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Metabarcoding advances agricultural invertebrate biomonitoring by enhancing resolution, increasing throughput, and facilitating network inference

Lookup NU author(s): Ben HawthorneORCiD, Dr Jordan CuffORCiD, Professor Darren Evans



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Biomonitoring of agriculturally important insects is increasingly vital given our need to understand a) the severity of impacts by pests and pathogens on crop yield and health, and b) the impact of environmental change and land management on insects, in line with sustainable development and global conservation targets. Traditional entomological traps remain an important part of the biomonitoring toolbox, but sample processing is laborious and introduces latency, and accuracy can be variable. The integration of molecular techniques such as environmental DNA and DNA metabarcoding into insect biomonitoring has gained increasing attention, but the advantages of doing so, the kind of data this can generate, and how easily and effectively molecular analyses can be integrated with the diverse types of entomological traps currently used remains relatively unclear. In this review, we examine how combining DNA metabarcoding with a range of conventional and unconventional entomological sampling techniques can advance biomonitoring in a way that is useful to researchers and practitioners. We highlight some of the key challenges and how to mitigate them, using examples of its integration with different sampling methods from the literature (e.g. interception, pitfall, and sticky traps) to demonstrate efficacy and suitability. We discuss how metabarcoding data can be used to infer ecological networks, emphasising the importance of this as a framework for understanding species interactions and ecosystem functioning for more effective and descriptive biomonitoring.Finally, future advances of biomonitoring are highlighted, alongside recommendations of best practice for researchers both new to and experienced in invertebrate biomonitoring with metabarcoding.

Publication metadata

Author(s): Hawthorne BSJ, Cuff JP, Collins LE, Evans DM

Publication type: Article

Publication status: Published

Journal: Agricultural and Forest Entomology

Year: 2024

Pages: epub ahead of print

Online publication date: 08/05/2024

Acceptance date: 27/04/2024

Date deposited: 29/04/2024

ISSN (print): 1461-9555

ISSN (electronic): 1461-9563

Publisher: Wiley-Blackwell Publishing Ltd.


DOI: 10.1111/afe.12628


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Funder referenceFunder name
Institute for Agri-Food Research and Innovation, IAFRI PhD Studentship