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Epistasis and environmental heterogeneity in the speciation process

Author

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  • Campos, Paulo R.A.
  • de Oliveira, Viviane M.
  • Rosas, Alexandre

Abstract

The study of evolutionary mechanisms driving evolution of natural populations is a central issue in evolutionary biology. In this context the question of genetic divergence and speciation in ecosystems is one of the most intriguing and complex challenges nowadays. The current manuscript aims to investigate the aforementioned problem by means of extensive computer simulations. Here we introduce a spatial model of evolution which assumes viability selection, mutations and random mating. The population evolves in a heterogeneous environment where the habitat diversity is an input of the model. As a model for the fitness landscape a variation of the NK model is assumed. We present results for the time evolution of fitness and genetic divergence and address the species-area relationship. The dependence of the quantities and scalings of the problem with epistasis is investigated. Depending on the mutation rate, the species-area relationship displays either two-phase or a triphasic scenario. In any case, for intermediate and large system sizes the relationship is well described by a power-law, with exponents within the range of values observed in real ecological niches. All the quantities show a strong dependence on the epistasis parameter. According to our simulations, a lower level of genetic divergence is needed in order to ensure sexual isolation when interactions among genes is strong.

Suggested Citation

  • Campos, Paulo R.A. & de Oliveira, Viviane M. & Rosas, Alexandre, 2010. "Epistasis and environmental heterogeneity in the speciation process," Ecological Modelling, Elsevier, vol. 221(21), pages 2546-2554.
    • Handle: RePEc:eee:ecomod:v:221:y:2010:i:21:p:2546-2554
    DOI: 10.1016/j.ecolmodel.2010.07.023
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    References listed on IDEAS

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    1. Ricardo B. R. Azevedo & Rolf Lohaus & Suraj Srinivasan & Kristen K. Dang & Christina L. Burch, 2006. "Sexual reproduction selects for robustness and negative epistasis in artificial gene networks," Nature, Nature, vol. 440(7080), pages 87-90, March.
    2. Campos, Paulo R.A & Adami, Christoph & Wilke, Claus O, 2002. "Optimal adaptive performance and delocalization in NK fitness landscapes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 304(3), pages 495-506.
    3. Swanack, Todd M. & Grant, William E. & Fath, Brian D., 2008. "On the use of multi-species NK models to explore ecosystem development," Ecological Modelling, Elsevier, vol. 218(3), pages 367-374.
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