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食物网中基序家族的起源。

The origin of motif families in food webs.

机构信息

Centre for Complexity Science, University of Warwick, Coventry, CV4 7AL, United Kingdom.

School of Mathematics, University of Birmingham, Birmingham, B15 2TT, United Kingdom.

出版信息

Sci Rep. 2017 Nov 23;7(1):16197. doi: 10.1038/s41598-017-15496-1.

Abstract

Food webs have been found to exhibit remarkable "motif profiles", patterns in the relative prevalences of all possible three-species subgraphs, and this has been related to ecosystem properties such as stability and robustness. Analysing 46 food webs of various kinds, we find that most food webs fall into one of two distinct motif families. The separation between the families is well predicted by a global measure of hierarchical order in directed networks-trophic coherence. We find that trophic coherence is also a good predictor for the extent of omnivory, defined as the tendency of species to feed on multiple trophic levels. We compare our results to a network assembly model that admits tunable trophic coherence via a single free parameter. The model is able to generate food webs in either of the two families by varying this parameter, and correctly classifies almost all the food webs in our database. This is in contrast with the two most popular food web models, the generalized cascade and niche models, which can only generate food webs within a single motif family. Our findings suggest the importance of trophic coherence in modelling local preying patterns in food webs.

摘要

食物网被发现具有显著的“模式特征”,即所有可能的三种物种子图的相对流行模式,这与生态系统的稳定性和鲁棒性等特性有关。通过分析 46 种不同类型的食物网,我们发现大多数食物网属于两种截然不同的模式家族之一。家族之间的分离可以通过有向网络中一个全局的层次秩序度量——营养相干性来很好地预测。我们发现营养相干性也是衡量泛食性程度的一个很好的指标,泛食性是指物种倾向于取食多个营养级的程度。我们将研究结果与一个网络组装模型进行了比较,该模型通过一个单一的自由参数来允许可调的营养相干性。通过改变这个参数,该模型能够在这两个家族中的任何一个中生成食物网,并且能够正确地对我们数据库中的几乎所有食物网进行分类。这与最流行的两种食物网模型——广义级联和生态位模型形成了鲜明对比,后两者只能在单个模式家族中生成食物网。我们的研究结果表明,在食物网中模拟局部捕食模式时,营养相干性非常重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04eb/5700930/0ed35a7102d2/41598_2017_15496_Fig1_HTML.jpg

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