ABSTRACT Environmental DNA ( eDNA ) metabarcoding has emerged as a powerful tool for biodiversity monitoring because it is non‐invasive, applicable across broad taxonomic groups, and capable of detecting rare and cryptic species. However, the characteristics and limitations of eDNA vary among target organisms. Whereas studies of microorganisms and plankton often recover high‐quality DNA from whole or near‐whole organisms, surveys of marine macrofauna, particularly vertebrates, rely on trace, frequently degraded DNA . Combined with the lack of standardized protocols, inconsistent taxonomic resolution, limited quantitative information, and the absence of life‐stage information, these constraints hinder ecological interpretation and comparisons across studies. In this Perspective, we advocate a phylogenetic turn in eDNA analyses through the integration of phylogenetic diversity ( PD ), which quantifies the amount of evolutionary history represented by detected taxa. By considering evolutionary relatedness in addition to taxa identities, PD complements conventional taxonomic metrics and can provide additional ecological insight, particularly when taxonomic resolution is incomplete. We discuss both the opportunities and limitations of this approach, including its practical implementation in eDNA metabarcoding. To illustrate this framework, we compared five marine eDNA metabarcoding datasets (2021–2025) spanning tropical to Arctic ecosystems and contrasting anthropogenic contexts. Across these case studies, anthropized sites often showed higher taxonomic richness but reduced phylogenetic divergence, reflecting communities dominated by closely related evolutionary lineages, whereas less disturbed sites supported fewer taxa but encompassed broader evolutionary histories. These contrasting patterns illustrate how PD metrics can reveal ecological processes, including environmental filtering and community assembly, that may not be apparent from taxonomic richness alone. By proposing a reproducible workflow based on standardized eDNA datasets, we highlight the potential of phylogenetic diversity to strengthen biodiversity assessment from eDNA metabarcoding. Integrating evolutionary information alongside taxonomic information provides a complementary framework for biodiversity monitoring and offers promising perspectives for long‐term monitoring, conservation planning, and environmental policy.
ABSTRACT Honey is primarily composed of sugars, along with various secondary components, including environmental DNA (eDNA) derived from all organisms directly or indirectly involved in its production process. Specifically, DNA of plant origin is mainly found in the pollen collected by honey bees from the same flowers where they collected nectar. The European chestnut ( Castanea sativa , Miller) is highly valued in beekeeping for its abundant nectar production. In this study, we gathered insights on the genetic variability of C. sativa by analyzing DNA extracted from 21 chestnut monofloral honey samples produced in four regions in Northern Italy. The DNA was amplified using six C. sativa microsatellite markers commonly used for genotyping chestnut tree genetic resources. All eDNA‐derived samples successfully amplified the microsatellite loci, showing a high level of genetic variability, with a total of 35 different alleles, averaging 23.95 ± 2.09 alleles per honey sample. Some unexpected and rare C. sativa alleles were also identified in several honey samples. Genetic diversity of C. sativa was evaluated using honey‐derived microsatellite fingerprints by categorizing honey samples based on their production region and comparing their profiles using the fixation index F ST . The highest F ST value was observed between honey samples from Emilia‐Romagna and Trentino‐Alto Adige regions, while the lowest F ST value was between Veneto and Trentino‐Alto Adige samples. Cluster analysis and Principal Component Analysis using microsatellite data indicated distinct geographically defined groups corresponding to the honey production regions. The findings suggest that honey eDNA can be utilized to assess the genetic variability of chestnut accessions, aiding in determining the geographical origin of chestnut honey samples, thus indirectly supporting their geographic authentication.
ABSTRACT Environmental DNA (eDNA) is transforming global biodiversity monitoring and ecological assessment, yet linking eDNA signals to interpretable bioassessment information remains challenging, particularly when taxonomic assignments are compromised by incomplete or regionally biased reference databases. Here, we used morphological, eDNA, and physicochemical data from 233 sites across five watersheds in Zhejiang Province, China, together with a curated Chinese freshwater macroinvertebrate barcode library (CMBL), to assess how reference database choice affects SML prediction of chemical and biological water quality metrics. Morphological identification yielded 377 macroinvertebrate taxa. After quality control, the eDNA dataset contained 30,633 taxonomy‐free OTUs, of which 42.6% were assigned to prokaryotes or non‐target eukaryotes, 7.0% to the target taxonomic groups, and 50.4% remained unassigned. Under leave‐one‐out cross‐validation, taxonomy‐free models generally achieved the highest predictive performance, although non‐target sequences accounted for 58.5% and 43.0% of their top 200 features for WQI and BMWP prediction, respectively. However, performance declined under leave‐one‐watershed‐out cross‐validation, with R 2 values generally below 0.3, indicating limited transferability among watersheds. At high‐congruence sites, where eDNA and morphological family compositions closely corresponded, CMBL‐annotated models approached the performance of taxonomy‐free models for WQI prediction and slightly outperformed it for BMWP prediction. In contrast, predictive performance declined substantially at low‐congruence sites. These findings indicate that regional database curation can improve regional taxonomic relevance and family‐level congruence relative to a broad public reference database, although it does not guarantee reliable lower‐level taxonomic assignments. Our study highlights a trade‐off in eDNA‐based SML bioassessment: taxonomy‐free OTUs maximized predictive performance, whereas annotated OTUs provided taxonomic context whose reliability depended on reference quality, database coverage, and assignment confidence.
ABSTRACT Mangrove‐associated lagoons are critical nursery and feeding habitats for fishes, yet their biodiversity in Sri Lanka remains poorly documented due to reliance on conventional, catch‐based methods. Here, we applied environmental DNA (eDNA) metabarcoding to characterize fish assemblages in Negombo (wet zone) and Puttalam (dry zone) lagoons. Next‐generation sequencing of eDNA extracted from water samples yielded over 1.68 million quality‐filtered reads, which were assigned to 194 operational taxonomic units (OTUs). These OTUs represented 87 species from 47 families in Negombo and 54 species from 35 families in Puttalam, with 39 species shared between the lagoons, the majority of which were euryhaline. Relative read abundance profiles revealed greater spatial heterogeneity in family composition within Negombo, whereas Puttalam was characterized by stronger dominance of a smaller number of fish families. Shannon diversity was highest at the lagoon mouth and lowest in the inner lagoon in both systems. Beta diversity analyses revealed a significant difference in fish community composition between the two lagoons (PERMANOVA, R 2 = 0.106, p = 0.001), whereas no significant differences were detected among regions within lagoons. Species richness estimates were broadly comparable to historical records based on conventional surveys. However, eDNA metabarcoding provided complementary insights by detecting a wider range of commercially important, cryptic, and reef‐associated taxa. These findings demonstrate the utility of eDNA metabarcoding for characterizing fish communities across marine–brackish–freshwater transitions. Our study provides an updated molecular‐based assessment of fish diversity in Negombo and Puttalam lagoons and highlights the potential of eDNA for biodiversity monitoring and fisheries management in Sri Lanka's coastal ecosystems.
ABSTRACT Insects are crucial for ecosystem functioning and provisioning services, yet the study of their decline is hampered by traditional monitoring systems. Airborne eDNA has the potential to help monitor the rapid changes insect communities are experiencing. Polyurethane foam passive air samplers (PUF‐PAS) are widely deployed to monitor environmental pollutants, yet their capacity to capture biological signals such as environmental DNA (eDNA) remains largely unexplored. Recent advances in airborne eDNA research create a timely opportunity to evaluate PUF‐PAS as a tool for biodiversity monitoring and to leverage existing global sampling networks for conservation. Focusing on insects, we assess whether PUF‐PAS can provide eDNA‐based biodiversity data comparable to those obtained with traditional sampling methods. We compared the taxonomic richness, community composition, and detection biases of PUF‐PAS to a conventional method for sampling flying insects, Malaise traps. We deployed both samplers across Montreal, Canada, during the entire flight season and collected 49 samples of each method. Insect communities were characterized at the order level using morphological identification (Malaise traps) and DNA metabarcoding (PUF‐PAS). Insect communities collected with both methods showed substantial overlap, with 11 insect orders detected by both methods; 3 were unique to Malaise traps and 1 to PUF‐PAS. On average, estimates of insect abundance from Malaise traps were strongly positively associated with PUF‐PAS detection probability and read counts. However, PUF‐PAS detection probability and read counts were best explained by Malaise trap counts measured several weeks prior and integrated over approximately 8 weeks, indicating a delayed biological signal. Our results suggest that PUF‐PAS is better suited for interannual monitoring of common insect taxa, particularly for detecting broad temporal trends. Given the availability of global passive air sampling infrastructure, this approach not only has strong potential for large‐scale biodiversity monitoring but also could foster interdisciplinary collaborations between environmental toxicologists and biodiversity scientists.
