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Assessing the potential impact of climate change on Kobus megaceros in South Sudan: a combination of geostatistical and species distribution modelling

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Abstract

Kobus megaceros is a wetland antelope listed as endangered by United Nations Educational, Scientific and Cultural Organization (UNESCO) in its natural habitat in South Sudan. The population of the species in South Sudan’s wetlands remains unknown. Climate change is expected to have a significant impact on the species population in a variety of ways. This paper aims to estimate the current population density and investigate the impact of climate change on K. megaceros by the end of the century. Bayesian Maximum Entropy (BME) and species distribution modelling (SDM) were used to estimate spatial density and predict habitat suitability for Kobus megacero in RCP4.5 and RCP8.5 pathways. The observed occurrences and abundances of Kobus megacero were downloaded from the global biodiversity information facility (GBIF) website. The Africlim online database was used to gather environmental predictors for current and future scenarios. We implemented SDM in R biomod2 package with Maxent algorithm to determine the geographical extent of habitat suitability for RCP4.5 and RCP8.5. The area under the ROC curve (AUC) and true skill statistics (TSS) were used to evaluate the model. The findings revealed that the current population density of Nile lechwe is too small; hence, this could accelerate the extinction of Nile lechwe. Although 4.97% of the country is currently highly suitable, future scenarios show that about 79–83% of the current suitable habitat will be lost due to climate change in the mid-2055s and mid-2085s. This implies that a proactive conservation strategy should be implemented to reduce the species’ chances of extinction.

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Data availability

The data used in this study is freely available on the GBIF database (www.gbif.org/).

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Alier, G., Idohou, R., Hounsou-Dindin, G. et al. Assessing the potential impact of climate change on Kobus megaceros in South Sudan: a combination of geostatistical and species distribution modelling. Model. Earth Syst. Environ. 10, 1531–1542 (2024). https://doi.org/10.1007/s40808-023-01889-x

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