Explore open access research and scholarly works from NERC Open Research Archive

Advanced Search

An individual‐based model to quantify the non‐breeding season impact of wind farms on seabirds

Buckingham, Lila ORCID: https://orcid.org/0000-0002-9846-2734; Masden, Elizabeth A. ORCID: https://orcid.org/0000-0002-1995-3712; Layton‐Matthews, Kate ORCID: https://orcid.org/0000-0001-5275-1218; Bringsvor, Ingar S.; Bråthen, Vegard Sandøy ORCID: https://orcid.org/0000-0002-7357-6727; Dehnhard, Nina ORCID: https://orcid.org/0000-0002-4182-2698; Fauchald, Per; Lorentsen, Svein‐Håkon ORCID: https://orcid.org/0000-0002-7867-0034; Reiertsen, Tone K. ORCID: https://orcid.org/0000-0002-9579-2420; Searle, Kate R. ORCID: https://orcid.org/0000-0003-4624-9023; Tarroux, Arnaud ORCID: https://orcid.org/0000-0001-8306-6694; Christensen‐Dalsgaard, Signe ORCID: https://orcid.org/0000-0003-1657-1919. 2026 An individual‐based model to quantify the non‐breeding season impact of wind farms on seabirds. Ecological Solutions and Evidence, 7 (1), e70196. 15, pp. 10.1002/2688-8319.70196

Abstract
•1. Many countries are developing offshore wind farms to provide renewable energy, yet such developments can harm biodiversity. Seabirds are a highly threatened group of birds and can be impacted by wind farms through lethal collisions and via sub-lethal displacement effects. However, we do not have a comprehensive understanding of the impacts of offshore wind farms on seabird populations, particularly outside of the breeding season. •2. We developed an individual-based model to predict the non-breeding season impacts of offshore wind farms on seabirds. We used long-term tracking data obtained from geolocation-immersion loggers to estimate population-level distributions and activity budgets. We simulated individual behaviour, movement, wind farm interactions (collision and displacement) and any resulting lethal or sub-lethal effects. •3. We demonstrated our model by assessing the impact of 10 simulated offshore wind farms on two populations that breed in Norway: common guillemots Uria aalge (Sklinna) and black-legged kittiwakes Rissa tridactyla (Ålesund). We quantified collision risk in kittiwakes and sub-lethal displacement effects in guillemots and converted these effects into a change in survival or end of season body mass as a proxy for condition. •4. We predicted that 49.6% of guillemots breeding at Sklinna would experience displacement effects during the non-breeding season. As the energetic impact of displacement is relatively unknown, we modelled a range of possible displacement costs and present several impact scenarios, with adult mortality levels ranging from 0% to 5.32% and end of season body masses of 97.12%–99.84% compared to those resulting from an unimpacted scenario. Despite 98.9% of kittiwakes flying through at least one wind farm footprint, we only predicted collisions in 0.055% of the population; this low mortality was primarily driven by low overlap between the modelled height of the turbine rotors and the probable flight height of kittiwakes. •5. Practical implication: Our model provides a tool that can be used to assess the non-breeding season impacts of OWFs on seabird populations, improving sustainability when developing renewable energy infrastructure. We highlight several key limitations as areas of research that are required to reduce uncertainty when predicting impacts. Our model is reproducible and adaptable for use on other species or for other marine threats.
Documents
540966:270936
[thumbnail of N540966JA.pdf]
Preview
N540966JA.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial 4.0.

Download (1MB) | Preview
Information
Library
Statistics

Downloads per month over past year

More statistics for this item...

Metrics

Altmetric Badge

Dimensions Badge

Share
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email
View Item