Use of maximum entropy (Maxent) niche modelling to predict the occurrence of threatened freshwater species in a biodiversity hotspot of Zimbabwe

Abstract

Globally, freshwater species are under threat from human mediated stressors. Therefore, there is an urgent need for methods to estimate population and species occurrences for conservation purposes. Here, we used a predictive species distribution model to determine the occurrence of three endangered species (Amietia inyangae, Chlorolestes elegans and Strongylopus rhodesianus) in Southern Africa (Eastern Highlands of Zimbabwe). The study revealed that the probability of occurrences for the three species increase with an increase in elevation and annual precipitation and decrease with an increase in annual mean temperature. Our results indicated that the highest probability of occurrences for A. inyange, C. elegans and S. rhodesianus is in the Nyanga, Stapleford and Chimanimani highland areas, with some probabilities of occurrence falling outside protected areas. Our findings suggest that the areas covered by protected areas may need to be revaluated. Our findings will be useful for managing threatened species.

Predicting the Spatial Distribution of the Mangshan Pit Viper (Protobothrops mangshanensis) under Climate Change Scenarios Using MaxEnt Modeling

“…Occurrence data were obtained from published [18,19] and unpublished (chronology of the survey records of Mangshan National Nature Reserve, Hunan Province) sources, yielding 83 occurrence points of P. mangshanensis (Figure 3). Utilizing the "remove duplicates" method, any duplicate presence points located within the same grid cell were eliminated [20,21]. Consequently, only one site per 1 km × 1 km grid was chosen, resulting in a total of 68 sites employed for the current modeling endeavor.…”

New paths for modelling freshwater nature futures

“…Recent examples of freshwater multiple-species-models are that of Inoue et al (2017) , who investigated abiotic and biotic factors underlying the distribution and co-occurrence of two mussel species in European river ecosystems to improve conservation efforts, and that of Barbarossa et al (2021) , who made a global model of riverine fish species to assess possible climate-related range shifts. Examples of single species models are present in Jähnig et al (2012) , where a chain of models was used to predict the occurrence of a freshwater bivalve in a river ecosystem, and in Mafuwe et al (2022) where the maximum entropy model MaxEnt was used to estimate the region of occurrence of three threatened Zimbabwean freshwater species for which limited data were available. As species models are more geared towards extrapolating patterns in nature, they are usually correlative (i.e.…”

Maxent Predictive Species Distribution Models and Model Accuracy Assessment for Two Species of Psilochalcis Kieffer (Hymenoptera: Chalcididae) Occurring in the Eastern Great Basin of Utah, USA

“…Maxent maintains predictive reliability for species where the number of known occurrence data points is very small [13][14][15]. It has been used successfully in predicting areas of suitable habitat for various threatened and endangered species, including frogs and damselflies [16], freshwater mussels [17], trees [11], and geckos [18].…”