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黑肩绿盲蝽和中华淡翅盲蝽的适宜生态空间和潜在分布分析 被引量:4

Ecological dimensions and potential distributions of two mirid predators,Cyrtorhinus lividipennis and Tytthus chinensis, in China
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摘要 为明确稻飞虱的2种重要天敌黑肩绿盲蝽Cyrtorhinus lividipennis和中华淡翅盲蝽Tytthus chinensis在中国的适宜生态空间,根据二者已有的分布记录,通过选取具有限制性意义的气候变量,对2种盲蝽的生态空间进行了对比;并通过界定合适的模型构建区域,基于赤池信息量准则选取最优模型,在默认参数和校正优化参数下分别构建MaxEnt模型,对其预测结果进行比较分析。结果显示,2种盲蝽在我国所占有的生态空间具有较大的重叠,基于默认和优化参数的MaxEnt模型的预测结果差别较大,其中基于默认参数的MaxEnt模型预测结果较为保守,而基于优化参数后的MaxEnt模型能够较好地预测中华淡翅盲蝽与黑肩绿盲蝽在我国的生态空间和潜在分布,二者在我国中部及东南部有较大的生态空间和潜在分布区重叠,包括河南、江苏、浙江、湖北、湖南、福建、广东、广西等省区,其中黑肩绿盲蝽在我国华北和西北部亦有较高的适生性。 Tytthus chinensis and Cyrtorhinus lividipennis are two major natural enemies of rice planthoppers, and their ecological dimensions and potential distributions were predicted using ecological niche model. Environmental spaces occupied by the two species were firstly compared using occurrence records that were attained from literature and environmental variables selected according to their ecological relevance. Based on geographic backgrounds delimited according to the accessibility of individual species, the default and fine-tuned MaxEnt models for T. chinensis and C. lividipennis to predict their potential distributions were generated. The fine-tuned MaxEnt model was selected based on the corrected Akaike information criterion. The results showed that environmental space occupied by the two species overlapped broadly, and the predictions based on default and fine-tuned MaxEnt models were different: predictions based on default settings was more conservative than that based on fine-tuned parameters. The fine-tuned MaxEnt could more accurately predict the ecological dimensions and potential distributions of T. chinensis and C. lividipennis in China, and both species showed high climate suitability in central and southeastern China, including Henan, Jiangsu, Zhejiang, Hubei, Hunan, Fujian, Guangdong and Guangxi;C. lividipennis also showed high suitability in the north and northwest of China.
作者 范靖宇 原雪姣 杨琢 李敏 朱耿平 Fan Jingyu;Yuan Xuejiao;Yang Zhuo;Li Min;Zhu Gengping(Key Laboratory of Animal and Plant Resistance in Tianjin,College of Life Sciences, Tianjin Normal University,Tianjin 300387,China)
出处 《植物保护学报》 CAS CSCD 北大核心 2019年第1期159-166,共8页 Journal of Plant Protection
基金 国家自然科学基金(31401962 31870523) 天津市"131"创新人才培养工程项目(ZX0471601006)
关键词 黑肩绿盲蝽 中华淡翅盲蝽 潜在分布 生态位模型 MaxEnt模型 Tytthus chinensis Cyrtorhinus lividipennis potential distribution ecological niche modeling MaxEnt model
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