Movement of an imperiled esocid fish in an agricultural drain
Bibliographic record
Abstract
Abstract Animal movement is increasingly affected by human alterations to habitat and climate change. In wetland systems, widespread hydrologic alterations from agriculture have changed the shape, function, and stability of shallow streams and wetland habitats. These changes in habitat quality and quantity may be especially consequential for freshwater fishes such as Grass Pickerel ( Esox americanus vermiculatus ), a small predatory fish found in disjunct populations across southern Ontario and listed as Special Concern under Canada’s Species at Risk Act . To characterize Grass Pickerel movement response to stream-channel alterations, Fisheries and Oceans Canada implemented a tracking study to monitor the movements of a Grass Pickerel population in an agricultural drain on the Niagara Peninsula (Ontario, Canada). From 2009 to 2013, 2007 Grass Pickerel were tagged and tracked in the 37.3 km 2 Beaver Creek watershed using a combination of mark-recapture surveys and eight fully automated passive integrated transponder tag antennas. Most individuals moved within 500 m (i.e., stationary fish) while 16% of the fish moved > 500 m (i.e., mobile fish), with a maximum median movement distance of 1.89 km and a maximum movement distance of 13.5 km (a long-tail distribution). Most movements occurred near the largest confluence where only a few were long-distance upstream or downstream movements. Mobile fish were larger than their stationary counterparts. Grass Pickerel in sites with higher abundance had more mobile fish, implying potential density dependence. Our results highlight that, while a long-distance dispersal ability exists in extant Grass Pickerel populations, the current conditions of riverscapes may prevent these dispersals from occurring. For declining Grass Pickerel populations, limitations to their movement ecology may substantially increase the likelihood of local extirpations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".