Coupling age-structured stock assessment and fish bioenergetics models: a system of time-varying models for quantifying piscivory patterns during the rapid trophic shift in the main basin of Lake Huron
Bibliographic record
Abstract
We quantified piscivory patterns in the main basin of Lake Huron during 1984–2010 and found that the biomass transfer from prey fish to piscivores remained consistently high despite the rapid major trophic shift in the food webs. We coupled age-structured stock assessment models and fish bioenergetics models for lake trout (Salvelinus namaycush), Chinook salmon (Oncorhynchus tshawytscha), walleye (Sander vitreus), and lake whitefish (Coregonus clupeaformis). The model system also included time-varying parameters or variables of growth, length–mass relations, maturity schedules, energy density, and diets. These time-varying models reflected the dynamic connections that a fish cohort responded to year-to-year ecosystem changes at different ages and body sizes. We found that the ratio of annual predation by lake trout, Chinook salmon, and walleye combined with the biomass indices of age-1 and older alewives (Alosa pseudoharengus) and rainbow smelt (Osmerus mordax) increased more than tenfold during 1987–2010, and such increases in predation pressure were structured by relatively stable biomass of the three piscivores and stepwise declines in the biomass of alewives and rainbow smelt. The piscivore stability was supported by the use of alternative energy pathways and changes in relative composition of the three piscivores. In addition, lake whitefish became a new piscivore by feeding on round goby (Neogobius melanostomus). Their total fish consumption rivaled that of the other piscivores combined, although fish were still a modest proportion of their diet. Overall, the use of alternative energy pathways by piscivores allowed the increases in predation pressure on dominant diet species.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".