Thermal acclimation of leaf photosynthetic traits in an evergreen woodland, consistent with the coordination hypothesis

Ecosystem models commonly assume that key photosynthetic traits, such as carboxylation capacity measured at a standard temperature, are constant in time. The temperature responses of modelled photosynthetic or respiratory rates then depend entirely on enzyme kinetics. Optimality considerations, however, suggest this assumption may be incorrect. The coordination hypothesis (that Rubisco- and electron-transport-limited rates of photosynthesis are co-limiting under typical daytime conditions) predicts, instead, that carboxylation (Vcmax) capacity should acclimate so that it increases somewhat with growth temperature but less steeply than its instantaneous response, implying that Vcmax when normalized to a standard temperature (e.g. 25 °C) should decline with growth temperature. With additional assumptions, similar predictions can be made for electron-transport capacity (Jmax) and mitochondrial respiration in the dark (Rdark). To explore these hypotheses, photosynthetic measurements were carried out on woody species during the warm and the cool seasons in the semi-arid Great Western Woodlands, Australia, under broadly similar light environments. A consistent proportionality between Vcmax and Jmax was found across species. Vcmax, Jmax and Rdark increased with temperature in most species, but their values standardized to 25 °C declined. The ci : ca ratio increased slightly with temperature. The leaf N  :  P ratio was lower in the warm season. The slopes of the relationships between log-transformed Vcmax and Jmax and temperature were close to values predicted by the coordination hypothesis but shallower than those predicted by enzyme kinetics.This research was funded by the Terrestrial Ecosystem Research Network (TERN), Macquarie University and the Australian National University. Henrique Fürstenau Togashi was supported by an international Macquarie University International Research Scholarship (iMQRES). Iain Colin Prentice, Bradley John Evans, and Henrique Fürstenau Togashi were funded by the Ecosystem Modelling and Scaling Infrastructure (eMAST, part of TERN). TERN and eMAST have been supported by the Australian Government through the National Collaborative Research Infrastructure Strategy (NCRIS). Owen Atkin acknowledges the support of the Australian Research Council (DP130101252 and CE140100008)

The China plant trait database: toward a comprehensive regional compilation of functional traits for land plants

Plant functional traits provide information about adaptations to climate and environmental conditions, and can be used to explore the existence of alternative plant strategies within ecosystems. Trait data are also increasingly being used to provide parameter estimates for vegetation models. Here we present a new database of plant functional traits from China. Most global climate and vegetation types can be found in China, and thus the database is relevant for global modelling. The China Plant Trait Database contains information on morphometric, physical, chemical and photosynthetic traits from 122 sites spanning the range from boreal to tropical, and from deserts and steppes through woodlands and forests, including montane vegetation. Data collection at each site was based either on sampling the dominant species or on a stratified sampling of each ecosystem layer. The database contains information on 1215 unique species, though many species have been sampled at multiple sites. The original field identifications have been taxonomically standardized to the Flora of China. Similarly, derived photosynthetic traits, such as electron-transport and carboxylation capacities, were calculated using a standardized method. To facilitate trait-environment analyses, the database also contains detailed climate and vegetation information for each site

A test of the 'one-point method' for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis

Simulations of photosynthesis by terrestrial biosphere models typically need a specification of the maximum carboxylation rate (Vcmax). Estimating this parameter using A–Ci curves (net photosynthesis, A, vs intercellular CO2 concentration, Ci) is laborious, which limits availability of Vcmax data. However, many multispecies field datasets include net photosynthetic rate at saturating irradiance and at ambient atmospheric CO2 concentration (Asat) measurements, from which Vcmax can be extracted using a 'one-point method'.\ud \ud We used a global dataset of A–Ci curves (564 species from 46 field sites, covering a range of plant functional types) to test the validity of an alternative approach to estimate Vcmax from Asat via this 'one-point method'.\ud \ud If leaf respiration during the day (Rday) is known exactly, Vcmax can be estimated with an r2 value of 0.98 and a root-mean-squared error (RMSE) of 8.19 μmol m−2 s−1. However, Rday typically must be estimated. Estimating Rday as 1.5% of Vcmax, we found that Vcmax could be estimated with an r2 of 0.95 and an RMSE of 17.1 μmol m−2 s−1.\ud \ud The one-point method provides a robust means to expand current databases of field-measured Vcmax, giving new potential to improve vegetation models and quantify the environmental drivers of Vcmax variation

Components of leaf-trait variation along environmental gradients

•Leaf area (LA), mass per area (LMA), nitrogen per unit area (Narea) and the leaf-internal to ambient CO2 ratio (χ) are fundamental traits for plant functional ecology and vegetation modelling. Here we aimed to assess how their variation, within and between species, tracks environmental gradients. •Measurements were made on 705 species from 116 sites within a broad north–south transect from tropical to temperate Australia. Trait responses to environment were quantified using multiple regression; within- and between-species responses were compared using analysis of covariance and trait-gradient analysis. •Leaf area, the leaf economics spectrum (indexed by LMA and Narea) and χ (from stable carbon isotope ratios) varied almost independently among species. Across sites, however, χ and LA increased with mean growing-season temperature (mGDD0) and decreased with vapour pressure deficit (mVPD0) and soil pH. LMA and Narea showed the reverse pattern. Climate responses agreed with expectations based on optimality principles. Within-species variability contributed 90% for χ, with LMA and Narea intermediate. •These findings support the hypothesis that acclimation within individuals, adaptation within species and selection among species combine to create predictable relationships between traits and environment. However, the contribution of acclimation/adaptation vs species selection differs among traits

Global photosynthetic capacity is optimized to the environment

Earth system models (ESMs) use photosynthetic capacity, indexed by the maximum Rubisco carboxylation rate (Vcmax), to simulate carbon assimilation and typically rely on empirical estimates, including an assumed dependence on leaf nitrogen determined from soil fertility. In contrast, new theory, based on biochemical coordination and co-optimization of carboxylation and water costs for photosynthesis, suggests that optimal Vcmax can be predicted from climate alone, irrespective of soil fertility. Here, we develop this theory and find it captures 64% of observed variability in a global, field-measured Vcmax dataset for C3 plants. Soil fertility indices explained substantially less variation (32%). These results indicate that environmentally regulated biophysical constraints and light availability are the first-order drivers of global photosynthetic capacity. Through acclimation and adaptation, plants efficiently utilize resources at the leaf level, thus maximizing potential resource use for growth and reproduction. Our theory offers a robust strategy for dynamically predicting photosynthetic capacity in ESMs

Corrigendum to "A test of the ‘one-point method’ for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis"

Since its publication, the authors of De Kauwe et al. (2016) have drawn to our attention that there is an error in Eqn 3 in their article. The correct Eqn 3 is shown below. We apologize to our readers for this mistake. (Formula presented). The original article can be accessed via http://ezproxy.uws.edu.au/login?url=http://doi.org/10.1111/nph.1381

The validity of optimal leaf traits modelled on environmental conditions

•The ratio of leaf intercellular to ambient CO2 (χ) is modulated by stomatal conductance (gs). These quantities link carbon (C) assimilation with transpiration, and along with photosynthetic capacities (Vcmax and Jmax) are required to model terrestrial C uptake. We use optimization criteria based on the growth environment to generate predicted values of photosynthetic and water-use efficiency traits and test these against a unique dataset. •Leaf gas-exchange parameters and carbon isotope discrimination were analysed in relation to local climate across a continental network of study sites. Sun-exposed leaves of 50 species at seven sites were measured in contrasting seasons. •Values of χ predicted from growth temperature and vapour pressure deficit were closely correlated to ratios derived from C isotope (δ13C) measurements. Correlations were stronger in the growing season. Predicted values of photosynthetic traits, including carboxylation capacity (Vcmax), derived from δ13C, growth temperature and solar radiation, showed meaningful agreement with inferred values derived from gas-exchange measurements. Betweensite differences in water-use efficiency were, however, only weakly linked to the plant’s growth environment and did not show seasonal variation. •These results support the general hypothesis that many key parameters required by Earth system models are adaptive and predictable from plants’ growth environments