Drought-induced stomatal closure rising canopy temperature observed from space
Historically many studies have investigated plant physiological responses to water limitation on individual trees or communities at local scales. Studies of these responses at landscape to regional scales consider air temperature, vegetation or moisture indices, but do not put them together. Additionally, most efforts have been applied to detection of drought effects in croplands and grasslands where land cover response to drought is fast. In forests, assessment of water use is critical to determine trees survival and growth rate over time. In this study we combined ground observations of climate data, field measurements of sap flux, and remotely sensed canopy surface temperature and spectral reflectance data to predict daily canopy water use. We use a Bayesian hierarchical approach to predict canopy water use from 1) atmospheric demand estimated from climate data, 2) stomata status determined by surface temperature; and 3) forest health interpreted from spectral reflectance. This new technique helps us to address three questions: how well canopy water use could be monitored using space-borne remote sensing techniques, how foliar physiological response to water shortage affects reflectance of radiation outside the visible range, and how canopy energy budgets are influenced by water limitation.
The results show agreements between model predictions and ground observations of sap flow from the years 2011 to 2014 at the Duke Forest, NC. Declines in sap flux are identified as declines in the near-infrared to red ratio, causing a moderate (~10%) decrease in the enhanced vegetation index. When water is available and the rate of sap flux is high, canopy surface temperature remains about 1 °C cooler than air temperature. During drought, low water use results in up to 2.4 °C increase in canopy surface temperature above air temperature. This response is consistent with drought induced stomatal closure resulting in an increase in canopy sensible heat. These techniques could be used in natural resource managements to assess vulnerability of ecosystems to predicted climate changes.