Empirical evaluation of predator-driven diel vertical migration in Lake Superior
Bibliographic record
Abstract
Recent studies on Lake Superior suggest that diel vertical migration (DVM) of prey (generalized Coregonus spp.) may be influenced by the density of predatory siscowet ( Salvelinus namaycush ). We empirically evaluated this hypothesis using data from acoustic, midwater trawl, and bottom trawl sampling at eight Lake Superior sites during three seasons in 2005 and a subset of sites in 2006. We expected the larger-bodied cisco ( Coregonus artedi ) to exhibit a shallower DVM compared with the smaller-bodied kiyi ( Coregonus kiyi ). Although DVM of kiyi and cisco were consistent with expectations of DVM as a size-dependent, predator-mediated process, we found no relationship between siscowet density and the magnitude of DVM of either coregonid. Cisco appear to have a size refuge from siscowet predation. Kiyi and siscowet co-occur in demersal habitat > 150 m during the day, where visual predation is unlikely, suggesting predator avoidance is not a factor in the daytime distribution of kiyi. Seasonal patterns of kiyi DVM were consistent with reported DVM of their primary prey Mysis relicta . Our results suggest that consideration of nonvisual foraging, rather than light-based foraging theory (i.e., the antipredation window), is necessary to understand the processes driving DVM in deepwater systems.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".