Risk analysis frameworks used in biological control and introduction of a novel Bayesian network tool
journal contribution
posted on 2023-05-03, 22:18authored byNicolas Meurisse, Bruce Marcot, Owen Woodberry, Barbara BarrattBarbara Barratt, Jacqui Todd
Classical biological control, the introduction of natural enemies to new environments to control unwanted pests or weeds, is, despite numerous successful examples, associated with rising concerns about unwanted environmental impacts such as population decline of nontarget species. Recognition of these biosafety risks is globally increasing, and prerelease assessments of biological control agents (BCAs) have become more rigorous in many countries. We review the current approaches to risk assessment for BCAs as used in Australasia, Europe, and North America. Traditionally, these assessments focus on providing assurance about the specificity of a proposed BCA, generally via a list of suitable versus nonsuitable hosts determined through laboratory specificity tests (i.e., by determining the BCA's physiological host range). The outcome of interactions of proposed agents in the natural environment can differ from laboratory-based predictions. Potential nontarget host testing may be incomplete, additional ecological barriers under field conditions may limit encounters between BCA and nontargets or reduce attack levels, and BCAs could disperse to habitats beyond those used by the target species and adversely affect nontarget species. We advocate for the adoption of more comprehensive, ecologically-based, probabilistic risk assessment approaches to BCA introductions. An example is provided using a Bayesian network that can integrate information on probabilities and uncertainties of a BCA to spread and establish in new habitats, interact with nontarget species in these habitats, and eventually negatively impact the populations of these nontarget species. Our new model, Biocontrol Adverse Impact Probability Assessment, aims to be incorporated into a structured decision-making framework to support national regulatory authorities.
Meurisse, N., Marcot, B. G., Woodberry, O., Barratt, B. I. P., & Todd, J. H. (2022). Risk analysis frameworks used in biological control and introduction of a novel Bayesian network tool. Risk Analysis, 42(6), 1255–1276. https://doi.org/10.1111/risa.13812