The overall aim of this project is to better understand biological evolution, speciation, and diversification through a study of the dynamic (and static) behavior of various mathematical models describing populations, species and clades. Using a combination of analytical methods and extensive numerical simulations, a number of mathematical models of evolutionary diversification taking into account various factors operating in natural populations will be studied. Both standard population genetics approaches and novel methods recently developed in theoretical evolutionary biology, mathematics, and physics will be used. This project has 3 interrelated specific aims. 1. Build mathematical foundations of a general theory of speciation, develop a mathematical theory of adaptive radiations, and formulate and study mathematical models linking evolutionary processes at different spatial and temporal scales (from speciation to adaptive radiation to macro evolutionary patters). 2. Establish closer connections between theory and empirical data through a better understanding of the implications of theoretical results for speciation in specific groups of organisms, exploration of how dynamical models of speciation can guide the development of statistical methods and hypotheses utilizing emerging comparative genomic data, and examination of how the data on molecular phylogenies and spatial range distributions can be used to infer the history of speciation and clade diversification. 3. Study the coevolutionary dynamics using explicit genetic and spatial models to analyze how antagonistic and mutualistic within- and between-species interactions depending on many loci and traits affect the evolutionary dynamics of populations in panmictic and spatially-structured systems. The studies proposed here may improve our understanding of the mechanisms responsible for the origin and maintenance of biodiversity and may be important for understanding and controlling the dynamics of host-pathogen interactions affecting human health.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM056693-10
Application #
7247906
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
Eckstrand, Irene A
Project Start
1998-01-01
Project End
2009-12-31
Budget Start
2008-01-01
Budget End
2008-12-31
Support Year
10
Fiscal Year
2008
Total Cost
$194,102
Indirect Cost
Name
University of Tennessee Knoxville
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
003387891
City
Knoxville
State
TN
Country
United States
Zip Code
37996
González-Forero, M (2015) Stable eusociality via maternal manipulation when resistance is costless. J Evol Biol 28:2208-23
Berner, D; Thibert-Plante, X (2015) How mechanisms of habitat preference evolve and promote divergence with gene flow. J Evol Biol 28:1641-55
Welch, John J; Jiggins, Chris D (2014) Standing and flowing: the complex origins of adaptive variation. Mol Ecol 23:3935-7
Roesti, Marius; Gavrilets, Sergey; Hendry, Andrew P et al. (2014) The genomic signature of parallel adaptation from shared genetic variation. Mol Ecol 23:3944-56
Duenez-Guzman, Edgar A; Vose, Michael D (2013) No free lunch and benchmarks. Evol Comput 21:293-312
Thibert-Plante, Xavier; Gavrilets, Sergey (2013) Evolution of mate choice and the so-called magic traits in ecological speciation. Ecol Lett 16:1004-13
Birand, Aysegul; Vose, Aaron; Gavrilets, Sergey (2012) Patterns of species ranges, speciation, and extinction. Am Nat 179:1-21
Mesterton-Gibbons, Mike; Gavrilets, Sergey; Gravner, Janko et al. (2011) Models of coalition or alliance formation. J Theor Biol 274:187-204
Rowell, Jonathan T (2010) Tactical population movements and distributions for ideally motivated competitors. Am Nat 176:638-50
Giraud, Tatiana; Gladieux, Pierre; Gavrilets, Sergey (2010) Linking the emergence of fungal plant diseases with ecological speciation. Trends Ecol Evol 25:387-95

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