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基于MaxEnt模型的细足捷蚁在我国的适生区分析

张彦静1,2,马方舟2*,徐海根2,范靖宇3,孙红英1,丁晖2   

  1. (1南京师范大学生命科学学院, 南京 210023;2环境保护部南京环境科学研究所/国家环境保护生物安全重点实验室, 南京 210042;3天津师范大学生命科学学院/天津市动植物抗性重点实验室, 天津 300387)
  • 出版日期:2018-11-10 发布日期:2018-11-10

Prediction of potential geographic distribution of Anoplolepis gracilipes (Homoptera: Formicinae) in China using MaxEnt model.

ZHANG Yan-jing1,2, MA Fang-zhou2*, XU Hai-gen2, FAN Jing-yu3, SUN Hong-ying1, DING hui2   

  1. (1College of Life Science, Nanjing Normal University, Nanjing 210023, China; 2Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing 210042, China; 3Tianjin Key Laboratory of Animal and Plant Resistance, College of Life Sciences, Tianjin Normal University, Tianjin 300387, China).
  • Online:2018-11-10 Published:2018-11-10

摘要: 细足捷蚁(Anoplolepis gracilipes)是新发现入侵我国南方地区的外来物种,对入侵地的生物多样性造成了严重威胁。为探究细足捷蚁的潜在扩散风险及其野生种群在我国的适生区范围,本文将细足捷蚁的分布点分为本土分布点和全球分布点,并分别构建了本土预测模型和全球预测模型,采用对细足捷蚁生存影响比较大的7个环境变量,通过调用ENMeval数据包调整MaxEnt模型参数,分别采用默认参数和优化参数并基于上述两种模型,对细足捷蚁在我国的适生区范围进行了预测,最后采用pROC方案对模型结果进行可信度检验。研究发现,在相同参数条件下,基于全球模型和本土模型的细足捷蚁适生区分布范围预测差异较大,而模型参数对模型预测的影响较小。综合4种情况的模型预测结果,发现细足捷蚁在我国云南、广西、广东、福建、海南和台湾均表现为高度适生,在湖南、贵州、江西和四川的部分地区表现为中度适生。此外,在世界范围内细足捷蚁于非洲中部和美洲中北部表现出高适生性。因此,作者认为,入侵昆虫细足捷蚁本土分布范围的界定对其在入侵地的预测结果有较大影响,也是影响模型预测结果准确性的重要因素。

关键词: 寒害, 极端性, 冬种生产, 重现期

Abstract: Yellow crazy ant, Anoplolepis gracilipes, a newly recorded invasive species in southern China, poses serious threats to native biodiversity. In order to reveal the potential risk of its expansion and adaptive distribution, the occurrence points were divided into two parts: the native points and the global points, with local and global prediction models being constructed, respectively. Seven climatic environmental factors, which strongly influence the survival of A. gracilipes, were selected for model analysis. The maximum entropy (MaxEnt) model was adjusted by using the ENMeval data package in R software. The prediction of the niche area of A. gracilipes in China was constructed using the local and global prediction models with the default and refined parameter settings. The pROC protocol was used to test the reliability of the models. The results showed that under the same setting, there was an obvious difference in the potential geographic distribution of A. gracilipes, based on the global model and the native model, while the influence of the refined parameter settings on the model’s prediction was minimal. Overall, the potential distribution of A. gracilipes with high suitability was Yunnan, Guangxi, Guangdong, Fujian, Hainan and Taiwan, whereas Hunan, Guizhou, Jiangxi and parts of Sichuan were areas of intermediate suitability. Moreover, for the native model, central Africa and northcentral America were the potential distributions of the highly adaptive A. gracilipes. The definition of the local scope of A. gracilipes has a considerable impact on the accuracy of the prediction results of the model.

Key words: extreme, winter planting, chilling, return period