DOI: 10.5061/dryad.8sf7m0cv8
title: SDM current and future projections for alternate CAM-based cultivation in SSA

description: Globally we are facing an emerging climate crisis, with impacts to be
 notably felt in semi-arid regions across the world. Cultivation of
 drought-adapted succulent plants has been suggested as a nature-based
 solution that could: (i) reduce land degradation, (ii) increase
 agricultural diversification and provide both economic and environmentally
 sustainable income through derived bioproducts and bioenergy, (iii) help
 mitigate atmospheric CO2 emissions, and (iv) increase soil sequestration
 of CO2. Identifying where succulents can grow and thrive is an important
 pre-requisite for the advent of a sustainable alternative ‘bio-economy’.
 Here we first explore the viability of succulent cultivation in Africa
 under future climate projections to 2100 using species distribution
 modelling to identify climatic parameters of greatest importance and
 regions of environmental suitability. Minimum temperatures and temperature
 variability are shown to be key controls in defining the theoretical
 distribution of three succulent species explored, and under both current
 and future SSP5 8.5 projections, the conditions required for growth of at
 least one of the species is met in most parts of sub-Saharan Africa. These
 results are supplemented with an analysis of potentially available land
 for alternative succulent crop cultivation. In total, up to 1.5 billion
 hectares could be considered ecophysiologically suitable and available for
 succulent cultivation due to projected declines in rangeland biomass and
 yields of traditional crops. These findings may serve to highlight new
 opportunities for farmers, governments, and key stakeholders in the
 agriculture and energy sectors to invest in sustainable bioeconomic
 alternatives that deliver on environmental, social and economic
 goals. 
description: The uploaded R script is to be used in R Studio and the libraries
 required are detailed within the script. 
description: Title: SDM current and future projections for alternate CAM-based
 cultivation in SSA Description: (1) The uploaded R script allows the user
 to recreate the species distribution models and projections for the
 species studied in the article: Buckland et al. (2023) Drought-tolerant
 succulent plants as an alternative crop under future global warming
 scenarios in sub-Saharan Africa. GCB Bioenergy. (2) The uploaded csv file
 provides the 2D response curve data associated with each of the three
 species (Opuntia ficus-indica, Euphorbia tirucalli, Portulacaria afra) and
 each explanatory variable. Data is organised by species, with
 'expl.nam' referring to bioclim variable, 'expl.var'
 refers to corresponding value for each bioclim variable, and
 'pred.val' gives the projected likelihood of species occurrence
 according to the respective explanatory variable. Instructions: (1)
 Instructions for usage of the R script are included in the code and ask
 the user to insert directory information and species choice as desired by
 the user. Models are trained on near historical (1970 – 2000 AD)
 environmental data downloaded from the WorldClim catalogue via script in
 the code, allowing the user to download the bioclim variables of interest
 directly. Future bioclim datasets that can be used to project the trained
 SDMs forward into future climatic conditions should be downloaded from the
 WorldClim catalogue https://www.worldclim.org/data/bioclim.html (Fick
 & Hijmans, 2017). Further data: (1) Supplementary data associated
 with the manuscript is available open access online:
 http://doi.org/10.1111/gcbb.13095 Supplementary data provides: (i) details
 on all the SDM datasets and parameters used in the R script; (ii) results
 from the 3D response curve analysis; (iii) available land analysis results
 presented in million hectares for each SSP scenario. (2) Additional data
 used in the manuscript was derived from the following authors and groups:
 Dr. Cecile Godde (CSIRO), Dr. Vassilis Daioglou (PBL Netherlands
 Environmental Assessment Agency) and the AgMIP research group.