4.5 Article

Modeling Species-Specific Collision Risk of Birds with Wind Turbines: A Behavioral Approach

Journal

SYMMETRY-BASEL
Volume 14, Issue 12, Pages -

Publisher

MDPI
DOI: 10.3390/sym14122493

Keywords

collision risk; IdentiFlight; wind turbine curtailment; phylogenetic signal; flight behavior; flight symmetry

Funding

  1. Vattenfall
  2. Aalborg Zoo Conservation Foundation (AZCF)
  3. [09-2020]

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This study aims to model collision risk by investigating flight behavioral traits and other influencing factors, and to study the specificity of species through a case study. The results indicate that these traits can be used to predict collision risk and identify high-risk species.
The increasing number of wind energy sites developed globally, has consequently resulted in a green-on-green predicament, due to an increase in avian mortality caused by collisions with wind turbines. The proportion of collision-related fatalities is not evenly distributed across species, indicating that some species groups are more prone to turbine collision. Such differences between species have been proposed to be affiliated with species-specific foraging and flight behavior. The aim of this study is to investigate how the flight behavioral traits; head position, active flight, track symmetry, and track tortuosity can be used to model collision risk along with other influencing factors i.e., weather variables (temperature, wind speed, and cloud coverage) and temporal variables (time of day and time of year). The study also sought to investigate the species-specificity of the four traits in relation to the phylogenetic relatedness of the study species. This was achieved through a case study at a wind farm on the Swedish island of Gotland in which the behavior of birds from 11 different genera was studied. The flight behavior of these species was assessed using data collected by the IdentiFlight system, e.g., flight trajectories and images of the birds throughout their flight track. The results confirm the species-specificity of the four flight behaviors and indicated that all four traits can be used to predict collision risk along with species as a categorical factor. The framework provided in this study along with the results of the case study can be used to identify risk-prone species based on phylogenetic relatedness and flight behavior.

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