The capacity of highly diverse systems to prevail has proven difficult to explain. In addition to methodological issues, the inherent complexity of ecosystems and issues like multicausality, non-linearity and context-specificity make it hard to establish general and unidirectional explanations. Nevertheless, in recent years, high order interactions have been increasingly discussed as a mechanism that benefits the functioning of highly diverse ecosystems and may add to the mechanisms that explain their persistence. Until now, this idea has been explored by means of hypothetical simulated networks. Here, we test this idea using an updated and empirically documented network for a coffee agroecosystem. We identify potentially key nodes and measure network robustness in the face of node removal with and without incorporation of high order interactions. We find that the system's robustness is either increased or unaffected by the addition of high order interactions, in contrast with randomized counterparts with similar structural characteristics. We also propose a method for representing networks with high order interactions as ordinary graphs and a method for measuring their robustness.

事实证明，高度多样化的系统能够盛行的能力难以解释。除了方法论问题外，生态系统固有的复杂性以及多重因果关系、非线性和上下文特定性等问题也使得很难建立一般性和单向性的解释。然而，近年来，高阶相互作用被越来越多地讨论为一种有利于高度多样化生态系统功能的机制，并可能增加解释其持久性的机制。到目前为止，这个想法是通过假设的模拟网络来探索的。在这里，我们使用更新和经验记录的咖啡农业生态系统网络来测试这个想法。我们识别潜在的关键节点，并在节点移除的情况下测量网络鲁棒性，无论是否包含高阶交互。我们发现，与具有相似结构特征的随机对应物相比，添加高阶相互作用会增加或不影响系统的鲁棒性。我们还提出了一种将具有高阶交互的网络表示为普通图的方法以及一种测量其鲁棒性的方法。