Geographically variable biotic interactions and implications for species ranges

Abstract The challenge Understanding how biotic interactions affect species’ geographical ranges, biodiversity patterns and ecological responses to environmental change is one of the most pressing challenges in macroecology. Extensive efforts are underway to detect signals of biotic interactions in macroecological data. However, efforts are limited by bias in the taxa and spatial scale for which occurrence data are available and by difficulty in ascribing causality to co‐occurrence patterns. Moreover, we are not necessarily looking in the right places; analyses are largely ad hoc, depending on availability of data, rather than focusing on regions, taxa, ecosystems or interaction types where biotic interactions might affect species’ geographical ranges most strongly. Unpicking biotic interactions We suggest that macroecology would benefit from the recognition that abiotic conditions alter two key components of biotic interaction strength: frequency and intensity. We outline how and why variation in biotic interaction strength occurs, explore the implications for species’ geographical ranges and discuss the challenges inherent in quantifying these effects. In addition, we explore the role of behavioural flexibility in mediating biotic interactions potentially to mitigate impacts of environmental change. New data We argue that macroecology should take advantage of “independent” data on the strength of biotic interactions measured by other disciplines, in order to capture a far wider array of taxa, locations and interaction types than are typically studied in macroecology. Data on biotic interactions are readily available from community, disease, microbial and parasite ecology, evolution, palaeontology, invasion biology and agriculture, but most are yet to be exploited within macroecology. Integrating biotic interaction strength data into macroecology Harmonization of data across interdisciplinary sources, taxa and interaction types could be achieved by breaking down interactions into elements that contribute to frequency and intensity. This would allow quantitative biotic interaction data to be incorporated directly into models of species distributions and macroecological patterns.