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Record W4245548903 · doi:10.1093/auk/121.1.15

Minimum Estimates of Survival and Population Growth for Cerulean Warblers (Dendroica Cerulea) Breeding in Ontario, Canada

2004· article· en· W4245548903 on OpenAlexaffabout
Jason Jones, Jennifer J. Barg, T. Scott Sillett, M. Lisa Veit, Raleigh J. Robertson

Bibliographic record

VenueThe Auk · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsQueen's University
Fundersnot available
KeywordsFecundityWarblerLeslie matrixBiologyVital ratesPopulationEcologyPopulation growthMark and recapturePopulation declinePopulation modelHabitatMortality rateDemography

Abstract

fetched live from OpenAlex

Abstract The Cerulean Warbler (Dendroica cerulea) tops many lists of species of conservation concern because of severe population declines and habitat loss. Here we present the first robust estimates of annual survival and population growth rates for this species. We used capture—mark—recapture models to estimate survival of adult male Cerulean Warblers in an eastern Ontario population that has been studied since 1994. Adult male survival probability (ϕ) was constant over time in our best-supported model. Our second-best-supported model indicated a negative effect of a 1998 ice storm on survival. The third-best-supported model indicated a significant year effect on survival. On the basis of those results and previously published estimates of annual fecundity, we calculated a population growth rate using a two-stage Leslie matrix. Population growth rate (λ) was 0.73, using the estimate for constant survival. Model elasticities imply that adult mortality had a stronger effect on λ than did seasonal fecundity. Oversummer survival estimates suggest that events during migration or on wintering grounds are responsible for most adult male mortality. It appears that our study population, thought to be one of the healthiest known for this species, may not be currently reproducing at a high enough rate to accommodate adult mortality. However, caution must be used when interpreting those results, given the possibility of underestimating survival and fecundity of this 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.043
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.203
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2004
Admission routes2
Has abstractyes

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