Foraging preferences and interspecific competition generate multimodal complexity-stability relationships in an adaptive food-web framework
Cite this dataset
Wang, Lin et al. (2023). Foraging preferences and interspecific competition generate multimodal complexity-stability relationships in an adaptive food-web framework [Dataset]. Dryad. https://doi.org/10.5061/dryad.sf7m0cg9x
Ecological theory predicts that complex ecological networks are unstable and are unlikely to persist, despite many empirical studies of such complexity in nature. To resolve real complexity-stability relationships, coupling population dynamics and trait dynamics is considered to be an important way to understand the long-term stability of ecological community assemblages. However, modelling eco-evolutionary dynamics in ecologically realistic networks is still a challenge. Here, we establish an adaptive food web model to evaluate the complexity-stability debate in a mutualist-exploiters-specialist forager-generalist forager system. Our theoretical model predicts that the connectance-stability relationship may show positive monotonic (/), negative monotonic (\), peaked (∩) and double-peaked (oscillatory) patterns. Moreover, the double-peaked pattern is only obtained when both the adaptation intensity and interspecific competition are high, which may explain no complexity-stability relationships revealed in empirical data. Finally, we deduce that foraging adaptation alters positive and/or negative feedback loops to affect the stability of real food webs.
National Natural Science Foundation of China, Award: 32201259
National Natural Science Foundation of China, Award: 20224BAB215010