Habitat Suitability Modeling for Wildlife Management Objectives by Using Maximum Entropy Method

Abbas Naqibzadeh,Marjan Mashkur,Ahad Sotoudeh,Jalil Sarhangzadeh,Judith Thomalsky

doi:10.28991/hef-2021-02-04-05

Abstract

Habitat suitability models are useful tools for a variety of wildlife management objectives. Distributions of wildlife species can be predicted for geographical areas that have not been extensively surveyed. The basis of these models' work is to minimize the relationship between species distribution and biotic and abiotic environments. For some species, there is information about presence and absence that allows the use of a variety of standard statistical methods. However, absence data is not available for most species. Nowadays, the methods that need presence-only data have been expanded. One of these methods is the Maximum Entropy (MaxEnt) model. The purpose of this study is to model the habitat of Urial (Ovis orientalis arkal) in the Samelghan plain in the North East of Iran with the MaxEnt method. This algorithm uses the Jackknife plot and percent contribution values to determine the significance of the variables. The results showed that variables such as southern aspects, Juniperus-Acer, Artemisia-Perennial plants, slope 0-5%, and asphalt road were the most important factors affecting the species’ habitat selection. The area under the curve (AUC) Receiver Operating Characteristic (ROC) showed excellent model performance. Suitable habitat was classified based on the threshold value (0.0513) and the ROC, which, based on the results, 28% of the area was a suitable habitat for Urial. Doi: 10.28991/HEF-2021-02-04-05 Full Text: PDF

Highlights

Suitable habitat has a significant impact on the survival and reproduction of species, management, and conservation of wildlife [1, 2]
The purpose of this study is to model the habitat of Urial (Ovis orientalis arkal) in the Samelghan plain areas with the Maximum Entropy (MaxEnt) method
Our results show that environmental variables cause significant changes in the suitability models for the Urial and based on these changes, management decisions can be made to protect species

Summary

Introduction

Suitable habitat has a significant impact on the survival and reproduction of species, management, and conservation of wildlife [1, 2]. Habitat modeling is predicting species geographical distribution based on environmental conditions of known sites, as well as an important method in analytical biology with applications in environmental protection and planning, evolution, epidemiology, ecology, management of invasive species, and other fields [5]. Species distribution models (SDMs) are empirical models relating field. Due to the irregular distribution of species in habitats, it is difficult and costly to determine the exact distribution of species [9] Such models are naturally static and probable because, statistically, the geographical distribution of species or communities is related to their current habitats [10], so these models can perform well in describing the natural distribution of species (within their current range). Species distribution models or habitat suitability models allow potentially predicting human effects on biodiversity patterns at different spatial scales, the origin more of modeling methods to predict of fauna and flora distribution have in environmental-species relations [11]. Absence data is not available for most species [17]

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