PS 86-53
Uncertainty in nutrient budgets in northern hardwood forests: Natural variation exceeds measurement error

Friday, August 14, 2015
Exhibit Hall, Baltimore Convention Center
Ruth D. Yanai, Forest and Natural Resources Management, SUNY College of Environmental Science and Forestry, Syracuse, NY
Paul J. Lilly, Spatial Informatics Group, Pleasanton, CA
Matthew A. Vadeboncoeur, Earth Systems Research Center, University of New Hampshire, Durham, NH
Steven P. Hamburg, Environmental Defense Fund, New York, NY
Joel D. Blum, Department of Geological Sciences, University of Michigan, Ann Arbor, MI
Mary A. Arthur, Department of Forestry, University of Kentucky, Lexington, KY
Carrie R. Levine, Environmental Science, Policy, and Management, University of California, Berkeley, Berkeley, CA
Kikang Bae, International Affairs Bureau, Korea Forest Service, Daejeon, Korea, Republic of (South)
Farrah Fatemi R., Environmental Studies, Saint Michael's College
Byung Bae Park, Department of Environment & Forest Resources, Chungnam National University,College of Agriculture and Life Sciences, Daejeon 305-764, Korea, Republic of (South)

Forest regrowth following harvesting is an important terrestrial carbon sink. However, it is difficult to quantify forest ecosystem budgets of Ca and other elements of interest with confidence, and the uncertainties associated with such budgets are rarely reported. Tree biomass and forest soils present different challenges: tree biomass is estimated nondestructively using allometric equations, often from other sites, and these equations are difficult to validate; soils are destructively sampled, which results in little measurement error at a point, but large sampling error in heterogeneous soil environments.  In this study, we report nutrient contents of soil and biomass pools in a northern hardwood forest from replicate plots within replicate stands in 3 age classes (14-19 yr, 26-29 yr, and > 100 yr) at the Bartlett Experimental Forest, USA. We compared variation within stands (i.e. variation among the replicate plots or soil pits in a stand) to variation between stands (i.e. variation among the replicate stands in each age class) and also compared these sources of spatial variation to the sources of uncertainty derived from allometric equations and measurement error (field measurements and laboratory analyses). We expected that measurement errors would be small compared to natural variation, using common sampling methods.


Variation in soil mass among pits within stands averaged 28% (coefficient of variation); variation among stands within an age class ranged from 9-25%.  Variation in Ca concentrations were higher yet (~50%, depending on the element and extraction type), perhaps because the depth increments contained varying proportions of genetic horizons.  To estimate nutrient contents of aboveground biomass, we propagated model uncertainty through allometric equations, and found errors ranging from 2-7%, depending on the stand.  The variation in biomass among plots within stands (6-19%) was consistently larger than the allometric uncertainties. Variability in measured nutrient concentrations of tree tissues were more variable than the uncertainty in biomass.  For calcium, CVs of concentrations in tree tissues averaged 23% (bark), 19% (foliage), 18% (branches) and 22% (wood).  For Ca content of biomass, variation among stands within an age class was 5-25%; Ca contents tripled from young to mid-aged and from mid-aged to mature stands.  Uncertainty analysis can help direct research effort to areas most in need of improvement.  In systems such as the one we studied, more intensive sampling would be the best approach to reducing uncertainty, as natural spatial variation was higher than model or measurement uncertainties.