Unit of Ecology and Evolution, University of Fribourg, 1700 Fribourg, Switzerland.
Am Nat. 2010 Aug;176(2):170-7. doi: 10.1086/653667.
Several stochastic models have tried to capture the architecture of food webs. This approach is interesting, but it is limited by the fact that different assumptions can yield similar results. To overcome this limitation, we develop a purely statistical approach. Body size in terms of an optimal ratio between prey and predator is used as explanatory variable. In 12 observed food webs, this model predicts, on average, 20% of interactions. To analyze the unexplained part, we introduce a latent term: each species is described by two latent traits, foraging and vulnerability, that represent nonmeasured characteristics of species once the optimal body size has been accounted for. The model now correctly predicts an average of 73% of links. The key features of our approach are that latent traits quantify the structure that is left unexplained by the explanatory variable and that this quantification allows a test of whether independent biological information, such as microhabitat use, camouflage, or phylogeny, explains this structure. We illustrate this method with phylogeny and find that it is linked to one or both latent traits in nine of 12 food webs. Our approach opens the door to the formulation of more complex models that can be applied to any kind of biological network.
已有一些随机模型试图捕捉食物网的结构。这种方法很有趣，但受到不同假设可能产生相似结果的限制。为了克服这个限制，我们开发了一种纯粹的统计方法。以猎物和捕食者之间最佳比例表示的身体大小被用作解释变量。在 12 个观察到的食物网中，该模型平均预测了 20%的相互作用。为了分析未解释的部分，我们引入了一个潜在项：每个物种由两个潜在特征来描述，觅食和易感性，这代表了在考虑最佳体型后物种未被测量的特征。该模型现在平均正确预测了 73%的链接。我们方法的关键特征是，潜在特征量化了解释变量未解释的结构，并且这种量化允许测试独立的生物信息（如微生境利用、伪装或系统发育）是否解释了这种结构。我们用系统发育来举例说明这种方法，并发现它在 12 个食物网中的 9 个中与一个或两个潜在特征相关。我们的方法为制定更复杂的模型打开了大门，这些模型可以应用于任何类型的生物网络。
