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Trade-off Function (trade-off + function)
Selected AbstractsPredictors of reproductive cost in female Soay sheepJOURNAL OF ANIMAL ECOLOGY, Issue 2 2005G. TAVECCHIA Summary 1We investigate factors influencing the trade-off between survival and reproduction in female Soay sheep (Ovis aries). Multistate capture,recapture models are used to incorporate the state-specific recapture probability and to investigate the influence of age and ecological conditions on the cost of reproduction, defined as the difference between survival of breeder and non-breeder ewes on a logistic scale. 2The cost is identified as a quadratic function of age, being greatest for females breeding at 1 year of age and when more than 7 years old. Costs, however, were only present during severe environmental conditions (wet and stormy winters occurring when population density was high). 3Winter severity and population size explain most of the variation in the probability of breeding for the first time at 1 year of life, but did not affect the subsequent breeding probability. 4The presence of a cost of reproduction was confirmed by an experiment where a subset of females was prevented from breeding in their first year of life. 5Our results suggest that breeding decisions are quality or condition dependent. We show that the interaction between age and time has a significant effect on variation around the phenotypic trade-off function: selection against weaker individuals born into cohorts that experience severe environmental conditions early in life can progressively eliminate low-quality phenotypes from these cohorts, generating population-level effects. [source] The evolution of trade-offs: geographic variation in call duration and flight ability in the sand cricket, Gryllus firmusJOURNAL OF EVOLUTIONARY BIOLOGY, Issue 4 2003D. A. Roff Abstract Quantitative genetic theory assumes that trade-offs are best represented by bivariate normal distributions. This theory predicts that selection will shift the trade-off function itself and not just move the mean trait values along a fixed trade-off line, as is generally assumed in optimality models. As a consequence, quantitative genetic theory predicts that the trade-off function will vary among populations in which at least one of the component traits itself varies. This prediction is tested using the trade-off between call duration and flight capability, as indexed by the mass of the dorsolateral flight muscles, in the macropterous morph of the sand cricket. We use four different populations of crickets that vary in the proportion of macropterous males (Lab = 33%, Florida = 29%, Bermuda = 72%, South Carolina = 80%). We find, as predicted, that there is significant variation in the intercept of the trade-off function but not the slope, supporting the hypothesis that trade-off functions are better represented as bivariate normal distributions rather than single lines. We also test the prediction from a quantitative genetical model of the evolution of wing dimorphism that the mean call duration of macropterous males will increase with the percentage of macropterous males in the population. This prediction is also supported. Finally, we estimate the probability of a macropterous male attracting a female, P, as a function of the relative time spent calling (P = time spent calling by macropterous male/(total time spent calling by both micropterous and macropterous male). We find that in the Lab and Florida populations the probability of a female selecting the macropterous male is equal to P, indicating that preference is due simply to relative call duration. But in the Bermuda and South Carolina populations the probability of a female selecting a macropterous male is less than P, indicating a preference for the micropterous male even after differences in call duration are accounted for. [source] Utility transversality: a value-based approachJOURNAL OF MULTI CRITERIA DECISION ANALYSIS, Issue 5-6 2005James E. Matheson Abstract We examine multiattribute decision problems where a value function is specified over the attributes of a decision problem, as is typically done in the deterministic phase of a decision analysis. When uncertainty is present, a utility function is assigned over the value function to represent the decision maker's risk attitude towards value, which we refer to as a value-based approach. A fundamental result of using the value-based approach is a closed form expression that relates the risk aversion functions of the individual attributes to the trade-off functions between them. We call this relation utility transversality. The utility transversality relation asserts that once the value function is specified there is only one dimension of risk attitude in multiattribute decision problems. The construction of multiattribute utility functions using the value-based approach provides the flexibility to model more general functional forms that do not require assumptions of utility independence. For example, we derive a new family of multiattribute utility functions that describes richer preference structures than the usual multilinear family. We also show that many classical results of utility theory, such as risk sharing and the notion of a corporate risk tolerance, can be derived simply from the utility transversality relations by appropriate choice of the value function. Copyright © 2007 John Wiley & Sons, Ltd. [source] | ||||||||||