Abstract:
Heterotrophic respiration (HR), the aerobic and anaerobic processes mineralizing organic
matter, is a key carbon flux but one impossible to measure at scales significantly larger than small experimental
plots. 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, genomicspecific
global models is not imminent, we suggest that a useful step to improve this situation would
be the development of “Decomposition Functional Types” (DFTs). Analogous to plant functional types
(PFTs), 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. We argue that DFTs should be initially informed by top-down expert opinion, but ultimately
developed using bottom-up, data-driven analyses, and provide specific examples of potential dependent
and independent variables that could be used. 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: collection and synthesis of existing data; more in-depth analyses
combining open data with rigorous testing of analytical results; using point measurements and realistic
forcing variables to constrain process-based models; and planning by the global modeling community for
decoupling decomposition from fixed site data. These are 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.
Year:
2016
Link:
Journal:
Ecosphere
Issue:
7(6)