The impact of alternative trait‐scaling hypotheses for the maximum photosynthetic carboxylation rate (V_cmax) on global gross primary production

Abstract

The maximum photosynthetic carboxylation rate (V ) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr , 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V variation in the field, particularly in northern latitudes.

Model parameterization to represent processes at unresolved scales and changing properties of evolving systems

“…Many other studies have also indicated that the predictive skills of models have been greatly improved if parameter values are linked to climate, vegetation, and edaphic properties. For example, the maximum rate of Rubisco activity varies with mean climate (Smith et al, ), leaf chlorophyll content (Luo et al, ), and leaf nitrogen (Walker et al, ). Similarly, global variation in inherent water use efficiency is significantly correlated with mean precipitation (Franks et al, ).…”

Global photosynthetic capacity is optimized to the environment

“…This approach was shown to perform well in a comparison of several model formulations (Walker et al . ). However, there are several important limitations to the N‐supply approach for predicting V cmax .…”

Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests

“…In the most widely used model of photosynthesis, the rate of CO 2 assimilation is determined by the maximum carboxylation rate of the enzyme Rubisco (V c,max ), the rate of RuBP regeneration through electron transport, and in some models, the utilization of triose phosphates (Farquhar et al, 1980;Sharkey et al, 2007). The V c,max25 , which is V c,max standardized to a reference temperature of 25°C (Bernacchi et al, 2013), is a key parameter at the heart of many ESMs, and variation in this parameter has repeatedly been shown to be the source of a large fraction of overall model uncertainty (Bonan et al, 2011;Rogers, 2014;Rogers et al, 2017a;Walker et al, 2017;Ricciuto et al, 2018). Accurate and comprehensive observations of the biogeography, ecology and overall distribution of V c,max25 are thus a critical research need for improving understanding of and model predictions for photosynthesis at local, regional and global scales.…”