In the latest issue of the Journal of Forestry (Vol 110, Issue 8, pg. 448-456), Ruth Yanai, Carrie Levine, Mark Green, and John Campbell describe methods for quantifying uncertainties in forest nutrient pools and fluxes. Nutrient budgets of forest ecosystems have not historically included error analysis, in spite of the importance of uncertainty to interpretation and extrapolation of the results. Uncertainty in ecosystem budgets derives from natural variability, such as spatial and temporal uncertainty, as well as knowledge uncertainty, such as model and analytical errors. For example, in the case of nutrient content of forest biomass, the overall uncertainty would be comprised of measurement uncertainty (variation between plots), analytic uncertainty (detection limits of analytical instruments), within-model uncertainty (error in allometric equations), and between-model uncertainty (choosing which allometric equations to use). This paper uses the Hubbard Brook Experimental Forest as an example and describes approaches for quantifying uncertainty in biomass, soils, and hydrologic inputs and outputs. The results suggest that change over time may have less uncertainty than a single measurement if the measures are consistently biased, for example the use of inaccurate allometric equations or soil sampling techniques. These methods can be adapted to many other ecosystems and can have important forest management applications. Identifying the largest uncertainties in nutrient budgets allows us to direct research efforts where the need for information is greatest.
Battles Lab
Forest Ecology & Ecosystem Dynamics at the University of California, Berkeley