Dynamic State Variable Models in Ecology

By C. Clark, Marc Mangel. 2000

292 citations recorded by the source corpus.

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Citations in the corpus

Optimal patch time allocation for time-limited foragers (2006, background): “Stochastic dynamic programming models are widely used in behavioural ecology to find optimal behavioural strate- gies, taking into account dynamically the state of the foraging animals (McNamara and Houston 1986; Houston et al. 1988; Clark and Mangel 2000).”
Mate choice in the face of costly competition (2003, methodology): “Our model took the form of a dynamic game (Clark and Mangel, 2000; Houston and McNamara, 1999; Mangel and Clark, 1988), in which the consequences of an individual’s actions depend critically on the behavior of others.”
The evolution of alternative strategies and tactics (2001, methodology): “the dynamic modeling approach (Mangel and Clark, 1988; Houston and McNamara, 1999; Clark and Mangel, 2000), we have the tools to put together realistic models that allow us to make specific predictions.”
The logic of skipped spawning in fish (2006, methodology): “In principle, the decision rule is simple: if an individual skips spawning, the loss in fecundity this year has to be outweighed by the chances of increased egg production in the future, discounted by the survival probability up to that point (Houston and McNamara 1999; Clark and Mangel 2000; Roff 2”
Concepts from complex adaptive systems as a framework for individual-based modelling (2001, methodology): “The UFT and related methods described by Mangel and Clark (1986), Clark and Mangel (2000) assume that animals select among known foraging habitats to maximize their expected fitness over some future time period, a process that requires overt prediction.”
Tests of Theory for Diel Variation in Salmonid Feeding Activity and Habitat Use (2005, methodology): “…predictive, fitnessmaximization approach to decision-making (Railsback et al. 1999), which modifies the dynamic state variable theory (Houston and McNamara 1999, Clark and Mangel 2000) by assuming animals use simple predictions to estimate their potential fitness over a future time horizon.”
The Theoretical Biologist's Toolbox: Quantitative Methods for Ecology and Evolutionary Biology (2006, background): “Colin Clark and I talk about this a bit in our book (Clark and Mangel 2000).”
Effects of Partial Sugar Deprivation on Lifespan and Carbohydrate Mobilization in the Parasitoid Macrocentrus grandii (Hymenoptera: Braconidae) (2001, background): “These strategies range from rapid depletion of both trehalose and glycogen (e.g., Ziegler 1991) to homeostatic regulation of trehalose levels mediated by the breakdown of glycogen ( Chapman 1998 ).”
Time allocation strategies in insect parasitoids: from ultimate predictions to proximate behavioral mechanisms (2006, background): “On the contrary to the static MVT, their aim is to find optimal behavioral strategies, taking into account the state of the foraging females (McNamara and Houston 1986; Houston et al. 1988; Clark and Mangel 2000).”
Death and danger at migratory stopovers: problems with “predation risk” (2003, background): “to explore the differential fitness of making or not making escape-performance-dependent conditional decisions in different ecological situations, Clark and Mangel 2003 ).”
Lifetime nutrient dynamics reveal simultaneous capital and income breeding in a parasitoid (2005, background): “Key words: host-feeding; host–parasitoid dynamics; income and capital breeding; life history strategies; lipids; nutrient acquisition; nutrient allocation; nutrient dynamics; parasitoids; population dynamics.”
Benefits and costs of parental care (2012, background): “In fact, Clutton-Brock’s (1991) seminal book did not address the mechanistic bases of parental care and most work in this field has been conducted over the last 20 years.”
The adaptive value of energy storage and capital breeding in seasonal environments (2009, background): “dynamic programming (Houston and McNamara 1999, Clark and Mangel 2000 ).”
Assessment of hypotheses about dispersal in a long-lived seabird using multistate capture–recapture models (2004, background): “depend on the individual state, such as condition, previous breeding success, breeding habitat and other environmental factors; Mangel & Clark 1988; McNamara & Houston 1996; Danchin et al . 1998; Clark & Mangel 2000 ).”
Early is better: seasonal egg fitness and timing of reproduction in a zooplankton life‐history model (2007, methodology): “The model finds optimal energy allocation and timing of diapause based on maximization of reproductive value by dynamic programming (Eq. A7; Houston and McNamara 1999, Clark and Mangel 2000 ).”
The behavioural ecology of personality: consistent individual differences from an adaptive perspective (2004, background): “These issues can be explored using dynamic state variable models, which have proven useful in understanding the tradeoffs involved with energy reserve management in general, including the influences of food supply, metabolic costs, predation risk and social interactions (see Houston & McNamara 1999;”
Assessing the robustness and optimality of alternative decision rules with varying assumptions (2002, unknown): “I use a dynamic state variable model ( Clark & Mangel 2000 ) to find optimal thresholds.”