Improved methodology to quantify the temperature sensitivity of the soil heterotrophic respiration in croplands

Delogu, E., Le Dantec, V., Mordelet, P., Ceschia, E., Aubinet, M., Buysse, P., Pattey, E., 2017. Improved methodology to quantify the temperature sensitivity of the soil heterotrophic respiration in croplands. Geoderma: in press.

Abstract

© 2017 Elsevier B.V. Soil heterotrophic respiration (RH) is usually modeled using simple temperature dependence equations where the temperature sensitivity of RH could vary for different soils and climate conditions. The temperature sensitivity is expressed as a function of the base rate of heterotrophic respiration (RH − 0) and the respiration change rate over a 10 °C temperature shift (Q10). A methodology was developed to better quantify these two parameters, and was validated using seven contrasting year-site soil respiration datasets collected in wheat fields. The data were acquired using soil respiration chambers and eddy flux towers in three mid-latitude European sites and one North American site. The first step consisted in parameterizing and initializing a semi-mechanistic process-based model then validating the prediction performance using 2/3 of the datasets. The coefficient of determinations between the predictions and the observations of daily soil respiration (Rs) was 0.71 and was 0.73 for its heterotrophic component (RH). The second step consisted in using the daily semi-mechanistic model predictions of RH for each growing season and site to calibrate a simple empirical model describing RH response to soil temperature and water content. It was shown with the contrasting years-sites that coherent results were only obtained when a common average Q10 value was determined prior to fit the base rate of heterotrophic respiration coefficient. Using a common Q10 value of 2.2 provided more stable RH − 0 for each site over time. It reflected the strong relationship between the RH − 0 and the slow decomposing C in the first 30-cm soil layer. The simple empirical model, which was validated using 1/3 of the data, explained between 42% and 92% of the variability of RH over the different sites.

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