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Record W4391889671 · doi:10.1098/rsbl.2023.0507

Urban tolerance does not protect against population decline in North American birds

2024· article· en· W4391889671 on OpenAlexafffund
Julianna A. Petrenko, Paul R. Martin, Rachel E. Fanelli, Frances Bonier

Bibliographic record

VenueBiology Letters · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Ontario
KeywordsBiologyPopulationEcologyHabitatUrban ecologyPopulation declineClimate changePopulation sizePopulation growthUrbanizationDemography

Abstract

fetched live from OpenAlex

Population declines of organisms are widespread and severe, but some species' populations have remained stable, or even increased. The reasons some species are less vulnerable to population decline than others are not well understood. Species that tolerate urban environments often have a broader environmental tolerance, which, along with their ability to tolerate one of the most human-modified habitats (i.e. cities), might allow them to persist in the face of diverse anthropogenic challenges. Here, we examined the relationship between urban tolerance and annual population trajectories for 397 North American bird species. Surprisingly, we found that urban tolerance was unrelated to species' population trajectories. The lack of a relationship between urban tolerance and population trajectories may reflect other factors driving population declines independent of urban tolerance, challenges that are amplified in cities (e.g. climate warming, disease), and other human impacts (e.g. conservation efforts, broad-scale land-use changes) that have benefitted some urban-avoidant species. Overall, our results illustrate that urban tolerance does not protect species against population decline.

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 score0.052
Threshold uncertainty score0.924

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)0.0010.000

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 head0.249
Teacher spread0.235 · 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

Citations6
Published2024
Admission routes2
Has abstractyes

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