Reproductive ecology and environmental change: nest survival, nest-site fidelity, and nest-site selection of emperor geese on the Yukon-Kuskokwim Delta, Alaska
Bibliographic record
Abstract
The effects of climate change have been most pronounced in the Arctic and sub-Arctic regions. Thus, environmental variation resulting from climate change will likely affect the ecology of organisms that rely on these regions. Environmental variation has the potential to affect reproductive ecology of Arctic-nesting geese; however, these effects likely vary by species. I used a combination of long-term data and short-term field-based studies to examine the influence of environmental variation on nest survival, nest-site fidelity, and nest-site selection of emperor geese (Anser canagicus), a marine species endemic to the Bering Sea region. In Chapter II, I used 24 years (1994–2017) of nest monitoring data from the Manokinak River on the Yukon-Kuskokwim Delta, Alaska, and hierarchical nest survival models to examine the influence of long-term variation in environmental conditions (e.g., spring phenology, temperature and precipitation during nesting, major flooding events, and indices of abundance of foxes and voles), individual variation (e.g., nest initiation date, maximum number of eggs, nest age), and researcher disturbance on nest survival of emperor geese. In Chapter III, I used 18 years (2000–2017) of capture-mark-reencounter data from the Manokinak River and a state-space multistate model to examine the influence of previous experience (i.e., nest fate) and environmental conditions (i.e., spring phenology and major flooding events) on nest-site fidelity of emperor geese and determine if nest-site fidelity was adaptive in that it led to higher nest survival. Lastly, in Chapter IV, I used nest monitoring data collected in 2021 on Kigigak Island, Alaska to examine the influence of physical characteristics of nests and proximity to conspecifics and heterospecifics on nest-site selection of emperor geese and tested whether nest-site selection was adaptive in that it led to higher nest survival. These separate but related studies will begin to fill knowledge gaps about reproductive ecology of emperor geese and help understand potential population-level responses to environmental change.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".