Reconciling carbon isotope discrimination between leaf biomass and tree-ring to estimate water-use efficiency of global forests

The response of intrinsic water-use efficiency (iWUE) to climate change is of uncertain magnitude owing to difficulties in accounting for physiological acclimation of plants. In particular, estimations based on controlled experiments, flux towers, and isotope data had significant differences in the historical trends of iWUE. Carbon isotope discrimination () in leaf biomass (BL) and tree rings (TR) are vital indicators of how plants adjust water-carbon relations. The theory of photosynthetic 12C/13C discrimination is well-established. However, isotope fractionation downstream of photosynthesis, known as post-photosynthetic fractionation (post), also affects the 13C signature of plant tissues. The influence of post on iWUE estimation remain uncertain, limiting quantitative study of iWUE using carbon isotopes.In this study, we derived a comprehensive, based iWUE model (iWUEcom) which explicitly incorporates mesophyll conductance, photorespiratory fractionation and post. We characterized the post based on the observations of BL and online carbon isotope discrimination (online). The iWUEcom model was further validated with independent datasets of BL, TR, and leaf-level gas exchange data paired by species, years, and locations across the globe.BL was consistently larger than online. Furthermore, the paired data of BL and TR showed a near constant offset, indicating that post was different between leaf biomass and tree rings. Applying the material-specific post values, iWUE estimated from BL aligned well with that estimated from TR and gas exchange. BL and TR showed a consistent iWUE trend with an average CO2 sensitivity of 0.15 ppm ppm-1 during 1975-2015, pointing out the overestimation of the historical iWUE response by the conventional model.A process-based framework has been suggested to predict iWUE of global forest based on isotope records in leaf biomass and tree rings, providing an ultimate tool to infer changes in carbon and water cycles under historical and future climate.