The energy landscape predicts flight height and wind turbine collision hazard in three species of large soaring raptor

1. Collisions of large soaring raptors with wind turbines and other infrastructures represent a growing conservation concern. We describe a way to leverage knowledge about raptor soaring behaviour to forecast the probability that raptors fly in the rotor-swept zone. Soaring raptors are theoretically...

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Veröffentlicht in:The Journal of applied ecology 2017-12, Vol.54 (6), p.1895-1906
Hauptverfasser: Péron, Guillaume, Fleming, Christen H., Duriez, Olivier, Fluhr, Julie, Itty, Christian, Lambertucci, Sergio, Safi, Kamran, Shepard, Emily L. C., Calabrese, Justin M.
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container_end_page 1906
container_issue 6
container_start_page 1895
container_title The Journal of applied ecology
container_volume 54
creator Péron, Guillaume
Fleming, Christen H.
Duriez, Olivier
Fluhr, Julie
Itty, Christian
Lambertucci, Sergio
Safi, Kamran
Shepard, Emily L. C.
Calabrese, Justin M.
description 1. Collisions of large soaring raptors with wind turbines and other infrastructures represent a growing conservation concern. We describe a way to leverage knowledge about raptor soaring behaviour to forecast the probability that raptors fly in the rotor-swept zone. Soaring raptors are theoretically expected to select energy sources (uplift) optimally, making their flight height dependent on uplift conditions. This approach can be used to forecast collision hazard when planning or operating wind farms. Empirical investigations of the factors influencing flight height have, however, so far been hindered by observation error. 2. We propose a two-pronged approach. First, we fitted state-space models to z-axis GPS tracking data to filter heavy-tailed observation error and estimate the relationship between vertical movement parameters and weather variables describing the energy landscape (thermal and orographic uplift potential). Second, we fitted a mechanistic model of flight height above ground based on aerodynamics and resource selection theories. The approach was replicated for five GPS-tracked Andean condors Vultur gryphus, eight griffon vultures Gyps fulvus, and six golden eagles Aquila chrysaetos. 3. In all individuals, movement parameters correlated with thermal uplift potential in the expected direction. In all species, collision hazard was lowest for high thermal uplift potential values. Species specificities in the presence of a peak in collision hazard for medium values of thermal uplift potential could be explained by differences in wing loading and aspect ratio. 4. Synthesis and applications. Our fitted models convert weather data (thermal uplift potential) into a prediction of collision hazard (probability to fly in the rotor-swept zone), making it possible to prioritize different wind development projects with respect to the relative hazard they would pose to raptors. However, our model should be combined with post-construction monitoring to document, and eventually account for turbine avoidance behaviours in collision rate predictions.
doi_str_mv 10.1111/1365-2664.12909
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C.</creatorcontrib><creatorcontrib>Calabrese, Justin M.</creatorcontrib><title>The energy landscape predicts flight height and wind turbine collision hazard in three species of large soaring raptor</title><title>The Journal of applied ecology</title><description>1. Collisions of large soaring raptors with wind turbines and other infrastructures represent a growing conservation concern. We describe a way to leverage knowledge about raptor soaring behaviour to forecast the probability that raptors fly in the rotor-swept zone. Soaring raptors are theoretically expected to select energy sources (uplift) optimally, making their flight height dependent on uplift conditions. This approach can be used to forecast collision hazard when planning or operating wind farms. Empirical investigations of the factors influencing flight height have, however, so far been hindered by observation error. 2. We propose a two-pronged approach. 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This approach can be used to forecast collision hazard when planning or operating wind farms. Empirical investigations of the factors influencing flight height have, however, so far been hindered by observation error. 2. We propose a two-pronged approach. First, we fitted state-space models to z-axis GPS tracking data to filter heavy-tailed observation error and estimate the relationship between vertical movement parameters and weather variables describing the energy landscape (thermal and orographic uplift potential). Second, we fitted a mechanistic model of flight height above ground based on aerodynamics and resource selection theories. The approach was replicated for five GPS-tracked Andean condors Vultur gryphus, eight griffon vultures Gyps fulvus, and six golden eagles Aquila chrysaetos. 3. In all individuals, movement parameters correlated with thermal uplift potential in the expected direction. In all species, collision hazard was lowest for high thermal uplift potential values. Species specificities in the presence of a peak in collision hazard for medium values of thermal uplift potential could be explained by differences in wing loading and aspect ratio. 4. Synthesis and applications. Our fitted models convert weather data (thermal uplift potential) into a prediction of collision hazard (probability to fly in the rotor-swept zone), making it possible to prioritize different wind development projects with respect to the relative hazard they would pose to raptors. 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source Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; JSTOR Archive Collection A-Z Listing; Wiley Free Content; Wiley Online Library All Journals
subjects Aerodynamics
Aspect ratio
Avoidance behavior
Biodiversity and Ecology
Birds
Birds of prey
Collision avoidance
Collision dynamics
Construction
continuous‐time
Development projects
Ecology, environment
Energy sources
Environmental Sciences
Flight
flight height
Global positioning systems
GPS
Hazards
Human-impacted systems
human–wildlife conflict
Landscape
Life Sciences
Meteorological data
Monitoring
movement ecology
raptor
Soaring
Species
State space models
Statistics
Tracking
Turbines
Uplift
Weather
Wildlife conservation
Wind farms
Wind power
Wind turbines
Wing loading
z‐axis GPS tracking data
title The energy landscape predicts flight height and wind turbine collision hazard in three species of large soaring raptor
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