Agricultural Systems Analysis and Modelling

Agricultural systems analysis and modelling brings together ecological, economic and social data to represent farms, landscapes and supply chains as interconnected networks of stocks and flows. By coupling process-based simulators with statistical, optimisation and machine-learning methods, researchers can explore system behaviours—from nutrient cycling and land‐use change to market responses—under current and future scenarios. Models range from field-scale crop simulators and biophysical optimisation tools to regional economic frameworks and integrated assessment platforms. They support decisions on cropping patterns, resource allocation, policy design and innovation pathways by quantifying trade-offs among productivity, resilience, environmental impact and livelihoods. As global pressures from climate change, biodiversity loss and resource scarcity mount, modelling offers a virtual laboratory in which to test adaptive measures, accelerate transitions to sustainable approaches and guide investments in precision management, circular food systems and nature-based solutions.

Research from Nature Portfolio

“Food without agriculture” used life-cycle modelling to show that certain key dietary fats can be chemosynthetically produced with greenhouse-gas emissions and land demand far below those of palm oil. This study highlights the potential to decouple staple ingredients from traditional cropping. A biophysical optimisation analysis of circularity scenarios in a major economic union demonstrated that redesigning regional food systems on circular principles could shrink agricultural land use by over 70% and cut per-capita emissions by nearly 30%, while maintaining nutritional self-sufficiency. Surplus land could feed hundreds of millions more globally under stress. Modelling compatibility between circular livestock feed systems and reference dietary guidelines revealed that recycling crop residues into animal diets can reduce arable land use by up to 40% and greenhouse-gas emissions by about 30%, but requires rebalancing among dairy, pork and poultry to meet nutrition targets.

Research from all publishers

A spatial-temporal Green Total Factor Productivity (GTFP) study across China (1998–2016) applied a slacks-based measure directional distance function and Malmquist-Luenberger index to reveal that technological progress outpaced efficiency gains, with highest annual GTFP growth in eastern provinces. The work underlines the need for targeted innovation policies in lagging regions. A global economic model incorporating livestock technical parameters assessed policies to promote low-opportunity-cost feed from residues and by-products. Simulations showed that subsidies and import tariffs can enhance circularity, reduce animal production and lower emissions, though complementary measures are needed to avoid unintended land-use and income shifts. In the Upper Indus Basin, a comparison of a process-based watershed simulator (SWAT) and a multilayer perceptron neural network found the latter better captured snowmelt-driven streamflow and hydropeaking events, suggesting hybrid frameworks can improve calibration of sensitive hydrological parameters under data scarcity.

Agricultural Systems Analysis and Modelling publication trend

The graph below shows the total number of articles in agricultural systems analysis and modelling across all publications each year (not limited to Nature Index journals).

Technical terms

Agroecosystem: An ecosystem shaped by human agricultural activities, including crops, livestock, soils and management practices.

Circular food system: A production model in which waste streams and by-products are reintegrated to minimise virgin resource use and environmental impacts.

Chemosynthetic production: Synthesis of food components using chemical or biological processes rather than soil-based agriculture.

Green Total Factor Productivity (GTFP): A productivity measure that integrates desirable outputs (yields) and undesirable environmental externalities (e.g., emissions).

Non-parametric index: An efficiency or productivity metric, such as the Malmquist-Luenberger index, that does not rely on pre-specified functional forms.

Homogeneous environmental conditions (HECs): Groupings of farms or fields with similar biophysical and climatic characteristics, used for benchmarking management practices.

References

1. Food without agriculture. Nature Sustainability (2023).
2. Circularity in Europe strengthens the sustainability of the global food system. Nature Food (2023).
3. Circularity in animal production requires a change in the EAT-Lancet diet in Europe. Nature Food (2022).
4. Spatial-Temporal Characteristics of Agriculture Green Total Factor Productivity in China, 1998–2016: Based on More Sophisticated Calculations of Carbon Emissions. International Journal of Environmental Research and Public Health (2019).
5. Unveiling the economic and environmental impact of policies to promote animal feed for a circular food system. Resources Conservation and Recycling (2024).
6. Comparison of machine learning and process-based SWAT model in simulating streamflow in the Upper Indus Basin. Applied Water Science (2022).