The identification of floral visitation by pollinators provides an opportunity to improve our understanding of the fine-scale ecological interactions between plants and pollinators, contributing to biodiversity conservation and promoting ecosystem health. In this review we outline the various methods which can be used to identify floral visitation, providing a comparison between molecular and non-molecular methods. We review the literature covering the ways in which DNA metabarcoding has been used to answer ecological questions relating to plant use by pollinators and discuss the findings of this research. We present detailed methodological considerations for each step of the metabarcoding workflow, from sampling through to amplification and finally bioinformatic analysis. Detailed guidance is provided to researchers for utilization of these techniques, emphasizing the importance of standardization of methods and improving the reliability of results. Future opportunities and directions of using molecular methods to analyze plant-pollinator interactions are then discussed.

A decade after environmental scientists integrated high-throughput sequencing technologies in their toolbox, the genomics-based monitoring of anthropogenic impacts on biodiversity and ecosystems is yet to be implemented by regulatory frameworks. Despite the broadly acknowledged potential of environmental DNA and RNA to cost-efficiently and accurately monitor biodiversity, technical limitations and conceptual issues still stand in the way of its routine application by end-users. In addition, the multiplicity of potential implementation strategies may contribute to a perception of the methodology as being premature or “in development”, hence restraining regulators from binding these tools into legal frameworks. This review focuses on the strengths and limitations of genomics-based strategies that have emerged over the past ten years and have been classified for this purpose into three broad strategies: (A) Taxonomy-based approaches that focus on known bio-indicators or the diversity of taxonomically described taxa, (B) De novo approaches that do not require well-established taxonomy, and (C) Function-based approaches that rely on community-wide metrics, where taxa are interchangeable, or on functional profiles instead of compositional turnovers. We finally propose a roadmap for the implementation of environmental genomics into routine monitoring programs that leverage recent analytical advancements, upon which some critical limitations are alleviated.