Predicting strike susceptibility and collision patterns of the common buzzard at wind turbine structures in the federal state of Brandenburg, Germany


Autoři: Anushika Bose aff001;  Tobias Dürr aff002;  Reinhard A. Klenke aff001;  Klaus Henle aff001
Působiště autorů: UFZ–Helmholtz Centre for Environmental Research, Department of Conservation Biology, Permoserstraße, Leipzig, Germany aff001;  Brandenburg State Agency for Environment, Brandenburg State Bird Conservation Centre, Nennhausen, Germany aff002
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0227698

Souhrn

With the increase in wind turbines, bird collisions have developed as a potential hazard. In the federal state of Brandenburg, Germany, despite the on-going mitigation efforts of increasing the distances of wind turbines from the breeding areas of the more severely affected populations of red kites (Milvus milvus), the additional detrimental influences on the buzzard populations (Buteo buteo) have added to the challenges for wind power expansion. Using data on the regional distribution of the buzzards, along with their carcass detections around the wind turbines (WTs), we aimed to better understand their collision distribution patterns in relation to their habitat use patterns to predict their exposure to collision risk using boosted regression trees (BRTs). Additionally, we integrated the developed collision potential map with the regional density map of buzzards to identify areas of increased strike susceptibility in turbine installations. Our study showed that the buzzard collisions were primarily concentrated at the turbines situated at sensitive distances from the edges of watercourses (>1000 metres), as well as those along the edges of grasslands (>750 metres), in the green open areas around/areas with minimal settlements (750 metres-1750 metres), and along the edges of bushlands (>1500 metres), together explaining 58% of the variance in their collision distribution. Conclusively, our study is applicable to conservation because it demonstrates the identification of potential collision areas along with the causes of the collisions, in addition to demonstrating the benefits of incorporating a species collision dataset as a proxy for species presence into species distribution models to make informed management decisions to eventually combat biodiversity loss.

Klíčová slova:

Alternative energy – Birds – Decision trees – Germany – Grasslands – Land use – Population density – Wind power


Zdroje

1. Moeller C, Meiss J, Mueller B, Hlusiak M, Breyer C, Kastner M, et al. Transforming the electricity generation of the Berlin–Brandenburg region, Germany. Renewable Energy. 2014; 39–50. doi: 10.1016/j.renene.2014.06.042

2. BMU- The German government's energy concept- long-term strategy for future energy supply; 2010.

3. Meyerhoff J, Ohl C & Hartje V. Landscape externalities from onshore wind power. Energy Policy. 2010; 38 (1): 82–92. doi: 10.1016/j.enpol.2009.08.055

4. Tikkanen H, Chiebao FB, Laaksonen T, Pakanen VM & Rytkoenen S. Habitat use of flying subadult White-tailed Eagles (Haliaeetus albicilla): implications for land use and wind power plant planning. Ornis Fennica. 2018; 95: 137–150.

5. Martín B, Perez-Bacalu B, Onrubia C, de Lucas A & Ferrer M. Impact of wind farms on soaring bird populations at a migratory bottleneck. European Journal of Wildlife Research. 2018; 64: 1–10. doi: 10.1007/s10344-018-1192-z

6. Watson R, Kolar P, Ferrer M, Nygard T, Johnston N, Hunt G et al. Raptor interactions with wind energy: case studies from around the world. Journal of Raptor Research. 2018; 52(1): 1–18. doi: 10.3356/JRR-16-100.1

7. de Lucas M, Ferrer M, Bechard MJ & Muñoz AR. Griffon Vulture mortality at wind farms in southern Spain: distribution of fatalities and active mitigation measures. Biological Conservation. 2012; 147:184–189. doi: 10.1016/j.biocon.2011.12.029

8. Carrete M, Sanchez-Zapata JA, Benitez JR, Lobon M & Donazar JA. Large scale risk-assessment of windfarms on population viability of a globally endangered long-lived raptor. Biological Conservation. 2009; 142: 2954–2961. doi: 10.1016/j.biocon.2009.07.027

9. Drewitt AL & Langston RHW. Assessing the impacts of wind farms on birds. Ibis. 2006; 148: 29–42. doi: 10.1111/j.1474-919X.2006.00516.x

10. Beston JA, Diffendorfer JE, Loss SR & Johnson DH. Prioritizing Avian Species for Their Risk of Population-Level Consequences from Wind Energy Development. PLOS ONE. 2016; 11(3): e0150813. doi: 10.1371/journal.pone.0150813 26963254

11. de Lucas M, Janss G & Ferrer M. The effects of a wind farm on birds in a migration point: the Strait of Gibraltar. Biodiversity and Conservation. 2004; 13: 395–407. doi: 10.1023/B:BIOC.0000006507.22024.93

12. de Lucas M, Janss G, Whitfield DP & Ferrer M. Collision fatality of raptors in wind farms does not depend on raptor abundance. Journal of Applied Ecology. 2008; 45:1695–1703. doi: 10.1111/j.1365-2664.2008.01549.x

13. Krone O & Scharnweber C. Two White-Tailed Sea Eagles (Haliaeetus albicilla) Collide with Wind Generators in Northern Germany. Journal of Raptor Research. 2003; 37(2): 174–176.

14. Langston R & Pullan J. Windfarms and Birds: An Analysis of the Effects of Windfarms on Birds, and Guidance on Environmental Assessment Criteria and Site Selection Issues; 2003. Report by BirdLife International.

15. Saether BE, Bakke O. Avian Life History Variation and Contribution of Demographic Traits to the Population Growth Rate. Ecology. 2000; 81: 642–653. doi: 10.1890/0012-9658(2000)081[0642:ALHVAC]2.0.CO;2

16. Hunt WG. Golden eagles in a perilous landscape—Predicting the effects of mitigation for wind turbine blade-strike mortality: Sacramento, California, Consultant Report to California Energy Commission under contract P500-02-043F, Public Interest Energy Research. 2002. pp. 72.

17. Bellebaum J, Korner-Nievergelt F, Dürr T & Mammen U. Wind turbine fatalities approach a level of concern in a raptor population. Journal of Nature Conservation. 2013; 21:394–400. doi: 10.1016/j.jnc.2013.06.001

18. de Lucas M, Janss G & Ferrer M. Birds and Wind Farms. Risk assessment and mitigation. Editorial Quercus, Madrid 2007; 280.

19. Der NEP. Neue Netze für Neue Energien- Erläuterungen und Überblick der Ergebnisse; 2012

20. LBV. Strukturatlas Land Brandenburg. Potsdam: Landesamt für Bauen und Verkehr. 2012. Available from: http://www.strukturatlas.brandenburg.de/

21. Twele J, Mueller B, Moeller C & Hlusia M. Szenarioberechnung einer Strom-und Wärmeversorgung der Region Brandenburg-Berlin auf Basis Erneuerbarer Energien. Berlin: Reiner Lemoine Institut; 2012.

22. The windpower- wind turbines and wind farms database of Brandenburg. 2012. Available from http://www.thewindpower.net/zones_en_2_brandenburg.php

23. EEG-Anlagenregister Berlin. Deutsche Gesellschaft für Sonnenenergie e.V. 2011; Available from: http://www.energymap.info.

24. LBV. Strukturatlas Brandenburg. Landesamt für Bauen und Verkehr. 2010. Available from: http://www.strukturatlas.brandenburg.de/

25. Grünkorn T, Blew J, Krüger O, Potiek A & Reichenbach M. A Large-Scale, Multispecies Assessment of Avian Mortality Rates at Land-Based Wind Turbines in Northern Germany In Köppel J (eds) Wind Energy and Wildlife Interactions: Presentations from the CWW2015 Conference (2017). Springer International Publishing. 2017. pp. 43–64.

26. Grünkorn T, Blew J, Coppack T, Krüger O & Nehls G. Prognosis and assessment of bird collision risks at wind turbines in northern Germany (PROGRESS). Final report commissioned by the Federal Ministry for Economic affairs and Energy in the framework of the 6. Energy research programme of the federal government; 2016. Available from: https://bioconsult-sh.de/site/assets/files/1575/1575.pdf

27. Eichhorn M, Johst K, Seppelt R & Drechsler M. Model-based estimation of collision risks of predatory birds with wind turbines. Ecology and Society. 2012; 17(2): 1. doi: 10.5751/ES-04594-170201

28. Dürr T. Vogelunfälle an Windradmasten. Der Falke. 2011; 58: 498–501.

29. Grünkorn T, Diederich A, Poszig D, Diederichs B & Nehls G. Wie viele Vögel kollidieren mit Windenergieanlagen? Natur und Landschaft. 2009; 84 (7): 309–14. doi: 10.1371/journal.pone.0162638

30. Walker G, Devine-Wright P, Hunter S, High H & Evans B. Trust and community: Exploring the meanings, contexts and dynamics of community renewable energy. Energy Policy. 2010; 38: 2655–2663. doi: 10.1016/j.enpol.2009.05.055

31. Carrete M, Sanchez-Zapata JA, Benitez JR, Lobon M, Montoya F & Donazar JA. Mortality at windfarms is positively related to large-scale distribution and aggregation in Griffon Vultures. Biological Conservation. 2012; 145:102–108. doi: 10.1016/j.enpol.2009.08.055

32. de Lucas M, Janss G & Ferrer M. A bird and small mammal BACI and IG design studies in a wind farm in Malpica (Spain). Biodiversity and Conservation. 2005; 14: 3289–3303.

33. Tikkanen H, Rytkoenen S, Karlin OP, Ollila T, Pakanen VM et al. Modelling golden eagle habitat selection and flight activity in their home ranges for safer wind farm planning. Environmental Impact Assessment Review. 2018; 71: 120–131. doi: 10.1016/j.eiar.2018.04.006

34. Ferrer M, de Lucas M, Janss GFE, Casado E, Muñoz AR, Bechard MJ et al. Weak relationship between risk assessment studies and recorded mortality in wind farms. Journal of Applied Ecology. 2012; 49: 38–46. doi: 10.1111/j.1365-2664.2011.02054.x

35. LAG VSW (Länderarbeitsgemeinschaft der Staatlichen Vogelschutzwarten in Deutschland). Abstandsempfehlungen für Windenergieanlagen zu bedeutsamen Vogellebensräumen sowie Brutplätzen ausgewählter Vogelarten in der Überarbeitung. 2015. Available from https://www.nabu.de/imperia/md/content/nabude/vogelschutz/150526-lag-vsw_-abstandsempfehlungen.pdf

36. Dürr T. Zur Gefährdung des Rotmilans (Milvus milvus) durch Windenergieanlagen in Deutschland. Inf.-dienst Naturschutz Niedersachsen. 2009; 29: 185–191.

37. Dürr T & Langgemach T. Populationsökologie Greifvogel- und Eulenarten. 2006; 5: 483–490.

38. Weinhold N. Neuer Problemvogel für die Windkraft. Erneuerbare Energien. 2016. Available from: http://www.erneuerbareenergien.de/neuer-problemvogel-fuer-die-windkraft/150/434/92551/

39. Elith J, Leathwick JR & Hastie T. A working guide to boosted regression trees. Journal of Animal Ecology. 2008; 77: 802–813. doi: 10.1111/j.1365-2656.2008.01390.x 18397250

40. De’ath G. Boosted trees for ecological modeling and prediction. Ecology. 2007; 88: 243–251. doi: 10.1890/0012-9658(2007)88[243:btfema]2.0.co;2 17489472

41. Ender C. Wind energy use in Germany- Status 31.12.2014. DEWI Magazine. 2015; 46: 26–37.

42. Quitter J. Brandenburg is world's no.1 region for wind energy development. Wind Power Monthly. 2010. Available from http://www.windpowermonthly.com/article/1029660/brandenburg-worlds-no1-region-wind-energy-development

43. Walker B. Power places 1. Brandenburg. Wind Power Monthly. 2010. Available from: http://www.windpowermonthly.com/article/1029660/brandenburg-worlds-no1-region-wind-energy-development

44. Bose A, Dürr T, Klenke RA & Henle K. Collision sensitive niche profile of the worst affected bird-groups at wind turbine structures in the Federal State of Brandenburg, Germany. Scientific Reports. 8; 3777. doi: 10.1038/s41598-018-22178-z 29491479

45. Dürr T. Vogelverluste an Windenergieanlagen in Deutschland. Daten aus der zentralen Fundkartei der Staatlichen Vogelschutzwarte. Landesamt für Umwelt, Gesundheit und Verbraucherschutz Brandenburg. 2014. Available from: http://www.mugv.brandenburg.de/cms/detail.php/bb2.c.451792.de

46. Erickson W, Wolfe M, Bay K, Johnson D, & Gehring JL. A comprehensive analysis of small-passerine fatalities from collision with turbines at wind energy facilities. PLOS ONE. 2014; 9(9): e107491. doi: 10.1371/journal.pone.0107491 25222738

47. BTLNK–Brandenburg Landesamt für Umwelt, Landwirtschaft und Geologie. Kartiereinheiten der Biotoptyen und Landnutzungskartierung Brandenburg; 2011. Available from: http://www.lugv.brandenburg.de/cms/media.php/lbm1.a.3310.de/btopkart.pdf

48. Hastie T, Tibshirani R & Friedman JH. The Elements of Statistical Learning: Data Mining: Inferences and Predictions. Springer, New York; 2011.

49. Friedman JH. Greedy function approximation: a gradient boosting machine. Annals of Statistics. 2001; 29: 1189–1232. doi: 10.1214/aos/1013203451

50. Heuck C, Brandl R, Albrecht J & Gottschalk TK. The potential distribution of the red kite (Milvus milvus) in Germany. Journal of Ornithology. 2013; 154: 911–921. doi: 10.1007/s10336-013-0955-2

51. Dormann CF, Elith J & Bacher S. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography. 2013; 36: 27–46. doi: 10.1111/j.1600-0587.2012.07348.x

52. Torres LG, Smith TD, Sutton P, MacDiarmid A, Banister & Miyashita T. From exploitation to conservation: Habitat models using whaling data predict distribution patterns and threat exposure of an endangered whale. Diversity and Distributions. 2013; 19(9): 1138–1152. doi: 10.1111/ddi.12069

53. Hijmans RJ, Phillips S, Leathwick J & Elith J. Package ‘dismo’; 2013. Available from http://cran.r-project.org/web/packages/dismo/index.html.

54. R Development Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. 2017. Available from: http://www.R-project.org

55. Fawcett T. An introduction to ROC analysis. Pattern Recognition Letters. 2006; 27: 861–874. doi: 10.1016/j.patrec.2005.10.010

56. Buston PM & Elith J. Determinants of reproductive success in dominant pairs of clownfish: a boosted regression tree analysis. Journal of Animal Ecology. 2011; 80: 528–538. doi: 10.1111/j.1365-2656.2011.01803.x 21284624

57. Ryslavy T, Haupt H & Beschow R. Die Brutvögel in Brandenburg und Berlin—Ergebnisse der ADEBAR-Kartierung 2005–2009. Otis Bd, 19 Sonderheft; 2011.

58. ESRI Inc. ArcGIS 10.1. Environmental Systems Research Institute, Inc., CA, USA; 2012.

59. LUGV–Landesamt für Umwelt, Gesundheit und Verbraucherschutz Brandenburg. Windkraftanlagen im Land Brandenburg. 2014. Interne Bezeichnung LUGV: WKA.

60. Hijmans RJ & Etten JV. raster: Geographic analysis and modeling with raster data. R package version 2.0–12. 2012. Available from: http://CRAN.R-project.org/package = raster

61. Weitekamp S, Timmermann H & Reichenbach H. Progress—predictive modelling versus empirical data—collision numbers in relation to flight activity in 55 German wind farm seasons. In Köppel J (eds) Wind Energy and Wildlife Interactions: Presentations from the CWW2015 Conference (2017). 2015. Springer International Publishing. pp. 242.

62. Langgemach T & Dürr T. Informationen über Einflüsse der Windenergienutzung auf Vögel. Landesamt für Umwelt, Gesundheit und Verbraucherschutz, Staatliche Vogelschutzwarte. 2015. Available from: https://lfu.brandenburg.de/media_fast/4055/vsw_dokwind_voegel.pdf

63. Schreiber M. Artenschutz und Windenergieanlagen. Anmerkungen zur aktuellen Fachkonvention der Vogelschutzwarten. Naturschutz und Landschaftsplanung. 2014; 46(12): 361–369.

64. Hötker H, Krone O & Nehls G. Greifvögel und Windkraftanlagen: Problemanalyse und Lösungsvorschläge. Schlussbericht für das Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit., Michael-Otto-Institut im NABU, Leitnitz-Institut für Zoo- und Wildtierforschung, BioConsult SH, Bergenhusen, Berlin, Husum; 2013. Available from: https://www.bmu.de/files/english/pdf/application/pdf/energiekonzept_bundesregierung_en.pdf

65. Rasran L & Dürr T. Kollisionen von Greifvögeln an Windenergieanlagen—Analyse der Fundumstände. In: Hötker H, Krone O, Nehls G (eds) Greifvögel und Windkraftanlagen: Problemanalyse und Lösungsvorschläge. Schlussbericht für das Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit, FKZ 0327684, Michael-Otto-Institut im NABU, Leibniz-Institut für Zoo- und Wildtierforschung, BioConsult SH, Bergenhusen, Berlin, Husum. 2013. Available from: https://bergenhusen.nabu.de/imperia/md/nabu/images/nabu/enrichtungen/bergenhusen/projekte/bmugreif/endbericht_griefvogelprojekt.pdf

66. Illner H. Kritik an den EU-Leitlinien „Windenergie-Entwicklung und NATURA 2000“, Herleitung vogelartspezifischer Kollisionsrisiken an Windenergieanlagen und Besprechung neuer Forschungsarbeiten. Eulen-Rundblick. 2012; 62: 83–100.

67. Guillera-Arroita G. Modelling of species distributions, range dynamics and communities under imperfect detection: advances, challenges and opportunities. Ecography. 2017; 40: 281–295. doi: 10.1111/ecog.02445

68. Lahoz-Monfort JJ. Imperfect detection impacts the performance of species distribution models. Global Ecological Biogeography. 2014; 23: 504–515. doi: 10.1111/geb.12138

69. Hull CL & Muir S. Search areas for monitoring bird and bat carcasses at wind farms using a Monte-Carlo model. Australasian. Journal of Environmental Management. 2010; 17: 77–87. doi: 10.1080/14486563.2010.9725253

70. Kéry M. Predicting species distributions from checklist data using site-occupancy models. Journal of Biogeography. 2010; 37: 1851–1862. doi: 10.1111/j.1365-2699.2010.02345.x

71. Schaub M. Spatial distribution of wind turbines is crucial for the survival of red kite populations. Biological Conservation. 2012; 155: 111–118. doi: 10.1016/j.biocon.2012.06.021

72. Vasilakis DP, Whitfield DP & Kati V. A balanced solution to the cumulative threat of industrialized wind farm development on cinereous vultures (Aegypius monachus) in south-eastern Europe. PLOSONE. 2017; 12: e0172685. doi: 10.1371/journal.pone.0172685 28231316

73. Vasilakis DP, Whitfield DP, Schindler S, et al. Reconciling endangered species conservation with wind farm development: cinereous vultures (Aegypius monachus) in south-eastern Europe. Biological Conservation. 2016; 196: 10–17. doi: 10.1016/j.biocon.2016.01.014

74. Reid T, Krüger S, Whitfield DP & Amar A. Using spatial analyses of bearded vulture movements in southern Africa to inform wind turbine placement. Journal of Applied Ecology. 2015; 52: 881–892. doi: 10.1111/1365-2664.12468

75. Bauer HG, Berthold P, Boye W, Knief P, Südbeck, et al. Rote Liste der Brutvögel Deutschlands 3., überarbeitete Fassung. Ber. Vogelschutz. 2002; 3: 50.

76. Stadt Rheinbach. Artenschutzrechtlicher Fachbeitrag zum Bebauungsplan der Stadt Rheinbach. Ing.- und Planungsbüro LANGE GbR. 65. 2015. Available from: http://www.rheinbach.de/imperia/md/content/cms121/bauenwohnenundstadtentwicklung/stadtentwicklung/181115_artenschutzrechtlicher_fachbeitrag.pdf

77. ABBO: Die Vogelwelt von Brandenburg und Berlin. Rangsdorf; 2001.

78. Bergen F. Untersuchungen zum Einfluss der Errichtung und des Betriebs von Windenergieanlagen auf Vögel im Binnenland. Dissertation. Ruhr Universität Bochum; 2001.

79. Sinning F & Gerjets D. Untersuchungen zur Annäherung rastender Vögel an Windparks in Nordwestdeutschland. Bremer Beiträge für Naturkunde und Naturschutz Bd. 1999; 4: 53–60.

80. Kuemmerle T, Levers C, Erb K, et al. Hotspots of land use change in Europe. Environmental Research Letters. 2016; 11: 064020. doi: 10.1088/1748-9326/11/6/064020

81. Mülner B. Winterliche Bestandsdichten, Habitatspräferenzen und Ansitzwartenwahl von Mäusebussard (Buteo buteo) und Turmfalke (Falco tinnunculus) im oberen Murtal (Steiermark). Egretta. 2000; 43: 20–36.

82. Probst R. Greifvogelu¨berwinterung 1998 bis 2002 im Bleistätter Moos, Kärnten. Carinthia II. 2002; 114: 509–516.

83. Penteriani V & Faivre B. Breeding density and landscape-level habitat selection of common Buzzards (Buteo Buteo) in a mountain area (Abruzzo Apennines, Italy). Journal of Raptor Research. 1997; 31(3): 208–212.

84. Hubert. Nest-site habitat selected by Common Buzzard (Buteo buteo) in south western France. Journal of Raptor Research. 1993; 27: 102–105.

85. Glutz von Blotzheim UN, Bauer KM & Bezzel E. Handbuch der Vögel Mitteleuropas. Bd. 9: Falconiformes. Aula-Verlag, Wiesbaden. 1989.

86. Graham IM, Redpatha SM & Thirgood SJ. The diet and breeding density of Common Buzzards (Buteo buteo) in relation to indices of prey abundance. Bird Study. 1995; 42: 165–173. doi: 10.1080/00063659509477162

87. Hohmann U. Status specific habitat use in the Common Buzzard (Buteo buteo). Raptor Conservation Today. Proc. IV World Conference on Birds of Prey and Owls. WWGBP/The Pica Press, Berlin, Germany; 1994: 359–366.

88. Schindler S, Hohmann U, Probst R, Nemeschkal HL & Spitzer G. Territoriality and habitat use of common Buzzards (Buteo buteo) during late autumn in northern Germany. Journal of Raptor Research. 2012; 46: 149–157. doi: 10.3356/JRR-11-22.1

89. Cerasoli M & Penteriani V. Nest-site and aerial meeting point selection, nesting density and reproduction of Common Buzzards. Journal Raptor Research. 1996; 30: 130–135.

90. Kenward RE, Clarke RT, Hodder KH & Walls SS. Density and linkage estimators of home range: nearest-neighbor clustering defines multinuclear cores. Ecology. 2001a; 82: 1905–1920. doi: 10.1890/0012-9658(2001)082[1905:DALEOH]2.0.CO;2

91. Kenward RE, Hall DG, Walls SS & Hodder KH. Factors affecting predation by Buzzards (Buteo buteo) on pheasants (Phasianus colchicus). Journal of Applied Ecology. 2001b; 38: 813–822. doi: 10.1046/j.1365-2664.2001.00636.x

92. Newton I. Population ecology of raptors, Second Ed. T. and A.D. Poyser. Berkhamsted, U.K; 1990.


Článek vyšel v časopise

PLOS One


2020 Číslo 1