A framework for improving treatment of uncertainty in offshore wind assessments for protected marine birds

Author:

Searle K R1ORCID,O'Brien S H2,Jones E L3,Cook A S C P4,Trinder M N5,McGregor R M5,Donovan C67,McCluskie A8,Daunt F1,Butler A3

Affiliation:

1. UK Centre for Ecology & Hydrology , Bush Estate, Edinburgh EH26 0QB , UK

2. Joint Nature Conservation Committee , Inverdee House Baxter Street, Aberdeen AB11 9QA , UK

3. Bioinformatics and Statistics Scotland, James Clerk Maxwell Building, Peter Guthrie Tait Road, The King’s Buildings , Edinburgh EH9 3FD , UK

4. British Trust for Ornithology, The Nunnery , Thetford IP24 2PU , UK

5. MacArthur Green , 93 S Woodside Rd, Glasgow G20 6NT , UK

6. DMP Statistical Solutions UK Ltd, The Coach House, Mount Melville House , St. Andrews KY16 8NT , UK

7. CREEM, School of Mathematics and Statistics, University of St. Andrews , St. Andrews KY16 9AJ , UK

8. RPSB , 2 Lochside View, Edinburgh EH12 9DH , UK

Abstract

AbstractGovernments worldwide are setting ambitious targets for offshore renewable energy development (ORD). However, deployment is constrained by a lack of understanding of the environmental consequences of ORD, with impacts on protected birds forming a key environmental consenting challenge. Assessing the impacts of ORD on marine birds is challenging, utilizing interlinked approaches to understand complex behavioural, energetic, and demographic processes. Consequently, there is considerable uncertainty associated with ORD assessments for marine birds, with current methods failing to quantify uncertainty in a scientifically robust, evidence-based manner. This leads to a high degree of precaution and a lack of confidence in the evidence used to inform ORD consenting decisions. We review the methods used to estimate ornithological ORD impacts in the UK, a country at the forefront of ORD. We identify areas in which uncertainty quantification could be improved through statistical modelling, data collection, or adaptation of the assessment process. We develop a framework for end-to-end quantification of uncertainty, integrating uncertainty estimates from individual stages of the assessment process. Finally, we provide research recommendations to better quantify and reduce uncertainty, to lower future ORD consenting risk. These recommendations extend beyond the UK and could improve impact assessments in other countries with different legislative frameworks.

Funder

Natural Environment Research Council

Publisher

Oxford University Press (OUP)

Subject

Ecology,Aquatic Science,Ecology, Evolution, Behavior and Systematics,Oceanography

Reference89 articles.

1. Estimating space-use and habitat preference from wildlife telemetry data;Aarts;Ecography,2008

2. Developing field and analytical methods to assess avian collision risk at windfarms;Band,2007

3. Using a collision risk model to assess bird collision risks for offshore windfarms;Band;The Crown Estate Strategic Ornithological Support Services (SOSS) report SOSS02,2012

4. Approximate Bayesian computation in population genetics;Beaumont;Genetics,2002

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