Lake shape predicts the degree of habitat coupling in Canadian Shield Lakes
Bibliographic record
Abstract
This thesis discriminates between two hypotheses that predict the degree of habitat coupling by mobile predators across a gradient of lake shape. In lake ecosystems, mobile predators forage among littoral and pelagic food chains, thereby coupling habitats historically considered to be isolated. Few studies have explored the mechanisms that determine the degree of habitat coupling by mobile predators. Herein I demonstrate that lake shape--via complexity--consistently predicts the degree of littoral habitat coupling by a mobile predator, lake trout ('Salvelinus namaycush') in seven Canadian Shield Lakes. Using lake trout isotopic diet data among lakes (i.e., circular to highly complex in shape) find lake trout to be more reliant on littorally derived energy in circular lakes (i.e., littoral diet comprised 11% compared to 24% in complex and circular lakes, respectively). I end by proposing a mechanism to explain this result, highlighting that habitat complexity negatively correlates to lake trout prey accessibility via thermal refugia.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".