Quantifying Age-Related Hydraulic and Biochemical Constraints on Tree Photosynthesis in the Southern Appalachian Mountains

Forest carbon accumulation generally declines with age, a trend largely attributed to reductions in gross primary production (GPP). However, for many species, uncertainty remains about the specific mechanisms limiting GPP. We examine both tree hydraulic and biochemical parameters affecting carbon uptake across a successional gradient in the southern Appalachian Mountains, utilizing a chronosequence approach with 5-, 10-, and 85-year old forest stands. We conducted measurements on four of the dominant species in the region: Liriodendron tulipifera, Betula lenta, Acer rubrum, and Quercus alba. To assess biochemical photosynthetic capacity, we estimated Vcmax and Jmax from over 140 gas exchange A/Ci curves. We determined that leaf gas exchange measurements performed on excised branches of A. saccharum, L. tulipifera, and Q. alba significantly underestimated assimilation by 35, 26, and 63% on average, respectively. Therefore, A/Ci measurements were performed on in situ canopy branches, using an 18 m boom lift to access the tallest trees. We examine how these photosynthetic parameters vary with age, height, and foliar nitrogen content among tree species and canopy positions. In order to investigate hydraulic factors driving stomatal behavior and therefore carbon uptake, we collected measurements of mid-day and pre-dawn leaf water potential (ψmd and ψpd) and xylem cavitation vulnerability. Preliminary results suggest that ψmd-ψpd decreases with along the chronosequence in anisohydric species, whereas ψmd-ψpd increases or remains stable with age/height in isohydric species. These data will be analyzed together with site- and species-specific hydraulic vulnerability data to assess whether the hydraulic safety margin changes with tree age/height, and explore how these patterns vary among species representing different xylem anatomies and a range of isohydric/anisohydric water management strategies. These results will provide improved estimates of common parameters in terrestrial ecosystem models, and contribute to our ability to predict carbon and water tradeoffs in a changing climate.