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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >Simple Prediction Of Interaction Strengths In Complex Food Webs
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Simple Prediction Of Interaction Strengths In Complex Food Webs

机译：复杂食物网中相互作用强度的简单预测

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摘要

Darwin's classic image of an "entangled bank" of interdependences among species has long suggested that it is difficult to predict how the loss of one species affects the abundance of others. We show that for dynamical models of realistically structured ecological networks in which pair-wise consumer-resource interactions allometrically scale to the 3/4 power-as suggested by metabolic theory-the effect of losing one species on another can be predicted well by simple functions of variables easily observed in nature. By systematically removing individual species from 600 networks ranging from 10-30 species, we analyzed how the strength of 254,032 possible pair-wise species interactions depended on 90 stochastically varied species, link, and network attributes. We found that the interaction strength between a pair of species is predicted well by simple functions of the two species' biomasses and the body mass of the species removed. On average, prediction accuracy increases with network size, suggesting that greater web complexity simplifies predicting interaction strengths. Applied to field data, our model successfully predicts interactions dominated by trophic effects and illuminates the sign and magnitude of important nontrophic interactions.
机译：达尔文关于物种相互依存的“纠缠库”的经典形象长期以来一直表明，很难预测一种物种的丧失如何影响另一种物种的丰度。我们证明，对于现实结构化的生态网络的动力学模型，其中成对的消费者-资源互动成角度地扩展到3/4幂（如新陈代谢理论所建议的），可以通过简单的函数很好地预测一种物种在另一种物种上失去的影响自然界中容易观察到的变量通过系统地从600种网络中删除10-30种物种中的单个物种，我们分析了254,032种可能的成对物种相互作用的强度如何取决于90个随机变化的物种，链接和网络属性。我们发现，通过两个物种的生物量的简单功能以及被移除物种的体重，可以很好地预测一对物种之间的相互作用强度。平均而言，预测精度随网络规模的增加而增加，这表明更高的网络复杂性简化了预测交互强度的过程。应用于现场数据，我们的模型成功地预测了由营养作用主导的相互作用，并阐明了重要的非营养相互作用的迹象和强度。

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