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Models of kleptoparasitism on networks: the effect of population structure on food stealing behaviour

Overview of attention for article published in Journal of Mathematical Biology, September 2017
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Title
Models of kleptoparasitism on networks: the effect of population structure on food stealing behaviour
Published in
Journal of Mathematical Biology, September 2017
DOI 10.1007/s00285-017-1177-7
Pubmed ID
Authors

Christoforos Hadjichrysanthou, Mark Broom, Jan Rychtář

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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 22%
Student > Bachelor 2 22%
Student > Master 2 22%
Student > Postgraduate 1 11%
Unknown 2 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 33%
Environmental Science 2 22%
Mathematics 1 11%
Earth and Planetary Sciences 1 11%
Unknown 2 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 April 2018.
All research outputs
#20,476,619
of 23,036,991 outputs
Outputs from Journal of Mathematical Biology
#547
of 663 outputs
Outputs of similar age
#278,092
of 318,354 outputs
Outputs of similar age from Journal of Mathematical Biology
#10
of 10 outputs
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So far Altmetric has tracked 663 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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