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Whitfield, D.P. & Urquhart, B. 2015. Deriving an avoidance rate for swans suitable for onshore wind farm collision risk modelling. Natural Research Information Note 6. Natural Research Ltd, Banchory, UK.
Abstract
Currently, according to SNH (2010) guidance the recommended avoidance rate for swans under the Band Collision Risk Model (CRM) is 98 %. The objective of the present report is to evaluate available contemporary information on the most suitable value for an avoidance rate for swans that may encounter at operational onshore wind farms.
We highlight that the avoidance rates recommended by SNH (2010) consist largely or entirely of a Micro component and do not, as claimed by SNH (2010), encapsulate both potential Micro and Macro (displacement) components. If there is evidence or arguments to support the need for such Macro avoidance measures to be considered as relevant in assessments of wind farm proposals, then the avoidance rates of SNH (2010) should be regarded as minima. We refer to reviews and other studies which document that large wildfowl (including swans) are susceptible to displacement (Macro avoidance).
Whitfield (2010) argued that swans should probably be considered to have similar avoidance rates to geese. At that time, the SNH guidance recommended a 95 % avoidance rate for swans. On the basis of Whitfield (2010) the avoidance rate for swans was increased to 98 % in SNH (2010), although the avoidance rate for geese was given as 99 % in SNH (2010). SNH (2013) later recommended increasing the 99 % avoidance rate of SNH (2010) for geese, to 99.8 %.
Subsequent to Whitfield (2010), based on a later published study by Fijn and colleagues (2012) in a Dutch polder for Bewick’s swan, the present report derives an estimated avoidance rate (Micro avoidance only) of 99.7 % or, including displacement of flying birds (Macro avoidance), at 99.8 % . If reported displacement of feeding birds would have been included, the derived avoidance rate would have been still higher.
Despite some previous reviews (e.g. Rees 2012) and the findings of Fijn et al. (2012), it is apparent from recent information that feeding large wildfowl (including, likely, swans) are not always dissuaded from feeding within turbine arrays. Hence, we do not recommend that assessments of wind farm proposals that involve feeding swans within proposed arrays should de facto increase our derived 99.7 % and 99.8 % avoidance rates to yet higher rates.
In assessments of wind farm proposals where swans are flying across a proposed development area that intercepts a commuting route we would recommend that rates of 99.7 % and/or 99.8 % should be used (according to circumstance), and not 98 % (SNH 2010).
While we acknowledge that these rates are based empirically on only a single study, we present several corroborative lines of other evidence; and note that the study was fundamentally precautionary as regards swan mortality. Our recommended avoidance rates are applicable only to the original Band CRM and not to any subsequent model extensions.
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Monitoring of wintering geese in the AES Geo Energy Wind Farm Sweti Nikola territory and the Kaliakra region in winter 2010-2011
This review considers data published on the effects of offshore and onshore windfarms
on swans and geese and finds that the information available is patchy. Of 72 swans or
geese reported as collision victims at 46 wind farms, most (39 birds) were reported at 23
wind farms in Germany where such data are collated. Post-construction monitoring was
undertaken for ≤ 1 year at 67% of 33 sites, making it difficult to test for cumulative
effects or annual variation in collision rates. Site use by the birds was measured at only
nine of 46 wind farms where collisions by swans and geese were monitored or recorded.
Displacement distances of feeding birds at wintering sites ranged from 100–600 m, but
preliminary evidence suggested that large-scale displacement also occurs, with fewer
swans and geese returning to areas after wind farms were installed. Eight studies of flight
behaviour all reported changes in flight-lines for swans or geese initially seen heading
towards the turbines, at distances ranging from a few hundred metres to 5 km; 50–100%
of individuals/groups avoided entering the area between turbines, but in some cases the
sample sizes were small. Key knowledge gaps remain, including whether wind farm
installation has a consistently negative effect on the number of birds returning to a
wintering area; whether flight avoidance behaviour varies with weather conditions, wind
farm size, habituation and the alignment of the turbines; provision of robust avoidance
rate measures; and the extent to which serial wind farm development has a cumulative
impact on specific swan and goose populations. It is therefore recommended that: 1)
post-construction monitoring and dissemination of results be undertaken routinely, 2)
the extent to which wind farms cause larger-scale displacement of birds from traditional
wintering areas be assessed more rigorously, 3) further detailed studies of flight-lines in
the vicinity of wind farms should be undertaken, both during migration and for birds
commuting between feeding areas and the roost, to provide a more rigorous assessment
of collision and avoidance rates for inclusion in collision risk models, and 4) the
combination of collision mortality and habitat loss at all wind farms in the species’ range
be analysed in determining whether they have a significant effect on the population.
Large soaring birds of prey, such as the white-tailed eagle, are recognized to be perhaps the
most vulnerable bird group regarding risk of collisions with turbines in wind-power plants. Their
mortalities have called for methods capable of modelling collision risks in connection with the
planning of new wind-power developments. The so-called “Band model” estimates collision risk
based on the number of birds flying through the rotor swept zone and the probability of being
hit by the passing rotor blades. In the calculations for the expected collision mortality a correction
factor for avoidance behaviour is included. The overarching objective of this study was to
use actual flight data and actual mortality to back-calculate the correction factor for white-tailed
eagles. The Smøla wind-power plant consists of 68 turbines, over an area of approximately 18
km2. Since autumn 2006 number of collisions has been recorded on a weekly basis. The
analyses were based on observational data from 12 vantage points collected in spring 2008; of
which six vantage points were placed inside the wind-power plant. The results were verified
using observational data from 10 vantage points within the wind-power plant from May 2009. In
total, five white-tailed eagles have collided with wind turbines during the vantage point periods,
between mid-March and the end of May 2008. In May 2009, only one white-tailed eagle was
found dead. Given the vantage point observations data the correction factor (i.e. “avoidance
rate”) used within the Band collision risk model for white-tailed eagles was 96.4 and 97.1% for
11 and 16 RPM, respectively. These values, however, assume that the wind turbines operated
continuously with the respective RPMs. The correction factor adjusted for the actual wind
speed distribution at Smøla WPA was 95.8%. We also derived uncertainty levels in the modelling,
which resulted in a mean correction factor of 92.5% ± 9.7 SD. This may be due to the
wind speed distribution during the period of interest, affecting both bird speed and flight activity.
This would decrease the total period of interest; and lower the expected number of bird
transits through the rotor swept zone. Although this modelling took into account variation in
wind and bird speed, daylight and flight activity, there may exist possible sources of error, such
as observer bias. These have been assessed. The correction factor was slightly lower using an
independent vantage point data set from May 2009. The relatively low correction factor including
uncertainty levels presented here, compared to that for most other raptor species, probably
results from high levels of flight and breeding display activity, as demonstrated at the Smøla
wind-power plant, where numerous collisions have occurred.
Each winter ∼ 30% of the Northwest European Bewick's Swan Cygnus columbianus bewickii population feeds in Polder Wieringermeer, the Netherlands, on waste crops left after the harvest. The area has also become important for generating energy as a result of wind farm development. This study analyses pre-and post-construction data on Bewick's Swan distribution, movements and foraging behaviour in the vicinity of a nine-turbine wind farm site, in order to determine the effects of wind turbines on wintering swans. The swans' flight-lines between feeding areas and the roost were recorded visually and using radar over 10 evenings in good weather conditions. Food availability on different agricultural plots appeared to be an important factor explaining swan numbers and distribution in the area. In circumstances with even food availability early in the season, swans showed a preference for foraging in areas further away from the turbines, indicating some displacement caused by the turbines. Nevertheless, swans increasingly fed closer to the wind turbines during the course of the season in response to food availability. The likelihood that a single Bewick's Swan passing through the wind farm will collide with a turbine (collision risk) at the nine-turbine site, determined from swan movements through the wind farm (number of swan flights per unit length per unit time) and from regular searches for carcasses, was estimated at 0-0.04% in winter 2006/2007. Avoidance behaviour was observed, with birds navigating around and between the lines of turbines. The observed disturbance of foraging birds early in the season, the acquired knowledge of avoidance responses, and the calculated collision rates in this study can be used for future assessments during planning and construction of new wind farms in wintering areas of Bewick's Swans, especially in areas where important congregations of world or flyway populations occur.
We studied the impact of a wind farm (line of 25 small to medium sized turbines) on birds at the eastern port breakwater in Zeebrugge, Belgium, with special attention to the nearby breeding colony of Common Tern Sterna hirundo, Sandwich Tern Sterna sandvicensis and Little Tern Sterna albifrons. With the data of found collision fatalities under the wind turbines, and the correction factors for available search area, search efficiency and scavenging, we calculated that during the breeding seasons in 2004 and 2005, about 168 resp. 161 terns collided with the wind turbines located on the eastern port breakwater close to the breeding colony, mainly Common Terns and Sandwich Terns. The mean number of terns killed in 2004 and 2005 was 6.7 per turbine per year for the whole wind farm, and 11.2 resp. 10.8 per turbine per year for the line of 14 turbines on the sea-directed breakwater close to the breeding colony. The mean number of collision fatalities when including other species (mainly gulls) in 2004 and 2005 was 20.9 resp. 19.1 per turbine per year for the whole wind farm and 34.3 resp. 27.6 per turbine per year for 14 turbines on the sea-directed breakwater. The collision probability for Common Terns crossing the line of wind turbines amounted 0.110-0.118 % for flights at rotor height and 0.007-0.030 % for all flights. For Sandwich Tern this probability was 0.046-0.088 % for flights at rotor height and 0.005-0.006 % for all flights. The breeding terns were almost not disturbed by the wind turbines, but the relative large number of tern fatalities was determined as a significant negative impact on the breeding colony at the eastern port breakwater (additional mortality of 3.0-4.4 % for Common Tern, 1.8-6.7 % for Little Tern and 0.6-0.7 % for Sandwich Tern). We recommend that there should be precautionary avoidance of constructing wind turbines close to any important breeding colony of terns or gulls, nor should artificial breeding sites be constructed near wind turbines, especially not within the frequent foraging flight paths.
We describe the model of Biosis Propriety Limited for quantifying potential risk to birds of collisions with wind turbines. The description follows the sequence of the model's processes from input parameters, through modules of the model itself. Aspects of the model that differentiate it from similar models are the primary focus of the description. These include its capacity to evaluate risk for multi-directional flights by its calculation of a mean presented area of a turbine; its use of bird flight data to determine annual flux of movements; a mathematical solution to a typical number of turbines that might be encountered in a given bird flight; capacity to assess wind-farm configurations ranging from turbines scattered in the landscape to linear rows of turbines; and the option of assigning different avoidance rates to structural elements of turbines that pose more or less risk. We also integrate estimates of the population of birds at risk with data for numbers of their flights to predict a number of individual birds that are at risk of collision. Our model has been widely applied in assessments of potential wind-energy developments in Australia. We provide a case history of the model's application to 2 eagle species and its performance relative to empirical experience of collisions by those species. © 2013 The Wildlife Society.
In the context of growing demand for offshore wind energy production in recent years, much effort has been made to determine the collision risk that offshore wind turbines pose to birds. Currently, only limited species‐specific data on migrating birds' avoidance rates and associated mortality at offshore wind farms exist.
During a 4‐year study, bird detection radar was used to monitor behavioural responses and flight changes of migrating pink‐footed geese in relation to two offshore wind farms during and after construction.
Radar recorded a total of 979 goose flocks migrating through the whole study area, of which 571 were visually confirmed as 39 957 pink‐footed geese A nser brachyrhynchus . Overall, we calculated that 97·25% of all flocks recorded by radar, in 2009 and 2010 combined, migrated without any risk of additional mortality associated with the constructed wind farms.
We identified a growing tendency of geese to avoid the wind farms and calculated that, for 2009 and 2010 combined, avoidance was exhibited by 94·46% of the original 292 flocks predicted to enter the wind farms.
Synthesis and applications . Migratory geese responded to offshore wind farms by adopting strong horizontal and vertical avoidance behaviour. For the first time, wind farm avoidance rates have been recorded for pink‐footed geese, and these rates will allow more robust impact assessments to be undertaken for both this species and waterfowl in general. Remote sensing techniques should be used to undertake long‐term impact assessments at offshore wind farms to provide an evidence‐base for assessing the mortality risk for migratory birds.