Data from: Climate change should drive mammal defaunation in tropical dry forests

Description

Raw data and code base for the research approach on climate change-driven biotic changes in tropical dry forest mammals in South America. Briefly, the code reproduces the traditional Ecological Niche Modelling (ENM) and the Ensemble of Small Models (ESM) framework; perform assemblage-level analysis in the resulting outputs; and build the figures used in the main text and supplementary material.

The modelling framework was built using the directory structure informed in the README.pdf file. The R-code provided have steps designed to replicate the directory structure as informed, but understanding it is a good starting point to navigate the output produced.

File content

Occurences Folder.zip: it represents the "Occurrence Folder" directory, as illustrated in the README.pdf. This zip includes three files representing the occurrence data for the plant species used in the modelling framework.

Datasets.zip: it represents the "Datasets" folder directory, as illustrated in the README.pdf. This zip contains 126 csv files. Among these csv files, we provide (i) species-level outputs (measures of species range shift), (ii) assemblage-level outputs (measures of richness, beta-diversity, average body mass), (iii) summary statistics (ENM-ESM model performance metrics, kruskal wallis tests, spatial correlations), and (iv) processed tables used to build the main figures in the manuscript.

Shapefiles.zip: it represents the "Shapefiles" folder directory, as illustrated in the README.pdf. There are five shapefiles in this zip. (i) Caatinga_wgs84, spatial polygon illustrating the study area. (ii) cea_grid_cells, 10x10 km equal-area grid cells created for the assemblage-level analysis. (iii) ne_110m_admin_0_countries, Natural Earth Vector draws boundaries of countries (see https://www.naturalearthdata.com/downloads). (iv) ne_110m_graticules_20, Natural Earth Vector draws graticules of the globe (see https://www.naturalearthdata.com/downloads). (v) Neotropical, the Neotropical realm limits extracted from https://ecoregions.appspot.com/). 

UncertaintyRasters.zip: it represents the "UncertaintyRasters" folder directory, as illustrated in the README.pdf. Aggregated uncertainty is a combined measure of variation in species habitat suitability across five generalized circulation models (GCM). This zip file contains 16 raster files in format tif, with each raster representing a combination between SSP scenario (ssp245 or ssp585) and extrapolation constraints (MOP00, MOP70, MOP80, or MOP90).

Raw_Dataset_GCB.xls: a Excel file containing the compiled data on mammal occurrence records previous to the data cleaning procedure. Please, see Moura et al. (2023) for extra details.

SpeciesBodyMass.csv: a table informing the taxonomic ranks (family, order), body mass (g), and source of body mass data for each mammal species expected to occur in the Caatinga.

RData.zip: it represents the "RData" folder directory, which is designed to store RData files produced during the running of the R-scripts.

R-code:

1. Moura_etal_GCB2023_Script1_ENM_DataAnalysis.R: perform data cleaning, prepare predictor layers, run traditional ecological niche models, get ensemble models across GCMs, apply extrapolation constraints, and compute species geographical range shifts.
2. Moura_etal_GCB2023_Script2_ESM_DataAnalysis.R: run ensemble of small models for rare species, get ensemble models across GCMs, apply extrapolation constraints, and compute species geographical range shifts.
3. Moura_etal_GCB2023_Script3_AssemblageLevelAnalysis.R: compute aggregated model uncertainty, extract presence-absence matrices, compute assemblage-level metrics, and assess changes in biodiversity patterns across regions subject to homogenization or heterogenization.
4. Moura_etal_GCB2023_Script4_Figures.R: build the figures reported in the main text and supplementary material.
5. AdaptedRFunctions.R: auxiliary script containing functions modified from existing R-packages.

wc2.1_5m_elev.tif: this file can be downloaded using the following link https://biogeo.ucdavis.edu/data/worldclim/v2.1/base/wc2.1_5m_elev.zip. Store it in the Working Directory.

Citation

Moura, M.R., Oliveira, G.A., Paglia, A.P., Pires, M.M.,  & Santos, B.A. (2023). Climate change should drive mammal defaunation in tropical dry forests. Global Change Biology, 29:6931-6944. doi: 10.1111/gcb.16979
Correspondence to: mariormoura@gmail.com