Comparing trophic structure and diversity in northern ecosystems using stable isotope data
Bibliographic record
Abstract
No abstracts are to be cited without prior reference to the author.Change in trophic level of catches has become a key indicator of fisheries impact, ecosystem structure and health. Whether because of fishing pressure, climate change or other sources to physical or biological changes in an ecosystem, we propose to use isotope metrics in comparing key species and functional groups in ecosystems across the northern hemisphere. Layman et al. (2007) suggested an interesting approach for using stable isotopes in community-wide measures to represent a species trophic role based on a bi-plot of δ13C – δ15N where they proposed 6 different metrics of food-web properties. As a case study, we attempt to use the approach of Layman to compare two northern ecosystems in Norway (Sørfjord (Nilsen et al. 2008) and Ullsfjord) with American Georges Bank (Fry 1988) and Newfoundland Labrador (Sherwood and Rose 2005) using stable isotope data. The systems exhibit similar physical and biological properties and share many of the same species.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".