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Record W6992908650

Molecular assays for the detection of invasive tunicates and phylogeography of a tunicate invasion in Prince Edward Island

2010· article· en· W6992908650 on OpenAlexaboutno aff

Bibliographic record

VenueIslandScholar (University of Prince Edward Island) · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Ecology and Invasive Species
Canadian institutionsnot available
Fundersnot available
KeywordsTunicateCiona intestinalisMusselLarvaAquacultureInvasive speciesAquatic animalPopulationBay
DOInot available

Abstract

fetched live from OpenAlex

There are currently four invasive tunicate species which are causing significant challenges to the aquaculture industry in Atlantic Canada: Ciona intestinalis, Styela clava, Botryllus schlosseri and Botrylloides violaceus. These tunicates foul mussel socks, aquaculture gear, boat hulls and wharves. As with many aquatic invasive species, detection of these tunicates mostly occurs once adult populations have reached significant population sizes. However, once populations have reached these levels, there is often little that can be done to stop or slow the invasion. Having efficient and sensitive assays that could detect invasive tunicates at microscopic stages would be advantageous as management strategies could be implemented before populations spike to invasive levels. Such an assay would also be useful in monitoring mussel processing plant effluent so that invasive tunicate eggs and larvae are not spread through effluent water discharge to adjacent bays. Molecular assays have been developed in this study that can detect the four invasive tunicate species in both mussel processing effluent water and in bay water surrounding mussel leases. These assays are highly specific and have a sensitivity of detection of 1-5 eggs and/or larvae per water sample. In addition qRT-PCR assays have been developed that can detect and distinguish between different life stages of Ciona intestinalis (egg and larvae) in water samples. This qRT-PCR assay also has the capacity to evaluate viability of free swimming larvae so that nonviable larvae do not cause false positives during mussel processing plant effluent monitoring. The high throughput capacity, high specificity and sensitivity of these assays shows excellent potential for use as a monitoring tool for aquatic invasive species in screening ballast water, effluent waste from shellfish processing plants, as well in local bays and rivers. This study also used phylogenetic analyses of the cytochrome oxidase 1 gene to determine that populations of Botryllus schlosseri in Prince Edward Island have low genetic diversity. Only two haplotypes of B. schlosseri were found in this study in PEI, one which was found in all aquaculture bays tested and the other found only on native substrate in one bay. It is likely that local activity spread this species to other areas of Prince Edward Island after the initial invasion. Phylogeographic analysis suggests that this species was likely transported from Massachusetts to Nova Scotia and then was transported to Prince Edward Island via local boating activity or through the movement of aquaculture species. Through the development of these efficient detection methods and by determining source populations and possible vectors responsible for transporting invasive species to this region, it is hoped that new invasions of aquatic invasive species can be prevented and/or managed before they pose a risk to the aquaculture industry in Prince Edward Island.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.195
Teacher spread0.189 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2010
Admission routes1
Has abstractyes

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