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6 results for “gamma diversity”
Data from: Evolution of floral diversity: genomics, genes and gamma
A salient feature of flowering plant diversification is the emergence of a novel suite of floral features coinciding with the origin of the most species-rich lineage, Pentapetalae. Advances in phylogenetics, developmental genetics and genomics, including new analyses presented here, are helping to reconstruct the specific evolutionary steps involved in the evolution of this clade. The enormous floral diversity among Pentapetalae appears to be built on a highly conserved ground plan of five-parted (pentamerous) flowers with whorled phyllotaxis. By contrast, lability in the number and arrangement of component parts of the flower characterize the early-diverging eudicot lineages subtending Pentapetalae. The diversification of Pentapetalae also coincides closely with ancient hexaploidy, referred to as the gamma whole-genome triplication, for which the phylogenetic timing, mechanistic details and molecular evolutionary consequences are as yet not fully resolved. Transcription factors regulating floral development often persist in duplicate or triplicate in gamma-derived genomes, and both individual genes and whole transcriptional programmes exhibit a shift from broadly overlapping to tightly defined expression domains in Pentapetalae flowers. Investigations of these changes associated with the origin of Pentapetalae can lead to a more comprehensive understanding of what is arguably one of the most important evolutionary diversification events within terrestrial plants.
Data from: Use of alpha, beta, and gamma diversity measures to characterize seed dispersal by animals
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Data from: Evolution of floral diversity: genomics, genes and gamma
Open the record for dataset details and reuse information.
Estimating alpha, beta, and gamma diversity through deep learning
<p>The reliable mapping of species richness is a crucial step for the identification of areas of high conservation priority, alongside other value considerations. This is commonly done by overlapping range maps of individual species, which requires dense availability of occurrence data or relies on assumptions about the presence of species in unsampled areas deemed suitable by environmental niche models. Here we present a deep learning approach that directly estimates species richness, skipping the step of estimating individual species ranges. We train a neural network model based on species lists from inventory plots, which provide ground truthing for supervised machine learning. The model learns to predict species richness based on spatially associated variables, including climatic and geographic predictors, as well as counts of available species records from online databases. We assess the empirical utility of our approach by producing independently verifiable maps of alpha, beta and gamma plant diversity at high spatial resolutions for Australia, a continent with highly contrasting diversity patterns. Our deep learning framework provides a powerful and flexible new approach for estimating biodiversity patterns.</p>
Code and data for 'Alpha, beta and gamma diversity in intact, mixed and transformed landscapes'
<p>The data and scripts in this database are analyses for a research:<strong> </strong>Alpha, beta and gamma diversity in intact, mixed and transformed landscapes. Please refer to the README file and the paper for details about the usage of the data and methodology.</p> <p>Software: R 4.1.0</p>
Figures and tables from: Host specialization and spatial divergence of bacteria associated with Peltigera lichens promote landscape gamma diversity
<p>This repository contains the figures and tables from the paper title "Host specialization and spatial divergence of bacteria associated with <em>Peltigera </em>lichens promote landscape gamma diversity". Detailed description of each figure and table are provided in the "Legends.docx" file.</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)
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.