Diversifying modelling techniques to disentangle the complex patterns of species richness and diversity in the protected afromontane grasslands

Abstract Ecological research has focused on the importance of environmental factors spatial biodiversity variations and organisation. This is important because scant conservation resources. We used stepwise backward selection random feature (RFE) to identify a parsimonious model that can predict species richness diversity metrics in response three models; biotic, abiotic, topo-edaphic. Our results show both are good predictors one another, mainly combination abundance, further highlights biotic variables predicting distribution. The two modelling techniques selected soil texture its interactions with topographic as most variables. However, forest performed worse than multiple linear regression prediction metrics. topographically controlled edaphic drivers mountainous grasslands where topography inherently controls geomorphic, hydrological, and, result, ecological processes.