A Comparison of Dynamic-State-Dependent Models of the Trade-Off Between Growth, Damage, and Reproduction

2011 ◽  
Vol 178 (6) ◽  
pp. 774-786 ◽  
Author(s):  
Who-Seung Lee ◽  
Neil B. Metcalfe ◽  
Pat Monaghan ◽  
Marc Mangel
Keyword(s):  
Dynamic State ◽  
Trade Off ◽  
State Dependent

scholarly journals On Uncertainty Relations and Entanglement Detection with Mutually Unbiased Measurements

2015 ◽  
Vol 22 (01) ◽  
pp. 1550005 ◽  
Author(s):  
Alexey E. Rastegin
Keyword(s):  
The State ◽  
Uncertainty Relations ◽  
Trade Off ◽  
Entropic Uncertainty Relations ◽  
Finite Dimensional ◽  
State Dependent ◽  
Entanglement Detection

We formulate some properties of a set of several mutually unbiased measurements. These properties are used for deriving entropic uncertainty relations. Applications of mutually unbiased measurements in entanglement detection are also revisited. First, we estimate from above the sum of the indices of coincidence for several mutually unbiased measurements. Further, we derive entropic uncertainty relations in terms of the Rényi and Tsallis entropies. Both the state-dependent and state-independent formulations are obtained. Using the two sets of local mutually unbiased measurements, a method of entanglement detection in bipartite finite-dimensional systems may be realized. A certain trade-off between a sensitivity of the scheme and its experimental complexity is discussed.

Guidance for Using State-and Prediction-Based Theory

2020 ◽  
pp. 93-122
Keyword(s):  
Population Level ◽  
Population Models ◽  
Dynamic State ◽  
Trade Off ◽  
State Variable

This chapter outlines the guidance on using state- and prediction-based theory (SPT) to build models of populations and communities of adaptive individuals, detailing five steps unique to SPT. The most important aspect of SPT to remember is that one is not trying to build optimal, or even necessarily accurate, models of how an organism's behavior affects its future fitness. Instead, one is trying to find simplistic models that produce realistic behavior in contexts where optimization is impossible. While SPT can be used like dynamic state variable modeling (DSVM), as a framework for thinking about and modeling how an individual makes a particular decision, its main purpose is to model adaptive trade-off decisions in individual-based population models. Thus, using SPT is part of the larger process of developing, analyzing, and applying an IBM to address population-level questions, and the five steps therefore include that process.

Games Embedded in Life

2020 ◽  
pp. 203-230
Author(s):  
John M. McNamara ◽  
Olof Leimar
Keyword(s):  
Reproductive Success ◽  
Dynamic Games ◽  
Traditional Approach ◽  
Holistic Approach ◽  
Current Situation ◽  
Lifetime Reproductive Success ◽  
Trade Off ◽  
State Dependent ◽  
Mean Lifetime ◽  
Payoff Structure

Many games focus on a part of the life of an organism. The payoff structure of the game then represents how the game affects fitness proxies such as mean lifetime reproductive success, which are concerned with the whole of the life of the organism. However, the traditional approach of specifying payoffs in advance of the analysis of the game can lead to inconsistencies because the rest of the life of an individual is not fixed but depends on what happens in the game. This chapter concerns this issue, identifying situations in which a more holistic approach is needed. A series of models illustrates links between the current situation and a lifetime perspective. When each of two parents must decide whether to care for their common young or desert, the payoff for desertion depends on the solution of the game and cannot be specified in advance. A game in which two males contest for a female illustrates the approach that must be taken if this game can be repeated at a later time. A game in which individuals must possess territories in order to breed is developed that highlights various interdependencies and, by incorporating learning, advances the understanding of owner–intruder interactions. The interdependencies in state-dependent dynamic games are also illustrated with a model in which individuals must trade off the risks of starvation and predation in a situation in which the choice of the best foraging habitat depends on the number of other animals that use that habitat.

Dynamic state-dependent modelling predicts optimal usage patterns of responsive defences

Oecologia ◽  
2009 ◽  
Vol 160 (2) ◽  
pp. 399-410 ◽  
Author(s):  
A. D. Higginson ◽  
G. D. Ruxton
Keyword(s):  
Dynamic State ◽  
State Dependent ◽  
Usage Patterns

scholarly journals Leaving safety to visit a feeding site: is it optimal to hesitate while exposed?

2017 ◽  
Vol 4 (1) ◽  
pp. 160910 ◽  
Author(s):  
Sean A. Rands
Keyword(s):  
Short Distance ◽  
Stochastic Dynamic Programming ◽  
Travel Behaviour ◽  
Stochastic Dynamic ◽  
Complex Environments ◽  
Trade Off ◽  
Feeding Site ◽  
State Dependent ◽  
Foraging Site ◽  
Optimal Behaviour

Animals living in complex environments experience differing risks of predation depending upon their location within the landscape. An animal could reduce the risk it experiences by remaining in a refuge site, but it may need to emerge from its refuge and enter more dangerous sites for feeding and other activities. Here, I consider the actions of an animal choosing to travel a short distance between a safe refuge and a dangerous foraging site, such as a bird leaving cover to visit a feeder. Although much work has been conducted examining the choice between a refuge and a foraging site when faced with a trade-off between starvation and predation risk, the work presented here is the first to consider the travel behaviour between these locations. Using state-dependent stochastic dynamic programming, I illustrate that there are several forms of optimal behaviour that can emerge. In some situations, the animal should choose to travel without stopping between sites, but in other cases, it is optimal for the animal to travel hesitantly towards the food, and to stop its travel at a point before it reaches the refuge. I discuss how this hesitant ‘dawdling’ behaviour may be optimal, and suggest further work to test these predictions.

scholarly journals Planktivore vertical migration and shoaling under a subarctic light regime

2009 ◽  
Vol 66 (4) ◽  
pp. 525-539 ◽  
Author(s):  
Karl Øystein Gjelland ◽  
Thomas Bøhn ◽  
John K. Horne ◽  
Ingrid Jensvoll ◽  
Frank Reier Knudsen ◽  
...  
Keyword(s):  
Predation Risk ◽  
Vertical Migration ◽  
Light Regime ◽  
Planktivorous Fish ◽  
Day Length ◽  
Coregonus Lavaretus ◽  
Trade Off ◽  
Light Levels ◽  
State Dependent ◽  
Daytime Behaviour

Visually foraging planktivorous fish are prey of visual predators, and their foraging behaviour may be affected by light levels both in terms of gain and risk. The large seasonal change in day length throughout a subarctic summer at 69°N was used to show the influence of light on diel vertical migration (DVM) and shoaling patterns in a planktivorous fish assemblage consisting of two species ( Coregonus lavaretus and Coregonus albula ). Under the midnight sun in June, night and daytime behaviour was similar, with extensive shoaling and limited DVM. With increasingly darker nights towards autumn, the fish dispersed during the dark hours and showed more extensive DVM. Throughout the changing light regime of both the day and the season, the planktivores consistently chose depths with light levels compatible with visual foraging and reduced predation risk as revealed from reactive distance modelling of coregonids and their salmonid predators. The findings support the hypothesis that behavioural decisions are based on a trade-off between foraging rate and predation risk, and increased predator avoidance behaviour towards autumn suggests that this trade-off is state-dependent.

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