Spatial distribution, hypervolumes, niche overlaps, and dynamics of the forest plant-community of Triplochiton scleroxylon, Terminalia superba, and Antiaris toxicaria in the context of climate change across Africa
Abstract
Abstract Climate change is the main drier of biodiversity loss across continents and its effects need to be investigated seriously to inform decisions on possible mitigation measures to assure conservation and sustainable use of natural resources. We therefore examined the effect of climate change on the spatial distribution, ecological niches, niche overlaps, and niche shifts of the plant-communities of Triplochiton scleroxylon, Terminalia superba , and Antiaris toxicaria. We used SDM packages that offered the possibility to compare the performances of several modelling methods. Based on the results on algorithms’ performances in our previous studies, we used three machine learning algorithms: MaxEnt, Boosted Regression Trees (BRT), and Random Forests (RF). From the main results, RF and Maxent outperformed BRT algorithm with respect to the key statistic values, AUC and TSS. However, Maxent outperformed the other algorithms with respect to its realistic predictions at present. Confidence intervals of Sorensen and Jaccard overlap statistics approved the hypervolumes’ overlaps of Triplochiton scleroxylon, Terminalia superba , and Antiaris toxicaria at 95% degree of confidence and therefore confirmed their degree of community. The degree of community between the three species is also confirmed in the future scenarios, SSP 245 and SSP 585, horizon 2040 with the General Circulation Model (GCM), Model for Interdisciplinary Research on Climate version 6 (MIROC6). Under climate…
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