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空间复杂性增强食物网的可预测性。

Spatial complexity enhances predictability in food webs.

机构信息

Department of Biological Science, Faculty of Life and Environmental Science, Shimane University, 1060 Nishikawatsu-cho, Matsue 690-8504, Japan.

出版信息

Sci Rep. 2017 Feb 27;7:43440. doi: 10.1038/srep43440.

Abstract

The prediction of an ecosystem's response to an environmental disturbance or the artificial control of ecosystems is a challenging task in ecology. Ecological theory predicts that disturbances frequently result in unexpected responses between interacting species due to the many indirect interactions within a complex community. However, such indeterminacy appears to be unusual in nature. Here using a meta-community food web, I show that spatiality is key to resolving this disparity. A moderate level of spatial coupling strength between habitats due to species migration increases the possibility of expected responses to press perturbation or predictability. Moreover, predictability increases with increasing spatial complexity, as measured by the number of local food webs and their connectivity. A meta-community network can attenuate the propagation of disturbances through indirect pathways due to species emigration to other habitats, thereby preserving the expected effect on the interacting species. These results suggest that the isolation of communities due to habitat destruction decreases the predictability of communities, thereby complicating the control of ecosystems.

摘要

预测生态系统对环境干扰的响应或对生态系统的人工控制是生态学中的一项具有挑战性的任务。生态理论预测,由于复杂群落中存在许多间接相互作用,干扰通常会导致相互作用的物种产生意想不到的反应。然而,这种不确定性在自然界中似乎并不常见。在这里,我使用一个元社区食物网表明,空间性是解决这一差异的关键。由于物种迁移导致的栖息地之间适度的空间耦合强度增加了对press 扰动或可预测性的预期反应的可能性。此外,可预测性随着空间复杂性的增加而增加,其由本地食物网的数量及其连通性来衡量。元社区网络可以通过物种迁移到其他栖息地来减弱干扰通过间接途径的传播,从而保留对相互作用物种的预期影响。这些结果表明,由于栖息地破坏导致的社区隔离降低了社区的可预测性,从而使生态系统的控制变得更加复杂。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d75/5327493/8335c3b3fe54/srep43440-f1.jpg

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