Open problems in PDE models for knowledge-based animal movement via nonlocal perception and cognitive mapping

TL;DR

This paper reviews PDE models incorporating cognition in animal movement, emphasizing nonlocal perception and cognitive mapping, and discusses mathematical challenges and biological implications for understanding movement behaviors.

Contribution

It synthesizes existing models that include cognitive processes in animal movement and highlights open problems and challenges in developing more accurate models.

Findings

Nonlocal PDE models effectively incorporate perception and memory.

Mathematical techniques and measures of success are discussed for model evaluation.

Numerous open problems bridge mathematics and ecology in cognitive animal movement modeling.

Abstract

The inclusion of cognitive processes, such as perception, learning and memory, are inevitable in mechanistic animal movement modelling. Cognition is the unique feature that distinguishes animal movement from mere particle movement in chemistry or physics. Hence, it is essential to incorporate such knowledge-based processes into animal movement models. Here, we summarize popular deterministic mathematical models derived from first principles that begin to incorporate such influences on movement behaviour mechanisms. Most generally, these models take the form of nonlocal reaction-diffusion-advection equations, where the nonlocality may appear in the spatial domain, the temporal domain, or both. Mathematical rules of thumb are provided to judge the model rationality, to aid in model development or interpretation, and to streamline an understanding of the range of difficulty in possible model conceptions. To emphasize the importance of biological conclusions drawn from these models, we briefly present available mathematical techniques and introduce some existing "measures of success" to compare and contrast the possible predictions and outcomes. Throughout the review, we propose numerous open problems relevant to this relatively new area, ranging from precise technical mathematical challenges to broader conceptual challenges at the cross-section between mathematics and ecology. This review paper is expected to act as a synthesis of existing efforts while also pushing the boundaries of current modelling perspectives to better understand the influence of cognitive movement mechanisms on movement behaviours and space use outcomes.