A picture of five wind turbines on an offshore wind farm

Offshore wind farm

OWFs can have an environmental impact on seabirds through mortality resulting from collisions with rotating turbine blades, but there are difficulties in quantifying collision rates due to the lack of empirical evidence, especially in the offshore environment.

Part of the difficulty in quantifying collision rates is that the limited empirical data suggest collisions are rare events. Considerable effort is therefore required to collect useful quantities of data, across every season and local environmental and weather conditions. Detection of collision events can also be limited by light levels at night or inclement weather, and also bird carcasses possibly being dispersed by currents or scavenging.

The project team carried out a review of existing technologies and discussed any known existing monitoring system. A strategic literature review was carried out, along with interviews with developers of the different monitoring technologies/systems and interviews with wind farm developers implementing monitoring campaigns.

In order to understand how much monitoring would be required to accurately estimate collision rates, a power analysis was carried out. As there was limited evidence to work with, the team used a classical hypothesis testing approach. They used a simulation-based power analysis to simulate ‘true’ collision rates. This power analysis uses the assumption of a monitoring method that can detect all collisions, and identify the bird involved to species level. The team used two model species, the northern gannet, and the black-legged kittiwake.

Statistical software was used to test a range of scenarios. Values were taken from an OWF environmental impact assessment to realistically parametrise the null collision rate. The ‘true’ collision rate was calculated by multiplying the null collision rate by the effect size, for a range of possible effect sizes. 1,000 runs of the simulation were carried out for each effect size and null collision value. For this analysis the collision rate is assumed to be independent and equal across all turbines.

The results of the power analysis revealed that significant effort would be required to fully quantify the collision rate. Depending on the scenario considered, the minimum sample size required would be monitoring 50 turbine-years (where the number of turbine-years is the product of the number of individual turbines monitored and the duration of the monitoring programme in years). In some scenarios, this increased to over 200 turbine-years required.

So, what is the final piece of the puzzle?

The results from this study will feed into work package four, which aims to provide advice and direction of designing a suitable future monitoring programme for wind farm developers. Greater sampling effort may be required to detect smaller effect sizes and effects on species with lower modelled collision rates. As it stands, this relies on undeveloped technology/systems that can unfailingly detect collision rates. We anticipate our work will be used as the benchmark and set standards to develop a future monitoring programme for offshore wind.

The full results of this study will be published via the ORJIP website.

APEM are leading the way in scientific research for offshore wind wildlife surveys. Find out more here.

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