Biodiversity Estimates Research Articles

DNA metabarcoding and morphological identification reveal similar richness, taxonomic composition and body size patterns among flying insect communities

Abstract Tracking insect biodiversity trends and predicting future trajectories is limited by a lack of monitoring data across large spatiotemporal scales. DNA metabarcoding is a time‐ and cost‐efficient method to obtain these data, but has several potential limitations in comparison to traditional morphological approaches. For example, metabarcoding may miss low‐abundance or smaller bodied individuals and is limited to presence/absence information, which may bias estimates of biodiversity and community composition. However, few comparisons of metabarcoding and morphology‐based identification have been made using insects, the by far most diverse animal taxonomic group. Here, we compared terrestrial insect communities identified via morphology versus metabarcoding across four different habitats and three seasons (late spring, mid‐summer and early autumn) during 2019. We compared identified species and community richness, composition and body size, with a focus on key taxonomic groups of bees, true bugs, butterflies and hoverflies. We identified 252 total species, with 54.8% identified by both methods, whereas 21.4% and 19.8% were solely detected with metabarcoding or morphology, respectively. Overall, total community richness, taxonomic composition and community body size were similar between methods. Metabarcoding detection successes declined in low‐abundance and smaller taxa, particularly bees, hoverflies and true bugs; however, species richness of hoverflies and butterflies tended to be higher compared with morphological identification. Our results show that metabarcoding can provide an accurate overview of insect community differences that are comparable to those determined via morphological identification. We recommend that insect monitoring programmes consider incorporating metabarcoding, although future research is needed to overcome some remaining limitations.

Species swarms and their caterpillar colonisers: phylogeny and polyphenols determine host plant specificity in New Guinean Lepidoptera

The majority of multi-cellular terrestrial life is found in tropical forests and is either an invertebrate or a plant: for decades ecologists have sought to understand why. As global change erodes the list of extant species on our planet quantifying what species remain, along with their origins and ecology, contributes to our ability to preserve ecosystem functioning and resilience. Here we study three feeding guilds of caterpillars (Lepidoptera) and seek to understand the drivers of their diet breadth across four diverse tropical plant genera in Papua New Guinea. Host specificity is central to biodiversity estimates and the resilience of ecological networks. Specifically, we calculate distance-based host specificity in relation to plant phylogenetic relationships alongside chemical and mechanical traits of leaves. In terms of chemical defenses, we focus on the major polyphenol groups, a compound class shared across many plant species. We refine our data exploration using food webs and ordinations to pick out specific traits of relevance to insect host specificity. Our results showed that the degree of specialization for caterpillars took the following order: phylogenetic>polyphenol>mechanical, such that insect specificity was explained best by host phylogeny and polyphenol chemistry in our study system. Leaf mining insects had higher host specificity than those feeding externally. Of the traits studied hexahydroxydiphenoyl derivatives, galloyl derivatives, trichome density, quinic acid derivatives, myricetins and successional index explained the most variation in overall insect community structure. Our findings build on earlier studies of New Guinean rainforest communities and add a mechanistic explanation to previous findings that host genera are functional islands for insect herbivores. Further, we demonstrate that different plant genera combine different defensive traits that appear to drive associated insect diversity. Our approach integrates trait data and phylogeny to explore dimensions of specialization and we welcome metabolomic studies that will provide more detailed explanations for insect-herbivore host use. Finally, chemical diversity is directly linked to organismal diversity and by studying a range of insect herbivore guilds we make a connection between feeding ecology and specialization that will help to predict species interactions and, potentially, the persistence of ecological networks.

Assessing the diversity of freshwater fish trematodes from Laguna Escondida, Los Tuxtlas tropical rainforest, Mexico, using morphology and 28S rDNA sequences as barcodes.

Despite a great effort made for almost 90 years, the diversity of freshwater fish trematodes in Mexico is still far from being fully known. The addition of molecular data to the description of trematode diversity in the last two decades added the potential to establish more robust species limits and a more accurate biodiversity estimation, but also led in some instances to the recognition of cryptic species complexes. Here, we used sequences of the large subunit of the nuclear ribosomal gene (28S rRNA) as barcodes, and morphological data, to assess the diversity of freshwater fish trematodes from a lake within a tropical rainforest. Eighty freshwater fish specimens of eight species were studied, and 120 trematode specimens were collected. Morphologically, specimens were allocated into nine genera; molecular phylogenetic analyses along with sequence divergence data provided evidence for recognising 11 trematode taxa, six adults and five metacercariae; six of them were identified to species level. Geographical distribution and host association patterns are briefly discussed for each trematode taxa.

Assessing fish diversity in abandoned mining ponds in Madre de Dios, Peru, using environmental DNA

AbstractThe Peruvian region of Madre de Dios is a biodiversity hotspot located in the Andean‐Amazon region. Since the 1970s, it has experienced the harsh effects of artisanal and small‐scale gold mining (ASGM), which has transformed the primary forests into numerous small mining ponds left abandoned after extraction. Preliminary surveys indicate that these ponds are being recolonized by surrounding biodiversity. These assessments are typically carried out using traditional methods that are costly, difficult to deploy at multiple locations, and have raised safety concerns. In this context, environmental DNA (eDNA) becomes a useful tool for biodiversity monitoring due to its simplicity for sample collection and performance to identify taxonomic groups. In this study, we evaluated fish biodiversity in two mining ponds created by ASGM along with two nearby pristine lakes, unimpacted by mining operations but also influenced by seasonal flooding. We compared two alternative eDNA processing methods and contrasted our results with historic data from traditional biodiversity monitoring. Both eDNA‐based methods yielded comparable results, varying only in logistic requirements and costs. In total, we detected 85 fish MOTUs (22 at the species level) from 5 orders, 22 families, and 41 genera. Some of the species identified with eDNA were rarely registered by traditional monitoring, and we could identify 6 genera associated with ASGM mining ponds only. A major restriction of the eDNA approach in this location was the insufficient local taxa registered in genomic databases which limited our taxonomic resolution. Despite this limitation, our results indicate that eDNA could be a powerful tool for biodiversity estimations in the Western Amazon, identifying more taxa, with much less time and money invested than traditional monitoring. Our results also confirm that abandoned mining ponds are being recolonized by surrounding ichthyofauna, reaching richness levels above nearby unmined oxbow lakes used as reference.

Test of two membrane filter types for biomass collectionin community profiling by metabarcoding

With the rapid development of microorganism biodiversity estimation and community profiling via DNA metabarcoding, there is a growing need to identify key stages affecting the results of experiment. In order to ensure high-quality reproducible results, all potential sources of bias should be explored. While bioinformatic pipelines can be often corrected and optimized to recalculate results, the initial steps of sample collection procedure, potentially influencing the downstream results of bacterial community profiling, are much harder to correct easily, without repeating the whole experiment. We examined the differences of the amplicon bacterial community profiles generated from aquatic microbial communities captured by polycarbonate (PC) and cellulose acetate (CA) filters. The microbial community profiles were shown to be significantly different by biodiversity. When using a PC-filters, alpha- and beta-diversity of communities were significantly higher. Differential abundance analysis showed enrichment of major cyanobacterial OTUs in CA-treated communities. Based on these results, the use of PC-filters is the most optimal for bacterial community profiling by metabarcoding of the 16S rRNA gene fragments.

Temperate rocky reef fish community patterns in a coastal marine protected area (MPA) from northern Chile, utilizing remote underwater video cameras (RUVs)

Shallow water seascapes are complex systems, important for the life history and connectivity of many marine fish species. Remote Underwater Video cameras (RUVs) are an increasingly used, non-lethal technique able to record the occurrence of reef fish species with little disturbance. In this study, RUVs were installed in a Marine Protected Area (Chañaral Island, northern Chile, 29°2'S, 71°34'W) at three different depth strata (5, 10, 15 m) in three different habitats (sand and boulder, bedrock, and kelp forest) during October 2018, July 2021 and October 2021. The RUV system recorded a total of 20 species belonging to 16 families over 73.5 h of videotaping. The most recurrent fishes were damselfish Chromis crusma, Chilean sandperch Pinguipes chilensis, and marblefish Aplodactylus punctatus. There was a significant difference in fish assemblage composition among depth strata and seasons, but not among habitats. In July 2021 (austral winter) higher densities of small cryptobenthic fish (Helcogrammoides spp.) and medium-sized carnivorous Chirodactylus variegatus were detected, whereas P. chilensis was associated to the deeper stratum, and the herbivorous blenny Scartichthys viridis was related to the shallower depths, which is likely due to differences in the habitat structure and composition. Winter 2021 showed a higher species richness than in spring 2018, while the evenness (Pielou’s J’) was significantly higher in spring 2018 than winter/spring 2021. There was no other strong or consistent pattern, which suggests that most fish species use the entire depth gradient throughout the year. Finally, the results suggest that the use of RUVs for the estimation of biodiversity of rocky reef fishes is a cost-effective way to improve our understanding of nearshore community shifts in relation to environmental forcing.

Mainstreaming biodiversity into policy–Do the numbers add-up?

In this paper, we review the literature on economic approaches to providing value estimates of biodiversity. In most cases, the value estimates represent a lower estimate for a multitude of reasons, emanating from the complexity of definition and conceptualization of biodiversity as a capital stock and/or an ensuing flow of various ecosystem services. However, this exercise is important for accounting for these values in national income accounts, policy reforms, and raising funds for biodiversity financing. We discuss some of the theoretical and empirical challenges towards this valuation exercise along with providing estimates of biodiversity values.

Response of Forest Plant Diversity to Drought: A Review

Forests, being the primary repository of terrestrial biodiversity, possess a significant capacity to regulate the phenomenon of climate change. It is additionally crucial to consider how natural disasters affect the state and development of forest biodiversity. The alteration of climate patterns over recent decades has had a discernible impact on forest ecosystems, specifically the damage caused by drought to ecosystems, has become increasingly evident. Nevertheless, there is limited research to elucidate the relationship between forest biodiversity and drought, as well as to explore the mechanisms of biodiversity response to drought. This review synthesizes the existing literature on the effects of climate change on forests across various scales and examines the adaptive responses of forest communities to drought-induced stress. Forest biodiversity can be influenced by various factors, including the severity of drought, initial climatic conditions, and the composition of species in drylands. During periods of drought, the biodiversity of forests is influenced by a range of intricate physiological and ecological factors, encompassing the capacity of plants to withstand drought conditions and their subsequent ability to recuperate following such periods. Moreover, the choice of different drought indices and biodiversity estimation methods has implications for subsequent response studies.

Biodiversity estimation by environment drivers using machine/deep learning for ecological management

Biodiversity is a crucial indicator of the health and resilience of ecosystems. Accurate estimation and prediction of biodiversity can support effective ecological management practices. This study aimed to estimate and predict biodiversity based on Environmental Factors (EFs), using Machine Learning (ML) including Deep Learning (DL) algorithms. First, the importance of EFs, including Mean Annual Precipitation (MAP), slope, aspect, and elevation, in influencing biodiversity was evaluated using Minimum Redundancy Maximum Relevance (MRMR) and Recursive Feature Elimination with Relief Feature Selection (RReliefF), and their correlations with multi-spatial biodiversity indices were analyzed. Our findings revealed that MAP was the most important environmental variable in estimating biodiversity, followed by slope, aspect, and elevation. Next, the ability of four ML algorithms (multiple linear regression, decision tree, random forest, support vector machine) and a deep neural network (DNN) to estimate biodiversity was evaluated by the coefficient of determination (r-square) and the root-mean-square error (RMSE) metrics. The DNN model achieved the highest accuracy (r-square: 0.884) among the ML algorithms and was further optimized to determine the optimal level of model complexity. These findings highlight the potential of DNN to effectively estimate biodiversity and suggest that using EF features with DL algorithms can improve our understanding of the relationships between environmental drivers and biodiversity, providing valuable insights for conservation and management decision-making towards sustainable development.

The Diptera of Lesotho: a history of collecting in the Mountain Kingdom, summary of recent collecting sites and introduction to the topical collection in African Invertebrates

The Kingdom of Lesotho in southern Africa is entirely bordered by South Africa, with which it shares many geological and vegetation types, but the vast extent of alpine vegetation and high altitudes suggests that differences in insect diversity should be expected. Globally, the Diptera are one of the most diverse orders of insects, though biodiversity estimates for the order are lacking for many regions. Here, we present a summary of the limited historical Diptera collections from Lesotho, summarise our collecting expeditions in 2021, 2022 and 2023, and provide photographs and descriptions of the collecting sites. This paper is the first of a series of papers in a Topical Collection of the Diptera of Lesotho in African Invertebrates. We hope to stimulate more research on Afrotropical Diptera and to improve their conservation in Lesotho in particular.

Agricultural drivers of field margin plant communities are scale-dependent

In recent decades, agricultural intensification has led to a strong decline in biodiversity. Field margins act as shelters and dispersal corridors for biodiversity in highly disturbed landscapes, and are critical to the maintenance of ecosystem services. However, they are also impacted by agricultural practices in neighboring fields. Agricultural impacts are often studied at field to landscape scales, and rarely across biogeographic regions. One of the challenges in large-scale studies is the lack of standardized monitoring schemes including both biodiversity and accurate estimation of agricultural practices. Here, we take advantage of a national monitoring scheme in 462 sites in France, to assess the effects of agricultural practices on field margin flora at different extents and resolutions. We used spatial simultaneous autoregressive and generalized dissimilarity models to assess the response of plant richness and composition to climatic, soil and landscape conditions, and to agricultural (fertilization, herbicides) and margin management drivers. Analyses were repeated at the site-level, 40 and 75 km resolutions, and at regional and national extents. We found that the impact of agricultural practices on species richness was most important at the site-level, whereas climate and crop diversity became more important at the 75 km resolution. Compositional variations responded differently, with climate being more important at the site-level, and fertilization and crop diversity at the coarsest resolution. There was a strong variation in the variance explained by models among regions, but climate effects were weaker within biogeographic units compared to the national level, and different agricultural practices stood out as influential in different regions, suggesting that the regional context is fundamental in determining plant community structure. To efficiently conserve biodiversity, we therefore recommend the implementation of agricultural measures adapted to each region.

The Entropy of Entropy: Are We Talking about the Same Thing?

In the last few decades, the number of published papers that include search terms such as thermodynamics, entropy, ecology, and ecosystems has grown rapidly. Recently, background research carried out during the development of a paper on "thermodynamics in ecology" revealed huge variation in the understanding of the meaning and the use of some of the central terms in this field-in particular, entropy. This variation seems to be based primarily on the differing educational and scientific backgrounds of the researchers responsible for contributions to this field. Secondly, some ecological subdisciplines also seem to be better suited and applicable to certain interpretations of the concept than others. The most well-known seems to be the use of the Boltzmann-Gibbs equation in the guise of the Shannon-Weaver/Wiener index when applied to the estimation of biodiversity in ecology. Thirdly, this tendency also revealed that the use of entropy-like functions could be diverted into an area of statistical and distributional analyses as opposed to real thermodynamic approaches, which explicitly aim to describe and account for the energy fluxes and dissipations in the systems. Fourthly, these different ways of usage contribute to an increased confusion in discussions about efficiency and possible telos in nature, whether at the developmental level of the organism, a population, or an entire ecosystem. All the papers, in general, suffer from a lack of clear definitions of the thermodynamic functions used, and we, therefore, recommend that future publications in this area endeavor to achieve a more precise use of language. Only by increasing such efforts it is possible to understand and resolve some of the significant and possibly misleading discussions in this area.

Mock samples resolve biases in diversity estimates and quantitative interpretation of zooplankton metabarcoding data

Metabarcoding is a rapidly developing tool in marine zooplankton ecology, although most zooplankton surveys continue to rely on visual identification for monitoring purposes. We attempted to resolve some of the biases associated with metabarcoding by sequencing a 313-b.p. fragment of the COI gene in 34 “mock” samples from the North Sea which were pre-sorted to species level, with biomass and abundance estimates obtained for each species and taxonomic group. The samples were preserved either in 97% ethanol or dehydrated for 24 h in a drying oven at 65 °C (the routine way of preserving samples for dry weight measurements). The visual identification yielded a total of 59 unique holoplanktonic and 16 meroplanktonic species/taxa. Metabarcoding identified 86 holoplanktonic and 124 meroplanktonic species/taxa, which included all but 3 of the species identified visually as well as numerous species of hard-to-identify crustaceans, hydrozoan jellyfish, and larvae of benthic animals. On a sample-to-sample basis, typically 90–95% of visually registered species were recovered, but the number of false positives was also high. We demonstrate robust correlations of relative sequence abundances to relative biomass for most taxonomic groups and develop conversion factors for different taxa to account for sequencing biases. We then combine the adjusted sequencing data with a single bulk biomass measurement for the entire sample to produce a quantitative parameter akin to species biomass. When examined with multivariate statistics, this parameter, which we call BWSR (biomass-weighed sequence reads) showed very similar trends to species biomass and comparable patterns to species abundance, highlighting the potential of metabarcoding not only for biodiversity estimation and mapping of presence/absence of species but also for quantitative assessment of zooplankton communities.

Enumerating soil biodiversity

Soil is an immense habitat for diverse organisms across the tree of life, but just how many organisms live in soil is surprisingly unknown. Previous efforts to enumerate soil biodiversity consider only certain types of organisms (e.g., animals) or report values for diverse groups without partitioning species that live in soil versus other habitats. Here, we reviewed the biodiversity literature to show that soil is likely home to 59 ± 15% of the species on Earth. We therefore estimate an approximately two times greater soil biodiversity than previous estimates, and we include representatives from the simplest (microbial) to most complex (mammals) organisms. Enchytraeidae have the greatest percentage of species in soil (98.6%), followed by fungi (90%), Plantae (85.5%), and Isoptera (84.2%). Our results demonstrate that soil is the most biodiverse singular habitat. By using this estimate of soil biodiversity, we can more accurately and quantitatively advocate for soil organismal conservation and restoration as a central goal of the Anthropocene.

Catchment-based sampling of river eDNA integrates terrestrial and aquatic biodiversity of alpine landscapes

Monitoring of terrestrial and aquatic species assemblages at large spatial scales based on environmental DNA (eDNA) has the potential to enable evidence-based environmental policymaking. The spatial coverage of eDNA-based studies varies substantially, and the ability of eDNA metabarcoding to capture regional biodiversity remains to be assessed; thus, questions about best practices in the sampling design of entire landscapes remain open. We tested the extent to which eDNA sampling can capture the diversity of a region with highly heterogeneous habitat patches across a wide elevation gradient for five days through multiple hydrological catchments of the Swiss Alps. Using peristaltic pumps, we filtered 60 L of water at five sites per catchment for a total volume of 1800 L. Using an eDNA metabarcoding approach focusing on vertebrates and plants, we detected 86 vertebrate taxa spanning 41 families and 263 plant taxa spanning 79 families across ten catchments. For mammals, fishes, amphibians and plants, the detected taxa covered some of the most common species in the region according to long-term records while including a few more rare taxa. We found marked turnover among samples from distinct elevational classes indicating that the biological signal in alpine rivers remains relatively localised and is not aggregated downstream. Accordingly, species compositions differed between catchments and correlated with catchment-level forest and grassland cover. Biomonitoring schemes based on capturing eDNA across rivers within biologically integrated catchments may pave the way toward a spatially comprehensive estimation of biodiversity.

Mechanistic neutral models show that sampling biases drive the apparent explosion of early tetrapod diversity

Estimates of deep-time biodiversity typically rely on statistical methods to mitigate the impacts of sampling biases in the fossil record. However, these methods are limited by the spatial and temporal scale of the underlying data. Here we use a spatially explicit mechanistic model, based on neutral theory, to test hypotheses of early tetrapod diversity change during the late Carboniferous and early Permian, critical intervals for the diversification of vertebrate life on land. Our simulations suggest that apparent increases in early tetrapod diversity were not driven by local endemism following the ‘Carboniferous rainforest collapse’. Instead, changes in face-value diversity can be explained by variation in sampling intensity through time. Our results further demonstrate the importance of accounting for sampling biases in analyses of the fossil record and highlight the vast potential of mechanistic models, including neutral models, for testing hypotheses in palaeobiology.

A generalized framework to expand incomplete phylogenies using non‐molecular phylogenetic information

AbstractAimThe increasing availability of molecular information has lifted our understanding of species evolutionary relationships to unprecedent levels. However, current estimates of the world's biodiversity suggest that about a fifth of all extant species are yet to be described, and we still lack molecular information for many of the known species. Hence, evolutionary biologists will have to tackle phylogenetic uncertainty for a long time to come. This prospect has urged the development of software to expand phylogenies based on non‐molecular phylogenetic information, and while the available tools provide some valuable features, major drawbacks persist and some of the proposed solutions are hardly generalizable to any group of organisms.InnovationHere, we present a completely generalized and flexible framework to expand incomplete phylogenies. The framework is implemented in the R package “randtip”, a toolkit of functions that was designed to randomly bind phylogenetically uncertain taxa in backbone phylogenies through a fully customizable and automatic procedure that uses taxonomic ranks as a major source of phylogenetic information. Although randtip can generate fully operative phylogenies for any group of organisms using just a list of species and a backbone tree, we stress that the “blind” expansion of phylogenies using “quick‐and‐dirty” approaches often leads to suboptimal solutions. Thus, we discuss a variety of circumstances that may require customizing simulation parameters beyond default settings to optimally expand the trees, including a detailed step‐by‐step tutorial that was designed to provide guidelines to non‐specialist users.Main ConclusionsPhylogenetic uncertainty should be tackled with caution, assessing potential pitfalls and opportunities to optimize parameter space prior to launch any simulation. Used judiciously, our framework will help evolutionary biologists to efficiently expand incomplete phylogenies and thereby account for phylogenetic uncertainty in quantitative analyses.

DNA metabarcoding analysis of three material types to reveal Joro spider (Trichonephila clavata) trophic interactions and web capture

Introduced species alter established trophic interactions and molecular analysis can resolve changes in community structure and associated foraging links. Joro spiders (Trichonephila clavata) were recently introduced to the United States and their range is rapidly expanding across the east coast. Here, we used DNA metabarcoding of fecal samples, prey remains from webs, and dissected guts to compare diet composition of female Joro spiders in the southeastern United States. We amplified DNA from three material types using arthropod-targeted COI primers and sequenced with IIlumina MiSeq. Prey remains from webs had the highest diversity, richness, as well as the highest proportion of prey reads relative to Joro spider reads. Recovery of prey reads from fecal samples and dissected gut content was low and both were overwhelmed by Joro spider DNA. Although fecal samples and gut content had high proportions of Joro spider reads, fecal samples had higher prey diversity and richness. Moreover, we detected prey DNA from fecal samples several days after capture from the field, which reveals initial gut retention time estimates for fecal samples collected from web-building spiders. Combined, our results offer a first glimpse at the complexity of trophic associations for an introduced web-building spider and identify a viable material, prey remains from webs, as a source of prey DNA for estimates of biodiversity associated with web-building spiders.

Структура угрупувань дощових червів в урбані­зованих біотопах Центрального Полісся

The article describes the results of the impact of urbanisation on the quantitative and qualitative structure of earthworm communities, since urbanisation is currently one of the main threats to biodiversity. Earthworms, as the most common representatives of the edaphic mesofauna, react sensitively to the level of environmental pollution. On the example of the city of Cherniakhiv, it has been established that the lumbricide fauna of the studied area includes eight species: Aporrectodea caliginosa (Savigny, 1826), A. rosea (Savigny, 1826), A. trapezoides (Dugesi, 1828), Lumbricus terrestris (Linnaeus, 1758), L. castaneus (Savigny, 1826), Octolasion lacteum (Örley, 1885), Eisenia fetida (Savigny, 1826), and Dendrobaena octaedra (Savigny, 1826). All detected worms are rather unevenly represented in the analysed samples. Background species in the study area are A. caliginosa, A. rosea, and L. terrestris. According to the analysis of the relative abundance in the samples, A. caliginosa is dominant, whereas A. rosea and O. lacteum are less common. According to the results of the spatial distribution of earthworms, a clear dominance of one species was noted in agrocoenoses and in areas with a significant recreational load, whereas in a less anthropogenically transformed zone a higher number and species diversity of lumbricides was noted. Using cluster analysis of k-means according to biodiversity estimates, two clusters of samples were selected. At the same time, such parameters as the number of species, the number of individuals in the sample, and the Brillouin index make the greatest contribution to the differentiation of clusters. A reliable correlation was found between the number of individuals in the sample and the reflectivity in the B8 band range, as well as between the indicator of the evenness of the grouping structure and the reflectivity in the B4, B5, B11, and B12 bands of the Sentinel-2 space image and the value of the NDVI vegetation index. These spectral characteristics were used to model the spatial distribution of the absolute number of lumbricides and the evenness of their groups. The model of the spatial distribution of the number of earthworms has a mosaic character: individual cells with a high number of lumbricides are replaced by areas where they are less abundant. There is a certain relationship between individual estimates of earthworm biodiversity and land cover spectral characteristics.

Toward freshwater plant diversity surveys with eDNA barcoding and metabarcoding

AbstractProviding reliable, cost‐effective data on species distribution is critical to ensuring biodiversity conservation. However, many species may go unrecorded by conventional surveys, especially in aquatic environments. Environmental DNA (eDNA) barcoding and metabarcoding are alternative approaches that could complete biodiversity estimates based on species observations. While eDNA surveys are being standardized for some animal groups (e.g., fish and amphibians), research on eDNA approaches for freshwater plant communities is just starting to bear fruit. Here, we synthesized the 22 studies that used eDNA barcoding and metabarcoding to survey plant biodiversity in freshwater systems. We present evidence that contemporary aquatic plants (macrophytes) and terrestrial plants can be detected in water and surficial sediment eDNA from lakes and rivers. The phenology (e.g., senescence) of the target taxa strongly influences species detection. The main application of eDNA barcoding targets the monitoring of invasive macrophytes, and barcoding assays are available for 14 taxa. The metabarcoding approach shows a range of applications: the detection of rare macrophytes, catchment‐scale floristic inventories, and sediment fingerprinting. Barcodes on the plastid genome (cpDNA) are preferred for both approaches: matK and trnH‐psbA for barcoding, trnL, and rbcL for metabarcoding. The intergenic transcribed spacer 1 (ITS1) from the nuclear ribosomal DNA (nrDNA) was used for designing eDNA barcoding assays on five invasive macrophytes. In contrast, only three metabarcoding studies used the ITS1 or IST2 with newly designed primers. However, metabarcoding applications should routinely use a multi‐locus approach, combining cpDNA and nrDNA barcodes. Barcode combinations and existing primers need further testing on eDNA samples. We recommend using local barcode reference databases (BRDs), ideally self‐made, to circumvent taxonomic gaps and heterogeneous sequences in public BRDs. Finally, new technologies and developments like droplet digital PCR and hybridisation capture offer new perspectives for eDNA‐based biodiversity monitoring approaches.