Trait-based projections of climate change effects on global biome distributions

DOI

Climate change will likely modify the global distribution of biomes, but the magnitude of change is debated. In the paper belonging to this dataset, we followed a trait-based, statistical approach to model the influence of climate change on the global distribution of biomes.Step 1. We predicted the global distribution of plant community mean specific leaf area (SLA), height, and wood density as a function of climate and soil characteristics using an ensemble of statistical models.Step 2. We predicted the probability of occurrence of biomes as a function of the three traits with a classification model.Step 3. We projected changes in plant community mean traits and corresponding changes in biome distributions to 2070 for low (RCP 2.6; +1.2°C) and extreme (RCP 8.5; +3.5°C) future climate change scenarios.Four R scripts are added to this dataset, starting with step two described in the paper: from traits to vegetation types (Traits.to.VegT.R). Input for this file is the csv file: all.trait.predictions.untransformed.csv which includes the predictions for community mean trait values for Specific Leaf Area (SLA), height and wood density, for the current climate and under the predictions under a climate change scenario with RCP2.6 and RCP8.5.

Identifier
DOI https://doi.org/10.17026/dans-xf5-qdxd
Metadata Access https://lifesciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-xf5-qdxd
Provenance
Creator C.C.F. Boonman
Publisher DANS Data Station Life Sciences
Contributor RU Radboud University
Publication Year 2021
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact RU Radboud University
Representation
Resource Type Dataset
Format text/csv; application/zip; type/x-r-syntax; text/plain
Size 6537488; 16506; 13178; 7368; 3732; 19866; 7607
Version 2.0
Discipline Earth and Environmental Science; Environmental Research; Geosciences; Life Sciences; Medicine; Natural Sciences