Abstract
Understanding of isotopic variations in leaf water is important for reconstruction of paleoclimate and assessment of global biochemical processes. We report here a study of isotopic distributions within a single needle of two pine species, Pinus resinosa Ait and Pinus strobes L., with the objective of understanding how isotopic compositions of leaf water are controlled by environmental and physiological variables. A 2D model was developed to simulate along-leaf isotopic variations and bulk leaf water isotopic compositions. In addition to variables common to all leaf water isotopic models, this 2D model also takes into account the specific geometry and dimensions of pine needles and the isotopic transport in xylem and mesophyll. The model can successfully simulate oxygen isotopic variations along a single needle and averaged over a leaf (bulk leaf water). The simulations suggest that isotopic composition of the bulk leaf water does not always depend only upon the average transpiration rate, which in turn raises questions about using leaf water isotopic values to estimate transpiration rates. An unsuccessful attempt to simulate along-needle hydrogen isotopic variations suggests that certain unknown biological process(es) may not have been incorporated into our 2D model, and if so, it calls for a reevaluation of all other models for hydrogen isotopic simulations of leaf water since they too lack these processes. Existing leaf water isotopic models are reviewed in this work. In particular, we evaluate the most frequently used model, the stomatal boundary layer model (also referred to as the Craig–Gordon model). We point out that discrepancy between the boundary layer model and the measured bulk leaf water seems to depend upon relative humidity. Using our 2D model, we show that this humidity dependency is a result of an interplay between environmental and physiological conditions: if the transpiration rate of plant leaves decreases with increasing relative humidity, our 2D model can reproduce the pattern of isotopic discrepancy between boundary layer model predictions and observations, enabling us to understand better the reason behind this discrepancy.
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