HR: 13:30h
AN: NB43B-01 INVITED     [Abstracts]
TI: Quantitative models and strength of evidence in causal inference
AU: * Gerritsen, J
EM: jeroen.gerritsen@tetratech.com
AF: Tetra Tech, Inc., 400 Red Brook Blvd., Suite 200, Owings Mills, MD 21117 United States
AU: Bailey, J
EM: JBAILEY@wvdep.org
AF: West Virginia Department of Environmental Protection, Division of Water and Waste Management, 601 - 57th Street, Charleston, WV 25304 United States
AU: Boschen, C
EM: clint.boschen@tetratech-ffx.com
AF: Tetra Tech, Inc., 10306 Eaton Place, Suite 300, Fairfax, VA 22030 United States
AU: Burton, J
EM: june.burton@tetratech-ffx.com
AF: Tetra Tech, Inc., 10306 Eaton Place, Suite 300, Fairfax, VA 22030 United States
AU: Lowman, B
EM: blowman@wvdep.org
AF: West Virginia Department of Environmental Protection, Division of Water and Waste Management, 601 - 57th Street, Charleston, WV 25304 United States
AU: Ludwig, J
EM: jon.ludwig@tetratech-ffx.com
AF: Tetra Tech, Inc., 405 Capitol Street, Suite 809, Charleston, WV 25301 United States
AU: Wilkes, S
EM: sam.wilkes@tetratech-ffx.com
AF: Tetra Tech, Inc., 405 Capitol Street, Suite 809, Charleston, WV 25301 United States
AU: Wirts, J
EM: jwirts@wvdep.org
AF: Tetra Tech, Inc., 10306 Eaton Place, Suite 300, Fairfax, VA 22030 United States
AU: Zheng, L
EM: lei.zheng@tetratech.com
AF: Tetra Tech, Inc., 400 Red Brook Blvd., Suite 200, Owings Mills, MD 21117 United States
AB: Human activities such as mining, logging, agriculture and residential development have caused biological degradation to streams of West Virginia. Total Maximum Daily Loads (TMDLs) are being developed for all biologically-impaired streams within the state, and require causes of impairment to be identified so that pollutants can be controlled. Using a statewide dataset, we examined macroinvertebrate community response to single and multiple stressors, and applied two quantitative modeling approaches for ranking stressors. A "dirty reference" approach examined community composition in clean and predefined stressed sites, and tolerance values of individual taxa were estimated with reciprocal averaging. We integrated the empirical models of biological impairment with onsite field observations of biota, habitat, water quality, watershed observations, within a strength of evidence approach to infer causes of impairment. Candidate causes were screened to eliminate those shown not to co-occur with effects. Remaining candidate causes were ranked according to considerations of evidence within each watershed, as well as from the statewide empirical models and from other published sources. Strongest inferences were obtained where the independent predictive model agreed with within-watershed observations of stressor measures. Final stressor determinations for each watershed will be used for the development and implementation of TMDLs.
DE: 1803 Anthropogenic effects
SC: North American Benthological Society [NB]
MN: 2005 Joint Assembly