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在异速生长受限的食物网中,复杂性增加可预测性。

Complexity Increases Predictability in Allometrically Constrained Food Webs.

作者信息

Iles Alison C, Novak Mark

出版信息

Am Nat. 2016 Jul;188(1):87-98. doi: 10.1086/686730. Epub 2016 May 2.

DOI:10.1086/686730
PMID:27322124
Abstract

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.

摘要

所有生态系统都会受到诸如收获、污染和气候变化等长期干扰。预测物种如何应对此类压力扰动的能力受到限制,这是因为我们对物种间成对相互作用强度以及干扰在物种间传播的许多直接和间接途径的了解并不精确。因此,网络复杂性(规模和连通性)被认为限制了生态系统的可预测性。在此,我们展示了一种抵消机制,当物种相互作用受通用异速生长约束支配时,间接效应的影响会随着网络复杂性的增加而下降。在这些约束条件下,网络规模和连通性相互作用,产生相互作用强度的偏态分布,随着复杂性增加,这种偏态会变得更加明显。综合来看,复杂网络中弱相互作用的普遍增加以及强相互作用相对强度和稀有性的增加,限制了干扰传播,并保持了净效应的定性可预测性,即便成对相互作用强度表现出很大的变化或不确定性。

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