Abiotic and biotic associations between the round goby<scp><i>Neogobius melanostomus</i></scp>and tubenose goby<scp><i>Proterorhinus marmoratus</i></scp>with the endangered northern madtom<scp><i>Noturus stigmosus</i></scp>in Canada
Bibliographic record
Abstract
Abstract Quantifying habitat associations and threats to the persistence of imperilled species is a fundamental step for initiating species recovery efforts, but the traits associated with species imperillment (e.g. rarity and vulnerability to stressors) also limit the ability to empirically inform recovery strategies. Novel sampling designs and modelling approaches are therefore needed to quantitatively assess habitat associations and the threats to species persistence. To improve the understanding of habitat associations and threats for one of the rarest endangered freshwater fish species in Canada, northern madtom (Noturus stigmosus), two‐species occupancy models were developed with two invasive gobies: round goby (Neogobius melanostomus) and tubenose goby (Proterorhinus marmoratus). Models were parameterized with data from a multi‐year benthic trawling survey of two large Great Lakes tributaries in southern Ontario, Canada, and subsequently used to evaluate the need for reducing measurement error with future sampling efforts. The probability of detecting northern madtom in the St. Clair (0.163) and Thames (0.194) rivers was low compared with round goby (St. Clair, 0.827; Thames, 0.833) and tubenose goby (St. Clair, 0.297). The best occupancy models indicated a negative association between northern madtom and round goby in the St. Clair River and the importance of gravel substrate for northern madtom. Up to 16 repeated non‐detections using benthic trawls are needed to be 95% confident that northern madtom is absent at a site, indicating that current sampling approaches are likely inadequate. Despite low detection probabilities, intensive trawling surveys combined with the two‐species occupancy modelling framework provided vital information for describing habitat associations for northern madtom and identified a significant negative association with round goby. Nonetheless, alternative sampling methods to improve the detection probability of northern madtom would allow a more robust evaluation of habitat associations and would provide more information on the negative association with round goby.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".