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Analytical, computational, and stati...

The University of Texas at Austin., Ecology, Evolution, and Behavior.

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Analytical, computational, and statistical approaches to studying speciation.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Analytical, computational, and statistical approaches to studying speciation./
Author:	Lemmon, Alan Richard.
Description:	230 p.
Notes:	Advisers: Mark Kirkpatrick; David M. Hillis.
Contained By:	Dissertation Abstracts International68-08B.
Subject:	Biology, Ecology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3277565
ISBN:	9780549166696

Analytical, computational, and statistical approaches to studying speciation.
Lemmon, Alan Richard.

Analytical, computational, and statistical approaches to studying speciation. - 230 p.

Advisers: Mark Kirkpatrick; David M. Hillis.

Thesis (Ph.D.)--The University of Texas at Austin, 2007.

Two of the most challenging goals of evolutionary biology are to reconstruct the evolutionary relationships among all extant species and to understand the processes by which new species form. Accomplishing these goals will require accurate computational methods for reconstructing phylogenetic trees, general analytic models of speciation, and powerful statistical tools for studying the process of speciation in natural systems.

ISBN: 9780549166696Subjects--Topical Terms:

1017726
Biology, Ecology.

Analytical, computational, and statistical approaches to studying speciation.
LDR:02735nam 2200325 a 45 001 852778
005 20100630
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020 $a 9780549166696
035 $a (UMI)AAI3277565
035 $a AAI3277565
040 $a UMI $c UMI
100 1 $a Lemmon, Alan Richard. $3 1018799
245 1 0 $a Analytical, computational, and statistical approaches to studying speciation.
300 $a 230 p.
500 $a Advisers: Mark Kirkpatrick; David M. Hillis.
500 $a Source: Dissertation Abstracts International, Volume: 68-08, Section: B, page: 4954.
502 $a Thesis (Ph.D.)--The University of Texas at Austin, 2007.
520 $a Two of the most challenging goals of evolutionary biology are to reconstruct the evolutionary relationships among all extant species and to understand the processes by which new species form. Accomplishing these goals will require accurate computational methods for reconstructing phylogenetic trees, general analytic models of speciation, and powerful statistical tools for studying the process of speciation in natural systems.
520 $a In the first chapter, I study the effects of improper model assumption on estimates of phylogeny. Using DNA sequence data simulated under a variety of models of sequence evolution, I demonstrate that use of oversimplified models can result in erroneous phylogeny estimates. This result suggests that if the models currently utilized are oversimplified then current estimates of phylogeny may be inaccurate and more complex models need to be developed and employed.
520 $a In the second and third chapters, I study one process thought to be important in completing the final stages of speciation: reinforcement. Using simulations of a hybrid zone, I show that the process of reinforcement can result in patterns other than reproductive character displacement. I also show that speciation by reinforcement is more likely when the genes involved in reproductive isolation are sex-linked.
520 $a In the fourth chapter, I develop a statistical model of quantifying the degree of isolation between species undergoing divergence. Using genotype data obtained from natural hybrid zones, this novel method can be used to estimate the fitness of hybrids during different stages of their life cycle. This approach offers a new approach to empirical biologists studying extrinsic postzygotic isolation in natural systems.
590 $a School code: 0227.
650 4 $a Biology, Ecology. $3 1017726
650 4 $a Biology, Genetics. $3 1017730
690 $a 0329
690 $a 0369
710 2 $a The University of Texas at Austin. $b Ecology, Evolution, and Behavior. $3 1018798
773 0 $t Dissertation Abstracts International $g 68-08B.
790 $a 0227
790 1 0 $a Hillis, David M., $e advisor
790 1 0 $a Kirkpatrick, Mark, $e advisor
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3277565