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Record W2098182050 · doi:10.1098/rspb.2012.0445

Historical pesticide applications coincided with an altered diet of aerially foraging insectivorous chimney swifts

2012· article· en· W2098182050 on OpenAlexaffabout
Joseph J. Nocera, Jules M. Blais, David Beresford, Leah Finity, Christopher Grooms, Lynda E. Kimpe, Kurt Kyser, Neal Michelutti, Matthew W. Reudink, John P. Smol

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsQueen's UniversityKingston Health Sciences CentreThompson Rivers UniversityUniversity of OttawaTrent UniversityMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsInsectivoreForagingPopulationChimney (locomotive)BiologyEcologyPredationInsectZoologyGeography

Abstract

fetched live from OpenAlex

Numerous environmental pressures have precipitated long-term population reductions of many insect species. Population declines in aerially foraging insectivorous birds have also been detected, but the cause remains unknown partly because of a dearth of long-term monitoring data on avian diets. Chimney swifts (Chaetura pelagica) are a model aerial insectivore to fill such information gaps because their roosting behaviour makes them easy to sample in large numbers over long time periods. We report a 48-year-long (1944-1992) dietary record for the chimney swift, determined from a well-preserved deposit of guano and egested insect remains in Ontario (Canada). This unique archive of palaeo-environmental data reflecting past chimney swift diets revealed a steep rise in dichlorodiphenyltrichloroethane (DDT) and metabolites, which were correlated with a decrease in Coleoptera remains and an increase in Hemiptera remains, indicating a significant change in chimney swift prey. We argue that DDT applications decimated Coleoptera populations and dramatically altered insect community structure by the 1960s, triggering nutritional consequences for swifts and other aerial insectivores.

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)0.001
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 score0.009
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.239
Teacher spread0.218 · 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

Citations85
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Royal Society B Biological SciencesSame topicIsotope Analysis in EcologyFrench-language works237,207