Optimization of landscape services under uncoordinated management by multiple landowners

Area of Science:

• Ecological modeling
• Landscape ecology
• Conservation science

Background:

• Landscapes are often fragmented by private ownership, complicating landscape-level management and conservation.
• Achieving landscape services is challenging due to difficulties in enforcing site-specific rules across multiple landowners.
• Uncoordinated landowner actions can hinder the conservation of critical landscape features.

Purpose of the Study:

• To develop a multi-objective simulation-optimization procedure for landscape management under multiple ownerships.
• To identify non-spatial management regimes that meet landscape-level objectives despite uncertain landowner responses.
• To demonstrate the procedure's utility in optimizing fuel treatments for cork oak forests.

Main Methods:

• A multi-objective genetic algorithm combined with a landscape pattern simulator.
• Approximation of the non-dominated Pareto frontier to balance competing objectives.
• Modeling landowner responses to management rules for forecasting landscape trends.

Main Results:

• A trade-off exists between management costs, fire risk reduction, and biodiversity protection.
• Optimal regimes involved ~60% of landowners managing understory at short intervals (5 years) and others at long intervals (75 years) or not at all.
• The resulting landscape mosaic favored fire risk reduction and biodiversity through varied understory conditions.

Conclusions:

• The simulation-optimization procedure effectively balances landscape-level objectives with uncoordinated landowner actions.
• This approach can be adapted for diverse socio-ecological systems requiring landscape heterogeneity maintenance.
• It offers a framework for managing complex landscapes with multiple stakeholders and uncertain compliance.