Biological Investigation of the Endangered Northern Madtom in the North Channel St. Clair River
Bibliographic record
Abstract
Abstract Aquatic organisms and the habitats they live in are declining globally, yet managers often lack even basic biological information for individual imperiled species. This makes assessment of the current status, management needs, and recovery targets for these species challenging. One such organism is the Northern Madtom Noturus stigmosus, a small, bottom-dwelling catfish of the family Ictaluridae. Northern Madtom are listed as endangered in the state of Michigan and the province of Ontario, with only a handful of isolated populations known in each region. To address life history uncertainties and to provide fisheries managers with baseline information to inform decision making, the Michigan Department of Natural Resources annually sampled Northern Madtom in the St. Clair River using minnow traps and amassed the largest known data set for this species. We handled 871 individuals from 2010 to 2022, with yearly catch rates ranging from 0.17 to 1.33 individuals/trap. Age estimates derived from otoliths and dorsal spines of 17 individuals showed no clear pattern of bias, indicating that nonlethally collected dorsal spines provide a suitable age estimation method. We developed an age–length key to assign ages to all individuals in our data set, calculated growth parameters, and determined that annual mortality rates across all ages ranged from 46% to 69%. Diet analysis revealed that caddisfly (order Trichoptera) larvae were the dominant prey item and fecundity averaged 178 eggs/female. We compared microsatellite allele frequencies and mitochondrial DNA haplotypes among samples collected in the St. Clair River and the Detroit River. Significant evidence of genetic structure was present, indicating limited gene flow and suggesting that separate management of these two populations may be warranted. Collectively, these data provide context for managers interested in the development of biological reference points and planning for the conservation and management of this species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".