Quantitative Paleontology is the practical application of quantitative analysis to paleontology, including the analysis of diversity through time, analysis of diversity in space, analysis of morphological disparity, and reconstruction of phylogenetic relationships.  Skills include Monte Carlo statistical tests, analysis of large data sets, use of relational SQL databases, and the application of finite element analysis to paleontological problems.

Module 1 - Introduction

Course overview and software installation. 

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Week 1 - Introduction.pdf

Module 2 - MySQL and Mathematica

Introduction to software, SQL queries, Mathematica interface, programming, and data queries. See handouts in right column of this page.

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Week 2 - Software and data.pdf

Module 3 - Time series and random walks

Discussion of papers, discussion of properties of time series and random walks, discussion of methods for assessing trends and correlations within and between time series.

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Week 3 - Trait evolution, random walks.pdf

Module 4 - Rates and modes of evolution

Discussion of papers, review of properties of time series and random walks, discussion of directional and stabilizing modes of evolution, discussion of step rates and net rates, discussion of expected scaling of net rates to directional, random, and stabilizing modes of evolution

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Week 4 - Rates and modes of evolution.pdf

Module 5 - Rates of evolution within lineages

Review discussion of the LineageEvolution function; modes of evolution, rates of evolution, thinking of step rate as a statistical distribution, LRI method for estimating step rate and mode, time series properties, serial correlation, McKinney's equation for time series process, correlation between time series. Introduction to evolution of quantitative trait on a phylogenetic tree.

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Week 5 - LineageEvolution and real data.pdf

Module 6 - Quantitative traits and phylogeny

Review of properties of random walks; discussion of assignment; star phylogenies and their properties; Simulating star phylogenies; expected covariances from phylogeny; C matrix; birth-death models; reconstructing ancestral nodes.

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Week 6 - Quantitative Traits and Phylogeny.pdf

Module 7 - Phylogeny, parsimony, and tree support

Review assignment; trees; continuous versus discrete characters; parsimony; character polarity; tree support, consistency index, retention index, bootstrapping; ML and Bayesian approaches; stratigraphy and phylogeny.

Week 7 - phylogenetic reconstruction.pdf

Module 8 - Tree support and disparity

Review assignment; tree support, and bootstrapping; ML phylogenetics; disparity; taxon distances

Week 8 - Disparity.pdf

Module 9 - Empirical diversity patterns

Review assignment; what is diversity or taxonomic richness; how is it estimated; first and last occurrences; rates or probabilities of origination and extinction.

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Week 9 - Diversity curves.pdf

Module 10 - Simulated diversity patterns

Discusison of Raup (1985); Diversity curves; extinction and speciation rates; cohort analysis; paraclade dynamics.

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Week 10 - Mathematica and Diversity curves.pdf

Module 11 - Introduction to Finite Element Analysis (FEA)

Lecture on FEA, introduction to FARO Arm laser scanner.

Week 12 - Finite Element Analysis.pdf

Module 12 - Climate

Introduction to climate and global climate models.

Week 13 - Climate.pdf