EARLY HEARING DETECTION AND INTERVENTION VIRTUAL CONFERENCE
MARCH 2-5, 2021
(Virtually the same conference, without elevators, airplane tickets, or hotel room keys)
6/05/2017 | 10:15 AM - 10:30 AM | EVALUATING SPATIAL AND TEMPORAL VARIATION OF ORGANIC-MATTER DECOMPOSITION TO ASSESS STREAM ‘HEALTH’ | 306A
EVALUATING SPATIAL AND TEMPORAL VARIATION OF ORGANIC-MATTER DECOMPOSITION TO ASSESS STREAM ‘HEALTH’
Organic-matter decomposition has been proposed as an integrative measure to detect human impacts to streams and rivers. However, fundamental information is lacking about spatial and temporal variation in decomposition rates among reference streams, which can limit the sensitivity of decomposition assays. In response, we evaluated among-stream and interannual variation in organic-matter decomposition in 26 reference streams in Michigan’s Upper Peninsula (USA) for 7 consecutive years (~182 stream-years) using the cotton-strip assay. Significant variation in decomposition rates (as percent tensile-strength loss of standardized cotton fabric) was observed among streams and among years. These spatial and temporal factors explained a similar and considerable amount of variation on a per-stream and per-year basis. Contrary to expectations, analyses of temperature-corrected decomposition rates did not reduce a large amount of variation among streams or years. Best subsets regression with environmental data from each stream, from a single year, indicated that variability in nutrient concentrations among streams, especially phosphorus and nitrogen, may contribute to variation in decomposition rates. By quantifying and assessing background variation, we hope to help develop a sensitive, reliable, and easy-to-use tool for assessing human impacts to stream ecosystems.
- C17 Bioassessment
- C31 Organic Matter Processing
- C31 Organic Matter Processing
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Presenters/Authors
Emily Messick
(), Dept. of Biological Sciences, Oakland University, elmessic@oakland.edu;
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Scott Tiegs
(), Dept. of Biological Sciences, Oakland University, tiegs@oakland.edu;
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Mark Isken
(), Dept. of Decision and Information Sciences, School of Business Administration, Oakland University, isken@oakland.edu;
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