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System metabolism in the Kanawha River basin: comparing two models
Citation:
Collins, S. E. AND J. E. FLOTEMERSCH. System metabolism in the Kanawha River basin: comparing two models. Presented at Association of Mid-Atlantic Aquatic Biologists Workshop, Berkeley Springs, WV, March 29 - 30, 2012.
Impact/Purpose:
The goal of this research is to develop methods and indicators that are useful for evaluating the condition of aquatic communities, for assessing the restoration of aquatic communities in response to mitigation and best management practices, and for determining the exposure of aquatic communities to different classes of stressors (i.e., pesticides, sedimentation, habitat alteration).
Description:
Resource managers and regulatory agencies typically monitor aquatic ecosystem condition using a combination of measures that describe stream structure (e.g. physical habitat variables, species richness metrics) and physiochemical properties (e.g., pH, DO, turbidity). Recently, measurements of stream ecosystem function have been advocated as a more holistic assessment approach. Ecosystem metabolism, for example, estimates gross primary productivity and community respiration and has emerged as a useful measure of overall stream health. Metabolism measurements can also provide an estimate of the energy base for the system (allochthonous vs. autochthonous). We used two models to estimate metabolism at 21 sites within the Kanawha River basin in West Virginia and Virginia during summer 2010. These models primarily use diel 02 fluctuations to establish overall metabolism. The Kanawha River basin has been previously characterized using tenets proposed by the Riverine Ecosystem Synthesis (RES) theory. The RES classified sites based on hydrogeomorphology into classes known as functional process zones (FPZs). Our sites fell within four FPZs that ranged from 3rd order streams to 6th order rivers. We analyzed results from both models using paired t-tests (for within site comparisons) and ANOVA (for between site comparisons) with stream order and FPZ used separate factors. The extent that stream metabolism can be predicted by FPZ, model efficacy, and stream order classifications will be addressed.