Towards a universal trait-based model of terrestrial primary production

Abstract:

Systematic variations of plant traits along environmental gradients have been observed for decades. For example, the tendencies of leaf nitrogen per unit area to increase, and of the leaf-internal to ambient CO₂ concentration ratio (c_i:c_a) to decrease, with aridity are well established. But ecosystem models typically represent trait variation based purely on empirical relationships, or on untested conjectures, or not at all. Neglect of quantitative trait variation and its adapative significance probably contributes to the persistent large uncertainties among models in predicting the response of the carbon cycle to environmental change. However, advances in ecological theory and the accumulation of extensive data sets during recent decades suggest that theoretically based and testable predictions of trait variation could be achieved.

Based on well-established ecophysiological principles and consideration of the adaptive significance of traits, we propose universal relationships between photosynthetic traits (c_i:c_a, carbon fixation capacity, and the ratio of electron transport capacity to carbon fixation capacity) and primary environmental variables, which capture observed trait variations both within and between plant functional types. Moreover, incorporating these traits into the standard model of C₃photosynthesis allows gross primary production (GPP) of natural vegetation to be predicted by a single equation with just two free parameters, which can be estimated from independent observations. The resulting model performs as well as much more complex models.

Our results provide a fresh perspective with potentially high reward: the possibility of a deeper understanding of the relationships between plant traits and environment, simpler and more robust and reliable representation of land processes in Earth system models, and thus improved predictability for biosphere-atmosphere interactions and climate feedbacks.