Hostname: page-component-5447f9dfdb-tm5m8 Total loading time: 0 Render date: 2025-07-28T23:27:51.796Z Has data issue: false hasContentIssue false
  • English
  • Français

Assessing the spatial overlap between planned offshore wind farms and wintering waterbirds: a Baltic Sea case study

Published online by Cambridge University Press:  04 June 2025

Dominik Marchowski Open the ORCID record for Dominik Marchowski [Opens in a new window] ,
Fredric Haas Open the ORCID record for Fredric Haas [Opens in a new window] ,
Tomasz Chodkiewicz Open the ORCID record for Tomasz Chodkiewicz [Opens in a new window]  and
Włodzimierz Meissner Open the ORCID record for Włodzimierz Meissner [Opens in a new window]
Dominik Marchowski*
Affiliation:
Ornithological Station, Museum and Institute of Zoology, https://ror.org/01dr6c206 Polish Academy of Sciences , Gdańsk, Poland
Fredric Haas
Affiliation:
Biodiversity and Evolution, Department of Biology, Lund University, Lund, Sweden
Tomasz Chodkiewicz
Affiliation:
Ornithological Lab, Museum and Institute of Zoology, Polish Academy of Sciences, Warsaw, Poland
Włodzimierz Meissner
Affiliation:
Ornithology Unit, Department of Vertebrate Ecology and Zoology, Faculty of Biology, University of Gdańsk, Gdańsk, Poland
*
Corresponding author: Dominik Marchowski; Email: dmarchowski@miiz.waw.pl
Get access Rights & Permissions [Opens in a new window]

Summary

This study presents a novel approach using machine learning, specifically Random Forest modelling, to create a sensitivity map that addresses the conflict between offshore wind farms (OWFs) and wintering waterbirds in the southern Baltic Sea. This region is crucial or of great importance for wintering species such as the Long-tailed Duck Clangula hyemalis and Velvet Scoter Melanitta fusca. In 2020, the southern and central Baltic Sea hosted approximately one million wintering birds, including over 560,000 Long-tailed Ducks (35% of the species’ biogeographical population), 230,000 Velvet Scoters (41% of the global population), and 4,500 Black Guillemot Cepphus grylle (8% of the Baltic population). Within the Polish Exclusive Economic Zone (PEEZ), 21 wind farms are planned, totalling a capacity of 17.6 GW with an estimated 1,164 turbines. To assess potential risks, a Normalised Overlap Index (NOI) was calculated for each wind farm, quantifying the level of potential threat to wintering birds. High conflict zones, such as the Southern Middle Bank and Pomeranian Bay, were identified, where wind farms significantly overlap with areas of high bird density. Although the wind farms do not intersect with Natura 2000 sites, partial overlaps with Important Bird Areas (IBAs) were noted. The method developed in this study not only addresses the challenges in the Baltic Sea but also offers potential applications in other marine and terrestrial environments. This framework provides a novel tool for evaluating and mitigating the impacts of renewable energy development on wildlife, contributing to the sustainable expansion of green energy solutions globally.

Keywords

Baltic SeaBird conservationEnvironmental impact assessmentMachine learningMarine biodiversityRenewable energy impactRisk mitigationSensitivity mappingSpatial analysisWintering waterbirds

Information

Type
Research Article
Information
Bird Conservation International , Volume 35 , 2025 , e15
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of BirdLife International

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Akinyelu, A.A. and Adewumi, A.O. (2014). Classification of phishing email using random forest machine learning technique. Journal of Applied Mathematics 2014, 425731. https://doi.org/10.1155/2014/425731CrossRefGoogle Scholar
Allison, T.D., Jedrey, E. and Perkins, S. (2008). Avian issues for offshore wind development. Marine Technology Society Journal 42, 28–38. https://doi.org/10.4031/002533208786829115CrossRefGoogle Scholar
Bailey, H., Brookes, K.L. and Thompson, P.M. (2014). Assessing environmental impacts of offshore wind farms: lessons learned and recommendations for the future. Aquatic Biosystems 10, 8. https://doi.org/10.1186/2046-9063-10-8CrossRefGoogle ScholarPubMed
Bartier, P.M. and Keller, C.P. (1996). Multivariate interpolation to incorporate thematic surface data using inverse distance weighting (IDW). Computers & Geosciences 22, 795–799.10.1016/0098-3004(96)00021-0CrossRefGoogle Scholar
BirdLife International (2025). Site factsheet: Södra Midsjöbanken. Downloaded from https://datazone.birdlife.org/site/factsheet/southern-midsjö-bank (accessed 29 May 2025).Google Scholar
BirdLife International (2020). Melanitta fusca. The IUCN Red List of Threatened Species 2020: e.T22724836A183801134. Available at https://doi.org/10.2305/IUCN.UK.2020-3.RLTS.T22724836A183801134.en (accessed 12 April 2024).CrossRefGoogle Scholar
Bradbury, G., Trinder, M., Furness, B., Banks, A.N., Caldow, R.W.G. and McDonald, J. (2017). Correction: Mapping seabird sensitivity to offshore wind farms. PLOS ONE 12, e0170863. https://doi.org/10.1371/journal.pone.0170863CrossRefGoogle ScholarPubMed
Buckland, S.T., Rexstad, E.A., Marques, T.A. and Oedekoven, C.S. (2015). Distance Sampling: Methods and Applications. Cham: Springer. https://doi.org/10.1007/978-3-319-19219-2CrossRefGoogle Scholar
Burnham, K.P. and Anderson, D.R. (2004). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach. New York: Springer.10.1007/b97636CrossRefGoogle Scholar
Chodkiewicz, T., Chylarecki, P., Sikora, A., Wardecki, Ł., Bobrek, R., Neubauer, G. et al. (2019). Report on the implementation of art. 12 of the Birds Directive in Poland in 2013–2018: status, changes, threats. Biuletyn Monitoringu Przyrody 20, 1–80.Google Scholar
Christensen, T.K., Hounisen, J.P., Clausager, I. and Petersen, I.K. (2004). Visual and Radar Observations of Birds in Relation to Collision Risk at the Horns Rev Offshore Wind Farm. Ronde, Denmark: National Environmental Research Institute.Google Scholar
Chylarecki, P., Chodkiewicz, T., Neubauer, G., Sikora, A., Meissner, W., Woźniak, B. et al. (2018). Birds Population Trends in Poland. Warsaw: Chief Inspectorate for Environmental Protection.Google Scholar
Dagys, M. and Hearn, R. (compilers) (2018). International Single Species Action Plan for the Conservation of the Velvet Scoter W Siberia & N Europe/NW Europe population. AEWA Technical Series No. 67. https://www.unep-aewa.org/sites/default/files/publication/velvet_scoter_11022020.pdfGoogle Scholar
Desholm, M. and Kahlert, J. (2005). Avian collision risk at an offshore wind farm. Biological Letters 1, 296–298. https://doi.org/10.1098/rsbl.2005.0336CrossRefGoogle Scholar
Dias, M.P., Martin, R., Pearmain, E.J., Burfield, I.J., Small, C., Phillips, R.A. et al. (2019). Threats to seabirds: A global assessment. Biological Conservation 237, 525–537. https://doi.org/10.1016/j.biocon.2019.06.033CrossRefGoogle Scholar
Díaz, H. and Guedes Soares, C. (2020). Review of the current status, technology, and future trends of offshore wind farms. Ocean Engineering 209, 107381. https://doi.org/10.1016/j.oceaneng.2020.107381CrossRefGoogle Scholar
Dickinson, M., Rutherford, M. and Gunton, T. (2010). Principles for integrated marine planning: A review of international experience. Environments Journal 37, 21–46.Google Scholar
Dierschke, V., Furness, R.W. and Garthe, S. (2016). Seabirds and offshore wind farms in European waters: Avoidance and attraction. Biological Conservation 202, 59–68. https://doi.org/10.1016/j.biocon.2016.08.016CrossRefGoogle Scholar
Donald, P.F., Fishpool, L.D.C., Ajagbe, A., Bennun, L.A., Bunting, G., Burfield, I.J. et al. (2019). Important Bird and Biodiversity Areas (IBAs): the development and characteristics of a global inventory of key sites for biodiversity. Bird Conservation International 29, 177–198. https://doi.org/10.1017/S0959270918000102CrossRefGoogle Scholar
Durinck, J., Skov, H., Jensen, F.P. and Pihl, S. (1994). Important Marine Areas for Wintering Birds in the Baltic Sea. Copenhagen: Ornis Consult Ltd.Google Scholar
Fox, A.D. and Petersen, I.K. (2019). Offshore wind farms and their effects on birds. Dansk Ornitologisk Forenings Tidsskrift 113, 86–97.Google Scholar
Furness, R.W., Garthe, S., Trinder, M., Matthiopoulos, J., Wanless, S. and Jeglinski, J. (2018). Nocturnal flight activity of northern gannets Morus bassanus and implications for modelling collision risk at offshore wind farms. Environmental Impact Assessment Review 73, 1–6. https://doi.org/10.1016/j.eiar.2018.06.006CrossRefGoogle Scholar
Furness, R.W., Wade, H.M. and Masden, E.A. (2013). Assessing vulnerability of marine bird populations to offshore wind farms. Journal of Environmental Management 119, 56–66. https://doi.org/10.1016/j.jenvman.2013.01.025CrossRefGoogle ScholarPubMed
Garthe, S., Schwemmer, H., Peschko, V., Markones, N., Müller, S., Schwemmer, P. et al. (2023). Large-scale effects of offshore wind farms on seabirds of high conservation concern. Scientific Reports 13, 4779. https://doi.org/10.1038/s41598-023-31601-zCrossRefGoogle ScholarPubMed
Glasson, J., Durning, B., Welch, K. and Olorundami, T. (2022). The local socio-economic impacts of offshore wind farms. Environmental Impact Assessment Review 95, 106783. https://doi.org/10.1016/j.eiar.2022.106783CrossRefGoogle Scholar
Hall, R. and Black, J. (2024). What level of monitoring is enough to detect displacement effects of offshore wind farms? Environmental Impact Assessment Review 105, 107449. https://doi.org/10.1016/j.eiar.2024.107449CrossRefGoogle Scholar
Hearn, R.D., Harrison, A.L. and Cranswick, P.A. (2015). International Single Species Action Plan for the Conservation of the Long-tailed Duck Clangula hyemalis, 2016–2025. AEWA Technical Series. http://www.unep-aewa.org/sites/default/files/document/mop6_27_draft_issap_ltd.pdfGoogle Scholar
HELCOM, H. (2021). Guidelines for monitoring seabirds at sea. HELCOM, Helsinki. Available at https://helcom.fi/wp-content/uploads/2021/11/HELCOM-Monitoring-guidelines-for-seabirds-at-sea-monitoring.pdf (accessed 29 May 2023).Google Scholar
HELCOM (2023). Abundance of Waterbirds in the Wintering Season. HELCOM Core Indicator Report. Available at https://indicators.helcom.fi/indicator/waterbirds-wintering-season/ (accessed 27 March 2024).Google Scholar
Joschko, P., Widok, A.H., Appel, S., Greiner, S., Albers, H. and Page, B. (2015). Modeling and simulation of offshore wind farm O&M processes. Environmental Impact Assessment Review 52, 31–39. https://doi.org/10.1016/j.eiar.2014.09.009CrossRefGoogle Scholar
Kelsey, E.C., Felis, J.J., Czapanskiy, M., Pereksta, D.M. and Adams, J. (2018). Collision and displacement vulnerability to offshore wind energy infrastructure among marine birds of the Pacific Outer Continental Shelf. Journal of Environmental Management 227, 229–247. https://doi.org/10.1016/j.jenvman.2018.08.051CrossRefGoogle ScholarPubMed
Komdeur, J., Bertelsen, J. and Cracknell, G. (eds) (1992). Manual for Aeroplane and Ship Surveys of Waterfowl and Seabirds . IWRB Special Publication No. 19. Kalø: National Environmental Research Institute.Google Scholar
Lamb, J., Gulka, J., Adams, E., Cook, A. and Williams, K.A. (2024). A synthetic analysis of post-construction displacement and attraction of marine birds at offshore wind energy installations. Environmental Impact Assessment Review 108, 107611. https://doi.org/10.1016/j.eiar.2024.107611CrossRefGoogle Scholar
Liaw, A. and Wiener, M. (2002). Classification and regression by Random Forest. R News 2, 18–22. https://CRAN.R-project.org/doc/Rnews/Google Scholar
Marchowski, D. (2021). Bycatch of seabirds in the Polish part of the Southern Baltic Sea in 1970–2018: A review. Acta Ornithologica 56, 139–158. https://doi.org/10.3161/00016454AO2021.56.2.001Google Scholar
Marchowski, D. (2024). Offshore wind farms: consequences for birds wintering in the Polish Exclusive Economic Zone. Presentation at the 2nd Wind Conference, 18–19April, Almond Hotel, Gdańsk, Poland.Google Scholar
Marchowski, D., Jankowiak, J., Ławicki, Ł., Wysocki, Ł. and Chylarecki, P. (2020). Fishery bycatch is among the most important threats to the European population of Greater Scaup Aythya marila. Bird Conservation International 30, 176–193. https://doi.org/10.1017/S0959270919000492CrossRefGoogle Scholar
Masden, E.A., Cook, A.S.C.P., McCluskie, A., Bouten, W., Burton, N.H.K. and Thaxter, C.B. (2021). When speed matters: The importance of flight speed in an avian collision risk model. Environmental Impact Assessment Review 90, 106622. https://doi.org/10.1016/j.eiar.2021.106622CrossRefGoogle Scholar
Mendel, B., Sonntag, N., Wahl, J., Schwemmer, P., Dries, H., Guse, N. et al. (2008). Profiles of Seabirds and Waterbirds of the German North and Baltic Seas: Distribution, Ecology, and Sensitivities to Human Activities Within the Marine Environment. Bonn–Bad Godesberg: Federal Agency for Nature Conservation (BfN).Google Scholar
Miller, D.L., Rexstad, E., Thomas, L., Marshall, L. and Laake, J.L. (2019). Distance sampling in R. Journal of Statistical Software 89, 1–28.10.18637/jss.v089.i01CrossRefGoogle Scholar
Nilsson, L. (1980). Wintering diving duck population and available food resources in the Baltic. Wildfowl 31, 131–143.Google Scholar
Nilsson, L. and Haas, F. (2016). Distribution and numbers of wintering waterbirds in Sweden in 2015 and changes during the last fifty years. Ornis Svecica 26, 3–54.10.34080/os.v26.21854CrossRefGoogle Scholar
Pavón-Jordán, D., Clausen, P., Dagys, M., Devos, K., Encarnaçao, V., Fox, A.D. et al. (2019). Habitat- and species-mediated short- and long-term distributional changes in waterbird abundance linked to variation in European winter weather. Diversity and Distributions 25, 225–239. https://doi.org/10.1111/ddi.12855CrossRefGoogle Scholar
Pavón-Jordán, D., Fox, A.D., Clausen, P., Dagys, M., Deceuninck, B., Devos, K. et al. (2015). Climate-driven changes in winter abundance of a migratory waterbird in relation to EU protected areas. Diversity and Distributions 21, 571–582. https://doi.org/10.1111/ddi.12300CrossRefGoogle Scholar
Pérez Lapeña, B., Wijnberg, K.M., Hulscher, S.J.M.H. and Stein, A. (2010). Environmental impact assessment of offshore wind farms: a simulation-based approach. Journal of Applied Ecology 47, 1110–1118. https://doi.org/10.1111/j.1365-2664.2010.01850.xCrossRefGoogle Scholar
Peschko, V., Mendel, B., Müller, S., Markones, N., Mercker, M. and Garthe, S. (2020). Effects of offshore windfarms on seabird abundance: Strong effects in spring and in the breeding season. Marine Environmental Research 162, 105157. https://doi.org/10.1016/j.marenvres.2020.105157CrossRefGoogle ScholarPubMed
Pettersson, J. (2005). The Impact of Offshore Wind Farms on Bird Life in Southern Kalmar Sound, Sweden. Lund: Lund University/Swedish Energy Agency.Google Scholar
Polish Ministry of Infrastructure (2024). GIS Resources: Offshore Wind Farm Data. Available at https://sipam.gov.pl/zasoby-gis/dane-gis/ (accessed 15 May 2024).Google Scholar
Rintala, J., Hario, M., Laursen, K. and Møller, A.P. (2022). Large-scale changes in marine and terrestrial environments drive the population dynamics of long-tailed ducks breeding in Siberia. Scientific Reports 12, 12355. https://doi.org/10.1038/s41598-022-16166-7CrossRefGoogle ScholarPubMed
Robertson, G.J. and Cooke, F. (1999). Winter philopatry in migratory waterfowl. The Auk 116, 20–34. https://doi.org/10.2307/4089450CrossRefGoogle Scholar
Sesana, E., Gagnon, A.S., Ciantelli, C., Cassar, J. and Hughes, J.J. (2021). Climate change impacts on cultural heritage: A literature review. WIREs Climate Change 12, e710. https://doi.org/10.1002/wcc.710CrossRefGoogle Scholar
Skov, H., Heinänen, S., Žydelis, R., Bellebaum, J., Bzoma, S., Dagys, M. et al. (2011). Waterbird Populations and Pressures in the Baltic Sea. Copenhagen: Nordic Council of Ministers. https://www.nordic-ilibrary.org/content/publication/tn2011-550Google Scholar
SMDI (2015). Environmental Impact Assessment Report for the Baltic Sea Middle II Offshore Wind Farm , Volume VI . Non-specialist Summary. [In Polish] Warsaw: Grupa Doradcza SMDI.Google Scholar
Trinder, M., O’Brien, S.H. and Deimel, J. (2024). A new method for quantifying redistribution of seabirds within operational offshore wind farms finds no evidence of within-wind farm displacement. Frontiers in Marine Science 11, 1235061. https://doi.org/10.3389/fmars.2024.1235061CrossRefGoogle Scholar
Turvey, S.T., Walsh, C., Hansford, J.P., Crees, J.J., Bielby, J., Duncan, C. et al. (2019). Complementarity, completeness and quality of long-term faunal archives in an Asian biodiversity hotspot. Philosophical Transactions of the Royal Society B: Biological Sciences 374, 20190217. https://doi.org/10.1098/rstb.2019.0217CrossRefGoogle Scholar
Wardecki, Ł., Chodkiewicz, T., Beuch, S., Smyk, B., Sikora, A., Neubauer, G. et al. (2021). Monitoring Ptaków Polski w latach 2018–2021 [Monitoring of Polish Birds in 2018–2021]. Biuletyn Monitoring Przyrody 22, 1–80.Google Scholar
Watson, D.F. (1992). Contouring: A Guide to the Analysis and Display of Spatial Data. Oxford: Pergamon Press.Google Scholar
Wetlands International (2010). Guidance on Waterbird Monitoring Methodology: Field Protocol for Waterbird Counting. Wageningen: Wetlands International. http://www.wetlands.orgGoogle Scholar
Wetlands International (2024). Waterbird Populations Portal. Available at wpp.wetlands.org (accessed 5 April 2024).Google Scholar
Wilk, T., Jujka, M., Krogulec, J. and Chylarecki, P. (eds) (2010). Important Bird Areas of International Importance in Poland. Marki: Polish Society for the Protection of Birds (OTOP).Google Scholar
Žydelis, R., Bellebaum, J., Österblom, H., Vetemaa, M., Schirmeister, B., Stipniece, A. et al. (2009). Bycatch in gillnet fisheries – An overlooked threat to waterbird populations. Biological Conservation 142, 1269–1281. https://doi.org/10.1016/j.biocon.2009.02.025CrossRefGoogle Scholar
Supplementary material: File

Marchowski et al. supplementary material

Marchowski et al. supplementary material
Download Marchowski et al. supplementary material(File)
File 16.4 KB