Understanding biodiversity means knowing which species are present, in what abundance, and how those communities change over time or in response to disturbance. This question sits at the core of conservation ecology, and increasingly shapes how land and ecosystems are managed. For most of scientific history, answering it meant painstaking specimen collection and visual identification, methods that are slow, resource-intensive, and blind to the microscopic organisms carrying out most of the metabolic work in any ecosystem.
Over the past few decades, metabarcoding has emerged as one of the primary tools for measuring biological communities from bulk or environmental samples. By sequencing a standardized genetic marker directly from collected material, researchers can identify thousands of species from a single run and compare community composition across sites, seasons, or treatment conditions. The approach has transformed biodiversity science, enabling the kind of large-scale, replicated surveys that were practically impossible with traditional methods.
The scientific importance of that capability reaches well beyond academic ecology. Metabarcoding data now informs decisions that are crucial to environmental health like land management, ecosystem restoration, invasive species surveillance, and agricultural soil health. But the sequencing platform used matters more than it might seem, shaping what species are detected, which are missed, and how much the final data can be trusted.
Now, a definitive new benchmarking study comparing Illumina, Oxford Nanopore, and PacBio across controlled mock communities and real soil samples demonstrates how HiFi sequencing delivers the most reliable results for environmental metabarcoding.
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What is metabarcoding?
Metabarcoding is a molecular technique that sequences a short, standardized region of DNA directly from an environmental or bulk biological sample as a way of determining what species are present in that sample. Rather than isolating and culturing organisms individually, the method captures genetic material from everything in the sample at once. The resulting sequences are matched against curated reference databases to assign taxonomic identities, producing a profile of which organisms are present and in what relative proportions.
The technique works across a wide range of sample types. Soil samples can reveal the full complexity of fungal, bacterial, viral, and protist communities, water and sediment samples can be screened for fish, invertebrates, or microbial populations, and bulk insect collections can be profiled for arthropod diversity without manual sorting. In each case, sequencing replaces the bottleneck of specimen-based identification and makes it practical to study biodiversity at meaningful geographic and temporal scales. This assessment is important, because these community profiles ultimately determine how well scientists can track ecosystem health, detect early warning signs of ecological stress, and directly influence conservation decisions and restoration efforts.
Why full-length barcodes matter
The most widely used genetic marker for fungal identification and a key barcode for plants, dinoflagellates, ciliates, and diatoms, is the internal transcribed spacer (ITS) region of ribosomal RNA. Full-length ITS sequences run between roughly 500 and 1,000 bases and provide robust taxonomic resolution at the species level, consistent with the specimen-based reference libraries built over decades of traditional taxonomy.
Due to its length, short-read platforms often struggle to sequence the full barcode. This limitation led researchers to develop “mini-barcodes,” abbreviated ITS regions that sacrifice taxonomic precision and are harder to reconcile with established reference collections.
The emergence of long-read sequencing has now expanded this approach, making it possible to sequence full-length ITS amplicons and enabling far more precise taxonomic classification than minibarcodes allow. A consequential new benchmarking study puts all three major platforms directly to the test to find out which delivers on that potential.
A head-to-head platform comparison
This recent paper led by researchers at the University of Tartu creates a rigorous metabarcoding comparison between Illumina, ONT, and PacBio HiFi sequencing technology. Using a mock fungal community with known composition alongside 45 real composite soil samples from cropland, grassland, and forest sites across Europe provides the researchers with near-ground-truth data on artifact rates while allowing them to test whether the use of different technologies translate into meaningful errors in ecological inference.
How HiFi sequencing outperforms Illumina and ONT in metabarcoding
With this study, HiFi sequencing on the Revio system produced the lowest overall error rate and recovered the highest number of taxa across both the mock and soil datasets. HiFi reads matched reference sequences at the highest rate of any platform in the study, and standard OTU-based filtering on PacBio data retained more than twice as many taxa as the ASV-based processing used for other platforms.
This confirms the data quality that has made HiFi the benchmark for long-read metabarcoding analyses. Standard OTU-based filtering on PacBio data retained rare taxa that more aggressive processing approaches discarded, a meaningful difference given that rare taxa represent a substantial share of true community diversity in soil and their loss introduces systematic bias into any downstream ecological inference.
In contrast, the data from the other two platforms told a different story. Illumina’s results from the MiSeq i100 exposed problems that filtering cannot fix. Index-switching assigned reads to the wrong samples at rates far beyond what standard decontamination tools handle, and a hard amplicon length ceiling systematically excluded taxa with longer ITS sequences, introducing measurable bias in relative abundance estimates across the study’s soil samples. And ONT’s MinION produced the highest proportion of low-quality reads of any platform and lost rare taxa during quality filtering.
HiFi sequencing in environmental research
HiFi sequencing is uniquely suited to the specific demands of metabarcoding because it produces reads long enough to span the full ITS barcode in a single pass and is accurate enough that rare taxa show up as genuine signal rather than filtered noise. This combination of length and accuracy is precisely what this approach requires.
Short-read platforms cannot capture the full barcode, introducing length bias that systematically skews community profiles, while long-read platforms that sacrifice accuracy require aggressive filtering that strips out the rare taxa carrying genuine ecological signal. HiFi avoids both failure modes, giving environmental researchers a foundation they can rely on for biodiversity assessments, conservation decisions, and ecosystem monitoring.
With SPRQ-Nx chemistry now available for the Revio and Vega systems, the practical case for HiFi sequencing in environmental research has strengthened further. Higher throughput per run at a lower cost per read makes it more realistic to design the kinds of large-scale surveys that produce the most scientifically meaningful results: studies spanning hundreds of sites, or longitudinal programs tracking how microbial communities respond to climate, land use, or restoration efforts over time.
Building better biodiversity baselines
Tracking and protecting biodiversity across ecosystems requires monitoring tools that are both scientifically precise and practical to deploy at scale. Metabarcoding is one of the few approaches that can characterize community composition across landscapes and through time at the scale policy and conservation require. Getting the platform right determines what species are detected, which rare taxa survive filtering, and how much of the resulting data reflects genuine biology rather than technical noise.
For researchers designing environmental monitoring programs, soil health assessments, or eDNA surveillance pipelines, the evidence points toward the accuracy, full-length amplicon coverage, and low artefact rates that HiFi sequencing provides. As the scope of environmental sequencing expands and the ecological questions researchers are asking grow more ambitious, that foundation only becomes more important.
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