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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container_title | The Journal of applied ecology |
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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. ; Calabrese, Justin M.</creator><contributor>Bauer, Silke</contributor><creatorcontrib>Péron, Guillaume ; Fleming, Christen H. ; Duriez, Olivier ; Fluhr, Julie ; Itty, Christian ; Lambertucci, Sergio ; Safi, Kamran ; Shepard, Emily L. C. ; Calabrese, Justin M. ; Bauer, Silke</creatorcontrib><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.</description><identifier>ISSN: 0021-8901</identifier><identifier>EISSN: 1365-2664</identifier><identifier>DOI: 10.1111/1365-2664.12909</identifier><language>eng</language><publisher>Oxford: John Wiley & Sons Ltd</publisher><subject>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</subject><ispartof>The Journal of applied ecology, 2017-12, Vol.54 (6), p.1895-1906</ispartof><rights>2017 British Ecological Society</rights><rights>2017 The Authors. Journal of Applied Ecology © 2017 British Ecological Society</rights><rights>Journal of Applied Ecology © 2017 British Ecological Society</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4789-45311afa9bc332605dd4c820dbc726d847b47cfbd3bde999baf1de55be033de03</citedby><cites>FETCH-LOGICAL-c4789-45311afa9bc332605dd4c820dbc726d847b47cfbd3bde999baf1de55be033de03</cites><orcidid>0000-0002-6311-4377 ; 0000-0003-1823-4721 ; 0000-0003-1868-9750</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/45024709$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/45024709$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,315,781,785,804,886,1418,1434,27929,27930,45579,45580,46414,46838,58022,58255</link.rule.ids><backlink>$$Uhttps://hal.science/hal-03905682$$DView record in HAL$$Hfree_for_read</backlink></links><search><contributor>Bauer, Silke</contributor><creatorcontrib>Péron, Guillaume</creatorcontrib><creatorcontrib>Fleming, Christen H.</creatorcontrib><creatorcontrib>Duriez, Olivier</creatorcontrib><creatorcontrib>Fluhr, Julie</creatorcontrib><creatorcontrib>Itty, Christian</creatorcontrib><creatorcontrib>Lambertucci, Sergio</creatorcontrib><creatorcontrib>Safi, Kamran</creatorcontrib><creatorcontrib>Shepard, Emily L. 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. 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.</description><subject>Aerodynamics</subject><subject>Aspect ratio</subject><subject>Avoidance behavior</subject><subject>Biodiversity and Ecology</subject><subject>Birds</subject><subject>Birds of prey</subject><subject>Collision avoidance</subject><subject>Collision dynamics</subject><subject>Construction</subject><subject>continuous‐time</subject><subject>Development projects</subject><subject>Ecology, environment</subject><subject>Energy sources</subject><subject>Environmental Sciences</subject><subject>Flight</subject><subject>flight height</subject><subject>Global positioning systems</subject><subject>GPS</subject><subject>Hazards</subject><subject>Human-impacted systems</subject><subject>human–wildlife conflict</subject><subject>Landscape</subject><subject>Life Sciences</subject><subject>Meteorological data</subject><subject>Monitoring</subject><subject>movement ecology</subject><subject>raptor</subject><subject>Soaring</subject><subject>Species</subject><subject>State space models</subject><subject>Statistics</subject><subject>Tracking</subject><subject>Turbines</subject><subject>Uplift</subject><subject>Weather</subject><subject>Wildlife conservation</subject><subject>Wind farms</subject><subject>Wind power</subject><subject>Wind turbines</subject><subject>Wing loading</subject><subject>z‐axis GPS tracking data</subject><issn>0021-8901</issn><issn>1365-2664</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNqFUT1PwzAQtRBIlMLMhGSJiSFgx3ESjxXiU5VgKLPl2JfGVYiDnVKVX49LoCs33Env3ns6vUPonJJrGuuGspwnaZ5n1zQVRBygyR45RBNCUpqUgtBjdBLCihAiOGMT9LloAEMHfrnFrepM0KoH3HswVg8B161dNgNu4GfEPd7Y2Ia1r2wHWLu2tcG6DjfqS3mDbYeHxgPg0IO2ELCro61fRsApb7sl9qofnD9FR7VqA5z9zil6u79b3D4m85eHp9vZPNFZUYok44xSVStRacbSnHBjMl2mxFS6SHNTZkWVFbquDKsMCCEqVVMDnFdAGDOxTdHV6NuoVvbeviu_lU5Z-Tibyx1GmCA8L9NPGrmXI7f37mMNYZArt_ZdPE9SkbOiLGnMbIpuRpb2LgQP9d6WErl7hNzFLnexy59HRAUfFRvbwvY_unx-vfvTXYy6VYiJ7XUZJ2lWxP03JxKU8Q</recordid><startdate>201712</startdate><enddate>201712</enddate><creator>Péron, Guillaume</creator><creator>Fleming, Christen H.</creator><creator>Duriez, Olivier</creator><creator>Fluhr, Julie</creator><creator>Itty, Christian</creator><creator>Lambertucci, Sergio</creator><creator>Safi, Kamran</creator><creator>Shepard, Emily L. C.</creator><creator>Calabrese, Justin M.</creator><general>John Wiley & Sons Ltd</general><general>Blackwell Publishing Ltd</general><general>Wiley</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7SS</scope><scope>7T7</scope><scope>7U7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-6311-4377</orcidid><orcidid>https://orcid.org/0000-0003-1823-4721</orcidid><orcidid>https://orcid.org/0000-0003-1868-9750</orcidid></search><sort><creationdate>201712</creationdate><title>The energy landscape predicts flight height and wind turbine collision hazard in three species of large soaring raptor</title><author>Péron, Guillaume ; Fleming, Christen H. ; Duriez, Olivier ; Fluhr, Julie ; Itty, Christian ; Lambertucci, Sergio ; Safi, Kamran ; Shepard, Emily L. C. ; Calabrese, Justin M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4789-45311afa9bc332605dd4c820dbc726d847b47cfbd3bde999baf1de55be033de03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Aerodynamics</topic><topic>Aspect ratio</topic><topic>Avoidance behavior</topic><topic>Biodiversity and Ecology</topic><topic>Birds</topic><topic>Birds of prey</topic><topic>Collision avoidance</topic><topic>Collision dynamics</topic><topic>Construction</topic><topic>continuous‐time</topic><topic>Development projects</topic><topic>Ecology, environment</topic><topic>Energy sources</topic><topic>Environmental Sciences</topic><topic>Flight</topic><topic>flight height</topic><topic>Global positioning systems</topic><topic>GPS</topic><topic>Hazards</topic><topic>Human-impacted systems</topic><topic>human–wildlife conflict</topic><topic>Landscape</topic><topic>Life Sciences</topic><topic>Meteorological data</topic><topic>Monitoring</topic><topic>movement ecology</topic><topic>raptor</topic><topic>Soaring</topic><topic>Species</topic><topic>State space models</topic><topic>Statistics</topic><topic>Tracking</topic><topic>Turbines</topic><topic>Uplift</topic><topic>Weather</topic><topic>Wildlife conservation</topic><topic>Wind farms</topic><topic>Wind power</topic><topic>Wind turbines</topic><topic>Wing loading</topic><topic>z‐axis GPS tracking data</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Péron, Guillaume</creatorcontrib><creatorcontrib>Fleming, Christen H.</creatorcontrib><creatorcontrib>Duriez, Olivier</creatorcontrib><creatorcontrib>Fluhr, Julie</creatorcontrib><creatorcontrib>Itty, Christian</creatorcontrib><creatorcontrib>Lambertucci, Sergio</creatorcontrib><creatorcontrib>Safi, Kamran</creatorcontrib><creatorcontrib>Shepard, Emily L. C.</creatorcontrib><creatorcontrib>Calabrese, Justin M.</creatorcontrib><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Toxicology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>The Journal of applied ecology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Péron, Guillaume</au><au>Fleming, Christen H.</au><au>Duriez, Olivier</au><au>Fluhr, Julie</au><au>Itty, Christian</au><au>Lambertucci, Sergio</au><au>Safi, Kamran</au><au>Shepard, Emily L. C.</au><au>Calabrese, Justin M.</au><au>Bauer, Silke</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The energy landscape predicts flight height and wind turbine collision hazard in three species of large soaring raptor</atitle><jtitle>The Journal of applied ecology</jtitle><date>2017-12</date><risdate>2017</risdate><volume>54</volume><issue>6</issue><spage>1895</spage><epage>1906</epage><pages>1895-1906</pages><issn>0021-8901</issn><eissn>1365-2664</eissn><abstract>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.</abstract><cop>Oxford</cop><pub>John Wiley & Sons Ltd</pub><doi>10.1111/1365-2664.12909</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-6311-4377</orcidid><orcidid>https://orcid.org/0000-0003-1823-4721</orcidid><orcidid>https://orcid.org/0000-0003-1868-9750</orcidid><oa>free_for_read</oa></addata></record> |
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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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