期刊
ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
卷 90, 期 -, 页码 -出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.eiar.2021.106622
关键词
Wind turbine; Renewable energy; Lesser Black-backed Gull; Mortality; GPS tracking; Offshore
资金
- Natural Environment Research Council [NE/L002728/1, NE/R014701/1]
- Natural England
- Orsted
- Department for Business, Energy and Industrial Strategy (BEIS) Offshore Energy Strategic Environmental Assessment research programme
- Marine Renewable Energy and the Environment (MaREE) - Highlands and Islands Enterprise
- European Regional Development Fund
- Scottish Funding Council
- NLeSC
- LifeWatch
- SURF Cooperative
- NERC [NE/R014701/1, NE/L002728/1] Funding Source: UKRI
Renewable energy is growing globally, with an increase in offshore wind farms, but wind energy developments may impact bird populations. Existing collision risk models are sensitive to parameters such as bird flight speed, and using site-specific GPS-derived flight speed data can reduce collision estimates. More representative flight speed data and site-specific data are needed for accurate assessment of seabird collision risk with offshore wind farms.
Renewable energy continues to grow globally, and the number of offshore wind farms is set to increase. Whilst wind energy developments provide energy security and reduced carbon budgets, they may impact bird populations through collision mortality, habitat modification and avoidance. To date, avian collision mortality has received the most attention and collision risk models have been developed to estimate the potential mortality caused by wind turbines. The utility of these models relies not only on their underlying assumptions but also on the data available to ensure the predictions are informative. Using a stochastic collision risk model (sCRM; based on the Band collision risk model) as an example, we explore the importance of bird flight speed and consider how the assumptions of the model influence the sensitivity to flight speed. Furthermore we explore the consequences of using site-specific GPS-derived flight speed rather than a standard generic value, with Lesser Black-backed Gulls Larus fuscus as an example, and consider how this generic value is currently used. We found that the model was most sensitive to the parameters of bird density, non-avoidance rate and percentage of birds at collision risk height, as well as bird flight speed. Using site-specific flight speed data derived from GPS tags rather than a standard value reduced the predicted number of collisions. We highlight that within the model, both the estimation of the probability of collision (PColl) and the flux of birds are sensitive to the bird flight speed; this sensitivity acts in opposite directions but the two do not necessarily balance out. Therefore, when the sCRM is used as generally done, there is little difference in collision estimates if airspeeds (bird flight speed relative to air through which it is moving) are used rather than groundspeeds (bird flight speed relative to ground). Estimates of seabird collision rates in relation to offshore wind farms are impacting future offshore wind development. By using site specific flight speed estimates and, accounting for different speeds in relation to wind direction, we demonstrate that cumulative collision estimates can be affected, highlighting the need for more representative flight speed data and where possible site-specific data.
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