A predictive approach to integrating connectivity into landscape scale protected areas planning

Area of Science:

• Conservation Science
• Landscape Ecology
• Biodiversity Management

Background:

• Global biodiversity loss necessitates protecting 30% of terrestrial lands by 2030 (30x30).
• Existing protected area networks often lack sufficient ecological connectivity.
• Improved planning is crucial for effective area-based conservation.

Purpose of the Study:

• To develop and validate methods for incorporating connectivity into protected area planning.
• To identify characteristics of new protected areas that maximize network connectivity.
• To provide a prioritization tool for protected area planners.

Main Methods:

• Connectivity analyses using simulated parks in Ontario, Canada.
• Regression modeling to identify predictors of optimal park placement for connectivity.
• Prioritization of candidate parks based on predicted connectivity benefits.

Main Results:

• All new parks improved network connectivity, but placement significantly impacted the degree of improvement.
• Optimal park placement involves low edge-to-area ratio, central location, proximity to network nodes, low internal human impact, and adjacency to developed areas.
• A predictive model was developed and applied to prioritize candidate sites.

Conclusions:

• The developed model offers a practical tool for evaluating and prioritizing candidate protected areas based on connectivity benefits.
• This approach supports Indigenous communities, land managers, and planners in meeting 30x30 targets with enhanced ecological connectivity.
• Explicitly incorporating connectivity into planning is vital for effective biodiversity conservation.