Review and analysis of strengths and weaknesses of agro-ecosystem models for simulating C and N fluxes
Open accessAbstract
Biogeochemical simulation models are important tools for describing and quantifying the contribution of agricultural systems to C sequestration and GHG source/sink status. The abundance of simulation tools developed over recent decades, however, creates a difficulty because predictions from different models show large variability. Discrepancies between the conclusions of different modelling studies are often ascribed to differences in the physical and biogeochemical processes incorporated in equations of C and N cycles and their interactions. Here we review the literature to determine the state-of-the-art in modelling agricultural (crop and grassland) systems. In order to carry out this study, we selected the range of biogeochemical models used by the CN-MIP consortium of FACCE-JPI (http://www.faccejpi.com): APSIM, CERES-EGC, DayCent, DNDC, DSSAT, EPIC, PaSim, RothC and STICS. In our analysis, these models were assessed for the quality and comprehensiveness of underlying processes related to pedo-climatic conditions and management practices, but also with respect to time and space of application, and for their accuracy in multiple contexts. Overall, it emerged that there is a possible impact of ill-defined pedo-climatic conditions in the unsatisfactory performance of the models (46.2%), followed by limitations in the algorithms simulating the effects of management practices (33.1%). The multiplicity of scales in both time and space is a fundamental feature, which explains the…
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The land, ecosystem, and greenhouse gas emission impacts resulting from beef production are highly dependent on the type of grazing management system utilized.
“Accordingly, the land, ecosystem, and GHG emission impacts resulting from beef production are highly dependent on the type of grazing management system utilized”
From Impacts of soil carbon sequestration on life cycle greenhouse gas emissions in Midwestern USA beef finishing systems (2018) · cites this paper as Brilli et al., 2017
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The DSSAT cropping system model
Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., Wilkens, P. W., Singh, U., Gijsman, A. J., & Ritchie, J. T. (2003) · European Journal of Agronomy · doi:10.1016/s1161-0301(02)00107-7 · Cited by 4,465 · see citing works
How relevant is recalcitrance for the stabilization of organic matter in soils?
Marschner, B., Brodowski, S., Dreves, A., Gleixner, G., Gude, A., Grootes, P. M., Hamer, U., Heim, A., Jandl, G., Ji, R., et al. (2008) · Journal of Plant Nutrition and Soil Science · doi:10.1002/jpln.200700049 · Cited by 743 · see citing works
Methodologies for simulating impacts of climate change on crop production
White, J. W., Hoogenboom, G., Kimball, B. A., & Wall, G. W. (2011) · Field Crops Research · doi:10.1016/j.fcr.2011.07.001 · Cited by 612 · see citing works
Measured soil organic matter fractions can be related to pools in the RothC model
Zimmermann, M., Leifeld, J., Schmidt, M. W. I., Smith, P., & Fuhrer, J. (2007) · European Journal of Soil Science · doi:10.1111/j.1365-2389.2006.00855.x · Cited by 469 · see citing works
Self-citationSimulating trends in soil organic carbon in long-term experiments using RothC-26.3
Coleman, K., Jenkinson, D. S., Crocker, G. J., Grace, P. R., Klír, J., Körschens, M., Poulton, P. R., & Richter, D. D. (1997) · Geoderma · doi:10.1016/s0016-7061(97)00079-7 · Cited by 420 · see citing works
Self-citationSensitivity and uncertainty analyses of crop yields and soil organic carbon simulated with EPIC
Wang, X., He, X., Williams, J. R., Izaurralde, R. C., & Atwood, J. D. (2005) · Transactions of the ASAE · doi:10.13031/2013.18515 · Cited by 144 · see citing works
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Luo, G., Li, L., Friman, V.-P., Guo, J., Guo, S., Shen, Q., & Ling, N. (2018) · Soil Biology and Biochemistry · doi:10.1016/j.soilbio.2018.06.002 · Cited by 546 · see citing works
Towards a multiscale crop modelling framework for climate change adaptation assessment
Peng, B., Guan, K., Tang, J., Ainsworth, E. A., Asseng, S., Bernacchi, C. J., Cooper, M., Delucia, E. H., Elliott, J. W., Ewert, F., et al. (2020) · Nature Plants · doi:10.1038/s41477-020-0625-3 · Cited by 322 · see citing works
Stanley, P. L., Rowntree, J. E., Beede, D. K., DeLonge, M. S., & Hamm, M. W. (2018) · Agricultural Systems · doi:10.1016/j.agsy.2018.02.003 · Cited by 266 · see citing works
“Accordingly, the land, ecosystem, and GHG emission impacts resulting from beef production are highly dependent on the type of grazing management system utilized (Brilli et al., 2017; Rowntree et al., 2016).”
Background
- Authors
- Brilli, L., Bechini, L., Bindi, M., Carozzi, M., Cavalli, D., Conant, R., Dorich, C. D., Doro, L., Ehrhardt, F., Farina, R., Ferrise, R., Fitton, N., Francaviglia, R., Grace, P., Iocola, I., Klumpp, K., Léonard, J., Martin, R., Massad, R. S., Recous, S., Seddaiu, G., Sharp, J., Smith, P., Smith, W. N., Soussana, J.-F., & Bellocchi, G.
- Affiliations
- Istituto di Biometeorologia (IT)
- University of Milan (IT)
- University of Florence (IT)
- AgroParisTech (FR)
- Colorado State University (US)
- University of Sassari (IT)
- Institut National de la Recherche Agronomique (FR)
- Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria (IT)
- University of Aberdeen (GB)
- Queensland University of Technology (AU)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Fractionnation of AgroResources and Environment (FR)
- Plant & Food Research (NZ)
- Agriculture and Agri-Food Canada (CA)
- Corresponding author
- Brilli, Lorenzo
- ORCID
- Brilli, Lorenzo
- Bechini, Luca
- Bindi, Marco
- Carozzi, Marco
- Cavalli, Daniele
- Conant, Richard
- Doro, Luca
- Ehrhardt, Fiona
- Farina, Roberta
- Ferrise, Roberto
- Fitton, Nuala
- Francaviglia, Rosa
- Grace, Peter
- Iocola, Ileana
- Klumpp, Katja
- Léonard, Joël
- Martin, Raphaël
- Massad, Raia Silvia
- Recous, Sylvie
- Sharp, Joanna
- Smith, Pete
- Smith, Ward N.
- Bellocchi, Gianni
- Venue
- Science of The Total Environment
- Publisher
- Elsevier BV
- Published
- 2017-11
- Volume
- 598
- Pages
- 445-470
- ISSN
- 0048-9697 (ISSN-L)
- OpenAlex
- W2608050375
- Cited by
- 244
- References
- 6
- Citations by year
- 2026: 26 · 2025: 23 · 2024: 22 · 2023: 39 · 2022: 33 · 2021: 23 · 2020: 24 · 2019: 30 · 2018: 19 · 2017: 5
- FWCI
- 2.28
- Type
- journal article
- Language
- en
- Open access
- green
- hal.science
- Licence
- Locations
- The Science of The Total Environment (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by-sa)
- Aberdeen University Research Archive (Aberdeen University) (submittedVersion)
- Florence Research (University of Florence) (submittedVersion)
- UnissResearch (Università degli Studi di Sassari) (submittedVersion)
- Funders
- Institut National de la Recherche Agronomique (ANR-13-JFAC-0001)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil Carbon and Nitrogen Dynamics
- Physical Sciences › Environmental Science › Environmental Chemistry › Sustainable Agricultural Systems Analysis
- Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil erosion and sediment transport
- Keywords
- carbon cycle modeling, biogeochemical modeling, cropping systems, grassland, soil organic matter decomposition, soil microbial biomass, soil gas transport, soil carbon sequestration, greenhouse gas emissions, model evaluation, model intercomparison, management practices
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