B53B-0544
Linking vegetation structure, function and physiology through spectroscopic remote sensing
Friday, 18 December 2015
Poster Hall (Moscone South)
Shawn Serbin1,2, Aditya Singh3, John J Couture4, Alexey N Shiklomanov5, Alistair Rogers2, Ankur R Desai3, Eric L Kruger4 and Philip A Townsend6, (1)Stony Brook University, Ecology and Evolution, Stony Brook, NY, United States, (2)Brookhaven National Laboratory, Biological, Environmental & Climate Sciences, Upton, NY, United States, (3)University of Wisconsin Madison, Madison, WI, United States, (4)University of Wisconsin-Madison, Forest and Wildlife Ecology, Madison, WI, United States, (5)Boston University, Boston, MA, United States, (6)University of Wisconsin, Madison, WI, United States
Abstract:
Terrestrial ecosystem process models require detailed information on ecosystem states and canopy properties to properly simulate the fluxes of carbon (C), water and energy from the land to the atmosphere and assess the vulnerability of ecosystems to perturbations. Current models fail to adequately capture the magnitude, spatial variation, and seasonality of terrestrial C uptake and storage, leading to significant uncertainties in the size and fate of the terrestrial C sink. By and large, these parameter and process uncertainties arise from inadequate spatial and temporal representation of plant traits, vegetation structure, and functioning. With increases in computational power and changes to model architecture and approaches, it is now possible for models to leverage detailed, data rich and spatially explicit descriptions of ecosystems to inform parameter distributions and trait tradeoffs. In this regard, spectroscopy and imaging spectroscopy data have been shown to be invaluable observational datasets to capture broad-scale spatial and, eventually, temporal dynamics in important vegetation properties. We illustrate the linkage of plant traits and spectral observations to supply key data constraints for model parameterization. These constraints can come either in the form of the raw spectroscopic data (reflectance, absorbtance) or physiological traits derived from spectroscopy. In this presentation we highlight our ongoing work to build ecological scaling relationships between critical vegetation characteristics and optical properties across diverse and complex canopies, including temperate broadleaf and conifer forests, Mediterranean vegetation, Arctic systems, and agriculture. We focus on work at the leaf, stand, and landscape scales, illustrating the importance of capturing the underlying variability in a range of parameters (including vertical variation within canopies) to enable more efficient scaling of traits related to functional diversity of ecosystems.
