Striking centennial-scale changes in the population size of a threatened seabird
Bibliographic record
Abstract
Many animal populations are under stress and declining. For numerous marine bird species, only recent or sparse monitoring data are available, lacking the appropriate temporal perspective needed to consider natural, long-term population dynamics when developing conservation strategies. Here, we use a combination of established palaeoenvironmental approaches to examine the centennial-scale dynamics of the world's largest colony (representing approx. 50% of the global population) of the declining and vulnerable Leach's Storm-petrel (Hydrobates leucorhous). By reconstructing the last approximately 1700 years of the colony's population trends, we corroborate recent surveys indicating rapid declines since the 1980s. More surprisingly, however, was that the colony size was smaller and has changed strikingly in the past, even prior to the introduction of human stressors. Our results challenge notions that very large colonies are generally stable in the absence of anthropogenic pressures and speak to an increasingly pressing need to better understand inter-colony movement and recruitment when inferring range- and species-wide trends. While the recently documented decline in storm-petrels clearly warrants conservation concern, we show that colony size was consistently much lower in the past and changed markedly in the absence of major anthropogenic activity. In response, we emphasize the need for enlarged protected area networks to maintain natural population cycles, coupled with continued research to identify the driver(s) of the current global seabird decline.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".