Liu et al., 2018

Talk/Poster

Synergistic data analytics and physical modeling for improved understanding of vegetation dynamics under climatological stress: a key uncertainty in ecosystem management

Liu, Y., M. Kumar, G.G. Katul, A. Parolari, A.M. Porporato, C.-W. Huang, A. Konings (2018)
American Geophysical Union 2018 Fall Meeting, Washington, DC, 10-14 Dec 2018  

Abstract

Vegetation serves as a dynamical filter of water and carbon fluxes between land and the atmosphere. Under climatological stress, water budget partitioned by vegetation across the soil-plant-atmosphere continuum and other ecosystem functions can be highly uncertain, in part due to alteration in hydraulic traits, adaptations, and mortality. The inherent uncertainties pose challenge for ecosystem and natural resources management, and is likely to have even greater ramifications under a warming climate with higher probability of extreme drought events.

This talk will focus on the need for improved understanding of vegetation dynamics under climatological stress. I will specifically discuss the need to develop (a) assessment metrics that capture forest mortality risk; (b) an early warning signal for forest mortality; and (c) an improved understanding of plant physiological responses (e.g., water and gas exchanges) under climatological stress. The accomplished and ongoing research will support ecosystem management and risk assessment related to extreme climate events and natural resources.

Citation

Liu, Y., M. Kumar, G.G. Katul, A. Parolari, A.M. Porporato, C.-W. Huang, A. Konings (2018): Synergistic data analytics and physical modeling for improved understanding of vegetation dynamics under climatological stress: a key uncertainty in ecosystem management. American Geophysical Union 2018 Fall Meeting, Washington, DC, 10-14 Dec 2018.

This Paper/Book acknowledges NSF CZO grant support.