The complexity of an entity or an organization presents the ability to provide a response to the multiple pressures, constraints, changes, and mutations it faces from the environment. Complexity as a property of a system is not a seen as handicap, and instead can be an asset and a long-term guarantee. Tackling complexity can lead to restructuring within the system - eliminating, acquiring, or modifying its components. Such evolutions lead to the emergence of new performances, new risks, and new ruptures, which must be recognized and understood.

Agriculture - through the interaction between all of its components (individuals, livestock, crops, premises, machinery, funders, legislators, customers, suppliers) - is by nature a complex activity, as it must meet multiple requirements. More specifically, three major challenges must be met; these are to ensure the quantity of food for a growing population, to guarantee the viability of farmers and trades associated with them, and to protect the environment in a sustainable way. These key objectives are even more difficult to achieve in a context that has been severely disrupted by the emergence of phenomena associated with climate change, one of the most pressing issues of the twenty-first century. The factors contributing to it are complex, and the more we know about these factors, the more complex the situation becomes. Climate change is probably the first global environmental issue to be recognized as radically systemic, and it is complex in relation to the causes related to its anthropogenic and/or natural origin, but also to the solutions envisaged to reverse the phenomenon such as fundamental changes in the way energy is transformed, distributed, and consumed, as well as changes in lifestyles and other related factors.

The aim of this Special Issue is to attract original research contributions and comprehensive reviews that highlight the new risks associated with agricultural systems. The papers will be presented from a complexity viewpoint, including factors associated with uncertainty, non-linear behaviour, multi-scale (geographical or spatial) effects, interaction, self-organization, network structure, emergence of chaotic behaviour, and cascade effects. In a non-exhaustive list, it could cover issues of crop selection and planning, rationalization of irrigation, pest control, farm and ecosystem management, natural risks (floods, drought, heavy rains, hail, bushfires, etc.), health issues (environmental pollution, food security), agricultural tourism development, and sustainability.

Potential topics include but are not limited to the following:

• Stochastic assessment of vulnerability, exposure and risk of complex agriculture systems
• Numerical methods for the multiscale modelling and simulation of agriculture systems
• Multi-dimensional models and multi-time varying models in yield forecast
• Nonlinear dynamics robustness and resilience of agriculture systems
• Optimal operation, protection, and planning for complex agriculture systems
• Bifurcation and chaotic organization analysis in agriculture systems
• Model validation through field experiment and measurements of complex agriculture systems
• Sensors, data collection, and complex knowledge handling for agricultural systems