Trade-offs and efficiencies in optimal budget-constrained multispecies corridor networks

Area of Science:

• Conservation biology
• Spatial planning
• Ecological modeling

Background:

• Isolated protected areas are insufficient for biodiversity goals.
• Single-species corridor design is ecologically suboptimal and expensive.
• Cost-effective, multispecies connectivity is needed.

Purpose of the Study:

• Develop and demonstrate algorithms for optimizing wildlife corridors for multiple species within a budget.
• Evaluate trade-offs between cost and connectivity for different species.
• Identify cost savings and ecological benefits of joint optimization.

Main Methods:

• Developed algorithms for multispecies corridor optimization under budget constraints.
• Applied algorithms in western Montana to assess connectivity for grizzly bears and wolverines.
• Compared joint optimization with single-species optimization and budget allocation scenarios.

Main Results:

• Joint optimization achieved near-optimal connectivity for individual species (grizzly bears: 14%, wolverines: 11%) while saving 75% of the cost.
• Combined budget optimization improved connectivity for both species compared to splitting the budget.
• Demonstrated economies of scale and complementarities in conservation planning.

Conclusions:

• Jointly optimizing corridor design for cost and multispecies connectivity is more effective than single-species approaches.
• This approach reduces acquisition costs and better aligns corridors with conservation priorities.
• Facilitates more efficient and effective wildlife corridor conservation planning.