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3,583 results for “elevations”
Figure 1 in Variation in a Darwin Wasp (Hymenoptera: Ichneumonidae) Community along an Elevation Gradient in a Tropical Biodiversity Hotspot: Implications for Ecology and Conservation
Figure 1. (a) Location of the Serra dos Órgãos National Park (gray shaded area), a protected tropical Atlantic Rain Forest in the State of Rio de Janeiro, southeast Brazil. (b) Map of the 15 study sites and their respective altitudes along the elevational gradient in the Park, where four different phytophysiognomies are observed: (c) lower montane forest (up to 500 m), which presents a 20 m high canopy but normally no other well-defined forest layers; (d) montane forest (500 m to 1500 m), with its clear stratification into arboreal, shrub, and herb layers, and large emergent trees reaching 40 m covered with abundant lianas and epiphytes; (e) high montane forest (1500 m to 2000 m) with smaller trees of up to 10 m covered with mosses and epiphytes, and great diversity of shrubs; and (f) high-altitude grassland, also known as campos de altitude (above 2000 m), dominated by herbal vegetation growing around rocks and scattered shrubs.
Figure 5. Pimplinae wasp community metrics against mean monthly temperature across 15 in Variation in a Darwin Wasp (Hymenoptera: Ichneumonidae) Community along an Elevation Gradient in a Tropical Biodiversity Hotspot: Implications for Ecology and Conservation
Figure 5. Pimplinae wasp community metrics against mean monthly temperature across 15 sites. (a) Abundance; (b) Log10 Species Richness; (c) Log10 Simpson's Index (1/D); and (d) Shannon Index. Lines are the equations of the model in Table 3 ± 95%CI. (a) cubic model; (b,d) quadratic models; and (c): linear model.
Data from "Elevation affects both the occurrence of ungulate browsing and its effect on tree seedling growth for four major tree species in European mountain forests"
<p>This repository contains the field data used in the paper from Bernard et al. on the interactive effect of elevation and ungulate browsing on tree regeneration. This dataset is associated with a github repository containing the code to run the analyses of the paper, publicly available at https://github.com/jbarrere3/BaccaraPaper</p>
Bathymetric elevation models of the Southern Hikurangi Subduction Margin, New Zealand
<p>Multibeam bathymetric data compiled by the National Institute of Water and Atmospheric Research (NIWA), New Zealand, are presented for the southern Hikurangi Subduction Margin, New Zealand. These datasets cover the eastern continental slope of southern Wairarapa, North Island, and Marlborough, South Island, the adjacent northwestern slope of the Chatham Rise, and the southern Hikurangi Trough. The data were collected for scientific research purposes, primarily for the study of continental margin active tectonics and sedimentary systems associated with NIWA SSIF Programme Marine Geological Processes (and its predecessors).</p><p>Prominent features of the data are:</p><ol><li>the numerous submarine canyons and gully systems that incise the continental slopes and deliver sediment from the shelf to the southern Hikurangi Trough. These include the Kaīkoura, Hurunui, Pegasus, Okains, and Pūkākī canyons of NE South Island, the Cook Strait Canyon and its numerous tributaries, and the Opouawe, Pahaua, Honeycomb, and Madden canyon systems of SE North Island;</li><li>Elongate bathymetric ridges along the Marlborough and Wairarapa continental slopes that result from seafloor uplift associated with tectonic thrust faults propagating beneath them;</li><li>The flat basin floor of the 2500-3000 m deep Hikurangi Trough, incised by the meandering Hikurangi Channel; and</li><li>Mernoo Bank on the crest of the Chatham Rise.</li></ol><p><strong>Bathymetric Data</strong></p><p>Two separate bathymetric data sets are provided, covering northern and southern regions. The northern dataset is presented at a 50 m grid resolution, and the southern at 25 m grid resolution. Both datasets are compilations of available multibeam bathymetric data collected on multiple voyages. Primarily, the bathymetric data was collected by NIWA on the RV <i>Tangaroa</i> using Kongsberg 30 kHz (EM300 and EM302) multibeam echo sounders, with some additional data collected by German and US vessels using 12 kHz multibeam echo sounders.</p><p><strong>List of data sets</strong></p><ol><li>32-bit float GeoTIFF grid of offshore Marlborough bathymetry, New Zealand, at 25 m cell size. (WGS 84 / Mercator 41 EPSG:3994 projection)</li><li>32-bit float GeoTIFF grid of offshore Wairarapa bathymetry, New Zealand, at 50 m cell size. (WGS 84 / UTM zone 60S EPSG:32760 projection)</li></ol>
Fig. 6. Canonical variate analysis between A in Quantifying elevational effect on the geometric body shape of Russian beetle Carabus exaratus (Coleoptera: Carabidae)
Fig. 6. Canonical variate analysis between A: dorsal and B: ventral views of Carabus exaratus populations. The colors represent the different levels of altitude: Lower elevation (plain): grey, middle elevation (foothill): green, and higher elevation (mountain): brown. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 4 in Quantifying elevational effect on the geometric body shape of Russian beetle Carabus exaratus (Coleoptera: Carabidae)
Fig. 4. Violin graph of centroid size representing the geometric body size for A: Dorsal and B: Ventral view of C. exaratus. The colors represent the different levels of altitude: Lower elevation (plain): grey, middle elevation (foothill): green, and higher elevation (mountain): brown. Graphical representation of the negative and positive shape contribution of the principal component 1. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5 in Quantifying elevational effect on the geometric body shape of Russian beetle Carabus exaratus (Coleoptera: Carabidae)
Fig. 5. Multivariate regression of shape on centroid size (independent variable) in Carabus exaratus. The colors represent the different levels of altitude: Lower elevation (plain): grey, middle elevation (foothill): green, and higher elevation (mountain): brown. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Quantifying elevational effect on the geometric body shape of Russian beetle Carabus exaratus (Coleoptera: Carabidae)
Fig. 3. Principal Component analysis of the ventral view of Carabus exaratus. The colors represent the different levels of altitude: Lower elevation (plain): grey, middle elevation (foothill): green, and higher elevation (mountain): brown. Graphical representation of the negative and positive shape contribution of the principal component 1. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Quantifying elevational effect on the geometric body shape of Russian beetle Carabus exaratus (Coleoptera: Carabidae)
Fig. 2. Principal Component analysis of the dorsal view of Carabus exaratus. The colors represent the different levels of altitude: Lower elevation (plain): grey, middle elevation (foothill): green, and higher elevation (mountain): brown. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1 in Quantifying elevational effect on the geometric body shape of Russian beetle Carabus exaratus (Coleoptera: Carabidae)
Fig. 1. Representation of dorsal and ventral landmarks of Carabus exaratus. A: dorsal (elytral) view with 19 landmarks, B: ventral view with 18 landmarks.
2020-2022-glacier-elevation-change-data-in-Muztag-Ata-and-Western-Nyainqentanglha-from-Pleiades-DEMs
<p>This data set provides outlier removed, gap filled elevation change values (in meters) of the glaciers in the Muztagh Ata and Western Nyainqentanglha massif in High Mountain Asia from 2020 to 2022.</p>
Elevator
Minecraft-styled elevator. Source: Objaverse 1.0 / Sketchfab
St. Clement's East Elevation
St. Clement's East Elevation Photogrametry Source: Objaverse 1.0 / Sketchfab
Data from: Elevated evolutionary rates of biting biomechanics reveal patterns of extraordinary cranio-dental adaptations in some herbivorous dinosaurs
<p>Adaptation to specialist ecologies is a key innovation that has contributed to the evolutionary success of many vertebrate clades, underpinning the acquisition of diverse skull morphologies. Dinosaurs, which dominated Mesozoic terrestrial faunas, acquired herbivory multiple times, including in clades historically regarded as predominantly carnivorous. The evolution of herbivory in theropod dinosaurs is linked to drastic changes in dental and craniomandibular functional morphology, yet whether such changes occurred more rapidly in herbivorous lineages compared to in carnivorous lineages remains untested in a phylogenetic framework. Here, we infer rates of phenotypic evolution in relative biting edge lengths to test the hypothesis that the acquisition of herbivory is associated with rapid changes in jaw biomechanics. We find elevated rates of biomechanical evolution in theropods with foreshortened and beaked skulls (Oviraptorosauria, <em>Limusaurus</em>), as well as in ceratopsians and <em>Diplodocus</em>. A reduced biting edge length and increased jaw efficiency unites these high-rate lineages, indicating selection for greater efficiency in biting biomechanics. Additionally, we hypothesise that extreme ontogenetic changes within species' lifetimes may be behind some instances of branch-wise elevated rates. Thus, we show how exceptional rates of biomechanical evolution can reveal signatures of adaptations within dinosaur lineages and potentially along ontogenetic sequences.</p>
Elevating Youth Football Talent Management with Artificial Intelligence
Open the record for dataset details and reuse information.
Data for: Interplay of abiotic conditions, density, and body size in shaping demography in a high-elevation toad population
<p>This dataset is used to estimate vital rates of a common toad (<em>Bufo bufo</em>) alpine population, and how they are associated with either abiotic (environmental conditions), biotic (in our case population size), and individual factors (body size). We have individual capture histories for the period 1993-2020 for 1615 males and 933 females, as well as body size measurements taken during capture events. For more info about the study system see: https://peercommunityjournal.org/articles/10.24072/pcjournal.240/</p> <p>We run a capture-mark-recapture model coupled with a growth model, the latter to obtain information on body size for the years when the individuals were not captured. Aside from sex-specific survival, we estimate female breeding probability, since they show intermittent breeding. We include as covariates for these vital rates the length of the active season, the temperature at emergence from hibernation, population size, and body size. </p> <p>We obtained climatic data for the period 1980–2020 from the DaymetCH dataset (data obtained from Bioclimatic maps of Switzerland © WSL, based on station data from the Federal Office of Meteorology and Climatology MeteoSwiss, and elaborated by the Land Change Science group, WSL).</p> <p>The README file further describes each uploaded file</p>
Leaf traits and leaf-to-air temperature differences in tropical plants suggest variability in thermoregulatory capacities across elevations
<p>Understanding thermoregulation in plants is critical to predicting the consequences of global warming on terrestrial ecosystems. I present empirical evidence that leaf traits and leaf-to-air temperature differ among plants from a tropical elevation gradient. These findings suggest the existence of specific plant adaptations for thermoregulation across varying elevational zones.</p>
Deep learning detects entire multiple-size Lunar craters driven by elevation data and topographic knowledge
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Figure 4 in Limited response of a spring bloom community inoculated with filamentous cyanobacteria to elevated temperature and pCO
Figure 4: Biovolume (mm3 l−1) of phytoplankton in different temperature and pCO2 treatments (a: 1°C 390 µatm, b: 1°C 970 µatm, c: 4°C 390 µatm, and d: 4°C 970 µatm). (A) Biovolume of filamentous cyanobacteria. (B) Biovolume of ciliates, dinoflagellates, pennate diatoms and centric diatoms. Error bars indicate standard deviation, n = 3.
Figure 1 in Limited response of a spring bloom community inoculated with filamentous cyanobacteria to elevated temperature and pCO
Figure 1: Environmental conditions during the experiment. (A) Temperature (°C) at ambient (blue: 1°C) and elevated (red: 4°C) conditions. (B) Radiation conditions (PAR, 400–700 nm) during the experiment. Gray areas (A) and error bars (B) indicate standard deviation, n = 2.
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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.