Coevolution in mutualistic networks: gene flow and selection mosaics
Ecological interactions such as predation, competition, and mutualism are important forces that influence species evolution. Coevolution is defined as reciprocal evolutionary change in interacting species. The Geographic Mosaic Theory of Coevolution (GMTC) provides a theoretical framework to explain...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2017 |
| País: | Brasil |
| Institución: | Universidade de São Paulo (USP) |
| Repositorio: | Biblioteca Digital de Teses e Dissertações da USP |
| Idioma: | inglés |
| OAI Identifier: | oai:teses.usp.br:tde-17102017-154829 |
| Acceso en línea: | http://www.teses.usp.br/teses/disponiveis/41/41134/tde-17102017-154829/ |
| Access Level: | acceso abierto |
| Palabra clave: | Ecological networks Geographic mosaic of coevolution Mosaico geográfico da coevolução Mutualismos Mutualisms Redes ecológicas |
| Sumario: | Ecological interactions such as predation, competition, and mutualism are important forces that influence species evolution. Coevolution is defined as reciprocal evolutionary change in interacting species. The Geographic Mosaic Theory of Coevolution (GMTC) provides a theoretical framework to explain how collections of populations should coevolve across space. Two fundamental aspects of the GMTC are gene flow among populations and the presence of selection mosaics, which are collections of localities with particular selection regimes. Several studies have explored how phenotypic trait matching between species evolves in pairs or small groups of species. However, ecological interactions frequently form large networks that connect dozens of species present in a given community. In networks of mutualisms, for instance, the organization of interactions may affect ecological and evolutionary processes. A next step in understanding the coevolutionary process is to investigate how aspects of the GMTC affect the evolution of species embedded in interaction networks. In this dissertation, we tried to fill this gap using a mathematical model of coevolution, complex networks tools, and information on empirical mutualistic networks. Our numerical simulations of the coevolutionary model allow us to draw three main conclusions. First, gene flow affects trait patterns generated by coevolution and may favor the emergence of trait matching depending on the selection mosaic. Second, the organization of mutualistic networks influences coevolution, but this effect may vanish when gene flow favors trait matching. Intimate mutualisms, such as protection of host plants by ants, form small and compartmentalized networks that generate higher trait matching than large and nested networks typical of mutualisms among free-living species, such as pollination. Third, habitat fragmentation resulting in the disruption of gene flow should reduce the reciprocal adaptations between interacting species and at the same time promote adaptations to the local abiotic environment. In conclusion, we show that a complex interplay between gene flow, the geographic structure of selection, and the organization of ecological networks shapes the evolution of large groups of species. Our results therefore allow predictions of how environmental impacts such as habitat fragmentation will modify the evolution of species interactions |
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