How to predict community responses to perturbations in the face of imperfect knowledge and network complexity
How to predict community responses to perturbations in the face of imperfect knowledge and network complexity
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DOI：
10.1098/rspb.2013.2355
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发表时间：
2013-12-22
影响因子：
4.7
通讯作者：
Lafferty, Kevin D.
中科院分区：
文献类型：
--
作者：
Aufderheide, Helge;Rudolf, Lars;Lafferty, Kevin D.
最近试图预测大型食物网对扰动的反应表明，在更大的系统中，需要越来越精确的系统元素信息。因此，良好预测所需的工作量随着系统的复杂性而迅速增长。在这里，我们表明，并不是所有的元素都需要同样好地衡量，这表明更有效地分配努力是可能的。我们开发了一种迭代技术，以确定一个有效的测量策略。在模型食物网中，我们发现，它是最重要的是精确测量的死亡率和捕食率的长寿，多面手，顶级捕食者。优先研究这些物种将使人们更容易理解复杂的食物网对扰动的反应。
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.