Habitat modification as a means of restoring crested auklet colonies
Bibliographic record
Abstract
ABSTRACT Seabirds that forage in dense groups can be especially vulnerable to anthropogenic threats at sea. To mitigate these threats to populations, nesting habitat restoration may be a viable option by reducing negative density dependence. Accordingly, we undertook a before‐after control‐impact (BACI) experiment to test whether habitat modification could be an effective means of restoring nesting habitat of crested auklets (Aethia cristatella) breeding on Gareloi Island, Alaska, USA. Despite supporting large numbers of crevice‐nesting auklets, many lava flows at Gareloi Island are in a stage of late vegetative succession that may prevent birds from accessing subterranean nesting habitat. We hypothesized that crested auklet density is highest in unvegetated blocky and porous lava, and predicted that removing vegetation from the surface would allow new recruits to secure previously unavailable nesting sites. In 2009 and 2010, we delineated 34 200‐m2 plots throughout the southeast colony at Gareloi, and color marked a subset of crested auklets landing in each plot to measure movement and abundance. We removed vegetative overgrowth and peat from half of each plot at the end of the 2009 (4 plots) and 2010 (30 plots) breeding seasons. Before and after vegetation removal, we counted the number of active nesting sites and calculated the ratio of banded to un‐banded breeders on the surface of each plot half. Overall, active nesting sites, number of individuals on the surface, and number of breeders landing did not increase after vegetation removal. However, among banded individuals that moved among plot halves, birds were 1.7 times more likely to move to a de‐vegetated plot half. Based on our experimental results, we found no evidence that vegetation removal increased crested auklet numbers at Gareloi Island, and thus in the short term this may not be a viable option for increasing crested auklet abundance. © 2016 The Wildlife Society.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".