Abstract
Locusts are short horned grasshoppers that exhibit two behaviour types depending on their local population density. These are: solitarious, where they will actively avoid other locusts, and gregarious where they will seek them out. It is in this gregarious state that locusts can form massive and destructive flying swarms or plagues. However, these swarms are usually preceded by the aggregation of juvenile wingless locust nymphs. In this paper we attempt to understand how the distribution of food resources affect the group formation process. We do this by introducing a multi-population partial differential equation model that includes non-local locust interactions, local locust and food interactions, and gregarisation. Our results suggest that, food acts to increase the maximum density of locust groups, lowers the percentage of the population that needs to be gregarious for group formation, and decreases both the required density of locusts and time for group formation around an optimal food width. Finally, by looking at foraging efficiency within the numerical experiments we find that there exists a foraging advantage to being gregarious.
Original language | English |
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Article number | e1008353 |
Journal | Plos Computational Biology |
Volume | 17 |
Issue number | 7 |
DOIs | |
Publication status | Published - 7 Jul 2021 |
Bibliographical note
Funding Information:JEFG received support from the School of Mathematical Sciences and the Faculty of Engineering, Computer and Mathematical Sciences, University of Adelaide through the Special Studies Programme between January-July 2019 (during which time this work was initiated). FG and NT were supported by the University of Newcastle, Australia, via a RTP PhD scholarship and start-up support respectively. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2021 Georgiou et al.
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Modelling and Simulation
- Ecology
- Molecular Biology
- Genetics
- Cellular and Molecular Neuroscience
- Computational Theory and Mathematics