Posted on Aug 8, 2008
Workshop on Predictive Modeling Using Tree Data - For Graduate Students and Postdocs in Herpetology
AmphibiaTree, an NSF-funded consortium of biologists from Harvard University, the University of Texas, the University of Kansas, and the University of California, Berkeley, will hold a workshop on “Predictive Species Distribution Modeling Using Tree Data” on December 5-6, 2008, at UC Berkeley.
The workshop will feature 5 invited speakers and hands-on training for all participants. Its emphasis will be the creative use of phylogenetic, i. e., tree, data to reconstruct ancestral ranges, phylogeographic patterns and climate change, historical-present-future biogeographic scenarios, etc., understanding and using the latest climate data and species distribution modeling applications in a spatial context. The general format includes presentations that illustrate conceptual issues (e. g., “are niches conservative over time?”) and practical considerations (e. g., understanding climate models, data preparation and organization, model choice, implementation, and GIS execution). Workshop participants will bring a dataset to work on during hands-on sessions to learn techniques; participants can then leave the workshop with real acquaintance with the tools. We will use the GIS computer lab of the Geospatial Imaging and Informatics Facility in the College of Natural Resources at Berkeley. A summary of techniques and results will be posted on the AmphibiaTree website (http://amphibiatree.org).
We expect to fund travel and accommodation for 10 graduate students and postdocs. US and foreign/overseas students are welcome to apply. Please send your cv and a statement of your interests relevant to the workshop, and what you hope to gain from it, to David (wakelab [at] berkeley.edu) and Marvalee (mhwake [at] berkeley.edu) Wake, Museum of Vertebrate Zoology, 3101 VLSB, University of California, Berkeley, CA 94720-3160, by 15 September 2008. Participants will be notified by 1 October and provided the workshop details.