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Record W2897775071 · doi:10.1650/condor-18-75.1

Demographic drivers of collapse in an island population of Tree Swallows

2018· article· en· W2897775071 on OpenAlexaffabout
Liam U. Taylor, Bradley K. Woodworth, Brett K. Sandercock, Nathaniel T. Wheelwright

Bibliographic record

VenueOrnithological Applications · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Guelph
FundersBowdoin CollegeNational Science Foundation
KeywordsPopulationJuvenileDemographyVital ratesPopulation declineBiologyEcologyPopulation sizePopulation growthImmigrationGeography

Abstract

fetched live from OpenAlex

Diagnosing causes of population declines requires an understanding of the contributions of demographic vital rates to interannual variability and long-term changes in population size. At Kent Island, New Brunswick, Canada, an isolated population of Tree Swallows (Tachycineta bicolor) collapsed between 1987 and 2010, providing a unique opportunity to reconstruct how demographic rates drive population dynamics. We fit an integrated population model to 24 yr of population count, reproductive success, and capture–recapture data to generate annual estimates of productivity, juvenile and adult survival, immigration, and the finite rate of population change (λ). The Kent Island population declined from 202 to 12 breeding adults over 24 yr, with a geometric mean decline of 11.6% per year. Annual apparent survival of adults averaged 56% across sexes, whereas annual survival and recruitment of juveniles never exceeded 6%. Transient life table response experiments revealed that variation in male and female immigration rates were the major contributors to both overall and interannual variation in λ, followed by female and male adult survival. Local recruitment and reproductive rates had little effect on variation in λ. Given broad-scale regional declines in Tree Swallows, our study shows how declines of isolated populations can be driven by reductions in immigration, especially when coupled with variation in adult survival and low local recruitment.

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 categoriesInsufficient 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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.263
Teacher spread0.249 · 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

Citations21
Published2018
Admission routes2
Has abstractyes

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