特质
理论(学习稳定性)
进化生物学
生物
生物系统
计算机科学
生态学
机器学习
程序设计语言
作者
Jan Timo Bachmann,Barbara Drossel
标识
DOI:10.1007/s12080-025-00621-y
摘要
Abstract Mutualistic interactions including pollination are essential for the functioning of ecosystems, but increasingly endangered due to anthropogenic disturbances. Understanding factors that affect their stability is therefore essential. We use a population dynamics model in combination with a trait-based network architecture to investigate the stability and structure of bipartite mutualistic networks. We find that pollinator specialisation increases robustness, i.e. the proportion of surviving species, when survival is limited by pollinator competition, by low interaction strengths, or by high mortality rates. In the opposite situations, networks with more generalists are more robust. When plant-pollinator interactions depend in an asymmetric way on their trait difference, nestedness is increased compared to a model with symmetric interactions, and specialists and generalists show a different distribution in trait space. Increased nestedness is only in some situations correlated with a higher robustness, while in other situations, the correlation is negative or neutral.
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