Effects of Endocrine Disrupting Chemicals on Wildlife in Canada: Past, Present and Future
Bibliographic record
Abstract
Abstract Within a few years of their widespread introduction into the environment, there were major concerns about the effects of man-made chemicals on wildlife in Canada. Biologists have found evidence of endocrine disruption in at least 16 species of birds (particularly fish-eating and predatory species), 3 species of terrestrial mammals and 1 whale, 1 reptile and several amphibians. These effects were seen in the Great Lakes, areas polluted with pulp and paper effluents, the forests of New Brunswick, a variety of agricultural habitats, acidified lakes in Nova Scotia, major rivers and inshore coastal waters, and the Arctic. They include decreased reproductive success, gross congenital abnormalities and interference with developmental/regenerational processes; thyroid dysfunction; metabolic abnormalities; feminization/demasculinization; alterations in sex ratios; altered brain development and behaviour; and altered immune function. These sublethal effects have the potential to alter an individual's quality of life, its survival, or reproductive fitness. Morbidity and mortality are rarely detected and grossly underestimated in wildlife populations and we are likely to have underestimated the occurrence, prevalence and severity of endocrine disruption in wildlife. There is no formal existing program in Canada for gathering long-term evidence for determining trends in the incidence and severity of effects in organisms. All of the information on endocrine disruption in Canadian wildlife reported in this review was gathered as a result of academic research or research-based monitoring. Much greater effort must be made to systematically detect and identify a much broader range of man-made chemicals, both persistent and nonpersistent, and their metabolites in wildlife tissues and environmental media. These efforts should be complimented by parallel measurements of various biological activities of extracts of the same wildlife tissues and environmental media. This monitoring information would then point to specific locations, effluents, agricultural practices, industrial processes, and products where investigations of effects should be conducted and to species and functions potentially at risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".