Smithsonian National Museum of Natural History

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Department of Paleobiology

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  • Gene Hunt
  • Curator of Ostracoda
  • Phone:   202-633-1331
  • Fax:   202-786-2832
  • E-mail Address:   hunte
  • Mailing Address:
    Smithsonian Institution
    PO Box 37012, MRC 121
    Washington, DC 20013-7012
  • Shipping Address:
    Smithsonian Institution
    National Museum of Natural History
    10th & Constitution NW
    Washington, DC 20560-0121
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Education

Ph.D. University of Chicago, 2003
B.S. Duke University, 1995

Research Interests

My research interests are diverse, but one common theme that underpins many of these projects is the translation of evolutionary processes acting on short time scales into patterns that are observable in the fossil record. Most commonly, I use the deep-sea microfossil record to investigate some of these connections between evolution on micro- and macro- time scales.

Morphologic evolution in deep-sea Ostracoda
My organismal work thus far has focused on the ostracode genus Poseidonamicus. One aspect of my research has focused on estimating phylogenetic relationships among populations of this genus. 
In addition to phylogeny, I have ongoing projects examining the development and morphology of carapace reticulation and analysis of body size trends over the Cenozoic, and the relationship of such trend to long-term climate change.

Variation and phenotypic evolution
Variation is the raw material of evolution, and the influence of this variation on evolutionary processes is well understood on time scales of a few generations. What is less clear, however, is what role phenotypic variation may play in structuring or constraining evolutionary change over much longer periods of time. Ongoing projects in this area include: (i) assessing the conservation of phenotypic covariance patterns within and among lineages, and (ii) testing the degree to which phenotypic variation has channeled macroevolutionary change in the deep-sea ostracode genus Poseidonamicus.

Analytical methods in paleontology
Other current and recent projects explore the use of quantitative approaches in paleobiological research. One current line of research revisits the use of statistical models in studying the mode and pace of phyletic evolution. 
Other research projects include analyzing the drivers of deep-sea diversity change in the context of the species-energy theory (Hunt, Cronin and Roy, 2005), and examining the extent of phylogenetic clumping in bivalve extinction with Kaustuv Roy.

Ecology, evolution and conservation biology of rocky intertidal mollusks
This line of research follows from my postdoctoral position with Dr. Kaustuv Roy of the University of California San Diego. More can be learned about this work by visiting http://www-biology.ucsd.edu/labs/roy/CBRISC/CBhome.html.

Resources

I have written a package for the R statistical software environment (http://www.r-project.org/) that performs the analyses described in my 2006 Paleobiology paper. This package is called paleoTS, and like all R packages, it is best downloaded from within R using the “Package Installer” or equivalent pull-down menu.

Below are some handouts I did for a 5-session course introducing users to R for paleontological analysis. Some of these cover how to use R in general, and some discusses specifically paleontological analyses that can be done with R. Each session includes practice exercises, with answers at the end. (Sessions are in Adobe Acrobat format, click on the link to read or download.)

  • Session 1  R basics, introduction to statistics and plotting
  • Session 2  Importing data, statistical models in R, biodiversity analyses
  • Session 3  Data manipulation, multivariate analysis
  • Session 4  Programming: loops, functions, etc.
  • Session 5  Phylogenetic comparative methods, re-sampling procedures

Publications

Hunt, G. 2007. The relative importance of directional change, random walks, and stasis in the evolution of fossil lineages. Proceedings of the National Academy of Sciences USA 104:18404-18408

Hunt, G. 2007. Paleontology: Variation and Early Evolution. Science 317:459-460.

Hunt, G. 2007. Evolutionary divergence in directions of high phenotypic variance in the ostracode genus Poseidonamicus. Evolution 61:1560-1576.

Hunt, G. 2007. Morphology, ontogeny, and phylogenetics of the genus Poseidonamicus (Ostracoda: Thaerocytherinae). Journal of Paleontology 81:607-631.

Frame, K., G. Hunt, and K. Roy. 2007. Intertidal meiofaunal biodiversity with respect to different algal habitats: a test using phytal ostracodes from Southern California. Hydrobiologia 586:331-342.

Hunt, G., L. E. Park, and M. LaBarbera. 2007. A novel crustacean swimming stroke: coordinated four-paddled locomotion in the cypridoidean ostracode Cypridopsis vidua (Müller). Biological Bulletin 212:67-73.

Hunt, G., and K. Roy. 2006. Climate change, body size evolution, and Cope's Rule in deep-sea ostracodes. Proceedings of the National Academy of Sciences USA 103(5):1347-1352.

Hunt, G. 2006. Fitting and comparing models of phyletic evolution: random walks and beyond.  Paleobiology 32(4):578-602.

Jablonski, D and Hunt, G. 2006. Larval ecology, geographic range, and species survivorship in Cretaceous mollusks: organismic versus species-level explanations. American Naturalist 168(4):556-564.

Hunt, G., T. M. Cronin, and K. Roy. 2005. Species-energy relationship in the deep sea: a test using the Quaternary fossil record. Ecology Letters 8:739-747.

Hunt, G., K. Roy, and D. Jablonski. 2005. Species-level heritability reaffirmed: a comment on "On the heritability of geographic range sizes". American Naturalist 166(1):129-135.

Hunt, G. 2004. Phenotypic variation in fossil samples: modeling the consequences of time-averaging. Paleobiology 30(3):426-443.

Hunt, G. 2004. Phenotypic variance inflation in fossil samples: an empirical assessment. Paleobiology 30(4):487-506.

Hunt, G. 2003. Morphology, Shape and Phylogeny (book review). The Palaeontological Association Newsletter 54:72-76.

Hunt, G., and R. E. Chapman. 2001. Evaluating hypotheses of instar-groupings in arthropods: a maximum likelihood approach. Paleobiology 27(3):466-484