How vertical patterns in leaf traits shift seasonally and the implications for modeling canopy photosynthesis in a temperate deciduous forest

Document Type

Article

Publication Date

9-1-2016

Abstract

© 2016 The Author 2016. Published by Oxford University Press. All rights reserved. Leaf functional traits are used in modeling forest canopy photosynthesis (Ac) due to strong correlations between photosynthetic capacity, leaf mass per area (LMA) and leaf nitrogen per area (Narea). Vertical distributions of these traits may change over time in temperate deciduous forests as a result of acclimation to light, which may result in seasonal changes in Ac. To assess both spatial and temporal variations in key traits, we measured vertical profiles of Narea and LMA from leaf expansion through leaf senescence in a sugar maple (Acer saccharum Marshall) forest. To investigate mechanisms behind coordinated changes in leaf morphology and function, we also measured vertical variation in leaf carbon isotope composition (δ13C), predawn turgor pressure, leaf water potential and osmotic potential. Finally, we assessed potential biases in Ac estimations by parameterizing models with and without vertical and seasonal Narea variations following leaf expansion. Our data are consistent with the hypothesis that hydrostatic constraints on leaf morphology drive the vertical increase in LMA with height early in the growing season; however, LMA in the upper canopy continued to increase over time during light acclimation, indicating that light is primarily driving gradients in LMA later in the growing season. Models with no seasonal variation in Narea overestimated Ac by up to 11% early in the growing season, while models with no vertical variation in Narea overestimated Ac by up to 60% throughout the season. According to the multilayer model, the upper 25% of leaf area contributed to over 50% of Ac, but when gradients of intercellular CO2, as estimated from δ13C, were accounted for, the upper 25% of leaf area contributed to 26% of total Ac. Our results suggest that ignoring vertical variation of key traits can lead to considerable overestimation of Ac.

Publication Title

Tree Physiology

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