Quantifying the Interannual Variability in Global Carbon Fluxes from Heterotrophic Respiration using a Testbed and Pulse Response Modeling Approach.

The atmospheric growth rate of carbon dioxide (CO2) varies interannually and is strongly correlated with climate factors, including temperature and drought. These climate drivers affect vegetation productivity and the rate of respiration of organic matter to CO2 (heterotrophic respiration). Here we quantified the interannual variability in global carbon fluxes from heterotrophic respiration and their relationship to climate drivers. We used a novel testbed approach to simulate respiration, then simulated the imprint that these modeled heterotrophic fluxes have on atmospheric CO2 using an idealized pulse response model. Two of the testbed formulations (MIMICS and CORPSE) are microbially explicit by incorporation of microbial physiological tradeoffs and microbial activity in soil near fine roots (rhizosphere soils), respectively, while the third model (CASA) uses a CENTURY-like microbially implicit framework. Modeled respiration exhibited subtle differences, with MIMICS showing the largest seasonal amplitude in the Northern Hemisphere and the strongest correlation with global temperature variations. At Mauna Loa (MLO) the simulated seasonal CO2 amplitude in response to global heterotrophic respiration ranged by a factor of 1.5 across the models with the MIMICS and CASA models producing the higher amplitude responses between 1987 and 2006. The seasonal CO2 amplitude at MLO varied by about 5% interannually, with the largest variation in the MIMICS model. In the Northern Hemisphere there was a similar response range in average peak-to-trough seasonal CO2 but all models showed slightly higher amplitude values. Comparatively in the Northern Hemisphere, the average seasonal CO2 amplitude in response to respiration ranged between 30%-41% of the seasonal CO2 amplitude in response to net primary productivity. We expect that exploring the imprint of heterotrophic respiration on atmospheric CO2 from these three different models will improve our understanding of the imprint that heterotrophic respiration imparts on atmospheric data. The aim of this work is to ultimately yield an approach for combining CO2 observations with remote sensing-based observations of terrestrial productivity to produce regional constraints on heterotrophic respiration.