Effects of Landscape Structure on Male Density and Spacing Patterns in Wild Turkeys (<i>Meleagris gallopavo</i>) Depend on Winter Severity
Bibliographic record
Abstract
The influence of landscape structure on abundance or spacing patterns of generalist bird species may be nonlinear and vary annually depending on the severity of environmental conditions. The Eastern Wild Turkey (Meleagris gallopavo sylvestris) is a generalist forest species that experiences high mortality when snow reduces food availability. Although increasing amounts of cornfield habitat may benefit Wild Turkeys by providing an alternate food source, reduced forest cover or elevated levels of forest fragmentation associated with increased corn (Zea mays) production could be detrimental. We evaluated the hypothesis that spring density of male Wild Turkeys increases with the amount of corn habitat as long as forest cover remains a dominant landscape component and that this increase is more prominent following a winter with thick snow accumulations. We performed point counts and corrected for imperfect detection in 2003 and 2004 at 130 randomly distributed sites in southern Québec. After a mild winter, male density peaked in landscapes characterized by 25–50% forest cover and a large amount of edge between forest and open habitats. After a harsh winter, male density decreased with annual crop cover when forests represented <20% of the landscape and increased when they represented >40%. Male aggregation was higher and increased with male density at a slower rate than if individuals had been randomly distributed, yet landscape structure had only a marginal effect on aggregation. Our results suggest that Wild Turkeys' response to landscape structure depends on environmental conditions and that this generalist forest species benefits from cornfields where forest cover is fragmented but abundant.
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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 | 0.000 | 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".