Coordinated aerial and ground surveys document long-term recovery of geese and eiders on the Yukon–Kuskokwim Delta, Alaska, 1985–2014
Bibliographic record
Abstract
Severe declines of waterfowl populations on the Yukon–Kuskokwim Delta (YKD), Alaska, from the 1960s through the mid-1980s, prompted the initiation in 1985 of standardized surveys of the region’s breeding birds. These entailed coordinated annual aerial and ground-based surveys, tiered by area and intensity of coverage, which have provided data for this area critical to waterfowl production. Aerial surveys were used to provide broad-scale indices of breeding pairs and the total bird population along the YKD’s entire coast, while ground surveys provided finer-scale estimates of breeding chronology, egg production, nesting effort, habitat use, and predation within core breeding habitats. The extensive coverage of the aerial surveys also provided objective data for expansion of the ground-based sampling, while the nest surveys contributed to a better understanding of aerial survey data, including indices of detection rates. Here we describe patterns of long-term population growth of the Cackling Goose (Branta hutchinsii minima), Greater White-fronted Goose (Anser albifrons frontalis), and Emperor Goose (Chen canagica) relative to population objectives for the Pacific Flyway. We also describe significant growth in the western Alaska population of the Spectacled Eider (Somateria fischeri) following the species’ listing as threatened under the Endangered Species Act in 1993. Growth rates of population indices were positive for the four species from 1985 to 2014, but rates varied within this interval. We found no evidence that dates of nest initiation and hatching advanced significantly between 1985 and 2014. The proportion of waterfowl recorded as pairs by aerial survey crews was correlated with the surveys’ start date for geese but not for the Spectacled Eider. The ratio of nests to aerially observed pairs was 4.8 for Cackling Geese, 5.2 for Greater White-fronted Geese, 5.4 for Emperor Geese, and 2.4 for Spectacled Eiders. The nest-to-pair ratio is one tool by which indices based on aerial surveys can be converted to an estimate of the number of breeding pairs. Together these aerial and ground-based surveys provide the information needed to implement waterfowl management and recovery plans, assess waterfowl distribution across the YKD, measure nesting chronology relative to changes in climate, develop indices to detection rate in aerial surveys, and assess waterfowl vulnerability.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".