A practical guide to DNA-based methods for biodiversity assessment.

Abstract

This book represents a synthesis of knowledge and best practice in the field of DNA-based biomonitoring at the time of writing. It has been written with end-users of molecular tools in mind, as well as those who are new to the field in research settings and are looking to gain an overall grounding in the subject area. For each of the main types of sample (water, soil / sediment, bulk invertebrates and diatoms), and for each stage of the field and laboratory processes, we outline key considerations, decisions that need to be made, factors that might influence those decisions, and trade-offs inherent in the choices made. We hope that this will help users, practitioners, and those commissioning DNA-based monitoring programmes to navigate this large field and critically evaluate the strengths and weaknesses of different analysis workflows based on context, project aims and available resources. DNA-based methods for species detection and identification have revolutionised our ability to assess biodiversity in terrestrial, freshwater and marine ecosystems. Starting from the seminal study that used eDNA to detect invasive american bullfrogs in France (Ficetola et al. 2008), research conducted over the last decade has demonstrated the power of these approaches for surveying a wide range of species and groups. Early applications included the use of eDNA to monitor Asian Carp in the USA (Jerde et al. 2013). Following heavy scrutiny, the method was eventually adopted, and is still employed today by the United States Geological Survey (USGS). A flurry of research followed, with tests designed for many threatened and invasive species including New zealand mudsnails (Goldberg et al. 2013), american crayfish (Geerts et al. 2018), gammarids (Blackman et al. 2017), and great crested newts (Biggs et al. 2015). The great crested newt eDNA test has been employed for regulatory monitoring in the UK since 2014. During the same time period, there was a proliferation of research studies that used high-throughput sequencing approaches to describe whole communities of organisms from mixed species and environmental samples, using an approach termed DNA metabarcoding (Taberlet et al. 2012c). As the field developed fast and the approaches were applied to a wide range of research and monitoring objectives, a high level of methodological variation was introduced at all stages of the workflow (Seymour 2019). Thus, while a significant level of consensus on scientific best-practice now exists in many areas, this may not be readily discerned from the now-extensive body of research literature. As environmental practitioners and policy makers are now increasingly starting to integrate DNAbased methods into routine monitoring applications including protected species licensing1, statutory monitoring2 (Hänfling et al. 2016) and environmental impact assessment3, various national and international efforts have been undertaken to standardise methods and integrate them into monitoring frameworks (Pilliod et al. 2019, Loeza-Quintana et al. 2020, Minamoto et al. 2021, Pawlowski et al. 2020a4). In Europe, the EU COST Action DNAqua-Net (Leese et al. 2018) has been working towards incorporating molecular monitoring tools for Biological Quality Elements (BQEs, e.g., fish, macroinvertebrates and phytoplankton- benthos) into the Water Framework Directive (WFD, 2000/60/EC)5 and the Marine Strategy Framework Directive (MSFD, 2008/56/EC)6. Thus, emphasis now shifts from fundamental research to robust and efficient application of DNAbased methods for operational use at large scales. This requires that scientific robustness is balanced with consideration of the practical realities faced by environmental managers. Moreover, there is increased need for strong quality assurance in a setting where non-expert field samplers and commercial laboratories are involved with the generation of data that non-specialist decision-makers then rely on to inform potentially costly action (or non-action). This places increased emphasis on robustness, replicability, traceability and ease-of-use, which may not always be the central focus of studies carried out in the academic research environment. This document aims to summarise the scientific consensus relating to every step of the field and laboratory workflows involved in the most common types of samples and analyses. We do not go into great detail regarding bioinformatics (computational processing of sequence data) and data analysis since these are extensive topics in their own right. We uniquely set the field and lab steps in the context of the practical and logistical constraints faced by environmental managers in terms of cost, logistics, safety, ease-of-use, and quality assurance, highlighting key decisions to be made and the inherent trade-offs associated with the various options. We hope that this will support non-experts, and those new to the field, to navigate the key considerations associated with planning or evaluating monitoring programmes using DNA-based monitoring methods. Additionally, it will aid decision-makers in writing and evaluating tenders and proposals, ensuring that the methods used for a given project are fit-for-purpose and that results are correctly interpreted. Alongside the many areas of emerging consensus, there remain some areas where further research is still required to balance scientific best-practice with the constraints and priorities of end-users. We hope that by shining a light on the importance of these issues, the research community will be encouraged to address them. More generally, we hope to inspire researchers in this now highly-applied scientific field to consider end-user constraints when designing and implementing research projects. This will help to accelerate uptake by users and maximise the impact of research. DNA-based bioassessment methods continue to evolve, and there are several emerging technologies that show exciting promise to move beyond even what is possible today. Examples include in-field sequencing using the MinION device from Oxford Nanopore Technologies (Pomerantz et al. 2018, Davidov et al. 2020, Hatfield et al. 2020), PCR-free metagenomic approaches (Bista et al. 2018, Giebner et al. 2020) and CRISPR for rapid detection of species, which is particularly relevant for invasive an non-native species monitoring (Williams et al. 2019, 2020). We recognise the potential of these methods, but do not consider them in detail here, since they are not yet far enough developed for routine application.