Growth rates of rainbow smelt in Lake Champlain: effects of density and diet
Bibliographic record
Abstract
Stritzel Thomson JL, Parrish DL, Parker‐Stetter SL, Rudstam LG, Sullivan PJ. Growth rates of rainbow smelt in Lake Champlain: effects of density and diet. Ecology of Freshwater Fish 2010. © 2010 John Wiley & Sons A/S Abstract – We estimated the densities of rainbow smelt ( Osmerus mordax ) using hydroacoustics and obtained specimens for diet analysis and groundtruthed acoustics data from mid‐water trawl sampling in four areas of Lake Champlain, USA–Canada. Densities of rainbow smelt cohorts alternated during the 2‐year study; age‐0 rainbow smelt were very abundant in 2001 (up to 6 fish per m 2 ) and age‐1 and older were abundant (up to 1.2 fish per m 2 ) in 2002. Growth rates and densities varied among areas and years. We used model selection on eight area–year‐specific variables to investigate biologically plausible predictors of rainbow smelt growth rates. The best supported model of growth rates of age‐0 smelt indicated a negative relationship with age‐0 density, likely associated with intraspecific competition for zooplankton. The next best‐fit model had age‐1 density as a predictor of age‐0 growth. The best supported models ( N = 4) of growth rates of age‐1 fish indicated a positive relationship with availability of age‐0 smelt and resulting levels of cannibalism. Other plausible models were contained variants of these parameters. Cannibalistic rainbow smelt consumed younger conspecifics that were up to 53% of their length. Prediction of population dynamics for rainbow smelt requires an understanding of the relationship between density and growth as age‐0 fish outgrow their main predators (adult smelt) by autumn in years with fast growth rates, but not in years with slow growth rates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".