Extracting abundance information from DNA-based data

Microbial, holobiont, and Tree of Life eDNA/eRNA for enhanced ecological assessment

Microbial environmental DNA and RNA (collectively 'eNA') originate from a diverse and abundant array of microbes present in environmental samples. These eNA signals, largely representing whole organisms, serve as a powerful complement to signals derived from fragments or remnants of larger organisms. Integrating microbial data into the toolbox of ecosystem assessments and biotic indices therefore has the potential to transform how we use eNA data to understand biodiversity dynamics and ecosystem functions, and to inform the next generation of environmental monitoring. Incorporating holobiont and Tree of Life approaches into eNA analyses offers further holistic insight into the range of ecological interactions between microbes and other organisms, paving the way for advancing our understanding of, and ultimately manipulating ecosystem properties pertinent to environmental management, conservation, wildlife health, and food production.

Host weight, seasonality and anthropogenic factors contribute to parasite community differences between urban and rural foxes

Pathogens often occur at different prevalence along environmental gradients. This is of particular importance for gradients of anthropogenic impact such as rural-urban transitions presenting a changing interface between humans and wildlife. The assembly of parasite communities is affected by both the external environmental conditions and individual host characteristics. Hosts with low body weight (smaller individuals or animals with poor body condition) might be more susceptible to infection. Furthermore, parasites' mode of transmission might affect their occurrence: rural environments with better availability of intermediate hosts might favour trophic transmission, while urban environments, typically with dense definitive host populations, might favour direct transmission. We here study helminth communities (141 intestinal samples) within the red fox (Vulpes vulpes), a synanthropic host, using DNA metabarcoding of multiple marker genes. We analysed the effect of urbanisation, seasonality and host-intrinsic (weight, sex) variables on helminth communities. Helminth species richness increased in foxes with lower body weight and in winter and spring. Season and urbanisation, however, had strong effects on the community composition, i.e., on the identity of the detected species. Surprisingly, transmission in two-host life cycles (trophic transmission) was more pronounced in urban Berlin than in rural Brandenburg. This disagrees with the prevailing hypothesis that trophically transmitted helminths are less prevalent in urban areas than in rural areas. Generally, co-infestations with multiple helminths and high infection intensity are associated with lighter (younger, smaller or low body condition) animals. Both host-intrinsic traits and environmental drivers together shape parasite community composition and turnover along urban-rural gradients.

Combining environmental DNA and remote sensing for efficient, fine-scale mapping of arthropod biodiversity

Arthropods contribute importantly to ecosystem functioning but remain understudied. This undermines the validity of conservation decisions. Modern methods are now making arthropods easier to study, since arthropods can be mass-trapped, mass-identified, and semi-mass-quantified into 'many-row (observation), many-column (species)' datasets, with homogeneous error, high resolution, and copious environmental-covariate information. These 'novel community datasets' let us efficiently generate information on arthropod species distributions, conservation values, uncertainty, and the magnitude and direction of human impacts. We use a DNA-based method (barcode mapping) to produce an arthropod-community dataset from 121 Malaise-trap samples, and combine it with 29 remote-imagery layers using a deep neural net in a joint species distribution model. With this approach, we generate distribution maps for 76 arthropod species across a 225 km2 temperate-zone forested landscape. We combine the maps to visualize the fine-scale spatial distributions of species richness, community composition, and site irreplaceability. Old-growth forests show distinct community composition and higher species richness, and stream courses have the highest site-irreplaceability values. With this 'sideways biodiversity modelling' method, we demonstrate the feasibility of biodiversity mapping at sufficient spatial resolution to inform local management choices, while also being efficient enough to scale up to thousands of square kilometres. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Towards holistic insect monitoring: species discovery, description, identification and traits for all insects

Holistic insect monitoring needs scalable techniques to overcome taxon biases, determine species abundances, and gather functional traits for all species. This requires that we address taxonomic impediments and the paucity of data on abundance, biomass and functional traits. We here outline how these data deficiencies could be addressed at scale. The workflow starts with large-scale barcoding (megabarcoding) of all specimens from mass samples obtained at biomonitoring sites. The barcodes are then used to group the specimens into molecular operational taxonomic units that are subsequently tested/validated as species with a second data source (e.g. morphology). New species are described using barcodes, images and short diagnoses, and abundance data are collected for both new and described species. The specimen images used for species discovery then become the raw material for training artificial intelligence identification algorithms and collecting trait data such as body size, biomass and feeding modes. Additional trait data can be obtained from vouchers by using genomic tools developed by molecular ecologists. Applying this pipeline to a few samples per site will lead to greatly improved insect monitoring regardless of whether the species composition of a sample is determined with images, metabarcoding or megabarcoding. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Three steps towards comparability and standardization among molecular methods for characterizing insect communities

Molecular methods are currently some of the best-suited technologies for implementation in insect monitoring. However, the field is developing rapidly and lacks agreement on methodology or community standards. To apply DNA-based methods in large-scale monitoring, and to gain insight across commensurate data, we need easy-to-implement standards that improve data comparability. Here, we provide three recommendations for how to improve and harmonize efforts in biodiversity assessment and monitoring via metabarcoding: (i) we should adopt the use of synthetic spike-ins, which will act as positive controls and internal standards; (ii) we should consider using several markers through a multiplex polymerase chain reaction (PCR) approach; and (iii) we should commit to the publication and transparency of all protocol-associated metadata in a standardized fashion. For (i), we provide a ready-to-use recipe for synthetic cytochrome c oxidase spike-ins, which enable between-sample comparisons. For (ii), we propose two gene regions for the implementation of multiplex PCR approaches, thereby achieving a more comprehensive community description. For (iii), we offer guidelines for transparent and unified reporting of field, wet-laboratory and dry-laboratory procedures, as a key to making comparisons between studies. Together, we feel that these three advances will result in joint quality and calibration standards rather than the current laboratory-specific proof of concepts. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Environmental DNA: The next chapter

Molecular tools are an indispensable part of ecology and biodiversity sciences and implemented across all biomes. About a decade ago, the use and implementation of environmental DNA (eDNA) to detect biodiversity signals extracted from environmental samples opened new avenues of research. Initial eDNA research focused on understanding population dynamics of target species. Its scope thereafter broadened, uncovering previously unrecorded biodiversity via metabarcoding in both well-studied and understudied ecosystems across all taxonomic groups. The application of eDNA rapidly became an established part of biodiversity research, and a research field by its own. Here, we revisit key expectations made in a land-mark special issue on eDNA in Molecular Ecology in 2012 to frame the development in six key areas: (1) sample collection, (2) primer development, (3) biomonitoring, (4) quantification, (5) behaviour of DNA in the environment and (6) reference database development. We pinpoint the success of eDNA, yet also discuss shortfalls and expectations not met, highlighting areas of research priority and identify the unexpected developments. In parallel, our retrospective couples a screening of the peer-reviewed literature with a survey of eDNA users including academics, end-users and commercial providers, in which we address the priority areas to focus research efforts to advance the field of eDNA. With the rapid and ever-increasing pace of new technical advances, the future of eDNA looks bright, yet successful applications and best practices must become more interdisciplinary to reach its full potential. Our retrospect gives the tools and expectations towards concretely moving the field forward.

Capacity and establishment rules govern the number of nonnative species in communities of ground-dwelling invertebrates

Nonnative species are a key agent of global change. However, nonnative invertebrates remain understudied at the community scales where they are most likely to drive local extirpations. We use the North American NEON pitfall trapping network to document the number of nonnative species from 51 invertebrate communities, testing four classes of drivers. We sequenced samples using the eDNA from the sample's storage ethanol. We used AICc informed regression to evaluate how native species richness, productivity, habitat, temperature, and human population density and vehicular traffic account for continent-wide variation in the number of nonnative species in a local community. The percentage of nonnatives varied 3-fold among habitat types and over 10-fold (0%-14%) overall. We found evidence for two types of constraints on nonnative diversity. Consistent with Capacity rules (i.e., how the number of niches and individuals reflect the number of species an ecosystem can support) nonnatives increased with existing native species richness and ecosystem productivity. Consistent with Establishment Rules (i.e., how the dispersal rate of nonnative propagules and the number of open sites limits nonnative species richness) nonnatives increased with automobile traffic-a measure of human-generated propagule pressure-and were twice as common in pastures than native grasslands. After accounting for drivers associated with a community's ability to support native species (native species richness and productivity), nonnatives are more common in communities that are regularly seasonally disturbed (pastures and, potentially deciduous forests) and those experiencing more vehicular traffic. These baseline values across the US North America will allow NEON's monitoring mission to document how anthropogenic change-from disturbance to propagule transport, from temperature to trends in local extinction-further shape biotic homogenization.

Novel community data in ecology-properties and prospects

New technologies for monitoring biodiversity such as environmental (e)DNA, passive acoustic monitoring, and optical sensors promise to generate automated spatiotemporal community observations at unprecedented scales and resolutions. Here, we introduce 'novel community data' as an umbrella term for these data. We review the emerging field around novel community data, focusing on new ecological questions that could be addressed; the analytical tools available or needed to make best use of these data; and the potential implications of these developments for policy and conservation. We conclude that novel community data offer many opportunities to advance our understanding of fundamental ecological processes, including community assembly, biotic interactions, micro- and macroevolution, and overall ecosystem functioning.

Consistent effects of independent domestication events on the plant microbiota

The effect of plant domestication on plant-microbe interactions remains difficult to prove. In this study, we provide evidence of a domestication effect on the composition and abundance of the plant microbiota. We focused on the genus Phaseolus, which underwent four independent domestication events within two species (P. vulgaris and P. lunatus), providing multiple replicates of a process spanning thousands of years. We targeted Phaseolus seeds to identify a link between domesticated traits and bacterial community composition as Phaseolus seeds have been subject to large and consistent phenotypic changes during these independent domestication events. The seed bacterial communities of representative plant accessions from subpopulations descended from each domestication event were analyzed under controlled and field conditions. The results showed that independent domestication events led to similar seed bacterial community signatures in independently domesticated plant populations, which could be partially explained by selection for common domesticated plant phenotypes. Our results therefore provide evidence of a consistent effect of plant domestication on seed microbial community composition and abundance and offer avenues for applying knowledge of the impact of plant domestication on the plant microbiota to improve microbial applications in agriculture.

Persisting roadblocks in arthropod monitoring using non-destructive metabarcoding from collection media of passive traps

Background

Broad-scale monitoring of arthropods is often carried out with passive traps (e.g., Malaise traps) that can collect thousands of specimens per sample. The identification of individual specimens requires time and taxonomic expertise, limiting the geographical and temporal scale of research and monitoring studies. DNA metabarcoding of bulk-sample homogenates has been found to be faster, efficient and reliable, but the destruction of samples prevents a posteriori validation of species occurrences and relative abundances. Non-destructive metabarcoding of DNA extracted from collection medium has been applied in a limited number of studies, but further tests of efficiency are required with different trap types and collection media to assess the consistency of the method.

Methods

We quantified the detection rate of arthropod species when applying non-destructive DNA metabarcoding with a short (127-bp) fragment of mitochondrial COI on two combinations of passive traps and collection media: (1) water with monopropylene glycol (H2O-MPG) used in window-flight traps (WFT, 53 in total); (2) ethanol with monopropylene glycol (EtOH-MPG) used in Malaise traps (MT, 27 in total). We then compared our results with those obtained for the same samples using morphological identification (for WFTs) or destructive metabarcoding of bulk homogenate (for MTs). This comparison was applied as part of a larger study of arthropod species richness in silver fir (Abies alba Mill., 1759) stands across a range of climate-induced tree dieback levels and forest management strategies.

Results

Of the 53 H2O-MPG samples from WFTs, 16 produced no metabarcoding results, while the remaining 37 samples yielded 77 arthropod MOTUs in total, of which none matched any of the 343 beetle species morphologically identified from the same traps. Metabarcoding of 26 EtOH-MPG samples from MTs detected more arthropod MOTUs (233) than destructive metabarcoding of homogenate (146 MOTUs, 8 orders), of which 71 were shared MOTUs, though MOTU richness per trap was similar between treatments. While we acknowledge the failure of metabarcoding from WFT-derived collection medium (H2O-MPG), the treatment of EtOH-based Malaise trapping medium remains promising. We conclude however that DNA metabarcoding from collection medium still requires further methodological developments and cannot replace homogenate metabarcoding as an approach for arthropod monitoring. It can be used nonetheless as a complementary treatment when enhancing the detection of soft-bodied arthropods like spiders and Diptera.

Conceptual and empirical bridges between micro- and macroevolution

Explaining broad molecular, phenotypic and species biodiversity patterns necessitates a unifying framework spanning multiple evolutionary scales. Here we argue that although substantial effort has been made to reconcile microevolution and macroevolution, much work remains to identify the links between biological processes at play. We highlight four major questions of evolutionary biology whose solutions require conceptual bridges between micro and macroevolution. We review potential avenues for future research to establish how mechanisms at one scale (drift, mutation, migration, selection) translate to processes at the other scale (speciation, extinction, biogeographic dispersal) and vice versa. We propose ways in which current comparative methods to infer molecular evolution, phenotypic evolution and species diversification could be improved to specifically address these questions. We conclude that researchers are in a better position than ever before to build a synthesis to understand how microevolutionary dynamics unfold over millions of years.

FAVIS: Fast and versatile protocol for non-destructive metabarcoding of bulk insect samples

Insects are diverse and sustain essential ecosystem functions, yet remain understudied. Recent reports about declines in insect abundance and diversity have highlighted a pressing need for comprehensive large-scale monitoring. Metabarcoding (high-throughput bulk sequencing of marker gene amplicons) offers a cost-effective and relatively fast method for characterizing insect community samples. However, the methodology applied varies greatly among studies, thus complicating the design of large-scale and repeatable monitoring schemes. Here we describe a non-destructive metabarcoding protocol that is optimized for high-throughput processing of Malaise trap samples and other bulk insect samples. The protocol details the process from obtaining bulk samples up to submitting libraries for sequencing. It is divided into four sections: 1) Laboratory workspace preparation; 2) Sample processing-decanting ethanol, measuring the wet-weight biomass and the concentration of the preservative ethanol, performing non-destructive lysis and preserving the insect material for future work; 3) DNA extraction and purification; and 4) Library preparation and sequencing. The protocol relies on readily available reagents and materials. For steps that require expensive infrastructure, such as the DNA purification robots, we suggest alternative low-cost solutions. The use of this protocol yields a comprehensive assessment of the number of species present in a given sample, their relative read abundances and the overall insect biomass. To date, we have successfully applied the protocol to more than 7000 Malaise trap samples obtained from Sweden and Madagascar. We demonstrate the data yield from the protocol using a small subset of these samples.

Aquatic environmental DNA: A review of the macro-organismal biomonitoring revolution

Environmental DNA (eDNA) is the fastest growing biomonitoring tool fuelled by two key features: time efficiency and sensitivity. Technological advancements allow rapid biodiversity detection at both species and community levels with increasing accuracy. Concurrently, there has been a global demand to standardise eDNA methods, but this is only possible with an in-depth overview of the technological advancements and a discussion of the pros and cons of available methods. We therefore conducted a systematic literature review of 407 peer-reviewed papers on aquatic eDNA published between 2012 and 2021. We observed a gradual increase in the annual number of publications from four (2012) to 28 (2018), followed by a rapid growth to 124 publications in 2021. This was mirrored by a tremendous diversification of methods in all aspects of the eDNA workflow. For example, in 2012 only freezing was applied to preserve filter samples, whereas we recorded 12 different preservation methods in the 2021 literature. Despite an ongoing standardisation debate in the eDNA community, the field is seemingly moving fast in the opposite direction and we discuss the reasons and implications. Moreover, by compiling the largest PCR-primer database to date, we provide information on 522 and 141 published species-specific and metabarcoding primers targeting a wide range of aquatic organisms. This works as a user-friendly 'distillation' of primer information that was hitherto scattered across hundreds of papers, but the list also reflects which taxa are commonly studied with eDNA technology in aquatic environments such as fish and amphibians, and reveals that groups such as corals, plankton and algae are under-studied. Efforts to improve sampling and extraction methods, primer specificity and reference databases are crucial to capture these ecologically important taxa in future eDNA biomonitoring surveys. In a rapidly diversifying field, this review synthetises aquatic eDNA procedures and can guide eDNA users towards best practice.

Future of DNA-based insect monitoring

Insects are crucial for ecosystem health but climate change and pesticide use are driving massive insect decline. To mitigate this loss, we need new and effective monitoring techniques. Over the past decade there has been a shift to DNA-based techniques. We describe key emerging techniques for sample collection. We suggest that the selection of tools should be broadened, and that DNA-based insect monitoring data need to be integrated more rapidly into policymaking. We argue that there are four key areas for advancement, including the generation of more complete DNA barcode databases to interpret molecular data, standardisation of molecular methods, scaling up of monitoring efforts, and integrating molecular tools with other technologies that allow continuous, passive monitoring based on images and/or laser imaging, detection, and ranging (LIDAR).