Carbon isotopes and water use efficiency: sense and sensitivity

• DOI: 10.1007/s00442-007-0932-7
• Publication Date: 2008-01-25T08:52:44Z
• Authors: Ulli Seibt; Abazar Rajabi; Howard Griffiths; Joseph A. Berry
• Keywords: Water Use Efficiency; Stomatal Conductance; Water use

We revisit the relationship between plant water use efficiency and carbon isotope signatures (delta(13)C) of plant material. Based on the definitions of intrinsic, instantaneous and integrated water use efficiency, we discuss the implications for interpreting delta(13)C data from leaf to landscape levels, and across diurnal to decadal timescales. Previous studies have often applied a simplified, linear relationship between delta(13)C, ratios of intercellular to ambient CO(2) mole fraction (C (i)/C (a)), and water use efficiency. In contrast, photosynthetic (13)C discrimination (Delta) is sensitive to the ratio of the chloroplast to ambient CO(2) mole fraction, C (c)/C (a) (rather than C (i)/C (a)) and, consequently, to mesophyll conductance. Because mesophyll conductance may differ between species and over time, it is not possible to determine C (c)/C (a) from the same gas exchange measurements as C (i)/C (a). On the other hand, water use efficiency at the leaf level depends on evaporative demand, which does not directly affect Delta. Water use efficiency and Delta can thus vary independently, making it difficult to obtain trends in water use efficiency from delta(13)C data. As an alternative approach, we offer a model available at http://carbonisotopes.googlepages.com to explore how water use efficiency and (13)C discrimination are related across leaf and canopy scales. The model provides a tool to investigate whether trends in Delta indicate changes in leaf functional traits and/or environmental conditions during leaf growth, and how they are associated with trends in plant water use efficiency. The model can be used, for example, to examine whether trends in delta(13)C signatures obtained from tree rings imply changes in tree water use efficiency in response to atmospheric CO(2) increase. This is crucial for predicting how plants may respond to future climate change.