eDNA metabarcoding reveals invertebrate diversity in the blackwater pools of southeast Queensland peatlands

eDNA metabarcoding reveals invertebrate diversity in the blackwater pools of southeast Queensland peatlands | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article eDNA metabarcoding reveals invertebrate diversity in the blackwater pools of southeast Queensland peatlands Grace Smith, Tomer Ventura, Catherine M. Yule This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9238693/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 11 You are reading this latest preprint version Abstract Despite harbouring a disproportionate diversity of rare and endemic species, the pyrophilic peatlands of southeast Queensland remain poorly characterized, particularly regarding their invertebrate communities. In the physiochemically extreme blackwater pools, microscopic invertebrate assemblages likely form critical trophic links but have never been described due to their low public profile, small size and cryptic nature. This study used 18S environmental DNA metabarcoding to characterize invertebrate communities across three peatland sites, revealing significantly greater taxonomic breadth than conventional surveys. 63 taxa across 10 phyla were detected, including five microscopic phyla previously unrecorded in these ecosystems (Cnidaria, Rotifera, Platyhelminthes, Nematoda and Gastrotricha). Metabarcoding exceeded the resolution achieved by field surveys for morphologically cryptic microcrustaceans, however field surveys achieved better resolution for hexapods, demonstrating that the methods target complementary niches, each focused at distinct components of the invertebrate community. The documented microfauna overlap in key life-history traits, including rapid maturation, parthenogenetic reproduction, and dormancy capabilities, occupying the crucial intermediary trophic link between microbial production and higher consumers. These traits likely enable rapid community recovery and ecosystem stabilization following fire disturbances characteristic of pyrophilic peatlands. Our findings reveal a previously unrecognized diversity of invertebrate taxa and demonstrate the efficacy of molecular tools in the description of cryptic community assemblages. Biological sciences/Ecology Earth and environmental sciences/Ecology Biological sciences/Evolution Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 Introduction While most peatlands globally are destroyed by fire, the Empodisma -dominated peatlands of southeast Queensland rely on periodic burns to maintain the dominance of the peat-forming wire rush Empodisma minus , making them the only known pyrophilic peatlands in the world [ 1 ]. These ecosystems are characterized by highly acidic, nutrient-poor blackwater pools which, despite their physiochemically harsh conditions, harbor a disproportionately high diversity of rare and locally endemic species, many of which are threatened with extinction [ 2 , 3 , 4 ]. The common denominator for threatened species vulnerability in southeast Queensland is the extensive habitat loss, fragmentation and degradation driven by rapid and ongoing urbanisation [ 5 , 6 , 7 , 8 ]. Where suitable habitat persists, threatened fauna maintain relatively high local abundances, indicating that ecosystem-level threats are the primary conservation concern [ 9 , 10 , 11 ]. The broader implication of this ecosystem-level threat is that all endemic species are subject to the same threatening processes, yet the invertebrate fauna remain almost entirely overlooked. Only two crayfish and one dragonfly species are formally recognized as threatened [ 2 , 12 , 13 ], and many species remain undescribed. Though the number of invertebrate species in Australia (> 320 000) far exceeds the number of vertebrates (~ 7400) [ 14 ]. Insects and crustaceans, let alone microscopic taxa, are typically neglected in assessments and descriptions, largely as a result of their low public profile and the taxonomic challenges posed by their tiny size and cryptic ecology [ 15 ]. Woinarski et al (2025) estimate that over 6000 undescribed Australian invertebrate species have already been lost in undocumented extinctions, dwarfing Australia’s 51 formally recognised vertebrate extinctions [ 16 , 17 ]. The diversity and abundance of predatory fishes, amphibians, and macroinvertebrates in peatland ecosystems implies a more substantial invertebrate prey base than currently documented [ 7 , 18 ]. Extreme environments promote high levels of endemism due to the unique selective pressures and isolation they impose [ 19 ]. Peatlands represent one such extreme ecosystem, where the physically and chemically recalcitrant vegetation produce unpalatable leaf litter and the acidic, tannin-darkened waters impede algal growth, creating a fundamentally different trophic structure than most freshwater systems. While the vegetation forms the structural foundation of the peat, basal energy pathways are thought to be dominated by chemotrophic microbes and fungi [ 20 , 21 ]. An exceptionally high diversity of more than 3700 sequence variants across 34 phyla of bacteria and archaea with 97% novelty has been documented in Empodisma- peatlands using 16S rRNA profiling [ 22 ]. Microbial communities are most abundant and diverse towards the surface layers of the peat, reflecting gradients in water availability, oxygen saturation, nutrients, and substrate variability. Metabolism is dominated by anaerobic and microaerophilic pathways, particularly hydrogenotrophic methanogenesis and sulphate reduction. This same vertical structuring is also observed in microbial enzymatic activity [ 23 ] and fungal abundance and diversity [ 24 ]. Microbes are key to carbon and nutrient cycling within these oligotrophic systems, likely forming the foundation of the peatland food web, given the toxic and nutrient-poor nature of the vegetation. However, the microscopic invertebrates that surely link microbial primary production to higher-order consumers remain largely invisible in both ecological research and conservation assessments. Built on the same principles as microbial genetic profiling, environmental DNA (eDNA) metabarcoding is a robust and widely employed biomolecular tool for biodiversity assessment across a range of ecosystems [ 25 , 26 , 27 , 28 ]. In peat systems, metabarcoding studies have predominantly employed 18S or CO1 markers favouring a short amplicon length due to the fragmented and degraded nature of peat eDNA [ 29 , 30 , 31 ]. By targeting trace genetic material shed by organisms into their environment, eDNA metabarcoding allows non-invasive detection while providing more comprehensive taxonomic coverage than is typically achievable through conventional survey methods alone. This approach circumvents the need for direct capture or visual observation, making it both cost and labour efficient, and is particularly effective for detecting rare, cryptic, or highly mobile taxa often underrepresented in traditional monitoring efforts [ 26 , 32 ]. To minimize false detections, eDNA surveys are typically conducted alongside field sampling, allowing molecular detections to be validated against observational records [ 31 , 33 ]. Here, we use eDNA metabarcoding to describe the invertebrate diversity in blackwater pools of southeast Queensland peatlands. Targeting areas of high endemism using combined molecular profiling and field morphological surveys, we aim to document invertebrate taxonomic diversity, including cryptic and microscopic taxa overlooked by traditional surveys. Our findings reveal a previously unrecognized diversity of invertebrate taxa and demonstrate the applicability and efficacy of molecular tools in the description of cryptic community assemblages. 2 Materials and Methods 2.1 Site description K’gari (also referred to as Fraser Island in literature up to 2021) is the world’s largest sand island, formed between 1.2–0.7 million years ago during Pleistocene sea-level fluctuations [ 34 ]. The peat swamps on K’gari are dominated by E. minus (50–90% cover), surrounding a mosaic of shallow ( 1.5m) blackwater pools. Co-dominant vegetation mostly comprises graminoids ( Lepironia articulata , Gahnia sieberiana ), forbs ( Gleichenia mendellii , Blechnum indicum , Hibbertia salicifolia , Drosera binata ), and shrubs ( Leptospermum liversidgei , Banksia robur , Epacris microphylla ) [ 35 , 36 ]. Three peat swamps with differing fire histories were selected for this study (Table 1 ; Fig. 1 ). Maximum peat depth ranged from 1.8m at Red Lagoon to 7.85m at Dilli Swamp. Dilli Swamp and Duck Creek have formed in fluvial plains and acidic clearwater streams which are hydrologically distinct and fed largely by groundwater, flow through these peatlands. These streams have a distinct fauna, including taxa needing higher oxygen levels that occur in the peatland pools as well as abundant algae. Table 1 Sample sites and fire history (most recent fire date shown in bold) Site name GPS Previous fire dates Managed burn (MB), Wildfire (W) Red Lagoon S -25.554969, E 153.06112 2008 (MB) Dilli Swamp S -25.598680, E 153.08353 1980(MB), 1983(MB), 1985(MB), 1991(W), 1996(MB), 2001(MB), 2008(MB), 2009(W), 2016 (MB) Duck Creek S -25.44355 E 153.01135 1985(MB), 1992(W), 2011 (MB) 2.2 Field sampling Sampling was conducted in July 2023. At each of the three sites, three replicate 1L water samples were collected, for a total of nine samples. Water was filtered in the field through 200µm mesh to remove coarse debris, collected in autoclaved plastic bottles, and transported on ice to the PC2 laboratory facilities at the University of the Sunshine Coast. Dipnet surveys were also conducted using three replicate 10 second sweeps per pool, at three pools per site. Macroinvertebrates were sorted in the field using white trays, identified to the lowest possible taxonomic level in situ where feasible, or preserved in 80% ethanol for laboratory identification under a stereomicroscope. 2.3 Sample processing Within 72 hours of collection, water samples were filtered through 0.45 µm nanopore membranes under sterile conditions in the University of the Sunshine Coast’s PC2 facility. Filter membranes were sectioned into ~ 1 mm strips and stored at 4°C until DNA extraction. All equipment was autoclaved and rinsed with ultrapure water prior to use and disinfected with ethanol between samples. Genomic DNA was extracted using the DNeasy PowerSoil Kit (Qiagen) following manufacturer instructions on a dedicated PCR-free bench. Multiple primer sets (18S, 16S, ITS, COI) were trialled, with 18S yielding the highest amplification efficiency. The V4 region of the 18S rRNA gene was amplified using the following forward and reverse primers [ 37 ]: Uni18S_450F: 5’ AGGGCAAKYCTGGTGCCAGC 3’ Uni18S_450R: 5’ GRCGGTATCTRATCGYCTT 3’ PCR reactions (25 µL total volume) used 1 µL each of forward and reverse primers, with cycling conditions as follows: initial denaturation at 75°C for 2 min, followed by 35 cycles of 75°C denaturation (40s), 55°C annealing (40s), and 72°C extension (10 min), with a final hold at 10°C. PCR products were visualised on 2% agarose gels and quantified using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Australia). Amplicons (30 µL per sample) were desiccated and sequenced using the Illumina MiSeq platform (Novogene, Hong Kong). 2.4 Bioinformatic analysis Raw paired-end reads were processed in Galaxy Australia (v25.0.3). Cutadapt was used to verify that primer sequences were removed, and read quality was assessed with FASTQC . Quality filtered reads were processed with the LotuS2 pipeline [ 38 ] to merge, demultiplex, and remove chimeras, in total generating 3809 operational taxonomic units (OTUs). LotuS2 was run with the following non-default parameters and specifications: Tax aligner = “Lambda, LCA”; Reference database = SILVA SSU/LSU database; Use the best BLAST hit only = “yes”; Chimera check = “OTU chimera check”; Amplicon type = “SSU”; Sequencing platform = “MiSeq.” Resulting OTUs were additionally queried against an inhouse custom 18S rRNA invertebrate database (Supplementary File 1), constructed from NCBI reference 18S sequences (GenBank 268.0). R v4.1.2 was used to complete taxonomic assignment and data processing (R Core Team, 2025). The SILVA and custom 18S taxonomic assignments were joined by accession number and filtered by minimum percent identity as follows: ≥98% = genus-level (custom database), ≥ 95% = family-level (custom database), ≥ 90% = order-level (custom database; SILVA annotation retained for two unresolved rotifer OTUs), < 90% = SILVA annotation (or custom database classification at class level if SILVA was unresolved). OTUs with taxonomic assignment confidence < 85% were discarded. Community structure was visualized using non-metric multidimensional scaling (nMDS) based on Bray-Curtis dissimilarities using the vegan package [ 39 ]. All figures were generated in ggplot2 [ 40 ], with a viridis colour palate [ 41 ]. Phylogenetic trees were generated using PhyloT (v2 2023.2) and visualized in iTOL v7 [ 42 ], with heatmap annotations overlaid in ggplot2 . 3 Results An average of 1.2 million high-quality reads were obtained per sample (range 1.01–1.41 million). After denoising to remove sequencing errors and artifacts, merging, and chimera removal, 1910 operational taxonomic units (OTUs) were retained. Of these, 1095 OTUs (57.3%) were successfully assigned a taxonomic classification using the combined SILVA and custom 18S reference databases as described above. 705 OTUs (36.9%) were resolved to at least order level (Fig. 2 ). The remaining 815 OTUs (42.7%) could not be assigned to any taxonomic group, which is within expected range for 18S V4 metabarcoding against the SILVA and/or curated NCBI databases [ 43 , 44 ]. nMDS based on OTU abundance showed distinct invertebrate community assemblages between sites, with samples clustering by site (Fig. 3 ) with a very low stress value (stress = 9.45e⁻⁵). Permutational multivariate analysis of variance (PERMANOVA) confirmed significant differences in community composition between the three peatland sites (PERMANOVA: R² = 0.77, F₂, ₆ = 10.04, p = 0.004). Site identity explained 77% of the variation in community composition, demonstrating that Duck Creek, Dilli Swamp, and Red Lagoon each have unique invertebrate assemblages consistent with the lack of connectivity due to hydrological isolation between the three peatland sites despite relatively close proximity. In total, eDNA metabarcoding identified 63 unique taxa representing 27 orders across 10 phyla (Fig. 4 , left panel). Detected taxa included one vertebrate group (bony fishes, Teleostei), three major arthropod clades (crustaceans, insects, and mites) and oligochaete annelids, all of which were previously documented in these systems through field surveys. Metabarcoding also revealed five microscopic invertebrate phyla which had not previously been recorded from southeast Queensland peatlands: Platyhelminthes, Nematoda, Gastrotricha, Rotifera, and one freshwater parasitic cnidarian (Myxozoa). Taxonomic resolution varied among groups, with crustaceans and insects generally resolved to family or genus level, while non-arthropod invertebrate phyla were typically resolved only to class or order level, likely due to their relative underrepresentation in reference databases. Comparison of eDNA metabarcoding and field morphological surveys found complementary strengths in each method (Fig. 4 , both panels). Metabarcoding was more effective in detecting cryptic, microscopic taxa, including worms (annelids, platyhelminths, nematodes), gastrotrichs, rotifers, and one myxozoan parasite. Field surveys recorded only a single oligochaete annelid among these phyla. Metabarcoding also provided finer taxonomic resolution for microcrustaceans, identifying copepods and cladocerans to genus or family level compared to order-level identification from morphological surveys (due to lack of taxonomic expertise in the lab for microcrustacea). For decapods, field surveys performed slightly better than metabarcoding. Both methods successfully detected Cherax crayfish and Heterias isopod, though only field surveys detected Caridina shrimp. Within hexapods, field surveys generally achieved finer taxonomic resolution. Collembola were resolved to family level by morphology but only to class level by metabarcoding. Unique method-specific detections were observed in both directions. Metabarcoding detected two dipterans, two odonatans, one hemipteran, and two coleopterans which were not detected in field surveys. However, some of these records were detected only at single sites and could represent false positives. By comparison, field surveys detected five dipterans, two odonatans, two hemipterans, two trichopterans, and one coleopteran which were not detected by metabarcoding, representing false negatives in the metabarcoding dataset. There were no false detections at the order level in either direction. nMDS found that sampling method (field surveys or metabarcoding) had a large but marginally significant effect on detected community assemblage (Method R² = 0.69, F₁, ₂ = 8.43, p = 0.08), while site did not have an effect (Site R² = 0.15, F₂,₂ = 0.92, p = 0.68) (Fig. 5 ). Methods separated primarily along the first dimension (nMDS1), with weaker differentiation of site along the second dimension (nMDS2). Method therefore had substantially stronger influence on observed community composition than actual variation between peatland sites. 4 Discussion 4.1 Community diversity overview Environmental DNA metabarcoding of 18S rRNA detected 63 invertebrate taxa across three southeast Queensland peatlands, revealing a considerably greater taxonomic breadth than conventional field surveys using dip nets. Sites showed strong spatial heterogeneity, each peatland hosting a distinct invertebrate assemblage, consistent with unique microbial communities detected across sites by Too et al (2026, manuscript in prep). Metabarcoding provided finer taxonomic resolution for morphologically cryptic microcrustaceans and detected five invertebrate phyla which had not previously been recorded from southeast Queensland peatlands (Cnidaria, Rotifera, Platyhelminthes, Nematoda, and Gastrotricha). For more conspicuous taxa (i.e. decapods and insects), field surveys typically provided better resolution, though neither method provided a complete taxonomic coverage. Integrated approaches that combine molecular and field methods would therefore yield the most complete characterization of invertebrate diversity. 4.2 Fish, crustaceans, and insects Combined survey methods detected four fish taxa, 17 crustacean taxa, and 29 hexapod taxa. Metabarcoding identified all four fish to genus level, each represented by a single local species within their respective genera: honey blue-eye ( Pseudomugil mellis ), Oxleyan pygmy perch ( Nannoperca oxleyana ), and firetail gudgeon ( Hypseleotris galii ), all documented to occur in local peatlands, and purple-spotted gudgeon ( Mogurnda adspersa ), which is documented from upstream habitats but not from peatland pools themselves [ 7 , 18 , 45 ]. This record likely represents DNA transport from upstream populations or could represent misidentification of the closely related ornate rainbowfish ( Rhadinocentrus ornatus ), which is well documented in peatlands but was not detected [ 18 ]. Acid fish are known to niche partition by diet, with N. oxleyana targeting mid-strata macroinvertebrates, P. mellis targeting surface skimmers and H. galii targeting larger surface invertebrates and macrophytes [ 5 ]. This diversity of feeding strategies implies a diverse macroinvertebrate prey assemblage. Both methods successfully detected the undescribed isopod Heterias sp. nov. and Cherax crayfish, though taxonomic resolution beyond genus was unresolved, as the 18S-v4 region does not distinguish between the endemic specialist Cherax robustus and the more widespread generalist C. dispar , both of which occur in the broader catchment. Caridina shrimp were detected only by field surveys. Metabarcoding achieved finer resolution within cladocerans and copepods, which are notoriously difficult to identify morphologically. The consistently high detection of copepods could indicate significant biomass, although could also be an artifact of primer bias. A high diversity of predatory insects was detected, including odonatans (Aeshnidae, Coenagrionidae, Lestidae, Libellulidae), hemipterans (Corixidae, Gerridae) and Coleopterans (Dytiscidae, Scirtidae, Hydraenidae, Chrysomelidae, Hydrophilidae), which suggests a high diversity of prey species to accommodate niche partitioning. Field surveys generally demonstrated better taxonomic resolution within Hexapoda. Metabarcoding achieved lower taxonomic resolution for Collembola and Chrysomeloidea beetles and failed to detect numerous insect families identified morphologically. Both methods showed perfect congruence at the order level (100% overlap in insect orders detected), but declined substantially at finer taxonomic scales, with less than one-third of insect genera detected by both methods. Our broad 18S approach therefore provides reliable presence/absence data at higher classification levels but lacks the resolution and sensitivity for genus-level assessment. 4.3 Microscopic diversity Six non-arthropod invertebrate phyla were detected by metabarcoding, five of which (Cnidaria, Rotifera, Platyhelminthes, Nematoda, and Gastrotricha) are the first records of these phyla southeast Queensland peatlands. A summary of functional traits and feeding strategies can be seen in Table 2 . These microscopic taxa are largely detritovores or bacterivores, rather than herbivores, with most groups primarily reproducing parthenogenically – the notable exceptions being nematodes, annelids, and rhabdocoelid flatworms, which exclusively reproduce sexually [ 46 , 47 , 48 ]. These groups represent complex trophic interactions, though their taxonomy and functional roles remain poorly resolved. The three worm phyla detected (Nematoda, Platyhelminthes, and Annelida) showed functional diversity spanning bacterivores, algal grazers, detritivores, and in some nematodes, parasites. Catenulid flatworms reproduce via asexual budding, but all other detected worm groups rely on sexual reproduction [ 48 , 49 ]. Rotifers also proved highly diverse across three detected orders, with feeding strategies ranging from sessile suspension filter feeding to active predation and grazing [ 50 , 51 ]. All rotifer groups share parthenogenic reproduction and possess dormancy mechanisms such as desiccation-resistant resting eggs [ 52 ]. All identified gastrotrichs belonged to the order Chaetonotida, benthic grazers which exhibit parthenogenetic reproduction, rapid development, and produce dormant resting eggs [ 53 , 54 ]. Targeted field sampling rewetting dried peat confirmed the presence of gastrotrichs in the genus Chaetonotus , including two undescribed species (A. Todaro pers comm.), providing validation of metabarcoding accuracy and lending support to other detections. The most unexpected finding was Bivalvulida (phylum Cnidaria), microscopic endoparasites detected at all three sites. Most described bivalvulids parasitize freshwater fishes, and are relatively common in oligotrophic systems, though poorly documented [ 55 ]. The detection of Bivalvulida across all surveyed peatland sites indicates active parasitism of local fish ( Pseudomugil, Nannoperca, Hypseleotris ) with an intermediate annelid host, [ 56 , 57 ], though specific transmission pathways remain unknown. Across these microscopic taxa, convergent life-history traits emerge that appear highly adaptive for characteristic peatland acidity, anoxia, fire, and hydrological variability. Parthenogenetic reproduction and short generation times enable rapid population recovery from small founding populations, while desiccation-resistant resting stages allow survival through fire and drought. Feeding strategies consistently target algae, bacteria, or detritus rather than vegetation. Collectively, these traits confer resilience to the boom-bust cycles characteristic of peatlands, drawing on similar patterns of desiccation resilience, anoxia tolerance and stationary phases as previously observed in the sympatric microbe communities [ 22 ]. Functionally, these microscopic invertebrates likely constitute the critical trophic link between microbial production and higher-order consumers. By consuming bacteria, fungi, and fine particulate organic matter, they convert microbial biomass into prey accessible to larger predators. The abundant and diverse assemblages of predatory copepods, odonatans, hemipterans, and fishes documented in these systems require a substantial prey base, which these microscopic taxa almost certainly provide. Moreover, their rapid recolonisation likely stabilizes ecosystem function following disturbance events, particularly fires, restoring food web connectivity and supporting the recovery of higher trophic levels. Table 2 Functional traits of microscopic invertebrate taxa identified by eDNA metabarcoding. Phylum Class Order Diet Reproduction Reference Gastrotricha Chaetonotida Chaetonotida Benthic microphagous detritivores Parthenogenesis, rapid development, resting eggs Todaro et al., 2019 Nematozoa Chromadorea Chromadorida Benthic bacteria/microbe grazer Dioecious; sexual reproduction (parthenogenesis uncommon) Yeates et al., 1993 Araeolamida Bacterivore Monhysterida Benthic bacterivore Tylenchida Root ectoparasite Peña-Santiago et al., 2006; Rizvi, 2017 Enoplea Enoplida Microphagous Moens & Vincx, 1997 Triplonchida Terrestrial plant parasite Rizvi, 2017 Platyhelminthes Catenulida Free-living detritovore Asexual paratomy Larsson, 2008; Moraczewski, 1977 Rhabditophora Rhabdocoela Predator/scavenger Hermaphrodites; sexual reproduction Larsson, 2008; Noreña et al., 2016 Rotifera Bdelloidea Adinetida Bacteria/detritus Obligate parthenogenesis; tolerant to desiccation Fontaneto & Ricci, 2006 Monogononta Flosculariacea Sessile filter feeder Cyclical parthenogenesis Wallace & Snell, 2001 Ploimida Omnivorous predator/filter-feeder/grazer Cyclical parthenogenesis or sexual reproduction; resting eggs Dhert et al., 1995; Leasi et al., 2009 Cnidaria Myxozoa Bivalvulida Endoparasitic Asexual reproduction (fish host); sexual reproduction (annelid host) Lom & Dyková, 2005; Dykova, 2006; Fiala et al., 2015 Annelida Oligocheta Haplotaxida Detritovore Hermaphrodites; sexual reproduction Martin et al., 2024 4.4 Outcomes and limitations Sites showed strong spatial structuring, with each peatland hosting a distinct invertebrate assemblage. This heterogeneity reflects the unique fire histories, hydrology, and lack of connectivity between each site. Duck Creek is geographically isolated from Dilli Swamp and Red Lagoon by K'gari's central dune ridge, while Dilli Swamp and Red Lagoon, despite geographic proximity, are separated by multiple smaller dunes and drainages. Given these site-specific characteristics, uniform management practices are unlikely to be equally effective across all peatland sites. The combined complementary strengths of metabarcoding and field surveys offer a cost-effective strategy for comprehensive monitoring that balances taxonomic breadth with detection sensitivity. eDNA metabarcoding provides several advantages, being non-invasive, minimising impacts on sensitive ecosystems and vulnerable populations, while enabling the detection of "dark taxa” typically invisible in conventional surveys. However, there are many inherent limitations which must be acknowledged in metabarcoding. Spatial uncertainty, such as DNA transport from upstream populations, complicates interpretation. False negatives arising from primer bias or incomplete reference databases can result in failure to detect present taxa. Aside from Chaetonotus (Gastrotricha) and Oligochaeta (Annelida), the microscopic taxa detected by metabarcoding remain unvalidated. Furthermore, eDNA cannot provide abundance estimates or demographic information (such as adults versus larvae). Hence, the continued necessity of field surveys for population monitoring, validation, and demographic data. The universal 18S primers employed here maximized taxonomic breadth at the cost of resolution, with most taxa identified only to order or family level. For targeted surveys, such as monitoring threatened fishes, taxa-specific primers would provide finer resolution, potentially to species level [ 63 , 64 ]. A combined monitoring approach, integrating morphological surveys with eDNA surveys, provides the most comprehensive taxonomic assessment. Expanding reference libraries through database development and voucher-based sequencing, particularly for endemic and undescribed taxa, could dramatically improve identification accuracy. 5 Conclusion This study used eDNA metabarcoding to document previously unrecorded invertebrate diversity in southeast Queensland's pyrophilic peatlands, detecting five phyla never recorded through conventional surveys and providing improved taxonomic resolution for morphologically cryptic microcrustaceans. The documented microscopic fauna likely constitutes the critical trophic link between microbial production and higher-order consumers. The convergent life-history traits observed across these taxa, including parthenogenetic reproduction, desiccation-resistant dormant stages, and rapid generation times, appear adaptive for the stochastic disturbance regimes characteristic of fire-dependent peatlands, enabling rapid community recovery following disturbance. Comparison with morphological surveys found that the methods were complementary, with neither approach alone capturing complete taxonomic diversity. Integration of both methods in biodiversity assessments therefore provides more comprehensive characterization than either approach in isolation. Future research should consider voucher-based sequencing to improve reference databases, formal taxonomic description of novel peatland taxa, and investigation of the functional roles of microscopic invertebrates in peatland food webs and post-fire ecosystem stabilization. Declarations Competing Interests Authors GS and TV declare no financial or non-financial competing interests. Author CY serves as an Editor for the Nature Portfolio Collection on Biodiversity and Ecosystem Functioning of Global Peatlands and on npj Biodiversity and had no role in the peer-review or decision to publish this manuscript. Author CY declares no financial competing interests. Supplementary information Annotated OTUs are available as Supplementary file 1.xlsx . Field sampling results used for comparison in Figs. 4 and 5 are available as Supplementary file 2.xlsx . The custom 18S rRNA invertebrate reference database will be made available on request. Author Contribution CY and GS conducted field sampling. GS and TV conducted lab work. GS conducted data analyses. GS wrote the original draft of the manuscript. CM and TV reviewed and revised the draft. All authors read and approved the final manuscript. Acknowledgement This study was funded by the Queensland Government Community Sustainability Action Grant CSAT22032 for Ecosystem based approach to protecting threatened species in subtropical peat swamps. The funder played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript.We thank Prof. Antonio Todaro (University of Modena & Reggio Emilia) for his validation of our gastrotrich samples. Data Availability Data availabilityRaw sequencing data is available via the NCBI Sequence Reference Archive (SRA) under BioProject #PRJNA1402468. Code availabilityR scripts used for statistical analyses and code used to generate all figures is available through the GitHub repository: github.com/graceponders/eDNA-methods-analysis.Supplementary informationAnnotated OTUs are available as Supplementary file 1.xlsx. Field sampling results used for comparison in figures 4 and 5 are available as Supplementary file 2.xlsx. 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Fairfax, R., et al., A preliminary investigation into ‘patterned fens’ of the Great Sandy Region. Unpublished report to the Commonwealth Department of Sustainability, Environment, Water, Population and Communities. Queensland Herbarium, Queensland Department of Environment and Resource Management, Brisbane, 2011. Ryan, T.S.e., Technical Descriptions of Regional Ecosystems of Southeast Queensland , D.o.S. Queensland Herbarium, Information Technology, Innovation and the Arts, Editor. 2012: Brisbane Zhan, A., et al., Performance comparison of genetic markers for high-throughput sequencing-based biodiversity assessment in complex communities . Molecular Ecology Resources, 2014. 14(5): p. 1049–1059. Özkurt, E., et al., LotuS2: an ultrafast and highly accurate tool for amplicon sequencing analysis . Microbiome, 2022. 10(1): p. 176. Oksanen, J., et al., vegan: Community Ecology Package . 2025. 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Marine & Freshwater Research, 2014. 66(1): p. 50–59. Noreña, C., et al., Platyhelminthes: Rhabdocoela: Typhloplanidae. 2016. Peña-Santiago, R., et al., Soil and freshwater nematodes of the Iberian fauna: a synthesis . Graellsia, 2006. 62(2): p. 179–198. Yeates, G.W., et al., Feeding habits in soil nematode families and genera—an outline for soil ecologists . Journal of nematology, 1993. 25(3): p. 315. Larsson, K., Taxonomy and phylogeny of Catenulida (Platyhelminthes) with emphasis on the Swedish Fauna . 2008, Acta Universitatis Upsaliensis. Wallace, R.L. and T.W. Snell, 8 - PHYLUM ROTIFERA , in Ecology and Classification of North American Freshwater Invertebrates (Second Edition) , J.H. Thorp and A.P. Covich, Editors. 2001, Academic Press: San Diego. p. 195–254. Fontaneto, D. and C. Ricci, Spatial gradients in species diversity of microscopic animals: the case of bdelloid rotifers at high altitude . Journal of Biogeography, 2006. 33(7): p. 1305–1313. Leasi, F., R. Pennati, and C. Ricci, First description of the serotonergic nervous system in a bdelloid rotifer: Macrotrachela quadricornifera Milne 1886 (Philodinidae) . Zoologischer Anzeiger-A Journal of Comparative Zoology, 2009. 248(1): p. 47–55. Todaro, M.A.D., Kingdom Animalia, phylum Gastrotricha (hairy-bellied worms) , in The Marine Biota of Aotearoa New Zealand. Updating our marine biodiversity inventory . 2023, NIWA Biodiversity Memoir. p. 187–191. Todaro, M.A., et al., An introduction to the study of Gastrotricha, with a taxonomic key to families and genera of the group . Diversity, 2019. 11(7): p. 117. Lom, J. and I. Dyková, Microsporidian xenomas in fish seen in wider perspective . Folia parasitologica, 2005. 52(1/2): p. 69. Fiala, I., et al., Adaptive radiation and evolution within the Myxozoa. Myxozoan evolution, ecology and development, 2015: p. 69–84. Dykova, I., Myxozoan genera: definition and notes on taxonomy, life-cycle terminology and pathogenic species. Folia parasitologica, 2006. Rizvi, A.N., Nematoda: Tylenchida, Triplonchida and Aphelenchida (Plant-Parasitic and Fungivorous Nematodes) . 2017, Zoological Survey of India. Moens, T. and M. Vincx, Observations on the feeding ecology of estuarine nematodes . Journal of the Marine Biological Association of the United Kingdom, 1997. 77(1): p. 211–227. Moraczewski, J., Asexual reproduction and regeneration of Catenula (Turbellaria, Archoophora) . Zoomorphologie, 1977. 88(1): p. 65–80. Dhert, P., et al., Production and evaluation of resting eggs of Brachionus plicatilis originating from the PR of China . Larvi, 1995. 95: p. 315–319. Martin, P., et al., Towards an integrative revision of Haplotaxidae (Annelida: Clitellata) . Zoological Journal of the Linnean Society, 2024. 202(4). Le Feuvre, M., S. Treadwell, and T. Mackintosh. Improving outcomes for a highly fragmented, poorly known River Blackfish population in peri-urban Melbourne . in Proceedings of the 11th Australian Stream Management Conference . 2024. Victor Harbour, SA. Bylemans, J., et al., A performance evaluation of targeted eDNA and eDNA metabarcoding analyses for freshwater fishes . Environmental DNA, 2019. 1(4): p. 402–414. Additional Declarations Competing interest reported. Authors GS and TV declare no financial or non-financial competing interests. Author CY serves as an Editor for the Nature Portfolio Collection on Biodiversity and Ecosystem Functioning of Global Peatlands and on npj Biodiversity and had no role in the peer-review or decision to publish this manuscript. Author CY declares no financial competing interests. Supplementary Files Supplementaryfile1.xlsx Supplementaryfile2.xlsx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 18 May, 2026 Reviews received at journal 11 May, 2026 Reviews received at journal 13 Apr, 2026 Reviews received at journal 10 Apr, 2026 Reviewers agreed at journal 02 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviewers agreed at journal 01 Apr, 2026 Reviewers invited by journal 01 Apr, 2026 Editor assigned by journal 31 Mar, 2026 Submission checks completed at journal 31 Mar, 2026 First submitted to journal 26 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9238693","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":616096257,"identity":"c9c43c91-a0f7-4f3d-916a-ffbd508d8c9d","order_by":0,"name":"Grace Smith","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYJCCA4wNEsz8EDYzkVoONliwSzaQooXhYEMFv8EBYrXI+59OPPxxh4S08Y30hx8YKqwTG9jPGODVYngjd8OBg2ckjM1u5BhLMJxJT2zgySGgZQYvUEubRDJQCxsDY9vhxAYGQlr6z4K11G+ekf6MgfEfUAv/G/xa5BlywVqYDSQSzBgYG4BaJAjYYiAB1HIWqEXizBtjiYRj6cZtEs8K8NvSf3bzh8q2Omb+dmCIfaixlu3nT96A35YDyLwEIGbDqx5kSwMhFaNgFIyCUTAKAPqbSzU2CrweAAAAAElFTkSuQmCC","orcid":"","institution":"University of the Sunshine Coast","correspondingAuthor":true,"prefix":"","firstName":"Grace","middleName":"","lastName":"Smith","suffix":""},{"id":616096258,"identity":"123e8f14-1fc2-4214-87e4-303c6e4455df","order_by":1,"name":"Tomer Ventura","email":"","orcid":"","institution":"University of the Sunshine Coast","correspondingAuthor":false,"prefix":"","firstName":"Tomer","middleName":"","lastName":"Ventura","suffix":""},{"id":616096263,"identity":"8afd6339-e29b-4456-b26b-cc791dd7336c","order_by":2,"name":"Catherine M. Yule","email":"","orcid":"","institution":"University of the Sunshine Coast","correspondingAuthor":false,"prefix":"","firstName":"Catherine","middleName":"M.","lastName":"Yule","suffix":""}],"badges":[],"createdAt":"2026-03-27 00:53:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9238693/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9238693/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106093783,"identity":"f7c21294-ed97-4d44-8981-8f011e483aaf","added_by":"auto","created_at":"2026-04-03 11:39:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":78771,"visible":true,"origin":"","legend":"\u003cp\u003eEnvironmental DNA samples were collected from three peat swamps on K’gari (Fraser Island). From north to south, sites sampled were Duck Creek (purple), Red Lagoon (brown), and Dilli Swamp (teal).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9238693/v1/1559b23cc1b687537a5a414b.png"},{"id":106094640,"identity":"81452b5c-f36d-49da-92e2-d848babafb2c","added_by":"auto","created_at":"2026-04-03 11:43:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":50421,"visible":true,"origin":"","legend":"\u003cp\u003eTaxonomic resolution of operational taxonomic units (OTUs) detected across all samples. Of 1,910 OTUs retained after quality filtering, 1,095 (57.3%) were assigned taxonomy using combined SILVA and custom 18S reference databases. Wedges show the number of OTUs resolved to each taxonomic rank, with 705 OTUs (36.9%) classified to at least order level.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9238693/v1/65faf85dca53bb08b8899b10.png"},{"id":105975178,"identity":"5aaccf67-eb94-4f73-9d37-6eb92465ecc5","added_by":"auto","created_at":"2026-04-02 05:06:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":42389,"visible":true,"origin":"","legend":"\u003cp\u003eInvertebrate community composition based on OTU abundance across three southeast Queensland peatland sites: Duck Creek (purple), Dilli Swamp (teal), and Red Lagoon (brown). Each point represents a biological replicate (n = 3 per site), and ellipses represent site standard deviation. Distinct clustering of samples by site indicates unique community assemblages at each location (PERMANOVA: R² = 0.77, F₂, ₆ = 10.04, p = 0.004; stress \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9238693/v1/b06e2abce9ebfbb502ed096b.png"},{"id":105975180,"identity":"a132c868-6391-4c73-9df1-44c2bfe7a29f","added_by":"auto","created_at":"2026-04-02 05:06:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":165140,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of taxonomic occurrence patterns detected by eDNA metabarcoding (left panel) and field surveys (right panel), with phylogenetic relationships indicated by dendrogram and major clades annotated. White boxes indicate taxa where methods differed in taxonomic resolution, with labels indicating the classification achieved by the less-resolved method. Colour represents log-corrected relative detection frequency across samples.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9238693/v1/fd67d4f63edb23b5f02291f6.png"},{"id":105975181,"identity":"cb03c17a-1254-4f3f-9bc7-0d50687c764e","added_by":"auto","created_at":"2026-04-02 05:06:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":26233,"visible":true,"origin":"","legend":"\u003cp\u003eInvertebrate assemblages detected by eDNA metabarcoding (triangles) versus field surveys (circles) across three peatland sites (stress = 0). Colours indicate site identity: Duck Creek (purple), Dilli Swamp (teal), and Red Lagoon (brown). Method explained 69% of variation, mostly across nMDS1, compared to 15% for site, mostly across nMDS2, however neither effect was statistically significant due to small sample size (PERMANOVA: Method R² = 0.69, p = 0.08; Site R² = 0.15, p = 0.68).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9238693/v1/769c6c4ade62b4200b821108.png"},{"id":106402066,"identity":"ddebbf68-4789-41b9-9420-b0f644231d37","added_by":"auto","created_at":"2026-04-08 09:10:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1084253,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9238693/v1/2c3c1ca2-5da1-4b5e-ba14-31d3ba0c868f.pdf"},{"id":105975175,"identity":"bdafb87e-aa31-40d0-89b0-58537be7ef85","added_by":"auto","created_at":"2026-04-02 05:06:15","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":300051,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9238693/v1/4500f2c218b83272ce4024ef.xlsx"},{"id":105975177,"identity":"becbee01-dcae-464a-be3d-2d3c1d334540","added_by":"auto","created_at":"2026-04-02 05:06:15","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":56225,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9238693/v1/67a9a6c9adf1dce6d4e80107.xlsx"}],"financialInterests":"Competing interest reported. Authors GS and TV declare no financial or non-financial competing interests. Author CY serves as an Editor for the Nature Portfolio Collection on Biodiversity and Ecosystem Functioning of Global Peatlands and on npj Biodiversity and had no role in the peer-review or decision to publish this manuscript. Author CY declares no financial competing interests.","formattedTitle":"eDNA metabarcoding reveals invertebrate diversity in the blackwater pools of southeast Queensland peatlands","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eWhile most peatlands globally are destroyed by fire, the \u003cem\u003eEmpodisma\u003c/em\u003e-dominated peatlands of southeast Queensland rely on periodic burns to maintain the dominance of the peat-forming wire rush \u003cem\u003eEmpodisma minus\u003c/em\u003e, making them the only known pyrophilic peatlands in the world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These ecosystems are characterized by highly acidic, nutrient-poor blackwater pools which, despite their physiochemically harsh conditions, harbor a disproportionately high diversity of rare and locally endemic species, many of which are threatened with extinction [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe common denominator for threatened species vulnerability in southeast Queensland is the extensive habitat loss, fragmentation and degradation driven by rapid and ongoing urbanisation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Where suitable habitat persists, threatened fauna maintain relatively high local abundances, indicating that ecosystem-level threats are the primary conservation concern [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The broader implication of this ecosystem-level threat is that \u003cem\u003eall\u003c/em\u003e endemic species are subject to the same threatening processes, yet the invertebrate fauna remain almost entirely overlooked. Only two crayfish and one dragonfly species are formally recognized as threatened [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and many species remain undescribed. Though the number of invertebrate species in Australia (\u0026gt;\u0026thinsp;320 000) far exceeds the number of vertebrates (~\u0026thinsp;7400) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Insects and crustaceans, let alone microscopic taxa, are typically neglected in assessments and descriptions, largely as a result of their low public profile and the taxonomic challenges posed by their tiny size and cryptic ecology [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Woinarski et al (2025) estimate that over 6000 undescribed Australian invertebrate species have already been lost in undocumented extinctions, dwarfing Australia\u0026rsquo;s 51 formally recognised vertebrate extinctions [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe diversity and abundance of predatory fishes, amphibians, and macroinvertebrates in peatland ecosystems implies a more substantial invertebrate prey base than currently documented [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Extreme environments promote high levels of endemism due to the unique selective pressures and isolation they impose [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Peatlands represent one such extreme ecosystem, where the physically and chemically recalcitrant vegetation produce unpalatable leaf litter and the acidic, tannin-darkened waters impede algal growth, creating a fundamentally different trophic structure than most freshwater systems. While the vegetation forms the structural foundation of the peat, basal energy pathways are thought to be dominated by chemotrophic microbes and fungi [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn exceptionally high diversity of more than 3700 sequence variants across 34 phyla of bacteria and archaea with 97% novelty has been documented in \u003cem\u003eEmpodisma-\u003c/em\u003epeatlands using 16S rRNA profiling [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Microbial communities are most abundant and diverse towards the surface layers of the peat, reflecting gradients in water availability, oxygen saturation, nutrients, and substrate variability. Metabolism is dominated by anaerobic and microaerophilic pathways, particularly hydrogenotrophic methanogenesis and sulphate reduction. This same vertical structuring is also observed in microbial enzymatic activity [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and fungal abundance and diversity [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Microbes are key to carbon and nutrient cycling within these oligotrophic systems, likely forming the foundation of the peatland food web, given the toxic and nutrient-poor nature of the vegetation. However, the microscopic invertebrates that surely link microbial primary production to higher-order consumers remain largely invisible in both ecological research and conservation assessments.\u003c/p\u003e \u003cp\u003eBuilt on the same principles as microbial genetic profiling, environmental DNA (eDNA) metabarcoding is a robust and widely employed biomolecular tool for biodiversity assessment across a range of ecosystems [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In peat systems, metabarcoding studies have predominantly employed 18S or CO1 markers favouring a short amplicon length due to the fragmented and degraded nature of peat eDNA [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. By targeting trace genetic material shed by organisms into their environment, eDNA metabarcoding allows non-invasive detection while providing more comprehensive taxonomic coverage than is typically achievable through conventional survey methods alone. This approach circumvents the need for direct capture or visual observation, making it both cost and labour efficient, and is particularly effective for detecting rare, cryptic, or highly mobile taxa often underrepresented in traditional monitoring efforts [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. To minimize false detections, eDNA surveys are typically conducted alongside field sampling, allowing molecular detections to be validated against observational records [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHere, we use eDNA metabarcoding to describe the invertebrate diversity in blackwater pools of southeast Queensland peatlands. Targeting areas of high endemism using combined molecular profiling and field morphological surveys, we aim to document invertebrate taxonomic diversity, including cryptic and microscopic taxa overlooked by traditional surveys. Our findings reveal a previously unrecognized diversity of invertebrate taxa and demonstrate the applicability and efficacy of molecular tools in the description of cryptic community assemblages.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Site description\u003c/h2\u003e \u003cp\u003eK\u0026rsquo;gari (also referred to as Fraser Island in literature up to 2021) is the world\u0026rsquo;s largest sand island, formed between 1.2\u0026ndash;0.7\u0026nbsp;million years ago during Pleistocene sea-level fluctuations [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The peat swamps on K\u0026rsquo;gari are dominated by \u003cem\u003eE. minus\u003c/em\u003e (50\u0026ndash;90% cover), surrounding a mosaic of shallow (\u0026lt;\u0026thinsp;30cm) to deep (\u0026gt;\u0026thinsp;1.5m) blackwater pools. Co-dominant vegetation mostly comprises graminoids (\u003cem\u003eLepironia articulata\u003c/em\u003e, \u003cem\u003eGahnia sieberiana\u003c/em\u003e), forbs (\u003cem\u003eGleichenia mendellii\u003c/em\u003e, \u003cem\u003eBlechnum indicum\u003c/em\u003e, \u003cem\u003eHibbertia salicifolia\u003c/em\u003e, \u003cem\u003eDrosera binata\u003c/em\u003e), and shrubs (\u003cem\u003eLeptospermum liversidgei\u003c/em\u003e, \u003cem\u003eBanksia robur\u003c/em\u003e, \u003cem\u003eEpacris microphylla\u003c/em\u003e) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Three peat swamps with differing fire histories were selected for this study (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Maximum peat depth ranged from 1.8m at Red Lagoon to 7.85m at Dilli Swamp. Dilli Swamp and Duck Creek have formed in fluvial plains and acidic clearwater streams which are hydrologically distinct and fed largely by groundwater, flow through these peatlands. These streams have a distinct fauna, including taxa needing higher oxygen levels that occur in the peatland pools as well as abundant algae.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSample sites and fire history (most recent fire date shown in bold)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGPS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePrevious fire dates\u003c/p\u003e \u003cp\u003eManaged burn (MB), Wildfire (W)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed Lagoon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS -25.554969,\u003c/p\u003e \u003cp\u003eE 153.06112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2008\u003c/b\u003e(MB)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDilli Swamp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS -25.598680,\u003c/p\u003e \u003cp\u003eE 153.08353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1980(MB), 1983(MB), 1985(MB), 1991(W), 1996(MB), 2001(MB), 2008(MB), 2009(W), \u003cb\u003e2016\u003c/b\u003e(MB)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuck Creek\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS -25.44355\u003c/p\u003e \u003cp\u003eE 153.01135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1985(MB), 1992(W), \u003cb\u003e2011\u003c/b\u003e(MB)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Field sampling\u003c/h2\u003e \u003cp\u003eSampling was conducted in July 2023. At each of the three sites, three replicate 1L water samples were collected, for a total of nine samples. Water was filtered in the field through 200\u0026micro;m mesh to remove coarse debris, collected in autoclaved plastic bottles, and transported on ice to the PC2 laboratory facilities at the University of the Sunshine Coast.\u003c/p\u003e \u003cp\u003eDipnet surveys were also conducted using three replicate 10 second sweeps per pool, at three pools per site. Macroinvertebrates were sorted in the field using white trays, identified to the lowest possible taxonomic level \u003cem\u003ein situ\u003c/em\u003e where feasible, or preserved in 80% ethanol for laboratory identification under a stereomicroscope.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Sample processing\u003c/h2\u003e \u003cp\u003eWithin 72 hours of collection, water samples were filtered through 0.45 \u0026micro;m nanopore membranes under sterile conditions in the University of the Sunshine Coast\u0026rsquo;s PC2 facility. Filter membranes were sectioned into ~\u0026thinsp;1 mm strips and stored at 4\u0026deg;C until DNA extraction. All equipment was autoclaved and rinsed with ultrapure water prior to use and disinfected with ethanol between samples.\u003c/p\u003e \u003cp\u003eGenomic DNA was extracted using the DNeasy PowerSoil Kit (Qiagen) following manufacturer instructions on a dedicated PCR-free bench. Multiple primer sets (18S, 16S, ITS, COI) were trialled, with 18S yielding the highest amplification efficiency. The V4 region of the 18S rRNA gene was amplified using the following forward and reverse primers [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eUni18S_450F: 5\u0026rsquo; AGGGCAAKYCTGGTGCCAGC 3\u0026rsquo;\u003c/p\u003e\u003cp\u003eUni18S_450R: 5\u0026rsquo; GRCGGTATCTRATCGYCTT 3\u0026rsquo;\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ePCR reactions (25 \u0026micro;L total volume) used 1 \u0026micro;L each of forward and reverse primers, with cycling conditions as follows: initial denaturation at 75\u0026deg;C for 2 min, followed by 35 cycles of 75\u0026deg;C denaturation (40s), 55\u0026deg;C annealing (40s), and 72\u0026deg;C extension (10 min), with a final hold at 10\u0026deg;C. PCR products were visualised on 2% agarose gels and quantified using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Australia). Amplicons (30 \u0026micro;L per sample) were desiccated and sequenced using the Illumina MiSeq platform (Novogene, Hong Kong).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Bioinformatic analysis\u003c/h2\u003e \u003cp\u003eRaw paired-end reads were processed in Galaxy Australia (v25.0.3). \u003cem\u003eCutadapt\u003c/em\u003e was used to verify that primer sequences were removed, and read quality was assessed with \u003cem\u003eFASTQC\u003c/em\u003e. Quality filtered reads were processed with the \u003cem\u003eLotuS2\u003c/em\u003e pipeline [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] to merge, demultiplex, and remove chimeras, in total generating 3809 operational taxonomic units (OTUs). LotuS2 was run with the following non-default parameters and specifications: \u003cem\u003eTax aligner\u003c/em\u003e = \u0026ldquo;Lambda, LCA\u0026rdquo;; \u003cem\u003eReference database\u003c/em\u003e\u0026thinsp;=\u0026thinsp;SILVA SSU/LSU database; \u003cem\u003eUse the best BLAST hit only\u003c/em\u003e = \u0026ldquo;yes\u0026rdquo;; \u003cem\u003eChimera check\u003c/em\u003e = \u0026ldquo;OTU chimera check\u0026rdquo;; \u003cem\u003eAmplicon type\u003c/em\u003e = \u0026ldquo;SSU\u0026rdquo;; \u003cem\u003eSequencing platform\u003c/em\u003e = \u0026ldquo;MiSeq.\u0026rdquo; Resulting OTUs were additionally queried against an inhouse custom 18S rRNA invertebrate database (Supplementary File 1), constructed from NCBI reference 18S sequences (GenBank 268.0).\u003c/p\u003e \u003cp\u003eR v4.1.2 was used to complete taxonomic assignment and data processing (R Core Team, 2025). The SILVA and custom 18S taxonomic assignments were joined by accession number and filtered by minimum percent identity as follows: \u0026ge;98% = genus-level (custom database), \u0026ge;\u0026thinsp;95% = family-level (custom database), \u0026ge;\u0026thinsp;90% = order-level (custom database; SILVA annotation retained for two unresolved rotifer OTUs), \u0026lt;\u0026thinsp;90% = SILVA annotation (or custom database classification at class level if SILVA was unresolved). OTUs with taxonomic assignment confidence\u0026thinsp;\u0026lt;\u0026thinsp;85% were discarded.\u003c/p\u003e \u003cp\u003eCommunity structure was visualized using non-metric multidimensional scaling (nMDS) based on Bray-Curtis dissimilarities using the \u003cem\u003evegan\u003c/em\u003e package [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. All figures were generated in \u003cem\u003eggplot2\u003c/em\u003e [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], with a \u003cem\u003eviridis\u003c/em\u003e colour palate [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Phylogenetic trees were generated using \u003cem\u003ePhyloT\u003c/em\u003e (v2 2023.2) and visualized in \u003cem\u003eiTOL\u003c/em\u003e v7 [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], with heatmap annotations overlaid in \u003cem\u003eggplot2\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cp\u003eAn average of 1.2\u0026nbsp;million high-quality reads were obtained per sample (range 1.01\u0026ndash;1.41\u0026nbsp;million). After denoising to remove sequencing errors and artifacts, merging, and chimera removal, 1910 operational taxonomic units (OTUs) were retained. Of these, 1095 OTUs (57.3%) were successfully assigned a taxonomic classification using the combined SILVA and custom 18S reference databases as described above. 705 OTUs (36.9%) were resolved to at least order level (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The remaining 815 OTUs (42.7%) could not be assigned to any taxonomic group, which is within expected range for 18S V4 metabarcoding against the SILVA and/or curated NCBI databases [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003enMDS based on OTU abundance showed distinct invertebrate community assemblages between sites, with samples clustering by site (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) with a very low stress value (stress\u0026thinsp;=\u0026thinsp;9.45e⁻⁵). Permutational multivariate analysis of variance (PERMANOVA) confirmed significant differences in community composition between the three peatland sites (PERMANOVA: R\u0026sup2; = 0.77, F₂, ₆ = 10.04, p\u0026thinsp;=\u0026thinsp;0.004). Site identity explained 77% of the variation in community composition, demonstrating that Duck Creek, Dilli Swamp, and Red Lagoon each have unique invertebrate assemblages consistent with the lack of connectivity due to hydrological isolation between the three peatland sites despite relatively close proximity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn total, eDNA metabarcoding identified 63 unique taxa representing 27 orders across 10 phyla (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, left panel). Detected taxa included one vertebrate group (bony fishes, Teleostei), three major arthropod clades (crustaceans, insects, and mites) and oligochaete annelids, all of which were previously documented in these systems through field surveys. Metabarcoding also revealed five microscopic invertebrate phyla which had not previously been recorded from southeast Queensland peatlands: Platyhelminthes, Nematoda, Gastrotricha, Rotifera, and one freshwater parasitic cnidarian (Myxozoa). Taxonomic resolution varied among groups, with crustaceans and insects generally resolved to family or genus level, while non-arthropod invertebrate phyla were typically resolved only to class or order level, likely due to their relative underrepresentation in reference databases.\u003c/p\u003e \u003cp\u003eComparison of eDNA metabarcoding and field morphological surveys found complementary strengths in each method (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, both panels). Metabarcoding was more effective in detecting cryptic, microscopic taxa, including worms (annelids, platyhelminths, nematodes), gastrotrichs, rotifers, and one myxozoan parasite. Field surveys recorded only a single oligochaete annelid among these phyla. Metabarcoding also provided finer taxonomic resolution for microcrustaceans, identifying copepods and cladocerans to genus or family level compared to order-level identification from morphological surveys (due to lack of taxonomic expertise in the lab for microcrustacea). For decapods, field surveys performed slightly better than metabarcoding. Both methods successfully detected \u003cem\u003eCherax\u003c/em\u003e crayfish and \u003cem\u003eHeterias\u003c/em\u003e isopod, though only field surveys detected \u003cem\u003eCaridina\u003c/em\u003e shrimp. Within hexapods, field surveys generally achieved finer taxonomic resolution. Collembola were resolved to family level by morphology but only to class level by metabarcoding. Unique method-specific detections were observed in both directions. Metabarcoding detected two dipterans, two odonatans, one hemipteran, and two coleopterans which were not detected in field surveys. However, some of these records were detected only at single sites and could represent false positives. By comparison, field surveys detected five dipterans, two odonatans, two hemipterans, two trichopterans, and one coleopteran which were not detected by metabarcoding, representing false negatives in the metabarcoding dataset. There were no false detections at the order level in either direction.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003enMDS found that sampling method (field surveys or metabarcoding) had a large but marginally significant effect on detected community assemblage (Method R\u0026sup2; = 0.69, F₁, ₂ = 8.43, p\u0026thinsp;=\u0026thinsp;0.08), while site did not have an effect (Site R\u0026sup2; = 0.15, F₂,₂ = 0.92, p\u0026thinsp;=\u0026thinsp;0.68) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Methods separated primarily along the first dimension (nMDS1), with weaker differentiation of site along the second dimension (nMDS2). Method therefore had substantially stronger influence on observed community composition than actual variation between peatland sites.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Community diversity overview\u003c/h2\u003e \u003cp\u003eEnvironmental DNA metabarcoding of 18S rRNA detected 63 invertebrate taxa across three southeast Queensland peatlands, revealing a considerably greater taxonomic breadth than conventional field surveys using dip nets. Sites showed strong spatial heterogeneity, each peatland hosting a distinct invertebrate assemblage, consistent with unique microbial communities detected across sites by Too et al (2026, manuscript in prep). Metabarcoding provided finer taxonomic resolution for morphologically cryptic microcrustaceans and detected five invertebrate phyla which had not previously been recorded from southeast Queensland peatlands (Cnidaria, Rotifera, Platyhelminthes, Nematoda, and Gastrotricha). For more conspicuous taxa (i.e. decapods and insects), field surveys typically provided better resolution, though neither method provided a complete taxonomic coverage. Integrated approaches that combine molecular and field methods would therefore yield the most complete characterization of invertebrate diversity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Fish, crustaceans, and insects\u003c/h2\u003e \u003cp\u003eCombined survey methods detected four fish taxa, 17 crustacean taxa, and 29 hexapod taxa. Metabarcoding identified all four fish to genus level, each represented by a single local species within their respective genera: honey blue-eye (\u003cem\u003ePseudomugil mellis\u003c/em\u003e), Oxleyan pygmy perch (\u003cem\u003eNannoperca oxleyana\u003c/em\u003e), and firetail gudgeon (\u003cem\u003eHypseleotris galii\u003c/em\u003e), all documented to occur in local peatlands, and purple-spotted gudgeon (\u003cem\u003eMogurnda adspersa\u003c/em\u003e), which is documented from upstream habitats but not from peatland pools themselves [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. This record likely represents DNA transport from upstream populations or could represent misidentification of the closely related ornate rainbowfish (\u003cem\u003eRhadinocentrus ornatus\u003c/em\u003e), which is well documented in peatlands but was not detected [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Acid fish are known to niche partition by diet, with \u003cem\u003eN. oxleyana\u003c/em\u003e targeting mid-strata macroinvertebrates, \u003cem\u003eP. mellis\u003c/em\u003e targeting surface skimmers and \u003cem\u003eH. galii\u003c/em\u003e targeting larger surface invertebrates and macrophytes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This diversity of feeding strategies implies a diverse macroinvertebrate prey assemblage.\u003c/p\u003e \u003cp\u003eBoth methods successfully detected the undescribed isopod \u003cem\u003eHeterias\u003c/em\u003e sp. nov. and \u003cem\u003eCherax\u003c/em\u003e crayfish, though taxonomic resolution beyond genus was unresolved, as the 18S-v4 region does not distinguish between the endemic specialist \u003cem\u003eCherax robustus\u003c/em\u003e and the more widespread generalist \u003cem\u003eC. dispar\u003c/em\u003e, both of which occur in the broader catchment. \u003cem\u003eCaridina\u003c/em\u003e shrimp were detected only by field surveys. Metabarcoding achieved finer resolution within cladocerans and copepods, which are notoriously difficult to identify morphologically. The consistently high detection of copepods could indicate significant biomass, although could also be an artifact of primer bias.\u003c/p\u003e \u003cp\u003eA high diversity of predatory insects was detected, including odonatans (Aeshnidae, Coenagrionidae, Lestidae, Libellulidae), hemipterans (Corixidae, Gerridae) and Coleopterans (Dytiscidae, Scirtidae, Hydraenidae, Chrysomelidae, Hydrophilidae), which suggests a high diversity of prey species to accommodate niche partitioning. Field surveys generally demonstrated better taxonomic resolution within Hexapoda. Metabarcoding achieved lower taxonomic resolution for Collembola and Chrysomeloidea beetles and failed to detect numerous insect families identified morphologically. Both methods showed perfect congruence at the order level (100% overlap in insect orders detected), but declined substantially at finer taxonomic scales, with less than one-third of insect genera detected by both methods. Our broad 18S approach therefore provides reliable presence/absence data at higher classification levels but lacks the resolution and sensitivity for genus-level assessment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Microscopic diversity\u003c/h2\u003e \u003cp\u003eSix non-arthropod invertebrate phyla were detected by metabarcoding, five of which (Cnidaria, Rotifera, Platyhelminthes, Nematoda, and Gastrotricha) are the first records of these phyla southeast Queensland peatlands. A summary of functional traits and feeding strategies can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. These microscopic taxa are largely detritovores or bacterivores, rather than herbivores, with most groups primarily reproducing parthenogenically \u0026ndash; the notable exceptions being nematodes, annelids, and rhabdocoelid flatworms, which exclusively reproduce sexually [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. These groups represent complex trophic interactions, though their taxonomy and functional roles remain poorly resolved.\u003c/p\u003e \u003cp\u003eThe three worm phyla detected (Nematoda, Platyhelminthes, and Annelida) showed functional diversity spanning bacterivores, algal grazers, detritivores, and in some nematodes, parasites. Catenulid flatworms reproduce via asexual budding, but all other detected worm groups rely on sexual reproduction [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRotifers also proved highly diverse across three detected orders, with feeding strategies ranging from sessile suspension filter feeding to active predation and grazing [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. All rotifer groups share parthenogenic reproduction and possess dormancy mechanisms such as desiccation-resistant resting eggs [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAll identified gastrotrichs belonged to the order Chaetonotida, benthic grazers which exhibit parthenogenetic reproduction, rapid development, and produce dormant resting eggs [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Targeted field sampling rewetting dried peat confirmed the presence of gastrotrichs in the genus \u003cem\u003eChaetonotus\u003c/em\u003e, including two undescribed species (A. Todaro pers comm.), providing validation of metabarcoding accuracy and lending support to other detections.\u003c/p\u003e \u003cp\u003eThe most unexpected finding was Bivalvulida (phylum Cnidaria), microscopic endoparasites detected at all three sites. Most described bivalvulids parasitize freshwater fishes, and are relatively common in oligotrophic systems, though poorly documented [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. The detection of Bivalvulida across all surveyed peatland sites indicates active parasitism of local fish (\u003cem\u003ePseudomugil, Nannoperca, Hypseleotris\u003c/em\u003e) with an intermediate annelid host, [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], though specific transmission pathways remain unknown.\u003c/p\u003e \u003cp\u003eAcross these microscopic taxa, convergent life-history traits emerge that appear highly adaptive for characteristic peatland acidity, anoxia, fire, and hydrological variability. Parthenogenetic reproduction and short generation times enable rapid population recovery from small founding populations, while desiccation-resistant resting stages allow survival through fire and drought. Feeding strategies consistently target algae, bacteria, or detritus rather than vegetation. Collectively, these traits confer resilience to the boom-bust cycles characteristic of peatlands, drawing on similar patterns of desiccation resilience, anoxia tolerance and stationary phases as previously observed in the sympatric microbe communities [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFunctionally, these microscopic invertebrates likely constitute the critical trophic link between microbial production and higher-order consumers. By consuming bacteria, fungi, and fine particulate organic matter, they convert microbial biomass into prey accessible to larger predators. The abundant and diverse assemblages of predatory copepods, odonatans, hemipterans, and fishes documented in these systems require a substantial prey base, which these microscopic taxa almost certainly provide. Moreover, their rapid recolonisation likely stabilizes ecosystem function following disturbance events, particularly fires, restoring food web connectivity and supporting the recovery of higher trophic levels.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFunctional traits of microscopic invertebrate taxa identified by eDNA metabarcoding.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhylum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOrder\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDiet\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReproduction\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrotricha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChaetonotida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChaetonotida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBenthic microphagous detritivores\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eParthenogenesis, rapid development, resting eggs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTodaro et al., 2019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eNematozoa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eChromadorea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChromadorida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBenthic bacteria/microbe grazer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eDioecious; sexual reproduction (parthenogenesis uncommon)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eYeates et al., 1993\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAraeolamida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBacterivore\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMonhysterida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBenthic bacterivore\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTylenchida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRoot ectoparasite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePe\u0026ntilde;a-Santiago et al., 2006; Rizvi, 2017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEnoplea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnoplida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMicrophagous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMoens \u0026amp; Vincx, 1997\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTriplonchida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTerrestrial plant parasite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRizvi, 2017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePlatyhelminthes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCatenulida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFree-living detritovore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAsexual paratomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLarsson, 2008; Moraczewski, 1977\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRhabditophora\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRhabdocoela\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePredator/scavenger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHermaphrodites; sexual reproduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLarsson, 2008; Nore\u0026ntilde;a et al., 2016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRotifera\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBdelloidea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdinetida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBacteria/detritus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eObligate parthenogenesis; tolerant to desiccation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFontaneto \u0026amp; Ricci, 2006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMonogononta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFlosculariacea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSessile filter feeder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCyclical parthenogenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWallace \u0026amp; Snell, 2001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePloimida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOmnivorous predator/filter-feeder/grazer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCyclical parthenogenesis or sexual reproduction; resting eggs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDhert et al., 1995; Leasi et al., 2009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCnidaria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMyxozoa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBivalvulida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEndoparasitic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAsexual reproduction (fish host); sexual reproduction (annelid host)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLom \u0026amp; Dykov\u0026aacute;, 2005; Dykova, 2006; Fiala et al., 2015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnnelida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOligocheta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHaplotaxida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDetritovore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHermaphrodites; sexual reproduction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMartin et al., 2024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Outcomes and limitations\u003c/h2\u003e \u003cp\u003eSites showed strong spatial structuring, with each peatland hosting a distinct invertebrate assemblage. This heterogeneity reflects the unique fire histories, hydrology, and lack of connectivity between each site. Duck Creek is geographically isolated from Dilli Swamp and Red Lagoon by K'gari's central dune ridge, while Dilli Swamp and Red Lagoon, despite geographic proximity, are separated by multiple smaller dunes and drainages. Given these site-specific characteristics, uniform management practices are unlikely to be equally effective across all peatland sites.\u003c/p\u003e \u003cp\u003eThe combined complementary strengths of metabarcoding and field surveys offer a cost-effective strategy for comprehensive monitoring that balances taxonomic breadth with detection sensitivity. eDNA metabarcoding provides several advantages, being non-invasive, minimising impacts on sensitive ecosystems and vulnerable populations, while enabling the detection of \"dark taxa\u0026rdquo; typically invisible in conventional surveys. However, there are many inherent limitations which must be acknowledged in metabarcoding. Spatial uncertainty, such as DNA transport from upstream populations, complicates interpretation. False negatives arising from primer bias or incomplete reference databases can result in failure to detect present taxa. Aside from \u003cem\u003eChaetonotus\u003c/em\u003e (Gastrotricha) and Oligochaeta (Annelida), the microscopic taxa detected by metabarcoding remain unvalidated. Furthermore, eDNA cannot provide abundance estimates or demographic information (such as adults versus larvae). Hence, the continued necessity of field surveys for population monitoring, validation, and demographic data.\u003c/p\u003e \u003cp\u003eThe universal 18S primers employed here maximized taxonomic breadth at the cost of resolution, with most taxa identified only to order or family level. For targeted surveys, such as monitoring threatened fishes, taxa-specific primers would provide finer resolution, potentially to species level [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. A combined monitoring approach, integrating morphological surveys with eDNA surveys, provides the most comprehensive taxonomic assessment. Expanding reference libraries through database development and voucher-based sequencing, particularly for endemic and undescribed taxa, could dramatically improve identification accuracy.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis study used eDNA metabarcoding to document previously unrecorded invertebrate diversity in southeast Queensland's pyrophilic peatlands, detecting five phyla never recorded through conventional surveys and providing improved taxonomic resolution for morphologically cryptic microcrustaceans. The documented microscopic fauna likely constitutes the critical trophic link between microbial production and higher-order consumers. The convergent life-history traits observed across these taxa, including parthenogenetic reproduction, desiccation-resistant dormant stages, and rapid generation times, appear adaptive for the stochastic disturbance regimes characteristic of fire-dependent peatlands, enabling rapid community recovery following disturbance.\u003c/p\u003e \u003cp\u003eComparison with morphological surveys found that the methods were complementary, with neither approach alone capturing complete taxonomic diversity. Integration of both methods in biodiversity assessments therefore provides more comprehensive characterization than either approach in isolation. Future research should consider voucher-based sequencing to improve reference databases, formal taxonomic description of novel peatland taxa, and investigation of the functional roles of microscopic invertebrates in peatland food webs and post-fire ecosystem stabilization.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eAuthors GS and TV declare no financial or non-financial competing interests. Author CY serves as an Editor for the Nature Portfolio Collection on Biodiversity and Ecosystem Functioning of Global Peatlands and on npj Biodiversity and had no role in the peer-review or decision to publish this manuscript. Author CY declares no financial competing interests.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e \u003ch2\u003eSupplementary information\u003c/h2\u003e \u003cp\u003eAnnotated OTUs are available as \u003cb\u003eSupplementary file 1.xlsx\u003c/b\u003e. Field sampling results used for comparison in Figs.\u0026nbsp;4 and 5 are available as \u003cb\u003eSupplementary file 2.xlsx\u003c/b\u003e. The custom 18S rRNA invertebrate reference database will be made available on request.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eCY and GS conducted field sampling. GS and TV conducted lab work. GS conducted data analyses. GS wrote the original draft of the manuscript. CM and TV reviewed and revised the draft. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThis study was funded by the Queensland Government Community Sustainability Action Grant CSAT22032 for Ecosystem based approach to protecting threatened species in subtropical peat swamps. The funder played no role in study design, data collection, analysis and interpretation of data, or the writing of this manuscript.We thank Prof. Antonio Todaro (University of Modena \u0026amp; Reggio Emilia) for his validation of our gastrotrich samples.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData availabilityRaw sequencing data is available via the NCBI Sequence Reference Archive (SRA) under BioProject #PRJNA1402468. Code availabilityR scripts used for statistical analyses and code used to generate all figures is available through the GitHub repository: github.com/graceponders/eDNA-methods-analysis.Supplementary informationAnnotated OTUs are available as Supplementary file 1.xlsx. Field sampling results used for comparison in figures 4 and 5 are available as Supplementary file 2.xlsx. The custom 18S rRNA invertebrate reference database will be made available on request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYule, C., \u003cem\u003ePeat was historically mined overseas because it burns so well. But Australia\u0026rsquo;s subtropical peat bogs need fire to survive\u003c/em\u003e. The Conversation, 2024. 4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePage, T.J., \u003cem\u003eNomination to change the conservation class of Cherax robustus under the Queensland Nature Conservation Act 1992\u003c/em\u003e. 2021, Department of Environment and Science: Brisbane.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArthington, A., \u003cem\u003eRecovery plan for the Oxleyan pygmy perch, Nannoperca oxleyana\u003c/em\u003e. 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Mackintosh. \u003cem\u003eImproving outcomes for a highly fragmented, poorly known River Blackfish population in peri-urban Melbourne\u003c/em\u003e. in \u003cem\u003eProceedings of the 11th Australian Stream Management Conference\u003c/em\u003e. 2024. Victor Harbour, SA.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBylemans, J., et al., \u003cem\u003eA performance evaluation of targeted eDNA and eDNA metabarcoding analyses for freshwater fishes\u003c/em\u003e. Environmental DNA, 2019. 1(4): p. 402\u0026ndash;414.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-biodiversity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjbiodivers","sideBox":"Learn more about [npj Biodiversity](https://www.nature.com/npjbiodivers/)","snPcode":"44185","submissionUrl":"https://mts-npjbiodivers.nature.com/cgi-bin/main.plex","title":"npj Biodiversity","twitterHandle":"@npjbiodiversity","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"npj","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-9238693/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9238693/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDespite harbouring a disproportionate diversity of rare and endemic species, the pyrophilic peatlands of southeast Queensland remain poorly characterized, particularly regarding their invertebrate communities. In the physiochemically extreme blackwater pools, microscopic invertebrate assemblages likely form critical trophic links but have never been described due to their low public profile, small size and cryptic nature. This study used 18S environmental DNA metabarcoding to characterize invertebrate communities across three peatland sites, revealing significantly greater taxonomic breadth than conventional surveys. 63 taxa across 10 phyla were detected, including five microscopic phyla previously unrecorded in these ecosystems (Cnidaria, Rotifera, Platyhelminthes, Nematoda and Gastrotricha). Metabarcoding exceeded the resolution achieved by field surveys for morphologically cryptic microcrustaceans, however field surveys achieved better resolution for hexapods, demonstrating that the methods target complementary niches, each focused at distinct components of the invertebrate community. The documented microfauna overlap in key life-history traits, including rapid maturation, parthenogenetic reproduction, and dormancy capabilities, occupying the crucial intermediary trophic link between microbial production and higher consumers. These traits likely enable rapid community recovery and ecosystem stabilization following fire disturbances characteristic of pyrophilic peatlands. Our findings reveal a previously unrecognized diversity of invertebrate taxa and demonstrate the efficacy of molecular tools in the description of cryptic community assemblages.\u003c/p\u003e","manuscriptTitle":"eDNA metabarcoding reveals invertebrate diversity in the blackwater pools of southeast Queensland peatlands","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-02 05:06:10","doi":"10.21203/rs.3.rs-9238693/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-18T07:54:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-11T19:19:14+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-13T12:11:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-10T08:55:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"251709145833248563624412932388007555531","date":"2026-04-02T08:00:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"312857174699988602645590021340414395816","date":"2026-04-01T16:40:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"480303080112362947256591803824391979","date":"2026-04-01T15:26:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-01T14:16:05+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-31T15:28:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-31T12:37:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Biodiversity","date":"2026-03-27T00:45:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-biodiversity","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"npjbiodivers","sideBox":"Learn more about [npj Biodiversity](https://www.nature.com/npjbiodivers/)","snPcode":"44185","submissionUrl":"https://mts-npjbiodivers.nature.com/cgi-bin/main.plex","title":"npj Biodiversity","twitterHandle":"@npjbiodiversity","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"npj","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d69d01a5-aae0-4407-bf01-cf59b7d3ef8d","owner":[],"postedDate":"April 2nd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-18T07:54:11+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-11T19:19:14+00:00","index":19,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":65562053,"name":"Biological sciences/Ecology"},{"id":65562054,"name":"Earth and environmental sciences/Ecology"},{"id":65562055,"name":"Biological sciences/Evolution"}],"tags":[],"updatedAt":"2026-05-18T08:08:26+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-02 05:06:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9238693","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9238693","identity":"rs-9238693","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}