4.4 Article

Variability in aboveground carbon driven by slope aspect and curvature in an eastern deciduous forest, USA

Journal

CANADIAN JOURNAL OF FOREST RESEARCH
Volume 47, Issue 2, Pages 149-158

Publisher

CANADIAN SCIENCE PUBLISHING
DOI: 10.1139/cjfr-2016-0147

Keywords

aboveground net primary productivity; basal area; litterfall; Quercus; Acer; Carya

Categories

Funding

  1. National Science Foundation [EAR 07-25019, EAR 12-39285, EAR 13-31726]
  2. Penn State College of Agriculture Sciences, Department of Ecosystem Science and Management
  3. Division Of Earth Sciences
  4. Directorate For Geosciences [1331726] Funding Source: National Science Foundation

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In forested ecosystems, topography and tree species contribute to spatial variability in carbon (C) dynamics through differential rates of C uptake and storage; therefore, estimates of species-specific and spatial variability in C can strengthen ecosystem budgets. To produce such estimates, we deconstructed watershed-scale C and component pools (e.g., wood biomass, litter) and fluxes at a fine scale using a small mixed deciduous forest catchment to determine the variation due to topographic position and species. Factors affecting fluxes included aspect, slope curvature, tree species contributions, and litter production. Annual C uptake into wood varied across the catchment from 0 to 34 kg C . year(-1) and was 20% greater on southern aspects than northern ones and 33% greater in swales than non-swale slopes. Of the more than 20 tree species found in the forest canopy of the catchment, highest C uptake in woody biomass was measured in Quercus rubra L. growing in swales, followed by Quercus prinus L. syn. growing on the southern aspect, with the lowest aboveground wood increment measured in Pinus at higher elevations on non-swale slopes. Quercus leaf litter moved from where it dropped into litter traps to where it settled on the forest floor, shifting the location of litter C inputs to the soil. Local variation in aboveground C rivals regional variation across regions and has the potential to introduce error when scaling C measures from points to landscapes.

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