Date of Award
Great Lakes Institute for Environmental Research
Individual-based Modeling Approach, Sympatric Speciation
Sympatric speciation, the emergence of new species in the absence of geographic isolation, is one of the most controversial issues in evolutionary biology. Although today the plausibility of the occurrence of sympatric speciation is theoretically acknowledged, its underlying mechanisms are still unknown. We applied a modeling approach with three trophic levels (primary resource, prey, and predator) and supplied prey species with two different food resources (Food 1 and Food 2) to track prey lineage through evolutionary time to detect any indicators of the occurrence of sympatric speciation caused by specialized food consumption. Whereas, Food 1 was the more available resource, Food 2 had higher energy content. Initially, when there was not yet any specific food specialization, Food 1 consumption rate was significantly higher compared to Food 2. Eventually, around time step 22,000 and after the emergence of food consumption specialization, the exploitation of Food 2 was higher than Food 1 in spite of the fact that prey individuals were more frequently encountered with Food 1 than Food 2. Drawing a comparison between simulations with only one food resource and simulations with two available food resources revealed that complete reproductive isolation caused by disruptive selective pressure exerted by adaptation to different resources plays a curial role in the emergence of sympatric species. Machine learning techniques were also employed to identify the shared patterns among sympatric species. Results showed that for most lineages sympatric divergence has occurred at the beginning of the process of the emergence of specialized use. If not, these species have possessed a high spatial distribution and had to meet two conditions to be diverged sympatrically: i. high genetic diversity and ii. a large population size.
KARIM POUR, MARYAM, "Investigation of sympatric speciation as the outcome of competition for food resource by means of an individual-based modeling approach" (2016). Electronic Theses and Dissertations. 5908.