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Phylogenetic Inference for Biogeogra...

Landis, Michael.

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Phylogenetic Inference for Biogeographic and Quantitative Trait Evolution.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Phylogenetic Inference for Biogeographic and Quantitative Trait Evolution./
作者:	Landis, Michael.
面頁冊數:	118 p.
附註:	Source: Dissertation Abstracts International, Volume: 77-08(E), Section: B.
Contained By:	Dissertation Abstracts International77-08B(E).
標題:	Evolution & development. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10086117
ISBN:	9781339592503

Phylogenetic Inference for Biogeographic and Quantitative Trait Evolution.
Landis, Michael.

Phylogenetic Inference for Biogeographic and Quantitative Trait Evolution. - 118 p.

Source: Dissertation Abstracts International, Volume: 77-08(E), Section: B.

Thesis (Ph.D.)--University of California, Berkeley, 2015.

A fundamental goal of evolutionary biology is to characterize the processes by which species traits evolve, and how those processes gave rise to the patterns of variation observed between species. Since interspecific variation often arises over millions of years, the tempo and mode of these processes cannot typically be observed directly or reproduced experimentally. Instead, they may be studied through a statistical framework called the phylogenetic comparative method. This dissertation focuses on phylogenetic models for two classes of traits: species geographical distributions (or biogeographic traits) and quantitative traits. The following contributions represent methodological advances that serve to render longstanding theoretical questions vulnerable to statistical analysis.

ISBN: 9781339592503Subjects--Topical Terms:

3172418
Evolution & development.

Phylogenetic Inference for Biogeographic and Quantitative Trait Evolution.
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245 1 0 $a Phylogenetic Inference for Biogeographic and Quantitative Trait Evolution.
300 $a 118 p.
500 $a Source: Dissertation Abstracts International, Volume: 77-08(E), Section: B.
500 $a Adviser: John P. Huelsenbeck.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2015.
520 $a A fundamental goal of evolutionary biology is to characterize the processes by which species traits evolve, and how those processes gave rise to the patterns of variation observed between species. Since interspecific variation often arises over millions of years, the tempo and mode of these processes cannot typically be observed directly or reproduced experimentally. Instead, they may be studied through a statistical framework called the phylogenetic comparative method. This dissertation focuses on phylogenetic models for two classes of traits: species geographical distributions (or biogeographic traits) and quantitative traits. The following contributions represent methodological advances that serve to render longstanding theoretical questions vulnerable to statistical analysis.
520 $a Chapter 1 develops an inference method to efficiently estimate historical biogeographic patterns using data augmented Markov chain Monte Carlo. This strategy increases the feasible number of areas per analysis from the tens to the thousands. Taking advantage of this increased resolution, the work introduces parameterizations for distance-dependent dispersal effects to greatly reduce model complexity. Analyzing Malesian Vireya (subgenus Rhododendron) biogeography, the method recovers Wallace's Line and Lydekker's Line as important geographical dispersal barriers, as well as ancestral range estimates for the clade.
520 $a Chapter 2 presents a technique called biogeographic dating that leverages paleogeographical information to estimate speciation events in absolute time. To achieve this, I construct a time-heterogeneous continuous-time Markov chain for the dispersal process, whose rate matrix takes values that are empirically informed by paleocontinental adjacencies. For biogeographic evolution, the time-heterogeneous process restores rate-time identifiability, thus enabling the estimation of absolute speciation times. Informed by the current paleogeographical literature, I construct an empirical dispersal graph using 25 areas and 26 epochs between the Cambrian (540 Ma) and the present (0 Ma). Applying biogeographic dating to Testudines (crown turtles), I recover a root age concordant with fossil-based estimates (≈205 Ma) to validate the efficacy of the method.
520 $a Chapter 3 introduces a class of models of continuous trait evolution that permit bursts of evolutionary change ("jumps"). Darwin's original conception of evolution proposed that species evolve gradually over time, which is typically modeled as a Brownian motion. However, many evolutionary mechanisms produce bursts in trait variation as punctuated change of large effect, such as rapid adaptation. I use Levy processes to model these effects, which are a flexible class of stochastic processes that produce gradual and/or punctuational patterns of change. Applying a data augmented Bayesian method to primates, I show that body mass and endocranial volume measurements both bear the signature of evolution with jumps.
590 $a School code: 0028.
650 4 $a Evolution & development. $3 3172418
650 4 $a Bioinformatics. $3 553671
650 4 $a Statistics. $3 517247
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690 $a 0715
690 $a 0463
710 2 $a University of California, Berkeley. $b Integrative Biology. $3 2096278
773 0 $t Dissertation Abstracts International $g 77-08B(E).
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791 $a Ph.D.
792 $a 2015
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10086117