Range-wide age and growth characteristics of shovelnose sturgeon from mark–recapture data: implications for conservation and management
Bibliographic record
Abstract
We used mark–recapture data from shovelnose sturgeon (Scaphirhynchus platorynchus) to describe range-wide growth characteristics and developed a model to estimate ages. Data were solicited throughout much of the current distribution of shovelnose sturgeon, specifically from the mainstem Missouri and Mississippi rivers and their tributaries. Shovelnose sturgeon exhibited variable growth among locations; however, adult fish exhibited almost no growth after they reached a particular size, presumably the size at sexual maturity. Shovelnose sturgeon from the Mississippi River basin attained greater maximum sizes and ages compared with the Missouri River basin. However, two populations from the Mississippi River that received high exploitation from commercial harvest had truncated age distributions with smaller asymptotic lengths. Lower Missouri River populations were characteristic of exploited populations (i.e., smaller fish and reduced longevity), presumably a result of anthropogenic effects. Wide discrepancies in maximum age and size suggest shovelnose sturgeon are capable of displaying phenotypic plasticity in response to exploitation or environmental influences. Determining metapopulation dynamics is a priority because it is unknown how population connectivity may influence dynamic rate functions and persistence of large-river fishes. Identifying potential source–sink connections in terms of population dynamics may provide a template for direction of future restoration and recovery efforts.
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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 | 0.002 |
| 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 | 0.001 |
| 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".