Biology subjects

Leese, F.

Publications and source records attributed to Leese, F..

At least 19 recordsLinked to original sources

bioRxiv2026

Charting the insect biodiversity of Crete: insights from a pilot metabarcoding survey

Among eukaryotes, insects are by far the most diverse organisms on Earth, yet their global decline threatens ecosystem stability. Understanding local and regional biodiversity patterns is critical for conservation planning, ecosystem management, and predicting responses to environmental change, but traditional surveys for assessing insect diversity (e.g., manual collection, morphological identification, and counting) are highly labor-intensive, time-consuming, and often require rare or simply unavailable dedicated taxonomic expertise. DNA metabarcoding offers an efficient, high-resolution alternative to assess insect communities. Here, we report on the first insect metabarcoding survey on Crete that spans two years of sample collection between 2021 and 2023 from a small area in Southern Central Crete in the context of a citizen science project. A total of 29 samples yielded 10,865 Exact Sequence Variants (ESVs), 10,516 of which were assigned to insects, covering 988 species, 900 genera, and 227 families across 14 orders. A comparison with the existing observation records reveals 406 potential newly-observed species and an estimated 690 unclassified species, indicating substantial cryptic diversity. Our results demonstrate that even small-scale sampling can unravel substantial insect diversity and highlight critical gaps in barcode reference databases. Our study demonstrates how DNA metabarcoding can accelerate biodiversity discovery and monitoring in understudied regions.

ecology↗

bioRxiv2026

Disentangling mitochondrial copy number variation and PCR amplification bias in DNA metabarcoding

DNA metabarcoding is a central tool in biodiversity research and monitoring, producing detailed taxa lists with comparatively little time and effort. One of its limitations, however, is the lack of quantitative data on biomass or abundance. This limitation has two main reasons: 1) DNA template copy number variation and 2) primer-induced PCR amplification bias. Many metabarcoding markers are mitochondrial and mitochondrial DNA copy numbers vary in animal tissues, potentially decoupling sequence counts from biomass. Additionally, primer mismatches can lead to taxon-specific amplification biases, for which PCR cycle calibration has been proposed as a solution. To mechanistically study both effects, we constructed and analyzed mock communities of different arthropod species. We combined digital PCR and COI metabarcoding to quantify relationships between biomass, mitochondrial copy number, and metabarcoding reads. Mitochondrial DNA copy numbers per biomass varied strongly within and among the different taxa. Metabarcoding reads did not reflect input mitochondrial DNA copies without a correction. Attempts to correct for amplification bias via PCR cycle calibration failed as read proportions remained stable across cycles. We therefore mathematically derived an approach to estimate relative amplification bias and initial mitochondrial DNA copy numbers in a sample based on a non-exponential amplification bias model and demonstrate its applicability. Still, the detected high variation in mitochondrial copy numbers and derived prerequisites necessary to calculate amplification efficiencies and mitochondrial copy numbers limit the practical application. Our study highlights fundamental constraints of quantitative metabarcoding and underscores the need for additional methodological approaches for quantitative insights while delivering essential conceptual insights.

molecular biology↗

bioRxiv2026

eDNA metabarcoding provides scalable and continuous biodiversity monitoring across the tree of life

Environmental DNA (eDNA) metabarcoding has the potential to substantially expand our knowledge of global biodiversity beyond that provided by conventional approaches. However, the degree to which eDNA data provides real ecological insight, rather than primarily reflecting environmental factors that affect eDNA shedding and degradation, remains unclear. Additional uncertainties arise in terms of cost-effectiveness and whether the price is worth any extra biodiversity information that is gleaned. Here, we established a high-resolution, bi-weekly eDNA time-series in Germany across aquatic and riparian habitats to quantify seasonal biodiversity dynamics, to relate eDNA to different potential environmental drivers, and to parametrize cost estimates. Over one year, eDNA metabarcoding detected more than 1,000 species across multiple trophic levels and primarily revealed real, taxon-specific seasonal patterns, in addition to some relationships to water temperature, discharge, and conductivity. Compared to historical records dating back to 1891, year-round eDNA monitoring increased reported species numbers by 2.4-fold for invertebrates, 2.2-fold for mammals, 1.7-fold for diatoms, 1.2-fold for fish and lamprey, and 1.03-fold for birds. Cumulative biodiversity estimates increased strongly with sampling frequency, demonstrating the value of eDNA for high-frequency time-series monitoring. Moreover, eDNA monitoring was highly cost-effective, providing more than twice the biodiversity information of many conventional surveys for one-sixth the cost, enabling scalable, high-resolution freshwater biodiversity assessments.

ecology↗

bioRxiv2025

Unraveling long-term trends and drivers of fish biodiversity change using environmental DNA metabarcoding of archived samples

AbstractLong-term biodiversity data are critical for assessing, understanding, and predicting ecosystem change globally, but are often limited by their availability. We present the longest eDNA metabarcoding time series for freshwater fishes based on archived suspended particulate matter (SPM) from Germanys Environmental Specimen Bank, covering 17 years (2005-2021) across six major European river systems (Rhine, Danube, Elbe, and their tributaries). From 211 annual samples collected according to highly standardized procedures at 13 sites, we detected 63 fish and lamprey species and traced their spatio-temporal trajectories. eDNA metabarcoding captured significantly declining trends at multiple sites with no recoveries. Common and sensitive species declined at nearly half of sites while invasive species spread. Site occupancy and relative read abundance trends were correlated, providing semi-quantitative indicators. Alpha and beta diversity shifted over time and Bayesian hierarchical models revealed that 19% of species showed significant declines in relative read abundance. The eDNA-derived trends showed strong concordance with long-term regulatory fish monitoring data, validating the patterns across methodological approaches. Random forest models and multivariate analyses identified multiple anthropogenic pollutants, measured from the same SPM samples, as drivers of biodiversity patterns. Pesticides, heavy metals, temperature, and fine sediment negatively affected species richness, with site-specific stressor combinations explaining 29% of community variation. Our results demonstrate that archived SPM, originally collected for chemical monitoring, provides a reliable, dual-purpose monitoring matrix integrating pollution and biodiversity trend assessments simultaneously. This approach enables holistic monitoring of global freshwater ecosystem change and can provide an early warning framework supporting evidence-based environmental management.

ecology↗

bioRxiv2025

Globally unified analysis of riverine eDNA reveals common associations of fish biodiversity with drainage characteristics

Freshwater biodiversity is declining at a pace that outstrips the capacity of existing monitoring approaches both in temporal and spatial dimensions, highlighting the urgent need for rapid and scalable assessment and attribution of biodiversity states and changes. Here, we present one of the first global assessments and unified analyses of riverine fish biodiversity using environmental DNA (eDNA) collected from 1818 sites across 113 river systems. We quantified species richness, functional redundancy, phylogenetic diversity, and genetic sequence diversity, and related them to drainage characteristics. Our results showed that eDNA effectively captured global patterns of multi-faceted riverine fish biodiversity and disentangled the roles of climate and human activities in shaping biodiversity-area relationships. Catchments in warmer climates consistently enhanced biodiversity accumulation with area, while higher human activity intensity weakened this scaling. Species richness, functional, and genetic sequence diversity exhibited stronger negative responses to human activities in larger catchments. In contrast, phylogenetic diversity showed the strongest negative effects in smaller catchments with these impacts diminishing as catchment area increased, highlighting the facet-dependent nature of biodiversity responses to environmental gradients. Our findings demonstrate the power of eDNA-based datasets for harmonized, multi-faceted biodiversity assessments, offering a scalable approach for detecting and attributing biodiversity change and informing conservation strategies under accelerating global change.

ecology↗

bioRxiv2025

Integrated reanalysis of global riverine fish eDNA datasets shows robustness and congruence of biodiversity conclusions

The analysis of environmental DNA (eDNA) has revolutionized biodiversity assessments in aquatic ecosystems, enabling non-invasive monitoring of fish communities across diverse regions. However, the global comparability of these eDNA datasets remains ambiguous due heterogeneous sampling protocols and bioinformatic workflows across studies, particularly regarding the robustness of their conclusions on biodiversity assessments. Here, we conducted a meta-analysis of 58 riverine fish eDNA metabarcoding datasets, covering 1,818 sampling sites worldwide, to evaluate the robustness of eDNA-derived biodiversity patterns. We found that species richness estimates and metrics of community structure derived under a common bioinformatic workflow were overall consistent with those of original analyses, despite the relatively high variability in bioinformatic analyses in the respective original studies. Contrastingly, congruence of species identity varied more extensively across datasets, mostly reflecting different completeness and regional relevance of reference databases. Restricting taxonomic assignment to basin-specific species pools improved species identification accuracy, while datasets lacking publicly accessible or well-curated reference data were more prone to mismatches. Year of sampling had a positive effect on taxonomic congruence, such that more recent studies showed increased robustness, also reflecting improved reference database coverage and enhanced species-level identification over time and overall method congruence in more recent years. Overall, the suitability and potential of eDNA for global biodiversity monitoring is corroborating overall robust biodiversity estimates, irrespective of the bioinformatic approaches. Our study underlines the effectiveness and need of further harmonization of bioinformatic workflows and strengthened region-specific reference databases for improved taxonomic resolution and comparability across studies.

ecology↗

bioRxiv2025

Environmental DNA metabarcoding of invertebrate-incubated water supports WFD-compliant and animal-friendly bioassessment with added trait insights

Environmental (eDNA) metabarcoding is recently being considered for bioassessment under the Water Framework Directive (WFD). While tissue-based ("bulk") metabarcoding of macroinvertebrates produces comparable ecological status class values to morphology-based methods, eDNA-based metabarcoding often includes DNA signals from upstream sites, limiting its site-specificity. A promising alternative involves the incubation of locally collected invertebrates in water, followed by eDNA metabarcoding of the incubated water. In this study, we tested the suitability of two different approaches of the incubation strategy for ecological status assessment under the WFD. The first approach uses conventional multi-habitat sampling (MH) for the collection of the local macroinvertebrates and the second natural substrate exposures (NSEs) that are actively colonised. Using metabarcoding of the incubated water from both approaches (MH/NSE eDNA), we compared community composition, trait diversity and the derived ecological status classes (ESCs) to the local signal reference (MH/NSE bulk DNA) and the regional signal reference (stream water eDNA). For both approaches, community and trait composition were highly congruent between the incubated water and bulk samples. Trait composition did not differ between MH and NSE samples or among NSE types (wood-leaf vs. gravel). However, we detected small-scale spatial differences in the trait composition between NSEs placed at different flow regimes (pool vs. riffle). ESCs derived from all approaches (MH/NSE incubated water eDNA, MH/NSE bulk DNA and stream water eDNA) were highly similar and consistent with those from morpho-taxonomic assessments. Our findings support the incubation strategy using the conventional MH sampling as the most suitable approach for a minimally invasive, site-specific stream bioassessment within the context of the WFD.

ecology↗

bioRxiv2025

Comparative Analysis of De Novo Assemblers and Quantification Software for RNA-sequencing Data in Non-Model Arthropods

BackgroundRNA-sequencing has greatly improved our understanding of the transcriptomic regulation of fundamental biological processes. Although the method has matured significantly within the last decade, bioinformatic processing of the resulting high-dimensional data sets is still challenging and the performance of algorithms can vary between data sets. As a consequence, for most non-model organisms, in particular arthropods, there is no or limited literature evidence which software is best suited to handle taxon-specific data characteristics. Therefore, we evaluated the performance of different de nonvo transcriptome assembler (Trinity, rnaSPAdes, IDBA-tran) and transcript quantification software (RSEM, Salmon) on transcriptomic data of a non-model insect and freshwater crustacean species, as well as the impact of different quality trimming strategies on the downstream bioinformatic processing results. ResultsWhile the trimming strategy had no considerable effect on the quality of transcriptome assemblies, the choice of the assembler had a substantial impact. IDBA-tran was less sensitive than the two other assemblers and produced the most fragmented transcriptome assemblies. The low remapping rates of reads against IDBA-tran assemblies further suggest that the input read data was not effectively leveraged by this algorithm. In contrast, Trinity and rnaSPAdes both generated comprehensive and contiguous de novo transcriptome assemblies, although Trinity appeared to be slightly more sensitive. This increased sensitivity, however, was associated with a higher redundancy in Trinity-generated assemblies compared to assemblies produced with rnaSPAdes. When the quality of the transcriptome assembly was high, RSEM and Salmon were able to identify the origin of at least 90% of the read data in the reference. Despite their different underlying quantification approaches, the estimated transcript counts of both tools were highly correlated and their expression signal was consistent. Notably, the alignment-free quantification algorithm Salmon was substantially faster than the alignment-based approach of RSEM. Furthermore, it was also slightly more sensitive, increasing the average re-mapping rate to [~]98%. ConclusionSince the performance of bioinformatic algorithms, especially of de novo assemblers, varies for different RNA-sequencing data sets, establishing an appropriate analysis workflow remains an important task. Our results show that the better performing combinations of algorithms produce congruent count data sets with consistent expression signal, highlighting the robustness of RNA-sequencing data analysis software.

bioinformatics↗

bioRxiv2024

Multiple stressors in river networks: local and downstream effects on freshwater macroinvertebrates

River networks are complex ecosystems characterized by a continuous exchange of material and energy through longitudinal gradients. These ecosystems are threatened by various human-induced stressors, which frequently co-occur and may interact in complex ways, potentially triggering cascading effects in the river network. Aiming at assessing single and combined effects of flow intermittency and light pollution on macroinvertebrate communities, we performed a multiple stressors experiment in 18 flow-through mesocosms. Each mesocosm was designed to mimic a simplified river network, with two upstream tributaries merging downstream, to assess both local and cascading effects. The experiment was performed in Summer 2021 for seven weeks (26 days of colonization, 23 days of treatment), applying the stressors either separately or combined in the upstream sections, in a randomized block design. Flow intermittency was simulated as the ponded phase of the drying process, whereas light pollution was applied with LED strips (set at 10 lux) that automatically turned on at sunset and off at sunrise. Drifting macroinvertebrates were sampled weekly during the treatment phase, and benthic macroinvertebrates at the end of the treatment phase. Both stressors individually applied had negative effects on the benthos, whereas drift decreased with flow intermittency and increased with light pollution. When combined upstream, stressors showed dominant effects of flow intermittency on the benthos and interactive effects on the drift. The effects of the single stressors and their interactions propagated along the river network, with stronger downstream effects when stressors co-occurred upstream. These findings showed that the spatial distribution of multiple stressors along the river network can affect their resultant downstream effects, highlighting the importance of framing multiple stressors research in a spatial context. Considering the pressing needs of the growing human population, our results represent a step forward in anticipating cumulative stressors effects, informing efficient conservation strategies for protecting freshwater ecosystems.

ecology↗

bioRxiv2024

Fish predation induces drifting and emergence in an experimental stream mesocosm system

Predator-prey interactions are important drivers of adaptation in aquatic communities, shaping the behaviour of invertebrates with cascading effects on community dynamics. Behavioural responses, such as moving with the downstream current (drift) or altering the timing of emergence, can be initiated and reduces the risk of encountering predators. This study aimed to examine the effects of indirect and direct predation pressure on drift behaviour and emergence patterns of aquatic invertebrates. Using an experimental mesocosm setup (ExStream), we analysed how the number of drifting and emerging invertebrates changed with elevated levels of chemical cues from fish (indirect predation, Gasterosteus aculeatus and Cottus rhenanus) and subsequent additional direct predation by Cottus rhenanus over a 9-day period. Our findings show that most of the analysed invertebrate groups displayed noticeable responses to either indirect, direct, or both forms of predation. Furthermore, our study revealed a significant impact of predation on emergence patterns, reducing the number and the size of emergent invertebrates. Given the importance of drift and emergence in dispersion and in facilitating resource flows into terrestrial systems, our findings indicate a strong effect of predation on the communities.

ecology↗

bioRxiv2024

Salinisation and warming disrupt predator-induced drift behaviour in aquatic predator-prey interactions

Predators act as a major selective force impacting biological communities in riverine ecosystems. Often predation risk is mediated by chemical cues upon which prey species display distinct morphological or behavioural defences. For stream invertebrates, predator-induced behaviours can be drifting and hiding. However, anthropogenic stressors increasingly impact freshwater ecosystems, with predicted consequences on the chemical information transfer, potentially affecting anti-predator behaviour. Despite this, knowledge and research on the extent to which these stressors may affect evolved predator-induced behaviour and subsequent ecosystems is scarce. Therefore, we conducted an outdoor mesocosm experiment (ExStream system) at a lowland stream in Germany, in which we investigated the effects of direct and indirect fish predation on invertebrate communities under different stressor conditions. As stressors, we tested elevated salinity (ambient vs + 136 mg/L NaCl), elevated temperature (ambient vs. + 3.4{degrees}C), and the combination of both. Our findings reveal distinct predator-induced drift behaviour, characterised by a greater number of drifting invertebrates and a concurrent reduction in overall invertebrate numbers in the communities. Increased salinity and temperature hampered the predator-induced drift behaviour. Our results support the possibility that stressors negatively impact the preys ability to perceive predators presence and respond appropriately. This disruption may alter predator-prey relationships, thereby affecting communities and potentially ecosystem functions. Highlights[vrecto] We hypothesised that anthropogenic stressors disrupt predator-induced behaviours in invertebrate prey species. [vrecto]Predator-induced drift behaviour was experimentally studied under ambient and elevated salinity and temperature conditions. [vrecto]Fish exposure elicited predator-induced drift behaviour, which decreased the number of invertebrate individuals of the communities. [vrecto]Elevated salt and elevated temperatures alone and in combination did not induce drift behaviour. [vrecto]We found that both stressors disrupted predator-induced drift behaviour, altering the anti-predator response of invertebrate prey. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/601583v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1eef03borg.highwire.dtl.DTLVardef@1ddda7corg.highwire.dtl.DTLVardef@332bdaorg.highwire.dtl.DTLVardef@1842dbb_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2024

Complex compositional and cellular response of river sediment microbiomes to multiple anthropogenic stressors

Rivers face constant anthropogenic stressors, resulting in significant changes in microbial community composition. What remains unclear is whether these changes render the microbiome better adapted to the stressed environment. Here, by subjecting 64 river-connected mesocosms to multiple stressors, we show that sediment microbiomes of small lowland rivers are highly sensitive to lowered flow velocity resulting in substantially altered community compositions not fully capable of compensating for the stressor effect within two weeks albeit having stable functions encoded in metagenomes. Transcriptomics revealed a systematic heat shock response in the community and a highly active, previously unknown anaerobic key stone species with great metabolic versatility. Increases in temperature (+3.5 {degrees}C) or salinity (+0.5 mS/cm) were outcompeted by lowered flow and elicited only minor responses at community or transcriptomic level with, e.g., upregulation of the photosystem of chloroplasts. Following a two-week recovery period, transcriptomic stress responses vanished completely compared to control mesocosms, exemplifying the river microbiomes resilience. We conclude that, given the complex community responses at both the cellular and compositional level, maintaining natural river flow is vital to preventing energy loss and reduced microbiome activity in river sediments.

ecology↗

bioRxiv2023

German-wide Malaise trap metabarcoding estimates over 33,000 insect species

Mitigating ongoing losses of insects and their key functions (e.g., pollination) requires accurately tracking large-scale and long-term community changes. However, doing so has been notoriously hindered by uniquely high insect species diversity that requires prohibitively high investments of time, funding, and taxonomic expertise. Here, we show that these concerns can be addressed through a comprehensive, scalable and cost-efficient DNA metabarcoding workflow. We use 1,815 samples from 75 Malaise traps across Germany from 2019 and 2020 to demonstrate how metabarcoding can be incorporated into large-scale insect monitoring networks for less than 50 {euro} per sample, including supplies, labor and maintenance. With on average 1.4M sequence reads per sample we uncovered 10,803 validated insect species, of which 83.9% were represented by a single OTU. We estimated another 21,403 plausible species, which likely either lack a reference barcode or are undescribed. The total of 31,846 species is similar to the number of insect species known for Germany ([~]35,500). Because Malaise traps capture only a subset of insects, our approach identified many species likely unknown from Germany or new to science. Our reproducible workflow ([~]80% OTU-similarity among years) provides a blueprint for large-scale biodiversity monitoring of insects and other biodiversity components in near real time.

ecology↗

bioRxiv2022

Predicting environmental stressor levels with machine learning: a comparison between amplicon sequencing, metagenomics, and total RNA sequencing based on taxonomically assigned data

BackgroundMicrobes are increasingly (re)considered for environmental assessments because they are powerful indicators for the health of ecosystems. The complexity of microbial communities necessitates powerful novel tools to derive conclusions for environmental decision-makers, and machine learning is a promising option in that context. While amplicon sequencing is typically applied to assess microbial communities, metagenomics and total RNA sequencing (herein summarized as omics-based methods) can provide a more holistic picture of microbial biodiversity at sufficient sequencing depths. Despite this advantage, amplicon sequencing and omics-based methods have not yet been compared for taxonomy-based environmental assessments with machine learning. In this study, we applied 16S and ITS-2 sequencing, metagenomics, and total RNA sequencing to samples from a stream mesocosm experiment that investigated the impacts of two aquatic stressors, insecticide and increased fine sediment deposition, on stream biodiversity. We processed the data using similarity clustering and denoising (only applicable to amplicon sequencing) as well as multiple taxonomic levels, data types, feature selection, and machine learning algorithms and evaluated the stressor prediction performance of each generated model for a total of 1,536 evaluated combinations of taxonomic datasets and data-processing methods. ResultsSequencing and data-processing methods had a substantial impact on stressor prediction. While omics-based methods detected much more taxa than amplicon sequencing, 16S sequencing outperformed all other sequencing methods in terms of stressor prediction based on the Matthews Correlation Coefficient. However, even the highest observed performance for 16S sequencing was still only moderate. Omics-based methods performed poorly overall, but this was likely due to insufficient sequencing depth. Data types had no impact on performance while feature selection significantly improved performance for omics-based methods but not for amplicon sequencing. ConclusionAmplicon sequencing might be a better candidate for machine-learning-based environmental stressor prediction than omics-based methods, but the latter require further research at higher sequencing depths to confirm this conclusion. More sampling could improve stressor prediction performance, and while this was not possible in the context of our study, thousands of sampling sites are monitored for routine environmental assessments, providing an ideal framework to further refine the approach for possible implementation in environmental diagnostics.

genomics↗

bioRxiv2022

It`s raining species: Rainwash eDNA metabarcoding as a minimally invasive method to assess tree canopy invertebrate diversity

O_LIForest canopies are a highly diverse ecosystem, but despite several decades of intense research, there remain substantial gaps in our knowledge of their biodiversity and ecological interactions. One fundamental challenge in canopy research is the limited accessibility of the ecosystem. Consequently, previous studies have relied on the application of either highly invasive methods such as chemical knockdown, or on time-consuming and expensive setups such as canopy walkways or cranes. Therefore, time- and cost-efficient, ideally minimally invasive yet comprehensive applications are required to help close this knowledge gap. High-throughput metabarcoding of environmental DNA (eDNA) collected from water, soil, or air provides a minimally invasive method for biodiversity assessment, yet its potential for canopy biodiversity monitoring has not been explored. C_LIO_LIHerein, we conducted metabarcoding of eDNA washed off the canopy via rainwater to explore its monitoring potential. We placed four 1 m2 rain samplers beneath the canopies of four different tree taxa prior to a major rain event, filtered eDNA from the collected rainwater, and performed cytochrome c oxidase subunit I (COI) metabarcoding to profile the invertebrate community. Additionally, we collected and identified all specimens present in the rainwater for verification. C_LIO_LIWe detected 50 invertebrate species by eDNA metabarcoding, of which 43 were not physically present in the water sample, thus likely representing true canopy biodiversity signals. Furthermore, we observed distinct species occurrence patterns corresponding to the four tree taxa, suggesting that ecological patterns such as host specificity can be assessed using the method. C_LIO_LIIn conclusion, our study provides a proof of principle that rainwash eDNA metabarcoding offers a minimally invasive and comprehensive method for tree canopy diversity monitoring. C_LI

molecular biology↗

bioRxiv2021

Fresh insights into Mediterranean biodiversity: Environmental DNA reveals spatio-temporal patterns of stream invertebrate communities on Sicily

The Mediterranean region with its islands is among top biodiversity hotspots. It houses numerous freshwater taxa with a high rate of endemism, but is heavily impacted by anthropogenic pressures and global climate change. To conserve biodiversity, reliable data on species and genetic diversity are needed especially for the scarcely known insular freshwater ecosystems. Environmental DNA metabarcoding provide a straight-forward opportunity to assess aquatic biodiversity. Therefore, we conducted the first eDNA metabarcoding study in one stream catchment on Sicily. Specifically, we aimed to i) investigate spatial diversity patterns of macroinvertebrate communities, ii) assess seasonal changes, and iii) check if dispersal barriers can be identified. Water samples were taken at 27 different sites in two seasons and eDNA metabarcoding performed using the COI gene. In total, we detected 98 macroinvertebrate species, including 28 taxa potentially new to Sicily. Exact sequence variant (ESV) and species composition data showed that diversity differed between seasons with less taxa detected in winter. We also detected a dispersal barrier, which had a stronger effect in autumn. Our findings show that eDNA metabarcoding provides valuable information on Sicilian freshwater biodiversity. We therefore encourage its application for understudied regions to better understand the state and dynamics of freshwater biodiversity.

ecology↗

bioRxiv2021

Beyond fish eDNA metabarcoding: Field replicates disproportionately improve the detection of stream associated vertebrate species

Fast, reliable, and comprehensive biodiversity monitoring data are needed for environmental decision making and management. Recent work on fish environmental DNA (eDNA) metabarcoding shows that aquatic diversity can be captured fast, reliably, and non-invasively at moderate costs. Because water in a catchment flows to the lowest point in the landscape, often a stream, it can often collect traces of terrestrial species via surface or subsurface runoff along its way or when specimens come into direct contact with water (e.g., for drinking purposes). Thus, fish eDNA metabarcoding data can provide information on fish but also on other vertebrate species that live in riparian habitats. This additional data may offer a much more comprehensive approach for assessing vertebrate diversity at no additional costs. Studies on how the sampling strategy affects species detection especially of stream-associated communities, however, are scarce. We therefore performed an analysis on the effects of biological replication on both fish as well as (semi-)terrestrial species detection. Along a 2 km stretch of the river Mulde (Germany), we collected 18 1-L water samples and analyzed the relation of detected species richness and quantity of biological replicates taken. We detected 58 vertebrate species, of which 25 were fish and lamprey, 18 mammals, and 15 birds, which account for 50%, 24%, and 7% of all native species to the German federal state of Saxony-Anhalt. However, while increasing the number of biological replicates resulted in only 25% more detected fish and lamprey species, mammal, and bird species richness increased disproportionately by 69% and 84%, respectively. Contrary, PCR replicates showed little stochasticity. We thus emphasize to increase the number of biological replicates when the aim is to improve general species detections. This holds especially true, when the focus is on rare aquatic taxa or on (semi-)terrestrial species, the so-called bycatch. As a clear advantage, this information can be obtained without any additional sampling or laboratory effort when the sampling strategy is chosen carefully. With the increased use of eDNA metabarcoding as part of national fish bioassessment and monitoring programs, the complimentary information provided on bycatch can be used for biodiversity monitoring and conservation on a much broader scale.

molecular biology↗

bioRxiv2020

Small in-stream barriers contribute little to strong local population genetic structure in five hololimnic macroinvertebrate taxa

Water flow in river networks is frequently regulated by man-made in-stream barriers. These obstacles can hinder dispersal of aquatic organisms and isolate populations leading to the loss of genetic diversity. Although millions of small in-stream barriers exist worldwide, such as weirs below 2 m or tunnels and pipes, their impact on the dispersal of macroinvertebrates with strictly aquatic life cycles is unclear. We therefore assessed the effects of such barriers on the population structure and effective dispersal of five macroinvertebrate species with strictly aquatic life cycles: the amphipod crustacean Gammarus fossarum (clade 11), three snail species of the Ancylus fluviatilis species complex and the flatworm Dugesia gonocephala. We studied populations at nine weirs and eight culverts (3 pipes, 5 tunnels), built 33-109 years ago, in the heavily fragmented catchment of the river Ruhr (Sauerland, Germany). To assess fragmentation and barrier effects, we generated genome-wide SNP data using ddRAD sequencing and evaluated clustering, differentiation between populations up- and downstream of each barrier and effective migration rates among sites and across barriers. Additionally, we applied population genomic simulations to assess expected differentiation patterns under different gene flow scenarios. Our data show that populations of all species are highly isolated at regional and local scales within few kilometres. While the regional population structure likely results from historical processes, the strong local differentiation suggests that contemporary dispersal barriers exist. However, we identified significant barrier effects only for pipes (for A. fluviatilis II and III) and few larger weirs (>1.3 m; for D. gonocephala). Therefore our data suggest that most small in-stream barriers can probably be overcome by all studied taxa frequently enough to prevent fragmentation. Thus, the barriers leading to population isolation after few kilometres still need to be identified. Specifically, it remains to be tested if the strong local differentiation is a result of a cumulative effect of small barriers, or if e.g. larger in-stream barriers, land use, chemical pollution, urbanisation, or a combination of these factors impede gene flow.

ecology↗