Change in terrestrial ecosystem water-use efficiency over the last three decades
Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem-scale water-use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data-driven models derived from satellite observations, and process-oriented carbon cycle models. The trend of EWUE was obtained using Theil-Sen linear regression of EWUE vs. year. Apart from global mean EWUE trends, we examined the Theil-Sen linear regression slope of EWUE at the per-pixel level as well. Partial correlation provides the correlation between the interannual fluctuation in EWUE and that in each of the three climatic factors while controlling for the other two.
Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C m-2 mm-1 yr-1 under the single effect of rising CO2 (‘CO2’), climate change (‘CLIM’) and nitrogen deposition (‘NDEP’), respectively. Global patterns of EWUE trends under the different scenarios suggest that: (i) EWUE-CO2 shows global increases, (ii) EWUE-CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE-NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data-driven MTE model, however, shows a slight decline of EWUE during the same period (-0.0005 g C m-2 mm-1 yr-1), which differs from process-models (0.0064 g C m-2 mm-1 yr-1) simulations with all drivers are taken into account. We attribute this discrepancy to the fact that the non-modeled physiological effects of elevated CO2 reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data-driven model and the process-oriented models across different ecosystems. Our analyses will facilitate mechanistic understanding of the carbon-water interactions over terrestrial ecosystems under global change.