Data and R code repository for 'Six decades of losses and gains in alpha diversity of European plant communities'
Data and R code repository for 'Six decades of losses and gains in alpha diversity of European plant communities'
We interpolated spatiotemporal changes in vascular plant species richness using a new method based on machine learning that does not require temporal replication at sites. Using 698,692 one-time survey vegetation plots from the European Vegetation Archive, we estimated trends in vascular plant alpha diversity across Europe and validated our approach against 22,852 independent time series from ReSurveyEurope.
The repository contains the comprehensive data outputs and R code for the study "Six decades of losses and gains in alpha diversity of European plant communities". This is a copy of the main GitHub repository (https://github.com/gmidolo/interpolated_S_change). Here, we provide large-size files (e.g., model output and predictions) necessary for full reproducibility.
Peer reviewed
- Spanish National Research Council Spain
- Czech University of Life Sciences Prague Czech Republic
biogeographic regions, random forests, Biogeographic regions, autocorrelation, latitudinal gradient, nature conservation, Biogeographical region, Vegetation resurvey, Nature conservation, Machine learning, Alpha diversity, Xgboost, Habitat specificity, Biodiversity change, vegetation resurvey, alpha diversity, Random forests, Latitudinal gradient, interpolation, Interpolation, xgboost, machine learning, biodiversity change, Autocorrelation, habitat specificity
biogeographic regions, random forests, Biogeographic regions, autocorrelation, latitudinal gradient, nature conservation, Biogeographical region, Vegetation resurvey, Nature conservation, Machine learning, Alpha diversity, Xgboost, Habitat specificity, Biodiversity change, vegetation resurvey, alpha diversity, Random forests, Latitudinal gradient, interpolation, Interpolation, xgboost, machine learning, biodiversity change, Autocorrelation, habitat specificity
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