摘要:物种间相互作用是影响生物群落稳定性和多样性的重要因素。基于Lotka-Volterra竞争模型，通过构建多宿主种群的种内和种间高阶相互作用模型，研究宿主种群的间接竞争效应对寄生群落动态的影响机制。为有效地揭示高阶作用对种群动态的影响，通过对比宿主-寄生群落的现象模型以及机制模型，利用机制模型产生的合理数据集对现象模型中高阶项的参数进行拟合，进而探讨了高阶相互作用在群落动态中的作用。结果显示，完整的高阶相互作用模型在描述多宿主-寄生系统的群落动态中表现最优，而直接相互作用模型对群落动态的描述相对较差，即同时考虑种间和种内的高阶相互作用模型更加符合机制模型所描述的群落动态。此外，种内高阶作用和种间高阶作用产生不对称效应，宿主间的种间高阶作用对群落产生的影响较种内高阶作用更为显著。该研究结果在一定意义上丰富了宿主-寄生生物群落的稳定性研究，为理解物种间相互作用的多样性研究提供了依据。



Abstract:Broad evidence has shown that species interactions could influence the stability and diversity of ecological communities. Higher-order interactions (HOIs) were defined as non-additive effects of density on per captia growth of species. Previous studies have showed that the non-additive effects could strongly influence community stability, patterns of diversity, and better explaining the dynamics of natural community. However, the effect of higher-order interactions on the parasitic community has received little attention. Following this line of thinking, we examined the role of higher-order interactions in the dynamics of multihost-parasite community. We first extended the Lotka-Volterra competition model into the phenomenological models describing a multihost community with three host species that incorporated a generalist, environmentally transmitted parasite. To explore the implications of higher-order interactions for the parasitic infection, we then included the intra-specific and/or inter-specific higher-order interactions in the multihost-parasite system. Phenomenological models can tell us something about where, when, and what of higher-order interactions, but they tell us little about how and why. We supposed these interactions arising via resource competition. Then, we further constructed the mechanistic models of resource competition of multihost-parasitic community, in which non-additive dynamics emerged implicitly, without the need to invoke the higher-order terms. Data generated from simulations of mechanistic models to assess the frequency and magnitude of higher-order interactions arising about the dynamics of multi-host system. Then, we fitted the four phenomenological models by regression analysis:(i) direct interactions model; (ii) intra-specific higher-order interactions model; (iii) inter-specific higher-order interactions model; and (iv) fully specified higher-order interactions model (including intra-specific and inter-specific higher-order interactions). The results revealed that the fit goodness displayed different results with models of higher-order interactions and direct interactions. Importantly, fully specified higher-order interactions model performed best in describing the community dynamic of multiple host-parasitic, but the direct interactions model showed the worst result among the four models. In addition, the results also revealed that the effects of intra-specific and inter-specific higher-order interactions were asymmetric, and the model with inter-specific higher-order interactions predicted accurately than that of intra-specific higher-order interactions. In order to test the sensitivity and robustness of the dataset generation and fitting process, we conducted additional simulations by changing perturbation densities to less than half of each host's carrying capacity. And the results showed that the simulation method is reasonable. Our results thus underlined the importance of considering higher-order interactions when investigating the multihost-parasite community, and provided a basis for understanding the diversity of interactions between species.





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