Land Cover Switching in Autumn by Female Mallards in Ohio
Bibliographic record
Abstract
ABSTRACT Autumn waterfowl habitat management often focuses on providing high energy food resources to attract and concentrate waterfowl for harvest. Similarly, many waterfowl conservation plans assume food resources are the primary, controllable limiting factor influencing waterfowl distribution during migration; however, hunting‐related disturbance also influences waterfowl distribution in autumn. We investigated factors influencing mallard (Anas platyrhynchos) movements in an intensively hunted and food‐rich landscape in Ohio, USA, during autumn of 2015 and 2016. We used locations from female mallards equipped with global positioning system (GPS) back‐pack‐transmitters to determine the probability of mallards switching land cover types based on seasonal and daily patterns of hunting disturbance and to determine the distances mallards moved between cover types that offer refuge and those that offer food resources as evidence for or against food resource depletion during the hunting season. Mallards switched cover types to exploit food‐rich but intensively hunted locations nocturnally and cover type switching during times subject to disturbance increased significantly from the early segment to the late segment of hunting season. Distances mallards moved between refuge cover types and food‐rich cover types did not change over the duration of the study. Hunting disturbance is a key variable influencing autumn movements and distribution of mallards, and mallards in a food‐rich and intensively hunted landscape likely employ nocturnal foraging as a strategy to survive autumn migration. Nocturnal foraging behavior has consequences for waterfowl managers tasked with providing quality waterfowl hunting opportunities because ducks that forage only at night are largely unavailable to hunters. © 2020 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 | 0.000 |
| 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 | 0.000 | 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".