Growth variation in the endangered fish <scp><i>Zingel asper</i></scp>: Contribution of substrate quality, hydraulics, prey abundance, and water temperature
Bibliographic record
Abstract
Abstract Intraspecific variation in life histories and its environmental correlates can indicate the degree of vulnerability to extinction of endangered taxa and guide conservation actions. Zingel asper (Percidae) is an endangered fish endemic to the Rhône catchment (France and Switzerland), where five populations subsist in separate river systems (Loue, Beaume, Durance, Verdon, and Doubs). Two populations of Z. asper differ in growth and longevity, but the existence of broader intraspecific differentiation in life histories and the environmental origins of this variation (if any) remain unknown. The age structure and growth profile of four populations of Z. asper (Loue, Beaume, Durance, and Verdon) and nine additional sub‐populations within the Durance system were determined by scale‐reading analysis, before evaluating the contribution of measured variation in substrate quality, hydraulics, prey availability, and water temperature to growth differentiation among and within populations. A trade‐off between early growth and longevity largely differentiated the populations of Z. asper along a slow (i.e. slower growth, smaller adult size, longevity of >5 years) to fast (i.e. faster growth, larger adult size, longevity of <4 years) continuum of life histories. This continuum differentiated populations from different river catchments along a south (Durance, Verdon) to north (Beaume, Loue) latitudinal gradient, and mapped onto an upstream–downstream gradient of sub‐populations within the Durance system. Differences in prey availability, hydraulics, and water temperature explained most of the growth variation among populations from different catchments, whereas local variation in prey availability, substrate quality, and water temperature mostly contributed to within‐river growth differentiation. These results indicate that short life cycles strongly expose all populations of Z. asper to extirpation and should motivate additional conservation actions. This study illustrates how quantifying intraspecific variation in life histories and its sensitivity to ecological context can reliably assess extinction risk and guide conservation actions by identifying endangered populations requiring priority management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".