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The Craig–Gordon type (C–G) leaf water isotope enrichment models assume a homogeneous distribution of enriched water across the leaf surface, despite observations that Δ18O can become increasingly enriched from leaf base to tip. Datasets of this 'progressive isotope enrichment' are limited, precluding a comprehensive understanding of (a) the magnitude and variability of progressive isotope enrichment, and (b) how progressive enrichment impacts the accuracy of C–G leaf water model predictions. Here, we present observations of progressive enrichment in two conifer species that capture seasonal and diurnal variability in environmental conditions. We further examine which leaf water isotope models best capture the influence of progressive enrichment on bulk needle water Δ18O. Observed progressive enrichment was large and equal in magnitude across both species. The magnitude of this effect fluctuated seasonally in concert with vapour pressure deficit, but was static in the face of diurnal cycles in meteorological conditions. Despite large progressive enrichment, three variants of the C–G model reasonably successfully predicted bulk needle Δ18O. Our results thus suggest that the presence of progressive enrichment does not impact the predictive success of C–G models, and instead yields new insight regarding the physiological and anatomical mechanisms that cause progressive isotope enrichment. Δ18O of needle water in two conifer species was drastically enriched down the length of the needle, the magnitude of which was driven by seasonal increases in VPD. Despite this progressive enrichment, traditional Craig‐Gordon model variants successfully predicted bulk needle water Δ18O. [ABSTRACT FROM AUTHOR]

Stomatal regulation presumably evolved to optimize CO2 for H2O exchange in response to changing conditions. If the optimization criterion can be readily measured or calculated, then stomatal responses can be efficiently modelled without recourse to empirical models or underlying mechanism. Previous efforts have been challenged by the lack of a transparent index for the cost of losing water. Yet it is accepted that stomata control water loss to avoid excessive loss of hydraulic conductance from cavitation and soil drying. Proximity to hydraulic failure and desiccation can represent the cost of water loss. If at any given instant, the stomatal aperture adjusts to maximize the instantaneous difference between photosynthetic gain and hydraulic cost, then a model can predict the trajectory of stomatal responses to changes in environment across time. Results of this optimization model are consistent with the widely used Ball-Berry-Leuning empirical model ( r2 > 0.99) across a wide range of vapour pressure deficits and ambient CO2 concentrations for wet soil. The advantage of the optimization approach is the absence of empirical coefficients, applicability to dry as well as wet soil and prediction of plant hydraulic status along with gas exchange. [ABSTRACT FROM AUTHOR]