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Abstract Stomatal opening in the light, observed in nearly all vascular land plants, is essential for providing access to atmospheric CO2 for photosynthesis. The speed of stomatal opening in the light is critical for maximizing carbon gain in environments in which light intensity changes, yet we have little understanding of how other environmental signals, particularly evaporative demand driven by vapor pressure deficit (VPD) influences the kinetics of this response. In angiosperms, and some fern species from the family Marsileaceae, a mechanical interaction between the guard cells and the epidermal cells determines the aperture of the pore. Here, we examine whether this mechanical interaction influences the speed of stomatal opening in the light. To test this, we investigated the speed of stomatal opening in response to light across a range of VPDs in seven plant species spanning the evolutionary diversity of guard cell and epidermal cell mechanical interactions. We found that stomatal opening speed is a function of evaporative demand in angiosperm species and Marsilea, which have guard cell and epidermal cell mechanical interactions. Stomatal opening speeds did not change across a range of VPD in species of gymnosperm and fern, which do not have guard cell mechanical interactions with the epidermis. We find that guard cell and epidermal cell mechanical interactions may play a key role in regulating stomatal responsiveness to light. These results provide valuable insight into the adaptive relevance of mechanical advantage.
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A theoretical and empirical assessment of stomatal optimization modeling
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.
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- Award ID(s):
- 1802880
- PAR ID:
- 10401915
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- New Phytologist
- Volume:
- 227
- Issue:
- 2
- ISSN:
- 0028-646X
- Page Range / eLocation ID:
- p. 311-325
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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