Data from: Biotic interactions in species distribution models enhance model performance and shed light on natural history of rare birds: a case study using the Straight-billed Reedhaunter (Limnoctites rectirostris)

Species distribution models (SDMs) have become a workhorse to explain, understand and predict distributions of birds. However, SDMs at broad scales are typically built using climatic variables, while ignoring the effects of biotic interactions. Although its role still remains controversial, the inclusion of biotic interactions into SDMs could confirm and/or provide new ecological insights of poorly known species. We modeled the distribution of the rare South American straight-billed reedhaunter (Limnoctites rectirostris, Furnariidae), a specialist of marshy areas linked to the spiny herb eryngo (Eryngium spp., Apiaceae), which provides the main food and nest resources. To do this, we first modeled the distribution of three eryngo species considered as the main biotic interactors (E. eburneum, E. horridum and E. pandanifolium) and included them into the straight-billed reedhaunter SDM. Second, we analyzed niche overlap between the straight-billed reedhaunter and eryngos in terms of environmental variables using dynamic range boxes, a novel approach to quantify size of n-dimensional hypervolumes. The inclusion of biotic interactions improved model performance relative to a model with climatic variables only. Climatic suitability of E. eburneum and mean temperature of wettest quarter were the most important predictors. By contrast, E horridum and E. pandanifolium resulted in poor predictors, suggesting that the straight-billed reedhaunter’s relative dependence on each eryngo species is different. The three eryngo environmental spaces largely covered the environmental space of the straight-billed reedhaunter, but the opposite was not true. Our findings suggest that biotic interactions play an important role in explaining and predicting the distribution of a rare bird at macro-scales, and that the assessment of niche overlap between interactors may confirm or improve the autoecological understanding of rare and cryptic birds. We advocate the use of an integrative modeling approach including climate and biotic interactions into SDMs to enhance ecological knowledge of poorly known bird species.物种分布模型（Species Distribution Models，SDMs）现已成为解释、认知并预测鸟类分布的核心工具。然而，大尺度下的物种分布模型通常仅基于气候变量构建，忽略了生物交互作用的影响。尽管其作用仍存在争议，但将生物交互作用纳入物种分布模型，可为认知不足的物种提供新的生态学视角，或验证已有认知。本研究对珍稀的南美直嘴芦鹪（Limnoctites rectirostris，灶鸟科Furnariidae）的分布进行了建模，该物种为栖息于沼泽生境的特化类群，依赖具尖刺的草本植物刺芹属（Eryngium spp.，伞形科Apiaceae），该属植物为其提供主要的食物与筑巢资源。为此，我们首先对被视为主要生物交互伙伴的三种刺芹物种（E. eburneum、E. horridum与E. pandanifolium）进行分布建模，并将其纳入直嘴芦鹪的物种分布模型中。其次，我们采用动态范围盒（dynamic range boxes）这一用于量化n维超体积大小的新方法，基于环境变量分析了直嘴芦鹪与刺芹属植物之间的生态位重叠情况。相较于仅使用气候变量的模型，纳入生物交互作用的模型性能得到了提升。E. eburneum的气候适宜度与最湿季度平均气温是最重要的预测因子。与之相反，E. horridum与E. pandanifolium的预测效果较差，这表明直嘴芦鹪对不同刺芹物种的相对依赖程度存在差异。三种刺芹的环境空间在很大程度上覆盖了直嘴芦鹪的环境空间，但反之则不成立。我们的研究结果表明，生物交互作用在大尺度下解释和预测珍稀鸟类分布方面发挥着重要作用，且对交互物种间生态位重叠的评估，可验证或加深对珍稀且隐秘性鸟类的个体生态学认知。我们倡导采用整合气候与生物交互作用的综合建模方法构建物种分布模型，以提升对认知不足鸟类物种的生态学认知水平。