A Dynamic Modeling Assessment of NEE, GHG Emissions and C-Costs of Biofuel Crop Production in Agricultural Landscape: Inclusion of Erosion-Induced Transient States.

Net Ecosystem Exchange (NEE) and C-costs associated with crop production systems which are outside of NEE must be determined to suggest optimal C mitigation options. In theory, NEE is negative, if SOC is building up, neutral or balanced, with no change in SOC, or positive, if C is lost also as a result of soil degradation processes. Unclearness in complex interactions between different processes in the landscape in combination with wide range of NEE determination uncertainties makes estimation of C exchange for landscape scale scarce. In this study we used a process-based modeling to assess C-costs associated with soil erosion, assessing NEE at different erosion-induced transient states in newly experiment settled in Northeastern Germany (53.379546N, 13.785954E) in a representative section of younger landscape of hummocky ground moraine (CarboZALF experimental field). We have used Monica, a soil-crop-atmosphere model well-validated for various crops and soil in Germany (http://monica.agrosystem-models.com/). In the model NEE (=-NEP) refers to NPP minus C losses in heterotrophic respiration, while NBE (=-NBP) refers to the change in SOC stocks after C losses due to regular (e.g. soil erosion) or occasional (e.g. harvest) disturbances. We have analyzed relationships between past geomorphic processes, landscape position, crop growth and NEE. At first we were focused on general trends and associated agroecosystem properties, rather than on magnitude of the fluxes. The results showed that past soil redistribution affected NEE at different slope positions, while the Monica-based scenarios in combination with data-based interpolations helped to interpret the NEE budgets. The modeling results were satisfactory when landscape hydrology has been considered. The model captured the magnitude of differences in the daily NEE values, but also the differences in an accumulated NEE fluxes between different erosion-induced transient states. Thus for both eroded and deposited positions NEE was negative. However absolute values of NEE were smaller for the deposited site compared to the eroded one, and NBE was only slightly different from zero for both landscape positions. We believe that our approach might improve the agroecosystem analysis in a way to reveal the uncertainties associated with the landscape scale. To increase credibility of this approach additional modeling was required i.e. i) validation of Monica against both short- and long-term NEE/C exchange data and ii) inclusion of total C-costs in the analysis, i.e. combination of NEE/C data with GHG emissions and crop growth. For this purpose we have used data from several energy-based crop rotations from Europe and North America. This study is funded by the EU FP7 project GAEMASS (no.255042).