Book contents
- Frontmatter
- Contents
- Contributors
- Introduction: Modelling perception with artificial neural networks
- Part I General themes
- Part II The use of artificial neural networks to elucidate the nature of perceptual processes in animals
- Part III Artificial neural networks as models of perceptual processing in ecology and evolutionary biology
- 9 Evolutionary diversification of mating behaviour: using artificial neural networks to study reproductive character displacement and speciation
- 10 Applying artificial neural networks to the study of prey colouration
- 11 Artificial neural networks in models of specialisation, guild evolution and sympatric speciation
- 12 Probabilistic design principles for robust multi-modal communication networks
- 13 Movement-based signalling and the physical world: modelling the changing perceptual task for receivers
- Part IV Methodological issues in the use of simple feedforward networks
- Index
- References
9 - Evolutionary diversification of mating behaviour: using artificial neural networks to study reproductive character displacement and speciation
from Part III - Artificial neural networks as models of perceptual processing in ecology and evolutionary biology
Published online by Cambridge University Press: 05 July 2011
- Frontmatter
- Contents
- Contributors
- Introduction: Modelling perception with artificial neural networks
- Part I General themes
- Part II The use of artificial neural networks to elucidate the nature of perceptual processes in animals
- Part III Artificial neural networks as models of perceptual processing in ecology and evolutionary biology
- 9 Evolutionary diversification of mating behaviour: using artificial neural networks to study reproductive character displacement and speciation
- 10 Applying artificial neural networks to the study of prey colouration
- 11 Artificial neural networks in models of specialisation, guild evolution and sympatric speciation
- 12 Probabilistic design principles for robust multi-modal communication networks
- 13 Movement-based signalling and the physical world: modelling the changing perceptual task for receivers
- Part IV Methodological issues in the use of simple feedforward networks
- Index
- References
Summary
Introduction
When species with similar sexual signals co-occur, selection may favour divergence of these signals to minimise either their interference or the risk of mis-mating between species, a process termed reproductive character displacement (Howard, 1993; Andersson, 1994; Servedio & Noor, 2003; Coyne & Orr, 2004; Pfennig & Pfennig, 2009). This selective process potentially results in mating behaviours that are not only divergent between species that co-occur but that are also divergent among conspecific populations that do and do not occur with heterospecifics or that co-occur with different heterospecifics (reviewed in Howard, 1993; Andersson, 1994; Gerhardt & Huber, 2002; Coyne & Orr, 2004; e.g., Noor, 1995; Saetre et al., 1997; Pfennig, 2000; Gabor & Ryan, 2001; Höbel & Gerhardt, 2003).
An oft-used approach to assessing whether reproductive character displacement has occurred between species relies on behavioural experiments that evaluate mate preferences from populations that do and do not occur with heterospecifics (sympatry and allopatry, respectively). In such experiments, individuals are presented the signals of heterospecifics and/or conspecifics to assess whether allopatric individuals are more likely to mistakenly prefer heterospecifics than are sympatric individuals (reviewed in Howard, 1993). The expectation is that individuals from sympatry should preferentially avoid heterospecifics, whereas those in allopatry should fail to distinguish heterospecifics from conspecifics (presumably because, unlike sympatric individuals, they have not been under selection to do so). Such patterns of discrimination have been observed, and they provide some of the strongest examples of reproductive character displacement (reviewed in Howard, 1993).
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- Modelling Perception with Artificial Neural Networks , pp. 187 - 214Publisher: Cambridge University PressPrint publication year: 2010