Optimization models of stomatal conductance (g ) attempt to explain observed stomatal behaviour in terms of cost--benefit tradeoffs. While the benefit of stomatal opening through increased CO uptake is clear, currently the nature of the associated cost(s) remains unclear. We explored the hypothesis that g maximizes leaf photosynthesis, where the cost of stomatal opening arises from nonstomatal reductions in photosynthesis induced by leaf water stress. We analytically solved two cases, CAP and MES, in which reduced leaf water potential leads to reductions in carboxylation capacity (CAP) and mesophyll conductance (g ) (MES). Both CAP and MES predict the same one-parameter relationship between the intercellular : atmospheric CO concentration ratio (c /c ) and vapour pressure deficit (VPD, D), viz. c /c ≈ ξ/(ξ + √D), as that obtained from previous optimization models, with the novel feature that the parameter ξ is determined unambiguously as a function of a small number of photosynthetic and hydraulic variables. These include soil-to-leaf hydraulic conductance, implying a stomatal closure response to drought. MES also predicts that g /g is closely related to c /c and is similarly conservative. These results are consistent with observations, give rise to new testable predictions, and offer new insights into the covariation of stomatal, mesophyll and hydraulic conductances.

Abstract. Separating the components of ecosystem-scale carbon exchange is crucial in order to develop better models and future predictions of the terrestrial carbon cycle. However, there are several uncertainties and unknowns related to current photosynthesis estimates. In this study, we evaluate four different methods for estimating photosynthesis at a boreal forest at the ecosystem scale, of which two are based on carbon dioxide (CO2) flux measurements and two on carbonyl sulfide (COS) flux measurements. The CO2-based methods use traditional flux partitioning and artificial neural networks to separate the net CO2 flux into respiration and photosynthesis. The COS-based methods make use of a unique 5-year COS flux data set and involve two different approaches to determine the leaf-scale relative uptake ratio of COS and CO2 (LRU), of which one (LRUCAP) was developed in this study. LRUCAP was based on a previously tested stomatal optimization theory (CAP), while LRUPAR was based on an empirical relation to measured radiation. For the measurement period 2013–2017, the artificial neural network method gave a GPP estimate very close to that of traditional flux partitioning at all timescales. On average, the COS-based methods gave higher GPP estimates than the CO2-based estimates on daily (23 % and 7 % higher, using LRUPAR and LRUCAP, respectively) and monthly scales (20 % and 3 % higher), as well as a higher cumulative sum over 3 months in all years (on average 25 % and 3 % higher). LRUCAP was higher than LRU estimated from chamber measurements at high radiation, leading to underestimation of midday GPP relative to other GPP methods. In general, however, use of LRUCAP gave closer agreement with CO2-based estimates of GPP than use of LRUPAR. When extended to other sites, LRUCAP may be more robust than LRUPAR because it is based on a physiological model whose parameters can be estimated from simple measurements or obtained from the literature. In contrast, the empirical radiation relation in LRUPAR may be more site-specific. However, this requires further testing at other measurement sites.

<p>The stomata on the leaves of terrestrial plants are a crucial pathway both in the soil-plant-atmosphere hydrological continuum and in the global carbon cycle. Stomatal optimization approaches have proven to be relevant in modelling the trade-off between carbon assimilation and water stress avoidance. In this in-depth case study, we use new optimization-based stomatal models in modelling vegetation gas exchange with the land surface model JSBACH.</p><p>The theoretical framework presented in Dewar et al. (2018) combines different optimization hypotheses and photosynthesis models to provide analytical solutions for various leaf-level state variables such as stomatal conductance and photosynthesis rate. The most successful combinations assume that plants regulate stomata as if to maximize photosynthesis at all times, and that photosynthesis is restricted by non-stomatal limitations related to water stress. In this study, we further develop the framework, which yields several promising stomatal conductance models.</p><p>We implement these stomatal models in the land surface model JSBACH, which we run for a single boreal forest site, the SMEAR II measurement station in southern Finland. The model runs are constrained with meteorological and soil moisture data and parametrized with plant properties previously measured at the site, such as xylem hydraulic conductance and photosynthetic parameters. Gross primary production and transpiration rates predicted by JSBACH under different stomatal and photosynthesis models are compared to eddy covariance measurements from SMEAR II, covering the years 2006 through 2012. The model results are also compared to each other and to those obtained using the Unified Stomatal Optimization model by Medlyn et al. (2011). The comparison is restricted to dry daytime hours in the growing season.</p><p> </p><p>References:<br>Dewar et al. 2018, <em>New Phytol. </em>217: 571–581<br>Medlyn et al. 2011, <em>Glob. Change Biol.</em> 17: 2134–2144</p>

<p>Stomatal conductance formulations are of great importance to how land surface models predict carbon assimilation and transpiration in vegetation. In this study, novel stomatal conductance formulations based on the CAP optimisation hypothesis (Dewar et al. 2018) are implemented in the land surface model JSBACH. Besides new stomatal conductance functions, the CAP framework enables a computational streamlining of the resolution of photosynthesis rate and leaf internal CO<sub>2</sub> concentration.</p><p>The formulations are based on the CAP optimisation hypothesis coupled to different photosynthesis models. Models constructed this way incorporate non-stomatal limitations to photosynthesis through the coupling of carbon assimilation to the soil-to-leaf hydraulic pathway. This entails a direct link from soil water status to stomatal conductance, photosynthesis rate and leaf internal CO<sub>2 </sub>concentration. While this construction does away with the need for some previous fitted or empirical parameters, new parameters are required to represent xylem hydraulic conductance and downregulation of photosynthesis during drought stress.</p><p>These new models are compared to the widely used USO stomatal conductance model (Medlyn et al. 2011). A standalone version of JSBACH is run for single grid cells representing two boreal Scots pine (<em>Pinus sylvestris</em>) dominated sites in Finland (Hyytiälä and Sodankylä). Climate forcing is done with FLUXNET data from 2001 through 2012 and observations are from eddy covariance measurements from the two sites.</p><p>Preliminary results indicate that some of the new formulations give reasonable results. This is very promising, since they are more detailed and theoretically robust than their semi-empirical predecessors, yet streamline the computational process.</p><p>References:<br>Dewar et al. 2018, <em>New Phytol. </em>217: 571–581<br>Medlyn et al. 2011, <em>Glob. Change Biol.</em> 17: 2134–2144</p>