No evidence for collateral effects of electromagnetic fields used to increase dissolved oxygen levels on the behavior and physiology of freshwater fishes
Bibliographic record
Abstract
Hypoxia in surface waters driven by warming climate and other anthropogenic stressors is a major conservation concern, and technological solutions for water quality remediation are sorely needed. One potential solution involves the use of low-intensity electromagnetic fields (EMFs) to increase dissolved oxygen levels, but potential collateral effects of the EMFs on aquatic animals have not been formally evaluated. We examined the effects of EMF exposure on wild-caught, captive sunfish (Lepomis spp.) over 8-day and 3-day exposures, with and without aeration in mesocosms and stock tanks (respectively). We also quantified ambient fish abundance in close proximity to EMF devices deployed in Opinicon Lake (ON). We found no significant differences in a suite of blood-based stress physiology biomarkers, behaviors, and putative aerobic capacities between EMF and control conditions over 8 days. Aerated mesocosms equipped with activated EMFs consistently had higher oxygen levels in the water than aerated controls. There were no differences in mortality during 3-day oxygen depletion trials under EMF or control conditions, and we detected no differences in fish abundance when the devices were activated in the lake. Our findings suggest that deploying EMF devices in field settings is not likely to exert negative effects on exposed fish populations. PRACTITIONER POINTS: Low-cost, low-energy technological solutions to remediate aquatic hypoxia are sorely needed Electromagnetic fields (EMFs) can increase oxygen flux across air/water interfaces and increase dissolved oxygen levels We found no evidence of negative effects of EMFs on fish physiology or behavior and our results support their use in alleviating hypoxic conditions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".