Water transport and storage through plants form the major pathway recycling water from the land surface back to the atmosphere. This plant hydraulic process directly affects water resources, ecosystem productivity, and plant susceptibility to drought. We build mechanistic models to describe water movement through the soil-plant-atmosphere system. Using stand-scale observations at FLUXNET sites, we study how plant hydraulics regulates transpiration under soil and atmospheric water stresses. Scaling up, we explore how microwave remote sensing products, when combined with the hydraulic model, can be used to derive plant hydraulic traits across the globe. Research along this line will facilitate better prediction of vegetation drought response and climate feedbacks models using Earth system models.
Extreme droughts threaten the stability and life of forests. Predicting drought-induced forest mortality at a large scale is particularly challenging given complex interactions among biotic-abiotic processes. We address this challenge through the viewpoint of ecosystem resilience based on nonlinear dynamical theory. We develop a Bayesian time series analysis method to track time-varying resilience using satellite images of normalized difference vegetation index. An application in Californian forests suggests reduced resilience can provide an early warning signal half to multiple years ahead and capture the spatial-temporal patterns of mortality documented in aerial surveys. The work highlights the operational potential of the early warning signal for near-term prediction, thereby opening up new possibilities for intervention and risk management of forest ecosystems.
Hydrologic variations actively shape the spatial-temporal variation of vegetation biomass. In return, hydrologic responses are also regulated by vegetation water use. We use a distributed hydrological model, which characterizes spatial hydrologic connection and surface-subsurface interactions, to estimate groundwater table in forested wetlands. This allows further investigation on how climate variation and seasonality – through hydrological processes – shape ecosystem functions, including methane emission, nutrient cycles, and vegetation distribution. Integrated analysis on vegetation-hydrology feedbacks will also help identify when and where dynamic vegetation representation can help improve water resources prediction.
Arctic shrub change
The Arctic is warming up twice as fast as the rest of the globe. Among the most prominent environmental changes with warming is enhanced shrub growth and colonization. Future climate feedbacks will depend on how quickly vegetation patterns change in response to warming, which, however, remains challenging to predict. We combine data from satellite remote sensing and field campaigns to characterize shrub change in the Arctic and identify its limiting factors among temperature, hydrological conditions, nutrient cycling, and fire disturbance. We further use the knowledge to improve the representations of Arctic vegetation dynamics and sensitivity to climate in a vegetation demographic model (ELM-FATES). Work in this direction will contribute to better understanding of Arctic ecosystem change and its global impact.