Geographic variability in the seasonality of euphausiid diel vertical migrations among three locations in coastal British Columbia, Canada
Bibliographic record
Abstract
Abstract Diel vertical migration (DVM) is a behaviour observed across zooplankton taxa in marine and limnetic systems worldwide. DVM influences biogeochemical cycling and carbon drawdown in oceanic systems and alters prey availability for zooplanktivorous species. DVM has been well studied among zooplankton, and many exogenous and endogenous triggers as well as adaptive significances have been hypothesized. However, second-order variability in DVM timing, the deviation of DVM times to respective dawn and dusk times throughout the year, is a less-studied phenomenon that can help identify the factors influencing migration timing as well as demonstrate the changes of DVM behaviours within and across systems. Here, we quantified seasonal trends in second-order variability of DVM timing of euphausiids at Brooks Peninsula, Clayoquot Canyon, and Saanich Inlet near Vancouver Island, British Columbia, Canada, over multiple years using upward-facing moored echosounders. We used generalized additive mixed models to characterize this seasonality. DVM timing relative to civil twilight times showed strong seasonality at all locations, with euphausiids remaining near the surface longer than expected in spring and summer, and shorter than expected in winter. Euphausiids spent less time near the surface at Brooks Peninsula and Clayoquot Canyon than at Saanich Inlet throughout the year. Increased primary productivity in Saanich Inlet, which reduced light penetration and hid euphausiids from visual predators, likely drove this difference. Our findings confirm that proper understanding of DVM behaviours must account for seasonal variability due to context-specific oceanographic and ecological parameters. This is particularly pertinent when attempting to model the biogeochemical or predator–prey interactions influenced by DVM behaviours.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".