Royal Statistical Society
Highlands Local Group

Local organising Committee


Dr Claus Mayer (Chair)
Biomathematics & Statistics Scotland
Aberdeen AB25 2ZD
Dr David McLernon (Hon Secretary)
Polwarth Building,
Aberdeen AB25 2ZD 
Phone: +44 (0) 1224 438652 Phone: +44 (0) 1224 437152  

We are delighted to announce that Alison Johnston, Researcher in Statistical Ecology at the University of Cambridge & Cornell University, will be delivering a talk for the RSS Highlands Local Group on 20th February. The details are below.

Date: Wednesday 20th February 2019

Speaker: Alison Johnston, Researcher in Statistical Ecology, Dept of Zoology, University of Cambridge & Cornell University

Time: 4.30pm

Venue: Room 224, Sir Duncan Rice Library, Old Aberdeen, UoA

Title: Offshore wind farms and birds: Developing statistical methods to better understand the spatial distribution of birds at sea

Abstract: Renewable energy is a growing industry and wind farms are an important component of renewable energy strategies. However, turbines pose a risk to birds and other wildlife, from disruption of habitat to physical collisions. In order to best understand how to mitigate the effects of wind turbines on birds, it is important to understand how birds are distributed at sea and how they use the marine environment. However, collecting data on birds at sea is challenging and many of the standard monitoring methods are not appropriate. Here I outline two statistical approaches we have developed for challenging data to aid the design of offshore wind farms to better understand the spatial distribution of birds at sea, in order to mitigate the effects of offshore windfarms on birds. Both revealed new patterns of bird distribution that helped to mitigate the effects of windfarms on bird populations around the UK coast.

We estimated the flight height of seabirds in relation to wind turbines. We developed a model to estimate continuous flight-height distributions from categorical human estimates of flight height. We used a spline with a multinomial likelihood to estimate a continuous distribution from categorical data. These distributions improved models of collision risk, by enabling estimates of varying collision risk at different heights and also by estimating the uncertainty associated with the flight height distributions.

Another project aimed to estimate the distribution of seabirds in order to optimise turbine locations to reduce the impact on birds. Aerial surveys that photograph the seabirds can be used to assess avian densities in given areas. Boat data provide good species identification, but have a number of other disadvantages. We used both boat data and aerial survey data in a joint analyses to produce population estimates for all species, even those with low species identification rates. This novel approach was used to estimate distributions of marine birds, by combining the strengths of digital aerial and boat surveys.

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