Identifying temporal bottlenecks for the conservation of large-bodied fishes: Lake Sturgeon (Acipenser fulvescens) show highly restricted movement and habitat use over-winter
Bibliographic record
Abstract
The relationship between species’ size and home range size has been well studied. In practice, home range may provide a good surrogate of broad spatial coverage needed for species conservation, however, many species can show restricted movement during critical life stages, such as breeding and over-wintering. This suggests the existence of either a behavioral or habitat mediated ‘temporal bottleneck,’ where restricted or sedentary movement can make populations more susceptible to harm during specific life stages. Here, we study over-winter movement and habitat use of Lake Sturgeon ( Acipenser fulvescens ), the largest freshwater fish in North America. We monitored over-winter movement of 86 fish using a hydro-acoustic receiver array in the South Saskatchewan River, Canada. Overall, 20 fish remained within our study system throughout the winter. Lake Sturgeon showed strong aggregation and sedentary movement over-winter, demonstrating a temporal bottleneck. Movement was highly restricted during ice-on periods (ranging from 0.9 km/day in November and April to 0.2 km/day in mid-November to mid-March), with Lake Sturgeon seeking deeper, slower pools. We also show that Lake Sturgeon have strong aggregation behavior, where distance to conspecifics decreased (from 575 to 313 m) in preparation for and during ice-on periods. Although the Lake Sturgeon we studied had access to 1100 kilometers of unfragmented riverine habitat, we show that during the over-winter period Lake Sturgeon utilized a single, deep pool (<0.1% of available habitat). The temporal discrepancy between mobile and sedentary behaviors in Lake Sturgeon suggest adaptive management is needed with more localized focus during periods of temporal bottlenecks, even for large-bodied 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".