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Record W3024930800 · doi:10.3391/mbi.2020.11.2.03

Environmental DNA (eDNA) detection of marine aquatic invasive species (AIS) in Eastern Canada using a targeted species-specific qPCR approach

2020· article· en· W3024930800 on OpenAlexaboutno aff
Francis LeBlanc, Valérie Belliveau, Erica Watson, Chantal Coomber, Nathalie Simard, Claudio DiBacco, Renée Bernier, Nellie Gagné

Bibliographic record

VenueManagement of Biological Invasions · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsnot available
FundersInterregNatural Environment Research CouncilLeuphana Universität Lüneburg
KeywordsEnvironmental DNABiologyInvasive speciesAquatic environmentEcologyFisheryBiodiversity

Abstract

fetched live from OpenAlex

Ireland, being an island situated on Europe's western seaboard, has a fewer number of native species than mainland European Union Member States (MS).Increased numbers of vectors and pathways have reduced the island's biotic isolation, increasing the risk of new introductions and their associated impacts on native biodiversity.It is likely that these risks are greater here than they are in continental MSs, where the native biodiversity is richer.A horizon scanning approach was used to identify the most likely invasive alien species (IAS) (with the potential to impact biodiversity) to arrive on the island of Ireland within the next ten years.To achieve this, we used a consensus-based approach, whereby expert opinion and discussion groups were utilised to establish and rank a list of 40 species of the most likely terrestrial, freshwater and marine IAS to arrive on the island of Ireland within the decade 2017-2027.The list of 40 included 18 freshwater, 15 terrestrial and seven marine IAS.Crustacean species (freshwater and marine) were taxonomically dominant (11 out of 40); this reflects their multiple pathways of introduction, their ability to act as ecosystem engineers and their resulting high impacts on biodiversity.Freshwater species dominated the top ten IAS (seven species out of ten), with the signal crayfish (Pacifastacus leniusculus) highlighted as the most likely species to arrive and establish in freshwaters, while roe deer (Capreolus capreolus) (second) and the warm-water barnacle (Hesperibalanus fallax) (fifth), were the most likely terrestrial and marine invaders.This evidence-based list provides important information to the relevant statutory agencies in both the Republic of Ireland and Northern Ireland to prioritise the prevention of the most likely invaders and aid in compliance with legislation, in particular the EU Regulation on Invasive Alien Species (EU 1143/2014).Targeted biosecurity in both jurisdictions is urgently required in order to manage the pathways and vectors of arrival, and is vital to maintaining native biodiversity on the island of Ireland.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.098
GPT teacher head0.197
Teacher spread0.099 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations64
Published2020
Admission routes1
Has abstractyes

Explore more

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