Chloroplasts to canopies: Analysis of leaf spectral trait variability across spatial scales

Alexey N Shiklomanov, Boston University, ashiklom@bu.edu (Presenter)
Michael Dietze, Boston University, dietze@bu.edu
Philip Townsend, University of Wisconsin, ptownsend@wisc.edu
Shawn Paul Serbin, Brookhaven National Laboratory, sserbin@bnl.gov

Leaves are the primary pathway for exchanges of energy, water, and carbon between plants and their environment. Constraining leaf traits in models is necessary to improve representation of many ecosystem processes, including primary production, interspecies competition, and water and energy fluxes between the soil, vegetation, and atmosphere. Understanding the scales that dominate the variability in leaf traits is the first step to identifying the processes that drive this variability and for directing future research in plant physiology and forest ecology. In this project, we investigate the variability in leaf structure and biochemistry using a novel Bayesian inversion of the PROSPECT-4 leaf optical properties model. We focus on spectral data because it is easy and fast to collect in-situ, and in the long term, provides an important link to remote sensing. The Bayesian approach has two distinct advantages: First, Bayesian parameter estimates are not point estimates but joint probability distributions, wherein important information about uncertainty, covariance, and skewness is implicitly embedded. Second, this approach accommodates prior information independent of the data at hand. Prior constraints on our inversion model parameters were obtained from literature review of past inversion studies. We obtained leaf reflectance and transmittance spectra and biochemistry data (e.g. d15N, LMA, and water content) from 12 forested ecosystems in the Mid-Atlantic and Upper Midwest USA. We observed that leaf water content and LMA correlate very tightly with their spectral counterparts for hardwoods and to a lesser extent for conifers. Furthermore, we found that interspecies differences explain less variability in traits than differences between individual leaves. In particular, we idntified relative position within a canopy was a critical source of leaf trait variability for hardwoods. These results have important implications for simulation of energy fluxes and physiological processes in ecosystem models.

Presentation Type:  Plenary Talk

Session:  Poster Speed Talks

Presentation Time:  Tue 4:30 PM  (1 minutes)