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2,170 results for “clouds”
Fig. 1 in Insights Into The Spatial And Temporal Ecology Of The Sunda Clouded Leopard Neofelis Diardi
Fig. 1. Study site, showing the home-range of the Sunda clouded leopard derived from radio telemetry.
Fig. 5 in Environmental heterogeneity causes differences in the amphibian assemblage structure of an undisturbed montane cloud forest in southern Mexico
Fig. 5. Canonical Correspondence Analysis of the most common amphibians. The arrow orientation and length represent the association, direction, and strength between the environmental variables and the ordination axis. Species names correspond to: Crm (C. matudai), Plm (Pl. matudai), Pls (Pl. sagorum), Pte (Pt. euthysanota), Bof (B. franklini), Boo (B. occidentalis), and Dex (D. xolocalcae) Environmental acronyms correspond to: Hum (Humidity), Understory_Den (Under story density), Le_Li_depth (leaf litter depth), and Temp (temperature).
Fig. 4 in Environmental heterogeneity causes differences in the amphibian assemblage structure of an undisturbed montane cloud forest in southern Mexico
Fig. 4. (a) Principal Component Analysis, grouping the eight sites present in the core zones according to eight environmental variables taken in each site. Blue triangles: TCZ (El Triunfo core zone) sites; pink circles: QCZ (El Quetzal core zone) site. (b) Eight environmental variables measured in the eight sites (four per core zone). Median (solid line), 25th and 75th percentiles (boundaries of boxes), minimum and maximum (lines).
Fig. 1 in Environmental heterogeneity causes differences in the amphibian assemblage structure of an undisturbed montane cloud forest in southern Mexico
Fig. 1. Location of the two sampled zones, El Triunfo core zone [TCZ] (1) and the El Quetzal core zone [QCZ] (3), in the El Triunfo Biosphere Reserve (ETBR), Sierra Madre de Chiapas, Mexico, and illustration of the sample design (core zones, sites, and plots).
Fig. 3 in Environmental heterogeneity causes differences in the amphibian assemblage structure of an undisturbed montane cloud forest in southern Mexico
Fig. 3. (a) Rank-abundance Curves for the El Triunfo core zone [TCZ] and Quetzal core zone [QCZ] in the El Triunfo Biosphere Reserve. Letters on the Rank-abundance Curves correspond to Crm (C. matudai), Crs (C. stuarti), Pll (Pl. lacertosa), Plh (Pl. hartwegii), Plm (Pl. matudai), Pls (Pl. sagorum), Dus (D. schmidtorum), Pte (Pt. euthysanota), Exs (E. sumichrasti), Lim (L. maculatus), Bof (B. franklini), Boo (B. occidentalis), Bofl (B. flavimembris), and Dex (D. xolocalcae). (b) Nonmetric multidimensional scaling of the eight sites within the core zones in the ETBR. Blue triangles: TCZ sites, pink circles: QCZ sites. (c) Dendrogram of functional groups of the El Triunfo core zone amphibian species, using Euclidian Distance, and tested functional groups by ANOSIM are highlighted in different colors (FG1: green; FG2: brown; FG3: blue; FG4: red, and FG5: yellow).
Fig. 2 in Environmental heterogeneity causes differences in the amphibian assemblage structure of an undisturbed montane cloud forest in southern Mexico
Fig. 2. Box plots of amphibian species diversity in the El Triunfo Biosphere Reserve (ETBR), Chiapas, Mexico, showing the median (solid line), 25th and 75th percentiles (boundaries of boxes), and minimum and maximum (lines). (a) Number of individuals, (b) Species richness (0D), (c) Common species (1D), and (d) Dominant species (2D).
Figs. 2–4 in Myrmecofauna (Hymenoptera: Formicidae) response to habitat characteristics of tropical montane cloud forests in central Veracruz, Mexico
Figs. 2–4. Species richness, diversity profiles, and rank–abundance curves. Fig. 2. Comparison of the richness of woody plants at a sampling coverage of 90% and of ants at 85% coverage, among 5 fragments of tropical montane cloud forest in central Veracruz, Mexico. Statistical differences are considered when 95% confidence intervals do not overlap, whereas no differences are assumed when they do overlap, with an α = 0.05. Fig. 3. Diversity profiles of the ant assemblages of F1–F5 based on the equivalent species number. Statistical differences are considered when 95% confidence intervals do not overlap, whereas no differences are assumed when they do overlap, with an α = 0.05. Fig. 4. Rank–abundance curves of the ant assemblages of F1–F5. Total number of ant incidences in each fragment is 60 traps. Only those species with a relative abundance equal to or higher than 10% in a given fragment are shown. Ant species are numbered in accordance with Table 2.
Figs. 5 and 6. Results from cluster and linkage tree analyses. Fig. 5 in Myrmecofauna (Hymenoptera: Formicidae) response to habitat characteristics of tropical montane cloud forests in central Veracruz, Mexico
Figs. 5 and 6. Results from cluster and linkage tree analyses. Fig. 5. Dendrogram of hierarchical standardized clustering based on the SØrensen similarity index of the studied fragments. The cophenetic correlation coefficient of the cluster is 0.89. The dendrogram displays with continuous lines the divisions for which the SIMPROF test rejects the null hypothesis (where assemblages in that group have no further structure to explore) and with dashed lines the groups of assemblages not separated (at P <0.05) by SIMPROF. Fig. 6. Linkage tree analysis (LINKTREE) showing divisive clustering of fragments (F1–F5) from species compositions constrained by inequalities on one or more environmental variables. Only binary partitions of uncorrelated environmental variables are shown in the cluster. The dendrogram displays with continuous lines the divisions for which the SIMPROF test rejects the null hypothesis (where assemblages in that group have no further structure to explore) and with dashed lines the groups of assemblages not separated (at P <0.05) by SIMPROF.
Fig. 1 in Myrmecofauna (Hymenoptera: Formicidae) response to habitat characteristics of tropical montane cloud forests in central Veracruz, Mexico
Fig. 1. Location of the study area in central Veracruz, Mexico. The black polygons indicate the selected fragments (F1–F5) of tropical montane cloud forest.
FIGURE 6 in A new species of cloud fish of the genus Hypsolebias from Northeast Brazil (Cyprinodontiformes: Rivulidae)
FIGURE 6 | Hypsolebias lulai, male, 50.6 mm SL, Brazil, Rio Grande do Norte, Lagoa Salgada, Coelho stream, rio Trairi basin.
FIGURE 2 in A new species of cloud fish of the genus Hypsolebias from Northeast Brazil (Cyprinodontiformes: Rivulidae)
FIGURE 2 | Hypsolebias lulai, paratype, UFPB 13354, 40.9 mm SL, female; Brazil, Rio Grande do Norte, Lagoa Salgada, Coelho stream, rio Trairi basin.
FIGURE 1 in A new species of cloud fish of the genus Hypsolebias from Northeast Brazil (Cyprinodontiformes: Rivulidae)
FIGURE 1 | Hypsolebias lulai, holotype, UFPB 14713, 44.9 mm SL, male; Brazil, Rio Grande do Norte, Lagoa Salgada, Coelho stream, rio Trairi basin.
FIGURE 5 in A new species of cloud fish of the genus Hypsolebias from Northeast Brazil (Cyprinodontiformes: Rivulidae)
FIGURE 5 | Hypsolebias longignatus from a temporary pool close to type-locality of species, 03°53'52.3"S 38°24'15.26"W, Aquiraz, Ceará, Brazil, rio Pacoti basin.
FIGURE 4 in A new species of cloud fish of the genus Hypsolebias from Northeast Brazil (Cyprinodontiformes: Rivulidae)
FIGURE 4 | Type-locality of Hypsolebias lulai, Brazil, Rio Grande do Norte, Lagoa Salgada, Coelho stream, rio Trairi basin.
Terrestrial Lidar Point Cloud Data for: Evaporation and condensation dynamics within saturated epiphyte communities in a Quercus virginiana forest
<p><span>Terrestrial lidar scans were captured using a BLK360 scanner (Leica Geosystems, Norcross, GA, USA) which has a range of 0.5 – 45 m and measurement rate up to 680,000 points s<sup>−1</sup> at the high-resolution setting. A georeferenced, 3-D point cloud of the study site was generated from 12 scans, approximately 50 m apart in both horizontal directions. Scans were performed in orientations intended to maximize branch exposure to the scanner and to scan during optimal weather conditions to minimize occlusion of features due to noise or movement generated by wind. Scan co-registration was done in Leica Geosystem’s Cyclone Register 360 software using its Visual Simultaneous Localization and Mapping algorithm (Visual SLAM) and resulted in relatively low overall co-registration error ranging from 0.005-0.009 m. From this study site point cloud, manual straight-line measurements from the ground to the sensors were made using Leica’s Cyclone Register 360 software.</span></p>
Planetary Boundary Layer Height Retrievals from the Cloud-Aerosol Transport System (CATS) around the US Southern Great Plains and the Eastern North Atlantic
<p>Planetary Boundary Layer Height (PBLH) retrievals in kilometers from the Cloud-Aerosol Transport System (CATS) around the DOE ARM US Southern Great Plains (SGP) and the Eastern North Atlantic (ENA), using a modified version of the Different Thermo-Dynamics Stability (DTDS) algorithm. Quality control Flags are included as follows:</p> <ul> <li>0 = 'Good Quality'</li> <li>1 = 'Mediate Quality'</li> <li>2 = 'Bad Quality'</li> </ul> <p>In addition, -999 values in the dataset represent no data. <br>The PBLH for daytime denoised CATS photon counts at SGP is named: "daytime-denoised-dtds-pblh-sgp.csv"<br>The PBLH for the original daytime and nighttime data at SGP and ENA, without denoising the data, are named: "original-cats-dtds-pblh-daytime-nighttime-sgp.csv" and "original-cats-dtds-pblh-daytime-nighttime-ena.csv"</p> <p>References: </p> <p>Roldán-Henao, N., Yorks, J., Su, T., Selmer, P., & Li, Z. (2024). Statistically Resolved Planetary Boundary Layer Height Diurnal Variability Using Spaceborne Lidar Data. <em>Remote Sensing. </em></p> <p>Su, T., Li, Z., & Kahn, R. (2020). A new method to retrieve the diurnal variability of planetary boundary layer height from lidar under different thermodynamic stability conditions. <em>Remote Sensing of Environment</em>, <em>237</em>, 111519.</p>
LiDAR 2023, RAW point cloud
<h2>Abstract</h2> <p>RAW LiDAR data from new flights on 30/09/23+ 01/10/23, high point density >10pts/sqm. </p> <p>This depositry contains data generated within the European S34 project. </p> <p> </p> <h2>Metadata Information</h2> <table> <tbody> <tr> <td> <p><strong>Identification</strong></p> </td> </tr> <tr> <td> <p>Full Title</p> </td> <td> <p>LiDAR 2023, RAW data</p> </td> </tr> <tr> <td> <p>Abstract</p> </td> <td> <p>RAW LiDAR data from new flights on 30/09/23+ 01/10/23, high point density >10pts/sqm</p> </td> </tr> <tr> <td> <p>Keywords</p> </td> <td> <p>LiDAR, RAW, 3D point cloud</p> </td> </tr> <tr> <td> <p>Pilot area</p> </td> <td> <p>Áramo</p> </td> </tr> <tr> <td> <p>Associated resources</p> </td> <td> <p>LiDAR-Trajectory (SHP)</p> <p>LiDAR footprints (SHP)</p> <p>Point density map (TIF)</p> <p>AOI, Tile definition (SHP)</p> </td> </tr> <tr> <td> <p>Language</p> </td> <td> <p>English</p> </td> </tr> <tr> <td> <p>URL</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Categories</p> </td> <td> <p>Lidar</p> </td> </tr> <tr> <td> <p><strong>Temporal reference</strong></p> </td> </tr> <tr> <td> <p>Creation date (dd.mm.yyyy)</p> </td> <td> <p>15.12.2023</p> </td> </tr> <tr> <td> <p>Revision date (dd.mm.yyyy)</p> </td> <td> <p>15.12.2023</p> </td> </tr> <tr> <td> <p><strong>Quality and validity</strong></p> </td> </tr> <tr> <td> <p>Representation type</p> </td> <td> <p>Other</p> </td> </tr> <tr> <td> <p>Fromat</p> </td> <td> <p>LAS/LAZ</p> </td> </tr> <tr> <td> <p>Lineage</p> </td> <td> <p>New LiDAR flight to derive high quality terrain data and detect small topographical elements. </p> </td> </tr> <tr> <td> <p>Spatial resolution</p> </td> <td> <p>>10 pts/sqm</p> <p>>20 pts/sqm on the mountain plateau</p> </td> </tr> <tr> <td> <p>Positional accuracy</p> </td> <td> <p><0,15m</p> </td> </tr> <tr> <td> <p>Maintenance information</p> </td> <td> <p>no updates planned</p> </td> </tr> <tr> <td> <p>Coordinate system</p> </td> <td> <p> EPSG 4326</p> </td> </tr> <tr> <td> <p><strong>Constranits related to access and use</strong></p> </td> </tr> <tr> <td> <p>Use limitation</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Access constraint</p> </td> <td> <p>/</p> </td> </tr> <tr> <td> <p>Public/Private</p> </td> <td> <p>Public</p> </td> </tr> <tr> <td> <p><strong>Responsible organisation</strong></p> </td> </tr> <tr> <td> <p>Responsible Contact</p> </td> <td> <p> Victoria Jadot</p> </td> </tr> <tr> <td> <p>Responsible Party</p> </td> <td> <p>Eurosense</p> </td> </tr> <tr> <td> <p><strong>Metadata on metadata</strong></p> </td> </tr> <tr> <td> <p>Contact</p> </td> <td> <p>Victoria Jadot </p> </td> </tr> <tr> <td> <p>Metadata language</p> </td> <td> <p>English</p> </td> </tr> </tbody> </table>
Cappadocia Mobile LiDAR 3D Point Cloud Dataset
<p>The dataset includes 6 3D point cloud files collected with Velodyne VLP-16 mobile LiDAR (*.las) belonging to 4 cultural and natural heritage structures located in Cappadocia, Türkiye. The structures are:</p> <p>1- St. Theodore Church (Interior & Exterior): The Church of St. Theodore is located in Yeşilöz Village in Ürgüp district of Nevşehir. Formerly known as Tagar, now known as Yesiloz Village is approximately 16 km from the center of Urgup district and is a settlement area built on the slope of the valley. The church was carved into a large rock mass on the hill northwest of the village. As a result of excavations near the village, a monastery with a courtyard on three sides was discovered. It is thought that the church belonged to this monastery. The church is called both St. Theodore and Tagar Church. Although it is not known where the name Theodore comes from, it is estimated that this name may have been given because the church was built in the name of St. Theodore. </p> <p>2- Mustafa Efendi Mosque (Interior & Exterior): The masonry Mustafa Efendi Mosque in Bahçeli Village of Ürgüp District of Nevşehir Province is the oldest of the 3 mosques built in the village. It is estimated that it was built about 50 years before the Osman Efendi Mosque, which was presented as a proposed building within the scope of the project, with a construction date of 1746. Although it is known to have a small inscription with the date of construction, this inscription was not found during the survey. According to this information, Mustafa Efendi Mosque is estimated to be a 17th-18th century work.</p> <p>3- Fairy Chimney: The distance between Bahçeli Village where the fairy chimney is located and Urgup district is 15 kilometers and the formations between these two areas are generally natural formations without caps and in the late fairy chimney period. It shows that the fairy chimney is a natural formation without a cap and in the late fairy chimney period. The fairy chimney is in the 1st degree natural protected area.</p> <p>4- Masonry House: Bahçeli Village, where the building examined within the scope of the project is located, is 15 km away from Ürgüp district and is a mixed settlement type. There are approximately 200 cove-carved and masonry historical buildings in the village. A large part of the village, including the structures examined in the village, is a 3rd degree natural protected area. The masonry-rock-carved civil architecture dwelling in Bahçeli Village, Ürgüp District, Nevşehir has not been in use since the 1980s and some of the spaces have been completely lost.</p> <p>The creation of this dataset was funded by the Scientific and Technological Research Council of Türkiye (TUBITAK) 1001 program under Project no. 122Y017.</p> <div> <div> <div> </div> <div> </div> <div> </div> </div> </div>
Data for the publication "Repurposing weather modification for cloud research showcased by ice crystal growth"
<p><span>This repository contains the data of the publication:</span></p> <p><span>"Repurposing weather modification for cloud research showcased by ice crystal growth"</span></p> <p><span>Ramelli et al., 2024, PNAS Nexus</span></p>
Linked collectors and determiners for: Two new species of Megarthrus (Coleoptera, Staphylinidae, Proteininae) from Mexican Cloud Forests.
Natural history specimen data linked to collectors and determiners held within, "Two new species of Megarthrus (Coleoptera, Staphylinidae, Proteininae) from Mexican Cloud Forests". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/db595c03-4859-4d5b-94f6-f9d73a40db69">https://bionomia.net/dataset/db595c03-4859-4d5b-94f6-f9d73a40db69</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/db595c03-4859-4d5b-94f6-f9d73a40db69">https://gbif.org/dataset/db595c03-4859-4d5b-94f6-f9d73a40db69</a>. Formatted as a Frictionless Data package.
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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.