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Record W2995354239 · doi:10.1098/rsbl.2019.0633

The dynamics underlying avian extinction trajectories forecast a wave of extinctions

2019· article· en· W2995354239 on OpenAlexaff
Melanie J. Monroe, Stuart H. M. Butchart, Arne Ø. Mooers, Folmer Bokma

Bibliographic record

VenueBiology Letters · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsExtinction (optical mineralogy)IUCN Red ListBiologyExtinction eventEcologyEndangered speciesCritically endangeredExtinct speciesPopulationDemographyEvolutionary biologyHabitatExtant taxonPaleontology

Abstract

fetched live from OpenAlex

Abstract Population decline is a process, yet estimates of current extinction rates often consider just the final step of that process by counting numbers of species lost in historical times. This neglects the increased extinction risk that affects a large proportion of species, and consequently underestimates the effective extinction rate. Here, we model observed trajectories through IUCN Red List extinction risk categories for all bird species globally over 28 years, and estimate an overall effective extinction rate of 2.17 × 10−4/species/year. This is six times higher than the rate of outright extinction since 1500, as a consequence of the large number of species whose status is deteriorating. We very conservatively estimate that global conservation efforts have reduced the effective extinction rate by 40%, but mostly through preventing critically endangered species from going extinct rather than by preventing species at low risk from moving into higher-risk categories. Our findings suggest that extinction risk in birds is accumulating much more than previously appreciated, but would be even greater without conservation efforts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.313

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.017
GPT teacher head0.236
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

Citations52
Published2019
Admission routes1
Has abstractyes

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