Measurements of carbon-14 in plant tissues help to reduce uncertainties in predictions of an ecosystem carbon cycle simulation model.
This study compared three carbon cycle simulation models which differed in their representation of how trees allocate carbon to growth vs. storage. Carbon isotopes were used as tracers in the model, allowing quantification of the age and transit time of carbon through the system, and providing new insights into the temporal dynamics of carbon allocation by plants.
The age and transit time of carbon cycling through ecosystems (which can be measured using 14C), serve as important diagnostics of model structure and could largely help to reduce uncertainties in model predictions.
Trees store carbohydrates, in the form of sugars and starch, as reserves to be used to power both future growth as well as to support day-to-day metabolic functions. These reserves are particularly important in the context of how trees cope with disturbance and stress—for example, as related to pest outbreaks, wind or ice damage, and extreme climate events. How quickly these reserves are used and replaced—i.e., their age—was assessed using carbon isotope analysis (14C). The isotope data were used to test and improve computer simulation models of carbon flow through forest ecosystems, with a focus on the mathematical representation of stored carbon reserves. The age of C in different pools, and the overall transit time of C through the system, were used as diagnostics to assess how different carbon allocation schemes influence rates of C cycling. The different model structures did not influence how much C was stored in the system at the conclusion of the model run, but they did result in large differences in age and transit time distributions. The inclusion of two storage compartments resulted in the prediction of a system mean age that was 7-10 years older than in the models with one or no storage compartments. These results suggest that ages and transit times, which can be indirectly measured using isotopic tracers, serve as important diagnostics of model structure and could largely help to reduce uncertainties in model structure and model predictions.
Contacts (BER PM)
Daniel Stover SC-23.1
Professor Andrew Richardson
Northern Arizona University, Center for Ecosystem Science and Society and School of Informatics, Computing and Cyber Systems
Tel. 928 523 3049
This research is based upon work supported by the US Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research.
Ceballos-Núñez, V., A.D. Richardson and C.A. Sierra. “Ages and transit times as important diagnostics of model performance for predicting carbon dynamics in terrestrial vegetation models.” Biogeosciences, 15(5),1607-1625 (2018). [DOI:10.5194/bg-15-1607-2018]
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