Conservation implications of mapping the potential distribution of an Ethiopian endemic versatile medicinal plant, Echinops kebericho Mesfin

Abstract

AbstractEchinops kebericho is a narrow‐range multipurpose medicinal plant confined to Ethiopia. Intense land use change and overharvesting for traditional medicine have resulted in narrow distributions of its populations. It is a threatened species with a decreasing population trend. This study aims to map its potential distribution, which is key to guide conservation efforts and sustainable use. We modeled the potential distribution of E. kebercho using the maximum entropy model (MaxEnt) employing 11 less correlated predictor variables by calibrating the model at two complexity levels and replicating each model 10 times using a cross validation technique. We projected the models into the whole of Ethiopia and produced binary presence–absence maps by classifying the average map from both complexity levels applying three threshold criteria and ensembling the resulting maps into one for the final result. We mapped suitable habitat predicted with high certainty and identified local districts where E. kebericho can be cultivated or introduced to enhance its conservation. We estimated that E.kebercho has about 137,925 km2 of suitable habitat, mainly concentrated in the western highlands of the Ethiopian mountains. Our models at both complexity levels had high average performances, AUC values of 0.925 for the complex model and 0.907 for the simpler model. The variations in performance among the 10 model replicates were not remarkable, an AUC standard deviation of 0.040 for complex and 0.046 for simple model. Although E. kebericho is locally confined, our models predicted that it has a remarkably wider potential distribution area. We recommend introducing E. kebericho to these areas to improve its conservation status and tap its multiple benefits on a sustainable basis. Locally confined threatened plants and animals likely have wider potential distributions than their actual distributions and thus similar methodology can be applied for their conservation.