Trophic adaptation of large terrestrial omnivores to global change
Bibliographic record
Abstract
Large omnivores at the top of food webs play a key role in ecosystems, as their ability to feed on multiple trophic levels stabilizes food-web dynamics and impacts ecosystem functioning. However, it is largely unexplored how large omnivores adapt their trophic interactions to altered resource availability under global change, particularly in terrestrial ecosystems. Here, we combine macroecological and paleoecological approaches and reveal that extant bears, the largest terrestrial omnivores, adapt their trophic position in food webs dynamically to net primary productivity and growing season length. Throughout their geographic ranges, extant bears occupy higher trophic positions in unproductive ecosystems with short growing seasons than in productive ecosystems with long growing seasons. Consistent with this geographic pattern, the trophic position of the brown bear sharply decreased at the transition from the Late Pleistocene to the Holocene, coinciding with an increase in net primary productivity and growing season length. These findings demonstrate that trophic interactions of omnivores are not static but change dynamically in response to environmental change. Our findings suggest that global change impacts on primary production and vegetation seasonality may trigger shifts in the functional role of omnivores, with consequences for food webs and ecosystem functions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".