Daytime depth and thermal habitat of two sympatric krill species in response to surface salinity variability in the Gulf of St Lawrence, eastern Canada
Bibliographic record
Abstract
Abstract Plourde, S., McQuinn, I. H., Maps, F., St-Pierre, J-F., Lavoie, D., and Joly, P. 2014. Daytime depth and thermal habitat of two sympatric krill species in response to surface salinity variability in the Gulf of St Lawrence, eastern Canada. – ICES Journal of Marine Science, 71: 272–281. We describe the response of acoustically determined weighted mean depth (WMD) of two sympatric species of krill, Thysanoessa raschii and Meganyctiphanes norvegica, to variations in surface salinity during summer in the Gulf of St Lawrence. In this coastal system, non-living particulates and CDOM carried by the freshwater run-off of the St Lawrence River and several large rivers have a strong impact on turbidity and light attenuance in the surface layer. The WMD of T. raschii and M. norvegica were significantly and positively related to surface salinity. However, M. norvegica was found deeper and in warmer water than T. raschii, and the latter had a steeper response to surface salinity. The species-specific relationships between daytime WMD and surface salinity enabled us to estimate both species regional and interannual variations in summertime temperature habitat during a 21-year period (1991–2011). The variability in daytime WMD resulted in significant inter- and intraspecific differences in the temperature experienced by adult krill that may impact development, growth, and reproduction. Our study illustrated the importance of considering species-specific responses to environmental forcing in coupled biophysical models that aim to explore the impacts of environmental variations on krill dynamics.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".