Concurrent and lagged impacts of an anomalously warm year on autotrophic and heterotrophic components of soil respiration: a deconvolution analysis

P>Partitioning soil respiration into autotrophic (R-A) and heterotrophic (R-H) components is critical for understanding their differential responses to climate warming. Here, we used a deconvolution analysis to partition soil respiration in a pulse warming experiment. We first conducted a sensitivity analysis to determine which parameters can be identified by soil respiration data. A Markov chain Monte Carlo technique was then used to optimize those identifiable parameters in a terrestrial ecosystem model. Finally, the optimized parameters were employed to quantify R-A and R-H in a forward analysis. Our results displayed that more than one-half of parameters were constrained by daily soil respiration data. The optimized model simulation showed that warming stimulated R-H and had little effect on R-A in the first 2 months, but decreased both R-H and R-A during the remainder of the treatment and post-treatment years. Clipping of above-ground biomass stimulated the warming effect on R-H but not on R-A. Overall, warming decreased R-A and R-H significantly, by 28.9% and 24.9%, respectively, during the treatment year and by 27.3% and 33.3%, respectively, during the post-treatment year, largely as a result of decreased canopy greenness and biomass. Lagged effects of climate anomalies on soil respiration and its components are important in assessing terrestrial carbon cycle feedbacks to climate warming.