Bigmouth Buffalo (<i>Ictiobus cyprinellus</i>) migratory behaviour and seasonal home range overlap are functions of geographic space in a fragmented riverscape
Bibliographic record
Abstract
In temperate rivers, where environmental conditions vary seasonally, many fishes migrate among summer, spawning, and winter habitats. Dams disrupt these migrations, limiting access to habitat and potentially affecting populations. Bigmouth Buffalo ( Ictiobus cyprinellus) is a species of fish with at-risk populations in central Canada. The impact of dams on the extent of Bigmouth Buffalo migration and the overlap between summer and winter home ranges is unknown. Here, we assessed the migratory history of 80 Bigmouth Buffalo tagged with acoustic transmitters in the Red River (USA and Canada), a large binational waterway regulated by semi-passable dams. We sought to understand when and why Bigmouth Buffalo migrate, and how river use varies seasonally. Following more than 6 years of data collection, we found that the degree and probability of overlap between winter and summer home ranges varied by river section between barriers. Importantly, overlap was lowest in the longest continuous river section where well-defined migratory behaviours were observed. The results of this study reveal previously unknown details about Bigmouth Buffalo migration, demonstrate the consequences of river fragmentation on geographic space use, and highlight the importance of river connectivity to fish migration.
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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 | 0.000 |
| 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".