Implications of climate change for parasitism of animals in the aquatic environment
Bibliographic record
Abstract
Climate change can occur over evolutionary and ecological time scales as a result of natural and anthropogenic causes. Considerable attention has been focused in recent years on the biological consequences of global warming. However, aside from studies on those deleterious parasites that cause disease in man, little effort has been dedicated to understanding the potential changes in the parasite fauna of animal populations, especially those in aquatic systems. Predictions using General Circulation Models, among others, are examined in terms of their consequences for parasite populations in freshwater and marine ecosystems, concentrating on the temperate and boreal regions of eastern North America. Biological effects due to global warming are not predictable simply in terms of temperature response. It is also essential to explore the effects on aquatic parasites of alterations in host distribution, water levels, eutrophication, stratification, ice cover, acidification, oceanic currents, ultraviolet-light penetration, weather extremes, and human interference. Evaluation of the potential response of parasites of aquatic organisms to climate change illustrates the complexity of hostparasite systems and the difficulty of making accurate predictions for biological systems. Parasites in aquatic systems will respond directly to changes in temperature but also indirectly to changes in other abiotic parameters that are mediated indirectly through changes in the distribution and abundance of their hosts. Local extirpations and introductions may be expected as a result. In the long term, climatic change may influence selection of different life-history traits, affecting parasite transmission and, potentially, virulence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".