Iterative scenarios for social-ecological systems.

Area of Science:

• Environmental Management
• Urban Planning
• Systems Ecology

Background:

• Social-ecological systems require adaptive management (AM) and scenario planning (SP) to address uncertainty and plan for the future.
• Existing approaches like AM and SP have limitations in managing complex social-ecological systems.
• High uncertainty in outcomes, diverse benefits, and social implications challenge current management strategies.

Purpose of the Study:

• Introduce iterative scenarios (IS) as a hybrid approach for social-ecological systems management.
• Combine the strengths of adaptive management and scenario planning to address complex uncertainties.
• Provide a framework for managing systems with numerous, cross-scale benefits and complex social dynamics.

Main Methods:

• Developed iterative scenarios (IS) by integrating adaptive management's iterative learning with scenario planning's futures orientation.
• Applied the IS approach to a green infrastructure project in Cleveland, Ohio, focusing on a disinvested neighborhood.
• Utilized the IS framework to manage high uncertainty regarding environmental learning and social desirability.

Main Results:

• Demonstrated the value of iterative scenarios (IS) in managing social-ecological systems with high uncertainty.
• Successfully applied IS to a green infrastructure project, balancing environmental learning with unknown social outcomes.
• Showcased IS as a suitable approach for complex, real-world management challenges.

Conclusions:

• Iterative scenarios (IS) is an effective hybrid approach for managing social-ecological systems under high uncertainty.
• IS accommodates the complexity inherent in natural resource management and social implications.
• The IS approach offers a valuable tool for achieving desirable regimes in diverse social-ecological contexts.