Adaptive search and information updating in sequential mate choice

被引:63
作者
Mazalov, V
Perrin, N
Dombrovsky, Y
机构
[1] UNIV LAUSANNE, INST ZOOL & ANIM ECOL, CH-1015 LAUSANNE, SWITZERLAND
[2] RUSSIAN ACAD SCI, SIBERIAN BRANCH, INST NAT RESOURCES, CHITA, RUSSIA
[3] ROSTOV STATE UNIV, DEPT MATH ECOL, ROSTOV NA DONU 344104, RUSSIA
关键词
D O I
10.1086/285914
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Classical treatments of problems of sequential mate choice assume that the distribution of the quality of potential mates is known a priori. This assumption, made for analytical purposes, may seem unrealistic, opposing empirical data as well as evolutionary arguments. Using stochastic dynamic programming, we develop a model that includes the possibility for searching individuals to learn about the distribution and in particular to update mean and variance during the search. In a constant environment, a priori knowledge of the parameter values brings strong benefits in both time needed to make a decision and average value of mate obtained. Knowing the variance yields more benefits than knowing the mean, and benefits increase with variance. However, the costs of learning become progressively lower as more time is available for choice. When parameter values differ between demes and/or searching periods, a strategy relying on fixed a priori information might lead to erroneous decisions, which confers advantages on the learning strategy. However, time for choice plays an important role as well: if a decision must be made rapidly, a fixed strategy may do better even when the fixed image does not coincide with the local parameter values. These results help in delineating the ecological-behavior context in which learning strategies may spread.
引用
收藏
页码:123 / 137
页数:15
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