Investigations of Lake Trout Salvelinus namaycush Ecology and Behaviour in Relation to Fragmented Thermal Habitats to Inform a Multifaceted Management Strategy
Bibliographic record
Abstract
Freshwater ecosystems have been experiencing rapid changes including altered thermal habitats.Natural processes and manmade disturbances can fragment and disrupt thermal habitats that can be detrimental to freshwater organisms.Thermal habitats are one of the largest drivers of biological processes for fish because they influence physiological mechanisms that dictate movement and behaviour, growth, reproduction, and survival.Lake Trout (Salvelinus namaycush) are a cold-water fish that inhabits oligotrophic ecosystems in northern North America.The species holds cultural, ecological, and economic value as it facilitates several ecological processes and supports subsistence, indigenous, recreational, and commercial fisheries.However, as alterations to thermal habitats occur, Lake Trout populations might experience declines in population health, affecting ecosystem stability and the sustainability of fisheries.The overall goal of my thesis was to gain knowledge on how changing thermal habitats influence the movement and behaviours, trophic relationships, growth, reproduction, and bioenergetics of Lake Trout.My thesis studied Lake Trout in a complex multibasin lake in western Quebec, Canada.Acoustic telemetry, stable isotope analysis, diet analysis, growth structures, and bioenergetic models, were used to meet the goals of my thesis.Lake Trout were captured for biological sampling and transmitter implantation and released near the site of capture within their capture basin.My observations suggest thermal habitats become seasonally fragmented forcing Lake Trout to limit movement to their capture basin.Depending on their capture basin, thermal habitats might be limited causing the use of suboptimal habitats (≥ 10°C).Changes in thermal habitat use resulted in reduced movement and feeding on pelagic and/or benthic food more than littoral sources.Pelagic and benthic food sources, in the study system, are limited to low energy sources (e.g., zooplankton and aquatic insects).Furthermore, iv constrained movement resulted in reduced energetic costs (i.e., lower active metabolism) that could be beneficial for Lake Trout.However, if food quality is poor, then an individual might expend more energy feeding to meet basic requirements thus, potentially affecting survivorship, growth rates, and reproductive capacity.My observations indicated that the size and availability of thermal habitats drives energy transfer in this freshwater ecosystem potentially having compounding consequences for Lake Trout and the ecosystem.In the context of management, incorporating methodologies and mitigation tactics to ensure thermal habitat stability could assist in maintaining Lake Trout populations and sustainable fisheries.v
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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 | 0.000 | 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".