Movement upscaled: From behavioural responses to population dynamics of interacting animals species

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Interspecific interactions between animals, such as competition, predation, and mutualism, are key to their local population and community dynamics. At the community level, which is pertinent to species distributions, biodiversity patterns, and conservation, interactions are typically considered aggregated as effects of species’ densities on each other. However, interactions occur first and foremost at the individual level and through behaviour. To understand population dynamics fully and to build effective predictive models, we must synergize the two perspectives. At the individual level, we can study interactions between animal species in their natural habitats by recording their movements, deciphering their dynamic spatiotemporal responses to each other, and relating these to space and habitat use and fitness components. While such considerations have already improved our understanding of predator-prey interactions, they are rare for ecologically similar species. This is surprising given a wide interest in the mechanisms that facilitate species coexistence and the potential relevance of fine-scale interspecific responses for avoidance of exploitation and interference competition or facilitation through interspecific information transfer. Most likely, the scarcity of such studies hinges on a combination of challenges related to data collection, data analysis, and the process of upscaling, and it limits our ability to quantify and understand competition at the community level. The proposed project will overcome these challenges by (i) developing new statistical methodology for quantifying fine-scale interactions based on movement data, (ii) analyzing a unique data set on interactive movements of two ecologically similar songbird species as model species in relation to fitness components, and (iii) investigating the consequences of fine-scale interactions at the community level and their relevance for aggregated density-based formulations of species interactions through individual-based modelling.