Changes in prey, turbidity, and competition reduce somatic growth and cause the collapse of a fish population
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Somatic growth exerts strong control on patterns in the abundance of animal populations via effects on maturation, fecundity, and survival rates of juveniles and adults. In this paper, we quantify abiotic and biotic drivers of rainbow trout growth in the Colorado River, Arizona, USA, and the resulting impact on spatial and temporal variation in abundance. Inferences are based on ~10,000 observations of individual growth rates obtained through an intensive mark–recapture effort conducted over 5 yrs (2012–2016) in a 130‐km long study segment downstream of Glen Canyon Dam. Prey availability, turbidity‐driven feeding efficiency, and intraspecific competition were the dominant drivers of rainbow trout growth. Discharge, water temperature, and solar insulation were also evaluated but had a smaller influence. Mixed‐effect models explained 79–82% of the variability in observed growth rates, with fixed covariate effects explaining 79–87% of the total variation in growth parameters across five reaches and 18 quarterly sampling intervals. Reductions in growth owing in part to a phosphorous‐driven decline in prey availability, led to a substantive loss in mass and poor fish condition. This in turn lowered survival rates and delayed maturation, which led to a rapid decline in abundance and later recruitments. Reductions in feeding efficiency, due to episodic inputs of fine sediment from tributaries, and warmer water temperatures, contributed to reduced growth in downstream reaches, which led to more severe declines in abundance. Somatic growth rates increased following the population collapse due to reduced competition, and in the absence of substantive increases in prey availability. Our study elucidates important linkages between abiotic and biotic factors, somatic growth, and vital rates, and demonstrates how variation in somatic growth influences temporal and spatial patterns in abundance.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it