scholarly journals Replicate DNA metabarcoding can discriminate seasonal and spatial abundance shifts in river macroinvertebrate assemblages

2021 ◽  
Vol 4 ◽  
Author(s):  
Alex Bush ◽  
Zacchaeus Compson ◽  
Matilda Kattilakoski ◽  
Natalie Rideout ◽  
Brianna Levenstein ◽  
...  
Keyword(s):  
Predatory Fish ◽  
Great Promise ◽  
Macroinvertebrate Communities ◽  
Ecological Studies ◽  
Biodiversity Data ◽  
Occurrence Data ◽  
Dna Metabarcoding ◽  
Species Abundances ◽  
Fine Resolution ◽  
Small Tributary

Metabarcoding is capable of delivering consistent and accurate fine-resolution biodiversity data, and offers great promise for improving aspects of environmental assessment and research. Even so, many ecologists are keen to make further inferences about species’ abundances and the number of sequence reads has proven to be a poor proxy for abundance. The conservative interpretation has been to treat metabarcoding data as presence/absence, and although such data are less rich, occurrence and abundance are only different expressions of the same phenomenon. Interestingly if we assume the probability of detecting individuals is constant, it should be possible to use changes in the frequency of detection to infer changes in the underlying abundance. We tested the possibility that changes in the abundance structure of benthic macroinvertebrate communities could be recovered using replicated metabarcoding. We conducted 5 monthly surveys from Jun-Nov 2019 at the Catamaran Brook, a small tributary of the Little Southwest Miramichi River in New Brunswick, Canada. Each survey collected 30 benthic samples divided between control and treatment cages that excluded predatory fish. A further 6 samples were taken for traditional microscopic identification and counting. Analysis of the metabarcoding data demonstrated that we could recover plausible changes in abundance from occurrence data, including significant responses to both seasonal dynamics and the experimental exclusion of predators. The microscopy samples merely confirmed that count data are highly stochastic, and therefore while specific estimates of expected abundance from our model are highly uncertain, they capture those differences we could validate. In summary, while we confirmed that occurrence data are more robust for routine bioassessment, it is possible to recover fine-resolution changes in abundance that can inform ecological studies using metabarcoding.

scholarly journals An Overview of DNA-Based Applications for the Assessment of Benthic Macroinvertebrates Biodiversity in Mediterranean Aquatic Ecosystems

Diversity ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 112
Author(s):  
Eftychia Tzafesta ◽  
Francesco Zangaro ◽  
Valeria Specchia ◽  
Maurizio Pinna
Keyword(s):  
Benthic Macroinvertebrates ◽  
Aquatic Ecosystems ◽  
Biodiversity Monitoring ◽  
Biodiversity Data ◽  
Management Tools ◽  
Aquatic Biodiversity ◽  
Current State ◽  
Dna Metabarcoding ◽  
Ecosystem Condition ◽  
Macroinvertebrate Species

The loss of aquatic biodiversity is increasing at a rapid rate globally. There is a worldwide effort to protect, preserve and restore aquatic ecosystems. For efficient biodiversity monitoring and reliable management tools, comprehensive biodiversity data are required. The abundance and species diversity of benthic macroinvertebrates are commonly used as indicators of the aquatic ecosystem condition. Currently, macroinvertebrate species biodiversity assessment is based on morpho-taxonomy, which could be enhanced by recent advances in DNA-based tools for species identification. In particular, DNA metabarcoding has the potential to identify simultaneously many different taxa in a pool of species and to improve aquatic biomonitoring significantly, especially for indicator species. This review is focused on the current state of DNA-based aquatic biomonitoring using benthic macroinvertebrates in the Mediterranean region.

scholarly journals PIMBA: a PIpeline for MetaBarcoding Analysis

2021 ◽  
Author(s):  
Renato R. M. Oliveira ◽  
Raissa L S Silva ◽  
Gisele L. Nunes ◽  
Guilherme Oliveira
Keyword(s):  
Environmental Samples ◽  
Next Generation Sequencing Data ◽  
Ecological Studies ◽  
Sequencing Data ◽  
Monitoring Method ◽  
Computational Tools ◽  
Dna Metabarcoding ◽  
Reference Databases ◽  
User Friendly ◽  
Generation Sequencing

DNA metabarcoding is an emerging monitoring method capable of assessing biodiversity from environmental samples (eDNA). Advances in computational tools have been required due to the increase of Next-Generation Sequencing data. Tools for DNA metabarcoding analysis, such as MOTHUR, QIIME, Obitools, and mBRAVE have been widely used in ecological studies. However, some difficulties are encountered when there is a need to use custom databases. Here we present PIMBA, a PIpeline for MetaBarcoding Analysis, which allows the use of customized databases, as well as other reference databases used by the softwares mentioned here. PIMBA is an open-source and user-friendly pipeline that consolidates all analyses in just three command lines.

scholarly journals Impacts of mountain forest dieback on aquatic insect communities: A DNA metabarcoding analysis of samples from the Bavarian Forest

2021 ◽  
Vol 4 ◽  
Author(s):  
Erik Rohe ◽  
Paul Schmidt Yáñez ◽  
Michael Monaghan
Keyword(s):  
Species Richness ◽  
Forest Management ◽  
Aquatic Insect ◽  
Ips Typographus ◽  
Macroinvertebrate Communities ◽  
Insect Communities ◽  
Forest Dieback ◽  
Dna Metabarcoding ◽  
Bavarian Forest ◽  
Disturbed Forest

Mountain forests are increasingly affected by changes in rainfall and pest outbreaks, and the way forests are managed can have direct consequences for the streams flowing through forests. Aquatic macroinvertebrate communities are great bioindicators and changes to their ecosystem likely translates to changes in their overall composition and abundance. The Bavarian Forest National Park (SE Germany) is dominated by the Norway spruce (Picea abies) which, weakened by storms and other stressors, is susceptible to infestation by the European spruce bark beetle (Ips typographus). The result is large scale forest dieback in some areas, and forest management practices that lead to a predominance of three different forest types (hereafter habitats): Intact forest that is healthy and not impacted by Ips typographus; Disturbed forest that was impacted by Ips typographus, left to regenerate naturally, and from which deadwood was not removed; and Salvaged forest that was heavily impacted by Ips typographus with the same consequences, but from which deadwood was removed, creating a treeless forest meadow. Intact forest that is healthy and not impacted by Ips typographus; Disturbed forest that was impacted by Ips typographus, left to regenerate naturally, and from which deadwood was not removed; and Salvaged forest that was heavily impacted by Ips typographus with the same consequences, but from which deadwood was removed, creating a treeless forest meadow. To analyze the impacts these different forest management strategies have on the aquatic insect communities, 30 samples from 11 different streams were taken using kick-sampling. Operational taxonomic units (OTUs) were identified by bulk metabarcoding of dried, ground samples. A mock community was used to verify the setup and a DNA spike-in with three foreign OTUs was added to each sample to measure the biases introduced by PCR amplification and sequencing. Biases varied across samples, but spike-in OTUs produced a pattern indicating predictable biases which could lead to quantifiable metabarcoding results in the future. In total, 260 macroinvertebrate OTUs were identified. In comparison, a morphological study by Bojková et al. (2018) in the same region with twice the number of sampling sites collected 194 taxa in the same month as our samples. This underlines the potential for metabarcoding in evaluating species richness. Species richness was high across all habitats. A significant difference between the forest conditions was detected: The number of detected Diptera OTUs was lowest in disturbed habitats (55) and highest in salvaged areas (73). A permutational multivariate analysis of variance (PERMANOVA) indicated that habitat (i.e., intact, disturbed, salvaged) had an effect on the observed OTU distribution (9.2%), but that the stream catchment had a much larger effect (39.3%) regardless of the habitat. Our findings indicate that forest management can affect stream macroinvertebrate communities, and that this was most pronounced for the Diptera, a group for which DNA metabarcoding is particularly well suited because of their small size and high diversity.

scholarly journals Estimating intraspecific genetic diversity from community DNA metabarcoding data

2018 ◽  
Author(s):  
Vasco Elbrecht ◽  
Ecaterina Edith Vamos ◽  
Dirk Steinke ◽  
Florian Leese
Keyword(s):  
Genetic Diversity ◽  
Biological Diversity ◽  
Intraspecific Diversity ◽  
Great Promise ◽  
Data Sets ◽  
Mock Community ◽  
Data Set ◽  
Dna Metabarcoding ◽  
Intraspecific Genetic Diversity ◽  
Primer Sets

Background. DNA metabarcoding is used to generate species composition data for entire communities. However, sequencing errors in high throughput sequencing instruments are fairly common, usually requiring reads to be clustered into operational taxonomic units (OTU), losing information on intraspecific diversity in the process. While COI haplotype information is limited in resolution, it is nevertheless useful in a phylogeographic context, helping to formulate hypothesis on taxon dispersal. Methods. This study combines sequence denoising strategies, normally applied in microbial research, with additional abundance-based filtering to extract haplotypes from freshwater macroinvertebrate metabarcoding data sets. This novel approach was added to the R package "JAMP" and can be applied to Cytochrome c oxidase subunit I (COI) amplicon datasets. We tested our haplotyping method by sequencing i) a single-species mock community composed of 31 individuals with different haplotypes spanning three orders of magnitude in biomass and ii) 18 monitoring samples each amplified with four different primer sets and two PCR replicates. Results. We detected all 15 haplotypes of the single specimens in the mock community with relaxed filtering and denoising settings. However, up to 480 additional unexpected haplotypes remained in both replicates. Rigorous filtering removes most unexpected haplotypes, but also can discard expected haplotypes mainly from the small specimens. In the monitoring samples, the different primer sets detected 177 - 200 OTUs, each containing an average of 2.40 to 3.30 haplotypes per OTU. Population structures were consistent between replicates, and similar between primer pairs, depending on the primer length. A closer look at abundant taxa in the data set revealed various population genetic patterns, e.g. Taeniopteryx nebulosa and Hydropsyche pellucidula with a difference in north-south haplotype distribution, while Oulimnius tuberculatus and Asellus aquaticus display no clear population pattern but differ in genetic diversity. Discussion. We developed a strategy to infer intraspecific genetic diversity from bulk invertebrate monitoring samples using metabarcoding data. It needs to be stressed that at this point metabarcoding-informed haplotyping is not capable of capture the full diversity present in such samples, due to variation in specimen size, primer bias and loss of sequence variants with low abundance. Nevertheless, for a high number of species intraspecific diversity was recovered, identifying potentially isolated populations and potential taxa for further more detailed phylogeographic investigation. While we are currently lacking large-scale metabarcoding data sets to fully take advantage of our new approach, metabarcoding-informed haplotyping holds great promise for biomonitoring efforts that not only seek information about biological diversity but also underlying genetic diversity.

scholarly journals Phylogeny Based Biodiversity Data Queries

2018 ◽  
Vol 2 ◽  
pp. e25589
Author(s):  
Scott Chamberlain
Keyword(s):  
Research Work ◽  
Sister Group ◽  
Data Sources ◽  
Work Flow ◽  
Use Case ◽  
Biodiversity Data ◽  
R Software ◽  
Occurrence Data ◽  
Simple Query ◽  
The Ideal

There is a large amount of publicly available biodiversity data from many different data sources. When doing research, one ideally interacts with biodiversity data programmatically so their work is reproducible. The entry point to biodiversity data records is largely through taxonomic names, or common names in some cases (e.g., birds). However, many researchers have a phylogeny focused project, meaning taxonomic names are not the ideal interface to biodiversity data. Ideally, it would be simple to programmatically go from a phylogeny to biodiversity records through a phylogeny based query. I'll discuss a new project `phylodiv` (https://github.com/ropensci/phylodiv/) that attempts to facilitate phylogeny based biodiversity data collection (see Fig. 1). The project takes the form of an R software package. The idea is to make the user interface take essentially two inputs: a phylogeny and a phylogeny based question. Behind the scenes we'll do many things, including gathering taxonomic names and hierarchies for the taxa in the phylogeny, send queries to GBIF (or other data sources), and map the results. The user will of course have control over the behind the scenes parts, but I imagine the majority use case will be to input a phylogeny and a question and expect an answer back. We already have R tools to do nearly all parts of the work-flow shown above: there's a large number of phylogeny tools, `taxize`/`taxizedb` can handle taxonomic name collection, while `rgbif` can handle interaction with GBIF, and there's many mapping options in R. There are a few areas that need work still however. First, there's not yet a clear way to do a phylogeny based query. Ideally a user will be able to express a simple query like "taxon A vs. its sister group". That's simple to imagine, but to implement that in software is another thing. Second, users ideally would like answers back - in this case a map of occurrences - relatively quickly to be able to iterate on their research work-flow. The most likely solution to this will be to use GBIF's map tile service to visualize binned occurrence data, but we'll need to explore this in detail to make sure it works.

scholarly journals ChiroVox: a public library of bat calls

PeerJ ◽  
2022 ◽  
Vol 10 ◽  
pp. e12445
Author(s):  
Tamás Görföl ◽  
Joe Chun-Chia Huang ◽  
Gábor Csorba ◽  
Dorottya Győrössy ◽  
Péter Estók ◽  
...  
Keyword(s):  
Open Access ◽  
Public Library ◽  
Ecological Studies ◽  
Biodiversity Data ◽  
Unique Identifier ◽  
Sound Recordings ◽  
Social Calls ◽  
Identification Of Species ◽  
Acoustic Analyses ◽  
Effective Use

Recordings of bat echolocation and social calls are used for many research purposes from ecological studies to taxonomy. Effective use of these relies on identification of species from the recordings, but comparative recordings or detailed call descriptions to support identification are often lacking for areas with high biodiversity. The ChiroVox website (www.chirovox.org) was created to facilitate the sharing of bat sound recordings together with their metadata, including biodiversity data and recording circumstances. To date, more than 30 researchers have contributed over 3,900 recordings of nearly 200 species, making ChiroVox the largest open-access bat call library currently available. Each recording has a unique identifier that can be cited in publications; hence the acoustic analyses are repeatable. Most of the recordings available through the website are from bats whose species identities are confirmed, so they can be used to determine species in recordings where the bats were not captured or could not be identified. We hope that with the help of the bat researcher community, the website will grow rapidly and will serve as a solid source for bat acoustic research and monitoring.

scholarly journals Estimating intraspecific genetic diversity from community DNA metabarcoding data

2018 ◽  
Author(s):  
Vasco Elbrecht ◽  
Ecaterina Edith Vamos ◽  
Dirk Steinke ◽  
Florian Leese
Keyword(s):  
Genetic Diversity ◽  
Biological Diversity ◽  
Intraspecific Diversity ◽  
Great Promise ◽  
Data Sets ◽  
Mock Community ◽  
Data Set ◽  
Dna Metabarcoding ◽  
Intraspecific Genetic Diversity ◽  
Primer Sets

Background. DNA metabarcoding is used to generate species composition data for entire communities. However, sequencing errors in high throughput sequencing instruments are fairly common, usually requiring reads to be clustered into operational taxonomic units (OTU), losing information on intraspecific diversity in the process. While COI haplotype information is limited in resolution, it is nevertheless useful in a phylogeographic context, helping to formulate hypothesis on taxon dispersal. Methods. This study combines sequence denoising strategies, normally applied in microbial research, with additional abundance-based filtering to extract haplotypes from freshwater macroinvertebrate metabarcoding data sets. This novel approach was added to the R package "JAMP" and can be applied to Cytochrome c oxidase subunit I (COI) amplicon datasets. We tested our haplotyping method by sequencing i) a single-species mock community composed of 31 individuals with different haplotypes spanning three orders of magnitude in biomass and ii) 18 monitoring samples each amplified with four different primer sets and two PCR replicates. Results. We detected all 15 haplotypes of the single specimens in the mock community with relaxed filtering and denoising settings. However, up to 480 additional unexpected haplotypes remained in both replicates. Rigorous filtering removes most unexpected haplotypes, but also can discard expected haplotypes mainly from the small specimens. In the monitoring samples, the different primer sets detected 177 - 200 OTUs, each containing an average of 2.40 to 3.30 haplotypes per OTU. Population structures were consistent between replicates, and similar between primer pairs, depending on the primer length. A closer look at abundant taxa in the data set revealed various population genetic patterns, e.g. Taeniopteryx nebulosa and Hydropsyche pellucidula with a difference in north-south haplotype distribution, while Oulimnius tuberculatus and Asellus aquaticus display no clear population pattern but differ in genetic diversity. Discussion. We developed a strategy to infer intraspecific genetic diversity from bulk invertebrate monitoring samples using metabarcoding data. It needs to be stressed that at this point metabarcoding-informed haplotyping is not capable of capture the full diversity present in such samples, due to variation in specimen size, primer bias and loss of sequence variants with low abundance. Nevertheless, for a high number of species intraspecific diversity was recovered, identifying potentially isolated populations and potential taxa for further more detailed phylogeographic investigation. While we are currently lacking large-scale metabarcoding data sets to fully take advantage of our new approach, metabarcoding-informed haplotyping holds great promise for biomonitoring efforts that not only seek information about biological diversity but also underlying genetic diversity.

scholarly journals Contribution of genome scale metabolic modeling to niche theory

2021 ◽  
Author(s):  
Antoine Regimbeau ◽  
Marko Budinich ◽  
Abdelhalim Larhlimi ◽  
Juan Jose Pierella Karlusich ◽  
Olivier Aumont ◽  
...  
Keyword(s):  
Probabilistic Inference ◽  
Metabolic Modeling ◽  
Niche Modeling ◽  
Functional Genes ◽  
Niche Theory ◽  
Ecological Studies ◽  
Occurrence Data ◽  
Genome Scale ◽  
The Way

Standard niche modeling is based on probabilistic inference from organismal occurrence data but does not benefit yet from genome-scale descriptions of these organisms. This study overcomes this shortcoming by proposing a new conceptual niche that encompasses the whole metabolic capabilities of an organism. The so-called metabolic niche resumes well-known traits such as nutrient needs and their dependencies for survival. Despite the computational challenge, its implementation allows the detection of traits and the formal comparison of niches of different organisms, emphasizing that the presence-absence of functional genes is not enough to approximate the phenotype. Further statistical exploration of an organism's niche sheds light on genes essential for the metabolic niche and their role in understanding various biological experiments, such as transcriptomics, paving the way for incorporating better the genome-scale description in ecological studies.

scholarly journals Correction to: Fish vs. Aliens: predatory fish regulate populations of Limnoperna fortunei mitigating impacts on native macroinvertebrate communities

Hydrobiologia ◽  
2021 ◽  
Author(s):  
Ivana Silva ◽  
Daniel Naya ◽  
Franco Teixeira de Mello ◽  
Alejandro D’Anatro ◽  
Giancarlo Tesitore ◽  
...  
Keyword(s):  
Predatory Fish ◽  
Macroinvertebrate Communities ◽  
Limnoperna Fortunei
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