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562 results for “cloud forest”
FIGURE 4 in Anticyphon gen. nov., a new genus of Scirtidae (Coleoptera: Scirtoidea) inhabiting high altitude Andean cloud forests and páramo formation
FIGURE 4. Anticyphon paramoensis sp. nov., ventrum, SEM micrograph. Abbreviations: mf—mesoventral fossa, mpmesoventral process, sgr—subgenal ridge.
FIGURE 7 in Anticyphon gen. nov., a new genus of Scirtidae (Coleoptera: Scirtoidea) inhabiting high altitude Andean cloud forests and páramo formation
FIGURE 7. Anticyphon ecuadorensis sp. nov., male genitalia. A) penis (right parameroid broken), B) tegmen, C) sternite VIII, D) sternite IX, E) tergite VIII, F) tergite IX. Scale bar = 0.5 mm.
FIGURE 6 in Anticyphon gen. nov., a new genus of Scirtidae (Coleoptera: Scirtoidea) inhabiting high altitude Andean cloud forests and páramo formation
FIGURE 6. Anticyphon davidsoni sp. nov., male genitalia. A) male genitalia, B) penis, C) tegmen, D) sternite VIII, E) sternite IX, F) tergite VIII, G) tergite IX. Scale bar = 0.5 mm. Abbreviations: dpp—dorsal process of penis, pe—penis, pm—paramere, pmd—parameroid, s—sternite, t—tergite, tg—tegmen, trg—trigonium.
FIGURE 2 in Anticyphon gen. nov., a new genus of Scirtidae (Coleoptera: Scirtoidea) inhabiting high altitude Andean cloud forests and páramo formation
FIGURE 2. Anticyphon gen. nov., mandibles (A, D, G), maxillae (B, E, H), labia (C, F, I). A – C) A. davidsoni sp. nov., D – F) A. oyonensis sp. nov., G – I) A. paramoensis sp. nov.
FIGURE 1. Anticyphon gen. nov., habitus. A in Anticyphon gen. nov., a new genus of Scirtidae (Coleoptera: Scirtoidea) inhabiting high altitude Andean cloud forests and páramo formation
FIGURE 1. Anticyphon gen. nov., habitus. A) A. davidsoni sp. nov., B) A. ecuadorensis sp. nov., C) A. oyonensis sp. nov., female, D) A. oyonensis sp. nov., male E) A. paramoensis sp. nov., light form, F) A. paramoensis sp. nov., dark form, G) A. peruvianus sp. nov., H) A. santanderensis sp. nov. Scale bars = 1.0 mm.
Cloud Forest Library
<p><strong>Cloud Forest Library</strong><br>This dataset is a point cloud collection of trees, shrubs, herbaceous plants, and other landscape elements. Each specimen is available as in .laz, .e57, .pcd, .ply, .xyz, and .3dm format. See the collection online at <a href="https://xyz.cct.lsu.edu/">xyz.cct.lsu.edu</a>.</p> <p><strong>License</strong><br>This dataset is released under the <a href="https://creativecommons.org/publicdomain/zero/1.0/">Creative Commons Zero 1.0 Universal Public Domain Dedication</a> by Brendan Harmon.</p>
dataset for "basic setting", "+ binary semantic loss", "+ class weights", "+ height weights", "+ region weights", "+ elastic distortion and subsampling", "+ TreeMix" in paper Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning
<p>dataset for "basic setting", "+ binary semantic loss", "+ class weights", "+ height weights", "+ region weights", "+ elastic distortion and subsampling", "+ TreeMix" in paper Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning</p>
FIG. 1 in Epiphyllous bryophyte diversity in lowland rain forest and lowland cloud forest of French Guiana
FIG. 1. ― Species accumulation curves and estimated total number of species (*) of epiphyllous bryophytes in the understory of lowland cloud forest (LCF) and lowland rain forest (LRF) at Nouragues, French Guiana.
Fig. 23 in A new genus of Cicadellini (Hemiptera: Cicadellidae) from the Oaxacan Cloud Forest, with taxonomic notes on allied red-striped genera
Fig. 23. Gillonella ampulla Nielson & Godoy, 1995 photographed in situ. Photo taken by Andrey Peraza.
Figs 19–22 in A new genus of Cicadellini (Hemiptera: Cicadellidae) from the Oaxacan Cloud Forest, with taxonomic notes on allied red-striped genera
Figs 19–22. Gillonella ampulla Nielson & Godoy, 1995, ♂ from Braulio Carrillo (MNCR), male terminalia. 19. Aedeagus, lateral view. 20. Aedeagus, posterior view. 21. Asymmetrical processes adjoined to anal tube, dorsal view. 22. Connective, ventral view.
Fig. 10 in A new genus of Cicadellini (Hemiptera: Cicadellidae) from the Oaxacan Cloud Forest, with taxonomic notes on allied red-striped genera
Fig. 10. Habitat of Christopherus mictlantecuhtli gen. et sp. nov. Ancient Cloud Forest from Sierra Juárez, Oaxaca, Mexico. Images taken by Juvenal Aragón-Parada.
Figs 11–13 in A new genus of Cicadellini (Hemiptera: Cicadellidae) from the Oaxacan Cloud Forest, with taxonomic notes on allied red-striped genera
Figs 11–13. Gillonella ampulla Nielson & Godoy, 1995, holotype, ♂ (CASENT 19796), habitus. 11. Body, dorsal view. 12. Body, lateral view. 13. Face, anterior view.
Figs 14–18 in A new genus of Cicadellini (Hemiptera: Cicadellidae) from the Oaxacan Cloud Forest, with taxonomic notes on allied red-striped genera
Figs 14–18. Gillonella ampulla Nielson & Godoy, 1995, holotype, ♂ (CASENT 19796), terminalia. 14. Pygofer and subgenital plate, lateral view. 15. Anal tube, lateral view. 16. Style, ventral view. 17. Aedeagus, basal atrial process, and asymmetrical processes adjoined to anal tube, lateral view. 18. Labels. a = minute tooth on posterior margin; b = dorsum of pygofer sclerotized; c = joint of aedeagus with asymmetrical processes adjoined to anal tube; d = asymmetrical processes tips.
Figs 4–8 in A new genus of Cicadellini (Hemiptera: Cicadellidae) from the Oaxacan Cloud Forest, with taxonomic notes on allied red-striped genera
Figs 4–8. Christopherus mictlantecuhtli gen. et sp. nov., holotype, ♂ (INHS), terminalia. 4. Pygofer, lateral view. 5. Subgenital plates and styles, ventral view. 6. Styles, ventral view. 7. Aedeagus and basal atrial process, lateral view. 8. Aedeagus and paraphysis, posterior view.
Figs 1–3 in A new genus of Cicadellini (Hemiptera: Cicadellidae) from the Oaxacan Cloud Forest, with taxonomic notes on allied red-striped genera
Figs 1–3. Christopherus mictlantecuhtli gen. et sp. nov., holotype, ♂ (INHS), overall habitus. 1. Body, dorsal view. 2. Body, lateral view. 3. Face, anterior view.
Replicated radiation of a plant clade along a cloud forest archipelago dataset
<p>Raw data complementary of https://github.com/eaton-lab/Orienotinus-phylogeny repository</p> <p>Assembly output of <em>Oreinotinus </em>species (<em>Viburnum</em>, Adoxaceae) using ipyrad pipeline and morphological matrix:</p> <p>List of files:</p> <ul> <li><code>full_dataset.loci</code> Custom format that shows each individual locus with variable sites indicated.</li> <li><code>full_dataset.phy </code>Concatenated RAD loci in Phylip format</li> <li><code>full_dataset.seqs.hdf5</code> Sequences formated as HDF5 file</li> <li><code>full_dataset.snps</code> Phylip files that includes only variable sites (SNPs)</li> <li><code>full_dataset.snps.hdf5</code> SNPs formated as HDF5 file</li> <li><code>full_dataset.snpsmap</code> Information about location (locus) of SNPs</li> <li><code>full_dataset_stats.txt</code> Statistics about the assembly</li> <li><code>leaf_traits_measurements.tsv</code> TSV file that contains leaf measurments used in the discriminant analyses.</li> <li><code>canopy_data.txt</code> Canopy cover data</li> <li><code>central_plateau_data.txt</code> Macroenvironmental data for the Chiapas central plateau</li> <li><code>full_distribution.txt</code> Specimen metadata and coordinates for all the points for Oreinotinus distribution</li> <li><code>leaf_wetness_temp.txt</code> Climate station data for leaf wetness, temperature</li> <li><code>leaf_traits_measurements.tsv</code> TSV file that contains leaf measurments used in the discriminant analyses.</li> <li><code>tree_accessions.txt</code> Species-level tree accessions with specimen metadata</li> </ul>
Detection of standing retention trees in boreal forests with airborne laser scanning point clouds and multispectral imagery
<p>1. In a landscape consisting primarily of intensive forestry interspersed with some protected areas, multifunctional forestry with retention trees can play a crucial role in nature conservation. Accurate mapping of retention trees is important for guiding landscape-level conservation and forest management and improving landscape connectivity. Sizeable dead and living retention trees play a particularly important ecological role but even their large-scale inventory is often intensive through field work and/or inaccurate. We aimed to detect and classify retention trees using the novel nationwide Finnish airborne laser scanning (ALS) data (~ 5 pulses/m<sup>2</sup>) in conjunction with unrectified color-infrared (CIR) aerial imagery. 2. Applying photogrammetric principles, we added spectral information from the CIR imagery to the ALS-derived point cloud. For a training dataset of 160 retention trees from 19 stands and a geographically separate validation dataset of 79 trees from 8 stands, we segmented trees via individual tree detection (ITD), removed most trees belonging to the regenerating vegetation layer, and classified trees into living conifers, living broadleaves, and dead trees by linear discriminant analysis. 3. The detection rate via ITD differed considerably for dead and living trees, with 41.7% of all dead and 83.8% of all living trees being detected with relatively low commission error rates. Dead trees with smaller diameters and heights were more likely missed, while grouping caused living tree omission. For classification into living conifers, living broadleaves, and dead trees, an overall accuracy of 67.3% was achieved in training and 71.2% in validation data only ALS-derived metrics. When adding spectral metrics, the overall accuracies were 79.6% and 61.0% for training and validation, respectively. 4. Our findings imply that wall-to-wall large-scale high density ALS data can be used to detect retention trees rather accurately – even larger dead trees – and that metrics derived solely from ALS data can accurately classify detected retention trees into living conifers, living broadleaves, and dead trees. Considering the ecological value of retention trees, our results are promising and indicate that ALS data of the studied pulse density are a cost-effective option for large area mapping of retention trees in countries with such data available.</p>
Fig. 5 in Abundance and microhabitat use of the Endangered toad Rhinella yanachaga (Anura: Bufonidae) in the cloud forest of Yanachaga Chemillén National Park, Peru
Fig. 5. Comparisons of the sizes of Rhinella yanachaga individuals. (A) Differences in size of females in dry and wet seasons. (B) Differences in size of males in dry and wet seasons. (C) Differences in size between males and females. (D) Differences in the size of individuals with respect to microhabitats. The different letters indicate significant differences at p ≤ 0.05 according to the Tukey test after GLMM. Error bars represent standard errors.
Fig. 4 in Abundance and microhabitat use of the Endangered toad Rhinella yanachaga (Anura: Bufonidae) in the cloud forest of Yanachaga Chemillén National Park, Peru
Fig. 4. Correlations between the elevation and size of Rhinella yanachaga according to sex. The model presents correlation factors of r2 = 0.34; p = 0.01 for females and r2 = 0.003; p = 0.41 for males. The colors indicate sex (blue for males and red for females) and the shaded areas indicate the 95% confidence limits.
Fig. 2 in Abundance and microhabitat use of the Endangered toad Rhinella yanachaga (Anura: Bufonidae) in the cloud forest of Yanachaga Chemillén National Park, Peru
Fig. 2. Number of Rhinella yanachaga individuals per transect, T1 = 2,800–2,700 m, T2 = 2,700–2,600 m, T3 = 2,600–2,500 m, and T4 = 2,500–2,400 m, according to the elevation gradient for both sexes, in (A) dry season and (B) wet season. (C) Correlation between the abundance of Rhinella yanachaga and elevation for both sexes and seasons. The grey band indicates the 95% confidence limits.
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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.