Project Title:
Statistics and Phylogenetic Community Ecology

Project Description (short):
The overall goal of this project is to advance the statistical methodology of phylogenetic community ecology. In doing so, we will contribute knowledge and ideas to a growing subdiscipline of ecology. More importantly, we will be preparing undergraduate students for graduate programs that utilize these approaches.

This is a multi-year project (although students can be involved for only one year) that will involve elements of statistical design and implementation, computer programming, and experimental field work using katydids (Orthoptera: Tettigoniidae), an insect family that is closely related to crickets. Our introduction to phylogenetic community ecology will occur in Spring 2007 through mini-lectures and group discussions of primary literature. These discussions will segue into statistical literature on randomization tests, inspection and manipulation of the Phylocom code, and the development and coding of more sophisticated statistical procedures using C language. We will design field experiments in early Summer 2007 and carry out the experiments during mid-late Summer 2007 (when katydids are adults) and early Fall 2007. Data analysis and synthesis will occur in Fall 2007.

Biological Background:

Phylogenetic community ecology (or ‘historical ecology’) describes a growing subdiscipline of ecology that utilizes the evolutionary history of species (phylogenies) to explain present-day community structure (Brooks and McLennan 2002, Webb et al. 2002, Cavender-Bares and Wilczek 2003). The emergence of phylogenetic community ecology was triggered by the need to integrate evolutionary explanations into ecological questions (Losos 1996, McPeek and Miller 1996), the widespread availability of software for phylogenetic reconstruction, and the reality that species in communities have shared evolutionary histories and are not independent entities(Orians 1962).

Researchers have been asking the following questions: Do the species in a habitat represent a random draw from the regional pool of species, or are the species more closely related than expected (phylogenetic clustering) or less closely related than expected (phylogenetic overdispersion) (Webb 2000, Cavender-Bares et al. 2004, Horner-Devine and Bohannan 2006)? Do species in a habitat have similar traits because of evolutionary history (phylogenetic conservatism) or because of convergent evolution (environmental filtering) (Ackerly et al. 2006, Lovette and Hochachka 2006)?

Statistical Background:

The development and usefulness of phylogenetic community ecology relies on statistical testing. The primary software package for this purpose is Phylocom (Webb et al. 2005, Webb et al. 2006). It is written in C source code and contains Macintosh OS X and Windows/DOS executables. The main feature of this software is that it calculates measures of phylogenetic relatedness within a community and tests the value of the measure against various null models using randomization tests. For example, researchers may test for phylogenetic clustering or overdispersion by randomizing the phylogenetic relationships among species in a community, calculating a measure of phylogenetic relatedness for each randomized community, and then comparing an observed value against the statistical distribution generated by the randomizations (Webb 2000). By using this approach, ecologists have found evidence for phylogenetic overdispersion and phylogenetic clustering.

There is a need to develop more sophisticated statistical procedures so that ecologists can continue to link the results of these studies with long-standing ecological paradigms. For example, the current randomization tests do not incorporate species abundance, yet many ecological and evolutionary principles are based on relative abundance of species in a community (e.g., species diversity, the log-normal distribution, species richness estimators, the probability of extinction and speciation). Ecologists must also be able to compare multiple communities simultaneously; that capability does not presently exist. Finally, most studies have utilized quasi-experimental designs, biogeographic surveys, or database surveys to collect and address questions in this subdiscipline. A rigorous experimental approach would allow us to test the efficacy of the statistical procedures and provide new insights into the structure of communities.

Skills needed:
General

• Enthusiasm for interdisciplinary research.
• Willingness to engage problems and issues outside their discipline
• Comfortable with group dynamics and interactions
• Willingness to conduct field work under arduous environmental conditions

• Required Coursework: BIOL 301 (Introduction to Ecology), STAT190 (Introduction to Statistics
• Preferred Coursework: BIOL 503 (Evolutionary Biology)
• Preferred Experience: Handling and sacrificing insects

• Required Coursework: STAT 290 (Introduction to Statistics)
• Preferred Coursework: BIOL 100 (General Biology), STAT 375 (ANOVA), STAT 378 (Regression)
• Preferred Experience: Computer programming experience (C, Java, Matlab)

Start Date:
January 2007

End Date:
To Be Determined

Mentors:
Prof. Dean DeCock (Biology), decock@truman.edu
Prof. Jon Gering (Mathematics), jgering@truman.edu

Accomplishments:

• N. Whelan*, B. Hartwig*, T. Blasingame*, D. De Cock, J. Gering. "Effects of Phylogenetic Tree Topology and Local and Regional Species Richness on NRI and NTI Distributions" SMB/JSMB Joint Annual Meetings, July 31-Aug 3, 2007, San Jose, CA.
• T. Blasingame*, B. Hartwig*, N. Whelan*, J. Gering, and D. De Cock. "The W Statistic: A New Approach for Testing the Relative Abundance Structure of Communities in a Phylogenetic Context" SMB/JSMB Joint Annual Meetings, July 31-Aug 3, 2007, San Jose, CA.
• D. De Cock, J. Gering, T. Blasingame*, N. Whelan* and B. Hartwig*. "The W Statistic: A New Approach for Testing the Relative Abundance Structure of Communities in a Phylogenetic Context" Evolution - Joint Annual Meeting of SSE, SSB, ASN, June 20-24, 2008. Minneapolis, MN.
• manuscript submitted to Ecology Letters

About Prof. DeCock:
Dr. De Cock was born and raised in eastern Iowa and rebelling against his Hawkeye upbringing, he chose to attend Iowa State University where he received a B.S. in Mechanical Engineering. Following several years in the working world as a project engineer he returned to school at the University of Iowa (Go Hawkeyes!) to complete an M.S. in Quality Management and Productivity. He then worked for several years as a Quality Engineer for Maytag before returning to Iowa State to complete a co-major Ph.D. in Statistics and Industrial Engineering. While working on his Ph.D. he spent his summers working for several large corporations (Lennox, 3M, Corning) as a statistical intern.

Dr. De Cock's past research interests include both orthogonal arrays and spatial statistics (kriging). Additionally, in his 4 years at Truman he has mentored capstone students in several different areas of applied statistics including regression, reliability, discriminant analysis, and micro-array analysis.

In his limited free time Dr. De Cock enjoys swimming, reading the Des Moines Register (Sundays at McDonalds), playing Xbox, fishing, and working out at the SRC. He roots for Iowa and Iowa State and watches them anytime they are on television!

About Prof. Gering:
Dr. Gering was born in Ritzville, WA in 1972. He attended Bethel College in Kansas and graduated with honors in 1994. After working for a year at the University of Kansas as a tutor for the athletic department, he left for graduate school at Miami University in Oxford, OH. He completed his M.S. (1997) and Ph.D. (2001) in the Zoology department at Miami University. Both degrees emphasized patterns and processes in ecological communities. He has been at Truman State University since 2001. Dr. Gering's lab uses macroevolutionary approaches to understand the population and community ecology of katydids (Orthoptera: Tettigoniidae).

Dr. Gering enjoys spending time with his wife (Deborah) and his 18-month old son (Benjamin). He also enjoys reading, traveling, racquetball, and the fellowship of eating. He roots for the Green Bay Packers and Seattle Seahawks during football season and rarely misses a televised Kansas Jayhawk game during the college basketball season.

Project Description (long):
None

REFERENCES CITED

Ackerly, D. D., D. W. Schwilk, and C. O. Webb.

2006. Niche Evolution and Adaptive Radiation: Testing the Order of Trait Divergence. Ecology 87:S50-S61.

Brooks, D. R., and D. A. McLennan. 2002.

The Nature of Diversity: An Evolutionary Voyage of Discovery. University of Chicago Press, Chicago.

Cavender-Bares, J., D. D. Ackerly, D. A. Baum, and F. A. Bazzaz. 2004.

Phylogenetic Overdispersion in Floridian Oak Communities. The American Naturalist 163:823-843.

Cavender-Bares, J., and A. Wilczek. 2003.

Integrating Micro- and Macroevolutionary Processes in Community Ecology. Ecology 84:592-587.

Horner-Devine, M. C., and B. J. M. Bohannan. 2006.

Phylogenetic Clustering and Overdispersion in Bacterial Communities. Ecology 87:S100-S108.

Losos, J. B. 1996.

Phylogenetic Perspectives on Community Ecology. Ecology 77:1344-1354.

Lovette, I. J., and W. M. Hochachka. 2006.

Simultaneous Effects of Phylogenetic Niche Conservatism and Competition on Avian Community Structure. Ecology 87:S14-S28.

McPeek, M. A., and T. E. Miller. 1996.

Evolutionary Biology and Community Ecology. Ecology 77:1319-1320.

Orians, G. H. 1962.

Natural Selection and Ecological Theory. American Naturalist 96:257-263.

Webb, C. 2000.

Exploring the Phylogenetic Structure of Ecological Communities: An Example for Rain Forest Trees. The American Naturalist 156:145-155.

Webb, C., D. Ackerly, M. McPeek, and M. Donoghue. 2002. Phylogenies and Community Ecology.

Annual Review of Ecology and Systematics 33:475-505.

Webb, C. O., D. Ackerly, and S. Kembel. 2005.

Phylocom: Software for the Analysis of Community Phylogenetic Structure and Character Evolution. http://www.phylodiversity.net/phylocom.

Webb, C. O., D. Ackerly, and S. W. Kembel. 2006.

Phylocom: Software for the Analysis of Community Phylogenetic Structure and Trait Evolution. http://www.phylodiversity.net/phylocom/.