B52A-01 – The challenge of establishing decomposition functional types to estimate heterotrophic respiration at large scales (Invited)


Ben P Bond-Lamberty
Pacific Northwest National Laboratory
Daniel Epron
University of Lorraine Nancy
Jennifer W Harden
USGS Geological Survey
Mark Harmon
Oregon State University
Forrest M. Hoffman (forrest at climatemodeling dot org)
Oak Ridge National Laboratory
Jitendra Kumar
Oak Ridge National Laboratory
Anthony David McGuire
U.S. Geological Survey
Rodrigo Vargas
University of Delaware


Advancing Understanding of Ecosystem Structure and Function through Remote Sensing III
Friday, December 16, 2016 10:20–10:35
Moscone West 2006


Heterotrophic respiration (HR), the aerobic and anaerobic processes mineralizing organic matter, is a key carbon flux but one impossible to measure at large scales. This impedes our ability to understand carbon and nutrient cycles, benchmark models, or reliably upscale point measurements. Given that a new generation of highly mechanistic, genomic-specific global models is not imminent, we suggest that a useful step would be the development of “Decomposition Functional Types” (DFTs). Analogous to established plant functional types (PFTs) and proposed ecosystem functional types, DFTs would abstract and capture important differences in HR metabolism and flux dynamics, allowing modelers and experimentalists to efficiently group and vary these characteristics across space and time. DFTs should be developed using bottom-up, data-driven analyses that will depend heavily on established databases and remote sensing products. We present an example clustering analysis to show how annual HR can be broken into distinct groups associated with global variability in biotic and abiotic factors, and demonstrate that these groups are distinct from (but complementary to) already-existing PFTs. A similar analysis incorporating observational data could form the basis for future DFTs. Finally, we suggest next steps and critical priorities, all critical steps to build a foundation for DFTs in global models, thus providing the ecological and climate change communities with robust, scalable estimates of HR.

Forrest M. Hoffman (forrest at climatemodeling dot org)