Dynamic models in behavioural and evolutionary ecology

Houston, Alasdair I.; Clark, Colin; McNamara, John M.; Mangel, Marc

doi:10.1038/332029a0

Cited by 330 publications

(196 citation statements)

References 25 publications

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“…A strategy is a rule for choosing between the actions available to a parent during the provisioning period based on its state and that of its offspring. Because the fitness consequences of an action depend on future actions, we solve for the optimal strategy numerically, using dynamic programming (Houston et al 1988;. We express all results as the proportion of time spent in a given state (for mortality rates and mean state values) or performing a particular action, as determined by direct computation.…”

Section: The Modelsmentioning

confidence: 99%

“…Throughout, we also assume that offspring are much more sensitive to variation in the time between feeding events than the parent; they can store fewer reserves and their metabolic demands use up a greater proportion of energetic input, which increases as they grow. Using dynamic programming (Houston et al 1988;, we find the policies that maximize the mothers' expected fitness as a function of their state, and that of their offspring, at the end of a provisioning period. We contrast the effects of energetic risk on optimal provisioning effort under regurgitation and lactation, and the consequent mortality rates of offspring (and mothers), along with their condition at independence.…”

Section: Introductionmentioning

confidence: 99%

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Evolution of mammals: lactation helps mothers to cope with unreliable food supplies

Dall

Boyd

2004

Proc. R. Soc. Lond. B

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Lactation is a ubiquitous feature of mammalian reproduction. Because lactating females can draw on their nutrient reserves for milk production, it offers mothers and their dependent young independence from fluctuations in their food supplies. However, converting food to reserves and milk is relatively inefficient at delivering nutrients to offspring. We use dynamic programming to contrast the performance of mothers that provision dependent, refuge-bound offspring optimally from their nutrient reserves with otherwise equivalent mothers that do so directly from the food they find. In this way, we demonstrate formally that the selective advantage to lactating mothers, who can provision-at a cost-without having found food recently, can be substantial with uncertain food supplies and few opportunities for future reproduction under a wide range of circumstances. Hence, it is likely that unreliability associated with the lifestyles of the small, primitive mammal-like reptiles that evolved extended maternal care, selected for fully-developed milk production and consumption, prompting the evolution of true mammals. Moreover, this work suggests that selection for coping with unreliable food access during provisioning may underlie key life-history differences between birds and mammals because the mass constraints imposed by flight restrict the level of reserves that mothers can carry and provision from.

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Section: The Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evolution of mammals: lactation helps mothers to cope with unreliable food supplies

Dall

Boyd

2004

Proc. R. Soc. Lond. B

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“…Dynamic state variable (DSV) models provide a framework in which multiple states and therefore rate processes can be simultaneously incorporated (Houston et al 1988). In this manner, predictions can be made about the behavioural routines that best compromise between competing physiological and/or environmental processes at multiple timescales.…”

Section: Introductionmentioning

confidence: 99%

Interactions between rate processes with different timescales explain counterintuitive foraging patterns of arctic wintering eiders

2010

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To maximize fitness, animals must respond to a variety of processes that operate at different rates or timescales. Appropriate decisions could therefore involve complex interactions among these processes. For example, eiders wintering in the arctic sea ice must consider locomotion and physiology of diving for benthic invertebrates, digestive processing rate and a nonlinear decrease in profitability of diving as currents increase over the tidal cycle. Using a multi-scale dynamic modelling approach and continuous field observations of individuals, we demonstrate that the strategy that maximizes long-term energy gain involves resting during the most profitable foraging period (slack currents). These counterintuitive foraging patterns are an adaptive trade-off between multiple overlapping rate processes and cannot be explained by classical rate-maximizing optimization theory, which only considers a single timescale and predicts a constant rate of foraging. By reducing foraging and instead digesting during slack currents, eiders structure their activity in order to maximize long-term energetic gain over an entire tide cycle. This study reveals how counterintuitive patterns and a complex functional response can result from a simple trade-off among several overlapping rate processes, emphasizing the necessity of a multi-scale approach for understanding adaptive routines in the wild and evaluating mechanisms in ecological time series.

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“…Hereby, suboptimal solutions are omitted during the search as illustrated in Houston et al (1988). In the context of optimal annual routine modelling, the terminal reward V(X T ) is assumed to equal one for all possible states.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…In mathematical biology, game theoretic approaches help to understand complex decision-making processes that lead to the maximization of fitness and the evolution of optimal strategies (Houston et al 1988, Parker and Smith 1990, McNamara et al 2001. Notably, stochastic dynamic programming (SDP) can be applied, which is a well-known method for solving multi-stage decision problems (Parker andSmith 1990, Bertsekas 2005).…”

Section: Introductionmentioning

confidence: 99%

sOAR: a tool for modelling optimal animal life‐history strategies in cyclic environments

et al. 2017

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Periodic environments determine the life cycle of many animals across the globe and the timing of important life history events, such as reproduction and migration. These adaptive behavioural strategies are complex and can only be fully understood (and predicted) within the framework of natural selection in which species adopt evolutionary stable strategies. We present sOAR, a powerful and user-friendly implementation of the well-established framework of optimal annual routine modelling. It allows determining optimal animal life history strategies under cyclic environmental conditions using stochastic dynamic programming. It further includes the simulation of population dynamics under the optimal strategy. sOAR provides an important tool for theoretical studies on the behavioural and evolutionary ecology of animals. It is especially suited for studying bird migration. In particular, we integrated options to differentiate between costs of active and passive flight into the optimal annual routine modelling framework, as well as options to consider periodic wind conditions affecting flight energetics. We provide an illustrative example of sOAR where food supply in the wintering habitat of migratory birds significantly alters the optimal timing of migration. sOAR helps improving our understanding of how complex behaviours evolve and how behavioural decisions are constrained by internal and external factors experienced by the animal. Such knowledge is crucial for anticipating potential species' response to global environmental change.

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Dynamic models in behavioural and evolutionary ecology

Cited by 330 publications

References 25 publications

Evolution of mammals: lactation helps mothers to cope with unreliable food supplies

Evolution of mammals: lactation helps mothers to cope with unreliable food supplies

Interactions between rate processes with different timescales explain counterintuitive foraging patterns of arctic wintering eiders

sOAR: a tool for modelling optimal animal life‐history strategies in cyclic environments

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