Environmental impact assessment of offshore wind farms: a simulation-based approach

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1.  Assessing and monitoring the impact of offshore wind farms on marine fauna is vital if we want to achieve ecologically sustainable development of this renewable energy resource. Given the complexity of the marine environment, a method capable of accommodating spatio-temporal behaviour of specific species and their interrelation with other marine phenomena is an essential prerequisite for investigating whether or not there has been any measurable impact to date. 2.  This paper presents a method based on geostatistical simulation to assess whether pre- and post-construction collected bird count data suggest displacement of birds due to the wind farm. The method takes into account spatial autocorrelation in species abundance at various scales, pre- and post-construction differences in environmental conditions and in survey effort and design. 3.   We demonstrate that taking these factors into account influences the conclusions about a wind farm’s impact on bird life. In particular, incorporating spatial autocorrelation in seabird numbers is an important factor in reducing the risk of wrongly identifying an effect of a wind farm on bird abundance. 4.  Synthesis and applications. The development of offshore wind farms is often in conflict with nature conservation interests. Environmental impact assessment and monitoring is essential to protect and manage the marine environment. The method described here will allow scarce data to be utilized effectively as a basis for well-informed environmental decisions. In addition, the method will assist in the design of optimal monitoring procedures at a given site, balancing costs and effectiveness in detecting potentially harmful impacts.
Original languageEnglish
Pages (from-to)1110-1118
JournalJournal of applied ecology
Issue number5
Publication statusPublished - 2010


  • METIS-266553
  • offshore construction
  • seabirds
  • IR-86434
  • geostatistics
  • impact assessment
  • Autocorrelation
  • Spatial Simulation
  • survey design


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