Species Affinities and Biome Area Predictions

Data package for the review of the paper "Approaching Peak Biodiversity: Non-linear Responses of Plant Biodiversity to Climate Warming". Please refer to the README.md file for detailed explanations on the content and individual columns of the CSV, as well as the provided notebooks. Here is a brief description of the main files: Prediction GeoTIFs BiomePredictions.tif: The predicted biome for each pixel. Different bands correspond to the different SSPs and year brackets. (e.g. "ssp126_2021-2040" is the predicted biome for SSP1-2.6 in the years 2021-2040). Values are: 4 = alpine, 7 = tussock grasslands, 10 = shrublands, 14 = podocarp forest, 15 = beech forest, 16 = Mixed podocarp/beech forest. PredictionUncertainty_Shape.tif: The extrapolation distance following (Velazco et al. 2024). The cutoff used in this paper is 1. Pixels above will be classified as "novel". PredictionUncertainty_Charney.tif: The extrapolation distance following (Charney et al. 2021). This method is discussed in the paper and compared in the supplementary materials, but not used. Computed Data ClimateChange.csv: Documents the change of environmental variables per biome. SpeciesAffinity.csv: Contains the affinity values computed for a species set (or bracket), biome, year bracket and SSP. The affinity values are normalised differently for making them comparable across species and/or variables. AffinityRegressions.csv: Contains the regressions for the affinities of difderent subsets/brackets of species in "Species Affinity.csv" using bent cable regression. LandscapeAffinity.csv: Analogous to "SpeciesAffinity.csv", but the affinity values for each species across the 6 biomes are now combined into a single landscape affinity value. Landscape affinity is always computed on the raw affinity values and then normalised in the same way as described above (Species normalisation with suffix _I, variable normalisation with suffix _V, full normalisation with suffix _F). LandscapeAffinityRegressions.csv: Analogous to "AffinityRegressions.csv".