B31E-04
Partitioning autotrophic and heterotrophic respiration to improve simulations of terrestrial carbon fluxes and stocks

Wednesday, 16 December 2015: 08:45
2004 (Moscone West)
Mariah Suzanne Carbone1, Andrew D Richardson2, Min Chen2, Eric A Davidson3, Kathleen E Savage4, Holly Hughes5, David Y Hollinger6 and The Howland Team, (1)Earth Systems Research Center, Durham, NH, United States, (2)Harvard University, Cambridge, MA, United States, (3)University of Maryland Center for Environmental Science Appalachian Laboratory, Frostburg, MD, United States, (4)Woods Hole Research Center, Falmouth, MA, United States, (5)Woods Hole Research Center, East Falmouth, MA, United States, (6)USDA Forest Service, Durham, NH, United States
Abstract:
Autotrophic (Ra) and heterotrophic (Rh) respiration are large components of the terrestrial C cycle, yet are among the most poorly constrained fluxes in C budgets. We partitioned the soil CO2 flux into its respective Ra and Rh components in an old growth, temperate-boreal forest (Howland Forest AmeriFlux site in Maine, USA). We used two different partitioning methods combined with automated chamber measurements of the soil CO2 flux: (1) a classic root trenching experiment and (2) an isotopic mass balance approach, using the radiocarbon (14C) bomb spike. We then assessed the “value” of the soil CO2 flux data and partitioning results as observational constraints for simulating current and future C fluxes and stocks using a simple ecosystem model (FöBAAR) and a model-data fusion approach.

We found generally greater Rh with the trenching experiment and greater Ra with the 14C approach. Over the growing season, Rh accounted for 53 ± 11% of the total soil CO2 flux in the trenching experiment, while the mean Rh from the four 14C sampling time points was 42 ± 9%.

For both current and future model runs, incorporating the partitioning data as constraints reduced the uncertainties of Ra and Rh fluxes by at least 60% (and as much as 85%) compared to the model runs where only the soil CO2 fluxes were used as constraints. Moreover, with best-fit model parameters, the two partitioning methods yielded fundamentally different estimates of the relative contributions of Ra and Rh to total soil CO2 flux. Surprisingly, however, modeled soil C and biomass C pool trajectories did not differ significantly between model runs, indicating that the model parameters compensated for these differences in partitioning with changes in allocation and decomposition rates.

Our findings show that incorporating constraints on the partitioning of soil CO2 flux dramatically reduces model uncertainties; however, the results are sensitive to the method used, and the impact on modeled pool sizes may be small.

<< Previous Abstract | Next Abstract >>