This project aims to explore an innovative approach to pest detection through molecular dietary analysis of natural predators. Traditional surveillance methods can be costly and labour-intensive, and there are some pests that are a challenge to trap, leading to delayed detection and eradication efforts. With climate change and global trade increasing the risk of new pest introductions, it is crucial to develop efficient and scalable monitoring systems. Techniques that analyse genetic material present in the diet of predators present promising alternatives by enabling passive, widespread pest detection. However, challenges such as selecting appropriate predator species, addressing technical biases in DNA analysis, and minimizing false positive and negative results must be carefully considered. A robust decision-making framework is needed to ensure that monitoring organizations adopt best practices and align with existing policies and regulations.

The project will conduct a systematic review of predator dietary analysis for pest detection, develop a decision-making framework for implementation, present three case studies using birds, bats, and spiders, and assess alignment with current regulatory frameworks. The review will analyse methodological developments, cost-effectiveness, and standardization opportunities, as well as evaluating ecological and technical considerations to optimize monitoring strategies, which will be brought together in a decision framework to guide future potential implementation of these approaches. The applied case studies will investigate real-world feasibility, exploring the integrating dietary metabarcoding with existing monitoring networks to potentially improve detection efficiency.

The project seeks to enhance Scotland’s pest surveillance capabilities and inform global best practices in predator diet analysis.