Cold shock and fish
Bibliographic record
Abstract
Rapid decreases in water temperature may result in a number of physiological, behavioural and fitness consequences for fishes termed ‘cold shock’. Cold‐shock stress occurs when a fish has been acclimated to a specific water temperature or range of temperatures and is subsequently exposed to a rapid decrease in temperature, resulting in a cascade of physiological and behavioural responses and, in some cases, death. Rapid temperature decreases may occur from either natural ( e.g. thermocline temperature variation, seiches and storm events) or anthropogenic sources ( e.g. varied thermal effluents from power generation and production industries). The magnitude, duration and frequency of the temperature change as well as the initial acclimation temperatures of individuals can influence the extent of the consequences of cold shock on fishes. Early research on cold shock focused on documenting mortality events associated with cold shock. However, in recent years, a shift in research has occurred where the focus of cold‐shock studies now involves characterizing the sublethal effects of cold shock in terms of the stress response in fishes. This shift has revealed that cold shock can actually be used as a tool for fisheries science ( e.g. to induce polyploidy). The cold‐shock stress response offers opportunities to develop many exciting research questions, yet to date, cold‐shock research has been largely unfocused. Few studies attempt to link laboratory physiology experiments with ecologically relevant field data on behaviour, growth, bioenergetics and fitness. Additional research will allow for the development of more focused and robust management policies and conservation initiatives. This review synthesizes the sublethal physiological and behavioural consequences of cold‐shock stress on fishes, identifies natural and anthropogenic sources of cold shock, discusses the benefits of cold shock to fisheries science and describes mitigation and management efforts. Existing knowledge gaps and opportunities for future cold‐shock research are presented.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".