A theoretical and empirical assessment of stomatal optimization modeling

Abstract

Summary Optimal stomatal control models have shown great potential in predicting stomatal behavior and improving carbon cycle modeling. Basic stomatal optimality theory posits that stomatal regulation maximizes the carbon gain relative to a penalty of stomatal opening. All models take a similar approach to calculate instantaneous carbon gain from stomatal opening (the gain function). Where the models diverge is in how they calculate the corresponding penalty (the penalty function). In this review, we compare and evaluate 10 different optimization models in how they quantify the penalty and how well they predict stomatal responses to the environment. We evaluate models in two ways. First, we compare their penalty functions against seven criteria that ensure a unique and qualitatively realistic solution. Second, we quantitatively test model against multiple leaf gas‐exchange datasets. The optimization models with better predictive skills have penalty functions that meet our seven criteria and use fitting parameters that are both few in number and physiology based. The most skilled models are those with a penalty function based on stress‐induced hydraulic failure. We conclude by proposing a new model that has a hydraulics‐based penalty function that meets all seven criteria and demonstrates a highly predictive skill against our test datasets.

On the inter‐ and intra‐annual variability of ecosystem evapotranspiration and water use efficiency of an oak savanna and annual grassland subjected to booms and busts in rainfall

“…We evaluated water use efficiency as the slope of the regression between daily integrated canopy carbon assimilation and transpiration (dA c /dE T ). We prefer this approach because it provides insights on water use for carbon gain (Cowan & Farquhar, 1977;Makela et al, 1996;Medlyn et al, 2011;Wang et al, 2020) at the ecosystem scale. To evaluate the relationship between water use efficiency and vapor pressure deficit, we binned the data into ten humidity deficit classes and evaluated the slope between A c and E T for each class.…”

A revised dry deposition scheme for land–atmosphere exchange of trace gases in ECHAM/MESSy v2.54

“…Dry deposition of trace gases to vegetation is calculated according to the multiple resistance scheme by Wesely (1989) shown in Fig. 1.…”

“…which consists of the soil resistance (R s,soil (X)), the incanopy aerodynamic resistance (R can ) (as in Kerkweg et al, 2006) and the leaf resistance (R leaf (X)). The gas uptake by leaves (leaf) can be separated in two parallel pathways: the cuticular (cut) and the stomatal (stom) with its associated mesophilic pathway (mes), where the latter has negligible resistance for ozone and highly soluble species (Wesely, 1989).…”

“…For highly reactive species (s reac = 1), the same property as for ozone is assumed (second term in Eq. 13), while for less reactive species (s reac = 0.1, 0) the uptake is effectively reduced (Wesely, 1989). For soluble species, the uptake at wet skin is assumed to be similar to the one of sulfur dioxide and is calculated as…”

“…Of particular interest are stomatal optimization models which, based on ecophysiological processes, maximize carbon gain while minimizing water loss. According to Wang et al (2020), these models are promising in representing stomatal behaviour and improving carbon cycle modelling. Non-stomatal deposition has been less investigated by now; therefore, most models use predefined constant resistances or scale it with leaf area index (e.g.…”