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	Crop Simulation Modeling	Agroecosystem Analysis
Ämnesområde	Food Agriculture Studies	Food Agriculture Studies
Familj	Process / pipeline	Process / pipeline
Ursprungsår	2003	1987
Upphovsperson	James W. Jones et al. (DSSAT); Dean Holzworth et al. (APSIM)	Gordon R. Conway
Typ	Process-based dynamic simulation pipeline for crop growth and yield	Systems-diagnosis pipeline for agroecosystem performance
Ursprungskälla	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). The DSSAT cropping system model. European Journal of Agronomy, 18(3-4), 235-265.	Conway, G. R. (1987). The properties of agroecosystems. Agricultural Systems, 24(2), 95-117.
Alias	Crop Growth Simulation, Process-Based Crop Modeling, Crop Systems Modeling, Dynamic Crop Modeling	AEA, Agroecosystem Properties Analysis, Conway Agroecosystem Analysis, Agroecosystem Diagnosis
Närliggande	4	4
Sammanfattning	Crop simulation modeling uses process-based, dynamic computer models to predict how a crop grows and yields under specified weather, soil, and management, by numerically integrating mechanistic equations for development, photosynthesis, and water and nutrient balances on a daily time step. The two most widely used platforms are DSSAT, documented by James Jones and colleagues in 2003, and APSIM, whose modern architecture was described by Dean Holzworth and colleagues in 2014. Rather than fitting a statistical curve to yield data, these models encode the underlying biophysics — temperature-driven phenology, radiation-use efficiency, soil water and nitrogen dynamics — so they can extrapolate to weather, soils, and management combinations never directly observed. This makes crop models powerful tools for in silico experimentation, scenario analysis, and climate-change and management impact assessment where field trials alone would be impossibly slow or costly.	Agroecosystem analysis (AEA) is a systems-diagnosis framework, formalized by Gordon Conway in 1987, that characterizes any agricultural system through four properties: productivity, stability, sustainability, and equitability. Rather than judging a farming system by yield alone, AEA treats the agroecosystem as an ecological system shaped by human management and asks how much it produces, how reliably it produces it across seasons and shocks, whether it can maintain output over the long run, and how its benefits are distributed among the people who depend on it. The analyst bounds a system at an appropriate hierarchical level — plot, field, farm, watershed, or region — and uses interdisciplinary teams, ranked questions, and simple structured diagrams to surface the key relationships and the trade-offs among the four properties that drive design and policy choices.