Including population and environmental dynamic heterogeneities in continuum models of collective behaviour with applications to locust foraging and group structure

Fillipe Georgiou, Camille Buhl, J. E.F. Green, Bishnu Lamichhane, Ngamta Thamwattana

Research output: Contribution to journalArticlepeer-review

Abstract

Collective behaviour occurs at all levels of the natural world, from cells aggregating to form tissues, to locusts interacting to form large and destructive plagues. These complex behaviours arise from relatively simple interactions amongst individuals and between individuals and their environment. For simplicity, mathematical models of these phenomena often assume that the population is homogeneous. However, population heterogeneity arising due to the internal state of individuals can affect these interactions and thus plays a role in the dynamics of group formation. In this paper, we present a partial differential equation model that accounts for this heterogeneity by introducing a state space that models an individual’s internal state (e.g. age, level of hunger) which affects its movement characteristics. We then apply the model to a concrete example of locust foraging to investigate the dynamic interplay of food availability, hunger, and degree of gregarisation (level of sociability) on locust group formation and structure. We find that including hunger lowers group density and raises the percentage of the population that needs to be gregarious for group formation. Within the group structure itself we find that the most gregarious and satiated locusts tend to be located towards the centre with hunger driving locusts towards the edges of the group. These two effects may combine to give a simple mechanism for locust group dispersal, in that hunger lowers the group density, which in turn lowers the gregarisation, further lowering density and creating a feedback loop. We also note that a previously found optimal food patch size for group formation may be driven by hunger. In addition to our locust results, we provide more general results and methods in the attached appendices.

Original languageEnglish
Article numbere1011469
JournalPlos Computational Biology
Volume21
Issue number4
DOIs
Publication statusPublished - 15 Apr 2025

Data Availability Statement

All relevant data and code are within the manuscript, Supporting Information files, Zenodo (DOI: 10.5281/zenodo.11613736) and a linked gitlab repository.

Funding

FG received a Lift-Off Fellowship from the Australian Mathematical Sciences Institute for this work (https://austms.org.au/award-and-grant/lift-off-fellowships/). All other authors received no specific funding for this work. The publication fee was covered under The University of Bath PLOS Flat Fee Arrangement (https://library.bath.ac.uk/open-access/publishing-deals)

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Modelling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

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