Tue, Aug 03, 2021:On Demand
Background/Question/Methods
Global evapotranspiration (ET) has increased in the last decades as a consequence of global warming. Changes in ET affect the frequency and severity of droughts and can compromise future water resources availability. To act accordingly, we need studies that integrate fine‐scaled mechanisms with broad‐scale patterns to provide reliable forecasts of how ecosystem-atmosphere exchange of water occurs on a large scale. While the contribution of forest ecosystems to the hydrological cycle through ET is well-documented, factors controlling the stability of their response to drought, i.e., ET stability, are still poorly understood. Here, we leverage a continuous satellite-derived ET data set to advance our knowledge on the stability of forest ET on a regional scale. Specifically, we aimed at identifying what environmental factors correlate with the magnitude (resistance) and recovery time (resilience) of ET positive extreme anomalies. We processed ~ 20 million forest pixels to assess trajectories of ET anomalies over 275 watersheds across the contiguous US from 2003 to 2017. We applied a Bayesian modeling approach to identify what long-term climatic factors and drought-related variables best predict forest ET stability.
Results/Conclusions We found a longitudinal pattern mostly driven by water availability and forest type, with more resistant but less resilient forests in the south and north-east than in the west. Our best model for resistance (R2 = 0.75) predicted a negative influence of winter-fall snow cover at low altitude, which became positive as elevation increased. ET resistance was higher in watersheds with abundant deciduous forests, while spring rainfall and soil moisture favored resistance, particularly in western and north-central ecoregions. Regarding ET resilience, our best model (MAE improvement by 66.2%) predicted that forests located in dry areas with high winter-fall snow cover, inter-annual rainfall seasonality, and deciduous forest cover recover faster after drought events. Overall, disturbance-related variables, such as frequency, duration, or intensity of droughts showed a minor influence on ET stability. This study provides important insights on how climatic stressors impact ecosystem-atmosphere exchange of water by 1) integrating the response of forest ecosystems at the watershed level and drawing the spatial pattern of ET stability on a regional scale, and 2) identifying what environmental factors best predict forests vulnerability to water loss and therefore, may have more permanence risk. These outcomes will be critical to assess forest water ecosystem services under future climate scenarios.
Results/Conclusions We found a longitudinal pattern mostly driven by water availability and forest type, with more resistant but less resilient forests in the south and north-east than in the west. Our best model for resistance (R2 = 0.75) predicted a negative influence of winter-fall snow cover at low altitude, which became positive as elevation increased. ET resistance was higher in watersheds with abundant deciduous forests, while spring rainfall and soil moisture favored resistance, particularly in western and north-central ecoregions. Regarding ET resilience, our best model (MAE improvement by 66.2%) predicted that forests located in dry areas with high winter-fall snow cover, inter-annual rainfall seasonality, and deciduous forest cover recover faster after drought events. Overall, disturbance-related variables, such as frequency, duration, or intensity of droughts showed a minor influence on ET stability. This study provides important insights on how climatic stressors impact ecosystem-atmosphere exchange of water by 1) integrating the response of forest ecosystems at the watershed level and drawing the spatial pattern of ET stability on a regional scale, and 2) identifying what environmental factors best predict forests vulnerability to water loss and therefore, may have more permanence risk. These outcomes will be critical to assess forest water ecosystem services under future climate scenarios.