Abstract: Objective　To assess the survival vulnerability of Oncomelania hupensis in Jiangxi Province under future climate scenarios, and to identify low⁃vulnerability areas for its survival in this province. Methods　Village⁃level O. hupensis snail survey and O. hupensis snail control with chemical treatments in Jiangxi Province from 2016 to 2024 were captured from the Parasitic Disease Prevention and Control Information Management System of China Disease Prevention and Control Information System. Climatic data were primarily sourced from the Resource and Environmental Science Data Platform, Chinese Academy of Sciences (http://www.resdc.cn/), including annual average temperature, annual average precipitation, annual accumulated temperature above 10 ℃, annual accumulated temperature above 0 ℃, annual maximum temperature, annual minimum temperature, and annual average relative humidity, and nineteen bioclimatic variables were downloaded from the WorldClim website (https://www.worldclim.org/), including mean diurnal range, isothermality, temperature seasonality, and so on. Elevation and normalized difference vegetation index were catprued from the Resource and Environmental Science Data Platform, Chinese Academy of Sciences (http://www.resdc.cn/), and distance to rivers was downloaded from the WorldPop website (http://www.worldpop.org), and land use and land cover (LULC) data were downloaded from the Big Earth Data Center, Chinese Academy of Sciences (https://data.casearth.cn/), and nature reserve data were obtained from the China Nature Reserve Specimen Resource Sharing Platform (http://www.papc.cn/). Three Shared Socioeconomic Pathways (SSPs) from the Beijing Climate Center⁃Climate System Model version 2⁃Medium Resolution (BCC⁃CSM2⁃MR) global climate model were employed as future climate scenarios, including SSP126, SSP245, SSP585, and the biomod2 ensemble model in R package was used to simulate suitable habitats for O. hupensis snails in Jiangxi Province in 2050 and 2070 under these scenarios. A snail survival vulnerability index was constructed based on the area of suitable snail habitats, area covered by snail control through chemical treatment, area covered by nature reserves, and changes in snail habitat fragmentation, and a map of snail survival vulnerability distribution was plotted. Results　The real area of snail habitats ranged from 78 486.76 to 85 309.47 hm2, and the area of snail control with chemical treatment ranged from 10 138.98 to 13 240.16 hm2 in Jiangxi Province from 2016 to 2024. There were 429 to 531 villages detected with snails during the nine⁃year period, and the number of actually snail⁃infested villages ranged from 645 to 686. A total of 818 snail⁃present points and 1 996 snail⁃absent points were obtained from snail survey records. The best performance of the biomod2 ensemble model was achieved if a weighted mean approach was used as the ensemble strategy, with a true skill statistic value of 0.799 and an area under the receiver operating characteristic curve of 0.957, and modeling identified annual average relative humidity and annual average precipitation as two most influencing climatic variables for snail distribution. Relative to the current areas of suitable snail habitats under present climate conditions, the area of suitable snail habitats was projected to expand by 24.49% to 46.28% in Jiangxi Province under future climate scenarios, and the proportion of nature reserves areas in the areas of suitable snail habitats was projected to decrease slightly from the current 2.77% to approximately 2.52%, while the proportion of areas of snail control through chemical treatment in areas of suitable snail habitats varied from 0.64% to 19.57%, and the percentage of changes in snail habitat fragmentation ranged from 3.86% to 12.23%. Based on these four indicators, the snail survival vulnerability index was estimated to range from –1.96 to 0.62 in Jiangxi Province. The arithmetic mean of the snail survival vulnerability index differed under three SSP scenarios (SSP126, SSP245 and SSP585), with the highest mean value (–0.69) in 2070 under SSP126, and the lowest mean value (–0.78) in 2070 under SSP585.  Conclusions　The snail survival vulnerability index ranges from –1.96 to 0.62 in Jiangxi Province under future climate scenarios, and the suitable habitats for O. hupensis snails appear an overall tendency towards expansion. Low⁃vulnerability snail habitats are mainly distributed along the shores of Poyang Lake and the Yangtze River in Jiangxi Province, partially overlapping with nature reserves. Intensified surveillance of O. hupensis snails is recommended in these areas in the future. 

Key words: Oncomelania hupensis, Climate change, Vulnerability assessment, Survival capacity, biomod2 ensemble model, Jiangxi Province  

摘要： 目的　基于未来气候情境，对江西省钉螺生存脆弱性进行评估，以识别钉螺生存低脆弱性区域。方法　自中国疾病预防控制信息系统寄生虫病防治信息管理系统获取2016—2024年江西省以村为单位的钉螺调查及药物灭螺数据。自中国科学院资源环境科学数据中心（http://www.resdc.cn/）获取年均气温、年均降水量、≥ 10 ℃年积温、≥ 0 ℃年积温、年最高温、年最低温、年均相对湿度数据，自世界气候数据网站（https://www.worldclim.org/）获取平均昼夜温差、等温性、温度季节性等19个生物气候数据。自中国科学院资源环境科学数据中心（http://www.resdc.cn/）获取海拔高度和归一化植被指数数据，自WorldPop网站（http://www.worldpop.org）下载距河流距离，自地球大数据共享服务系统（https://data.casearth.cn/）下载土地利用与覆盖数据，自中国自然保护区标本资源共享平台（http://www.papc.cn/）获取自然保护区数据。以北京气候中心气候系统模式第2版⁃中等分辨率版本（Beijing Climate Center⁃Climate System Model version 2⁃Medium Resolution，BCC⁃CSM2⁃MR） 全球气候模式中的3种共享社会经济路径（SSP126、SSP245及SSP585）作为未来气候情景，并通过R软件中的biomod2集成模型对2050、2070年江西省钉螺适生区进行模拟。采用钉螺适生区面积、药物灭螺覆盖面积、自然保护区覆盖面积、生境破碎化变化率4个指标构建钉螺生存脆弱性指数，绘制钉螺生存脆弱性分布地图。结果 2016—2024年，江西省实有钉螺面积为78 486.76～85 309.47 hm2，药物灭螺面积为10 138.98～13 240.16 hm2。9年间江西省查出有螺村429～531个，实际有螺村645～686个。基于查螺信息共获取818个钉螺分布点和1 996个钉螺不存在点。biomod2集成模型集成方式采用加权平均时模型性能最佳，真实技能统计量值为0.799，受试者工作特征曲线下面积为0.957；模型分析结果显示，对钉螺分布影响较大的气候因子为年均相对湿度和年均降水量。以当前气候条件下江西省钉螺适生区面积为基准，未来气候情境下该省钉螺适生区面积将扩大24.49%～46.28%，自然保护区面积占适生区面积的比例由当前的2.77%小幅下降至2.52%，药物灭螺面积占适生区面积的比例在0.64%～19.57%，生境破碎化变化率在3.86%～12.23%。基于上述4个指标计算得出江西省钉螺脆弱性指数范围为-1.96～0.62。在3种共享社会经济路径（SSP126、SSP245、SSP585）下，江西省钉螺脆弱性指数的算术平均值存在差异，其中SSP126情景下2070年的平均值最高（−0.69），SSP585情景下2070年的平均值最低（−0.78）。结论　未来气候情境下，江西省钉螺生存脆弱性指数范围为−1.96～0.62，钉螺适生区总体呈扩张趋势。该省钉螺生存低脆弱性区域主要分布于鄱阳湖沿岸及长江沿线，与自然保护区分布范围部分重叠，未来需加强此区域内的钉螺监测。

关键词: 钉螺, 气候变化, 脆弱性评估, 生存能力, biomod2集成模型, 江西省