Estimation of intrinsic water-use efficiency from δ13C signature of C3 leaves: Assumptions and uncertainty

Carbon isotope composition (delta C-13) has been widely used to estimate the intrinsic water-use efficiency (iWUE) of plants in ecosystems around the world, providing an ultimate record of the functional response of plants to climate change. This approach relies on established relationships between leaf gas exchange and isotopic discrimination, which are reflected in different formulations of C-13-based iWUE models. In the current literature, most studies have utilized the simple, linear equation of photosynthetic discrimination to estimate iWUE. However, recent studies demonstrated that using this linear model for quantitative studies of iWUE could be problematic. Despite these advances, there is a scarcity of review papers that have comprehensively reviewed the theoretical basis, assumptions, and uncertainty of C-13-based iWUE models. Here, we 1) present the theoretical basis of C-13-based iWUE models: the classical model (iWUE(sim)), the comprehensive model (iWUE(com)), and the model incorporating mesophyll conductance (iWUE(mes)); 2) discuss the limitations of the widely used iWUE(sim) model; 3) and make suggestions on the application of the iWUE(mes) model. Finally, we suggest that a mechanistic understanding of mesophyll conductance associated effects and post-photosynthetic fractionation are the bottlenecks for improving the C-13-based estimation of iWUE.

Automated summary

Carbon isotope composition (delta C-13) is widely used to estimate the intrinsic water-use efficiency (iWUE) of plants, providing valuable insights into the functional response of plants to climate change. However, the current literature lacks comprehensive review papers on the theoretical basis, assumptions, and uncertainty of C-13-based iWUE models. This study presents different models and discusses their limitations, emphasizing the importance of understanding mesophyll conductance and post-photosynthetic fractionation for improving the accuracy of iWUE estimation.