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How to predict community responses to perturbations in the face of imperfect knowledge and network complexity

机译:在知识和网络复杂性不佳的情况下如何预测社区对摄动的反应

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摘要

Recent attempts to predict the response of large food webs to perturbations have revealed that in larger systems increasingly precise information on the elements of the system is required. Thus, the effort needed for good predictions grows quickly with the system's complexity. Here, we show that not all elements need to be measured equally well, suggesting that a more efficient allocation of effort is possible. We develop an iterative technique for determining an efficient measurement strategy. In model food webs, we find that it is most important to precisely measure the mortality and predation rates of long-lived, generalist, top predators. Prioritizing the study of such species will make it easier to understand the response of complex food webs to perturbations.
机译:预测大型食物网对扰动响应的最新尝试表明,在较大的系统中,越来越需要有关系统元素的精确信息。因此,随着系统的复杂性,良好预测所需的工作量迅速增加。在这里,我们表明并非所有要素都需要得到同样良好的衡量,这表明可以更有效地分配工作量。我们开发了一种迭代技术来确定有效的测量策略。在模型食物网中,我们发现精确测量长寿,通才,顶级捕食者的死亡率和捕食率至关重要。优先研究此类物种将使人们更容易理解复杂食物网对扰动的响应。

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