Ignoring temperature variation leads to underestimation of the temperature sensitivity of plant litter decomposition

The majority of terrestrial net primary production decomposes, fueling detrital food webs and converting dead plant carbon to atmospheric CO2. There is considerable interest in determining the sensitivity of this process to climate warming. A common approach has been to use spatial gradients in temperature (i.e., latitude or elevation) to estimate temperature sensitivity. However, these studies typically relate decomposition rates to average temperatures at each site along such gradients, ignoring within-site temperature variation. To evaluate the potential effects of temperature variation on estimates of temperature sensitivity, we simulated plant litter decomposition using both randomly generated and real time series of temperature. This simulation approach illustrated how temperature variation leads to higher decomposition rates at a given mean temperature than is predicted from simulations in which temperature is held constant. Increases in decomposition rate were most evident at cooler sites, where temporal variation in temperature tends to be greater than at warmer sites. This unbalanced effect of temperature variation shifted the slope of the relationships between average temperature and decomposition rate, resulting in lower estimated temperature sensitivities than were used to simulate decomposition. For example, estimates of activation energy (E-a) were as much as 0.15 eV lower than the true E-a when decomposition was simulated with the true E-a set to the canonical respiration value of 0.65 eV. We found that the estimated E-a was lower than the true E-a for surface, soil, and air temperatures, but not for stream temperatures, for which there was only a weak relationship between temperature variation and mean temperature. Our results suggest that commonly used methods may underestimate the temperature dependence of litter decomposition, particularly in terrestrial environments. We encourage publication of temperature data that include variation estimates and suggest an alternative method for calculating temperature sensitivity that accounts for variation in temperature.