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Record W7005660899

Reproductive ecology and environmental change: nest survival, nest-site fidelity, and nest-site selection of emperor geese on the Yukon-Kuskokwim Delta, Alaska

2022· dissertation· en· W7005660899 on OpenAlexaboutno aff

Bibliographic record

VenueMinds at UW (University of Wisconsin) · 2022
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicMarine Invertebrate Physiology and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsNest (protein structural motif)Climate changeEmperorArcticWaterfowlGoosePhenologyFlooding (psychology)Wetland
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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.

Opus teacher head0.015
GPT teacher head0.195
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMinds at UW (University of Wisconsin)Same topicMarine Invertebrate Physiology and EcologyFrench-language works237,207