协变量潜在相互作用模型：预测鸟类-植物相互作用中的地理和分类偏差
Covariate-informed latent interaction models: Addressing geographic & taxonomic bias in predicting bird-plant interactions
摘要：
自然栖息地的减少促使我们更好地了解物种的相互联系以及生物群落如何应对环境变化。然而，物种相互作用的生态学研究受到其地理和分类重点的限制，这可能会扭曲我们对相互作用动力学的理解。我们专注于鸟类与植物的相互作用，即潜在的水果消耗和种子传播的情况。我们开发了一种预测物种相互作用的方法，该方法解释了记录的相互作用网络中的错误，解决了现有研究的地理和分类学偏见，基于潜在因素以增加灵活性并借用跨物种的信息，以灵活的方式合并协变量以告知潜在因素，并使用来自85项单独研究的荟萃分析数据集。我们专注于232种鸟类和511种植物在大西洋森林中的相互作用，并确定5%的物种对与未记录的相互作用，但后验概率的相互作用是可能的80%以上。最后，我们开发了一个基于置换的变量重要性程序的潜在因素网络模型，并确定鸟类的身体质量和植物的果实直径是重要的，在驱动存在的物种相互作用，具有乘法关系，表现出阈值和匹配行为。
英文摘要：
Reductions in natural habitats urge that we better understand species' interconnection and how biological communities respond to environmental changes. However, ecological studies of species' interactions are limited by their geographic and taxonomic focus which can distort our understanding of interaction dynamics. We focus on bird-plant interactions that refer to situations of potential fruit consumption and seed dispersal. We develop an approach for predicting species' interactions that accounts for errors in the recorded interaction networks, addresses the geographic and taxonomic biases of existing studies, is based on latent factors to increase flexibility and borrow information across species, incorporates covariates in a flexible manner to inform the latent factors, and uses a meta-analysis data set from 85 individual studies. We focus on interactions among 232 birds and 511 plants in the Atlantic Forest, and identify 5% of pairs of species with an unrecorded interaction, but posterior probability that the interaction is possible over 80%. Finally, we develop a permutation-based variable importance procedure for latent factor network models and identify that a bird's body mass and a plant's fruit diameter are important in driving the presence of species interactions, with a multiplicative relationship that exhibits both a thresholding and a matching behavior.
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