|Del Grosso, Stephen - Steve|
Submitted to: Biogeochemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/3/2004
Publication Date: 3/1/2005
Citation: Del Grosso, S.J., Mosier, A.R., Parton, W.J., Ojima, D. 2005. Modeling soil co2 emissions from ecosystems. Biogeochemistry. 73:71-91.
Interpretive Summary: Estimating carbon dioxide (CO2) emissions from natural and managed ecosystems is important because CO2 is the primary long-lived greenhouse gas. Although the net annual flux of CO2 from ecosystems is close to neutral because the vast majority of CO2 taken up by plants is respired back to the atmosphere, gross CO2 emissions from ecosystems are about 10 times the emissions from burning of fossil fuels. Consequently, small changes in the balance between CO2 uptake by plants and release by decomposition have significant impacts on atmospheric CO2 levels. Reliable modeling of CO2 emissions from soils is important to project how changes in land use and clime will affect soil CO2 fluxes. Using data from various native and managed ecosystems, we developed a model that predicts soil CO2 emissions based on soil water and temperature. Extensive testing showed that our model is superior to similar models used to predict soil CO2 emissions.
Technical Abstract: We present a new soil respiration model, describe a formal model testing procedure, and compare our model with five alternative models using an extensive data set of observed soil respiration. Gas flux data from rangeland soils that included a large number of measurements at low temperatures were used to model soil CO2 emissions as a function of soil temperature and water content. Our arctangent temperature function predicts that Q10 values vary inversely with temperature and that CO2 fluxes are significant below 0 oC. Independent data representing a broad range of ecosystems and temperature values were used for model testing. The effects of plant phenology, differences in substrate availability among sites, and water limitation were accounted for so that the temperature equations could be fairly evaluated. Four of the six tested models did equally well at simulating the observed soil CO2 respiration rates. However, the arctangent variable Q10 model agreed closely with observed Q10 values over a wide range of temperatures (r 2 = 0.94) and was superior to published variable Q10 equations using the Akaike information criterion (AIC). The arctangent temperature equation explained 16–85% of the observed intra-site variability in CO2 flux rates. Including a water stress factor yielded a stronger correlation than temperature alone only in the dryland soils. The observed change in Q10 with increasing temperature was the same for data sets that included only heterotrophic respiration and data sets that included both heterotrophic and autotrophic respiration.