Distributed Plant Hydraulic and Hydrological Modeling to Understand the Susceptibility of Riparian Woodland Trees to Drought‐Induced Mortality

Abstract

The mechanistic understanding of drought‐induced forest mortality hinges on improved models that incorporate the interactions between plant physiological responses and the spatiotemporal dynamics of water availability. We present a new framework integrating a three‐dimensional groundwater model, Parallel Flow, with a physiologically sophisticated plant model, Terrestrial Regional Ecosystem Exchange Simulator. The integrated model, Parallel Flow‐Terrestrial Regional Ecosystem Exchange Simulator, was demonstrated to quantify the susceptibility of riparian cottonwoods (Populus angustifolia, Populus deltoides, and native hybrids) in southwestern Canada to sustained atmospheric drought and variability in stream flow. The model reasonably captured the dynamics of soil moisture and evapotranspiration in both wet and dry years, including the resilience of cottonwoods despite their high vulnerability to xylem cavitation. Unrealistic predictions of mortality could be generated when ignoring lateral groundwater flow. Our results also illustrated a mechanistic linkage between streamflow and cottonwood health. In the absence of precipitation, normal streamflow could sustain 94% of cottonwoods, and higher streamflows would be required to sustain all of the floodplain cottonwoods. Further, the risk of mortality was mediated by plant hydraulic properties. These results underpin the importance of integrating groundwater processes and plant hydraulics in order to analyze the forest response to sustained severe drought, which could increase in the future due to climate change combined with increasing river water withdrawals.

Hydraulic traits that buffer deep‐rooted plants from changes in hydrology and climate

“…Opportunities to better understand the adaptive significance of hydraulic trait expression, as it relates to how phreatophytic taxa respond to groundwater depletion and changing ecohydrological conditions, may be amplified by taking advantage of cutting‐edge tools to evaluate plant stress. Recent advances in whole‐genome sequencing (Tuscan et al, ), high throughput phenotyping (Araus & Cairns, ), hyperspectral imaging of forest canopies (Asner et al, ), and coupled fluvial hydrologic/plant hydraulics modeling (Tai et al, ), among many other advances, provide emerging opportunities to rapidly evaluate and predict patterns of mortality in groundwater‐dependent vegetation exposed to groundwater depletion and climate change. Approaches that merge a broad suite of phenotypic traits with process‐based models will provide a new way forward to studying and protecting groundwater‐dependent vegetation and predicting feedbacks of vegetation change on hydrological processes.…”

“…Understanding and quantifying hydraulic trait variation across ecohydrological gradients will improve efforts to model carbon and water cycling processes of GDEs at multiple scales. Likewise, a robust (Tuscan et al, 2006), high throughput phenotyping (Araus & Cairns, 2014), hyperspectral imaging of forest canopies (Asner et al, 2017), and coupled fluvial hydrologic/plant hydraulics modeling (Tai et al, 2018), among many other advances, provide emerging opportunities to rapidly evaluate and predict patterns of mortality in groundwater-dependent vegetation exposed to groundwater depletion and climate change.…”

Coupled ecohydrology and plant hydraulics modeling predicts ponderosa pine seedling mortality and lower treeline in the US Northern Rocky Mountains

“…Experimentally determined water potential thresholds of hydraulic impairment (Choat et al ., ) have been used to map mortality risk using correlative metrics such as temperature and climatic water deficit (Williams et al ., ; Anderegg et al ., ). Alternative studies have used mechanistic models to simulate plant water potential, loss of xylem conductivity and plant carbon status to predict plant responses to drought and mortality (Mackay et al ., ; Ogée et al ., ; McDowell et al ., ; Tai et al ., , ). To reduce computational costs, mechanistic models are often run over small domains (Tai et al ., ), are forced with meteorological data that are too coarse to resolve topoclimatatic influences (McDowell et al ., ), or use terrain indices rather than fully integrated methods of addressing topographic controls on hydrology (Tai et al ., ).…”

Forecasting semi‐arid biome shifts in the Anthropocene

“…Plant hydraulic impairment, plant water potential thresholds, and the duration spent below a given threshold are known to precede plant mortality (Adams et al, 2017;McDowell et al, 2018). Therefore, models that integrate surface hydrological processes, plant hydraulic function and climate variability are expected to capture many of the elements anticipated to be important in predicting drought-induced vegetation impacts (Tai et al, 2018;Venturas et al, 2018;Mencuccini et al, 2019). A new ecophysiological framework suggests that delayed tree mortality responses to drought may be caused by the long-term carbon costs associated with xylem repair (Cailleret et al, 2017;Trugman et al, 2018).…”

“…Ecohydrological models can be very effective at predicting water flow and ecosystem-level plant growth, but a fundamental problem for these models is simulating fine-scale processes over large areas (Ratajczak et al, 2017;Wang et al, 2018;Fan et al, 2019). Recent efforts are improving fine-scale simulations of soil water availability and predictions of vegetation water stress on the landscape (Schlaepfer et al, 2017;Guo et al, 2018;Tai et al, 2018). In a recent example, Schwantes et al (2018) used a non-linear stochastic model of soil moisture that incorporated information on topography and soil type to predict water stress in Juniper across a watershed in Texas, USA (Fig.…”