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气候变化情景下刚竹毒蛾在中国适生区预测分析
Predicting the future distribution of Pantana phyllostachysae in China in a changing climate
张华峰
点击:259次 下载:13次
DOI:10.7679/j.issn.2095-1353.2023.087
作者单位:
中文关键词:刚竹毒蛾;MaxEnt;气候变化;适生区;预测
英文关键词:Pantana phyllostachysae; MaxEnt; climate change; suitable distribution area; prediction
中文摘要:

目的】 在气候变化情况下,研究刚竹毒蛾Pantana phyllostachysae Chao潜在适生区的分布,有助于做好该虫监测预警,减少对竹林的危害。【方法】 基于169条刚竹毒蛾的分布记录,以及当代和未来气候数据,应用MaxEnt模型和ArcGIS预测刚竹毒蛾在不同气候情景下的潜在适生区,探讨气候变化对其适生区分布的影响。【结果】 MaxEnt模型受试者工作特征曲线(Receiver operating characteristic, ROC),训练AUC值均大于0.944 8,表明预测结果极好;最干月降水量(bio14)和最冷季平均降水量(bio19)是影响我国刚竹毒蛾分布最主要的限制因子。MaxEnt模型预测结果表明,当代刚竹毒蛾在我国的适生区总面积为1.49×106  km2,高度和中度适生区主要分布于江西、福建、湖南、浙江等长江以南地区。在未来气候条件下,刚竹毒蛾在我国适生区总面积变化不显著,但发生程度有变化,低适生区面积略有减少,中高适生区面积略有增加;在地理分布格局上,适生区向北、向南和向西扩张,江苏、安徽、河南和湖北等地将成为刚竹毒蛾新的适生区。【结论】 随着全球气候变暖,刚竹毒蛾适生区面积总体变化不大,但适生区发生程度和地理分布格局发生变化,未来要加强对新增刚竹毒蛾适生区的预警和防控。

 

 


英文摘要:
[ObjectivesPantana phyllostachysae Chao is the main leaf-feeding pest in bamboo forest. Understanding the potential future distribution of this pest in a changing climate will be helpful for future pest monitoring and forecasting, and protecting bamboo forests. [Methods]  Based on 169 distribution records, as well as contemporary and future climate data, we used the Maxent model and ArcGIS to predict the potential distribution of P. phyllostachysae under different climate scenarios. [Results]  The AUC values of receiver operating characteristic curve (ROC) training in the MaxEnt model were all greater than 0.944 8, indicating that results of the predictive model were excellent. Precipitation in the driest month (bio14) and mean precipitation in the coldest quarter (bio19) are the main limiting factors affecting the distribution of P. phyllostachysae in China. The results of the MaxEnt model predict that the total habitat potentially suitable for P. phyllostachysae in China is 1.49 × 106 km2, and that areas of high and moderate suitability are mainly distributed in Jiangxi, Fujian, Hunan and Zhejiang provinces. In the predicted future climate conditions, the total area of suitable habitat did not change significantly, but abundance did. The area of low suitability habitat decreased slightly, and the area of medium and high suitability habitat increased slightly. In terms of geographical distribution, suitable areas are predicted to expand northward, southward and westward. Jiangsu, Anhui, Henan and Hubei are predicted to become suitable for P. phyllostachysae in the future.  [Conclusion]  Global warming is predicted to have little effect on the distribution of P. phyllostachysae, but will affect the abundance and geographical distribution pattern of this pest. Monitoring, forecasting and control of P. phyllostachysae should be implemented in the areas predicted to become more suitable for this pest.

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