{"title":"基于MaxEnt的白背秃鹫生境适宜性预测","authors":"A. Kimsing, J. Ngukir, T. Biju, D. Mize","doi":"10.9734/ajob/2022/v15i130229","DOIUrl":null,"url":null,"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.","PeriodicalId":8477,"journal":{"name":"Asian Journal of Cell Biology","volume":"68 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"White-rumped Vulture’s Habitat Suitability Prediction using MaxEnt in Arunachal Pradesh\",\"authors\":\"A. Kimsing, J. Ngukir, T. Biju, D. Mize\",\"doi\":\"10.9734/ajob/2022/v15i130229\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":8477,\"journal\":{\"name\":\"Asian Journal of Cell Biology\",\"volume\":\"68 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Asian Journal of Cell Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9734/ajob/2022/v15i130229\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Asian Journal of Cell Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9734/ajob/2022/v15i130229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
White-rumped Vulture’s Habitat Suitability Prediction using MaxEnt in Arunachal Pradesh
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.