Effect of low-level flying military aircraft on the behaviour of spring staging waterfowl at Lac Fourmont ashkui, Labrador, Canada
Bibliographic record
Abstract
Military jet over-flight activities pose a potential threat to staging waterfowl and pilots. The migration period is important for nutrient acquisition and courtship as these waterfowl enter the breeding season. Using a focal animal (continuous) technique for five-minute intervals, diurnal Time/Activity (TA) budgets for Canada Geese (Branta canadensis canadensis) (n=751), American Black Duck (Anas rubripes) (n=474) and Common Goldeneye (Bucephala clangula) (n=1274) were compiled during 216 hours of behavioural observation. The study was conducted from 26 April to 27 May, 2002 at the outlet of Lac Fourmont, Labrador (52° 03' 30"N, 60° 31' 01" W), in an ashkui or area of open water in an otherwise frozen landscape, which is known historically as a place to hunt waterfowl. These staging grounds are within the 130 000 km2 Low-level Training Area (LLTA) of the Quebec-Labrador Peninsula. Generalized Linear Modeling (GLM) of ranked variables was used to analyze behaviour by: observer, sex, pair status, time of day, date, and each weather parameter. Male Common Goldeneye spent more time in courtship behaviours (2.7%) than females (1.1%) and they spent most of the daylight hours feeding (males 53.3% and females 54.5%), with little time resting (4.8% and 5.2%, respectively). In contrast, Black Ducks and Canada Geese spent relatively little time feeding (12.4% and 5% respectively) and most of their time sleeping (35% and 38% respectively) and locomotion (37.8% and 11% respectively). Ashkui are important to Common Goldeneyes for foraging, and to Canada Geese and Black Ducks for resting prior to the breeding season. Ninety-one low-level jet over-flights occurred and sound levels (n=336 h) at the study site were measured. Effects of low-level jet over-flights were analyzed using GLM of ranked variables in order to analyze a number of variables simultaneously. All behavioural observations that occurred in the quarter hour periods up to 165 minutes after an over-flight were analyzed. Alert and courtship behaviours of Canada Geese increased after over-flights. Other behaviours were negatively affected to a lesser degree. Locomotor activities by Black Ducks increased significantly immediately following over-flights with a stronger movement response with increased noise. Increases in agonistic and comfort behaviours of Common Goldeneye were detected following over-flights with few other significant affects on their behaviour.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".