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Title: Quantifying uncertainty in forest nutrient budgets
Author: Yanai, Ruth D.; Levine, Carrie R.; Green, Mark B.; Campbell, John L.;
Source: Journal of Forestry. 110(8): 448-456.
Publication Series: Scientific Journal (JRNL)
Description: Nutrient budgets for forested ecosystems have rarely included error analysis, in spite of the importance of uncertainty to interpretation and extrapolation of the results. Uncertainty derives from natural spatial and temporal variation and also from knowledge uncertainty in measurement and models. For example, when estimating forest biomass, researchers commonly report sampling uncertainty but rarely propagate the uncertainty in the allometric equations used to estimate tree biomass, much less the uncertainty in the selection of which allometric equations to use. Change over time may have less uncertainty than a single measurement, if the measures are consistently biased, as by the use of inaccurate allometric equations or soil sampling techniques. Quantifying uncertainty is not as difficult as is sometimes believed. Here, we describe recent progress in quantifying uncertainty in biomass, soils, and hydrologic inputs and outputs, using examples from the Hubbard Brook Experimental Forest, New Hampshire, USA.
Keywords: allometry, soil, input-output, Hubbard Brook Experimental Forest
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Yanai, Ruth D.; Levine, Carrie R.; Green, Mark B.; Campbell, John L. 2012. Quantifying uncertainty in forest nutrient budgets. Journal of Forestry. 110(8): 448-456.
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