HR: 15:30h
AN: NB44B-01 INVITED     [Abstracts]
TI: Pulling Pattern From Pandemonium: Using Stream Community Data to Diagnose Stressors
AU: * Paul, M J
EM: mjpaul@howard.edu
AF: Howard University, Department of Biology 415 College Street NW, Washington, DC 20737
AB: Proliferation of bioassessment methods has increased knowledge about biological condition of streams in the US. Identifying degradation is only the first step; diagnosing likely causes is a harder task and community data have not traditionally been used in this process. However, the potential for taxa or even assemblage based responses to specific stressors exists. In this paper, I discuss two approaches using community assessment data for diagnosing stressors. I built RIVPACS type predictive models using the Maryland Biological Stream Survey invertebrate dataset. These models were used to identify degraded sites. These were split into primary degradation types based on land use and water chemistry data. I then compared two methods to identify taxa related to the specific stressors. The first was to ordinate community data from reference and stressor sites to identify specific taxa responses to stress, and then weigh the responses to generate stressor probabilities. The second approach used predictive model output to identify tolerance characteristics of each taxon to specific stressors. Taxa scores for each stressor were summed to score likely stressors for a site. Both approaches had advantages and disadvantages, but the predictive modeling derived scores relied on less additional analyses. Both approaches hold promise for diagnosis.
DE: 1803 Anthropogenic effects
DE: 1845 Limnology
SC: North American Benthological Society [NB]
MN: 2005 Joint Assembly