Climate-diversity relationships underlying cross-taxon diversity of the Africa fauna and their implications for conservation
Pinkert, Stefan et al. (2021), Climate-diversity relationships underlying cross-taxon diversity of the Africa fauna and their implications for conservation, Dryad, Dataset, https://doi.org/10.5061/dryad.nk98sf7r5
Our analyses were based on vector maps of the distributions of all 1,001 terrestrial mammalian species, 1,942 bird species and 723 amphibian species (from IUCN, 2016 and BirdLife International and NatureServe, 2016) as well as all 731 dragonfly species (from Clausnitzer et al., 2012, accessed August 16, 2016) of sub-Saharan Africa. Vector maps were reassigned to a grid with a grain size of approximately 50 km × 50 km (Lambert azimuthal equal area projection centred on 5°N 20°E) using functions provided in the R-package raster (Hijmans et al., 2016).
Based on the distribution data, we first calculated the species richness and rarity of the assemblages (e.g. mamma_rich and mamma_CWE). Subsequently, we predicted the variation in these diversity patterns based on contemporary climate (e.g. pred_mamma_current) and the climatic changes since the LGM (e.g. pred_mamma_current), respectively (see the section “Statistical analysis” for details). Hotspots of diversity patterns were arbitrarily defined as the 300 grid cells with the highest (raw or predicted) species richness and rarity (e.g. mamma_300).
We evaluated the importance of contemporary climate and climatic changes since the LGM (PMIP boundary conditions for the LGM, CCSM4 coupled climate model prediction) for shaping the species richness and rarity patterns of the considered taxa, based on the same 4 bioclimatic variables for each time period (for results based on all 19 bioclimatic variables see Supporting Information). The environmental variables were downloaded from http://chelsa-climate.org (Karger et al., 2017, 2018). All variables were aggregated to obtain mean values for the grid cells. To estimate climatic changes since the LGM, for each grid the AMT, TS, AP and PS (i.e. bio1 = annual mean temperature, bio4 = temperature seasonality, bio12 = annual precipitation, bio15 = precipitation seasonality) values during the LGM were subtracted from those of the corresponding contemporary climate variables (e.g. current_bio1 - paleo_bio1 = ano_bio1).
Raw data of species distributions is available at request from the above-mentioned institutions and authors.