Data from: Complexity increases predictability in allometrically constrained food webs

All ecosystems are subjected to chronic disturbances, such as harvest, pollution, and climate change. The capacity to forecast how species respond to such press perturbations is limited by our imprecise knowledge of pairwise species interaction strengths and the many direct and indirect pathways along which perturbations can propagate between species. Network complexity (size and connectance) has thereby been seen to limit the predictability of ecological systems. Here we demonstrate a counteracting mechanism in which the influence of indirect effects declines with increasing network complexity when species interactions are governed by universal allometric constraints. With these constraints, network size and connectance interact to produce a skewed distribution of interaction strengths whose skew becomes more pronounced with increasing complexity. Together, the increased prevalence of weak interactions and the increased relative strength and rarity of strong interactions in complex networks limit disturbance propagation and preserve the qualitative predictability of net effects even when pairwise interaction strengths exhibit substantial variation or uncertainty.

所有生态系统均会遭受采伐、污染、气候变化等持续性扰动。当前我们对物种间两两相互作用强度的认知精度有限，且扰动可通过物种间众多直接与间接路径传播，这两大因素共同制约了我们预测物种对这类持续性扰动（press perturbations）响应的能力。因此，网络复杂性（涵盖规模与连接度）一直被认为会限制生态系统的可预测性。本研究揭示了一种抵消性机制：当物种间相互作用受普适性异速生长约束（allometric constraints）调控时，间接效应的影响会随网络复杂性提升而减弱。在该约束条件下，网络规模与连接度相互作用，会产生相互作用强度的偏态分布，且该分布的偏态程度会随复杂性提升愈发显著。复杂网络中弱相互作用的占比升高，同时强相互作用的相对强度更高且更为稀有，二者共同限制了扰动的传播，即便两两相互作用强度存在显著变异或不确定性，仍可维持净效应的定性可预测性。