CAJ | 학술논문

目的探讨采用空间信息技术及生态位理论预测新疆准噶尔盆地大沙鼠的适生区分布,提高鼠疫监测效率.方法通过现场调查获得准噶尔盆地大沙鼠分布的全球定位系统经纬度信息,通过遥感获得环境变量图层,利用Maxent软件建模,结合地理信息系统获得大沙鼠适生区分布图,对模型评价并划分风险分级图,叠加人口数据标示重点关注地区.结果模型预测精度较高,曲线下面积值为0.968,灵敏度为91.4％,特异度为63.3％,准确度为73.8％,阳性预测值为59.7％,阴性预测值为92.6％,Kappa系数为0.495.大沙鼠适生区分布在准噶尔盆地及其周边大部分区县,高风险地区总面积约37 304 km2,约占总面积的6.2％,主要分布在昌吉回族自治州、乌鲁木齐市米东区及克拉玛依市,其中米东区、克拉玛依市辖区及乌尔禾区的分布较广;区域内人口约12万,分布于261 km2区域内.重点监测地区包括乌鲁木齐市、五家渠市、克拉玛依市、博乐市、精河县、奎屯市、阜康市、吉木萨尔县及木垒哈萨克自治县.结论生态位理论和遥感环境数据可预测新疆准噶尔盆地大沙鼠潜在适生区,并显著缩小了重点监测的靶地区.
목적 탐토채용공간신식기술급생태위이론예측신강준갈이분지대사서적괄생구분포,제고서역감측효솔.방법 통과현장조사획득준갈이분지대사서분포적전구정위계통경위도신식,통과요감획득배경변량도층,이용Maxent연건건모,결합지리신식계통획득대사서괄생구분포도,대모형평개병화분풍험분급도,첩가인구수거표시중점관주지구.결과 모형예측정도교고,곡선하면적치위0.968,령민도위91.4％,특이도위63.3％,준학도위73.8％,양성예측치위59.7％,음성예측치위92.6％,Kappa계수위0.495.대사서괄생구분포재준갈이분지급기주변대부분구현,고풍험지구총면적약37 304 km2,약점총면적적6.2％,주요분포재창길회족자치주、오로목제시미동구급극랍마의시,기중미동구、극랍마의시할구급오이화구적분포교엄;구역내인구약12만,분포우261 km2구역내.중점감측지구포괄오로목제시、오가거시、극랍마의시、박악시、정하현、규둔시、부강시、길목살이현급목루합살극자치현.결론 생태위이론화요감배경수거가예측신강준갈이분지대사서잠재괄생구,병현저축소료중점감측적파지구.
Objective In order to understand the distribution of the host animals in Junggar Basin,this study intended to map the spatial distribution and identifying the risk of Rhombomys opimus in the framework of ecological niche theory based on the "3S" technology.Methods Data on Rhombomys opimus was obtained through a series of field surveys.Environmental variables were achieved through data from Remote Sensing.Maxent modeling was built to map the potential distribution of Rhombomys opimus,with its risks identified.Results The prediction model showed ideal accuracy,with the AUC value as 0.968.Probability of Maximum Youden Index was defined as the threshold being used.The sensitivity and specificity showed as 91.4％ and 63.3％,respectively.The accuracy was 73.8％,and the Kappa coefficient was 0.495.The positive predictive value was 59.7％.The negative predictive value was 92.6％.The predicted high risk area was 37 304 km2,with 6.2％ in the whole area,distributed in 18 counties,including Changji Hui Autonomous Prefecture,Urumqi,Karamay and so on.The number of people under high risk would come about 120 000,scattering in the areas of 261 square kilometers.Conclusion It was feasible to predict the potential distribution of Rhombomys opimus based on the ecological niche theory as well as environmental variables derived from data through remote sensing.More specific high-risk areas could be identified under this technique so as to guide the monitoring programs.