Movement behaviour of endangered white sturgeon Acipenser transmontanus responds to changing environmental conditions below a dam
Bibliographic record
Abstract
Acoustic telemetry allows for fine-scale, or positional, tracking of fish in localised environments, and advancement in analytical techniques allows for quantifiable patterns in fish movement and behaviour. White sturgeon Acipenser transmontanus in the regulated Upper Columbia River are listed as endangered in Canada due to their considerable decline over the last century. An improved understanding of where, when, and why white sturgeon move in relation to river regulation is important for species recovery. A VEMCO Positioning System was used to collect the positions of white sturgeon in critical habitats immediately downstream of a dam on the Upper Columbia River over a 1 yr period. We applied hidden Markov models and generalised linear mixed models to (1) identify ecologically meaningful movement behaviours within the positions dataset; and (2) investigate the relationships between movement behaviour and biological (sex) and environmental (e.g. discharge, temperature, habitat) factors. Two behaviour states were identified: ‘residential’, characterised by short movements with less frequent turns, and ‘exploratory’, characterised by longer movements with more frequent turns. Water temperature largely influenced the mean weekly probability of a behaviour state, while discharge influenced the spatial distribution of movement behaviours. Changes in movement patterns were also apparent across seasons, with a higher occurrence of residential behaviour in the winter and spring and exploratory behaviour in the summer and fall. Results will help inform species recovery measures, such as overall flow management and optimization of operations to reduce impacts of river regulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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; both teacher heads agree on what is shown here.
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".