Global patterns of leaf traits based on optimality theory

Plant functional traits are a key component of land vegetation models. We present global maps of specific leaf area (SLA) and leaf nitrogen content (N) by mass and area, derived from optimality principles. Leaf N per unit area (N_area) is proposed to be determined primarily by the amount of leaf tissue (is related to LMA = 1/SLA) and its metabolic activity (is related to  carboxylation capacity at 25˚C, known as V_cmax,25). SLA is predicted via optimality hypothesis that LMA maximizes average net carbon over the life cycle of the leaf, with separate calculations for evergreen and deciduous plant types. Global maps then use a remote sensing-based land cover product to assign fractional coverage of each type. V_cmax,25  is predicted via the coordination hypothesis, which posits that V_cmax under current growth conditions tends towards a value that balances the Rubisco- and electron transport-limited rates of photosynthesis.  Predicted trait values are compared to in-situ observations, showing good agreement for all three traits. Predicted global distributions are further compared with recently developed, data-based global trait maps. This research indicates how an optimality perspective can help to improve our understanding of vegetation functional diversity and ecosystem function, and potentially enhance vegetation models.