Department of Ecology & Evolution, Computation Institute, University of Chicago, 1101 E. 57th Chicago, IL 60637, USA.
J Theor Biol. 2011 Jun 21;279(1):161-8. doi: 10.1016/j.jtbi.2010.06.040. Epub 2010 Jul 13.
Few food web theory hypotheses/predictions can be readily tested using likelihoods of reproducing the data. Simple probabilistic models for food web structure, however, are an exception as their likelihoods were recently derived. Here I test the performance of a more complex model for food web structure that is grounded in the allometric scaling of interactions with body size and the theory of optimal foraging (Allometric Diet Breadth Model-ADBM). This deterministic model has been evaluated by measuring the fraction of trophic relations it correctly predicts. I contrasted this value with that produced by simpler models based on body sizes and found that the quantitative information on allometric scaling and optimal foraging does not significantly increase model fit. Also, I present a method to compute the p-value for the fraction of trophic interactions correctly predicted by the ADBM, or any other model, with respect to three probabilistic models. I find that the ADBM predicts significantly more links than random graphs, but other models can outperform it. Although optimal foraging and allometric scaling may improve our understanding of food webs, the ADBM needs to be modified or replaced to find support in the data.
很少有食物网理论假说/预测可以通过重现数据的可能性来轻易验证。然而，简单的食物网结构概率模型是一个例外，因为它们的可能性最近已经被推导出来。在这里，我测试了一个更复杂的食物网结构模型的性能，该模型基于与体型的相互作用的比例关系和最优觅食理论（比例饮食广度模型-ADBM）。这个确定性模型已经通过测量它正确预测的营养关系的分数来进行评估。我将这个值与基于体型的更简单模型产生的值进行了对比，发现关于比例关系和最优觅食的定量信息并没有显著增加模型拟合度。此外，我提出了一种方法，用于计算 ADBM 或任何其他模型正确预测的营养关系分数相对于三个概率模型的 p 值。我发现 ADBM 预测的链接数量显著多于随机图，但其他模型也可以表现更好。虽然最优觅食和比例关系可能会提高我们对食物网的理解，但 ADBM 需要进行修改或替换，才能在数据中得到支持。
