One Term, Fourteen Metrics: Why Water Use Efficiency Means Different Things to Different Scientists

Water use efficiency sounds like one of the simplest ideas in ecology: how much carbon a plant gains for each unit of water it loses. Yet a sweeping new review in Current Climate Change Reports argues that this apparent simplicity hides a deep conceptual fragmentation that is quietly complicating climate science, ecosystem modeling, and even international water policy. Paulina F. Puchi of the Italian National Research Council, Matthias Saurer of the Swiss Federal Institute for Forest, Snow and Landscape Research, and Alessio Collalti catalog no fewer than fourteen distinct formulations of the metric in current use, spanning leaf gas exchange, stable isotopes, tree rings, eddy covariance towers, satellite products, process-based models, and theoretical optimality frameworks. Their central message is provocative: water use efficiency is not a single, universally interchangeable quantity but a family of context-dependent metrics, each encoding different processes, scales, and assumptions.

The scale of the confusion is easy to quantify. A search for the term on Google Scholar returned more than 7.4 million results, with over 322,000 more in Web of Science, reflecting both enormous scientific interest and a sprawling, inconsistent literature. The concept traces back to 1913, when agricultural scientists Briggs and Shantz defined the water requirements of plants as the ratio of dry matter produced to water lost through transpiration. Since then, the term has been adopted by physiologists, isotope geochemists, ecosystem ecologists, remote sensing specialists, and Earth system modelers, each community shaping it to fit its own instruments and questions. The result is a metric whose numerical value can change dramatically depending not on the vegetation being measured, but on who is doing the measuring and how.

At the leaf level, the two most common formulations already diverge in meaning. Instantaneous water use efficiency is the ratio of net carbon assimilation to transpiration, while intrinsic water use efficiency divides assimilation by stomatal conductance to water vapor. The distinction matters because transpiration depends strongly on the vapor pressure deficit of the surrounding air, the physical driver of evaporation, whereas stomatal conductance does not. Intrinsic water use efficiency therefore strips out atmospheric demand and isolates the plant’s own regulatory behavior, which is why it can be reconstructed from carbon isotope discrimination in tree rings and used to track century-scale changes in forest physiology. But the two are not interchangeable, and the review stresses that even the familiar equivalence between intrinsic water use efficiency and the ratio of intercellular to atmospheric CO2 concentrations holds only under specific gas-exchange assumptions, such as a negligible cuticular conductance. Recent recalculations of photosynthesis measurement systems have shown that incorporating cuticular conductance and more complete transport physics can alter estimated stomatal conductance and intercellular CO2 while leaving measured fluxes unchanged, undermining naive conversions between formulations.

Perhaps the most conceptually important distinction in the review separates ratio-based metrics from optimality-based ones. Ratios like assimilation divided by transpiration describe realized carbon-water exchange, but they respond strongly to environmental conditions and say little about strategy. By contrast, the marginal water cost of carbon gain, denoted lambda and defined as the partial derivative of transpiration with respect to assimilation, emerges from the Cowan-Farquhar optimality framework, which assumes plants regulate their stomata to maximize carbon gain per unit water risk. Liang and colleagues showed that these quantities capture genuinely different aspects of plant water use, and Bonan and colleagues demonstrated that stomatal optimization schemes built on different objective functions produce different predictions of how conductance and assimilation respond to atmospheric demand. In other words, the choice of water use efficiency formulation is not a neutral act of bookkeeping; it encodes a hypothesis about how plants balance carbon against water.

This leads to an uncomfortable question: is water use efficiency even a functional trait? Following the influential definition by Violle and colleagues, a functional trait should be measurable without reference to the environment. Most water use efficiency formulations fail this test. Assimilation-to-conductance and assimilation-to-transpiration ratios shift with vapor pressure deficit, irradiance, temperature, atmospheric CO2, and soil moisture, even when the underlying plant strategy is unchanged. A rise in the metric during drought, for example, may simply reflect stomatal closure reducing water loss faster than carbon gain, without indicating improved drought tolerance or higher productivity. The authors therefore recommend treating water use efficiency as a process metric whose interpretation is always conditional on context, rather than as an environment-independent property of an organism.

The problems compound as measurements move up the hierarchy of biological organization. Ecosystem-scale water use efficiency is typically computed from gross primary productivity divided by evapotranspiration, but evapotranspiration includes soil evaporation and canopy interception alongside transpiration. Because these non-transpirational components do not respond to CO2-driven stomatal closure the way transpiration does, evapotranspiration-based ecosystem metrics tend to overestimate the sensitivity of water use efficiency to rising CO2 relative to leaf-scale intrinsic measures. Separately, because evapotranspiration exceeds transpiration, using it in the denominator deflates the absolute magnitude of the ratio. These two effects operate in opposite directions and are frequently conflated, the review warns, making explicit partitioning of transpiration from total evapotranspiration essential for sound interpretation. Where partitioning is unavailable, the evapotranspiration-based formulation remains the appropriate empirical choice, but its values cannot be compared directly with transpiration-based ones without correction.

Units and variable choices add further traps. Stomatal conductance is conventionally reported on a water vapor basis, but isotope-based and optimality-derived formulations often use a CO2 basis, related by a diffusivity factor of 1.6; mixing the two without conversion introduces a systematic 60 percent error in intrinsic water use efficiency. Denominators may be transpiration or evapotranspiration, numerators may be leaf assimilation, gross or net primary productivity, or biomass, and fluxes may be instantaneous rates or seasonal sums. Even vapor pressure deficit normalization is contested: the widely used underlying water use efficiency formulation assumes a fixed optimality exponent of 0.5, yet recent work shows this exponent varies dynamically with soil water content, atmospheric drought, and species-specific hydraulic strategies, suggesting that fixed corrections may oversimplify carbon-water coupling in water-limited ecosystems.

The methodological provenance of an estimate matters as much as its formula. Empirical measurements from gas exchange, isotopes, and eddy covariance are constrained by instrument accuracy and site conditions. Model-derived estimates depend on process representations, parameterization, and assumptions about canopy structure and physiology. Satellite products such as those from MODIS offer global coverage but infer, rather than measure, the underlying fluxes. Optimality-based approaches derive efficiency from assumed principles of plant regulation rather than observed fluxes. The review provides a comparability matrix showing which pairs of metrics can be converted directly, which require caution, and which quantify fundamentally different quantities, along with a supplementary conversion guide detailing the assumptions each translation requires.

The stakes extend well beyond academic tidiness. Water use efficiency is embedded in United Nations Sustainable Development Goal Target 6.4 and its Indicator 6.4.1, with the Food and Agriculture Organization as custodian, tying the metric directly to global water management and food security. Under climate change, rising CO2, warming temperatures, and intensifying drought are altering plant carbon-water dynamics across every biome, and recent studies suggest that increases in intrinsic water use efficiency do not necessarily translate into higher productivity, because the relationship depends on hydroclimatic constraints and hydraulic limitations. The authors propose standardized reporting practices, including stating the exact formula, the temporal and spatial scales, the units, whether vapor pressure deficit normalization was applied, and the transpiration fraction of evapotranspiration. Their glossary assigns unique names and abbreviations to each of the fourteen metrics, reserving prefixes and suffixes to signal conductance basis, scale, and provenance. The goal, they emphasize, is not to eliminate methodological diversity but to make it explicit, traceable, and scientifically interpretable, so that a number labeled water use efficiency finally means the same thing to the physiologist, the modeler, and the policymaker reading it.

Subject of Research: Reconciling divergent definitions and formulations of water use efficiency in plant and ecosystem science

Article Title: One Metric, Many Meanings: Reconciling Water Use Efficiency Definitions

Article References: One Metric, Many Meanings: Reconciling Water Use Efficiency Definitions. (n.d.). https://doi.org/10.1007/s40641-026-00210-z

Image Credits: AI Generated

DOI: 10.1007/s40641-026-00210-z

Keywords: water use efficiency, intrinsic water use efficiency, stomatal conductance, transpiration, evapotranspiration, carbon-water coupling, stable isotopes, eddy covariance, stomatal optimization, vapor pressure deficit, functional traits, climate change