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Methods in Ecology and Evolution
Article . 2012 . Peer-reviewed
License: Wiley Online Library User Agreement
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Representing the acquisition and use of energy by individuals in agent‐based models of animal populations

Authors: Jacob Nabe-Nielsen; Peter Calow; Christopher J. Topping; Alice S. A. Johnston; Pernille Thorbek; Richard M. Sibly; Volker Grimm; +4 Authors

Representing the acquisition and use of energy by individuals in agent‐based models of animal populations

Abstract

SummaryAgent‐based models (ABMs) are widely used to predict how populations respond to changing environments. As the availability of food varies in space and time, individuals should have their own energy budgets, but there is no consensus as to how these should be modelled. Here, we use knowledge of physiological ecology to identify major issues confronting the modeller and to make recommendations about how energy budgets for use inABMs should be constructed.Our proposal is that modelled animals forage as necessary to supply their energy needs for maintenance, growth and reproduction. If there is sufficient energy intake, an animal allocates the energy obtained in the order: maintenance, growth, reproduction, energy storage, until its energy stores reach an optimal level. If there is a shortfall, the priorities for maintenance and growth/reproduction remain the same until reserves fall to a critical threshold below which all are allocated to maintenance. Rates of ingestion and allocation depend on body mass and temperature. We make suggestions for how each of these processes should be modelled mathematically.Mortality rates vary with body mass and temperature according to known relationships, and these can be used to obtain estimates of background mortality rate.If parameter values cannot be obtained directly, then values may provisionally be obtained by parameter borrowing, pattern‐oriented modelling, artificial evolution or from allometric equations.The development ofABMs incorporating individual energy budgets is essential for realistic modelling of populations affected by food availability. SuchABMs are already being used to guide conservation planning of nature reserves and shell fisheries, to assess environmental impacts of building proposals including wind farms and highways and to assess the effects on nontarget organisms of chemicals for the control of agricultural pests.

Country
United Kingdom
Keywords

individual-based models, Population Dynamics, energy budget, bioenergetics

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    137
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
137
Top 1%
Top 10%
Top 10%
Green
gold