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

Abstract

Biomonitoring of agriculturally important insects is increasingly important 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 their processing is laborious and introduces latency, and they are variably accurate. The integration of molecular techniques such as 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 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, malaise, and sticky traps) to demonstrate efficacy and suitability. Finally, we discuss how these 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.