Quantifying Ecological Impacts of Offshore Renewables - A Statistical Perspective

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Tuesday 01 October 2019, 05:30pm - 07:30pm

Location Lecture Theatre 3, Appleton Tower, 11 Crichton St, Edinburgh EH8 9LE


Andrew B Gill (PhD, FRSB), Cranfield University

Understanding the data needs for determining the impacts of offshore renewable energy developments on marine organisms

Kate Searle, Centre for Ecology and Hydrology

The need for end to end quantification of uncertainty in assessments for impacts of offshore renewable energy on seabirds

Daniel Johnston, British Trust for Ornithology

Investigating the foraging ecology of black guillemots in relation to tidal stream turbines


Andrew B Gill:

It is acknowledged that the deployment of offshore renewable energy devices alters the local environment. Many organisms will colonise, seek refuge or associate themselves with the structures and the consequences of this is changes in animal distribution and communities. The environmental impact process requires some monitoring of these changes however it is limited to specific species and also uses limited methods to monitor the changes. To truly understand the changes and how meaningful they are (i.e.
their true biological impact) we need to ask the right questions and use appropriate analysis at the right scale to properly decipher a biological change or effect from a significant impact. This presentation will present a couple of examples of changes that occur associated with offshore renewable energy and will invite thoughts (from the statistical audience) on how appropriately targeted and better planned study design and statistical analysis can help us determine the changes occurring and provide better evidence for use in decision making about planning and deploying offshore renewable energy in our seas to assist in combating climate change effects. (Please note I am not a statistician but have to look towards statistics to ensure robust scientific evidence is the

Kate Searle:

There is a need for the development of a strategic assessment framework for seabird impacts that may result from offshore renewable energy developments (ORDs), which utilises currently available tools and data products, and provides coherent best practice recommendations for informing policy and consenting decisions. Such a strategic assessment requires combining multiple data types within both deterministic and statistical models, with different methods having widely diverging abilities to quantify uncertainty in outputs. This divergence risks leading to a disjointed approach to uncertainty quantification in assessments, with implications for the precautionary nature of policy decisions. Here, we identify currently available methods, which when combined, may provide strategic end-to-end assessments of ORD impacts on seabirds, and assess the degree to which uncertainty is currently, or could in the future, be properly quantified within such an end-to-end assessment.

Daniel Johnston:

Inshore diving seabirds such as black guillemots Cepphus grylle have been suggested to be vulnerable to potential alterations to their foraging habitat related to the construction of tidal stream turbines. During foraging, individuals are known to associate with tidal currents and dive to depths at which tidal turbines will likely operate, and are therefore at risk of collision with turbine blades. As well as posing a potential collision risk, these devices may alter tidal current flow, and change benthic habitats, which may alter the distribution of the black guillemots prey. However, the extent to which these devices will affect black guillemots is unknown due to a lack of knowledge on their foraging ecology. This study addresses this knowledge gap using GPS tracking technology, and intensive study of chick diet using camera traps and visual observations, to identify the spatial and temporal aspects of foraging behaviour and habitat use.

Organiser Name Adam Butler

Email Address This email address is being protected from spambots. You need JavaScript enabled to view it.

Organising Group(s) Environmental Statistics Section and Edinburgh Local Group of the Royal Statistical Society





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