Squeezed by a habitat split: Warm ocean conditions and old‐forest loss interact to reduce long‐term occupancy of a threatened seabird
Bibliographic record
Abstract
Abstract Theory predicts that species requiring multiple habitat types simultaneously should have heightened sensitivity to anthropogenic pressures, yet tests of this prediction are especially rare. We tested whether breeding site occupancy of the threatened marbled murrelet ( Brachyramphus marmoratus ) was driven by the synergistic effects of nesting habitat loss in forests, and changing ocean conditions. We paired 70,700 murrelet surveys at 19,837 sites across 20 years from the Oregon Coast Range with annual data on the extent of old forest and biophysical ocean conditions. Dynamic occupancy models indicated that local murrelet colonization rates were strongly reduced during warm ocean conditions with low prey availability. Landscapes that contained more old forest and were closer to the ocean showed reduced rates of local extinction. Given predictions of accelerated ocean warming and increased global timber demand, our results suggest murrelets may continue to be imperiled by deterioration of the two habitats upon which they depend.
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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 | 0.000 | 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 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".