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Record W7133286413

Use of drugs and pesticides by the Canadian marine finfish aquaculture industry in 2016-2018

2022· other· en· W7133286413 on OpenAlexaboutno aff
B. D. Chang, F. H. Page, D. H. Hamoutene

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPesticideAquaculturePesticide residueFish farmingAgriculture
DOInot available

Abstract

fetched live from OpenAlex

This document is part of a CSAS process in support of the development of a post-deposit monitoring program for drug and pesticide use at Canadian marine finfish farms. This report focusses on the usage (number of farms treated and amount of active ingredient used) of drugs and pesticides at Canadian marine finfish farms during 2016-2018. Total Canadian marine finfish aquaculture production showed a slight decrease during these years: 148 900 t in 2016; 140 500 t in 2017; and 138 400 t in 2018. By province, 61-63% of the annual production was in British Columbia (BC), 17-20% in New Brunswick (NB), 11-17% in Newfoundland & Labrador (NL), and 4-8% in Nova Scotia (NS); production was >95% Atlantic salmon. The Government of Canada has required marine finfish farms to report their usage of drugs and pesticides on an annual basis since 2016. Data on drug and pesticide use in 2016-2018 were obtained from the National Aquaculture Public Reporting Data (NAPRD) and the Aquaculture Integrated Information System (AQUIIS). The reported drugs (applied in-feed) and pesticides (applied in bath treatments) included antibiotic drugs (oxytetracycline, florfenicol, erythromycin, ormetoprim, and trimethoprim), pest control drugs (emamectin benzoate, ivermectin, and selamectin for sea louse control; and praziquantel for parasitic worm control), and pesticides (azamethiphos and hydrogen peroxide; both for sea louse control). Individual farms used from zero to six drugs and pesticides in 2016, and zero to five in 2017 and 2018. Of the 136-152 active marine finfish farms in each year during 2016-2018, 108-128 (74-84%) used at least one drug or pesticide in each year. By province, 52-58% of treated farms were in BC, 26-30% in NB, 13-18% in NL, and 0-3% in NS. The percentage of active farms that used at least one drug or pesticide was: 83-86% in BC; 69-86% in NB; 74-95% in NL; and 0-38% in NS. Of the five antibiotic drugs reported, florfenicol was used at the most farms (47-50 farms per yr), followed by oxytetracycline (17-24 farms per yr); the other three were used by ≤5 farms per yr. BC had the largest number of farms treated with florfenicol and the highest quantity used in each year (34-35 farms per yr). The largest number of farms treated with oxytetracycline was in NB in 2016 (10 farms) and in BC in 2017 (7 farms) and 2018 (10 farms); the highest quantity used was in NL in 2016 and 2017, and in BC in 2018. Of the pest control drugs, emamectin benzoate was used at the most farms in all three years (56-70 farms per yr). BC had the largest number of farms treated with emamectin benzoate in all three years (32-38 farms per yr), while NL used the largest quantity in all three years. Ivermectin was used at 14-20 farms per yr and was only used in NB and NL, with NB having the larger number of farms treated and the larger quantity used in each year. Selamectin was used on a trial basis only (one NB farm in 2017 and one NB farm in 2018). Praziquantel was used only in NL, and only in 2016 and 2017. One other sea louse control drug, lufeneron, was used in freshwater hatcheries in BC, NB, and NL. The pesticide azamethiphos was used at 20-42 farms per yr; it was used only in NB and NL. In 2016, NB had the larger number of farms treated with azamethiphos (29 farms) and the larger quantity used; in 2017 and 2018, NB and NL had equal numbers of farms treated (20 farms each in 2016, 10 farms each in 2017), while NL used the larger quantity in both years. Hydrogen peroxide was used at 25-37 farms per yr; it was used in BC, NB, and NL. In 2016, NB had the largest number farms treated with hydrogen peroxide (14 farms) and also used the largest quantity; in 2017 and 2018, BC had the largest number of treated farms (17 in 2017; 22 in 2018) and also used the largest quantity in both years. There were differences in usage between salmon year-classes for some of the chemicals: florfenicol and ivermectin were used primarily on smolts, while emamectin benzoate and azamethiphos were used more on pre-market fish. In BC, treatments with drugs and pesticides occurred throughout the year, while in NB and NL, treatments did not occur in winter and early spring; in NS, the only treatments were in August 2016 and in June-August 2018 (all NS treatments were antibiotics). The three years of data were insufficient to discern clear inter-annual trends in drug and pesticide use.

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)0.001
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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