Early mortality and freshwater forage fish recruitment: nonnative alewife and native rainbow smelt interactions in Lake Champlain
Bibliographic record
Abstract
We studied the consequences of a nonnative species introduction and changes in temperature on early mortality and recruitment of native rainbow smelt (Osmerus mordax) and nonnative alewife (Alosa pseudoharengus) in Lake Champlain using a simulation model. Distribution patterns of adults and young-of-the-year (YOY) fish were predicted using a model based on observed distribution of different age groups as a function of temperature and light profiles simulated on a daily basis. Mortality rates averaged over the growing season were calculated as a function of fish densities and overlap between adults and YOY. Survival of YOY rainbow smelt and alewife depended on which predator was most abundant. Rainbow smelt YOY mortality rates are highest when rainbow smelt adults are abundant, and alewife YOY mortality rates are highest when alewife adults are abundant, potentially allowing coexistence. August and September mortality rates were higher in the climate change scenario because of increased overlap of adults and YOY of both species. These results indicate that accounting for spatiotemporal fish distribution patterns can be important when forecasting the interacting effects of climate change and aquatic invasive species on fish recruitment.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".