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Record W4409126920 · doi:10.1080/15594491.2024.2444074

Band recovery data illustrate spatiotemporal and taxonomic patterns of seabird collisions with anthropogenic structures

2025· article· en· W4409126920 on OpenAlexaboutno aff
Riley R. Lawson, Holly M. Todaro, Lucas R. Bobay, Matthew S. Broadway, Dylan A. Cooper, Madeline M. Eori, Alexander J. Harman, Landon K. Neumann, Scott R. Loss, Timothy J. O’Connell

Bibliographic record

VenueThe Wilson Journal of Ornithology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsSeabirdGeographyEcologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Seabird populations are declining rapidly due to numerous anthropogenic threats, including habitat destruction, invasive species, longline fisheries bycatch, and plastic ingestion. However, few studies have investigated seabird collisions with anthropogenic structures, and those studies have primarily focused on a particular taxon or location. Little research has addressed seabird collisions with buildings and similar structures despite bird-building collisions being a major source of mortality for other groups of birds in coastal and inland areas. We conducted an analysis of seabird collisions using band recovery data spanning from 1930 to 2023 from the North American Bird Banding Program, focusing on records categorized as: “caught due to striking: stationary object other than wires or towers.” Our objective was to describe taxonomic and spatiotemporal patterns emerging from these collision records, information that can be used to identify research needs and make recommendations for monitoring seabird collisions. There were 407 records of 39 seabird species representing 13 families that were categorized as striking buildings or similar structures. Species in Laridae (gulls and terns) and Pelecanidae (pelicans) represented 80% of records; Diomedeidae (albatrosses) was the only other family representing more than 5% of records. Band recoveries of collision victims were concentrated in the eastern United States, southern Canada, and urban areas on the West Coast of the U.S. and Canada. Over half of records (n = 228) were from ocean coastlines, with fewer from inland (n = 146) and offshore locations (n = 30). Most records (~90%) had no information about the type of structure with which the bird collided, but observer remarks indicate that seabirds collided with buildings, offshore oil platforms, docks/piers, and even boats. Elucidating and mitigating impacts of collisions with structures on seabird populations requires increased collision monitoring at coastal and offshore structures, which are highly underrepresented in this dataset and are likely a significant threat to seabirds. There is also a need for formal mechanisms for reporting seabird fatalities that account for sampling and detection-related biases and that allow observers to report specific structure types.

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 score0.004
Threshold uncertainty score0.570

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 studies0.0000.001
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 head0.024
GPT teacher head0.272
Teacher spread0.247 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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