Diets and growth potential of early stage larval yellow perch and alewife in a nearshore region of southeastern Lake Michigan
Bibliographic record
Abstract
Transition from endogenous to exogenous feeding is thought to be a critical period for many fish larvae, when prey availability (type, size, and density) and ambient physical conditions (e.g., temperature, water clarity) can strongly influence survival. In Lake Michigan, two important fish species, yellow perch (Perca flavescens) and alewife (Alosa pseudoharengus), hatch and, presumably, begin exogenously feeding in the nearshore zone, an area characterized by short-term variation in environmental conditions. During 2010-2011, we examined environmental conditions and spatial and temporal distributions of larval yellow perch, larval alewife, and their potential prey in a nearshore region of southeastern Lake Michigan. To consider implications of environmental conditions on larval fish habitat quality, we quantified diet contents of young larval yellow perch and alewife and modeled bioenergetic growth rate potential (an index of habitat quality) under observed and predicted prey consumption scenarios. As expected, in this dynamic nearshore zone temperatures, light levels, zooplankton prey availability, and resulting growth rate potential were highly variable. Many larval fish digestive tracts were empty, suggesting that starvation may affect cohort survival. Among early-feeding larval fish, relatively small diet items were common, with larval alewives consuming diatoms and larval yellow perch consuming veligers of invasive dreissenid mussels. Though the mechanisms underlying such prey consumption and the consequences of ingesting these prey items remain largely unexplored, our results suggest dreissenid mussel veligers present early-feeding larvae with a relatively abundant prey source that may partially offset the apparent low consumption of other prey sources within Lake Michigan’s nearshore region.
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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 | 0.000 |
| 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 | 0.000 |
| 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 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".