Halocline Behavior and Salinity Preference in the Estuarine Teleost Fish, the Mummichog ( <i>Fundulus heteroclitus</i> )
Bibliographic record
Abstract
Mummichogs prefer seawater but have wide ability to acclimate to extreme temperatures and salinities and spawn in dilute brackish water. Haloclines are common features of estuaries, but how fish react to them is not known. The objective was to reveal how mummichogs select microhabitats in the estuary and whether haloclines were a major feature affecting behavior. In the field, minnow trapping revealed that mummichogs move progressively into low salinity warmer water during early spring after ice melt and show significant aversion to colder temperatures and high salinity. First appearance in estuarine shallows occurred above 10 ºC and catch increased to 21 ºC over four weeks. Threespine stickleback ( Gasterosteus aculeatus ) also preferred warmer low salinity locations, but preferred slow moving streams, whereas mummichogs preferred tidal ponds. In the laboratory, artificial haloclines were made to test isothermal salinity preference, between 28 ‰ full strength seawater (SW, below) and 10 % SW (3.0 ‰, above). Mummichogs of both sexes acclimated to 5 ºC in SW strongly preferred SW. Surprisingly, freshwater (0 % SW) acclimated mummichogs at 21 ºC also preferred SW. In sexually mature fish acclimated to 21 ºC SW, only the males preferred SW; the females showed no significant preference for SW, meaning they freely entered low salinity. SW preference was manifested by a stereotypic passive aversion to the dilute upper layer at the halocline. We conclude that the overall movement of mummichogs into summer breeding grounds of low salinity is driven by maturation of females and their preference for warmer water (regardless of salinity) that overcomes the general tendency of the immature and male fish to avoid dilute waters. Support or Funding Information Supported by NSERC Discovery Grant RGPIN3698‐2009 to WSM and UCR scholarship to JCT.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".