Biodiversity monitoring using environmental DNA

Abstract

Monitoring biodiversity is essential to protect, preserve and restore ecosystems, particularly in the context of current challenges such as climate change, habitat destruction and globalization (Baird & Hajibabaei, 2012). Biomonitoring is needed for developing biotic indices for assessing ecological status, measuring impacts of anthropogenic activities in natural ecosystems, evaluating biodiversity loss, surveying nonindigenous species, conservation, and identifying cryptic species (Balvanera et al., 2006;Fišer et al., 2018). Thus, spatially and temporally structured biomonitoring activities provide a powerful tool for the implementation of regional, national and international regulations, directives and policies for nature conservation.However substantial impediments exist including access to remote locations, limited specialist taxonomic knowledge, cost, slow pace of human-driven data analyses, and typically low sensitivity for detection of rare and elusive species (Zinger et al., 2020). These drawbacks are often translated into expensive monitoring activities with limited spatial, temporal and taxonomic coverage. In this context, new approaches for biomonitoring are being explored, among which advanced DNA-based technologies are emerging (Kissling et al., 2018). The field of biodiversity monitoring through the analysis of the pool of DNA isolated from environmental samples, referred to as environmental DNA or eDNA (Pawlowski et al., 2020;Taberlet et al., 2012), is rapidly growing. This growth is being driven through improved approaches for sampling, data generation and analyses, and with recent advances on how eDNA should be interpreted for biodiversity assessments (Bohmann et al., 2014). The success of eDNA-based biomonitoring is reflected in exponential growth of publications within this area and increasing submissions to Molecular Ecology Resources in particular (Figure 1). Molecular Ecology Resources aims to publish high quality eDNA studies that serve as broad resources, including innovative methodologies for DNA sampling, enhanced laboratory protocols for data generation, or new computer programs and statistical advances for data analyses. Thus, the aim of this editorial is to contribute to producing good quality DNA dataderived essential biodiversity variables (EBVs) (Kissling et al., 2018) by providing guidance to the community submitting articles on the subject. For that purpose, we have summarized best practices established in published literature related to the different phases involved in the process, namely sampling, laboratory work, bioinformatic analyses and data interpretation (Figure 2).

Environmental DNA provides quantitative estimates of Pacific hake abundance and distribution in the open ocean

“…[6]), uncertainty about the strength of the eDNA-abundance relationship due to the complexity of eDNA generation, transport, degradation and detection have limited the application of eDNA in many quantitative applications [5,7,8]. While the use of eDNA methods has grown exponentially from tens of publications in 2010 to many hundreds in 2020 [6,9], reflecting widespread adoption of eDNA technologies, basic questions about the characteristics of eDNA limit its practical application and slow its adoption in environmental management.…”

Fish community surveys in eelgrass beds using both eDNA metabarcoding and seining: implications for biodiversity monitoring in the coastal zone

“…Environmental DNA (eDNA) metabarcoding is a revolutionary approach for measuring biodiversity, which can rapidly and reliably characterize species composition from environmental samples without isolating target organisms (Taberlet et al 2012;Rodríguez-Ezpeleta et al 2021).…”

Editorial 2022

“…prior to further analyses (Jauhal and Newcomb, 2021). There were also multiple articles providing guidance for biodiversity monitoring with eDNA (Bensch et al, 2021;Jurburg et al, 2021;Rodríguez-Ezpeleta et al, 2021). Kolář, 2021).…”

“…Specifically, articles included achieving high quality reference genome assemblies (Whibley et al, 2021) and best practices for downstream sequencing applications such as combining data across sequencing platforms (De‐Kayne et al, 2021) and assessing reference genomes prior to further analyses (Jauhal and Newcomb, 2021). There were also multiple articles providing guidance for biodiversity monitoring with eDNA (Bensch et al, 2021; Jurburg et al, 2021; Rodríguez‐Ezpeleta et al, 2021).…”