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Reduced stomatal conductance is a common plant response to rising atmospheric CO₂and increases water use efficiency (W). At the leaf-scale,Wdepends on water and nitrogen availability in addition to atmospheric CO₂. In hydroclimate modelsWis a key driver of rainfall, droughts, and streamflow extremes. We used global climate data to derive Aridity Indices (AI) for forests over the period 1965–2015 and synthesised those with data for nitrogen deposition andWderived from stable isotopes in tree rings. AI and atmospheric CO₂account for most of the variance inWof trees across the globe, while cumulative nitrogen deposition has a significant effect only in regions without strong legacies of atmospheric pollution. The relation of aridity andWdisplays a clear discontinuity.Wand AI are strongly related below a threshold value of AI ≈ 1 but are not related where AI > 1. Tree ring data emphasise that effective demarcation of water-limited from non-water-limited behaviour of stomata is critical to improving hydrological models that operate at regional to global scales.

Rates of change in intrinsic water use efficiency (W) of trees relative to those in atmospheric [CO₂] (c_a) have been mostly assessed via short-term studies (e.g., leaf analysis, flux analysis) and/or step increases inc_a(e.g., FACE studies). Here we use compiled data for abundances of carbon isotopes in tree stems to show that on decadal scales, rates of change (dW/dc_a) vary with location and rainfall within the global tropics. For the period 1915–1995, and including corrections for mesophyll conductance and photorespiration,dW/dc_afor drier tropical forests (receiving ~ 1000 mm rainfall) were at least twice that of the wettest (receiving ~ 4000 mm). The data also empirically confirm theorized roles of tropical forests in changes in atmospheric¹³C/¹²C ratios (the¹³C Suess Effect). Further formal analysis of geographic variation in decade-to-century scaledW/dc_awill be needed to refine current models that predict increases in carbon uptake by forests without hydrological cost.