Hybrid model for ecological vulnerability assessment in Benin

• Main Authors: Jacqueline Fifame Dossou, Xu Xiang Li, Mohammed Sadek, Mohamed Adou Sidi Almouctar, Eman Mostafa
• Format: Article
• Language: English
• Published: Nature Publishing Group 2021-01-01
• Series: Scientific Reports
• Online Access: https://doi.org/10.1038/s41598-021-81742-2

Abstract Identifying ecologically fragile areas by assessing ecosystem vulnerability is an essential task in environmental conservation and management. Benin is considered a vulnerable area, and its coastal zone, which is subject to erosion and flooding effects, is particularly vulnerable. This study assessed terrestrial ecosystems in Benin by establishing a hybrid ecological vulnerability index (EVI) for 2016 that combined a composite model based on principal component analysis (PCA) with an additive model based on exposure, sensitivity and adaptation. Using inverse distance weighted (IDW) interpolation, point data were spatially distributed by their geographic significance. The results revealed that the composite system identified more stable and vulnerable areas than the additive system; the two systems identified 48,600 km2 and 36,450 km2 of stable areas, respectively, for a difference of 12,150 km2, and 3,729 km2 and 3,007 km2 of vulnerable areas, for a difference of 722 km2. Using Moran’s I and automatic linear modeling, we improved the accuracy of the established systems. In the composite system, increases of 11,669 km2 in the potentially vulnerable area and 1,083 km2 in the highly vulnerable area were noted in addition to a decrease of 4331 km2 in the potential area; while in the additive system, an increase of 3,970 km2 in the highly vulnerable area was observed. Finally, southern Benin was identified as vulnerable in the composite system, and both northern and southern Benin were identified as vulnerable in the additive system. However, regardless of the system, Littoral Province in southern Benin, was consistently identified as vulnerable, while Donga Province was stable.