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2,052 results for “tree species”
FIGURE. Phylogram of Tolypocladium generated from Maximum likelihood analysis of ITS, SSU and LSU sequence data. Purpureocillium lilacinum (CBS 284.36) was selected as an outgroup taxon. The tree topology of the ML analysis was similar to the BI. Maximum likelihood bootstrap values greater than 75 and Bayesian posterior probabilities over 0.90 were indicated above the nodes. The scale bar indicates 0.006 changes. The new species was in blue. in Yunnan-Guizhou Plateau: a mycological hotspot
FIGURE. Phylogram of Tolypocladium generated from Maximum likelihood analysis of ITS, SSU and LSU sequence data. Purpureocillium lilacinum (CBS 284.36) was selected as an outgroup taxon. The tree topology of the ML analysis was similar to the BI. Maximum likelihood bootstrap values greater than 75 and Bayesian posterior probabilities over 0.90 were indicated above the nodes. The scale bar indicates 0.006 changes. The new species was in blue.
FIG. 1.—Bayesian analysis tree for 16S in A New Bromeligenous Species of Fritziana Mello-Leitão, 1937 (Amphibia: Anura: Hemiphractidae) from High Elevations in the Serra Dos Órgãos, Rio de Janeiro, Brazil
FIG. 1.—Bayesian analysis tree for 16S sequence (GTR þ G; lnL ¼ 6452.395) of species of Fritziana. Posterior probability nodal support values (>0.8) from the Bayesian consensus tree are labeled above the branches. Different colors correspond to the conspecific lineages analyzed. Photos provided by R. Pontes (F. ohausi), B. Handam (F. fissilis), L.F.G. Peixoto (F. goeldii), and J.L. Gasparini (F. tonimi). A color version of this figure is available online.
Figure 2 in From the mud to the tree: phylogeny of Austrolebias killifishes, new generic structure and description of a new species (Cyprinodontiformes: Rivulidae)
Figure 2. Phylogenetic relationships of the Austrolebias genus group based on molecular markers [four mitochondrial markers (12s, 16s, cytb and cox1) and six nuclear markers (glyt, rag1, enc1, rh1, sh3px3 and 28s)]. Left, Bayesian analysis (numbers on nodes represent posterior probabilities) and right, maximum parsimony analysis performed under implied weighting (K = 3; numbers on nodes represent symmetric resampling, GC values).
FIGURE 2. Majority rule consensus tree from a in A new species of gecko of the genus Lygodactylus (Sauria: Gekkonidae) from southeastern Kenya
FIGURE 2. Majority rule consensus tree from a Bayesian analysis of concatenated sequences of 16S and RAG-1 for representative Lygodactylus including L. tsavoensis sp. nov. and related species. Numbers at nodes are maximum likelihood bootstrap values/Bayesian posterior probabilities.
Plot Data from Tree Species Inventory in a Nigerian Rainforest v1.1.0
<p>These are plot data from fifteen 40 m by 40 m sample plots established in Oban Division of Cross River National Park, Nigeria, between 23<sup>rd</sup> August 2019 and 9<sup>th</sup> September 2019. We have also included data summaries and RStudio codes used for analysis and generating results for the manuscript entitled: "Impact of human foraging on tree diversity, composition and abundance in a tropical rainforest", submitted for publication as an original research article in Biotropica. All data and R code required to generate the results as shown in the manuscript have been included. </p>
F in Finding the host tree species of Notiobia nebrioides Perty (Coleoptera, Carabidae), a member of the seed-feeding guild at fruit falls in Amazonian non-inundated lowland rainforest
F. 1. Food niches for the Notiobia species community at Reserva Ducke, Central Amazonia.
Dataset on frugivory interactions among tree and animal species in Afrotropical forests
<p>We present the dataset on frugivory interactions among tree and animal species in Afrotropical forests used in the article titled “Trait-matching and sampling effort shape the structure of the frugivory network in Afrotropical forests” by Durand-Bessart C, Cordeiro N, Chapman C, Abernethy K, Forget P-M, Fontaine C and Bretagnolle F; published in NewPhytologist.</p> <p>This dataset was created by the compilation of 256 literature sources, and involved 807 tree and 285 frugivore species across Afrortropical forests. Species characteristics are also included.</p> <p> </p>
Tree species annotations for deep learning
<p>The dataset contains >10,000 labeled tree species and the model weights for tree species detection. Format: Image tiles (.twf) with a 256 × 256 pixel size stride in the PASCAL VOC format. The labels are saved as a .xml. The RGB orthophotos are open source and can be accessed at: https://www.swisstopo.admin.ch/de/geodata/images/ortho/swissimage10.html.</p> <p>The methodology used to create the data is presented in Beloiu et al. 2023, Individual tree-crown detection and species identification in heterogeneous forests using aerial RGB imagery and deep learning, Remote sensing.</p> <p>Table 1. Tree species and the number of labels available for them.</p> <table align="center"> <tbody> <tr> <td> <p><strong>Scientific name</strong></p> </td> <td> <p><strong>Common name</strong></p> </td> <td> <p><strong>Class</strong></p> </td> <td> <p><strong>Total</strong></p> </td> </tr> <tr> <td> <p><em>Picea abies</em></p> </td> <td> <p>Norway spruce</p> </td> <td> <p>10</p> </td> <td> <p><strong>3459</strong></p> </td> </tr> <tr> <td> <p><em>Abies alba</em></p> </td> <td> <p>Silver fir</p> </td> <td> <p>11</p> </td> <td> <p><strong>2375</strong></p> </td> </tr> <tr> <td> <p><em>Pinus sylvestris</em></p> </td> <td> <p>Scots pine</p> </td> <td> <p>15</p> </td> <td> <p><strong>599</strong></p> </td> </tr> <tr> <td> <p><em>Fagus sylvatica</em></p> </td> <td> <p>European beech</p> </td> <td> <p>50</p> </td> <td> <p><strong>4181</strong></p> </td> </tr> <tr> <td> <p><strong><em>Total</em></strong></p> </td> <td> <p> </p> </td> <td> <p> </p> </td> <td> <p><strong><em>10614</em></strong></p> </td> </tr> </tbody> </table>
Phylogenetic Species Trees used in QfO benchmarking
<p>Phylogenetic Trees used in all Species Tree Discordance Challenges of Quest for Orthologs Benchmarking workflow 2018 (https://github.com/qfo/benchmark-webservice/tree/elixir).</p>
Eukaryota, Luca, Vertebrata and Fungi Species Tree used in Quest for Orthologs Benchmarking
<p>Eukaryota, Luca, Vertebrata and Fungi Species Tree used in Quest for Orthologs Benchmarking by the 2018 event workflow (https://github.com/qfo/benchmark-webservice/tree/elixir). It is used specifically by the old variant of the generalized species tree discordance benchmark and defines the multifurcating reference species tree with collapsed edges for some of the more debated splits.</p>
Eukaryota, Luca, Vertebrata and Fungi Species Tree used in Quest for Orthologs Benchmarking
<pre>Eukaryota, Luca, Vertebrata and Fungi Species Tree used in Quest for Orthologs Benchmarking by the 2018 event workflow (https://github.com/qfo/benchmark-webservice/tree/elixir). It is used specifically by the old variant of the generalized species tree discordance benchmark and defines the multifurcating reference species tree with collapsed edges for some of the more debated splits.</pre>
Trees and Alignments for: A species-level phylogenetic framework and infrageneric classification for the genus Maesa (Primulaceae)
<p>Alignments, gene trees and species trees from phylogenomic analyses in Sumanon et al. (in prep.), A species-level phylogenetic framework and infrageneric classification for the genus Maesa (Primulaceae).</p> <p>Raw sequence data are deposited in Sequence Read Archive (SRA) data available on NCBI servers under BioProject number PRJNA774956. Scripts for all phylogenetic analyses are available at https://github.com/pebgroup/Maesa_sptree.</p>
ScienceDex guides
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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.