Biology subjects

Hajibabaei, M.

Publications and source records attributed to Hajibabaei, M..

At least 19 recordsLinked to original sources

bioRxiv2025

Fine-scale ecological biomonitoring in a large, complex agriculturally impacted watershed via eDNA metabarcoding

DNA-based approaches utilizing high-throughput sequencing (HTS) (e.g. DNA metabarcoding) have revolutionized ecological biomonitoring by providing higher sample throughput, greater reproducibility, and better cost-benefits compared to traditional morphology-based bioassessment studies. Here, we utilized DNA metabarcoding in a watershed in Ontario (Canada) dominated by agricultural land uses. Our aim is to understand patterns of biodiversity in benthic taxa from data generated and inferred at various taxonomic scales and to compare these findings with over a decade of traditional morphological data. We sampled 18 watercourses during summer and fall 2023, spanning a forested-to-agricultural land-use gradient. We found significant differences between metabarcoding and historical morphology data where DNA provided more richness values at both the species (p = 2x10-5) and order (p = 0.008) levels. Whereas the morphology dataset contained many unresolved taxa, DNA metabarcoding captured a broader taxonomic breadth with diverse genetic profiles among taxa. Non-metric multidimensional scaling (NMDS) analyses on DNA metabarcoding data produced tighter clusters, more precise separation by land use, and greater consistency across taxonomic scales. Both urban context and land use had significant associations with metabarcoding patterns observed, with differences being strongest between agriculturally-dominated and primarily forested sites (median R{superscript 2} {approx} 0.08-0.11). We also found strong, consistent environmental signals linked to agricultural settings, such as water conductivity and turbidity, and pH. Altogether, our DNA-based results demonstrate the differences in community composition among different land uses in this watershed. Importantly, our work highlights the need for more taxonomic resolution (obtained through DNA analysis) to decipher community changes linked to anthropogenic and environmental drivers, as morphological data alone may lack the precision needed to capture these patterns.

ecology↗

bioRxiv2025

eDNA metabarcoding and whole genome sequencing detect European-American Eel hybrids in northeastern Canada

American and European Eels (Anguilla rostrata and Anguilla anguilla, respectively) are sister species of conservation concern, as they have declined in abundance in recent decades. Although there is evidence of gene flow between the two species, most previous hybrid detections have been found in Iceland. Here we expand upon existing reports of interspecific hybrids using a combination of an environmental DNA (eDNA) survey and whole genome sequencing of 347 eels from Newfoundland and Labrador. Metabarcoding of eDNA samples at multiple loci detected the presence of European Eel mitochondrial DNA (mtDNA) at eight locations primarily along the south coast of Newfoundland. Genome sequencing of eels collected in the region revealed three hybrid individuals with levels of European admixture consistent with one first generation hybrid and two North American backcrosses, all with European mtDNA. This work supports the presence of a previously unknown, seemingly localized region of hybrid occurrence in southern Newfoundland and expands our understanding of the relationship between these species across the North Atlantic.

genomics↗

bioRxiv2023

NAMERS: a purpose-built reference DNA sequence database to support applied eDNA metabarcoding

Applied eDNA metabarcoding is increasingly being used to generate actionable results to inform management decisions, regulations, or policy development. Because of these important downstream considerations, optimizing workflow elements is now essential to increasing standardization, efficiency, and confidence of metabarcoding results. Reference DNA sequences are critical workflow elements that currently lack consistent approaches to generating, curating, or publishing. Here we present a complete (mitochondrial genome and nuclear ribosomal DNA cistron) and high quality reference DNA sequence library for the freshwater fishes of British Columbia, Canada. This resource is published as the Novel Applied eDNA Metabarcoding Reference Sequences (NAMERS) repository (https://namers.ca), a user-friendly and interactive website for specialists and non-specialists alike to explore and generate custom reference libraries for taxa and genes of interest. We demonstrate the power of NAMERS to optimize applied eDNA metabarcoding workflows at the study design stage by analyzing the number of primer mismatches and resolution power of existing metabarcoding markers. To meet the increasing demand for actionable eDNA metabarcoding applications, NAMERS demonstrates that high quality curated genomic information is within a reasonable reach. It is timely to establish this framework as the new gold standard and coordinate our efforts to generate this type of reference data at scale.

genetics↗

bioRxiv2022

Multi-marker DNA metabarcoding detects suites of environmental gradients from an urban harbour

There is increasing need for biodiversity monitoring, especially in places where potential anthropogenic disturbance may significantly impact ecosystem health. We employed a combination of traditional morphological and bulk macroinvertebrate metabarcoding analyses to benthic samples collected from Toronto Harbour (Ontario, Canada) to compare taxonomic and functional diversity of macroinvertebrates and their responses to environmental gradients. At the species rank, sites assessed using COI metabarcoding showed more variation than sites assessed using morphological methods. Depending on the assessment method, we detected gradients in magnesium (morphological taxa), ammonia (morphological taxa, COI sequence variants), pH (18S sequence variants) as well as gradients in contaminants such as metals (COI & 18S sequence variants) and organochlorines (COI sequence variants). Observed responses to contaminants such as aromatic hydrocarbons and metals align with known patchy distributions in harbour sediments. We determined that the morphological approach may limit the detection of macroinvertebrate responses to lake environmental conditions due to the effort needed to obtain fine level taxonomic assignments necessary to investigate responses. DNA metabarcoding, however, need not be limited to macroinvertebrates, can be automated, and taxonomic assignments are associated with a certain level of accuracy from sequence variants to named taxonomic groups. The capacity to detect change using a scalable approach such as metabarcoding is critical for addressing challenges associated with biodiversity monitoring and ecological investigations.

genomics↗

bioRxiv2022

Decision Tree Ensembles Utilizing Multivariate Splits Are Effective at Investigating Beta-Diversity in Medically Relevant 16S Amplicon Sequencing Data

Developing an understanding of how microbial communities vary across conditions is an important analytical step. We used 16S rRNA data isolated from human stool to investigate if learned dissimilarities, such as those produced using unsupervised decision tree ensembles, can be used to improve the analysis of the composition of bacterial communities in patients suffering from Crohns Disease and adenomas/colorectal cancers. We also introduce a workflow capable of learning dissimilarities, projecting them into a lower dimensional space, and identifying features that impact the location of samples in the projections. For example, when used with the centered log-ratio transformation, our new workflow (TreeOrdination) could identify differences in the microbial communities of Crohns Disease patients and healthy controls. Further investigation of our models elucidated the global impact ASVs had on the location of samples in the projected space and how each ASV impacted individual samples in this space. Furthermore, this approach can be used to integrate patient data easily into the model and results in models that generalize well to unseen data. Models employing multivariate splits can improve the analysis of complex high-throughput sequencing datasets since they are better able to learn about the underlying structure of the dataset. Author SummaryThere is an ever-increasing level of interest in accurately modeling and understanding the role that commensal organisms play in human health and disease. We show that learned representations can be used to create informative ordinations. We also demonstrate that the application of modern model introspection algorithms can be used to investigate and quantify the impact of taxa in these ordinations and that the taxa identified by these approaches have been associated with immune-mediated inflammatory diseases and colorectal cancer.

bioinformatics↗

bioRxiv2022

Fungal community dynamics and carbon mineralization in coarse woody debris across decay stage, tree species, and stand development stage in northern boreal forests

Fungi are primary agents of coarse woody debris (CWD) decay in forests, playing an essential role in nutrient cycling and carbon storage. Characterizing fungal communities within CWD will promote further understanding of the fungal controls on CWD decomposition. We compared fungal community assemblages using alpha and beta diversity metrics, carbon mineralization, and physical and chemical properties of CWD across 3 tree species (trembling aspen [Populus tremuloides], black spruce [Picea mariana], and jack pine [Pinus banksiana]), 5 decay classes, and 2 stand development stages, differing in time-since-stand replacing disturbance (i.e., young/self-thinning and mature/steady-state) in Ontarios boreal forest region. In total, we sampled 180 individual CWD logs from 6 independent stands, with 3 replicates per each species x decay class combination at each site. We found that fungal community structure significantly differed across tree species, decay stage, and stand age. Higher proportions of white rot fungi were found in trembling aspen CWD, whereas higher proportions of brown rot fungi were found in black spruce and jack pine CWD. Proportions of specialized wood decay fungi increased with decay stage and were higher in CWD located in mature forest stands. Fungal diversity was highest in decay class 4 CWD. We found that Mn and K concentrations, total carbon, C/N ratio, carbon mineralization (mg CO2 g dry CWD-1 d-1), and moisture content were important predictors of fungal composition across CWD species and/or decay stage, though how CWD chemistry influences fungal species composition (and vice versa) is unknown. Carbon mineralization was highest in trembling aspen CWD and increased with decay stage, perhaps facilitated by increased N concentrations. This study suggests that forest management guidelines that consider both deadwood quantity and quality will support a broader range of fungal species and communities through post-disturbance stand development, thereby conserving biodiversity over the longer-term in our managed forest systems.

ecology↗

bioRxiv2021

Multi-marker metabarcoding resolves subtle variations in freshwater condition: Bioindicators, ecological traits, and trophic interactions

Freshwater systems are experiencing rapid biodiversity losses resulting from high rates of habitat degradation. Ecological condition is typically determined through identifying either macroinvertebrate or diatom bioindicator assemblages and comparing them to their known tolerance to stressors. These comparisons are typically conducted at family or genus levels depending on the availability of taxonomic keys and expertise for focal groups. The objective of this study was to test whether a more taxonomically comprehensive assessment of communities in benthic samples can provide a different perspective of ecological conditions. DNA metabarcoding was used to identify macroinvertebrates and diatoms from kick-net samples collected from sites with different habitat status. Sites with good condition were associated with higher beta diversity as well as slightly higher directed connectance and modularity indicating higher resilience compared with fair condition sites. Indicator value and correlation analyses used DNA metabarcoding data to detect 29 site condition indicator species consistent with known bioindicators and expected relative tolerances. DNA metabarcoding and trophic network analysis also recovered 11 keystone taxa. This study demonstrates the importance of taxonomic breadth across trophic levels for generating biotic data to study ecosystem status, with the potential to scale-up ecological assessments of freshwater condition, trophic stability, and resilience.

ecology↗

bioRxiv2021

Profile hidden Markov model sequence analysis can help remove putative pseudogenes from DNA barcoding and metabarcoding datasets

BackgroundPseudogenes are non-functional copies of protein coding genes that typically follow a different molecular evolutionary path as compared to functional genes. The inclusion of pseudogene sequences in DNA barcoding and metabarcoding analysis can lead to misleading results. None of the most widely used bioinformatic pipelines used to process marker gene (metabarcode) high throughput sequencing data specifically accounts for the presence of pseudogenes in protein-coding marker genes. The purpose of this study is to develop a method to screen for obvious pseudogenes in large COI metabarcode datasets. We do this by: 1) describing gene and pseudogene characteristics from a simulated DNA barcode dataset, 2) show the impact of two different pseudogene removal methods on mock metabarcode datasets with simulated pseudogenes, and 3) incorporate a pseudogene filtering step in a bioinformatic pipeline that can be used to process Illumina paired-end COI metabarcode sequences. Open reading frame length and sequence bit scores from hidden Markov model (HMM) profile were used to detect pseudogenes. ResultsOur simulations showed that it was more difficult to identify pseudogenes from shorter amplicon sequences such as those typically used in metabarcoding ([~]300 bp) compared with full length DNA barcodes that are used in construction of barcode libraries ([~] 650 bp). It was also more difficult to identify pseudogenes in datasets where there is a high percentage of pseudogene sequences. We show that existing bioinformatic pipelines used to process metabarcode sequences already remove some apparent pseudogenes, especially in the rare sequence removal step, but the addition of a pseudogene filtering step can remove more. ConclusionsThe combination of open reading frame length and hidden Markov model profile analysis can be used to effectively screen out obvious pseudogenes from large datasets. There is more to learn from COI pseudogenes such as their frequency in DNA barcode and metabarcoding studies, their taxonomic distribution, and evolution. Thus, we encourage the submission of verified COI pseudogenes to public databases to facilitate future studies.

bioinformatics↗

bioRxiv2020

Environmental DNA for tracking waterhole visitation in savanna ecosystems

Game parks are the last preserve of many large mammals, and in savanna ecosystems, management of surface waters poses a conservation challenge. In arid and semi-arid regions, water can be a scarce resource during dry seasons and drought. Artificial waterholes are common in parks and reserves across Africa, but can alter mammal community composition by favoring drought intolerant species, with consequences for disease dynamics, and population viability of drought-tolerant species. Analysis of waterborne environmental DNA (eDNA) is increasingly used to inform conservation of rare and invasive species, and conduct large-scale biodiversity assessments. To explore the reliability of eDNA as an indicator of mammal waterhole use in savannas, we compare eDNA metabarcoding and camera traps for documenting artificial waterhole use in the Kruger National Park, South Africa, a global hotspot for mammal diversity. We show that eDNA metabarcoding can recover the majority of mammal species detected by camera traps, including a number of endangered species, but DNA signatures of mammal visitation are temporally limited, with best performance when tracking water-dependent large bodied mammals visiting within two days of sampling. Our results highlight limitation of eDNA based monitoring in these systems, including the lack of long-term eDNA persistence in small and highly utilized waterholes, and variability in detection rates among species. However, we demonstrate that eDNA-based approaches can be used to track mammals of conservation concern, and reflect patterns of recent waterhole use and co-occurrence across water-dependent species, both of which are crucial for making evidence-based decisions regarding water management and provisioning.

ecology↗

bioRxiv2020

METAWORKS: A flexible, scalable bioinformatic pipeline for multi-marker biodiversity assessments

Multi-marker metabarcoding is increasingly being used to generate biodiversity information across different domains of life from microbes to fungi to animals such as for molecular ecology and biomonitoring applications in different sectors from academic research to regulatory agencies and industry. Current popular bioinformatic pipelines support microbial and fungal marker analysis, while ad hoc methods are often used to process animal metabarcode markers from the same study. MetaWorks provides a harmonized processing environment, pipeline, and taxonomic assignment approach for demultiplexed Illumina reads for all biota using a wide range of metabarcoding markers such as 16S, ITS, and COI. A Conda environment is provided to quickly gather most of the programs and dependencies for the pipeline. Several workflows are provided such as: taxonomically assigning exact sequence variants, provides an option to generate operational taxonomic units, and facilitates single-read processing. Pipelines are automated using Snakemake to minimize user intervention and facilitate scalability. All pipelines use the RDP classifier to provide taxonomic assignments with confidence measures. We extend the functionality of the RDP classifier for taxonomically assigning 16S (bacteria), ITS (fungi), and 28S (fungi), to also support COI (animals), rbcL (eukaryotes, land plants, diatoms), 12S (fish), 18S (eukaryotes, diatoms) and ITS (fungi, plants). MetaWorks properly handles ITS by trimming flanking conserved rRNA gene regions as well as protein coding genes by providing two options for removing obvious pseudogenes. MetaWorks is available at https://github.com/terrimporter/MetaWorks along with quick-start instructions using test data, detailed workflow descriptions, and a tutorial for new users.

bioinformatics↗

bioRxiv2020

Deconstructing biodiversity-ecosystem function relationships: Filtering of macroinvertebrate traits in a large river floodplain

The Biodiversity-Ecosystem Function hypothesis postulates that higher biodiversity is correlated with ecosystem function by providing a high number of filled niches through species response types and resource use patterns. Through their high spatio-temporal habitat diversity, floodplains are highly productive ecosystems, supporting communities that are naturally resilient and highly diverse. We examined linkages among floodplain wetland habitats, invertebrate communities and their associated traits, and ecosystem function across 60 sites within the floodplain wetlands of the lower Wolastoq | Saint John River, New Brunswick, using structural equation modelling and Threshold Indicator Taxa ANalysis (TITAN2). We identified key environmental filters of invertebrate communities, namely linking increased niche differentiation through historical change, flood pulse dynamics, and macrophyte bed complexity with increased taxa and functional diversity. Examination of traits linked to ecosystem functions revealed that healthy wetlands with higher primary productivity were associated with greater functional evenness and richness, while habitat patches with increased decomposition rates had low functional richness, reflecting highly disturbed habitat. Our results highlight key differences between wetland and riverine ecosystems, relating to how critical functions support healthy wetland habitats by providing increased resilience to disturbance, here associated with differing levels of conservation protection.

ecology↗

bioRxiv2020

Freshwater diatom biomonitoring through benthic kick-net metabarcoding

Biomonitoring is an essential tool for assessing ecological conditions and informing management strategies. The application of DNA metabarcoding and high throughput sequencing has improved data quantity and resolution for biomonitoring of taxa such as macroinvertebrates, yet, there remains the need to optimise these methods for other taxonomic groups. Diatoms have a longstanding history in freshwater biomonitoring as bioindicators of water quality status. However, periphyton scraping, a common diatom sampling practice, is time-consuming and thus costly in terms of labour. This study examined whether the benthic kick-net technique used for macroinvertebrate biomonitoring could be applied to bulk-sample diatoms for metabarcoding. To test this approach, we collected samples using both conventional microhabitat periphyton scraping and bulk-tissue kick-net methodologies in parallel from replicated sites with different habitat status (good/fair). We found there was no significant difference in community assemblages between conventional periphyton scraping and kick-net methodologies, but there was significant difference between diatom communities depending on site quality (P = 0.029). These results show the diatom taxonomic coverage achieved through DNA metabarcoding of kick-net is suitable for ecological biomonitoring applications. The shift to a more robust sampling approach and capturing diatoms and macroinvertebrates in a single sampling event has the potential to significantly improve efficiency of biomonitoring programmes.

genomics↗

bioRxiv2020

The Red Queen's Crown: an evolutionary arms race between coronaviruses and mammalian species reflected in positive selection of the ACE2 receptor among many species

The world is going through a global viral pandemic with devastating effects on human life and socioeconomic activities. This pandemic is the result of a zoonotic coronavirus, Severe Acute Respirsatory Syndrom Coronavirus 2 (SARS-CoV-2) which is believed to have originated in bats and transferred to humans possibly through an intermediate host species (Zhou et al. 2020; Coronaviridae Study Group of the International Committee on Taxonomy of Viruses 2020). The virus attacks host cells by attaching to a cell membrane surface protein receptor called ACE2 (Ge et al. 2013; Zhou et al. 2020). Given the critical role of ACE2 as a binding receptor for a number of coronaviruses, we studied the molecular evolution of ACE2 in a diverse range of mammalian species. Using ACE2 as the target protein, we wanted to specifically test the Red Queen hypothesis (Dawkins and Krebs 1979) where the parasite and host engage in an evolutionary arms race which can result in positive selection of their traits associated to their fitness and survival. Our results clearly show a phylogenetically broad evolutionary response, in the form of positive selection detected at the codon-level in ACE2. We see positive selection occurring at deep branches as well as 13 incidents at the species level. We found the strongest level of positive selection in Tasmanian devil (Sarcophilus harrisii), donkey (Equus asinus), large flying fox (Pteropus vampyrus), Weddell seal (Leptonychotes weddellii), and dog (Canis lupus familiaris). At the codon-level, we found up to 10% of ACE2 codons are impacted by positive selection in the mammalian lineages studied. This phylogenetically broad evolutionary arms race can contribute to the emergence of new strains of coronaviruses in different mammalian lineages with a potential to transfer between species given the common binding receptor ACE2. Our study provides a molecular evolutionary perspective to the current pandemic and sheds light on its evolutionary mechanisms. "Nothing in biology makes sense except in the light of evolution" (Theodosius Dobzhansky)

evolutionary biology↗

bioRxiv2020

The effects of Hurricane Otto on the soil ecosystems of three forest types in the Northern Zone of Costa Rica

Hurricanes rapidly deposit large amounts of canopy material onto tropical forest floors, stimulating metabolic processes involved in the decomposition of these materials and production of N and C resources into the food web. However, little is known about the effects that hurricanes have on specific soil microbial taxa or functional groups involved in these processes. The objectives of this study were to determine how Hurricane Otto influenced three different tropical forest soil ecosystems within the first 8 months after causing damage to a tropical forest by assessing the soil C and N factors and how the soil bacterial and fungal community compositions differed before and after the hurricane. Soil samples were collected from five 2000 m2 permanent plots in Lowland, Upland and Riparian forest systems within the same area in the Northern Zone of Costa Rica. Standard methods were used to measure the amounts Total N, NO3-, NH4+, Total organic C, and Biomass C, while Illumina MiSeq methods were used to generate bacterial and fungal sequences. All data were analyzed using univariate and multivariate statistical methods. Using this "before and after" study design, it was found that the levels of the inorganic N and Biomass C were greater in the Post-Hurricane soil samples. The mean proportion of DNA sequences of complex C degrading/lignin degrading, NH4+-producing, and ammonium oxidizing bacteria, and the complex C degrading/wood rot/lignin degrading and ectomycorrhizal fungi also were greater in the Post-Hurricane soils. We also provide evidence that the excessive amounts of canopy leaf litter and woody debris deposited on the forest floor during Hurricane Otto appears to be selecting for genera that become more dominant Post-Hurricane, perhaps because they may be better able to rapidly process the newly deposited C and N-rich canopy material. This is a rare "before and after" a natural hurricane design that warrants further monitoring.

microbiology↗

bioRxiv2020

The utility of a metagenomics approach for marine biomonitoring

1The isolation and analysis of environmental DNA (eDNA) for ecosystem assessment and monitoring has become increasingly popular. A majority of studies have taken a metabarcoding approach--that is, amplifying and sequencing one or more gene targets of interest. Shotgun sequencing of eDNA--also called metagenomics--while popular in microbial community analysis has not seen much adoption for the analysis of other groups of organisms. Especially in light of the existence of extremely high-capacity DNA sequencers, we decided to test the performance of a shotgun approach side-by-side with a metabarcoding approach on marine water samples obtained from offshore Newfoundland. We found that metabarcoding remains the most efficient technique, but that metagenomics also has significant power to reveal biodiversity patterns, and in fact can be treated as an independent confirmation of ecological gradients. Moreover, we show that metagenomics can also be used to infer factors related to ecosystem health and function.

ecology↗

bioRxiv2020

Propylene glycol-based antifreeze as an effective preservative for DNA metabarcoding of benthic arthropods

Maintaining the integrity of DNA in bulk environmental samples from source to laboratory is crucial for capturing the true range of taxa present within an ecosystem. Preservation consideration of DNA is particularly important if samples are being collected in remote areas and by non-specialist citizen scientists in nationwide programs. Traditionally, absolute ethanol is used as the preferred preservative for environmental samples collected for downstream DNA metabarcoding analyses. However, transport, shipping and DNA extraction of samples preserved in ethanol is a lengthy procedure due to safety restrictions and the requirement of full ethanol evaporation prior to extraction. We examined the efficacy of an easily accessible, non-toxic propylene glycol-based antifreeze as an alternative to absolute ethanol for preserving macroinvertebrate DNA from bulk-benthos DNA samples. We tested the differences in both cytochrome oxidase I (COI) exact sequence variants (ESVs) and COI taxonomic orders detected in both ethanol and antifreeze samples using two processing methods (no evaporation of preservative versus full evaporation). In addition, we assessed the detection of families and genera within the Arthropoda phylum for preservative type, site and processing method. Our results suggest that antifreeze is a suitable alternative to ethanol, a greater global ESV richness reported for antifreeze samples. Additionally, a higher proportion of arthropod reads in ESVs were detected in antifreeze (average 69%) compared with ethanol (average 53%). Finally, antifreeze samples produced similar results for the different processing methods, whereas ethanol samples failed to produce similar results without prior evaporation. Although ethanol is currently widely used for DNA preservation, our results demonstrate that by using antifreeze, it is possible to achieve similar taxonomic coverage and community assemblages of bulk-benthos DNA samples for macroinvertebrates, with the added simplicity and shorter laboratory processing time achieved using an easily available, unregulated preservative.

genomics↗

bioRxiv2019

Metabarcoding a Metacommunity: detecting change in a wetland wilderness

The complexity and natural variability of ecosystems present a challenge for reliable detection of change due to anthropogenic influences. This issue is exacerbated by necessary trade-offs that reduce the quality and resolution of survey data for assessments at large-scales. The Peace-Athabasca Delta (PAD) is a large inland wetland complex in northern Alberta, Canada. Despite its geographic isolation, the PAD is threatened by encroachment of oil sands mining in the Athabasca watershed, and hydroelectric dams in the Peace watershed. Methods capable of reliably detecting changes in ecosystem health are needed to evaluate and manage risks. Between 2011 and 2016, aquatic macroinvertebrates were sampled across a gradient of wetland flood frequency, applying both microscope-based morphological identification, and DNA metabarcoding. Using multi-species occupancy models, we demonstrate that DNA metabarcoding detected a much broader range of taxa and more taxa per sample compared to traditional morphological identification, and was essential to identifying significant responses to flood and thermal regimes. We show that family-level occupancy masks high variation among genera, and for the first time, quantify the bias of barcoding primers on the probability of detection in a natural community. Interestingly, patterns of community assembly were near random, suggesting a strong role of stochasticity in the dynamics of the metacommunity. This variability seriously compromises effective monitoring at local scales, but also reflects resilience to hydrological and thermal variability. Nevertheless, simulations showed the greater efficiency of metabarcoding, particularly at a finer taxonomic resolution, provided the statistical power needed to detect change at the landscape scale.

ecology↗

bioRxiv2019

Validating metabarcoding-based biodiversity assessments with multi-species occupancy models: a case study using coastal marine eDNA

Environmental DNA (eDNA) metabarcoding is an increasingly popular method for rapid biodiversity assessment. As with any ecological survey, false negatives can arise during sampling and, if unaccounted for, lead to biased results and potentially misdiagnosed environmental assessments. We developed a multi-scale, multi-species occupancy model for the analysis of community biodiversity data resulting from eDNA metabarcoding; this model accounts for imperfect detection and additional sources of environmental and experimental variation. We present methods for model assessment and model comparison and demonstrate how these tools improve the inferential power of eDNA metabarcoding data using a case study in a coastal, marine environment. Using occupancy models to account for factors often overlooked in the analysis of eDNA metabarcoding data will dramatically improve ecological inference, sampling design, and methodologies, empowering practitioners with an approach to wield the high-resolution biodiversity data of next-generation sequencing platforms.

ecology↗