Integrating fire predisposition assessment into decision support systems for mountain forest management

Area of Science:

• Forestry science
• Climate change adaptation
• Ecosystem management

Background:

• Long-term planning for European Alpine mountain forests requires balancing biodiversity and ecosystem services (BES) with disturbance risks under climate change.
• Existing decision support systems (DSSs) integrate climate-sensitive modeling and disturbance risk assessments (bark beetle, windthrow) but need adaptation for emerging threats like forest fires.

Purpose of the Study:

• To introduce the integration of a fire predisposition assessment system (PAS) into a DSS for enhanced long-term mountain forest management.
• To enable identification of conflicting forest management objectives concerning BES provision and disturbance mitigation under climate change.

Main Methods:

• Developed and integrated a fire predisposition assessment system (PAS) into a DSS.
• The fire PAS incorporates factors including topography, climate, wildland-urban interface, and stand structure.
• The system allows for integrated evaluation of fire predisposition alongside risks from bark beetle and windthrow, and BES provision.

Main Results:

• The enhanced DSS can assess multiple predisposing factors for forest fires.
• Integrated evaluation of fire risk with other disturbances and BES provision is now possible.
• The modular structure of the fire PAS allows for flexible adaptation to different scales and integration with various forest models.

Conclusions:

• The expanded DSS supports informed management decisions by identifying conflicts between BES provision and disturbance mitigation in mountain forests.
• This approach is crucial for adapting forest management strategies to climate-change-induced shifts in disturbance regimes.
• The system's adaptability enhances its utility across diverse forest ecosystems and planning scenarios.