Models of kleptoparasitism on networks: the effect of population structure on food stealing behaviour
Authored by Christoforos Hadjichrysanthou, Mark Broom, Jan Rychtar
Date Published: 2018
DOI: 10.1007/s00285-017-1177-7
Sponsors:
European Union
Simons Foundation
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
The behaviour of populations consisting of animals that interact with
each other for their survival and reproduction is usually investigated
assuming homogeneity amongst the animals. However, real populations are
non-homogeneous. We focus on an established model of kleptoparasitism
and investigate whether and how much population heterogeneities can
affect the behaviour of kleptoparasitic populations. We consider a
situation where animals can either discover food items by themselves or
attempt to steal the food already discovered by other animals through
aggressive interactions. Representing the likely interactions between
animals by a network, we develop pairwise and individual-based models to
describe heterogeneities in both the population structure and other
individual characteristics, including searching and fighting abilities.
For each of the models developed we derive analytic solutions at the
steady state. The high accuracy of the solutions is shown in various
examples of populations with different degrees of heterogeneity. We
observe that highly heterogeneous structures can significantly affect
the food intake rate and therefore the fitness of animals. In
particular, the more highly connected animals engage in more conflicts,
and have a reduced food consumption rate compared to poorly connected
animals. Further, for equivalent average level of connectedness, the
average consumption rate of a population with heterogeneous structure
can be higher.
Tags
individual-based models
Evolution
Dynamics
networks
interference
Prey
Consequences
Structured populations
Predators
Stochastic-models
Kleptoparasitism
Food stealing
Pairwise models
Ideal