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模糊逻辑揭示伊比利亚蝴蝶的集合种群模式

Metapopulation Patterns of Iberian Butterflies Revealed by Fuzzy Logic.

作者信息

Pulido-Pastor Antonio, Márquez Ana Luz, Guerrero José Carlos, García-Barros Enrique, Real Raimundo

机构信息

Biogeography, Diversity and Conservation Research Team, Departamento de Biología Animal, Universidad de Málaga, 29071 Málaga, Spain.

Laboratorio de Desarrollo Sustentable y Gestión Ambiental del Territorio, Instituto de Ecología y Ciencias Ambientales, Facultad de Ciencias, Universidad de la República, 11400 Montevideo, Uruguay.

出版信息

Insects. 2021 Apr 28;12(5):392. doi: 10.3390/insects12050392.

Abstract

Metapopulation theory considers that the populations of many species are fragmented into patches connected by the migration of individuals through an interterritorial matrix. We applied fuzzy set theory and environmental favorability (F) functions to reveal the metapopulational structure of the 222 butterfly species in the Iberian Peninsula. We used the sets of contiguous grid cells with high favorability (F ≥ 0.8), to identify the favorable patches for each species. We superimposed the known occurrence data to reveal the occupied and empty favorable patches, as unoccupied patches are functional in a metapopulation dynamics analysis. We analyzed the connectivity between patches of each metapopulation by focusing on the territory of intermediate and low favorability for the species (F < 0.8). The friction that each cell opposes to the passage of individuals was computed as 1-F. We used the r.cost function of QGIS to calculate the cost of reaching each cell from a favorable patch. The inverse of the cost was computed as connectivity. Only 126 species can be considered to have a metapopulation structure. These metapopulation structures are part of the dark biodiversity of butterflies because their identification is not evident from the observation of the occurrence data but was revealed using favorability functions.

摘要

集合种群理论认为,许多物种的种群被分割成斑块,这些斑块通过个体在领地间基质中的迁移而相互连接。我们应用模糊集理论和环境适宜性(F)函数来揭示伊比利亚半岛222种蝴蝶的集合种群结构。我们使用具有高适宜性(F≥0.8)的相邻网格单元集,来识别每个物种的适宜斑块。我们叠加已知的出现数据,以揭示已占据和未占据的适宜斑块,因为未占据的斑块在集合种群动态分析中具有作用。我们通过关注物种适宜性处于中等和低水平(F<0.8)的区域,来分析每个集合种群斑块之间的连通性。每个单元格对个体通行的阻力计算为1-F。我们使用QGIS的r.cost函数来计算从一个适宜斑块到达每个单元格的成本。成本的倒数被计算为连通性。只有126种蝴蝶可被认为具有集合种群结构。这些集合种群结构是蝴蝶暗生物多样性的一部分,因为它们的识别从出现数据的观察中并不明显,而是通过适宜性函数揭示出来的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/938b/8145449/775f59c89476/insects-12-00392-g001.jpg

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