Soil moisture supply and atmospheric demand for water independently limit—and profoundly affect—vegetation productivity and water use during periods of hydrologic stress1,2,3,4. Disentangling the impact of these two drivers on ecosystem carbon and water cycling is difficult because they are often correlated, and experimental tools for manipulating atmospheric demand in the field are lacking. Consequently, the role of atmospheric demand is often not adequately factored into experiments or represented in models5,6,7. Here we show that atmospheric demand limits surface conductance and evapotranspiration to a greater extent than soil moisture in many biomes, including mesic forests that are of particular importance to the terrestrial carbon sink8,9. Further, using projections from ten general circulation models, we show that climate change will increase the importance of atmospheric constraints to carbon and water fluxes in all ecosystems. Consequently, atmospheric demand will become increasingly important for vegetation function, accounting for >70% of growing season limitation to surface conductance in mesic temperate forests. Our results suggest that failure to consider the limiting role of atmospheric demand in experimental designs, simulation models and land management strategies will lead to incorrect projections of ecosystem responses to future climate conditions.
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We acknowledge the US Department of Energy for its support of the Ameriflux Management Project administered by Lawrence Berkeley National Lab, and for its support of the Climate Model Diagnosis and Intercomparison Project. We thank the Ameriflux site teams for sharing their data, and the individual climate modelling groups for sharing their model output. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for the Coupled Model Intercomparison Project (CMIP). K.A.N. acknowledges National Science Foundation (NSF) grant DEB 1552747. P.C.S. acknowledges NSF grants DEB 1552976 and EF 1241881. S.A.P. acknowledges NSF grant EAR 125501. L.W. acknowledges NSF grant EAR 155489. B.N.S. acknowledges support from NOAA/GFDL-Princeton University Cooperative Institute for Climate Science.
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Satellite data-driven modeling of field scale evapotranspiration in croplands using the MOD16 algorithm framework
Remote Sensing of Environment (2019)