Spatial and temporal variability in the diet of Pacific marten (<i>Martes caurina</i>) on Haida Gwaii: an apex predator in a highly modified ecosystem
Bibliographic record
Abstract
Knowledge of the diet ecology of apex predators in insular island ecosystems has direct applications to the conservation of endemic species at risk of extinction. We used stable isotopes of carbon and nitrogen to infer resource-use strategies of an indigenous predator, the Pacific marten (Martes caurina (Merriam, 1890)), in a highly modified ecosystem on Haida Gwaii, British Columbia, Canada. We used Bayesian isotopic mixing models to estimate the relative contributions of different food sources to marten diet across seasons and during overall lifetime, and to determine how diet varied with different levels of access to marine resources. Isotopes of carbon and nitrogen measured in hair and muscle tissue suggested that marten consumed salmon (3%–17%) and berries (25%–37%) seasonally; these diet groups were relatively minor components of the lifetime diet. Analysis of bone collagen suggested that terrestrial fauna — including birds, deer, small mammals, and invertebrates — contributed the most to diet (41%–55%), and marine invertebrates (38%–48%), not salmon (0%–3%), were the main allochthonous marine nutrient subsidy to lifetime diet. Plasticity in foraging ecology, combined with a broad dietary niche, introduced prey, notably the invasive Sitka black-tailed deer (Odocoileus hemionus sitkensis Merriam, 1898), as well as abundant marine resources, may allow marten to outcompete other indigenous and endemic carnivores on Haida Gwaii.
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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 | 0.001 | 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) | 0.000 | 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 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".