Abstract

Species distribution modelling is gaining popularity due to significant habitat shifts in many plant and animal species caused by climate change. This issue is particularly pressing for species that provide significant ecosystem goods and services. A prominent case is the valuable African rosewood tree (Pterocarpus erinaceus) that is threatened in sub-Saharan Africa, while its present distribution, habitat requirements and the impact of climate change are not fully understood. This native species naturally occurs in various savanna types, but anthropogenic interventions have considerably reduced its natural populations in the past decades. In this study, ensemble modelling was used to predict the current and future distribution potential of the species in Burkina Faso. Fifty-four environmental variables were selected to describe its distribution in the years 2050 and 2070 based on the greenhouse gas concentration trajectories RCP4.5 and 8.5, and the general circulation models CNRM-CM5 and HadGEM2-CC. A network of protected areas in Burkina Faso was also included to assess how many of the suitable habitats may contribute to the conservation of the species. The factors isothermality (31%), minimum temperature of coldest month (31%), pH in H2O at horizon 0–5 cm (11%), silt content at horizon 60–100 cm (9.2%) and precipitation of warmest quarter (8%) were the most influential distribution drivers for the species. Under current climate conditions, potentially highly suitable habitats cover an area of 129,695 km2, i.e., 47% of Burkina Faso. The projected distribution under RCP4.5 and 8.5 showed that this area will decrease, and that the decline of the species will be pronounced. The two models used in this study, forecast a habitat loss of up to 61% for P. erinaceus. Hence, development and implementation of a conservation programme are required to save the species in its native range. This study will help land managers prioritise areas for protection of the species, and avoid introducing it to inappropriate areas unless suitable conditions are artificially created through the management options applied.

Full Text
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