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Record W3196734913 · doi:10.1016/j.jglr.2021.08.009

Advances in the use of lampricides to control sea lampreys in the Laurentian Great Lakes, 2000–2019

2021· article· en· W3196734913 on OpenAlexaffvenueabout
W. Paul Sullivan, Dale P. Burkett, Michael A. Boogaard, Lori A. Criger, Christopher E. Freiburger, Terrance D. Hubert, Keith G. Leistner, Bruce J. Morrison, Shawn M. Nowicki, Shawn N.P. Robertson, Alan K. Rowlinson, Barry J. Scotland, Timothy B. Sullivan

Bibliographic record

VenueJournal of Great Lakes Research · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans Canada
FundersAmerican Fisheries Society
KeywordsPetromyzonLampreyFisherySalvelinusTributaryEnvironmental scienceTroutWildlifeEcologyBiologyFish <Actinopterygii>Geography

Abstract

fetched live from OpenAlex

The periodic application of chemical lampricides that selectively kill larval sea lampreys (Petromyzon marinus) in their nursery habitats remains a primary component of the Great Lakes Fishery Commission’s (GLFC) Sea Lamprey Control Program in the Laurentian Great Lakes. Lampricides include 3-trifluoromethyl-4-nitrophenol (TFM) and niclosamide, the 2-aminoethanol salt of 2′, 5-dichloro-4′-nitrosalicylanilide, which may be used as an additive to TFM during stream treatments, or alone in a granular, bottom-release formulation to target sea lamprey larvae in deepwater environments where dilution would render TFM ineffective. During the early 1990s, the GLFC identified lampricide reduction targets in response to societal concerns with pesticide use, rising lampricide costs, and promising research into alternative controls. By 1999, the GLFC’s control agents, Fisheries and Oceans Canada (DFO) and the U.S. Fish and Wildlife Service (USFWS), had reduced TFM use by 36%. However, without effective alternative methods to compensate for increasing larval and juvenile production, sea lamprey abundance and lake trout (Salvelinus namaycush) marking rates rose throughout the Great Lakes. Beginning in the early 2000s, the GLFC and its control agents responded to burgeoning sea lamprey populations by implementing measures to advance the use of lampricides, which included: 1) assessing and controlling sea lamprey larvae that survived treatment; 2) enhancing treatment efficacy; 3) developing new technology to effectively treat larval populations that inhabit deepwater environments; 4) increasing operational capacity to treat more tributaries and lentic areas at shorter intervals; and, 5) conducting large-scale and targeted treatment strategies. When comparing lampricide use between the decades of 1990–1999 and 2010–2019, significant increases occurred in the mean number of treatments and amounts of TFM and niclosamide applied annually. Concurrent with these actions, researchers undertook studies to identify factors that erode lampricide treatment efficiency, elucidate physiological mode of action, and investigate lethal and sub-lethal impacts of lampricide exposure on aquatic organisms. By integrating new operational tactics and strategies with advances in science and technology, the GLFC, DFO, and USFWS, with support from the U.S. Geological Survey and the U.S. Army Corps of Engineers, have achieved unprecedented suppression of sea lampreys and reduction in lake trout marking in the Great Lakes. However, emerging challenges potentially threaten the future use of lampricides.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.872
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.045
GPT teacher head0.318
Teacher spread0.273 · 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 source (direct Gemma or distilled Codex), 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

Citations44
Published2021
Admission routes3
Has abstractyes

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