Modelling organic matter dynamics in headwater streams of south-western British Columbia,Canada |
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| Institution: | 1. AF-Environmental Research Group, P.O. Box 8133, SE-104 20 Stockholm, Sweden;2. Department of Forest Sciences, 3041-2424 Main Mall, University of British Columbia, Vancouver, BC, Canada V6T 1Z4;3. National Marine Fisheries Service, Northwest Fisheries Science Center, 2725 Montlake Blvd. East, Seattle, 98112 WA, USA;1. USDA Forest Service, Rocky Mountain Research Station, 240 W. Prospect Rd., Fort Collins, CO 80526, United States;2. Post Oak Savannah Groundwater Conservation District, Milano, TX 76556, United States;1. U.S. Fish and Wildlife Service, Southeast Region Inventory and Monitoring Network, Okefenokee National Wildlife Refuge, 2700 Suwannee Canal Rd., Folkston, GA 31537, USA;2. Natural Resource Conservation LLC, 1400 Colorado Street, Boulder City, NV 89005, USA;3. School of Agricultural, Forest and Environmental Sciences, Clemson University, Clemson, SC 29634, USA;1. Department of Geosciences, National Taiwan University, Taipei, Taiwan;2. Central Geological Survey, Ministry of Economic Affairs, Taipei, Taiwan;3. Institute of Oceanography, National Taiwan University, Taipei, Taiwan;1. Department of Forest and Natural Resources Management, The State University of New York College of Environmental Science and Forestry (SUNY-ESF), 1 Forestry Drive, Syracuse, NY 13210, United States;2. Department of Environmental and Forest Biology, The State University of New York College of Environmental Science and Forestry (SUNY-ESF), 1 Forestry Drive, Syracuse, NY 13210, United States;1. Keshava Deva Malaviya Institute of Petroleum Exploration (KDMIPE), Oil and Natural Gas Corporation (ONGC), Dehradun, India;2. Gas Hydrate Research & Technology Center (GHRTC), Oil and Natural Gas Corporation (ONGC), Mumbai, India |
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| Abstract: | A mass-balance model was developed to simulate organic matter (OM) dynamics in headwater stream ecosystems of south-western British Columbia, Canada. Empirical data from two streams were used to structure and test a mass-balance model of the riparian–stream system. The model was driven by data on inputs, outputs, processing rates, discharge and water temperature. Statistical sub-models were derived for different processes (e.g. decomposition rates and periphyton growth). Inputs and outputs of OM were modelled on the basis of a series of assumptions of system properties, such as temperature and hydrological regimes. Major uncertainties identified through Monte-Carlo simulations of model predictions and variables important in controlling OM dynamics in these streams were dissolved OM (DOM) import and export, stream area and litterfall import. DOM was quantitatively the most important source of OM, accounting for 80% of total export of OM, followed by export of fine particulate organic matter (FPOM) at 15%. Different scenarios of logging and temperature regimes on the system were simulated to predict how these factors would affect standing stock of OM in the stream. When inputs of riparian litterfall were simulated to mirror reductions predicted from forest harvesting in the riparian area particulate OM (POM) standing stock was reduced by almost 80%. In comparison, a 3 °C increase in water temperature resulted in only a 20% reduction of POM standing stock due to enhanced mineralisation. |
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