The ongoing journey of modelling intercropping systems: A conceptual resource sharing intercomparison from model developers and expert users
Year: 2026
Type: article
Abstract: Context The global shift toward sustainable agriculture has increased interest in using process-based models to design and optimize intercropping systems. However, these models differ fundamentally in how they represent trade-offs (competition for light, water, and nutrients) and synergies (facilitation, complementarity) in resource sharing between species. This conceptual variation creates uncertainty in model selection and application, particularly since most models were originally developed for monoculture and subsequently adapted for intercropping. Objective In this study, we describe how current crop models represent interspecies resource-sharing mechanisms, analyse their structural differences, and synthesize findings from existing validation studies to understand how their structural differences affect model performance. The models examined include APSIM (APSIM-Canopy, APSIM-Micromet, APSIM-Strip, APSIM-Alternating, APSIM-APSwim, APSIM-SoilArbitrator), DayCent, DSSAT-Mixed, DSSAT-MPI, LandscapeDNDC, LUCIA, MONICA, SIMPLACE Lintul5-Intercrop, STICS-Big-Leaf, STICS-Multilayer, and WaNuLCAS. Methods Through the Agricultural Model Intercomparison and Improvement Project (AgMIP) platform, we engaged with model developers and expert users to collect detailed information on how crop models represent intercropping systems using structured interviews and questionnaires. We then developed a framework that groups models by their core conceptual approaches to simulating resource sharing. Finally, we synthesize findings from existing quantitative validation studies to connect conceptual intercomparison to predictive performance across different intercrop characteristics and environments. Results and Conclusions Our analysis identifies six distinct conceptual approaches for simulating light sharing and four for belowground resource (water and nutrient) competition. Intercrop models show greater structural divergence in canopy than in belowground representation. Furthermore, competitive trade-offs (light, water, and nutrients) are widely represented while facilitative and other complex processes like N₂-fixation, plasticity (shoot and root), microclimate effects or hydraulic lift are often simplified or omitted. Our analysis of model validation studies reveals a critical trade-off: structurally complex models often perform well in simulating intercropping when calibration is done on sole crops, whereas simpler models require extensive intercrop-specific calibration to achieve better prediction performance. This distinction is vital for model application in data-scarce environments, as more complex architectures can leverage existing sole-crop data to effectively simulate intercrop systems. The classification of the structural resource capture differences in combination with the evaluated model performance analysis allowed us to devise an evidence-based model selection criteria framework useful also for for non-specialist , while the unique detailed description provided are highly valuable for the model research community. Significance This study establishes a conceptual framework that provides the necessary foundation for a meaningful quantitative intercomparison of intercrop models, as structural understanding enables the interpretation of numerical differences in model outputs. It also guides hypothesis testing, model choice, priorities in model development and improvements.
Source: Field Crops Research
Authors: Adam Muhammad Adam, Myriam Adam, Folkard Asch, Kenneth J Boote, Vimbayi Grace Petrova Chimonyo, Mathias Christina, Marc Corbeels, Antoine Couëdel, Mathilde De Freitas, Tomas Della Chiesa, Frank Ewert, Gatien N Falconnier, Kathrin Fuchs, Thomas Gaiser, Ken E Giller, Gerrit Hoogenboom, Neil Huth, Jibrin Mohammed Jibrin, Eric Justes, Alpha Y Kamara, Michael Kermah, Nuttapon Khongdee, Eric Koomson, David Kraus, Marcos Lana, Moritz Laub, Betha Lusiana, Carsten Marohn, Patricia Moreno-Cadena, Claas Nendel, Wanwisa Pansak, Willingthon Pavan, Jacques Fils Pierre, Hanna J Poffenbarger, Ehsan Eyshi Rezaei, Alex C Ruane, Montserrat Salmerón, Clemens Scheer, Sabine J Seidel, Pacsu Simwaka, Upendra Singh, Johan Six, Amit Kumar Srivastava, Meine van Noordwijk, Johanna Volk, Jing Yu, Georg Cadisch
Institutions: University of Hohenheim, Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Amélioration Génétique et Adaptation des Plantes méditerranéennes et tropicales, University of Florida, Centro Internacional de Mejoramiento de Maíz Y Trigo, International Maize and Wheat Improvement Center, International Maize and Wheat Improvement Center, Agro-écologie et intensification durable des cultures annuelles, International Institute of Tropical Agriculture, Universidad de Buenos Aires, University of Bonn, Leibniz Centre for Agricultural Landscape Research, University of Zimbabwe, Karlsruhe Institute of Technology, Wageningen University & Research, Commonwealth Scientific and Industrial Research Organisation, International Institute of Tropical Agriculture, Bayero University Kano, Chiang Mai University, Swedish University of Agricultural Sciences, ETH Zurich, Center for International Forestry Research, Julius Kühn-Institut, Forschungsinstitut für Biologischen Landbau, Bioversity International, International Center for Tropical Agriculture, University of Potsdam, Mahidol University, International Fertilizer Development Center, University of Kentucky, Goddard Institute for Space Studies, BOKU University
Language: English
Subfield: Agronomy and Crop Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: hybrid
Estimated APC paid: $3,680
Funders: National Science Foundation, European Commission, Department of Science and Technology, Ministry of Science and Technology, India, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Consortium of International Agricultural Research Centers, Horizon 2020 Framework Programme, Biotechnology and Biological Sciences Research Council, Leibniz-Gemeinschaft, FP7 Coordination of Research Activities, Leibniz-Zentrum für Agrarlandschaftsforschung
Awards: G1198078426, G2026862226, G2097902111, G269356847, EXC 2070: PhenoRob Robotik und Phänotypisierung für Nachhaltige Nutzpflanzenproduktion, G7187260211, G720894491, G8255642693, SYNERGISTIC USE AND PROTECTION OF NATURAL RESOURCES FOR RURAL LIVELIHOODS THROUGH SYSTEMATIC INTEGRATION OF CROPS, SHRUBS AND LIVESTOCK IN THE SAHEL, G8908324091, Developing Intercropping for agrifood Value chains and Ecosystem Services delivery in Europe and Southern countries
OpenAlex ID: W7160051101