1. The behaviour of ecological systems mainly relies on the interactions between the species it involves. We consider the problem of inferring the species interaction network from abundance data.
2. To be relevant, any network inference methodology needs to handle count data and to account for possible environmental effects. It also needs to distinguish between direct interactions and indirect associations and graphical models provide a convenient framework for this purpose.
3. A simulation study shows that the proposed methodology compares well with state‐of‐the‐art approaches, even when the underlying graph strongly differs from a tree. The analysis of two datasets highlights the influence of covariates on the inferred network.
4. Accounting for covariates is critical to avoid spurious edges. The proposed approach could be extended to perform network comparison or to look for missing species.

中文翻译：

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从丰度数据中基于树的物种相互作用网络推断

1. 生态系统的行为主要取决于它所涉及的物种之间的相互作用。我们考虑从丰度数据推断物种相互作用网络的问题。
2. 与此相关的是，任何网络推论方法都需要处理计数数据并考虑可能的环境影响。它还需要区分直接交互和间接关联，并且图形模型为此目的提供了方便的框架。
3. 仿真研究表明，即使基础图与树有很大不同，所提出的方法也可以与最新方法很好地比较。对两个数据集的分析突出了协变量对推断网络的影响。
4. 考虑协变量对于避免虚假边缘至关重要。提议的方法可以扩展为执行网络比较或寻找缺失的物种。