Biology subjects

Steinke, D.

Publications and source records attributed to Steinke, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Assessment of Leaf-Litter Invertebrate Biodiversity Using High Throughput Sequencing

Leaf litter ecosystems and their fauna are largely understudied, despite their critical ecological roles. Here, we investigate challenges associated with estimating biodiversity in terrestrial leaf litter. Current methodologies for biodiversity assessment are fraught with limitations, amongst the most significant is a decline in taxonomic expertise, complicating the process of species identification and the significant costs associated with species-level morphological identifications. DNA barcoding employs the mitochondrial gene cytochrome c oxidase I (COI) to identify animal species, and DNA metabarcoding facilitates the identification of multiple species without necessitating taxonomic expertise. Recent studies indicate that environmental DNA (eDNA) may exhibit greater sensitivity compared to traditional methods. To test whether these methods work in a real-world application, we sampled leaf litter across a temperate forest/field ecotone. Leaf litter was dried, ground and processed to extract environmental DNA. We evaluated the DNA extraction protocols to test their relative efficacy. We found that the Qiagen Blood and Tissue Kit was the most effective at recovering invertebrate diversity and that there were notable differences in biodiversity between forest and field habitats. Temperature emerged as a significant factor influencing the composition of the communities observed. Our methodology is applicable across various environments for efficient biodiversity assessment and might be particularly beneficial for monitoring pests and invasive species. Our approach offers a cost-effective and timely alternative to conventional biodiversity assessment methods and underscores the significance of accurate assessment methodologies for leaf litter communities.

ecology↗

bioRxiv2024

What we can find in what's left behind: DNA metabarcoding of semi-aquatic insect exuviae

Semi-aquatic insects contribute to critical ecological functioning of freshwater habitats in both the aquatic and terrestrial phase of their life. Traditional methods of studying their emergence rely on the capture of insects as they emerge, and morphological identification with taxonomic keys. This is not only time consuming but can have large impacts on the study population, obstacles that can be removed by the use of DNA. This study investigated the potential of using exuviae collected from the water surface as DNA source. Both emergence trap samples and insect exuviae were collected from a constructed wetland and a small creek in southern Ontario. Metabarcoding provided a total of 40 samples with 254 distinct taxa from emergence traps (26 samples), and 135 from exuviae (14 samples). There were many similarities between both two sample types, especially for the rich chironomid diversity. Nonetheless, the exuviae samples were able to identify more orders containing semi-aquatic insects. Furthermore, they showed a higher level of diversity within these orders. This higher level of diversity seen in exuviae samples may be due to limitations of emergence traps, such as they only account for a small defined surface area. In contrast, exuviae are representing a much larger area and are free floating, thus collection of emerging taxa is not limited to the emerging site. We were able to show that identification of emerging aquatic insects through metabarcoding of exuviae is a useful method for the study of insect emergence.

ecology↗

bioRxiv2024

Towards a Taxonomy Machine. A Training Set of 5.6 Million Arthropod Images

The taxonomic identification of organisms from images is an active research area within the machine learning community. Current algorithms are very effective for object recognition and discrimination, but they require extensive training datasets to generate reliable assignments. This study releases 5.6 million images with representatives from 10 arthropod classes and 26 insect orders. All images were taken using a Keyence VHX-7000 Digital Microscope system with an automatic stage to permit high-resolution (4K) microphotography. Providing phenotypic data for 324,000 species derived from 48 countries, this release represents, by far, the largest dataset of standardized arthropod images. As such, this dataset is well suited for testing the efficacy of machine learning algorithms for identifying specimens to higher taxonomic categories.

bioinformatics↗

bioRxiv2024

Welcome to Hotel Hymenoptera: monitoring cavity-nesting bee and wasp distribution and their trophic interactions using community science and metabarcoding

Essential ecosystem services are provided by many interactions, including plant-pollinator, predator-prey, and host-parasitoid. These services support food and natural systems through pollination and pest control, however they are challenging to qualify, and previous observational studies may underestimate their complexity. The cavity nesting Hymenoptera are a good example showing all these three interactions and they can be monitored using trap nests. For this study, trap nests were installed at schools across Canada by community scientists to investigate cavity-nesting bee and wasp distributions and interactions. DNA metabarcoding was used to identify the occupants and their food sources. New bee and wasp distributions were found that might be the result of previous under-sampling or recent range expansions. Detailed bipartite and tripartite networks describing species interactions suggest some novel bee, wasp, and parasite associations. These results encourage further investigation into these interactions using molecular methods as detailed range maps and networks provide information to natural historians and conservationists alike.

ecology↗

bioRxiv2023

BirT: a novel primer pair for avian environmental DNA metabarcoding

Environmental DNA metabarcoding has become a widely used technique to detect animals from environmental samples and is on the brink of being implemented into routine species monitoring. Surprisingly, birds are among the taxonomic groups which until recently, received comparably little attention in eDNA research, a fact that is changing rapidly, with the growing number of air eDNA analyses. Since birds are hardly ever the most abundant species in aquatic or terrestrial habitats, a high specificity of the employed metabarcoding primers is key to limit non-target amplifications and enable reliable detection from environmental samples. Here, we present a novel primer pair (BirT) for metabarcoding of avian environmental DNA. We optimized specificity and fragment length regarding taxonomic resolution and available sequencing technology. Additionally, we evaluated the availability of 12S reference sequences for birds and filled database gaps by generating novel 12S barcodes. Finally, we tested the applicability of this approach using field-collected eDNA samples obtained with three different filter types. These results were compared to visual observations uploaded to eBird (www.eBird.org) during the sampling period. Our results confirm the suitability of the BirT primer pair for bird eDNA metabarcoding with optimized fragment length, no amplification of key non-target groups, and taxonomic resolution provided by the amplified fragment. Albeit there are still substantial gaps in the 12S reference sequence database, the analysis of bird eDNA from water samples resulted in species-level taxonomic resolution for 92% of the detected taxa. All tested filter/filtration combinations delivered similar results for total read numbers per sample (mean: 613,972 {+/-} 340,088 SD) and species detected per sample (mean: 5.5 {+/-} 2.3 SD). Ninety-five percent of the bird detections were highly plausible and 58% confirmed by visual observations. The majority of the detected bird species was closely associated with aquatic habitats confirming the suitability of water samples for the detection of waterfowl and species inhabiting similar ecological niches via eDNA.

molecular biology↗

bioRxiv2023

Unravelling bird nest arthropod community structure using metabarcoding

Bird nests are fascinating microcosms harboring a wide range of arthropods parasitizing the nesting birds or feeding on prey remains, feces, and the nest material. Studies of these communities have been entirely based on emergence traps which collect live organisms out of the nests. The analysis of nest contents and environmental DNA (eDNA) via metabarcoding could expand our knowledge and identify prey, exuviae, and other animal remains in bird nests. Here, we investigated the potential of arthropod remains, nest dust, and feathers to better describe taxonomic diversity accumulated in 20 bird nests collected in Guelph (Canada). We used subsampling strategies and tested two extraction approaches to investigate the distribution of DNA in nests, account for low-quality DNA, and the presence of inhibitory substances. In total, 103 taxa were detected via metabarcoding. Arthropod remains delivered the highest number of taxa (n=67), followed by nest dust (n=29). Extractions with the PowerSoil kit outperformed DNeasy extractions coupled with PowerClean Pro inhibitor removal. The subsamples of the same nest showed 5.5% and 47.1% taxonomic overlap for arthropod remains and PowerSoil extracted nest dust, respectively, indicating a heterogeneous eDNA distribution in nests. Most detected species were either feeding in the nest, i.e., herbivorous / predatory, or bird food. We also detected molecular traces of 25 bird species, whose feathers were likely used as nest material. Consequently, the metabarcoding of bird nest materials provides a more complete picture of nest communities, which can enable future studies on functional diversity and better comparisons between nesting species.

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

Reconstruction of Small Subunit Ribosomal RNA from High-Throughput Sequencing Data: A Comparative Study of Metagenomics and Total RNA Sequencing

The small subunit (SSU) ribosomal RNA (rRNA) is the most commonly used marker for the identification of microbial taxa, but its full-length reconstruction from high-throughput sequencing (HTS) data remains challenging, especially for complex and diverse environmental samples. Metagenomics and total RNA sequencing (total RNA-Seq) are target-PCR-free HTS methods that are used to characterize microbial communities and simultaneously reconstruct SSU rRNA sequences. However, more testing is required to determine and improve their effectiveness. In this study, we processed metagenomics and total RNA-Seq data retrieved from a commercially available mock microbial community using 112 combinations of commonly used data-processing tools, determined SSU rRNA reconstruction completeness of both sequencing methods for each species in the mock community, and analyzed the impact of data-processing tools on SSU rRNA and genome completeness. Total RNA-Seq allowed for the complete or near-complete reconstruction of all mock community SSU rRNA sequences and outperformed metagenomics. SSU rRNA completeness of metagenomics strongly correlated with the genome size of mock community species. The impact of data-processing tools was overall low, although certain tools resulted in significantly lower SSU rRNA completeness. These results are promising for the high-throughput reconstruction of novel full-length SSU rRNA sequences and could advance the simultaneous application of multiple -omics approaches in routine environmental assessments to allow for more holistic assessments of ecosystems.

genomics↗

bioRxiv2022

Metagenomics vs. total RNA sequencing: most accurate data-processing tools, microbial identification accuracy, and implications for freshwater assessments

Metagenomics and total RNA sequencing (total RNA-Seq) have the potential to improve the taxonomic identification of diverse microbial communities, which could allow for the incorporation of microbes into routine freshwater assessments. However, these targeted-PCR- free techniques require more testing and optimization. In this study, we processed metagenomics and total RNA-Seq data from a commercially available microbial mock community using 768 data-processing workflows, identified the most accurate data-processing tools, and compared their microbial identification accuracy at equal and increasing sequencing depths. The accuracy of data-processing tools substantially varied among replicates. Total RNA-Seq was more accurate than metagenomics at equal sequencing depths and even at sequencing depths almost one order of magnitude lower than those of metagenomics. We show that while data-processing tools require further exploration, total RNA-Seq might be a favorable alternative to metagenomics for targeted-PCR-free taxonomic identifications of microbial communities and might enable a substantial reduction in sequencing costs while maintaining accuracy. This could be particularly an advantage for routine freshwater assessments, which require cost-effective yet accurate methods, and might allow for the incorporation of microbes into freshwater assessments.

genomics↗

bioRxiv2021

Message in a Bottle, Metabarcoding Enables Biodiversity Comparisons Across Ecoregions

BackgroundTraditional biomonitoring approaches have delivered a basic understanding of biodiversity, but they cannot support the large-scale assessments required to manage and protect entire ecosystems. This study employed DNA metabarcoding to assess spatial and temporal variation in species richness and diversity in arthropod communities from 52 protected areas spanning three Canadian ecoregions. ResultsThis study revealed the presence of 26,263 arthropod species in the three ecoregions and indicated that at least another 3,000-5,000 await detection. Results further demonstrate that communities are more similar within than between ecoregions, even after controlling for geographical distance. Overall -diversity declined from east to west, reflecting a gradient in habitat disturbance. Shifts in species composition were high at every site with turnover greater than nestedness, suggesting the presence of many transient species. ConclusionsDifferences in species composition among their arthropod communities confirm that ecoregions are a useful synoptic for biogeographic patterns and for structuring conservation efforts. The present results also demonstrate that metabarcoding enables large-scale monitoring of shifts in species composition, making it possible to move beyond the biomass measurements that have been the key metric employed in prior efforts to track change in arthropod communities.

ecology↗

bioRxiv2021

Diet composition of reintroduced Red-and-Green Macaws (Ara chloropterus) reflects gradual adaption to life in the wild

Over the last two centuries, the Red-and-green Macaw (Ara chloropterus) has become locally extinct in Argentina. In an attempt to restore its key ecosystem functions as both disperser and regulator of large-seeded plants, a reintroduction project was initiated at the Ibera National Park in northeastern Argentina. The ability of released individuals to find food is crucial, in particular when working with captive-bred animals, as long-term establishment of a self-sustaining population depends on their short-term ability to exploit wild food sources. Monitoring of feeding habits is usually conducted through behavioral observation, but in recent years DNA metabarcoding has emerged as an alternative for obtaining highly resolved data on diet composition. In this study we use a combination of both techniques to characterize the breadth and composition of the reintroduced macaws diet. In addition, we evaluate the efficiency of both direct field observations and metabarcoding of feces as techniques to assess diet composition. Individuals fed on a variety of plant species (n = 49) belonging to a broad phylogenetic spectrum (28 families). Dietary richness estimated by direct observation and metabarcoding was similar, though smaller than the combination of the two datasets as both techniques detected at least 15 species not recorded by the other method. While the total number of detected species was higher for observational data, the rate of species-detection per sampling day was higher for metabarcoding. These results suggest that a combination of both methods is required in order to obtain the most accurate account of the total diversity of the diet of a species. The ability of the reintroduced macaws to successfully exploit local food resources throughout the year indicates a good level of adjustment to the release site, an important step towards the creation of a stable, self-sustaining population of Red-and-green Macaws in Northern Argentina. RESUMENEn el transcurso de los ultimos dos siglos, el Guacamayo Rojo (Ara chloropterus) se ha extinguido en la Argentina. Buscando recuperar su rol ecologico tanto de dispersor como de depredador de semillas de gran tamano, se comenzo un proyecto de reintroduccion de la especie en el Parque Nacional Ibera, en la region noreste del pais. La capacidad para encontrar alimento por parte de los individuos liberados es crucial, particularmente cuando se trabaja con animales provenientes de condiciones de cautiverio, ya que el establecimiento de una poblacion autosuficiente a largo plazo dependera de la habilidad de estos para explotar fuentes de alimento silvestre a corto plazo. El monitoreo de habitos alimenticios se realiza usualmente a traves de observaciones comportamentales. Sin embargo, en los ultimos anos la tecnica del meta-codigo de barras de ADN ha surgido como una alternativa para la obtencion de datos de composicion dietaria con alto nivel de resolucion. En este estudio, utilizamos una combinacion de ambas tecnicas para caracterizar la amplitud y composicion de la dieta de los guacamayos reintroducidos. A su vez, evaluamos la eficiencia de la observacion directa y el codigo de barras genetico de heces como tecnicas para evaluar la composicion de la dieta. Los individuos se alimentaron de una amplia variedad de especies (n = 49), abarcando un amplio espectro filogenetico (28 familias). La riqueza dietaria estimada por observacion directa y por meta-codigo de barras genetico fue similar, aunque menor a la resultante de la combinacion de todos los datos ya que ambas tecnicas detectaron al menos 15 especies no registradas por el otro metodo. Mientras que el numero total de especies detectadas fue mayor para los metodos observacionales, la tasa de deteccion de especies por dia de muestreo fue mayor para el analisis genetico. Estos resultados sugieren que una combinacion de ambos metodos es necesaria para obtener la descripcion mas precisa posible de la diversidad dietaria total de una especie. La capacidad de los guacamayos reintroducidos para explotar recursos alimenticios locales a lo largo del ano estaria indicando un buen nivel de adaptacion al sitio de liberacion, un paso muy importante hacia el establecimiento de una poblacion de Guacamayo Rojo estable y autosuficiente en el norte de Argentina. Palabras claveAra chloropterus, Conservacion, Dieta, Frugivoria, Meta-codigo de barras, Guacamayo Rojo, Reintroduccion, Ecologia trofica LAY SUMMARYO_LIThe Red-and-green Macaw reintroduction project aims to restore this species to Argentina, where it is locally extinct. To assess if reintroduced macaws are successfully adapting to life in the wild, we studied their foraging habits at the Ibera National Park. Their food consumption was observed visually, and their feces were analyzed with molecular methods for traces of the consumed plants. C_LIO_LIMacaws fed from a large diversity of food items, exhibiting a flexible diet which varied with fruit availability in different months. A combination of both methods was required to obtain the most accurate account of the total diversity of the diet of a species. C_LIO_LIThe reintroduced macaws were able to successfully locate and exploit food resources throughout the year, indicating a good level of adjustment to the release site. C_LI

ecology↗

bioRxiv2020

Effects of Malaise trap spacing on species richness and composition of terrestrial arthropod bulk samples

The Malaise trap has gained popularity for assessing diverse terrestrial arthropod communities because it collects large samples with modest effort. A number of factors that influence collection efficiency, placement being one of them. For instance, when designing larger biotic surveys using arrays of Malaise traps we need to know the optimal distance between individual traps that maximises observable species richness and community composition. We examined the influence of spacing between Malaise traps by metabarcoding samples from two field experiments at a site in Waterloo, Ontario, Canada. For one experiment, we used two trap pairs deployed at weekly increasing distance (3m increments from 3 to 27 m). The second experiment involved a total of 10 traps set up in a row at 3m distance intervals for three consecutive weeks. Results show that community similarity of samples decreases over distance between traps. The amount of species shared between trap pairs shows drops considerably at about 15m trap-to-trap distance. This change can be observed across all major taxonomic groups and for two different habitat types (grassland and forest). Large numbers of OTUs found only once within samples cause rather large dissimilarity between distance pairs even at close proximity. This could be caused by a large number of transient species from adjacent habitat which arrive at the trap through passive transport, as well as capture of rare taxa, which end up in different traps by chance.

ecology↗

bioRxiv2020

At each site its diversity: DNA barcoding reveals remarkable earthworm diversity in neotropical rainforests of French Guiana

Despite their recognized essential role in soil, earthworms in tropical environments are still understudied. The aim of this study was to re-evaluate the diversity at the regional scale, as well as to investigate the environmental and spatial drivers of earthworm communities. We sampled earthworm communities across a range of habitats at six locations in French Guiana using three different sampling methods. We generated 1675 DNA barcodes and combined them with data from a previous study. Together, all sequences clustered into 119 MOTUs which were used as proxy to assess species richness. Only two MOTUs were common between the six locations and 20.2 % were singletons, showing very high regional species richness and a high number of rare species. A canonical redundancy analysis was used to identify key drivers of the earthworm community composition. The RDA results and beta-diversity calculations both show strong species turnover and a strong spatial effect, resulting from dispersal limitations that are responsible for the current community composition. Sampling in different microhabitats allowed the discovery of 23 MOTUs that are exclusively found in decaying trunks and epiphytes, highlighting hidden diversity of earthworms outside of soil.

ecology↗

bioRxiv2020

Metabarcoding, direct stomach observation and stable isotope analysis reveal a highly diverse diet for the invasive green crab in Atlantic Patagonia

The European green crab Carcinus maenas and its sister species C. aestuarii are highly invasive species causing damage to coastal ecosystems and contributing to severe economic losses worldwide. C. maenas was first detected at the Atlantic Patagonian coast in 2001. In this work, we studied the diet of the green crab in a recently invaded location in Golfo Nuevo, using three complementary techniques: direct stomach observation, metabarcoding of gut content and stable isotope analysis. Direct stomach observation and metabarcoding showed that green crabs have a broad omnivorous diet, ingesting most of the phyla present in the study area. Gut content metabarcoding allowed a detailed description of algal diversity and revealed other taxa that went unnoticed in the visual stomach analysis. Stable isotope analysis showed that the major contribution to the crabs diet was from the phytoplankton chain (by bivalve consumption) and not directly from algae. This study approach combining three complementary techniques also allowed us to detect some differences in the diet between sexes, which suggests that male and female crabs are not as ecologically equivalent as previously thought. Besides, we detected sequences corresponding to C. aestuarii suggesting that the green crab Patagonian population is a hybrid of both sister species. These findings are key to understanding the impacts green crabs can have on the local ecosystem.

ecology↗

bioRxiv2020

Assessment of current taxonomic assignment strategies for metabarcoding eukaryotes

The effective use of metabarcoding in biodiversity science has brought important analytical challenges due to the need to generate accurate taxonomic assignments. The assignment of sequences to a generic or species level is critical for biodiversity surveys and biomonitoring, but it is particularly challenging. Researchers must select the approach that best recovers information on species composition. This study evaluates the performance and accuracy of seven methods in recovering the species composition of mock communities which vary in species number and specimen abundance, while holding upstream molecular and bioinformatic variables constant. It also evaluates the impact of parameter optimization on the quality of the predictions. Despite the general belief that BLAST top hit underperforms newer methods, our results indicate that it competes well with more complex approaches if optimized for the mock community under study. For example, the two machine learning methods that were benchmarked proved more sensitive to the reference database heterogeneity and completeness than methods based on sequence similarity. The accuracy of assignments was impacted by both species and specimen counts which will influence the selection of appropriate software. We urge the usage of realistic mock communities to allow optimization of parameters, regardless of the taxonomic assignment method used.

bioinformatics↗

bioRxiv2020

A2G2: A Python wrapper to perform very largealignments in semi-conserved regions

SummaryAmplicons to Global Gene (A2G2) is a Python wrapper that uses MAFFT and an "Amplicon to Gene" strategy to align very large numbers of sequences while improving alignment accuracy. It is specially developed to deal with conserved genes, where traditional aligners introduce a significant amount of gaps. A2G2 leverages the add sequences option of MAFFT to align the sequences to a global reference gene and a local reference region. Both of these references can be consensus sequences of trusted sources. Efficient parallelization of these tasks allows A2G2 to align a very large number of sequences (> 500K) in a reasonable amount of time. A2G2 can be imported in Python for easier integration with other software, or can be run via command line. AvailabilityA2G2 is implemented in Python 3 (3.6) and depends on MAFFT availability. Other package requirements can be found in the requirements.txt file at https://github.com/jshleap/A2G. A2G2 is also available via PyPi (https://pypi.org/project/A2G). It is licensed under the LGPLv3. Supplementary informationSupplementary material is available at github as jupyter notebook.

bioinformatics↗

bioRxiv2020

A workflow for accurate metabarcoding using nanopore MinION sequencing

Metabarcoding has become a common approach to the rapid identification of the species composition in a mixed sample. The majority of studies use established short-read high-throughput sequencing platforms. The Oxford Nanopore MinION, a portable sequencing platform, represents a low-cost alternative allowing researchers to generate sequence data in the field. However, a major drawback is the high raw read error rate that can range from 10% to 22%. To test if the MinION represents a viable alternative to other sequencing platforms we used rolling circle amplification (RCA) to generate full-length consensus DNA barcodes (658bp of cytochrome oxidase I - COI) for a bulk mock sample of 50 aquatic invertebrate species. By applying two different laboratory protocols, we generated two MinION runs that were used to build consensus sequences. We also developed a novel Python pipeline, ASHURE, for processing, consensus building, clustering, and taxonomic assignment of the resulting reads. We were able to show that it is possible to reduce error rates to a median accuracy of up to 99.3% for long RCA fragments (>45 barcodes). Our pipeline successfully identified all 50 species in the mock community and exhibited comparable sensitivity and accuracy to MiSeq. The use of RCA was integral for increasing consensus accuracy, but it was also the most time-consuming step during the laboratory workflow and most RCA reads were skewed towards a shorter read length range with a median RCA fragment length of up to 1262bp. Our study demonstrates that Nanopore sequencing can be used for metabarcoding but we recommend the exploration of other isothermal amplification procedures to improve consensus length.

bioinformatics↗

bioRxiv2020

CommDivMap: Modelling and mapping species richness at different spatial scales

1. Modern ecosystem models have the potential to greatly enhance our capacity to predict community responses to change, but they demand comprehensive spatial distribution information, creating the need for new approaches to gather and synthesize biodiversity data. 2. Metabarcoding or metagenomics can generate comprehensive biodiversity data sets at species-level resolution but they are limited to point samples. 3. CommDivMap contains a number of functions that can be used to turn OTU tables resulting from metabarcoding runs of bulk samples into species richness maps. We tested the method on a series of arthropod bulk samples obtained from various experimental agricultural plots. 4. The script runs smoothly and is reasonably fast. We hope that our assemble first, predict later approach to statistical modelling of species richness will set the stage for the transition from data-rich but finite sets of point samples to spatially continuous biodiversity maps.

bioinformatics↗