Simulation of CO2 and Attribution Analysis at Six European Peatland Sites Using the ECOSSE Model

• In this study, we simulated heterotrophic CO2 (Rh) fluxes at six European peatland sites using the ECOSSE model and compared them to estimates of Rh made from eddy covariance (EC) measurements. The sites are spread over four countries with different climates, vegetation and management. Annual Rh from the different sites ranged from 110 to 540 g C m(-2). The maximum annual Rh occurred when the water table (WT) level was between -10 and -25 cm and the air temperature was above 6.2 degrees C. The model successfully simulated seasonal trends for the majority of the sites. Regression relationships (r(2)) between the EC-derived and simulated Rh ranged from 0.28 to 0.76, and the root mean square error and relative error were small, revealing an acceptable fit. The overall relative deviation value between annual EC-derived and simulated Rh was small (-1 %) and model efficiency ranges across sites from -0.25 to +0.41. Sensitivity analysis highlighted that increasing temperature, decreasing precipitation and lowering WT depth could significantly increase Rh from soils. Thus, management which lowers the WT could significantly increase anthropogenic CO2, so from a carbon emissions perspective, it should be avoided. The results presented here demonstrate a robust basis for further application of the ECOSSE model to assess the impacts of future land management interventions on peatland carbon emissions and to help guide best practice land management decisions.

Subject headings

NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Naturgeografi (hsv//swe)

NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Physical Geography (hsv//eng)

LANTBRUKSVETENSKAPER  -- Lantbruksvetenskap, skogsbruk och fiske -- Skogsvetenskap (hsv//swe)

AGRICULTURAL SCIENCES  -- Agriculture, Forestry and Fisheries -- Forest Science (hsv//eng)

Keyword

Peatland

ECOSSE

Heterotrophic CO2

Attribution analysis

Publication and Content Type

art (subject category)

ref (subject category)