AUTHOR=White Cian D. , Collier Marcus J. , Stout Jane C. TITLE=Anthropogenic Induced Beta Diversity in Plant–Pollinator Networks: Dissimilarity, Turnover, and Predictive Power JOURNAL=Frontiers in Ecology and Evolution VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/ecology-and-evolution/articles/10.3389/fevo.2022.806615 DOI=10.3389/fevo.2022.806615 ISSN=2296-701X ABSTRACT=

Biogeography has traditionally focused on the distribution of species, while community ecology has sought to explain the patterns of community composition. Species interactions networks have rarely been subjected to such analyses, as modeling tools have only recently been developed for interaction networks. Here, we examine beta diversity of ecological networks using pollination networks sampled along an urbanization and agricultural intensification gradient in east Leinster, Ireland. We show, for the first time, that anthropogenic gradients structure interaction networks, and exert greater structuring force than geographical proximity. We further showed that species turnover, especially of plants, is the major driver of interaction turnover, and that this contribution increased with anthropogenic induced environmental dissimilarity, but not spatial distance. Finally, to explore the extent to which it is possible to predict each of the components of interaction turnover, we compared the predictive performance of models that included site characteristics and interaction properties to models that contained species level effects. We show that if we are to accurately predict interaction turnover, data are required on the species-specific responses to environmental gradients. This study highlights the importance of anthropogenic disturbances when considering the biogeography of interaction networks, especially in human dominated landscapes where geographical effects can be secondary sources of variation. Yet, to build a predictive science of the biogeography of interaction networks, further species-specific responses need to be incorporated into interaction distribution modeling approaches.