The role of habitat configuration in shaping animal population processes: a framework to generate quantitative predictions

Abstract

By shaping where individuals move, habitat configuration can fundamentally structure animal populations. Yet, we currently lack a framework for generating quantitative predictions about the role of habitat configuration in modulating population outcomes. For example, it is well known that the social structure of animal populations can shape spreading dynamics, but it remains underexplored to what extent such dynamics are determined by the underlying habitat configuration. To address this gap, we propose a framework and model inspired by studies using networks to characterize habitat connectivity. We first define animal habitat networks, explain how they can integrate information about the different configurational features of animals habitats, and highlight the need for a bottom-up generative model that can depict realistic variations in habitat structural connectivity. Second, we describe a model for simulating animal habitat networks (available in the R package AnimalHabitatNetwork), and demonstrate its ability to generate alternative habitat configurations based on empirical data, which forms the basis for exploring the consequences of alternative habitat structures. Finally, we use our framework to demonstrate how transmission properties, such as the spread of a pathogen, can be impacted by both local connectivity and landscape-level characteristics of the habitat. Our study highlights the importance of considering the underlying habitat configuration in studies linking social structure with population-level outcomes.