Comparison of Ground and Helicopter Surveys for Breeding Waterfowl in New Jersey
Bibliographic record
Abstract
ABSTRACT New Jersey has participated in the Atlantic Flyway Breeding Waterfowl Survey by conducting ground surveys in the salt marsh strata, which are important for breeding waterfowl, particularly American black ducks ( Anas rubripes ). Ground surveys in salt marshes are time‐intensive, tide dependent, costly, and take several days to complete. We investigated the use of helicopters and compared the results of mallard ( Anas platyrhnchos ), black duck, and Canada goose ( Branta canadensis ) estimates to ground surveys. Expected mean point estimates for all species were consistently higher during ground than helicopter surveys. Expected mean point estimates were higher during both ground and helicopter surveys at twilight than at midday for Canada geese and black ducks, whereas mallard observations were higher during midday than twilight for both survey methods. We found no differences in results from helicopter surveys conducted at high versus low tide. Although helicopter contracts are expensive, ground surveys took 8.5 times more staff time to complete, resulting in similar cost between survey platforms. Helicopters provide an alternative for ground surveys in salt marshes of the Atlantic Flyway, and we provide recommendations to develop visibility correction factors for different species groupings to account for visibility bias associated with helicopter observations. © 2021 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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".