基于集成物种分布模型的广东省藁杆双脐螺分布特征及未来适宜区预测研究

doi:10.19871/j.cnki.xfcrbzz.2025.06.006

新发传染病电子杂志 ›› 2025, Vol. 10 ›› Issue (6): 38-45.doi: 10.19871/j.cnki.xfcrbzz.2025.06.006

基于集成物种分布模型的广东省藁杆双脐螺分布特征及未来适宜区预测研究

卢茜¹, 何英俊², 沈培林³, 陈攀爵², 高世同⁴

1.深圳市龙岗区疾病预防控制中心业务管理科,广东深圳 51800;
2.深圳市龙岗区吉华公共卫生服务中心行政部,广东深圳 51800;
3.深圳市龙岗区疾病预防控制中心消毒与病媒生物管理科,广东深圳 51800;
4.深圳市疾病预防控制中心传染病防治所,广东深圳 51800

收稿日期:2025-10-09 出版日期:2025-12-31 发布日期:2026-01-26
通讯作者: 高世同,Email：gst@szcdc.net
基金资助:
1.深圳市自然科学基金面上项目（JCYJ20220531103808020）; 2.深圳市龙岗区医疗卫生技术攻关扶持项目（LGKCYLWS2024-3）

Distribution characteristics and future suitable area prediction of Biomphalaria straminea in Guangdong Province based on integrated species distribution model

Lu Qian¹, He Yingjun², Shen Peilin³, Chen Panjue², Gao Shitong⁴

1. Business Management Section, Shenzhen Longgang District Center for Disease Control and Prevention, Guangdong Shenzhen 51800, China;
2. Administration Department, Jihua Public Health Service Center, Longgang District, Guangdong Shenzhen 51800, China;
3. Disinfection and Vector Management Section, Shenzhen Longgang District Center for Disease Control and Prevention, Guangdong Shenzhen 51800, China;
4. Institute of Communicable Disease Prevention and Control, Shenzhen Center for Disease Control and Prevention, Guangdong Shenzhen 51800, China

Received:2025-10-09 Online:2025-12-31 Published:2026-01-26

摘要/Abstract

摘要： 目的本研究旨在利用当前气候和土地特征分析广东省藁杆双脐螺适宜生境分布,并评估未来气候情景下该物种生境的变化,为藁杆双脐螺的精准监测、入侵风险防控及生态安全管理提供科学依据。方法通过实地调查、文献查阅和检索数据库（https://www.gbif.org）收集藁杆双脐螺分布数据。使用堆叠物种分布模型R软件包构建包括支持向量机、随机森林、广义加性模型、梯度提升机和多元自适应回归样条在内的物种分布模型。采用表现最佳的模型构建集合物种分布模型,预测广东省当前和未来不同情景下的藁杆双脐螺适宜生境分布。结果研究发现,人类足迹、等温性和坡向是影响藁杆双脐螺分布的最显著环境变量。在当前条件下,藁杆双脐螺的高适宜栖息地集中在珠江三角洲和潮汕地区,面积约为26 100km²。在未来情景下,藁杆双脐螺适宜区域将显著扩张,并且在SSP3-7.0情景下的藁杆双脐螺平均栖息地适宜区域面积始终高于SSP1-2.6情景。结论人类足迹、等温性和坡向是驱动藁杆双脐螺入侵的主要因素。同时,未来的气候变化将成为影响其潜在地理分布和扩散趋势的关键因素,大幅加剧藁杆双脐螺由南向北蔓延的风险。这迫切需要政府采取针对性、前瞻性的监测和控制策略,以预防藁杆双脐螺作为中间宿主的曼氏血吸虫病在中国南方形成新的地方性流行区域。

关键词: 藁杆双脐螺, 曼氏血吸虫病, 集成物种分布模型, 机器学习, 适宜区域

Abstract: Objective The purpose is to analyze the suitable habitat distribution of Biomphalaria straminea in Guangdong Province using current climate and land characteristics and to assess the changes in these habitats under future climate scenarios. Method We collected distribution data of B. straminea through field surveys, literature reviews, and search online database (https://www.gbif.org). Species distribution models, including support vector machine, random forest, generalized additive model, gradient boosting machine, and multivariate adaptive regression splines, were constructed using the R package "SSDM" and environmental factors. The best-performing model was selected to build an ensemble species distribution model (ESDM) to predict the suitable habitat distribution in Guangdong Province under current and future scenarios. Result Research revealed that that human footprint, isothermality and aspect are the most significant environmental and socio-economic factors driving the distribution of Biomphalaria straminea. Under current conditions, highly suitable habitats for B. straminea are concentrated in the Pearl River Delta and Chaoshan regions, covering an area of approximately 26 100km². Under future scenarios, the suitable range for B. straminea is predicted to expand significantly, and the average area of suitable habitats under the SSP3-7.0 scenario is consistently larger than that under the SSP1-2.6 scenario. Conclusion Human activities, isothermality, and aspect are the main factors driving the invasion of Biomphalaria straminea. Simultaneously, future climate change will become a critical factor influencing its potential geographical distribution and diffusion trend, significantly increasing the risk of the snail's south-to-north spread. This urgently requires the government to formulate targeted and forward-looking monitoring and control strategies to prevent Schistosomiasis mansoni, for which Gastrocopta armilla acts as an intermediate host, from forming new endemic areas in Southern China.

Key words: Biomphalaria straminea, Schistosomiasis mansoni, Climate change, Ensemble species distribution model, Machine learning, Suit ablearea

中图分类号:

R725.1

卢茜, 何英俊, 沈培林, 陈攀爵, 高世同. 基于集成物种分布模型的广东省藁杆双脐螺分布特征及未来适宜区预测研究[J]. 新发传染病电子杂志, 2025, 10(6): 38-45.

Lu Qian, He Yingjun, Shen Peilin, Chen Panjue, Gao Shitong. Distribution characteristics and future suitable area prediction of Biomphalaria straminea in Guangdong Province based on integrated species distribution model[J]. Electronic Journal of Emerging Infectious Diseases, 2025, 10(6): 38-45.

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基于集成物种分布模型的广东省藁杆双脐螺分布特征及未来适宜区预测研究

Distribution characteristics and future suitable area prediction of Biomphalaria straminea in Guangdong Province based on integrated species distribution model

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