – same, ventral view; 3 – antennal club, latero-ventral view; 4 – head, dorsal view; 5 – mentum, ventral view; 6 – prosternum; 7 – propygidium and pygidium; 8 – lateral disc of metaventrite + metepisternum; 9 – protibia, dorsal view.
Fig. 5 in A New Species of Nannoscincus Günther (Squamata: Scincidae) from High Elevation Forest in Southern New Caledonia
Fig. 5. Isolated closed forest patch on Mont Çidoa, typical of habitat in the area from which the types of Nannoscincus garrulus n.sp. were collected.
Fig. 2 in A New Species of Nannoscincus Günther (Squamata: Scincidae) from High Elevation Forest in Southern New Caledonia
Fig. 2. Dorsal (upper), lateral (middle), and ventral (lower) views of the head of holotype of Nannoscincus garrulus
Fig. 3 in A New Species of Nannoscincus Günther (Squamata: Scincidae) from High Elevation Forest in Southern New Caledonia
Fig. 3. Left manus of holotype of Nannoscincus garrulus n.sp. (MNHN 2003.1002) showing extensive underside "webbing" between digits of the forelimbs (right) and enlarged dorsal scales at the base of the third and fourth digits (left).
Data Storage for Baylis and Boomhower (2022): LANDFIRE Aspect, Elevation, Slope, and Anderson 13 Fuel Models
<pre># Description Zenodo data storage for large, non-proprietary data used in "The Economic Incidence of Wildfire Suppression in the United States", by Patrick Baylis and Judson Boomhower. Main OpenICPSR repository (contains code and main README.txt): https://www.openicpsr.org/openicpsr/workspace?goToPath=/openicpsr/144601 # Contents This storage mirrors the following offline directories used in the code. Each .tar file contains a directory of the same name. To replicate the existing code, users should decompress each directory into raw/, following the structure used in the code. (Note: as described in the main README, running most of the code requires access to proprietary data which is not included in this storage). ## Resulting directory structure To be consistent with the original source code, included the .tar files should be decompressed into the following directory structure within the directory designated by the RAW global in 01_Code/globals.R in the main reposistory. LANDFIRE/Aspect/ LANDFIRE/DEM_Elevation/ LANDFIRE/Slope/ LANDFIRE/US_140FBFM13_12052016/</pre>
A 30-meter terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine
<p>This dataset contains the China terrace map at 30 m resolution in 2018. The map values and their corresponding classes are as follows:</p> <p><em>0: Non-terrace 1: Terrace 255: No data</em></p> <p>The 30 m China terrace map can also be viewed online at <a href="https://cbw.users.earthengine.app/view/chinaterracemap">https://cbw.users.earthengine.app/view/chinaterracemap</a></p> <p><strong>Citations:</strong></p> <p>When using this dataset, please cite both the dataset and the following data description article:</p> <p><em>Cao, B., Yu, L., Naipal, V., Ciais, P., Li, W., Zhao, Y., Wei, W., Chen, D., Liu, Z., and Gong, P.: A 30 m terrace mapping in China using Landsat 8 imagery and digital elevation model based on the Google Earth Engine, Earth Syst. Sci. Data, 13, 2437–2456, https://doi.org/10.5194/essd-13-2437-2021, 2021.</em></p> <p> </p>
Floral preferences of mountain bumble bees are constrained by functional traits but flexible through elevation and season
Patterns of resource use by animals can clarify how ecological communities have assembled in the past, how they currently function, and how they are likely to respond to future perturbations. Bumble bees (Hymentoptera: Bombus spp.) and their floral hosts provide a diverse yet tractable system in which to explore resource selection in the context of plant-pollinator networks. Under conditions of resource limitation, the ability of bumble bees species to coexist should depend on dietary niche overlap. In this study, we report patterns and dynamics of floral morphotype preferences in a mountain bumble bee community based on ~13,000 observations of bumble bee floral visits recorded along a 1400 m elevation gradient. We found that bumble bees are highly selective generalists, rarely visiting floral morphotypes at the rates predicted by their relative abundances. Preferences also differed markedly across bumble bee species, and these differences were well-explained by variation in bumble bee tongue length, generating patterns of preference similarity that should be expected to predict competition under conditions of resource limitation. Within species, though, morphotype preferences varied by elevation and season, possibly representing adaptive flexibility in response to the high elevational and seasonal turnover of mountain floral communities. Patterns of resource partitioning among bumble bee communities may determine which species can coexist under the altered distributions of bumble bees and their floral hosts caused by climate and land use change.
Semi‐quantitative metabarcoding reveals how climate shapes arthropod community assembly along elevation gradients on Hawaii Island
<p>Spatial variation in climatic conditions along elevation gradients provides an important backdrop by which communities assemble and diversify. Lowland habitats tend to be connected through time, whereas highlands can be continuously or periodically isolated, conditions that have been hypothesized to promote high levels of species endemism. This tendency is expected to be accentuated among taxa that show niche conservatism within a given climatic envelope. While species distribution modeling approaches have allowed extensive exploration of niche conservatism among target taxa, a broad understanding of the phenomenon requires sampling of entire communities. Species-rich groups such as arthropods are ideal case studies for understanding ecological and biodiversity dynamics along elevational gradients given their important functional role in many ecosystems, but community-level studies have been limited due to their tremendous diversity. Here, we develop a novel semi-quantitative metabarcoding approach that combines specimen counts and size-sorting to characterize arthropod community-level diversity patterns along two elevational gradients across two volcanoes on the island of Hawai`i. We find that arthropod communities between the two transects become increasingly distinct compositionally at higher elevations. Resistance surface approaches suggest that climatic differences between sampling localities are an important driver in shaping beta-diversity patterns, though the relative importance of climate varies across taxonomic groups. Nevertheless, the climatic niche position of OTUs between transects was highly correlated, suggesting that climatic filters shape the colonization between adjacent volcanoes. Taken together, our results highlight climatic niche conservatism as an important factor shaping ecological assembly along elevational gradients and suggest topographic complexity as an important driver of diversification.</p>
Figure 1: Study area: A Digital Elevation Model of the North Island and the Manawatū-Whanganui dune field
<p>Figure 1 of article: Managing coastal sand drift in the Anthropocene: A case study of the Manawatū-Whanganui Dune Field, New Zealand, 1800s-2020s; authors: Sampath, Ruwan; Beattie, James; Freitas, Joana Gaspar; journal Environment & History [forthcoming]</p> <p>an article accepted in June 29, 2021</p> <p>https://zenodo.org/badge/DOI/10.5281/zenodo.5075980.svg</p>
La Laguna Catchment, Chile - Surface Elevation Change and Velocity Rasters
<p>Datasets from Robson et al 2022. The zip contains two sub-folders:</p> <p>1) Surface elevation changes 1956 to 2020 with time steps 1956 - 1978, 1978 - 2000, 2000 - 2012, 2012 - 2015, 2015 - 2020. Datasets cover Tapado Glacier, La Laguna Catchment, Chile. Additionally surface elevation changes 2012 - 2020 covering rock glaciers in the La Laguna catchment are included.</p> <p>2) Surface velocity raster (annual displacements between 2012 and 2020) for glaciers and rock glaciers in the La Laguna catchment.</p> <p>For details on the processing, please refer to the publication:</p> <p> Robson, B. A., MacDonell, S., Ayala, Á., Bolch, T., Nielsen, P. R., and Vivero, S (2022). Glacier and Rock Glacier changes since the 1950s in the La Laguna catchment, Chile, The Cryosphere</p> <p> </p>
Supplementary GIS data - Potential and implications of automated pre-processing of LiDAR-based digital elevation models for large-scale archaeological landscape analysis
<p>A supplementary dataset related to the paper discussing preparation of a digital elevation model derived from DMR 5G (LiDAR-based DEM of the Czech Republic) cleaned of modern artificial features. It includes data used as a clipping mask and data produced during the testing phase.</p> <p>Contents:</p> <ul> <li>..\clipping_buffers.gdb\ - Clipping buffers based on ZABAGED dataset used for masking the original data stored as ESRI geodatabase.</li> <li>..\drainages\ - Drainages with Strahler order higher than four (potential watercourses) for the original and filtered DEMs. <ul> <li>drainages_filtered - Drainges identified in the filtered DEM stored as GeoTIFF.</li> <li>drainages_original - Drainges identified in the original DEM stored as GeoTIFF. </li> </ul> </li> <li>..\LSC\ - Locations with significant land surface curvature for the original and filtered DEMs. <ul> <li>LSC_filtered - Significant LSC identified in the filtered DEM stored as GeoTIFF. </li> <li>LSC_original - Significant LSC identified in the original DEM stored as GeoTIFF. </li> </ul> </li> <li>..\visibility\ - Viewsheds computed over the original and filtered DEMs. <ul> <li>Libice\ - Sample viewsheds computed for the early medieval hillfort of Libice. <ul> <li>Libice_visibility_filtered - Viewshed based on the filtered DEM stored as GeoTIFF. </li> <li>Libice_visibility_original - Viewshed based on the original DEM stored as GeoTIFF. </li> <li>observer_points - Observer points used for calculating the viewsheds.</li> </ul> </li> <li>regular_grid\ - Cumulative viewsheds calculated for regularly spaced points in a 10 x 10 km grid with a visibility radius of 5 km and an observer height of 2 m; a total of 574 viewsheds. <ul> <li>visibility_filtered - Cumulative viewshed for the filtered DEM stored as GeoTIFF.</li> <li>visibility_original - Cumulative viewshed for the original DEM stored as GeoTIFF. </li> <li>visibility_test_buffers - Buffers used for the viewshed calculations stored as ESRI shapefile.</li> <li>visibility_test_observers - Observer points used for the viewshed calculations stored as ESRI shapefile.</li> </ul> </li> </ul> </li> </ul> <p> </p> <p>Preprint version of the related paper:</p> <p>Novák, David and Pružinec, Filip, Potential and Implications of Automated Pre-Processing of Lidar-Based Digital Elevation Models for Large-Scale Archaeological Landscape Analysis. Available at SSRN: <a href="https://ssrn.com/abstract=4063514">https://ssrn.com/abstract=4063514</a></p>
Morphological and molecular evidence support elevating Erythroxylum macrophyllum var. savannarum (Erythroxylaceae) to specific status
<p><em>Erythroxylum macrophyllum</em> is a morphologically variable and widely distributed species complex in Central and South America with several sub-specific taxa and numerous species included in its synonymy. A single variety grows in the Colombo-Venezuelan savanna region which can be distinguished from the rest of the <em>E. macrophyllum</em> complex by the size of leaves, cataphyll and stipule characteristics, and shape of calyx lobes. A molecular phylogeny reconstructed from 519 nuclear genes also reveals that the savanna variety is more closely related to <em>E. acuminatum </em>and <em>E. pauciflorum</em> than <em>E. macrophyllum</em>. This phylogenomic evidence also suggests <em>Erythroxylum </em>sect. <em>Macrocalyx</em>, to which <em>E. macrophyllum</em> belongs, is a polyphyletic taxonomic section. We thus propose elevating this variety to specific status. We provide an updated taxonomic description, information about its habitat and distribution, and justify its IUCN categorization of Near Threatened (NT).</p>
Digital Elevation Model from Pléiades stereo images - Upper Tuolumne basin, California, 2017-08-13
<p><br> Digital Elevation Model (DEM) derived from a triplet of stereo images of the Pléiades satellite.<br> The images were acquired on 13th August 2017 and cover a part of the upper Tuolumne basin (California).<br> The DEM was calculated at a 3 m resolution with the Ames Stereo Pipeline software (Beyer et al., 2018).<br> Details about the processing of the images and the accuracy of the DEM are given in Deschamps-Berger et al. (2020).</p> <p> </p> <p>References<br> Beyer, R. A., Alexandrov, O., and McMichael, S. (2018). The Ames Stereo Pipeline: NASA’s open source software for deriving and processing terrain data. <em>Earth and Space Science</em>, 5, 537–548. https://doi.org/10.1029/2018EA00040</p> <p>Deschamps-Berger, C., Gascoin, S., Berthier,<br> E., Deems, J., Gutmann, E., Dehecq, A., Shean, D., and Dumont, M. (2020).<br> Snow depth mapping from stereo satellite imagery in mountainous terrain :<br> evaluation using airborne lidar data. <em>The Cryosphere</em>, (February):1–28. https://doi.org/10.5194/tc-14-2925-2020</p>
Methane fluxes from four elevation zones in a St. Lawrence Estuary salt marsh
<p>Dataset used in <a href="https://iopscience.iop.org/article/10.1088/2752-664X/ac706a/meta">Spartina alterniflora has the highest methane emissions in a St. Lawrence estuary salt marsh - IOPscience</a>.</p> <p>The dataset contains methane fluxes calculated from gas measurements taken over a 40 or 60 minute period using a dark static chamber method. Methane fluxes were measured at six locations in four elevation zones of a northern salt marsh on the St. Lawrence River estuary at La Pocatière, Quebec (47°22'24.7"N 70°03'26.3"W). Additional environmental data was collected including carbon dioxide fluxes, extractable soil nitrate, extractable soil ammonium, extractable soil dissolved organic carbon, extractable soil total dissolved nitrogen, salinity, temperature, water table depth, soil total organic carbon, soil total nitrogen, soil organic carbon to nitrogen ratio and bulk density. Soil cores were collected from 0-15 cm and used for extractable nutrient analysis, bulk density and soil organic carbon and nitrogen analysis. The work was carried out with funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie Grant Agreement 838296, a NSERC Discovery Grant and a Natural Environment Research Council grant number (NE/T012323/1). This dataset is used in a publication entitled <em>Spartina alterniflora</em> has the highest methane emissions in a St. Lawrence Estuary salt marsh in Environmental Research: Ecology (https://doi.org/10.1088/2752- 664X/ac706a), which also contains more details on fieldsite and methodology.</p> <p>Gas samples were collected from dark, static chambers (18L, 26 cm diameter), which were placed onto pre-inserted collars in the vegetated zones (inserted to 2.5 cm, 3 days prior to sampling) or placed directly onto the mudflat. The chambers were insulated and fitted with fans and venting tubes. Gas samples were collected on the 23rd August 2020 from all sites, soil cores were collected between the 24-25th August 2020 and the 19-20th September 2020. Soil samples were collected at 0-15 cm using a 2.5 cm diameter dutch gouge corer.</p> <p>Soil temperature was measured at 10 cm depth using a soil thermometer, (°C, DeltaTrak 11050, Pleasanton, USA), salinity was measured in the laboratory using a portable ATC refractometer. Water table depth was measured using a PVC piezometer, a plastic pipe with tubing was inserted into the piezometer and blown into to determine water table depth through bubbling sound (cm). Soil cores were dried at 60 °C to constant weight and the dry weight over core volume used to calculate bulk density (g cm-3), soil was finely ground and analysed for total organic carbon and total nitrogen (%) using an Elemental Analyser (ThermoFinnigan Flash EA 1112 CN analyser, Carlo Erba, Milan, Italy) with an accuracy of ±5 % for N and ±1 % for C, and a limit of 171 detection of 0.05 % for both N and C. Extractable nitrate+nitrite (assumed to be nitrate) were analysed in soil extractant (2M KCl, 5:1 of extractant to soil) using a microplate reader and methods in Sims et al., 1995 (<a href="https://doi.org/10.1080/00103629509369298">https://doi.org/10.1080/00103629509369298</a>) with a limit of detection of 0.1 ppm and accuracy of ±5%. Extractable dissolved organic carbon and total dissolved nitrogen were analysed in soil extractant (ultrapure water 18.2 MΩ, 5:1 of extractant to soil) on a TOC/TDN analyser (TOC VCSn + TMN-1, Shimadzu, Kyoto, Japan), with a 50 mg C l -1 standard resulting in an accuracy and precision of 3.0 and ±4.4 mg l-1, respectively. CH4 and CO2 concentrations were measured in the gas samples using a gas chromatograph (GC-14, Shimadzu, Kyoto, Japan) fitted with a flame ionisation detector, CO2 was methanised to CH4 before analysis. Standards of CH4 (5.1 ppm) and CO2 (5000 ppm) resulted in an accuracy and precision of 6.6±1.5 and 0.4 ppm, and 5324±324 and 78 ppm, respectively, for CH4 and CO2. Changes in gas concentration over time were converted to fluxes using a linear regression of the linear portion fo the flux and if fluxes were below the minimum detectable concentration difference (see <a href="https://doi.org/10.1002/2017JG003783">https://doi.org/10.1002/2017JG003783</a>), they were set to zero. Results from the experiments were entered into an Excel spreadsheet for ingestion into the Zenodo data repository.</p>
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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
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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.