| 林浩宇,曾丽琼,詹芳芳,宋海天,裴家昌,毛新杰,蔡守平,,气候变化与人类活动对樟蚕在中国潜在适生区分布的影响[J].环境昆虫学报,(): |
| 气候变化与人类活动对樟蚕在中国潜在适生区分布的影响 |
| Impacts of climate change and human activities on the potential suitable distribution of Eriogyna pyretorum in China |
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| DOI： |
| 中文关键词: 樟蚕 适生区预测 MaxEnt 物种分布模型 |
| 英文关键词:Eriogyna pyretorum adaptive area prediction MaxEnt species distribution model |
| 基金项目:福建省科学技术厅农业引导性（重点）项目（2024N0015） |
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| 中文摘要: |
| 【目的】樟蚕Eriogyna pyretorum是一种危害樟树猖獗的食叶性害虫，大量发生时造成生物灾害及严重的经济损失。根据已知的樟蚕分布点和环境变量，采用优化后的MaxEnt模型来预测和分析樟蚕在中国的潜在适生区分布，为后续樟蚕的防治和建立相关预警机制提供理论依据。【方法】通过文献收集、实地调查获取樟蚕的537个点的分布数据，并引入人类影响指数、地形数据和气候变量，采用优化后的MaxEnt模型来预测当前和2050s（2041-2060）、2070s（2061-2080）3个时期不同情景（SSP126，SSP245，SSP585）条件）下樟蚕在中国生区的分布范围。【结果】樟蚕的分布受多种环境变量的影响，其中温度和降水对樟蚕的分布起到主导作用，其中年平均气温（Bio1），年降水量（Bio12），昼夜温差月均值（Bio2），等温性（Bio3）对樟蚕分布的影响的累积贡献达到了91.6%。MaxEnt模型预测结果表明测试可信度极高，模型AUC值为0.997。MaxEnt模型预测当前条件下樟蚕在中国的高、中度适生区主要集中在中国广东、广西、湖南、江西等地，面积占中国陆地面积的12.5%。SSP126，SSP585情景下，2050年樟蚕在安徽、浙江、福建等地区的高适生区范围扩大。此外，樟蚕在SSP245，SSP585情景下，2070年适生区边界向北部、西部偏移。【结论】MaxEnt模型的预测结果能够反映樟蚕在中国的分布特征，樟蚕的未来发生范围有可能向中国的西部和北部扩散。应当从多方面监测并建立完善的预警机制，以防其进一步的扩散。 |
| 英文摘要: |
| 【Aim】Eriogyna pyretorum is a destructive defoliator of Cinnamomum camphora, and its outbreaks can cause significant ecological damage and economic losses. Based on the known distribution points and environmental variables, an optimized MaxEnt model was employed to predict and analyze the potential suitable habitats of E. pyretorum in China. The findings of this study provide a theoretical basis for developing effective pest control strategies and establishing early warning mechanisms.【Methods】A total of 537 distribution points of E. pyretorum were collected through literature review and field surveys. Integrating human impact index, terrain data, and climate variables, the optimized MaxEnt model was employed to predict the suitable habitat distribution of E. pyretorum in China for the current period and the 2050s (2041-2060) and 2070s (2061-2080) under three Shared Socioeconomic Pathways (SSP126, SSP245, and SSP585).【Results】The distribution of E. pyretorum is influenced by multiple environmental variables, with temperature and precipitation playing a key role in distribution of E. pyretorum. Specifically, the cumulative contribution of annual mean temperature (Bio1), annual precipitation (Bio12), mean diurnal range (Bio2), and isothermality (Bio3) reached 91.6%. The MaxEnt model demonstrated excellent predictive performance, with an Area Under the Curve (AUC) value of 0.997. Under current climate conditions, high and moderately suitable habitats are primarily concentrated in Guangdong, Guangxi, Hunan, and Jiangxi provinces, accounting for approximately 12.5% of China’s total land area. By the 2050s, the highly suitable areas are projected to expand in Anhui, Zhejiang, Fujian provinces under the SSP126 and SSP585 scenarios. In addition, by 2070 under the SSP245 and SSP585 scenarios. Furthermore, by the 2070s, the boundaries of suitable habitats are expected to shift northward and westward under the SSP245 and SSP585 scenarios.【Conclusion】The MaxEnt model predictions effectively reflect the distribution patterns of E. pyretorum in China, indicating a potential range expansion toward the west and north. It is recommended to implement multi?faceted monitoring and establish a comprehensive early warning system to prevent its further spread. |
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