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Record W4312469586 · doi:10.1139/facets-2022-0105

Effects of turbine height and cut-in speed on bat and swallow fatalities at wind energy facilities

2022· article· en· W4312469586 on OpenAlexafffundvenueabout
Alexandra M. Anderson, Catherine Jardine, J. Ryan Zimmerling, Erin F. Baerwald, Christina M. Davy

Bibliographic record

VenueFACETS · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsMinistry of Energy, Northern Development and MinesCarleton UniversityEnvironment and Climate Change CanadaBirds CanadaUniversity of Northern British ColumbiaTrent University
FundersEnvironment and Climate Change CanadaMitacsGovernment of Ontario
KeywordsHirundoTurbineWind powerCliffWildlifeEnvironmental scienceGeographyFisheryForestryEcologyBiologyEngineeringArchaeology

Abstract

fetched live from OpenAlex

Understanding the relationship between the height of wind turbines and wildlife fatalities is important for informing and mitigating wildlife collisions as ever taller and denser arrays of wind turbines are erected across the landscape. We examined relationships between turbine height and fatalities of bats and swallows at 811 turbines in Ontario, Canada, ranging from 119 to 186 m tall. We accounted for cut-in speeds, operational mitigation, and taller turbines projecting carcasses farther from the turbine base than shorter turbines. Fatalities of hoary bats ( Lasiurus cinereus Palisot de Beauvois, 1796), silver-haired bats ( Lasionycteris noctivagans Le Conte, 1831), and big brown bats ( Eptesicus fuscus Palisot de Beauvois, 1796) increased with increased maximum blade height of turbines. In contrast, fatalities of little brown bat ( Myotis lucifugus Le Conte, 1831) and eastern red bat ( Lasiurus borealis Müller, 1776) decreased with increased turbine height. Fatalities of purple martins ( Progne subis Linnaeus, 1758) and tree swallows ( Tachycineta bicolor Vieillot, 1808) were higher at taller turbines than shorter turbines. However, fatalities of cliff swallow ( Petrochelidon pyrrhonota Vieillot, 1817) and barn swallow ( Hirundo rustica Linnaeus, 1758) were not associated with turbine height. Our results suggest that varying flight height among species may be one factor affecting collision risk.

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 score0.278
Threshold uncertainty score0.245

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 head0.010
GPT teacher head0.181
Teacher spread0.171 · 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
Published2022
Admission routes4
Has abstractyes

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