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Record W2338257819 · doi:10.1126/sciadv.1500310

Trait-mediated trophic cascade creates enemy-free space for nesting hummingbirds

2015· article· en· W2338257819 on OpenAlexaff
Harold F. Greeney, M. Rocio Meneses, Chris E. Hamilton, Eli Lichter-Marck, R. William Mannan, Noel F. R. Snyder, Helen A. Snyder, Susan M. Wethington, Lee A. Dyer

Bibliographic record

VenueScience Advances · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsTrent University
FundersU.S. Fish and Wildlife Service
KeywordsPredationEcologyTrophic levelTrophic cascadeForagingBiologyHummingbirdTraitHabitatHabitat fragmentationPredator

Abstract

fetched live from OpenAlex

The indirect effects of predators on nonadjacent trophic levels, mediated through traits of intervening species, are collectively known as trait-mediated trophic cascades. Although birds are important predators in terrestrial ecosystems, clear examples of trait-mediated indirect effects involving bird predators have almost never been documented. Such indirect effects are important for structuring ecological communities and are likely to be negatively impacted by habitat fragmentation, climate change, and other factors that reduce abundance of top predators. We demonstrate that hummingbirds in Arizona realize increased breeding success when nesting in association with hawks. An enemy-free nesting space is created when jays, an important source of mortality for hummingbird nests, alter their foraging behavior in the presence of their hawk predators.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.284
Teacher spread0.260 · 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

Citations34
Published2015
Admission routes1
Has abstractyes

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