基于机器学习的云南省蝙蝠空间分布及其危害分析  

Analysis on Spatial Distribution and Harm of Bats in Yunnan Province Based on Machine Learning

作　　者：周鹏飞 刘琳 杨晋帆 刘婷婷[1] 魏贵宇 周汝良[1] ZHOU Pengfei;LIU Lin;YANG Jinfan;LIU Tingting;WEI Guiyu;ZHOU Ruliang(School of Geography and Ecotourism,Southwest Forestry University,Kunming Yunnan 650224,China;College of Science,Southwest Forestry University,Kunming Yunnan 650224,China)

机构地区：[1]西南林业大学地理与生态旅游学院,云南昆明650224 [2]西南林业大学理学院,云南昆明650224

出　　处：《广西师范大学学报（自然科学版）》2023年第6期139-149,共11页Journal of Guangxi Normal University:Natural Science Edition

基　　金：云南省科技厅重大科技专项(202002AA100007);国家自然科学基金(31760212,42061004)。

摘　　要：生存或寄生于野外的各种病原体通过进化、基因变异或生态适宜性改变,可能具有潜在的感染人类的风险。因此,开展人类与重要寄主动物的时空交错风险分析,对不明疫病感染的溯源追踪、野外环境健康管理与预警具有重要意义。蝙蝠类动物携带着多种危险病原,本文以其为目标寄主构建随机森林模型,预测蝙蝠适生分布区,并融合与蝙蝠、人类活动有关的空间变量,建立人与蝙蝠空间交错的风险评估模型,制作风险分布地图;为方便行政管理,还进行以乡镇级为管理单元的风险分析。结果表明:1)影响蝙蝠适生的主导变量有年均降水量、温度全年波动范围、昼夜温差月均值、温度季节性变化、降水量季节性变化和最冷季度均温。2)随机森林预测蝙蝠高适生分布区面积为9.7965×10^(4)km^(2),占云南省总面积的24.86%,主要分布在云南省南部、西南部和中东部地区。3)疫病传染风险评估发现45个乡镇属疫病传染高风险区,面积约0.5346×10^(4)km^(2),受影响人口约287万,主要分布在云南省南部、西南部和中东部地区。Various pathogens that live or are parasitic in the wild may have the potential to infect humans through evolution,genetic variation,or ecological suitability alteration.Therefore,it is important to carry out risk analysis of spatial and temporal intersection of human and important host animals for traceability tracking of unknown epidemic infections,field environmental health management and early warning.Bats carry a variety of dangerous pathogens.In this paper,a random forest model was constructed to predict the suitable distribution area of bats as the target hosts,and spatial variables related to bats and human activities were integrated to establish a risk assessment model with spatial intersection of humans and bats,and to produce a risk distribution map;for the convenience of administrative management,a risk analysis at the township level as the management unit was conducted.The results show that,1)The dominant variables affecting bat fitness are average annual precipitation,annual temperature fluctuation range,monthly mean diurnal temperature difference,seasonal variation of temperature,seasonal variation of rainfall and mean temperature of the coldest quarter.2)The random forest predicted the high fitness distribution area of bats was 9.7965×10^(4)km^(2),accounting for 24.86%of the total area of Yunnan Province,mainly distributed in southern part of Yunnan Province.3)The risk assessment of epidemic infection found 45 townships belonging to the high risk area of epidemic infection,with an area of about 0.5346×10^(4)km^(2)and an affected population of about 2.87 million,mainly distributed in the southern,southwestern and central-eastern parts of Yunnan Province.

关 键 词：蝙蝠 适生区 随机森林模型 风险评估模型 空间分布 

分 类 号：Q958[生物学—动物学]