Temperature sensitivity of soil respiration and its effects on ecosystem carbon budget: Nonlinearity begets surprises

Nonlinearity is a salient feature in all complex systems, and it certainly characterizes biogeochemical cycles in ecosystems across a wide range of scales. Soil carbon emission is a major source of uncertainty in estimating the terrestrial carbon budget at the ecosystem level and above. Due to the lack of consideration of the nonlinearity in temperature sensitivity of soil respiration, several commonly used ecosystem models produce substantially different estimates of soil respiration with the same or similar model input. In this paper we demonstrated that the response of soil respiration to changes in temperature sensitivity is nonlinear and, thus, that the oversimplified formulations may significantly reduce the accuracy of ecosystem models in predicting carbon fluxes. To alleviate this problem, we have developed a general model of temperature sensitivity of soil respiration that explicitly considers this nonlinearity. The model was supported by our field measurements from a forest ecosystem, and used to assess the uncertainty in estimating the soil CO₂ efflux with several commonly used ecosystem models. Our results indicated that the variations and nonlinearity of the soil respiration-temperature relationship and its dependence on moisture may have important implications for ecosystem carbon modeling at regional and global scales. In other words, 'small causes' may lead to 'large effects' in complex ecosystems in terms of carbon dynamics. In particular, when the variability in temperature sensitivity of soil respiration was incorporated in the several commonly used ecosystem models, the carbon source-sink relationship for terrestrial ecosystems under future global warming scenarios became dramatically different from those reported previously. Thus, we advocate that confidence limits are both necessary and feasible for simulated carbon budget from ecosystem models. Based on field measurements and model simulations, our study provides useful information for computing such confidence limits. In addition, our new model of temperature sensitivity of soil respiration seems more general and yet realistic, and can improve the accuracy of ecosystem models in predicting carbon fluxes at large scales.