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Data from: Temporal changes in taxonomic and functional alpha and beta diversity across tree communities in subtropical Atlantic forests

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NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/10658949
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The study is published in Oikos and available at: https://doi.org/10.1111/oik.10961 Here we aim to assess temporal taxonomic and functional alpha and beta diversity of adult and juvenile tree communities across 11 sites in the subtropical Brazilian Atlantic Forest to infer about trends and drivers of biodiversity change. The tree communities were evaluated for temporal changes in: (1) taxonomic and functional alpha diversity, (2) taxonomic and functional composition (beta diversity), and (3) identifying potential abiotic and biotic drivers of these changes, considering three censuses across a period of 10 years.   Description for the files: traits-adults.csv - adult tree species and their functional traits values. traits-juveniles.csv - juvenile tree species and their functional trait values. abundance-adults_synthesis.csv - adult tree species abundance over the three time periods of forest surveys (T1, T2, and T3). Data on the individual level is available at ForestPlots.net database (https://forestplots.net/) abundance-juveniles_synthesis.csv - juvenile tree species abundance over the three time periods of forest surveys (T1, T2, and T3). Data on the individual level is available at ForestPlots.net database (https://forestplots.net/). Functional traits abbreviations are defined as follows: LA = leaf area; SLA = specific leaf area; WD = wood density; SM = seed mass; range_temp = range of mean annual temperature; range_CWD = range of climatological water deficit; and biomes_distrib = number of Brazilian biomes that the species occur according to Flora and Funga do Brazil.   Acknowledgments This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brazil (CAPES) – Finance Code 001, through Portal de Periódicos and scholarships granted to JMFK, JK and RCP. The fieldwork was supported by Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS grant numbers 2218 – 2551/12-2 and 19/2551-0001698-0), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq/FAPERGS/PELD number 441590/2020-9), and the Instituto Nacional de Ciência e Tecnologia (INCT) in Ecology, Evolution and Biodiversity Conservation, supported by MCTIC/CNPq (grant number 465610/2014-5). KMB gratefully acknowledge the financial support by the National Institute of Science and Technology in Low Carbon Emission Agriculture (INCT-ABC) sponsored by Brazil’s National Council for Scientific and Technological Development (CNPq, grant no. 406635/2022-6), the Foundation for Research Support of the State of Rio Grande do Sul (Fapergs, grant no. 22/2551-0000392-3), and the Ministry of Agriculture (MAPA). SCM is supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq; grant number 309659/2019-1.   Please find below the data used in the study.
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2025-02-26
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