Global change effects on the long‐term feeding ecology and contaminant exposures of <scp>E</scp>ast <scp>G</scp>reenland polar bears
Bibliographic record
Abstract
Rapid climate changes are occurring in the Arctic, with substantial repercussions for arctic ecosystems. It is challenging to assess ecosystem changes in remote polar environments, but one successful approach has entailed monitoring the diets of upper trophic level consumers. Quantitative fatty acid signature analysis (QFASA) and fatty acid carbon isotope (δ(13) C-FA) patterns were used to assess diets of East Greenland (EG) polar bears (Ursus maritimus) (n = 310) over the past three decades. QFASA-generated diet estimates indicated that, on average, EG bears mainly consumed arctic ringed seals (47.5 ± 2.1%), migratory subarctic harp (30.6 ± 1.5%) and hooded (16.7 ± 1.3%) seals and rarely, if ever, consumed bearded seals, narwhals or walruses. Ringed seal consumption declined by 14%/decade over 28 years (90.1 ± 2.5% in 1984 to 33.9 ± 11.1% in 2011). Hooded seal consumption increased by 9.5%/decade (0.0 ± 0.0% in 1984 to 25.9 ± 9.1% in 2011). This increase may include harp seal, since hooded and harp seal FA signatures were not as well differentiated relative to other prey species. Declining δ(13) C-FA ratios supported shifts from more nearshore/benthic/ice-associated prey to more offshore/pelagic/open-water-associated prey, consistent with diet estimates. Increased hooded seal and decreased ringed seal consumption occurred during years when the North Atlantic Oscillation (NAO) was lower. Thus, periods with warmer temperatures and less sea ice were associated with more subarctic and less arctic seal species consumption. These changes in the relative abundance, accessibility, or distribution of arctic and subarctic marine mammals may have health consequences for EG polar bears. For example, the diet change resulted in consistently slower temporal declines in adipose levels of legacy persistent organic pollutants, as the subarctic seals have higher contaminant burdens than arctic seals. Overall, considerable changes are occurring in the EG marine ecosystem, with consequences for contaminant dynamics.
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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 | 0.000 | 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".