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Using the Ensemble Modeling Approach to Predict the Potential Distribution of the Muscat Mouse-Tailed Bat, Rhinopoma muscatellum (Chiroptera: Rhinopomatidae), in Iran

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Abstract

Habitat suitability models can be generated using methods requiring information on presence of species or presence and absence of species. Rhinopoma muscatellum is one of the six mouse-tailed bats (Rhinopomatidae) and is known as an extremely frequent bat in Iran. In this study, 76 presence points were identified and recorded in distribution range of species. Presence-only (Domain, Bioclim, and one-class SVM) and presence/pseudo-absence (P/PA) data-based methods were used to model the distribution of R. muscatellum in Iran. In this study, in order to establish the pseudo-absence points, the output of presence-only map with the highest validity on AUC statistics was used. Using the output of the Domain method map (AUC = 0.8), 720 pseudo-absence points of the species were designed and entered into the P/PA models, including generalized linear model (GLM), maximum entropy (MaxEnt), maximum likelihood (MaxLike), classification and regression trees (CART), rough set, back-propagation artificial neural networks (BP-ANN), and two-class support vector machine (two-class SVM). The models were validated by the kappa coefficient of agreement as a threshold-based index. The coefficient of agreement was measured above 0.8 for all running models. Then, all binary maps were entered into the ensemble method, and the distribution map was presented as the output map with the result of ten implemented models. In order to evaluate the effect of each habitat variable on species distribution, sensitivity was measured by logistic regression method. The results of the modeling showed that the southeastern, southern, and southwestern regions of the country have a high suitability for this species, which was also confirmed by the ensemble modeling method. Based on the sensitivity results, the maximum temperature of the warmest months of the year, mean daily temperature, and distance from the mines had the highest effect on species distribution. The results of this study showed that R. muscatellum distribution models can be useful in identifying the species habitat suitability and the distribution maps obtained from these models can be considered as a suitable tool for population studies.

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Acknowledgements

The authors thank the Razi University authorities, Kermanshah, for their help and support in this study as a part of a PhD research project. Special thanks go to Dr. Peyman Karami for his careful reading of, and useful modifications to, early versions of the manuscript. The authors also thank the anonymous reviewers and the editor for informative corrections and comments on the penultimate version of the manuscript.

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  1. Department of Biology, Faculty of Science, Razi University, Kermanshah, Iran

    Sasan Kafaei, Vahid Akmali & Mozafar Sharifi

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  1. Sasan Kafaei
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  2. Vahid Akmali
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Correspondence to Vahid Akmali.

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Kafaei, S., Akmali, V. & Sharifi, M. Using the Ensemble Modeling Approach to Predict the Potential Distribution of the Muscat Mouse-Tailed Bat, Rhinopoma muscatellum (Chiroptera: Rhinopomatidae), in Iran. Iran J Sci Technol Trans Sci 44, 1337–1348 (2020). https://doi.org/10.1007/s40995-020-00953-w

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