Mechanisms by which marine heatwaves affect seabirds
Bibliographic record
Abstract
Marine heatwaves (MHWs) are characterized by periods of extreme warming of local to basin-scale marine habitat. Effects of MHWs on some seabirds (e.g. mass die-offs) are well documented, but mechanisms by which seabirds respond to MHWs remain poorly understood. Following from a symposium at the 3rd World Seabird Conference, this Theme Section presents recent research to address this knowledge gap. Studies included here spanned one or more MHW event, at spatial scales from individual seabird colonies to large marine ecosystems in subtropical, temperate, and polar oceans, and over timespans from months to decades. The findings summarized herein indicate that MHWs can affect seabirds directly by creating physiological heat stress that affects behavior or survival, or indirectly by disrupting seabird food webs, largely by altering metabolic rates in ectothermic prey species, leading to effects on their associated predators and prey. Four main mechanisms by which MHWs affect seabirds are (1) habitat modification, (2) physiological forcing, (3) behavioral responses, and (4) ecological processes or species interactions. Most seabird species have experienced limited effects from MHWs to date, owing to ecological and behavioral adaptations that buffer MHW effects. However, the intensity and frequency of MHWs is increasing due to global warming, and more seabird species may have difficulty coping with future heatwave events. Also, MHW impacts can persist for years after a MHW ends, so consequences of recent or future MHWs could continue to unfold over time for many long-lived seabird species.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".