Feasibility study of large-scale deployment of colour-ringing on black-legged kittiwake populations to improve the realism of demographic models assessing the population impacts of offshore wind farms

Abstract

• Renewable energy developments, including offshore wind farms have been identified as a key component in international efforts to mitigate climate change and its impact on biodiversity. This has led to an increasing number of offshore wind farms around the UK, however, these can have negative impacts on seabird populations. • Population Viability Analysis (PVA) is frequently used to quantify these potential negative effects on seabird populations and is a vital part of the consenting process. However, a lack of empirical data on many aspects of seabird demography means that there can be considerable uncertainty in these assessments. • Black-legged Kittiwake Rissa tridactyla populations are thought to be particularly sensitive to additional mortality caused by collision with offshore wind turbines and are often highlighted as a feature of Special Protection Areas (SPAs). Offshore wind farms, therefore, have been identified as potentially causing an adverse effect on site integrity at some SPAs. • Despite being a relatively well-studied species, there is still much uncertainty in our knowledge of Kittiwake demographic rates and meta-population dynamics, which impedes our ability to accurately assess the way populations might respond to additional wind farm-induced mortality. • The Offshore Wind Strategic Monitoring and Research Forum (OWSMRF) identified a large-scale colour-ringing programme of Kittiwake colonies across the UK as one potential approach for improving empirical estimates of Kittiwake demographic rates. • Therefore, the main aim of this project was to determine the extent to which colour-ringing can be used to obtain reliable baseline estimates of key demographic rates in Kittiwake populations to improve the realism of demographic models assessing the population impacts of offshore wind farms, and thereby reduce uncertainty around these predicted impacts