MétaCan
Menu
Back to cohort
Record W2797564622 · doi:10.1038/s41598-018-22253-5

Noise Source and Individual Physiology Mediate Effectiveness of Bird Songs Adjusted to Anthropogenic Noise

2018· article· en· W2797564622 on OpenAlexafffund
Claire Curry, Paulson G. Des Brisay, Patrícia Rosa, Nicola Koper

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCenovus EnergyU.S. Department of AgricultureNational Institute of Food and AgricultureNational Science Foundation
KeywordsNoise (video)Environmental scienceAggressionEcologyComputer scienceVariation (astronomy)WildlifeBiologyPsychologyArtificial intelligenceSocial psychologyPhysics

Abstract

fetched live from OpenAlex

Anthropogenic noise is a pervasive pollutant altering behaviour of wildlife that communicates acoustically. Some species adjust vocalisations to compensate for noise. However, we know little about whether signal adjustments improve communication in noise, the extent to which effectiveness of adjustments varies with noise source, or how individual variation in physiology varies with response capacity. We played noise-adjusted and unadjusted songs to wild Passerculus sandwichensis (Savannah Sparrows) after measurements of adrenocortical responsiveness of individuals. Playbacks using songs adjusted to noisy environments were effective in restoring appropriate conspecific territorial aggression behaviours in some altered acoustic environments. Surprisingly, however, levels of adrenocortical responsiveness that reduced communication errors at some types of infrastructure were correlated with increased errors at others. Song adjustments that were effective in communicating for individuals with lower adrenocortical responsiveness at pumpjacks were not effective at screwpumps and vice versa. Our results demonstrate that vocal adjustments can sometimes allow birds to compensate for disruptions in communication caused by anthropogenic noise, but that physiological variation among receivers may alter effectiveness of these adjustments. Thus mitigation strategies to minimize anthropogenic noise must account for both acoustic and physiological impacts of infrastructure.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.023
GPT teacher head0.292
Teacher spread0.269 · 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 designBench or experimental
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

Citations27
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueScientific ReportsSame topicAnimal Vocal Communication and BehaviorFrench-language works237,207