Seabird flight height data collection at an offshore wind farm: final report

Understanding seabird flight heights and behaviour in and around operational offshore wind farms is a priority knowledge gap. Using aircraft mounted LiDAR technology, this study collected data on seabird flight height and shows the potential for using it in offshore windfarm impact assessments.


6. References

APEM, 2018. Pre‐construction Aerial Survey Report 2018. APEM Scientific Report for Moray Offshore Windfarm (East) Limited, November 2018.

Band B., 2012. Using a collision risk model to assess bird collision risks for offshore windfarms. British Trust for Ornithology.

Bates D., Mächler M., Bolker B., Walker S., 2015. "Fitting Linear Mixed-Effects Models Using lme4." Journal of Statistical Software, 67(1), 1–48. doi: 10.18637/jss.v067.i01.

[BTO] The British Trust for Ornithology, 2015. The BTO at Sea. Annual Review 2015. September–October 2015 316: 10–1.1.

Canty, A. and Ripley, B., 2010. boot: bootstrap R (S-Plus) functions. R package version 1.2-42.

Cook, A.S.C.P., Ward, R.M., Hansen, W.S. and Larsen, L., 2018. Estimating seabird flight height using LiDAR. Scottish Marine and Freshwater Science, 9(14), pp.1-52.

Cohen, J., 1988. Statistical Power Analysis for Behavioural Sciences. 2nd Edition. Lawrance Erblaum Associates, Hillsdale, New Jersey.

Efron, B. & Tibshirani, R.J. 1993. An introduction to the bootstrap. Chapman & Hall, London.

Forewind, 2013. Dogger Bank Creyke Beck Environmental Statement Chapter 11 Appendix A - Ornithology Technical Report. F-ONC-CH-011 Appendix A, Issue 1.

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, pp.56-66.

Johnston, A., Cook, A.S., Wright, L.J., Humphreys, E.M. and Burton, N.H., 2014. Modelling flight heights of marine birds to more accurately assess collision risk with offshore wind turbines. Journal of Applied Ecology, 51(1), pp.31-41.

MacArthur Green, 2019. Beatrice Offshore Wind Farm Year 1 Post construction Ornithological Monitoring Report 2019. MacArthur Green Scientific Report for Beatrice Offshore Windfarm. April 2019.

Maclean, I.M., Skov, H., Rehfisch, M.M. and Piper, W., 2006. Use of aerial surveys to detect bird displacement by offshore windfarms. BTO Research Report, 446.

Masden, E.A. and Cook, A.S.C.P., 2016. Avian collision risk models for wind energy impact assessments. Environmental Impact Assessment Review, 56, pp.43-49.

McGovern, S., Wilmott, J.R., Lampman, G., Pembroke, A., Warford, S., Rehfisch, M. and Clough, S., 2019. The First Large-Scale Offshore Aerial Survey Using a High-Resolution Camera System. In Wind Energy and Wildlife Impacts (pp. 115-123). Springer, Cham.

McGregor, R.M., King, S., Donovan, C.R., Caneco, B., Webb, A. 2018. A Stochastic Collision Risk Model for Seabirds in Flight. HiDef BioConsult Scientific Report to Marine Scotland, 06/04/2018, Issue I, 59 pp.

QGIS.org, 2021. QGIS 3.16. Geographic Information System User Guide. QGIS Association. Electronic document: https://docs.qgis.org/3.16/en/docs/user_manual/index.html

R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

Scarff, G., Fitzsimmons, C. and Gray, T., 2015. The new mode of marine planning in the UK: Aspirations and challenges. Marine Policy, 51, pp.96-102.

Scottish Government, 2020. Sectoral marine plan for offshore wind energy. Available at:https://www.gov.scot/publications/sectoral-marine-plan-offshore-wind-energy/documents/ (2022).

Contact

Email: REEAadmin@gov.scot

Back to top