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Am Nat. 2003 Mar;161(3):380-94. doi: 10.1086/367588.
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特征取代与配偶选择的进化:一种人工神经网络方法。

Character displacement and the evolution of mate choice: an artificial neural network approach.

作者信息

Pfennig Karin S, Ryan Michael J

机构信息

Section of Integrative Biology, University of Texas, C0390, Austin, TX 78712, USA.

出版信息

Philos Trans R Soc Lond B Biol Sci. 2007 Mar 29;362(1479):411-9. doi: 10.1098/rstb.2006.1968.

DOI:10.1098/rstb.2006.1968
PMID:17255015
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2323559/
Abstract

Interactions with heterospecifics can promote the evolution of divergent mating behaviours between populations that do and do not occur with heterospecifics. This process--reproductive character displacement--potentially results from selection to minimize the risk of mating with heterospecifics. We sought to determine whether heterospecific interactions lead to divergence of female preferences for aspects of conspecific male signals. We used artificial neural network models to simulate a mate recognition system in which females co-occur with different heterospecifics in different populations. Populations that evolved conspecific recognition in the presence of different heterospecifics varied in their preferences for aspects of conspecific male signals. When we tested networks for their preferences of conspecific versus heterospecific signals, however, we found that networks from allopatric populations were usually able to select against heterospecifics. We suggest that female preferences for aspects of conspecific male signals can result in a concomitant reduction in the likelihood that females will mate with heterospecifics. Consequently, even females in allopatry may discriminate against heterospecific mates depending on the nature of their preferences for conspecifics. Such a pattern could potentially explain cases where reproductive character displacement is expected, but not observed.

摘要

与异种个体的相互作用能够促进在与异种个体共存和不共存的种群之间,不同交配行为的进化。这个过程——生殖特征替代——可能是由于选择以尽量减少与异种个体交配的风险而产生的。我们试图确定异种个体的相互作用是否会导致雌性对同种雄性信号特征的偏好出现分化。我们使用人工神经网络模型来模拟一个配偶识别系统,在这个系统中,雌性在不同种群中与不同的异种个体共存。在不同异种个体存在的情况下进化出同种识别能力的种群,在对同种雄性信号特征的偏好上存在差异。然而,当我们测试这些网络对同种信号与异种信号的偏好时,我们发现来自异域种群的网络通常能够对异种个体进行筛选。我们认为,雌性对同种雄性信号特征的偏好可能会同时降低雌性与异种个体交配的可能性。因此,即使是异域的雌性也可能根据它们对同种个体偏好的性质来区分异种配偶。这样一种模式可能潜在地解释了预期会出现生殖特征替代,但却未观察到的情况。