Data from: Context-dependency and anthropogenic effects on individual plant-frugivore networks

Anthropogenic activities, such as grazing by domestic animals, are considered drivers of environmental changes that may influence the structure of interaction networks. The study of individual-based networks allows testing how species-level interaction patterns emerge from the pooled interaction modes of individuals within populations. Exponential random graph models (ERGMs) examine the global structure of networks by allowing the inclusion of specific node (i.e. interacting partners) properties as explanatory covariates. Here we assessed the structure of individual plant-frugivore interaction networks and the ecological variables that influence the mode of interactions under different land-use (grazed vs ungrazed protected areas). We quantified the number of visits, the number of fruits removed per visit and the interaction strength of mammal frugivore species at each individual tree. Additionally we quantified ecological variables at the individual, microhabitat, neighborhood and habitat scales that generated interaction network structure under the different land uses. Individual plant-frugivore networks were significantly modular in both land uses but the number of modules was higher in the grazed areas. We found interaction networks for grazed and ungrazed lands were structured by phenotypic traits of individual trees, by the microhabitat beneath the tree canopy and were affected by habitat modifications of anthropogenic origin. The neighborhood surrounding each individual plant influenced plant-frugivore interactions only at the grazed-land trees. We conclude that anthropogenic land uses influence the topological patterns of plant-frugivore networks and the frugivore visitation to trees through modification of both habitat complexity and the ecological traits underlying interactions between individual plants and frugivore species.人为活动（如家畜放牧）被视为环境变化的驱动因素之一，这类变化可能会影响交互网络的结构。基于个体的交互网络研究，可用于检验物种类群水平的交互模式如何由种群内个体的聚合交互模式衍生而来。指数随机图模型（Exponential random graph models, ERGMs）通过将特定节点（即交互伙伴）的属性作为解释性协变量纳入模型，得以分析网络的全局结构。本研究评估了不同土地利用方式（放牧区与未放牧保护区）下的植物-果食性动物个体交互网络结构，以及影响交互模式的生态变量。我们量化了每棵个体树木上，哺乳动物果食性动物的访食次数、单次访食移除的果实数量，以及交互强度。此外，我们还量化了个体、微生境、邻域以及生境尺度下的生态变量，这些变量塑造了不同土地利用方式下的交互网络结构。两种土地利用方式下的植物-果食性动物个体交互网络均呈现显著的模块化结构，但放牧区的模块数量更多。研究发现，放牧与未放牧样地的交互网络结构，均受个体树木的表型性状、冠层下方微生境的影响，同时也受到人为活动导致的生境改造的作用。仅在放牧区的树木中，单株植物周围的邻域环境才会对植物-果食性动物交互产生影响。本研究结论表明，人为土地利用活动可通过改变生境复杂性，以及植物与果食性动物个体间交互背后的生态性状，进而影响植物-果食性动物交互网络的拓扑模式，以及果食性动物对树木的访食行为。