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Record W3045314977 · doi:10.1111/ele.13573

A meta‐analysis of global avian survival across species and latitude

2020· review· en· W3045314977 on OpenAlexafffund
Micah N. Scholer, Matthew Strimas‐Mackey, Jill E. Jankowski

Bibliographic record

VenueEcology Letters · 2020
Typereview
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaSpirit AeroSystems
KeywordsLatitudeTemperate climateBiologyEcologySouthern HemisphereAvian clutch sizeNorthern HemisphereTropicsGeographyReproductionClimatology

Abstract

fetched live from OpenAlex

Tropical birds are purported to be longer lived than their temperate counterparts, but it has not been shown whether avian survival rates covary with latitude worldwide. Here, we perform a global-scale meta-analysis of 949 estimates from 204 studies of avian survival and demonstrate that a latitudinal survival gradient exists in the northern hemisphere, is dampened or absent for southern hemisphere species, and that differences between passerines and nonpasserines largely drive these trends. We also show that while extrinsic factors related to climate were poor predictors of apparent survival compared to latitude alone, the relationship between apparent survival and latitude is strongly mediated by intrinsic traits - large-bodied species and species with smaller clutch size had the highest apparent survival. Our findings reveal that differences among intrinsic traits and whether species were passerines or nonpasserines surpass latitude and its underlying climatic factors in explaining global patterns of apparent avian survival.

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)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.009
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.070
GPT teacher head0.326
Teacher spread0.257 · 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 designMeta-analysis
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

Citations50
Published2020
Admission routes2
Has abstractyes

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