Space Use and Habitat Associations of Long-Distance Migratory First-Year Golden Eagles (Aquila chrysaetos) from Interior Alaska in a Changing Landscape
Bibliographic record
Abstract
Understanding a species space use and habitat associations is integral to comprehensive wildlife management. Habitat associations change spatially and temporally and those changes may be especially dramatic for animals that cover long distances throughout their annual cycle. While many studies of habitat associations and space use concentrate on breeding season behavior, studies of migratory connectivity demonstrate how condition of habitats on non-breeding ranges potentially affect key demographic parameters, such as survival, reproduction, and movement in other seasons. This is also important because wildlife habitats, especially land cover, are changing rapidly from both anthropogenic and natural forces in direct and indirect ways.;The goal of this research was to describe (1) space use and habitat associations of a long-distance migratory avian predator, the Golden Eagle (Aquila chrysaetos) during summer and winter, and (2) to assess land cover change in eagle use areas. I studied first-year Golden Eagles hatched in Denali National Park and Preserve, Alaska (Denali). Radio-tagged eagles spent winter in western North America and summer in Alaska and northwest Canada. The birds I studied were a subset of those radio-tagged as nestlings in Denali from 1997 to 1999.;I first used three different home range models to characterize winter space use of 15 first-year Golden Eagles hatched in Denali. Size of home ranges in winter was most biologically reasonable when measured with Kernel Density Estimates (KDEs). KDE home ranges were 4,429 to 69,478 km2 in size and did not differ between sexes. I used land cover, topography and physiographic data to test a priori defined hypotheses to evaluate drivers of movement behavior. Ranging behavior was best explained by the presence of steep slopes and canyons and degree of topographic roughness. The presence of topographic factors were, in general, more important than presence of land cover in explaining size of home range. Results from this study further the understanding of drivers of space use and habitat associations for young Golden Eagles on their wintering grounds.;To characterize how land cover change may influence these Golden Eagles, I also studied how land cover changed over an 11 year period (2001 -- 2011) within summer and winter areas used in 1997 -- 2000 (n=16 individuals; comprising 25 seasonal ranges, 15 winter, and 10 summer). Summer home ranges calculated with Kernel Density Estimates were larger than those in winter, they ranged from 20,990 to 224,375 km2, and those of males were larger than those of females. Land
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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 | 0.000 | 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) | 0.000 | 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".