Loss of soil organic C (SOC) may lead to reduced soil fertility and increased soil erosion [1]. The loss of SOC has been identified as a major threat towards the soil resource [2], and small but consistent increases in SOC could mitigate climate change effects by storing atmospheric CO2-C [3]. Application of exogenous organic matter (EOM) to cultivated land may lead to SOC accumulation [4]. Different EOMs differ in their potential contribution to SOC, depending on their origin and degree of transformation of the organic matter they contain [5]. Since C stocks change slowly, long-term field studies, such as long-term field experiments, are needed to evaluate the effects of repeated applications of EOM [6]. Models of C turnover in soil accurately simulate SOC dynamics in long-term field experiments under different climatic conditions and soil types [7]. In this study, RothC (one of the most widely used model that simulates SOC dynamic) was used to study changes in soil C stocks after repeated applications of EOM from four long-term experiments.

Main results

The RothC model simulates soil C dynamics by considering five organic C pools: a labile pool (DPM: “decomposable plant material”; mean residence time of 1.2 months), a resistant pool (RPM: “resistant plant material”; mean residence time of 3.3 yrs), a humified pool (HUM; mean residence time of 50 yrs), a microbial biomass pool (BIO; mean residence time 1.5 yrs) and a pool of inert organic matter that is not degraded (IOM). This model is widely used for predicting changes in C stocks of arable soils. However, rigorous routines for establishing entry pools that account for the diversity of EOM applied to croplands are still lacking. We obtained data on changes in soil C stocks after repeated applications of EOM from four long-term experiments (LTEs): Askov K2 (Denmark, 31 yrs), Qualiagro (France, 11 yrs) (figure), SERAIL (France, 14 yrs) and Ultuna (Sweden, 52 yrs).

Figure : Accumulation of soil C compared to reference plots after EOM applications during the Qualiagro experiment. Measured values (symbols, errors bars ¼ standard deviation) and values simulated with RothC using partition coefficients fitted with field data (black lines) or predicted using the IROC indicator (grey dashed lines). MSW: municipal solid waste compost, FYM: farmyard manure, GWS: green waste and sludge compost, BIOW: biowaste compost. -N: plots with minimum mineral N fertilization, +N: plots with optimum mineral N fertilization. Coefficient of variation of the RMSE (CV(RMSE)) and model efficiency (EF) of the simulations using the predicted partition coefficients calculated for the +N and -N parts of the experiment taken together, Delta CV(RMSE): difference between the CV(RMSE) values obtained using the predicted and fitted partition coefficients.

The adjustment of the partition coefficients of total organic C in EOM (EOM-TOC) into the labile, resistant and humified entry pools of RothC (fDPM, fRPM, fHUM, respectively) provided a successful fit to the accumulation of EOM-derived C in the LTE soils. Using the EOM partition coefficients calculated from the IROC indicator [8] resulted in RothC simulations with only slightly larger errors than simulations based on partition coefficients fitted from LTE soil data, except for EOMs that caused very large accumulations of C in soil (e.g. peat) possibly due to factors not accounted for in the RothC model, such as change in soil pH. The proposed partitioning of EOM-TOC allows the potential soil C storage after EOM applications to be predicted regardless of field location and specific composition of EOMs.

References

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2. European Commission, 2006. Proposal for a Directive of the European Parliament and of the Council Establishing a Framework for the Protection of Soil. http://ec. europa.eu/environment/soil/pdf/com_2006_0232_en.pdf.

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4. Marmo, L., Feix, I., Bourmeau, E., Amlinger, F., Bannick, C.G., De Neve, S., Favoino, E., Gendebien, A., Gibert, J., Givelet, M., Leifert, I., Morris, R., Rodriguez Cruz, A., Ruck, F., Siebert, S., Tittarelli, F., 2004. Reports of the Technical Working Groups.

5. Bipfubusa, M., Angers, D.A., N’Dayegamiye, A., Antoun, H., 2008. Soil aggregation and biochemical properties following the application of fresh and composted organic amendments. Soil Science Society of America Journal 72, 160-166.

6. IPCC, 1997. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. In: Reference Manual. Intergovernmental Panel on Climate Change, vol. 3. http://www.ipcc-nggip.iges.or.jp/public/gl/invs6.html.

7. Smith, P., Smith, J.U., Powlson, D.S., McGill, W.B., Arah, J.R.M., Chertov, O.G., Coleman, K., Franko, U., Frolking, S., Jenkinson, D.S., Jensen, L.S., Kelly, R.H., Klein-Gunnewiek, H., Komarov, A.S., Li, C., Molina, J.A.E., Mueller, T., Parton,W.J., Thornley, J.H.M., Whitmore, A.P., 1997b. A comparison of the performance of nine soil organic matter models using datasets from seven long-term experiments. Geoderma 81, 153-225.

8. Lashermes, G., Nicolardot, B., Parnaudeau, V., Thuriès, L., Chaussod, R., Guillotin, M.L., Linères, M., Mary, B., Metzger, L., Morvan, T., Tricaud, A., Villette, C., Houot, S., 2009. Indicator of potential residual carbon in soils after exogenous organic matter application. European Journal of Soil Science 60, 297-310.

Affiliations

a INRA, UMR ECOSYS (previously EGC, Environnement et Grandes Cultures) INRA, AgroParisTech, Université Paris-Saclay, 78850 Thiverval-Grignon, France

b Department of Agroecology, Aarhus University, AU Foulum, P.O.Box 50, DK-8830 Tjele, Denmark

c Ctifl/SERAIL Experimental Station, 123 chemin du Finday, F-69126 Brindas, France

d Department of Soil and Environment, Swedish University of Agricultural Sciences, P.O. Box 7014, 750 07 Uppsala, Sweden