2005
DOI: 10.1111/j.0014-3820.2005.tb01058.x
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Sexual Selection When Fertilization Is Not Guaranteed

Abstract: Abstract. Much of the theory of sexual selection assumes that females do not generally experience difficulties getting their eggs fertilized, yet sperm limitation is occasionally documented. How often does male limitation form a selection for female traits that improve their mating rate? The question is difficult to test, because if such traits evolve to be efficient, sperm limitation will no longer appear to be a problem to females. Here, we suggest that changes in choosiness between populations, and in parti… Show more

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Cited by 143 publications
(127 citation statements)
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“…Empirically, it is well established that females change their mate preferences based on prior experience [37 -41], that they can become choosier when a range of male phenotypes is experienced [21,42], and that both sexes can learn about the distribution of male phenotypes in the environment based on interactions with conspecifics [26,43,44]. Taken together, these observations validate theoretical models that predict that females should flexibly modify their choosiness based on social interactions, that different populations should vary in that flexibility and that populations experiencing sexual selection should exhibit strong, positive C [9,45]. Quantifying C for traits involved in mate choice should yield insights about the dynamics of sexual selection in a given population or species [46].…”
Section: Discussionsupporting
confidence: 57%
“…Empirically, it is well established that females change their mate preferences based on prior experience [37 -41], that they can become choosier when a range of male phenotypes is experienced [21,42], and that both sexes can learn about the distribution of male phenotypes in the environment based on interactions with conspecifics [26,43,44]. Taken together, these observations validate theoretical models that predict that females should flexibly modify their choosiness based on social interactions, that different populations should vary in that flexibility and that populations experiencing sexual selection should exhibit strong, positive C [9,45]. Quantifying C for traits involved in mate choice should yield insights about the dynamics of sexual selection in a given population or species [46].…”
Section: Discussionsupporting
confidence: 57%
“…Thus, while one can imagine dispersal rules that lead to high-density aggregations in both sexes, the example of figure 1b shows that the details of adaptive mate searching rules can retain, or even accentuate, the effects of low density. The need of females to adapt to situations of high or low mate availability should, therefore, not be immediately dismissed (Kokko & Mappes 2005).…”
Section: Strategies Of the Limiting Sex: Choosiness Resistance And mentioning
confidence: 99%
“…Unsurprisingly, models that incorporate mate encounter rates generally predict that females become less selective when mate availability is low (Hubbell & Johnson 1987;Crowley et al 1991;Kokko & Monaghan 2001;Härdling & Kaitala 2005;Kokko & Mappes 2005), yet few studies have predicted the net effect on the rate of multiple mating (but see Härdling & Kaitala 2005). A less direct way to assess the effects of density is achieved by varying the cost of mate sampling: low density corresponds to high costs of locating another male.…”
Section: Strategies Of the Limiting Sex: Choosiness Resistance And mentioning
confidence: 99%
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“…However, equation (2) is not valid for situations where females cannot be certain about local male density. While females possess evolutionary knowledge regarding typical male densities, circumstances will often deviate from the average (Kokko and Mappes 2005), and females should adjust their signaling effort over time if previous efforts have not led to a desirable male arrival rate. Consider the female in a habitat patch where signaling leads to a low arrival rate, described by l L (S) p 5 (1 Ϫ exp(ϪS)), or in a patch where higher arrival rates can be expected, l H (S) p 10 (1 Ϫ exp(ϪS)) (depicted in fig.…”
Section: Optimizing Male Arrival Ratementioning
confidence: 99%