COS 125-5 - Quantifying Uncertainty in Ecosystem Studies (QUEST): A cross-site comparison of watershed input-output budgets

Friday, August 12, 2011: 9:20 AM
5, Austin Convention Center
Carrie R. Levine1, John L. Campbell2, Ruth D. Yanai3, Mark B. Green4, Mary Beth Adams5, Douglas A. Burns6, Donald C. Buso7, Mark E. Harmon8, Trevor Keenan9, Shannon L. LaDeau10, Gene E. Likens7, William H. McDowell11, Jordan N. Parman12, Stephen D. Sebestyen13, James Vose14 and Mark Williams12, (1)Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, CA, (2)Northern Research Station, USDA Forest Service, Durham, NH, (3)Forest and Natural Resources Management, SUNY College of Environmental Science and Forestry, Syracuse, NY, (4)Center for the Environment, Plymouth State University, Plymouth, NH, (5)Northern Research Station, USDA Forest Service, Morgantown, WV, (6)US Geologic Survey, Troy, NY, (7)Cary Institute of Ecosystem Studies, Millbrook, NY, (8)Forest Ecosystems and Society, Oregon State University, Corvallis, OR, (9)Department of Organismic and Evolutionary Biology, Harvard University, (10)Cary Insitute of Ecosystem Studies, Millbrook, NY, (11)Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH, (12)Department of Geography, University of Colorado, Boulder, CO, (13)Northern Research Station, USDA Forest Service Research, Grand Rapids, MN, (14)Coweeta Hydrologic Laboratory, USDA Forest Service Southern Research Station, Otto, NC

Quantification of uncertainty in ecosystem input-output budgets is needed for determining the significance of observed differences, analyzing trends over time, and guiding research investments by identifying which components contribute the most to the overall uncertainty. However, quantification of natural variability and model uncertainty is missing from most estimates of ecosystem budgets. The mission of QUEST (Quantifying Uncertainty in Ecosystem Studies) is to improve the quality and frequency of uncertainty analyses in ecosystem studies. Our goals are to raise consciousness about the value of uncertainty analysis, provide guidance to researchers interested in uncertainty analysis, and provide support to both developers and users of uncertainty analyses.

We are conducting a cross-site comparison of small watersheds to assess whether uncertainties in hydrologic element fluxes in precipitation and streamflow volume and chemistry arise from fundamental differences in ecosystem function across sites or in sampling or computational methods. Sources of uncertainty include the precision and accuracy of measurements, natural variation in space and time, and errors in conceptualizing or modeling the system. We are propagating the uncertainty through streamwater input-output budgets and comparing a variety of models to estimate the model uncertainty for a 10-year period at several long-term study sites throughout the US.


In a preliminary analysis of phosphorus inputs and outputs at Hubbard Brook, we used a Monte Carlo simulation with 10000 iterations and estimated an average precipitation input of 0.063 kg P ha-1 yr-1 with a 95% CI of 0.041-0.107 kg P ha-1 yr-1. We estimated an average streamflow output of 0.0067 kg P ha-1 yr-1 with a 95% CI of 0.0035-0.0102 kg P ha-1 yr-1. The difference between precipitation inputs and streamflow outputs was 0.056 kg P ha-1 yr-1 with a 95% CI of 0.034-0.098 kg P ha-1 yr-1. We are using a similar approach at six other watershed study sites (Andrews LTER, Biscuit Brook Watershed, Coweeta LTER, Fernow Experimental Forest, Luquillo LTER, Marcell Experimental Forest, and Niwot Ridge LTER) to estimate uncertainty over a ten-year period (1995-2005).

In addition to the improvement to ecosystem budgets, the results of this work have important implications for monitoring programs and the assessment of trends with environmental change. In future work, we also plan to expand this analysis to include other ecosystem measurements such as vegetation, soils, and atmospheric deposition.

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