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FIGURA 3 in Distribuição de caranguejos Trichodactylidae (Crustacea, Brachyura) em alagados do Pantanal Mato-Grossense (Brasil) e sua correlação com a proximidade do rio Cuiabá e cobertura vegetal
FIGURA 3: Correlação entre a abundância de caranguejos em alagados e a distância do rio Cuiabá, Pantanal Mato-Grossense.
FIGURA 2 in Distribuição de caranguejos Trichodactylidae (Crustacea, Brachyura) em alagados do Pantanal Mato-Grossense (Brasil) e sua correlação com a proximidade do rio Cuiabá e cobertura vegetal
FIGURA 2: Abundância de caranguejos nas diferentes fitofisionomias em alagados do Pantanal Mato-Grossense.
FIGURA 1 in Distribuição de caranguejos Trichodactylidae (Crustacea, Brachyura) em alagados do Pantanal Mato-Grossense (Brasil) e sua correlação com a proximidade do rio Cuiabá e cobertura vegetal
FIGURA 1: Mapa com a localização das parcelas de amostragem em: a = América do Sul; b = Pantanal; c = mesopotâmia entre os rios Cuiabá e São Lourenço. A1 a A5 são parcelas em algodoais, B1 a B5, em monoculturas de Brachiaria spp., C1 a C5, em cambarazais e N1 a N5 parcelas em campos nativos.
FIGURA 4 in Distribuição de caranguejos Trichodactylidae (Crustacea, Brachyura) em alagados do Pantanal Mato-Grossense (Brasil) e sua correlação com a proximidade do rio Cuiabá e cobertura vegetal
FIGURA 4: Correlação entre a abundância de caranguejos a cobertura por gramíneas submersas em alagados do Pantanal Mato-Grossense.
Global distribution of primary and secondary vegetation at 1km spatial resolution
<p>This dataset provides the global spatial distribution of primary and secondary vegetation at approx. 1km spatial resolution (0.01°). It combines Hilda+ landuse/cover data by Winkler et al. (2020) and the global dataset on human influence by Riggio et al. (2020).</p> <p>The data consists of three NetCDF files: </p> <ul> <li>Primary vegetation</li> <li>Primary vegetation minimal use</li> <li>Secondary vegetation</li> </ul> <p>Primary vegetation is assigned where forests, unmanaged grass-/ shrubland or land with sparse vegetation according to the HILDA+ dataset (classes 44, 55, 66) are under full agreement of low human influence according to the global dataset on human influence.</p> <p>The same HILDA+ classes (44, 55, 66) with full agreement to be under very low human influence according to Riggion et al. (2020) are defined as primary vegetation minimal use.</p> <p>Secondary vegetation consists of forests, unmanaged grass-/ shrubland or land with sparse vegetation according to the Hilda+ dataset (classes 44, 55, 66) that are not classified as primary vegetation.</p> <p> </p> <p>Sources:</p> <p>Winkler, K., Fuchs, R., Rounsevell, M. D. A., Herold, M. (2020): HILDA+ Global Land Use Change between 1960 and 2019. PANGAEA. <a href="https://doi.org/10.1594/PANGAEA.921846">https://doi.org/10.1594/PANGAEA.921846</a> </p> <div> <div> <div> <div> <div> <div> <p>Riggio, J. et al. (2020): Global human influence maps reveal clear opportunities in conserving Earth’s remaining intact terrestrial ecosystems. Dryad. <a href="https://doi.org/10.25338/B80G7Z">https://doi.org/10.25338/B80G7Z</a></p> </div> </div> </div> </div> </div> </div> <p> </p> <p>This seperation of primary and secondary vegetation has been used e.g. in the following studies:</p> <p>Schneider et al. (2024): Effects of profit-driven cropland expansion and conservation policies. Nature Sustainability. <a href="https://doi.org/10.1038/s41893-024-01410-x">https://doi.org/10.1038/s41893-024-01410-x</a></p> <p><span>Piipponen et al. (2024): Protein and energy from grazing or crops - does livestock have a chance? Preprint: </span><a href="https://doi.org/10.21203/rs.3.rs-3392089/v1"><span>https://doi.org/10.21203/rs.3.rs-3392089/v1</span></a></p>
A Dataset for Response of Oceanic Meridional Overturning Circulation to Vegetation Removal on Different Continents
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Apendices(Effect of Vegetation Structure on Secondary Wind Dispersal Distance of Diaspores)
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Summary statistics of vegetation composition of Chitanga, Mafai, and Nwamukuku heritage forests in Inhambane province, Mozambique
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Land surface phenology derived from 3 sets of vegetation indices
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Feldman et al. 2024 "Large global scale vegetation sensitivity to daily rainfall variability"
<p>These data and scripts are a part of the Feldman et al. manuscript accepted in principle titled "Large global scale vegetation sensitivity to daily rainfall variability".</p> <p>The data and scripts here can be used to generate all steps of the analysis. It includes:</p> <p>(1) The final generated outputs of the analysis and the python script to generate the figures in the main text, extended data, and supplemental information. This figure generation script is: "MainScript_GenerateFigures_V4.py"</p> <p>(2) The python script to conduct the main analysis in an example region in Africa, which is named: "MainScript_SatelliteVegetationProcessing_Example.py". </p> <p>(3) The python script to conduct the main analysis across the globe (to generate figure 1), which is named: "MainScript_SatelliteVegetationProcessing_V2.py". Input data for this script are available at a separate Zenodo account here: https://zenodo.org/records/10947071.</p> <p>(4) Scripts and input data to conduct rainfall trend analyses and mechanism analyses.</p> <p>(5) Scripts to show how the gridded datasets were processed into their one degree gridding to be input into other components of the analysis.</p> <p>Due to their size, the full global datasets to conduct the global analysis are available on a separate Zenodo account here: https://zenodo.org/records/10947071.</p> <p>Please consult the README.txt file for more information about python and names of files and scripts being used. </p> <p>For any use of the datasets and scripts, please cite (1) the Feldman et al "Large global scale vegetation sensitivity to daily rainfall variability" publication. Additionally, (2) please acknowledge the use of the scripts and/or datasets in the acknowledgements section of your publication. The use of any scripts or data are not allowed unless the paper is in print. For questions, please contact Andrew Feldman at andrew.feldman@nasa.gov. </p>
FIGURE 1. Erythroxylum riparium. A. Vegetative Branch. B in Erythroxylum riparium (Erythroxylaceae), a new species from the Brazilian Atlantic Forest
FIGURE 1. Erythroxylum riparium. A. Vegetative Branch. B. Detail of branch with cataphylls, stipule, leaf and longistylous flower. C. Stipule. D. Bracteole. E. Petal, adaxial view. F. Brevistylous flower, petals removed. G. Open staminal cup. H. Gynoecium from brevistylous flower. I. Detail of longistylous flower, petals removed and staminal cup open to show pistil. J. Gynoecium from longistylous flower. K. Drupe. (Figures A to E and I to K from T. Araújo et al. 42; figures F to H from T. Araújo & C. Pessoa 211).
FIGURE 3 in A checklist of woody Leguminosae in the South American Corridor of Dry Vegetation
FIGURE 3. Graph showing the variation in species richness by vegetation type using different data sources (herbarium collections and literature, only herbarium collections and only literature). Brazilian Savannas (Bs), Chaco (Ch), Seasonal Forest (Sf) and Thorny Woodland (Tw).
FIGURE 2 in A checklist of woody Leguminosae in the South American Corridor of Dry Vegetation
FIGURE 2. Graph showing the species richness (literature and herbarium records), and species present exclusively in different types of seasonally vegetation in the South American Corridor of Dry Vegetation.
FIGURE 6. M in A revision of Mezoneuron (Leguminosae: Caesalpinioideae) in New Caledonia, with perspectives on vegetation, geology, and conservation
FIGURE 6. M. montrouzieri: 6a, c. leaves (Clark, R.P. 150, 160); 6b. young inflorescence (Clark, R.P. 160); 6d, e. inflorescences (Clark, R.P. 137, 150); 6f. fruit (Clark, R.P. 150)
FIGURE 11 in A revision of Mezoneuron (Leguminosae: Caesalpinioideae) in New Caledonia, with perspectives on vegetation, geology, and conservation
FIGURE 11. Phylogeny of the Mezoneuron containing clade of the informal Caesalpinia Group. Strict consensus of 100,000 equally parsimonious trees based on rps16 plastid sequences. Bootstrap support is shown in bold above branches, and posterior probability values are shown italicised, below the branch (Gagnon et al. 2013). The branches of the tree shown in yellow indicate species found in Australia, and the branch in red is a New Caledonian endemic species. Fruits of species within the New Caledonian species containing clade are shown (except C. nitens, the fruit of which are unknown), and contrasted with that of the winged fruit of Pterolobium within the sister clade. Fruit illustrations by R. Clark
FIGURE 1 in A checklist of woody Leguminosae in the South American Corridor of Dry Vegetation
FIGURE 1. Map highlighting the seasonally dry vegetation of South America. Thorny Woodland (A), Brazilian Savannas (B), Seasonal Forests (C or black) and Chaco (D).
FIGURE 2 in A revision of Mezoneuron (Leguminosae: Caesalpinioideae) in New Caledonia, with perspectives on vegetation, geology, and conservation
FIGURE 2. Illustration of M. montrouzieri, with leaf detail of all species. (a) M. montrouzieri habit, leaf and inflorescence, with detail showing idioblasts on leaf undersurface; flower, side view; flower opened out; petals, inner surface (median, 2 upper laterals, 2 lower laterals); ovary and style; fruit with detail of hairs—drawn from Clark, R.P. 160; (a)(i) M. montrouzieri glabrous ovary; (a)(ii) leaf pinna—drawn from Clark, R.P. 150 (specimen formerly identified as M. deverdiana); (b) pinna of M. baudouinii—drawn from Clark, R.P. 141; (c), (c)(i) pinnae of M. schlechteri (showing variation)–drawn from Clark, R.P., 132, 134; (d) pinna of M. rubiginosum—drawn from McPherson, G. 2089; (e) pinna of M. ouenensis—drawn from Balansa, B. 312. Illustration by Margaret Tebbs.
FIGURE 2. Salzmannia arborea. A. Vegetative branch. B. Bark. C. Infructescence. D in Taxonomic notes on Chiococca and Salzmannia (Rubiaceae, Chiococceae) in northeastern Brazil, with a new combination and a new species
FIGURE 2. Salzmannia arborea. A. Vegetative branch. B. Bark. C. Infructescence. D. Apical bud with resinous exudate, indicated by arrow. (From J.G. Jardim & J.L. Paixão 6458). Photos by Jomar Jardim.
FIGURE 3. Campanula hortelensis. A. Habit. B. Vegetative branch. C. and D. The two distinct radical leaves. E. Cauline leaf. F. and G. Flowers. H in Two new species of Campanula (Campanulaceae) from the island of Santo Antão, Cabo Verde archipelago
FIGURE 3. Campanula hortelensis. A. Habit. B. Vegetative branch. C. and D. The two distinct radical leaves. E. Cauline leaf. F. and G. Flowers. H. Dissection of a flower. I. Fruiting calyx (capsule). Drawings by V. Damianthe from Gardère 473 (A, E–H), Gardère 467 (B–D) and Gardère 471 (I).
FIGURE 1. Campanula feijoana. A. Habit. B. Vegetative branch. C. and D. The two distinct radical leaves. E. Cauline leaf. F. and G. Flowers. H in Two new species of Campanula (Campanulaceae) from the island of Santo Antão, Cabo Verde archipelago
FIGURE 1. Campanula feijoana. A. Habit. B. Vegetative branch. C. and D. The two distinct radical leaves. E. Cauline leaf. F. and G. Flowers. H. Dissection of a flower. I. Fruiting calyx (capsule). Drawings by V. Damianthe from Gardère 461 (A–H) and Gardère 460 (I).
ScienceDex guides
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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.