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Vulnerability to climate changes of tropical forests across Africa

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DataONE2025-02-27 更新2025-04-26 收录
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Aim: Global climate projections identify tropical regions as hotspots of climate change during the 21st century. The few ground data in tropical Africa confirm significant warming and drying over the last decades, but how plant communities will tolerate these new climate conditions remain vastly uncertain. In this study, we assess the climatic vulnerability of tropical moist forests across Africa. Location: Tropical Africa. Methods: We mapped climate change exposure across the tropical moist forest biome, focusing on mean annual temperature (MAT), mean annual precipitation (MAP), and climatological water deficit (CWD) using climate projections for 2080 from five regional models under RCP4.5 and RCP8.5. Using occurrence records for 3,536 tree and shrub species, we estimated species’ climatic limits and safety margins, then averaged these margins at the community level. Finally, we combined exposure and safety margins to assess species- and community-level risk by 2080. Results: Unde..., , , # Vulnerability to climate changes of tropical forests across Africa [https://doi.org/10.5061/dryad.7h44j105d](https://doi.org/10.5061/dryad.7h44j105d) ## Description of the data and file structure We have provided the floristic data contained in the **occurrence_data **folder, the climatic data stored in the **current_climate_layers **and **future_climate_layers **folders, as well as the R script (*R_code_to_read_data.R*) that allows for reading and manipulating the data used to generate our results. ## Description ### occurrence\_data This folder contains the (*occurrence_records_filtered.csv*) file, which includes georeferenced occurrence records of tree and shrub species extracted from the RAINBIO database. This file contains 321,727 observations and the following 8 variables : * **tax_sp_level** = Binomial name of the species * **tax_fam** = Botanical family to which the species belongs * **tax_gen** = Botanical genus of the species * **country** = Country where the species ...
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2025-02-28
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