A decision framework for prioritizing multiple management actions for threatened marine megafauna

Area of Science:

• Conservation Biology
• Resource Management
• Optimization Theory

Background:

• Insufficient resources for biodiversity conservation demand systematic prioritization frameworks.
• Existing methods often lack integration of local knowledge and socio-political context.
• Prioritizing management actions is crucial for maximizing conservation outcomes.

Purpose of the Study:

• To develop and test a novel framework for prioritizing conservation actions under budget constraints.
• To integrate local and Indigenous community knowledge with expert opinion and optimization software.
• To maximize conservation outcomes by minimizing threats across a species' range.

Main Methods:

• Developed a systematic framework using budget constraints to maximize conservation outcomes.
• Integrated local knowledge and expert opinion with optimization software for action prioritization.
• Applied the framework to the flatback turtle (Natator depressus) in a data-poor context.

Main Results:

• The framework successfully identified optimal management actions for flatback turtle egg conservation.
• Optimized scenarios, particularly those combining aerial and ground strategies, outperformed others.
• Optimized scenarios demonstrated higher cost-effectiveness compared to preselected scenarios.

Conclusions:

• The novel framework provides a foundation for more effective conservation investments.
• It offers guidance for prioritizing actions within recovery plans, considering socio-political context.
• The adaptable method can be applied to diverse species, scales, and life stages.