HR: 09:15h
AN: NB41E-04 INVITED     [Abstracts]
TI: A Bayesian Approach for Combining Data Sets to Improve Estimates of Taxon Optima
AU: * Yuan, L L
EM: yuan.lester@epa.gov
AF: Office of Research and Development, US Environmental Protection Agency, 1200 Pennsylvania Ave, NW Mail code 8623N, Washington, DC 20460 United States
AU: Stockton, T
EM: stockton@neptuneinc.org
AF: Neptune and Company, 1505 15th St, Suite 6, Los Alamos, NM 87544 United States
AB: Predictions of the responses of stream ecosystems to different types of disturbance would be facilitated by accurate knowledge of the environmental preferences of different taxa. These preferences are often expressed in terms of taxon optima, or the location along an environmental gradient where a particular taxon is most likely to be observed. Several empirical methods exist for estimating taxon optima from a single data set. However, these optima estimates can be biased by the range of environmental conditions sampled within the data set and by environmental gradients that covary with the gradient of interest. Optima estimates can therefore differ between different data sets. By combining different datasets, we can potentially improve optima estimates by increasing sample sizes and better controlling for covarying gradients. Here, we present a Bayesian approach for improving optima estimates using disparate data sets. The Bayesian model provides a means of accounting for factors that are unique to each data set, while estimating a parameter (the optima) that is assumed to be fixed. We present estimates of temperature optima for several aquatic insects that were developed using different data sets. For certain taxa, this modeling approach may lead to more reliable estimates of their optima.
DE: 9810 New fields (not classifiable under other headings)
SC: North American Benthological Society [NB]
MN: 2005 Joint Assembly