Terrestrial plants remove CO2 from the atmosphere through photosynthesis, a process that is accompanied by the loss of water vapour from leaves. The ratio of water loss to carbon gain, or water-use efficiency, is a key characteristic of ecosystem function that is central to the global cycles of water, energy and carbon. Here we analyse direct, long-term measurements of whole-ecosystem carbon and water exchange. We find a substantial increase in water-use efficiency in temperate and boreal forests of the Northern Hemisphere over the past two decades. We systematically assess various competing hypotheses to explain this trend, and find that the observed increase is most consistent with a strong CO2 fertilization effect. The results suggest a partial closure of stomata-small pores on the leaf surface that regulate gas exchange-to maintain a near-constant concentration of CO2 inside the leaf even under continually increasing atmospheric CO2 levels. The observed increase in forest water-use efficiency is larger than that predicted by existing theory and 13 terrestrial biosphere models. The increase is associated with trends of increasing ecosystem-level photosynthesis and net carbon uptake, and decreasing evapotranspiration. Our findings suggest a shift in the carbon- and water-based economics of terrestrial vegetation, which may require a reassessment of the role of stomatal control in regulating interactions between forests and climate change, and a re-evaluation of coupled vegetation-climate models.

Soil moisture supply and atmospheric demand for water independently limit-and profoundly a ect-vegetation productivity and water use during periods of hydrologic stress [1][2][3][4] . Disentangling the impact of these two drivers on ecosystem carbon and water cycling is di cult 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 models 5-7 . 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 sink 8,9 . 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. Ecosystem moisture stress is often characterized by changes in soil water availability 10,11 . Declining soil moisture impedes the movement of water to evaporating sites at the soil or leaf surface 12 , reducing the surface conductance to water vapour (G S )-a key determinant of carbon and water cycling-and thereby evapotranspiration (ET). However, atmospheric demand for water, which is directly related to the atmospheric vapour pressure deficit (VPD), also affects G S and ET. Plants close their stomata to prevent excessive water loss when VPD is high [13][14][15][16] and thus, increases in VPD during periods of hydrologic stress represent an independent constraint on plant carbon uptake and water use in ecosystems.While the plant physiological community has long recognized the critical role of VPD in determining plant functioning, VPD is often overlooked in many fields of hydrologic and climate science. For example, precipitation manipulation experiments are frequently used to draw conclusions about ecosystem response to drought stress, even though VPD is unaffected by precipitation manipulation 10 . Some terrestrial ecosystem and ecohydrological models do not permit stomatal conductance to vary with atmospheric demand 5,11 . Many models designed to capture these impacts rely on empirical parameterizations for soil moisture and VPD stress that promote compensating effects and model equifinality 5 , and/or use relative humidity instead of VPD as the primary driver, with significant consequences for projections of

Deforestation in mid-to high latitudes is hypothesized to have the potential to cool the Earth's surface by altering biophysical processes [1][2][3] . In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo-sea ice feedback 4,5 . This feedback is crucial in the model predictions; without it other biophysical processes may overwhelm the albedo effect to generate warming instead 5 . Ongoing land-use activities, such as land management for climate mitigation, are occurring at local scales (hectares) presumably too small to generate the feedback, and it is not known whether the intrinsic biophysical mechanism on its own can change the surface temperature in a consistent manner 6,7 . Nor has the effect of deforestation on climate been demonstrated over large areas from direct observations. Here we show that surface air temperature is lower in open land than in nearby forested land. The effect is 0.85 6 0.44 K (mean 6 one standard deviation) northwards of 456 N and 0.21 6 0.53 K southwards. Below 356 N there is weak evidence that deforestation leads to warming. Results are based on comparisons of temperature at forested eddy covariance towers in the USA and Canada and, as a proxy for small areas of cleared land, nearby surface weather stations. Night-time temperature changes unrelated to changes in surface albedo are an important contributor to the overall cooling effect. The observed latitudinal dependence is consistent with theoretical expectation of changes in energy loss from convection and radiation across latitudes in both the daytime and night-time phase of the diurnal cycle, the latter of which remains uncertain in climate models 8 .The latitudinal gradient of land-use impact is evident in the comparison of the surface air temperature recorded at FLUXNET (www.fluxnet.ornl.gov) forest towers 9 (Supplementary Table 1 and Supplementary Fig. 1) and surface weather stations in North America (Fig. 1a). Here we use the surface stations as proxies for cleared land. In accordance with the requirement of the World Meteorological Organization, these stations are located in open grassy fields that have biophysical characteristics similar to those of open land, such as being covered by snow in northern latitudes in the winter 10 . Latitude accounts for 31% of the variations in the temperature difference DT between the forest sites and the adjacent open lands (number of site pairs n 5 37). The rate of change in DT with latitude is 20.070 6 0.010 K per degree (mean 6 one standard error, s.e., P , 0.005). At these sites, the annual net all-wave radiation R n

The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO 2 exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long-term measurements (emphasizing the period 2000-2006) from 10 forested sites within the AmeriFlux and Fluxnet-Canada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were 566-584, doi: 10.1111/j.1365-2486.2011.02562.x This article is a U.S. government work, and is not subject to copyright in the United States.Global Change Biology (2012) 18,typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over-prediction of gross ecosystem photosynthesis by +160 ± 145 g C m À2 yr À1 during the spring transition period and +75 ± 130 g C m À2 yr À1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under-predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO 2 exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately and therefore will misrepresent the seasonality and interannual variability of key biosphere-atmosphere feedbacks and interactions in coupled global climate models.