Leaf traits and associated ecosystem characteristics across subtropical and timberline forests in the Gongga Mountains, Eastern Tibetan Plateau
- 10 November 2004
- journal article
- research article
- Published by Springer Nature in Oecologia
- Vol. 142 (2) , 261-273
- https://doi.org/10.1007/s00442-004-1729-6
Abstract
Knowledge of how leaf characteristics might be used to deduce information on ecosystem functioning and how this scaling task could be done is limited. In this study, we present field data for leaf lifespan, specific leaf area (SLA) and mass and area-based leaf nitrogen concentrations (Nmass, Narea) of dominant tree species and the associated stand foliage N-pool, leaf area index (LAI), root biomass, aboveground biomass, net primary productivity (NPP) and soil available-N content in six undisturbed forest plots along subtropical to timberline gradients on the eastern slope of the Gongga Mountains. We developed a methodology to calculate the whole-canopy mean leaf traits to include all tree species (groups) in each of the six plots through a series of weighted averages scaled up from leaf-level measurements. These defined whole-canopy mean leaf traits were equivalent to the traits of a leaf in regard to their interrelationships and altitudinal trends, but were more useful for large-scale pattern analysis of ecosystem structure and function. The whole-canopy mean leaf lifespan and leaf Nmass mainly showed significant relationships with stand foliage N-pool, NPP, LAI and root biomass. In general, as elevation increased, the whole-canopy mean leaf lifespan and leaf Narea and stand LAI and foliage N-pool increased to their maximum, whereas the whole-canopy mean SLA and leaf Nmass and stand NPP and root biomass decreased from their maximum. The whole-canopy mean leaf lifespan and stand foliage N-pool both converged towards threshold-like logistic relationships with annual mean temperature and soil available-N variables. Our results are further supported by additional literature data in the Americas and eastern China.Keywords
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