The International Journal of Life Cycle Assessment

, Volume 23, Issue 10, pp 2007–2023 | Cite as

Impacts of onshore wind energy production on birds and bats: recommendations for future life cycle impact assessment developments

  • Tiago Laranjeiro
  • Roel May
  • Francesca Verones



Models for quantifying impacts on biodiversity from renewable energy technologies are lacking within life cycle impact assessment (LCIA). We aim to provide an overview of the effects of wind energy on birds and bats, with a focus on quantitative methods. Furthermore, we investigate and provide the necessary background for how these can be integrated into new developments of LCIA models in future.


We reviewed available literature summarizing the effects of wind energy developments on birds and bats. We provide an overview of available quantitative assessment methods that have been employed outside of the LCIA framework to model the different impacts of wind energy developments on wildlife. Combining the acquired knowledge on impact pathways and associated quantitative methods, we propose possibilities for future approaches for a wind energy impact assessment methodology for LCIA.

Results and discussion

Wind energy production has impacts on terrestrial biodiversity through three main pathways: collision, disturbance, and habitat alterations. Birds and bats are consistently considered the most affected taxonomic groups, with different responses to the before-mentioned impact pathways. Outside of the LCIA framework, current quantitative impact assessment prediction models include collision risk models, species distribution models, individual-based models, and population modeling approaches. Developed indices allow scaling of species-specific vulnerability to mortality, disturbance, and/or habitat alterations.


Although insight into the causes behind collision risk, disturbance, and habitat alterations for bats and birds is still limited, the current knowledge base enables the development of a robust assessment tool. Modeling the impacts of habitat alterations, disturbance, and collisions within an LCIA framework is most appropriate using species distribution models as those enable the estimation of species’ occurrences across a region. Although local-scale developments may be more readily feasible, further up-scaling to global coverage is recommended to allow comparison across regions and technologies, and to assess cumulative impacts.


Collision  Disturbance  Habitat alteration  LCIA  Quantitative models  Wind turbine 



This work was funded by the Research Council of Norway through the SURE project (project number 244109). We thank John Woods for support as a native English speaker and for valuable insight and discussions. We also thank Bram van Moorter for very constructive and insightful thoughts that helped us improve our ideas. Finally, we thank Craig Jackson for proofreading this article on the quality of a native English speaker.


  1. Ahlén I, Baagøe HJ, Bach L (2009) Behavior of Scandinavian bats during migration and foraging at sea 90:1318–1323Google Scholar
  2. Arnett EB, Hayes JP, Huso MMP (2006) Patterns of pre-construction bat activity at a proposed wind facility in south-central Pennsylvania: 2005 annual report. An Annu Rep Prep Bats Wind Energy Coop 5(01):75–78. CrossRefGoogle Scholar
  3. Arnett EB, Inkley DB, Larkin RP et al (2007) Impacts of wind energy facilities on wildlife and wildlife habitat. Wildlife Society Technical Review:07–02Google Scholar
  4. Artsdatabanken (2017) ArtsdatabankenGoogle Scholar
  5. Arvesen A, Hertwich EG (2012) Assessing the life cycle environmental impacts of wind power: a review of present knowledge and research needs. Renew Sust Energ Rev 16(8):5994–6006. CrossRefGoogle Scholar
  6. Azevedo LB, Henderson A, van Zelm R et al (2013) Assessing the importance of spatial variability versus model choices in life cycle impact assessment: the case of freshwater eutrophication in Europe. Am Chem Soc 47:13565–13570Google Scholar
  7. Baerwald EF, Barclay RMR (2011) Patterns of activity and fatality of migratory bats at a wind energy facility in Alberta, Canada. J Wildl Manag 75(5):1103–1114. CrossRefGoogle Scholar
  8. Baerwald EF, Edworthy J, Holder M, Barclay RMR (2009) A large-scale mitigation experiment fatalities at wind energy facilities. J Wildl Manag 73(7):1077–1081. CrossRefGoogle Scholar
  9. Band MW, Madders M, Whitfield DP (2007) Developing field and analytical methods to assess avian collision risk at wind farms. Birds Wind farms risk Assess Mitig:259–275Google Scholar
  10. Barclay RMR, Baerwald EF, Gruver JC (2007) Variation in bat and bird fatalities at wind energy facilities: assessing the effects of rotor size and tower height. Can J Zool 85(3):381–387. CrossRefGoogle Scholar
  11. Barrios L, Rodríguez A (2004) Behavioural and environmental correlates of soaring-bird mortality at on-shore wind turbines. J Appl Ecol 41(1):72–81. CrossRefGoogle Scholar
  12. Bastos R, Pinhancos A, Santos M et al (2016) Evaluating the regional cumulative impact of wind farms on birds: how can spatially explicit dynamic modelling improve impact assessments and monitoring? J Appl Ecol 53(5):1330–1340. CrossRefGoogle Scholar
  13. Beissinger SR, McCullough DR (2002) Population viability analysis. University of Chicago PressGoogle Scholar
  14. Bellebaum J, Korner-Nievergelt F, Dürr T, Mammen U (2013) Wind turbine fatalities approach a level of concern in a raptor population. J Nat Conserv 21(6):394–400. CrossRefGoogle Scholar
  15. Beston JA, Diffendorfer JE, Loss SR, Johnson DH (2016) Prioritizing avian species for their risk of population-level consequences from wind energy development. PLoS One 11(3):e0150813. CrossRefGoogle Scholar
  16. Bevanger K (1994) Bird interactions with utility structures: collision and electrocution, causes and mitigating measures. Ibis (Lond 1859) 136:412–425CrossRefGoogle Scholar
  17. BirdLife International (2017) Soaring Bird Sensitivity Map.
  18. BirdLife International (2018) BirdLife Data Zone. Accessed 4 Jan 2018
  19. Blumstein DT (2006) Developing an evolutionary ecology of fear: how life history and natural history traits affect disturbance tolerance in birds. Anim Behav 71(2):389–399. CrossRefGoogle Scholar
  20. Bright J, Langston RHW, Bullman R et al (2008) Map of bird sensitivities to wind farms in Scotland: a tool to aid planning and conservation. Biol Conserv 141(9):2342–2356. CrossRefGoogle Scholar
  21. Brinkmann R (2006) Survey of possible operational impacts on bats by wind facilities in southern Germany. A rep ordered by Adm Dist Freibg-dep 56 Conserv Landsc Manag, 63 ppGoogle Scholar
  22. Brinkmann R, Mayer K, Kretzschmar F, Witzlebeben JV (2006) Auswirkungen von Windkraftanlagen auf Fledermäuse:11Google Scholar
  23. Busch M, Garthe S (2016) Approaching population thresholds in presence of uncertainty: assessing displacement of seabirds from offshore wind farms. Environ Impact Assess Rev 56:31–42. CrossRefGoogle Scholar
  24. Calvert AM, Bishop CA, Elliot RD et al (2013) A synthesis of human-related avian mortality in Canada Synthèse des sources de mortalité aviaire d ’ origine anthropique au Canada. Avian. Conserv Ecol 8:11Google Scholar
  25. Carrete M, Sánchez-Zapata JA, Benítez JR et al (2009) Large scale risk-assessment of wind-farms on population viability of a globally endangered long-lived raptor. Biol Conserv 142(12):2954–2961. CrossRefGoogle Scholar
  26. Chamberlain DE, Rehfisch MR, Fox AD et al (2006) The effect of avoidance rates on bird mortality predictions made by wind turbine collision risk models. Ibis (Lond 1859) 148:198–202. CrossRefGoogle Scholar
  27. Chaudhary A, Verones F, De Baan L, Hellweg S (2015) Quantifying land use impacts on biodiversity: combining species-area models and vulnerability indicators. Environ Sci Technol 49(16):9987–9995. CrossRefGoogle Scholar
  28. Cook ASCP, Humphreys EM, Masden EA, Burton NHK (2014) The avoidance rates of collision between birds and offshore turbines. Scottish Marine Freshwater Sci 5(16):247 pp. Edinburgh: Scottish government. CrossRefGoogle Scholar
  29. Cook ASCP, Robinson RA (2017) Towards a framework for quantifying the population-level consequences of anthropogenic pressures on the environment: the case of seabirds and windfarms. J Environ Manag 190:113–121. CrossRefGoogle Scholar
  30. Cosme N, Jones MC, Cheung WWL, Larsen HF (2017) Spatial differentiation of marine eutrophication damage indicators based on species density. Ecol Indic 73:676–685. CrossRefGoogle Scholar
  31. Cryan PM, Barclay RMR, Arnett EB et al (2008) Mating behavior as a possible cause of bat fatalities at wind turbines. An Annu Rep Prep Bats Wind Energy Coop 14:1330–1340Google Scholar
  32. Cryan PM, Gorresen PM, Hein CD, Schirmacher MR, Diehl RH, Huso MM, Hayman DTS, Fricker PD, Bonaccorso FJ, Johnson DH, Heist K, Dalton DC (2014) Behavior of bats at wind turbines. Proc Natl Acad Sci 111(42):15126–15131. CrossRefGoogle Scholar
  33. Dahl EL (2014) Population dynamics in white-tailed eagle at an on-shore wind farm area in coastal NorwayGoogle Scholar
  34. Dai K, Bergot A, Liang C, Xiang WN, Huang Z (2015) Environmental issues associated with wind energy—a review. Renew Energy 75:911–921. CrossRefGoogle Scholar
  35. de Baan L, Mutel CL, Curran M et al (2013) Land use in life cycle assessment: global characterization factors based on regional and global potential species extinction. Environ Sci Technol 47:9281–9290CrossRefGoogle Scholar
  36. de Lucas M, Janss GFE, Whitfield DP, Ferrer M (2008) Collision fatality of raptors in wind farms does not depend on raptor abundance. J Appl Ecol 45(6):1695–1703. CrossRefGoogle Scholar
  37. Denzinger A, Schnitzler HU (2013) Bat guilds, a concept to classify the highly diverse foraging and echolocation behaviors of microchiropteran bats. Front Physiol 4:1–15CrossRefGoogle Scholar
  38. Diffendorfer JE, Beston JA, Merrill MD et al (2015) Preliminary methodology to assess the national and regional impact of U.S. wind energy development on birds and bats. doi:
  39. Drewitt AL, Langston RHW (2006) Assessing the impacts of wind farms on birds. Ibis (Lond 1859) 148:29–42. CrossRefGoogle Scholar
  40. Drewitt AL, Langston RHW (2008) Collision effects of wind-power generators and other obstacles on birds. Ann N Y Acad Sci 1134(1):233–266. CrossRefGoogle Scholar
  41. Duerr AE, Miller TA, Lanzone M, Brandes D, Cooper J, O'Malley K, Maisonneuve C, Tremblay J, Katzner T (2012) Testing an emerging paradigm in migration ecology shows surprising differences in efficiency between flight modes. PLoS One 7(4):e35548. CrossRefGoogle Scholar
  42. Edenhofer O, Pichs-Madruga R, Sokona Y et al (2012) Renewable energy sources and climate change mitigation: special report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USAGoogle Scholar
  43. Eichhorn M, Johst K, Seppelt R, Drechsler M (2012) Model-based estimation of collision risks of predatory birds with wind turbines. Ecol Soc 1/(2):1Google Scholar
  44. Elith J, Graham CH, Anderson RP et al (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography (Cop) 29(2):129–151. CrossRefGoogle Scholar
  45. Erickson RA, Eager EA, Stanton JC, Beston JA, Diffendorfer JE, Thogmartin WE (2015) Assessing local population vulnerability with branching process models: an application to wind energy development. Ecosphere 6(12):art254. CrossRefGoogle Scholar
  46. Erickson WP, Johnson GD, Young Jr DP (2005) A summary and comparison of bird mortality from anthropogenic causes with an emphasis on collisions. USDA for Serv gen tech PSW-GTR-19:1029–1042. Doi: Erickson, Wallace P, Gregory D Johnson, and David P young Jr. 2005. “A summary and comparison of bird mortality from anthropogenic causes with an emphasis on collisions”Google Scholar
  47. Evans A, Strezov V, Evans TJ (2009) Assessment of sustainability indicators for renewable energy technologies. Renew Sust Energ Rev 13(5):1082–1088. CrossRefGoogle Scholar
  48. Ferreira D, Freixo C, Cabral JA, Santos R, Santos M (2015) Do habitat characteristics determine mortality risk for bats at wind farms? Modelling susceptible species activity patterns and anticipating possible mortality events. Ecol Inform 28:7–18. CrossRefGoogle Scholar
  49. Furmankiewicz J, Kucharska M (2009) Migration of bats along a large river valley in southwestern Poland. J Mammal 90(6):1310–1317. CrossRefGoogle Scholar
  50. Furness RW, Wade HM, Masden EA (2013) Assessing vulnerability of marine bird populations to offshore wind farms. J Environ Manag 119:56–66. CrossRefGoogle Scholar
  51. García-Ripollés C, López-López P (2011) Integrating effects of supplementary feeding, poisoning, pollutant ingestion and wind farms of two vulture species in Spain using a population viability analysis. J Ornithol 152(4):879–888. CrossRefGoogle Scholar
  52. Garthe S, Hüppop O (2004) Scaling possible adverse effects of marine wind farms on seabirds: developing and applying a vulnerability index. J Appl Ecol 41(4):724–734. CrossRefGoogle Scholar
  53. Garvin JC, Jennelle CS, Drake D, Grodsky SM (2011) Response of raptors to a windfarm. J Appl Ecol 48(1):199–209. CrossRefGoogle Scholar
  54. GBIF (2017) Global Biodiversity Information Facility. Accessed 4 Jan 2018
  55. Green RE, Langston RHW, McCluskie A, Sutherland R, Wilson JD (2016) Lack of sound science in assessing wind farm impacts on seabirds. J Appl Ecol 53(6):1635–1641. CrossRefGoogle Scholar
  56. Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, Goss-Custard J, Grand T, Heinz SK, Huse G, Huth A, Jepsen JU, Jørgensen C, Mooij WM, Müller B, Pe’er G, Piou C, Railsback SF, Robbins AM, Robbins MM, Rossmanith E, Rüger N, Strand E, Souissi S, Stillman RA, Vabø R, Visser U, DeAngelis DL (2006) A standard protocol for describing individual-based and agent-based models. Ecol Model 198(1-2):115–126. CrossRefGoogle Scholar
  57. Grünkorn T, Blew J, Coppack T et al (2016) Ermittlung der Kollisionsraten von (Greif)Vögeln und Schaffung planungsbezogener Grundlagen für die Prognose und Bewertung des Kollisionsrisikos durch Windenergieanlagen (PROGRESS). pp 338Google Scholar
  58. Guisan A, Thuiller W (2005) Predicting species distribution: offering more than simple habitat models. Ecol Lett 8(9):993–1009. CrossRefGoogle Scholar
  59. Harte J, Smith AB, Storch D (2009) Biodiversity scales from plots to biomes with a universal species-area curve. Ecol Lett 12(8):789–797. CrossRefGoogle Scholar
  60. Hauschild MZ, Huijbregts MAJ (2015) Life cycle impact assessment. LCA compendium—the complete world of life cycle assessment. Springer Science+Business Media B.V., pp 1–16Google Scholar
  61. Hayes MA, Cryan PM, Wunder MB (2015) Seasonally-dynamic presence-only species distribution models for a cryptic migratory bat impacted by wind energy development. PLoS One 10:1–20Google Scholar
  62. Hein C, Schirmacher M (2016) Impact of wind energy on bats: a summary of our current knowledge. Human–Wildlife Interact 10(1):19–27Google Scholar
  63. Herrera-Alsina L, Villegas-Patraca R, Eguiarte LE, Arita HT (2013) Bird communities and wind farms: a phylogenetic and morphological approach. Biodivers Conserv 22(12):2821–2836. CrossRefGoogle Scholar
  64. Heymann Y, Steenmans C, Croissille G, Bossard M (2000) CORINE land cover technical guide. Off Publ Eur. Communities:1–94Google Scholar
  65. Hirzel AH, Hausser J, Chessel D, Perrin AN (2002) Ecological-niche factor analysis: how to compute habitat-suitability maps without absence data? Ecology 83(7):2027–2036CrossRefGoogle Scholar
  66. Hodos W (2003) Minimization of motion smear: reducing avian collisions with wind turbines. Subcontract Rep period Perform July 12, 1999- August 31, 2002 43Google Scholar
  67. Holmstrom LA, Hamer TE, Colclazier EM et al (2011) Assessing avian–wind turbine collision risk: an approach angle dependent model. Wind Eng 35(3):289–312. CrossRefGoogle Scholar
  68. Hötker H, Thomsen K, Jeromin H (2006) Impacts on biodiversity of exploitation of renewable energy sources: the example of birds and bats—facts, gaps in knowledge, demands for further research, and ornithological guidelines for the development of renewable energy exploitation. Michael-Otto-Institut im NABU, Berghusen, pp 1–65Google Scholar
  69. IEA (2016) Key Renewables Trends—Excerpt from: Renewables informationGoogle Scholar
  70. International Energy Agency (2013) Technology roadmap—wind energy. Technol Roadmap 58Google Scholar
  71. IUCN (2017) The IUCN Red List of Threatened Species - Version 2017-3. Accessed 4 Jan 2018
  72. Janss GFE (2000) Avian mortality from power lines: a morphologic approach of a species-specific mortality. Biol Conserv 95(3):353–359. CrossRefGoogle Scholar
  73. Johnson GD, Perlik MK, Erickson WP, Strickland MD (2004) Bat activity, composition, and collision mortality at a large wind plant in Minnesota. Wildl Soc Bull 32:1278–1288CrossRefGoogle Scholar
  74. Kartverket (2017) Geonorge. Accessed 28 Jul 2017
  75. Korner-Nievergelt F, Brinkmann R, Niermann I, Behr O (2013) Estimating bat and bird mortality occurring at wind energy turbines from covariates and carcass searches using mixture models. PLoS One 8(7):e67997. CrossRefGoogle Scholar
  76. Kunz TH, Arnett EB, Cooper BM et al (2007a) Assessing impacts of wind-energy development on nocturnally active birds and bats: a guidance document. J Wildl Manag 71(8):2449–2486. CrossRefGoogle Scholar
  77. Kunz TH, Arnett EB, Erickson WP, Hoar AR, Johnson GD, Larkin RP, Strickland MD, Thresher RW, Tuttle MD (2007b) Ecological impacts of wind energy development on bats: questions, research needs, and hypotheses. Front Ecol Environ 5(6):315–324Google Scholar
  78. Kuvlesky WP, Brennan LA, Morrison ML et al (2007) Wind energy development and wildlife conservation: challenges and opportunities. J Wildl Manag 71(8):2487–2498. CrossRefGoogle Scholar
  79. Lacy RC, Pollak JP (2014) Vortex: a stochastic simulation of the extinction process. Version 10.2.9. Chicago Zoological Society, Brookfield, Illinois, USAGoogle Scholar
  80. Langston RHW (2013) Birds and wind projects across the pond: a UK perspective. Wildl Soc Bull 37(1):5–18. CrossRefGoogle Scholar
  81. Langston RHW, Pullan JD (2003) Wind farms and birds: an analysis of the effects of wind farms on birds, and guidance on environmental assessment criteria and site selection issues. Report by BirdLife International and Royal Society for the Protection of Birds (RSPB), pp 58Google Scholar
  82. Larsen JK, Madsen J (2000) Effects of wind turbines and other physical elements on field utilization by pink-footed geese (Anser brachyrhynchus): a landscape perspective. Landsc Ecol 15(8):755–764. CrossRefGoogle Scholar
  83. Liechti F, Guélat J, Komenda-Zehnder S (2013) Modelling the spatial concentrations of bird migration to assess conflicts with wind turbines. Biol Conserv 162:24–32. CrossRefGoogle Scholar
  84. Madsen J, Boertmann D (2008) Animal behavioral adaptation to changing landscapes: spring-staging geese habituate to wind farms. Landsc Ecol 23(9):1007–1011. CrossRefGoogle Scholar
  85. Marques AT, Batalha H, Rodrigues S, Costa H, Pereira MJR, Fonseca C, Mascarenhas M, Bernardino J (2014) Understanding bird collisions at wind farms: an updated review on the causes and possible mitigation strategies. Biol Conserv 179:40–52. CrossRefGoogle Scholar
  86. Martínez E, Sanz F, Pellegrini S, Jiménez E, Blanco J (2009) Life cycle assessment of a multi-megawatt wind turbine. Renew Energy 34(3):667–673. CrossRefGoogle Scholar
  87. Masden EA (2010) Assessing the cumulative impacts of wind farms on birds. PhD thesis, University of GlasgowGoogle Scholar
  88. Masden EA, Cook ASCP (2016) Avian collision risk models for wind energy impact assessments. Environ Impact Assess Rev 56:43–49. CrossRefGoogle Scholar
  89. Masden EA, Fox AD, Furness RW, Bullman R, Haydon DT (2010a) Cumulative impact assessments and bird/wind farm interactions: developing a conceptual framework. Environ Impact Assess Rev 30(1):1–7. CrossRefGoogle Scholar
  90. Masden EA, Haydon DT, Fox AD, Furness RW, Bullman R, Desholm M (2009) Barriers to movement: impacts of wind farms on migrating birds. ICES J Mar Sci 66(4):746–753. CrossRefGoogle Scholar
  91. Masden EA, Haydon DT, Fox AD, Furness RW (2010b) Barriers to movement: modelling energetic costs of avoiding marine wind farms amongst breeding seabirds. Mar Pollut Bull 60(7):1085–1091. CrossRefGoogle Scholar
  92. Masden EA, Reeve R, Desholm M, Fox AD, Furness RW, Haydon DT (2012) Assessing the impact of marine wind farms on birds through movement modelling. J R Soc Interface 9(74):2120–2130. CrossRefGoogle Scholar
  93. May R (2015) A unifying framework for the underlying mechanisms of avian avoidance of wind turbines. Biol Conserv 190:179–187. CrossRefGoogle Scholar
  94. May R, Nygård T, Dahl EL, et al (2011) Collision risk in white-tailed eagles: Modelling kernel-based collision risk using satellite telemetry data in Smøla wind- power plant. In: NINA Rep. 692.
  95. May R, Gill AB, Köppel J, et al (2017) Future research directions to reconcile wind turbine–wildlife interactions. In: Wind energy and wildlife interactions. Springer, pp 255–276, DOI:
  96. May R, Hoel PL, Langston RHW et al (2010) Collision risk in white-tailed eagles. Modelling collision risk using vantage point observations in Smøla wind-power plant—NINA Report:639, 25 ppGoogle Scholar
  97. May R, Nygård T, Dahl EL, Bevanger K (2013) Habitat utilization in white-tailed eagles (Haliaeetus albicilla) and the displacement impact of the Smøla wind-power plant. Wildl Soc Bull 37(1):75–83. CrossRefGoogle Scholar
  98. May R, Reitan O, Bevanger K, Lorentsen SH, Nygård T (2015) Mitigating wind-turbine induced avian mortality: sensory, aerodynamic and cognitive constraints and options. Renew Sust Energ Rev 42:170–181. CrossRefGoogle Scholar
  99. Mcnew LB, Hunt LM, Gregory AJ et al (2014) Effects of wind energy development on nesting ecology of greater prairie-chickens in fragmented grasslands. Conserv Biol 28(4):1089–1099. CrossRefGoogle Scholar
  100. Miller TA, Brooks RP, Lanzone M et al (2014) Assessing risk to birds from industrial wind energy development via paired resource selection models. Conserv Biol 28(3):745–755. CrossRefGoogle Scholar
  101. Munday PL (2004) Habitat loss, resource specialization, and extinction on coral reefs. Glob Chang Biol 10(10):1642–1647. CrossRefGoogle Scholar
  102. NASA (2016) NASA Langley Research Center Atmospheric Science Data Center–Surface Meteorology and Solar Energy (SSE). Accessed 20 Jul 2016
  103. New L, Bjerre E, Millsap B, Otto MC, Runge MC (2015) A collision risk model to predict avian fatalities at wind facilities: an example using golden eagles, Aquila chrysaetos. PLoS One 10(7):e0130978. CrossRefGoogle Scholar
  104. Norberg UML (2006) Flight and scaling of flyers in nature. WIT transactions on state of the art in science and engineering, Vol 3, WIT press, ISSN 1755-8336, doi:
  105. NVE (2017) NVE Kartkatalog. Accessed 28 Jul 2017
  106. Pearce-Higgins J, Stephen L, Langston RHW, Bright J (2008) Assessing the cumulative impacts of wind farms on peatland birds: a case study of golden plover Pluvialis apricaria in Scotland. Mires Peat 4:1–13Google Scholar
  107. Pearce-Higgins JW, Stephen L, Douse A, Langston RHW (2012) Greater impacts of wind farms on bird populations during construction than subsequent operation: results of a multi-site and multi-species analysis. J Appl Ecol 49(2):386–394. CrossRefGoogle Scholar
  108. Pearce-Higgins JW, Stephen L, Langston RHW et al (2009) The distribution of breeding birds around upland wind farms. J Appl Ecol:1323–1331Google Scholar
  109. Pearson RG, Raxworthy CJ, Nakamura M, Townsend Peterson a. (2007) Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. J Biogeogr 34:102–117CrossRefGoogle Scholar
  110. Pedersen MB, Poulsen E (1991) Impact of a 90m/2MW wind turbine on birds: avian responses to the implementation of the Tjaereborg wind turbine at the Danish Wadden Sea. Danske Vildtundersogelser 47:1–44Google Scholar
  111. Pennycuick CJ (2008) Modelling the flying bird. ElsevierGoogle Scholar
  112. Pereira HM, Daily GC (2009) Modeling biodiversity dynamics in countryside landscapes published by: ecological Society of America Stable URL: your use of the JSTOR archive indicates your acceptance of JSTOR ’ s terms and conditions of use, avai. 87:1877–1885
  113. Petersen IK, Monique M, Rexstad EA et al (2011) Comparing pre- and post-construction distributions of long-tailed ducks Clangula hyemalis in and around the Nysted offshore wind farm, Denmark: a quasi-designed experiment accounting for imperfect detection, local surface features and autocorrelation. 1–16Google Scholar
  114. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190(3-4):231–259. CrossRefGoogle Scholar
  115. Pocewicz A, Estes-Zumpf WA, Andersen MD, et al (2013) Mapping migration: important places for Wyoming’s migratory birds. Pp 1–16Google Scholar
  116. Podolsky R (2008) Method of and article of manufacture for determining probability of avian collision. US pat 7,315,799 1:14 ppGoogle Scholar
  117. Rayner JMV (1988) Form and function in avian flight. Curr Ornithol 5:1–66Google Scholar
  118. Rebelo H, Jones G (2010) Ground validation of presence-only modelling with rare species: a case study on barbastelles Barbastella barbastellus (Chiroptera: Vespertilionidae). J Appl Ecol 47(2):410–420. CrossRefGoogle Scholar
  119. Reid T, Krüger S, Whitfield DP, Amar A (2015) Using spatial analyses of bearded vulture movements in southern Africa to inform wind turbine placement. J Appl Ecol 52(4):881–892. CrossRefGoogle Scholar
  120. Richardson WJ (1998) Bird migration and wind turbines: migration timing, flight behaviour and collision risk. Proc Natl Avian-Wind Power Plan Meet III 132–140Google Scholar
  121. Roscioni F, Rebelo H, Russo D, Carranza ML, di Febbraro M, Loy A (2014) A modelling approach to infer the effects of wind farms on landscape connectivity for bats. Landsc Ecol 29(5):891–903. CrossRefGoogle Scholar
  122. Rushworth I, Krüger S (2014) Wind farms threaten southern Africa’s cliff-nesting vultures. Ostrich 85(1):13–23. CrossRefGoogle Scholar
  123. Rydell J, Bach L, Dubourg-Savage M-J, Green M, Rodrigues L, Hedenström A (2010a) Mortality of bats at wind turbines links to nocturnal insect migration? Eur J Wildl Res 56(6):823–827. CrossRefGoogle Scholar
  124. Rydell J, Bach L, Dubourg-Savage M-J, Green M, Rodrigues L, Hedenström A (2010b) Bat mortality at wind turbines in northwestern Europe. Acta Chiropterologica 12(2):261–274. CrossRefGoogle Scholar
  125. Rydell J, Engström H, Swedish T et al (2012) The effect of wind power on birds and bats power—a synthesis. Naturvårdsverket, ISBN 9162065114, 9789162065119Google Scholar
  126. Santos H, Rodrigues L, Jones G, Rebelo H (2013) Using species distribution modelling to predict bat fatality risk at wind farms. Biol Conserv 157:178–186. CrossRefGoogle Scholar
  127. Sanz-Aguilar A, Sánchez-Zapata JA, Carrete M, Benítez JR, Ávila E, Arenas R, Donázar JA (2015) Action on multiple fronts, illegal poisoning and wind farm planning, is required to reverse the decline of the Egyptian vulture in southern Spain. Biol Conserv 187:10–18. CrossRefGoogle Scholar
  128. Schaub M (2012) Spatial distribution of wind turbines is crucial for the survival of red kite populations. Biol Conserv 155:111–118. CrossRefGoogle Scholar
  129. Schuster E, Bulling L, Köppel J (2015) Consolidating the state of knowledge: a synoptical review of wind energy’s wildlife effects. Environ Manag 56(2):300–331. CrossRefGoogle Scholar
  130. Smallwood KS, Rugge L, Morrison ML (2009) Influence of behavior on bird mortality in wind energy developments. J Wildl Manag 73(7):1082–1098. CrossRefGoogle Scholar
  131. Smallwood KS, Thelander CG (2004) Developing methods to reduce bird mortality in the Altamont Pass Wind Resource Area. Report by BioResource Consultants, pp 363Google Scholar
  132. Smallwood KS, Thelander CG, Morrison ML, Rugge LM (2007) Burrowing owl mortality in the Altamont Pass Wind Resource Area. J Wildl Manag 71(5):1513–1524. CrossRefGoogle Scholar
  133. Sovacool BK (2013) The avian benefits of wind energy: a 2009 update. Renew Energy 49:19–24. CrossRefGoogle Scholar
  134. Swihart RK, Gehring TM, Kolozsvary MB, Nupp TE (2003) Responses of ‘resistant’ vertebrates to habitat loss and fragmentation: the importance of niche breadth and range boundaries. Divers Distrib 9(1):1–18. CrossRefGoogle Scholar
  135. Tucker VA (1996a) Using a collision model to design safer wind turbine rotors for birds. J Sol Energy Eng 118(4):263. CrossRefGoogle Scholar
  136. Tucker VA (1996b) A mathematical model of bird collisions with wind turbine rotors. J Sol Energy Eng 118(4):253. CrossRefGoogle Scholar
  137. U.S. Geological Survey (2016) Earth Resources Observation and Science (EROS) Center. Accessed 20 Jul 2016
  138. Verones F, Bare J, Bulle C, Frischknecht R, Hauschild M, Hellweg S, Henderson A, Jolliet O, Laurent A, Liao X, Lindner JP, Maia de Souza D, Michelsen O, Patouillard L, Pfister S, Posthuma L, Prado V, Ridoutt B, Rosenbaum RK, Sala S, Ugaya C, Vieira M, Fantke P (2017a) LCIA framework and cross-cutting issues guidance within the UNEP-SETAC life cycle initiative. J Clean Prod 161:957–967. CrossRefGoogle Scholar
  139. Verones F, Huijbregts MAJ, Chaudhary A, de Baan L, Koellner T, Hellweg S (2015) Harmonizing the assessment of biodiversity effects from land and water use within LCA. Environ Sci Technol 49(6):3584–3592. CrossRefGoogle Scholar
  140. Verones F, Pfister S, van Zelm R, Hellweg S (2017b) Biodiversity impacts from water consumption on a global scale for use in life cycle assessment. Int J Life Cycle Assess 22(8):1247–1256. CrossRefGoogle Scholar
  141. Verones F, Saner D, Pfister S, Baisero D, Rondinini C, Hellweg S (2013) Effects of consumptive water use on biodiversity in wetlands of international importance. Environ Sci Technol 47(21):12248–12257. CrossRefGoogle Scholar
  142. Wade PR (1998) Calculating limits to the allowable human-caused mortality of cetaceans and pinnipeds. Mar Mammal Sci 14(1):1–37. CrossRefGoogle Scholar
  143. Wang S, Wang S, Smith P (2015) Ecological impacts of wind farms on birds: questions, hypotheses, and research needs. Renew Sust Energ Rev 44:599–607. CrossRefGoogle Scholar
  144. Warwick-Evans V, Atkinson PW, Walkington I, Green JA (2017) Predicting the impacts of windfarms on seabirds: an individual based model. J Appl Ecol.
  145. Wessman CA (1992) Spatial scale and global change: bridging the gap from plots to GCM grid cells. Annu Rev Ecol Syst 23(1):175–200. CrossRefGoogle Scholar
  146. Wilman H, Belmaker J, Simpson J, de la Rosa C, Rivadeneira MM, Jetz W (2014) EltonTraits 1.0: species-level foraging attributes of the world’s birds and mammals. Ecology 95(7):2027. CrossRefGoogle Scholar
  147. Winter Y (1999) Flight speed and body mass of nectar-feeding bats (Glossophaginae) during foraging. J Exp Biol 202(Pt 14):1917–1930Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Industrial Ecology ProgrammeNorwegian University of Science and Technology (NTNU)TrondheimNorway
  2. 2.Norwegian Institute for Nature Research (NINA)TrondheimNorway

Personalised recommendations