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RESEARCH PRODUCT
Variation between Self- and Mutual Assessment in Animal Contests
Stephen HeapMike Mesterton-gibbonssubject
Self-assessmentCompetitive BehaviorComputer sciencePopulationVariation (game tree)CONTESTModels Biologicalstrategic errorMicroeconomicsmutual assessmentAnimalseducationEcology Evolution Behavior and Systematicstietoeducation.field_of_studycontestBehavior AnimalMutual assessmentAdversaryInvestment (macroeconomics)self-assessmentBiological EvolutionAnimal Communicationta1181Functional significancesignalingdescription
Limited resources lead animals into conflicts of interest, which are resolved when an individual withdraws from a direct contest. Current theory suggests that the decision to withdraw can be based on a threshold derived from an individual’s own state (self-assessment) or on a comparison between their own state and their opponent’s (mutual assessment). The observed variation between these assessment strategies in nature does not conform to theory. Thus, we require theoretical developments that explain the functional significance of different assessment strategies. We consider a hawk-dove game with two discrete classes that differ in fighting ability, in which the players strategically decide on their investment toward mutual assessment. Analysis of the model indicates that there are simultaneous trade-offs relating to assessment strategies. First, weak individuals in a population must decide on whether to acquire information about their opponents at the cost of providing opponents with information about themselves. Secondly, all individuals must decide between investing in mutual assessment and being persistent in contests. Our analysis suggests that the potential for individuals to make errors during contests and differences in the consequences of sharing information within a population may serve as fundamental concepts for explaining variation in assessment strategy. peerReviewed
year | journal | country | edition | language |
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2014-01-01 |