Factors influencing emigration of Ross's and snow geese from an Arctic breeding area
Bibliographic record
Abstract
ABSTRACT Emigration is one of the most difficult demographic rates to estimate, yet understanding movement among populations has important consequences for wildlife conservation. We studied factors that affected emigration by adult Ross's geese ( Chen rossii ) and lesser snow geese ( C. caerulescens caerulescens ) during a demographic study from 1997 to 2013 of nesting geese at the Karrak Lake colony south of Queen Maud Gulf in the Central Canadian Arctic. Rising abundance of both species in recent decades has led to concerns about their impacts on Arctic ecosystems. We used Burnham's model to estimate true survival and fidelity (i.e., the complement of emigration). Mean estimates of fidelity were higher for Ross's geese (male = 0.91 ± 0.02, female = 0.95 ± 0.01) than for snow geese (male = 0.76 ± 0.02, female = 0.90 ± 0.02). Fidelity declined with prior nesting season abundance in both species with evidence that a reduction in population size led to greater fidelity in the following year. Fidelity was positively influenced by mean nest success in the previous year with similar responses by both species. However, years of low nest success were more frequent for snow geese resulting in higher emigration. We expected that deeper snow before nesting would motivate greater emigration but found the opposite effect in both species, suggesting that individuals may be discouraged from dispersing in snow‐covered landscapes. We also tested whether a large decline in the number of snow geese nesting at Karrak Lake in 2007–2008 was related to a mass emigration event but found no evidence for a change in fidelity in these years. Moreover, survival of both species showed an increasing trend from 1997 to 2013 so the decline in nesting snow geese likely was an outcome of temporary non‐breeding, rather than emigration or death. The destination of emigrants remains unknown, but we expect this movement has broader consequences for metapopulation dynamics of light geese across the central Arctic. © 2015 Her Majesty the Queen in Right of Canada published on behalf of The Journal of Wildlife Management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".