Simulating CO2 seasonal cycle amplitude in northern high latitudes with an eco-evolutionary optimality model

Land-atmosphere carbon exchanges and feedbacks constitute one of the largest uncertainties in future climate projections. Seasonal variations in atmospheric CO2 content depend on uptake by photosynthesis and release by autotrophic and heterotrophic respiration, providing an atmospheric signal of land ecosystem activity. Large increases in the seasonal cycle amplitude (SCA) of CO2 have occurred since the 1950s, especially in northern high latitudes. However, land surface and dynamic vegetation models have produced a wide range of magnitudes for the SCA, and have generally underestimated its increase. We explored the controls of the SCA by using a parameter-sparse eco-evolutionary optimality (EEO) model, the ‘P model’, combined with generic representations of plant and decomposer respiration, to simulate seasonal cycles and decadal trends of net ecosystem exchange (NEE). Simulated NEE fields were used to model near-surface CO2 concentrations during the satellite era, with the help of the atmospheric chemistry-transport model TM5. The P model has previously been shown to reproduce trends of gross primary production (GPP) at flux sites with long records. Our model set-up also generated a realistic simulation of global net terrestrial carbon uptake, comparable with results produced by more complex dynamic vegetation models; and allowed us to attribute causes to observed SCA increases at high-latitude CO2 monitoring stations.