Lessons from other disciplines for setting management thresholds for biodiversity conservation

Area of Science:

• Ecology
• Conservation Biology
• Systems Management

Background:

• State-dependent management aims to maintain systems in desired states using defined boundaries and action plans.
• This approach is common in various sectors but relatively new to conservation management, despite practitioner interest.
• Concerns exist regarding the lack of robust processes for implementing state-dependent management in conservation.

Purpose of the Study:

• To review literature on threshold-based management across diverse industries.
• To identify methods for setting management thresholds and potential lessons for conservation.
• To understand how different objectives influence threshold setting and action selection.

Main Methods:

• Conducted an extensive literature review of threshold-based management.
• Analyzed 843 studies from 22 industries, identifying 75 different threshold-setting methods.
• Categorized methods into six broad approaches: expert-driven, statistical, predictive, optimization, experimental, and artificial intelligence.

Main Results:

• Identified 75 threshold-setting methods across 22 industries, spanning six broad approaches.
• Found that study objectives influenced the methods used for setting thresholds and selecting actions.
• Observed that expert judgment, often supported by computational tools, plays a significant role in threshold setting across industries.

Conclusions:

• Methods from other disciplines can inform conservation decision-making for setting management thresholds.
• Implementing threshold-based management can link monitoring to timely and effective conservation actions.
• Adopting diverse threshold-setting approaches can enhance the robustness of conservation management systems.