Harnessing photosynthetic C¹⁸O¹⁶O discrimination dynamics under leaf water nonsteady state to estimate mesophyll...

Mesophyll conductance (g_m) is a crucial plant trait that can significantly limit photosynthesis. Measurement of photosynthetic C¹⁸O¹⁶O discrimination (Δ¹⁸O) has proved to be the only viable means of resolving g_m in both C₃ and C₄ plants. However, the currently available methods to exploit Δ¹⁸O for g_m estimation are error prone due to their inadequacy in constraining the degree of oxygen isotope exchange (θ) during mesophyll CO₂ hydration. Here, we capitalized on experimental manipulation of leaf water isotopic dynamics to establish a novel, nonsteady state, regression-based approach for simultaneous determination of g_m and θ from online Δ¹⁸O measurements. We demonstrated the methodological and theoretical robustness of this new Δ¹⁸O-g_m estimation approach and showed through measurements on several C₃ and C₄ species that this approach can serve as a benchmark method against which to identify previously-unrecognized biases of the existing Δ¹⁸O-g_m methods. Our results highlight the unique value of this nonsteady state-based approach for contributing to ongoing efforts toward quantitative understanding of mesophyll conductance for crop yield improvement and carbon cycle modeling.