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Record W3093095462

Effects of Spatial and Temporal Variation in Resource Availability on the Growth Rates and Survival of Dunlin (Calidris Alpina Hudsonia) Chicks

2020· dissertation· en· W3093095462 on OpenAlexfundaboutno aff
Brandan Tyler Norman

Bibliographic record

VenueYork University Digital Library (York University) · 2020
Typedissertation
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
FundersNational Wildlife Research CenterEnvironment and Climate Change Canada
KeywordsCalidrisResource (disambiguation)Variation (astronomy)GeographyBiologyEcologyComputer scienceHabitat
DOInot available

Abstract

fetched live from OpenAlex

Long-distant migrants nesting in the Arctic experience condensed breeding seasons and shorter periods of high arthropod availability due to climate change. Shorebirds have precocial chicks which may compensate for food shortages by responding to spatial and temporal variation in arthropod availability. I hypothesize that shorebirds capitalize on this mobility to select quality foraging habitats to maximize chick growth and survival. I monitored arthropod biomass during chick rearing in Churchill, Manitoba and East Bay, Nunavut to document variation in habitat use, growth and survival in relation to variation in arthropod biomass. Movements of Dunlin (Calidris alpina hundsonia) chicks were observed from hatch until fledging to investigate whether chicks responded to resource hotspots. Dunlin chicks, however, did not significantly respond to hotspots of arthropod biomass. Despite potential asynchronies between chick rearing and food resources from climate change, flexibility of foraging behaviour among Arctic-breeding shorebirds may contribute to reducing vulnerabilities for other species.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.161
Teacher spread0.155 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2020
Admission routes2
Has abstractyes

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