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ABSTRACT Soil water content (SWC) data are central to evaluating how soil moisture varies over time and space and influences critical plant and ecosystem functions, especially in water‐limited drylands. However, sensors that record SWC at high frequencies often malfunction, leading to incomplete timeseries and limiting our understanding of dryland ecosystem dynamics. We developed an analytical approach to impute missing SWC data, which we tested at six eddy flux tower sites along an elevation gradient in the southwestern United States. We impute missing data as a mixture of linearly interpolated SWC between the observed endpoints of a missing data gap and SWC simulated by an ecosystem water balance model (SOILWAT2). Within a Bayesian framework, we allowed the relative utility (mixture weight) of each component (linearly interpolated vs. SOILWAT2) to vary by depth, site and gap characteristics. We explored “fixed” weights versus “dynamic” weights that vary as a function of cumulative precipitation, average temperature, and time since the start of the gap. Both models estimated missing SWC data well (R² = 0.70–0.88 vs. 0.75–0.91 for fixed vs. dynamic weights, respectively), but the utility of linearly interpolated versus SOILWAT2 values depended on site and depth. SOILWAT2 was more useful for more arid sites, shallower depths, longer and warmer gaps and gaps that received greater precipitation. Overall, the mixture model reliably gap‐fills SWC, while lending insight into processes governing SWC dynamics. This approach to impute missing data could be adapted to accommodate more than two mixture components and other types of environmental timeseries. 

Summary Vulnerability to embolism varies between con‐generic species distributed along aridity gradients, yet little is known about intraspecific variation and its drivers. Even less is known about intraspecific variation in tissues other than stems, despite results suggesting that roots, stems and leaves can differ in vulnerability. We hypothesized that intraspecific variation in vulnerability in leaves and stems is adaptive and driven by aridity.We quantified leaf and stem vulnerability ofQuercus douglasiiusing the optical technique. To assess contributions of genetic variation and phenotypic plasticity to within‐species variation, we quantified the vulnerability of individuals growing in a common garden, but originating from populations along an aridity gradient, as well as individuals from the same wild populations.Intraspecific variation in water potential at which 50% of total embolism in a tissue is observed (P₅₀) was explained mostly by differences between individuals (>66% of total variance) and tissues (16%). There was little between‐population variation in leaf/stem P₅₀in the garden, which was not related to site of origin aridity. Unexpectedly, we observed a positive relationship between wild individual stem P₅₀and aridity.Although there is no local adaptation and only minor phenotypic plasticity in leaf/stem vulnerability inQ. douglasii, high levels of potentially heritable variation within populations or strong environmental selection could contribute to adaptive responses under future climate change.