Risk Analysis Frameworks Used in Biological Control and Introduction of a Novel Bayesian Network Tool

Area of Science:

• Ecology
• Conservation Biology
• Risk Assessment

Background:

• Classical biological control introduces natural enemies to manage pests and weeds.
• Growing concerns exist regarding environmental impacts, including harm to non-target species.
• Prerelease assessments for biological control agents (BCAs) are becoming more rigorous globally.

Purpose of the Study:

• To review current risk assessment approaches for BCAs in Australasia, Europe, and North America.
• To advocate for more comprehensive, ecologically-based, probabilistic risk assessment methods.
• To introduce a new model, Biocontrol Adverse Impact Probability Assessment (BAPA), for structured decision-making.

Main Methods:

• Review of traditional laboratory-based specificity tests focusing on physiological host range.
• Analysis of limitations of laboratory predictions compared to real-world ecological interactions.
• Development of a Bayesian network model to integrate probabilities of BCA spread, establishment, and non-target impacts.

Main Results:

• Laboratory host range testing may not fully predict field outcomes.
• Ecological barriers and BCA dispersal can lead to unforeseen non-target effects.
• The BAPA model offers a probabilistic framework to assess adverse impacts.

Conclusions:

• Current BCA risk assessments require enhancement with ecological data and probabilistic approaches.
• The BAPA model provides a structured framework to support regulatory decision-making for BCA introductions.
• Adopting ecologically-based risk assessments is crucial for minimizing unintended environmental consequences.