Soil water availability strongly modulates soil CO2 efflux in different Mediterranean ecosystems: Model calibration using the Bayesian approach

International audience

إنجليزي. Soil respiration in drought prone regions is highly dependent on the precipitation regime and soil moisture conditions, which are expected to change in a global warming context. In the present study we used an extensive collection of field chamber measurements of soil respiration (R-s) from forest and grassland sites of centre and south of Portugal distributed over a 10 year period. This data were summarized and analysed with the objective to describe seasonal variability of R-s as affected by soil moisture (H-s) and soil temperature (T-s). A Bayesian framework was used to test the effectiveness of soil bioclimatic models in estimating R-s on a daily and monthly time step. R-s seasonality was similar between sites, reaching a maximum in spring and autumn and a minimum in the dry season (July-September). No differences were observed for R-s between sites with different standing biomass or soil carbon stocks either on an annual or seasonal timescale. H-s, and not T-s, was the driving factor of R-s during most of the year. T-s drove R-s response only above certain H-s limits: 10% for forest sites and 15% for grassland sites leading to a Q(10) of 2.01, 1.61 and 1.31 for closed forests, open forests and grasslands, respectively. The Bayesian analysis showed that models using H-s as an independent variable performed better than models driven by T-s alone. Monthly estimates of R-s in grasslands can be predicted by simple climatic models based on H-s but none of them was suitable for forest ecosystems, stressing the need for a process-based approach. This study adds to the evidence that H-s controls R-s fluxes for Mediterranean ecosystems and should always be taken into account for extrapolation purposes.