A Life History Model for Peppered Chub, a Broadcast‐Spawning Cyprinid
Bibliographic record
Abstract
Abstract We estimated age‐specific fecundity and survival rates for peppered chub Macrhybopsis tetranema from the Canadian River, New Mexico and Texas. We used these estimates to construct a life history matrix model that assumed age‐0 survival was related to river discharge. Model predictions agreed well with the observed abundance of peppered chub for the 6‐year period from 1996 to 2001. Based on the Akaike information criterion, this model received greater support from observed catches of peppered chub than did two alternative null models (one null model assumed a static or fixed population and the other assumed a population with a constant growth rate over the 6‐year study period). Elasticity analysis showed that the peppered chub population growth rate was most sensitive to changes in age‐0 survival (elasticity = 0.48) and age‐1 fecundity (elasticity = 0.44). We performed sensitivity simulations to determine the effect of parameter uncertainty on the observed elasticities. Based on 1,000 simulations, we found that the peppered chub population growth rate was most sensitive to age‐0 survival and age‐1 fecundity and was robust with respect to uncertainty in our estimates of these parameters. Our model accurately predicts changes in peppered chub abundance based on river discharge and provides a mechanistic explanation for previous anecdotal observations indicating that the reproductive success of peppered chub is related to river discharge.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".