Separating environmental effects from those of interspecific interactions on species distributions has always been a central objective of community ecology. Despite years of effort in analysing patterns of species co-occurrences and the developments of sophisticated tools, we are still unable to address this major objective. A key reason is that the wealth of ecological knowledge is not sufficiently harnessed in current statistical models, notably the knowledge on interspecific interactions. Here, we develop ELGRIN, a statistical model that simultaneously combines knowledge on interspecific interactions (i.e., the metanetwork), environmental data and species occurrences to tease apart their relative effects on species distributions. Instead of focusing on single effects of pairwise species interactions, which have little sense in complex communities, ELGRIN contrasts the overall effect of species interactions to that of the environment. Using various simulated and empirical data, we demonstrate the suitability of ELGRIN to address the objectives for various types of interspecific interactions like mutualism, competition and trophic interactions. We then apply the model on vertebrate trophic networks in the European Alps to map the effect of biotic interactions on species distributions.Data on ecological networks are everyday increasing and we believe the time is ripe to mobilize these data to better understand biodiversity patterns. ELGRIN provides this opportunity to unravel how interspecific interactions actually influence species distributions.

翻译：将环境效应与种间相互作用对物种分布的影响区分开来一直是群落生态学的核心目标。尽管多年来致力于分析物种共现模式并开发了复杂的工具，我们仍未能实现这一主要目标。一个关键原因在于当前统计模型未能充分利用丰富的生态学知识，尤其是关于种间相互作用的知识。在此，我们开发了ELGRIN统计模型，该模型同时整合了种间相互作用知识（即元网络）、环境数据和物种出现记录，以分离它们对物种分布的相关影响。ELGRIN不关注在复杂群落中意义有限的成对物种相互作用的单一效应，而是对比物种相互作用的整体效应与环境效应。利用多种模拟和实证数据，我们证明了ELGRIN适用于实现针对各类种间相互作用（如互利共生、竞争和营养相互作用）的目标。随后，我们将该模型应用于欧洲阿尔卑斯山脉的脊椎动物营养网络，以绘制生物相互作用对物种分布的影响。生态网络数据日益增多，我们相信，动员这些数据以更好地理解生物多样性格局的时机已成熟。ELGRIN提供了揭示种间相互作用如何实际影响物种分布的机会。