White-rumped Vulture’s Habitat Suitability Prediction using MaxEnt in Arunachal Pradesh

A. Kimsing, J. Ngukir, T. Biju, D. Mize
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Abstract

Few reports showed that White-rumped vulture is present in Arunachal Pradesh. However, they were reported from a few places only. Such sightings suggest that either the region is not explored completely or the habitats are not suitable for the species. Therefore, knowing and predicting the habitat suitability of WRV and revealing the relative contribution of environmental variables determining such distribution can be important for their protection and conservation. The present study was based on the current distribution of WRV in Arunachal Pradesh that we had surveyed from 2016 to 2020. We followed the road count and point count methods to obtain primary occurrence data. Also, secondary data on occurrence records and data on environmental variables (landscape variables, anthropogenic variables, and climatic variables) were obtained and used. The data were processed using ArcMap. 29 occurrence records (filtered) and 11 environmental variables were used to build the prediction model using maximum entropy (MaxEnt). The MaxEnt predicted model showed high accuracy with area under the receiver operating characteristic curve value equals to 0.95 and True Skill Statistics value equals to 0.87. Of the total area, only 2629.63 km2 (3.20 %) is suitable for WRV while the majority of the area is unsuitable (79542.84 km2) (96.79 %). The elevation (32.2%), land use land cover (31.7%), and normalized difference vegetation index of November (26.7%) were the most influencing variables impacting the distribution of WRV. Among bioclimatic variables, the mean temperature of the warmest quarter and precipitation of the wettest quarter had the highest contribution. This work is the first attempt to understand the spatial distribution of WRV and the environmental factors associated with their distribution in the state. The findings can be relevant for designing conservation efforts to conserve this species in the state.
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基于MaxEnt的白背秃鹫生境适宜性预测
很少有报道显示白背秃鹫存在于**。然而,他们只报道了几个地方。这样的发现表明,要么该地区没有被完全探索,要么栖息地不适合该物种。因此,了解和预测WRV的生境适宜性,揭示决定其分布的环境变量的相对贡献,对WRV的保护和养护具有重要意义。本研究基于我们在2016 - 2020年调查的**地区WRV的分布现状。我们采用道路计数法和点数法来获得主要发生数据。此外,还获得并使用了关于发生记录和环境变量(景观变量、人为变量和气候变量)的二次数据。使用ArcMap对数据进行处理。利用29条发生记录(经过过滤)和11个环境变量,利用最大熵(MaxEnt)建立预测模型。MaxEnt预测模型具有较高的准确度,其受试者工作特征曲线下面积值为0.95,真实技能统计值为0.87。其中,适合WRV的面积为2629.63 km2(3.20%),不适合WRV的面积为79542.84 km2(96.79%)。高程(32.2%)、土地利用、土地覆被(31.7%)和11月归一化植被指数(26.7%)是影响WRV分布的主要变量。在生物气候变量中,最暖季的平均气温和最湿季的降水贡献最大。本研究首次揭示了WRV在中国的空间分布及其与之相关的环境因子。这些发现可能与设计保护工作有关,以保护该州的这种物种。
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