[Biology-U-L] Mapping Ancient Forests

[Biology Undergraduate List]

We are pleased to announce that Christopher Paciorek will be presenting 
a seminar onWednesday, February 13, 2008 3:15pm (Refreshments will be 
served at 3pm) in the Sobel Seminar Room which is located in the 
Statistics Department in South Hall 5607F.


Mapping Ancient Forests: Bayesian Inference for Forest Composition Using 
the Fossil Pollen Proxy Record

Ecologists are interested in understanding changes in tree species 
abundances and spatial distributions over       thousands of years since 
the last glacial maximum. To    estimate forest composition and 
investigate how much  information is available from fossil pollen 
deposited in lake sediments, we build a Bayesian spatio-temporal 
hierarchical model that predicts forest composition in southern New 
England, USA, based on fossilized pollen. The critical relationships 
between abundances of taxa in the pollen record and abundances in actual 
vegetation are estimated using modern data and data from colonial 
records, for which both pollen and direct vegetation data are available. 
For these time periods, the model relates pollen and vegetation data to 
a latent multivariate spatial process representing forest composition, 
which allows estimation of several key parameters.  For time periods in 
the past, we use only pollen data and the estimated model parameters to 
make predictions and assess uncertainty about the latent spatio-temporal 
process over the last 2000 years.  A new graphical assessment of feature 
significance helps to infer which spatial patterns are reliably 
estimated.  The modeling involves a complex hierarchical model that 
integrates disparate data sources. I will discuss a variety of issues 
arising in such models and the practical strategies we used to address 
them.  I will also emphasize the importance of understanding which 
aspects of the data inform which aspects of the model.