Date of Award

Spring 2018

Project Type

Thesis

Program or Major

Natural Resources

Degree Name

Master of Science

First Advisor

Scott Ollinger

Second Advisor

Andrew Ouimette

Third Advisor

Mark Ducey

Abstract

Biomass production in forests is a key process in the global carbon (C) cycle that is strongly linked to photosynthesis and related leaf traits. Spatially, relationships among leaf traits can vary as a function of climate, soils and species composition. As modeling approaches to estimate C gain improve, the need to understand variability in leaf traits becomes increasingly important. Here, we characterized the relationship between photosynthetic capacity (Amax), foliar nitrogen and leaf mass per area (LMA) within and across species in northern hardwood and evergreen stands of the White Mountain National Forest in New Hampshire, a region that has been underrepresented in past leaf trait studies. Results were used to parameterize a forest ecosystem model (PnET) that has been widely used in the Northeast region to predict ecosystem C fluxes. Within all species, Amax was strongly and positively related to mass-based foliar percent nitrogen (%N). The observed relationship between foliar %N and Amax differed significantly from the previously used model parameterization that was based on leaf trait data from forest stands in Wisconsin, and was largely a function of differences in leaf mass per area. Using site-specific foliar %N and LMA to estimate Amax in PnET improved the estimation of GPP by 5.5% in comparison with GPP estimates derived from an eddy covariance tower.

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