Models of Adaptive Behaviour: An Approach based on State

By P. Bednekoff. 2000

320 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/46c7bb6ed8f532f6e5a52dd08be2a4ee9af1e567

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Citations in the corpus

How noisy information and individual asymmetries can make ‘personality’ an adaptation : a simple model (2006, methodology): “We use state here in the same sense as Houston & McNamara (1999) to refer to any aspect of the individual that can be measured and is needed to understand the strategic options, payoffs and dynamics of behaviour (a state variable).”
Natural mortality: Its ecology, how it shapes fish life histories, and why it may be increased by fishing☆ (2013, methodology): “Weuse optimization by dynamic programming (Clark andMangel, 2000; Houston and McNamara, 1999) to find optimal strategies for energy allocation and the growth strategy.”
Mass-dependent energetics and survival in Harbour Seal pups (2005, background): “Such predictions of optimal strategies can be investigated using state-dependent dynamic models ( Houston & McNamara 1999; Noren & Mangel 2004).”
Covariation between personalities and individual differences in coping with stress: Converging evidence and hypotheses (2010, background): “Stochastic influences on development are many and varied and will often favour alternative actions for individuals in different states (Houston and McNamara, 1999).”
The timing of birds' breeding seasons: a review of experiments that manipulated timing of breeding (2008, background): “For birds and other organisms living in seasonal environments, the timing (laying date) and intensity of reproduction (clutch size) are two key decisions in the annual cycle in the sense that these traits are often strongly associated with fitness (Daan & Tinbergen 1997; Houston & McNamara 1999).”
A strategic taxonomy of biological communication (2005, unknown): “Developments in evolutionary modelling beyond the scope of this paper (see e.g. Eshel 1996; Geritz et al. 1998; Houston & McNamara 1999) have increased and modified our understanding of evolutionary stability.”
Studying personality variation in invertebrates: why bother? (2014, background): “Most of the proposed hypotheses assume that differences in states (e.g. variation in morphology, physiology, experience or neurobiology; sensu Houston & McNamara, 1999) coupled with state-dependent behaviour mediate adaptive personality differences (reviewed in Dingemanse &Wolf, 2010).”
The evolution of prudent choice (2005, methodology): “Our model also automatically takes into account the numerical dynamics at the population level, and is thus self-consistent (Houston and McNamara, 1999).”
Mate choice in the face of costly competition (2003, methodology): “Starting from an arbitrarily chosen population strategy, we identified the ESS by a process of iteration (for an outline of this method, see Houston and McNamara, 1999).”
Models of pace-of-life syndromes (POLS): a systematic review (2018, background): “Both use stochastic dynamic programming (Mangel and Clark 1988; Houston and McNamara 1999) to model risk-taking (specifically, a trait that increases resource acquisition at the expense of increased probability of mortality) as a function of residual reproductive value (RRV), where RRV represents…”
FUNCTIONAL RESPONSES WITH PREDATOR INTERFERENCE: VIABLE ALTERNATIVES TO THE HOLLING TYPE II MODEL (2001, background): “However, given a large empirical and theoretical literature addressing changes in prey behavior across predator abundances (Lima 1998, Houston and McNamara 1999), prey behavior almost surely contributes to the phenomenon of predator dependence in some of the 19 data sets and in many other…”
State-dependent Energy Allocation in Cod (Gadus Morhua) (2006, unknown): “104 Structure 105 The modelling approach in this paper uses dynamic programming to find optimal 106 allocation strategies (Houston and McNamara 1999; Clark and Mangel 2000).”
A framework for the study of genetic variation in migratory behaviour (2006, unknown): “In annual routine models, the optimum scheduling and effort of birds are derived by using dynamic optimisation models (Holmgren and Hedenström 1995; Houston and McNamara 1999).”
Toward an ecological synthesis: a case for habitat selection (2003, background): “Fretwell 1972), interspecific interactions (Rosenzweig 1974, 1979, 1981; Morris 1988, 1989, 1999a; Danielson 1992), resource distributions (Pulliam and Caraco 1974; Sutherland 1983; Fagen 1987; Morris 1994; Morris and Knight 1996; Morris and Davidson 2000), spatial scale (Pulliam 1988; Pulliam and D”
Capital or income breeding? A theoretical model of female reproductive strategies (2007, background): “Decisions regarding offspring condition and the speed at which offspring reserves should be increased can only properly be viewed in light of optimization over a full annual routine (e.g., Houston and McNamara 1999 ).”
Evolutionary Dynamics of Biological Games (2004, background): “Evolutionarily stable strategies (ESSs) were introduced to discuss the prevalence of ritual fighting in interspecific animal conflicts, which also led to asymmetric and multistep games ( 7 , 14 ).”
The logic of skipped spawning in fish (2006, unknown): “In principle, the decision rule is simple: if an 264 individual skips spawning, the loss in fecundity this year has to be outweighed by the chances 265 of increased egg production in the future, discounted by the survival probability up to that 266 point (Houston and McNamara 1999; Clark and Mangel ”