Integrating resource memory and cue-based territoriality to simulate movement dynamics: a process-explicit and pattern-oriented approach

Meryl Theng, Thomas A.A. Prowse, Steven Delean, Phillip Cassey and Chloe Bracis

Ecological Modelling, 2024, vol. 487, issue C

Abstract: Animal movement is central to ecology and of paramount importance to understand processes underlying the emergence of empirical space-use patterns. In this study, we investigated how integrating two well-established movement processes in the field of theoretical movement ecology, (i) memory-based resource use; and (ii) cue- or scent-based territoriality, affects emergent space-use patterns. We integrated the two mechanisms of space-use into a single individual-based modelling framework, and then quantified how varying degrees of each process affects emergent space-use patterns. Both mechanisms together led to the formation of exclusive, resource- and population density-dependent utilisation distributions, which were responsive to perturbations in the conspecific environment (i.e., removing individuals). Utilisation distribution patterns (area and overlap) were primarily influenced by memory and scent decay rate parameters, controlling an animal's inherent exploratory tendency and its desire to avoid conspecifics respectively. Model application to a population of feral cats demonstrated that general space-use measures (e.g., median UD area, resident and transient dynamics) could be approximated through simulation, though replication of finer-scale space use patterns (e.g., cumulative UD area) was poorly matched. Though application of mechanistic movement models remains both challenging and limited, the potential of such endeavours to ultimately predict population response cannot be overstated.

Keywords: Movement ecology; Animal space use; Individual-based models; Mechanistic model; Mechanistic (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:487:y:2024:i:c:s0304380023002909

DOI: 10.1016/j.ecolmodel.2023.110560

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