Improving Our Understanding of Seabird Behaviour at Sea

1 Introduction

In order to mitigate the impacts of climate change, the Scottish Government aim to generate 100% of Scotland's gross electricity consumption from renewable sources by 2020. Globally, Offshore wind farms are likely to play a key role in strategies to reduce our reliance on energy generated using fossil fuels (Toke 2011). In Scotland, operational projects at Robin Rigg and the Aberdeen Bay European Offshore Wind Deployment Centre (EOWDC) and the larger Round Three projects in the Moray Firth and the outer Forth and Tay estuaries which are either under construction or, have received planning consent, will play a key role in meeting the government's ambitious targets for renewable energy. Further projects are likely as part of ScotWind (Crown Estate Scotland), the next offshore wind leasing round in Scotland and with the successful ongoing testing of floating wind turbines, there is the potential for these wind farms to be located further offshore.

However, there are also concerns about the potential for offshore wind farms to negatively impact the environment, with the risk to seabirds receiving particular attention (Furness et al. 2013). Scotland hosts internationally important populations of seabirds (Mitchell et al., 2004) and there are concerns about the potential for these populations to be affected through collisions with turbines, the loss of habitat as a result of displacement and barrier effects resulting in elevated energy expenditure costs. Consequently, potential impacts on seabird populations are a key focus of Environmental Impact Assessments (EIAs) carried out as part of the consenting process for proposed offshore wind farms.

Concern about the potential impacts of offshore wind farms on seabird population has led to the refusal of planning consent in relation to one offshore wind farm in England (Broadbent & Nixon, 2019) and legal challenges in relation to others (Scottish Courts and Tribunals, 2016; Scottish Courts and Tribunals, 2017). This can involve significant costs for all involved and may put the financial viability of projects in doubt. Furthermore, the delays such challenges cause to the consenting process can cause problems in relation to attracting the necessary financial support from government required for the project to proceed.

It is important that consenting decisions made in relation to offshore wind farms make use of the best available evidence. In relation to seabirds, this has traditionally involved making use of data collected using boat or digital aerial surveys (Buckland et al., 2012; Camphuysen et al., 2004; Thaxter & Burton, 2009). In addition to providing information on the distribution and numbers of birds at sea, they often include additional information such as species flight heights (Johnston & Cook, 2016; Johnston et al. 2014). However, these surveys are limited to daylight hours and conditions of good visibility and sea states of four or less (Camphuysen et al. 2004). Consequently, there is concern that the data currently used during EIAs may be biased towards particular times and conditions, and not accurately reflect seabird use of the offshore environment at other times.

There is a growing recognition of the potential for tagging data to inform EIAs for offshore wind farms (Fijn & Gyimesi, 2018; Furness et al. 2018; Ross-Smith et al. 2016). There are an increasing number of tracking studies from a wide range of seabirds tagged at breeding colonies around the UK (and Europe), and comparison between transect-based survey data and tracking data collected during the breeding season has revealed a far greater degree of overlap in the location of high use areas at sea than would be expected by chance alone (Sansom et al. 2018). However, the extent of this overlap declines with increasing distance from colony. Area usage also appears to differ in relation to environmental conditions. This may have implications for the assessment of displacement. For example, if distributions differ between good and poor weather conditions, then the potential for displacement in different conditions may also differ.

In addition to understanding how distributions may vary between times when boat and digital aerial survey data can, or can't, be collected, it is important to understand how species behaviour may differ. This is particularly important in relation to assessing potential collision risk. Collision Risk Models (CRMs) such as the Band model (Band, 2012) require reliable estimates of behavioural parameters such as estimates of species-specific flight heights, flight speeds and levels of nocturnal activity (Masden & Cook, 2016). In assessing collision risk, estimates of species flight heights have typically been based on boat or digital aerial survey data (Johnston & Cook, 2016; Johnston et al. 2014). However, it has been demonstrated that Lesser Black-backed Gull flight heights may differ between day and night (Ross-Smith et al., 2016). This has implications for the assessment of collision risk in this species as it means birds are less likely to encounter turbine blades during the night than during the day. It seems likely that other aspects of bird flight behaviour may differ between day and night as well. Furthermore, estimates of parameters such as flight speed and levels of nocturnal activity have been drawn from studies with limited sample sizes or, based on reviews inferred from our understanding of the ecology of the species concerned (Alerstam et al. 2007; Garthe & Huppop, 2004). Recent analyses of tracking data have highlighted how these assumptions may be misleading, with potential consequences for the assessment of collision risk (Fijn & Gyimesi, 2018; Furness et al. 2018).

In order to assist the Scottish Government deliver its ambitious targets for renewable energy generation, we aim to use seabird tracking data to enable a better understanding of seabird behaviour at sea, by considering seabird data collected in different weather conditions and throughout the diel cycle. This will allow, for the first time, an assessment of the potential biases in EIAs based solely on transect-based survey and the potential implications this has in relation to assessing the potential impacts of offshore renewable energy developments on seabirds. We will also consider the potential for tracking data to improve the evidence base with which to assess the potential impacts of offshore wind farms on seabird populations. This will help mitigate conflict in the consenting process, reducing costs for all stakeholders and minimise the potential for delays by reducing uncertainty in relation to the data that are used in the assessment process (Masden et al., 2015).