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• Birds colliding with turbine rotor blades is a well‐known negative consequence of wind‐power plants. However, there has been far less attention to the risk of birds colliding with the turbine towers, and how to mitigate this risk. • Based on data from the Smøla wind‐power plant in Central Norway, it seems highly likely that willow ptarmigan (the only gallinaceous species found on the island) is prone to collide with turbine towers. By employing a BACI‐approach, we tested if painting the lower parts of turbine towers black would reduce the collision risk. • Overall, there was a 48% reduction in the number of recorded ptarmigan carcasses per search at painted turbines relative to neighboring control (unpainted) ones, with significant variation both within and between years. • Using contrast painting to the turbine towers resulted in significantly reduced number of ptarmigan carcasses found, emphasizing the effectiveness of such a relatively simple mitigation measure.
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Ecology and Evolution. 2020;10:5670–5679.www.ecolevol.org
1 | INTRODUCTION
Renewable energy production is regarded essential to meet the in-
creasing energy demands while also reducing emissions of CO2 nec-
essary to reduce risk of global warming (IEA, 2016; IPCC, 2014). In
recent years, the production of wind energy has increased world-
wide and is still developing fast (IRENA, 2017).
Although regarded as a low-carbon energy option, wind energy
production may cause negative environmental effects, especially on
wildlife (Tabassum-Abbasi, 2014). At onshore wind-power plants,
birds and bats are particularly vulnerable, with effects ranging from
mortality caused by collisions with turbines, to displacement/avoid-
ance and habitat loss (Drewitt & Langston, 2006; Langston, Fox, &
Drewitt, 2006; May, 2015; Smith & Dwyer, 2016).
Direct mortality of birds due to collision with turbine blades has
been reported from many sites (e.g., Loss, Will, & Marra, 2015; de
Lucas, Janss, Whitfield, & Ferrer, 2008; de Lucas & Perrow, 2017;
Wang, Wang, & Smith, 2015) and may in some species negatively af-
fect population viability (see May, Masden, Bennet, & Perron, 2019).
Species particularly vulnerable to collide with turbine blades are
those spending time in the air at blade height, such as soaring rap-
tors and birds with aerial displays (e.g., de Lucas & Perrow, 2017). On
Received: 23 Novembe r 2019 
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Revised: 5 March 2020 
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Accepted: 30 March 2020
DOI: 10.1002/ece3.6307
ORIGINAL RESEARCH
Effect of tower base painting on willow ptarmigan collision
rates with wind turbines
Bård G. Stokke1| Torgeir Nygård1| Ulla Falkdalen2| Hans C. Pedersen1|
Roel May1
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,
provided the original work is properly cited.
© 2020 The Authors. Ecology and Evolutio n published by John Wiley & Sons Ltd.
1Norwegian Institute for Nature Research
(NINA), Trondheim, Norway
2Lake Ånnsjön Bird Observatory, Duved,
Sweden
Correspondence
Bård G. Stokke, Nor wegian Institute for
Nature Research (NINA), P. O. Box 5685
Torgarden, 7485 Trondheim, Norway.
Email: bard.stokke@nina.no
Funding information
Research Council of Norway, Grant/
Award Number: 226241; Statkraft; Statoil;
Vattenfall; Norwegian Water Resources
and Energy Directorate; Energy Norway;
TrønderEnergi Kraft
Abstract
1. Birds colliding with turbine rotor blades is a well-known negative consequence of
wind-power plants. However, there has been far less attention to the risk of birds
colliding with the turbine towers, and how to mitigate this risk.
2. Based on data from the Smøla wind-power plant in Central Norway, it seems
highly likely that willow ptarmigan (the only gallinaceous species found on the
island) is prone to collide with turbine towers. By employing a BACI-approach, we
tested if painting the lower parts of turbine towers black would reduce the colli-
sion risk.
3. Overall, there was a 48% reduction in the number of recorded ptarmigan car-
casses per search at painted turbines relative to neighboring control (unpainted)
ones, with significant variation both within and between years.
4. Using contrast painting to the turbine towers resulted in significantly reduced
number of ptarmigan carcasses found, emphasizing the effectiveness of such a
relatively simple mitigation measure.
KEYWORDS
carcass searches, contrast painting, mitigation measures, mortality, Smøla, willow ptarmigan,
wind energy development
  
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 5671
STOKKE E T al.
the other hand, there are few reports of birds colliding with turbine
towers.
Grouse (Tetraonidae) are known to have poorly developed vi-
sion and flight maneuverability (Rayner, 1988; Sillman, 1973). In
addition, many such species are often active during dusk and dawn
when visibility is poor. These characteristics all make grouse es-
pecially prone to collide with man-made objects (Bevanger, 1994,
1998; Bevanger & Brøseth, 2000; Bevanger, May, & Stokke, 2016).
Studies of grouse in relation to wind-power plants are addressing
both mortality due to collision and displacement due to distur-
bance (e.g., Hovick, Elmore, Dahlgren, Fuhlendorf, & Engle, 2014;
Pruett, Patten, & Wolfe, 2009; Winder, Gregory, McNew, &
Sandercock, 2015; Winder et al., 2014a; Winder et al., 2014b;
Zeiler & Grunschachner-Berger, 2009). Considering collisions, car-
casses of willow ptarmigan (Lagopus lagopus) at the Smøla wind-
power plant are often found only a few meters from the tower
base, showing signs of direct impact with a “wall” rather than cuts
and fractures usual for hits by turbine blades (Figure 1). In one
case, fresh blood smear and feathers was also observed on the
tower base where a fresh ptarmigan carcass was found (Bevanger
et al., 2010). Galliformes typically fly relatively low above ground;
97% (138 of 142 flights recorded) of willow ptarmigan that were
flushed on Smøla, Norway showed a flight height lower than
15 m (Pedersen, 2017). Both data from autopsy and flight height
indicate that grouse are more prone to collide with the turbine
tower bases than the rotor blades. In support of this, several black
grouse (Tetrao tetrix) that were found immediately under turbines
in an area in Styria, Austria, presumably died because of collision
with tower bases and not the rotor blades, even though the cause
of death was never observed directly (Zeiler & Grunschachner-
Berger, 2009). Corpses were analyzed by veterinarians, who con-
cluded that injurie s were consistent with t he birds flying into a hard
surface. Furthermore, collision between a willow ptarmigan and
the tower base has been confirmed by actual observation once in
Sweden (Falkdalen, Lindahl, & Nygård, 2013; Pedersen, 2017), and
twice in Scotland (Coppes et al., 2020). In Sweden, it was observed
that one individual, part of a group of 10 birds, crashed directly
into the tower base at 2.7 m height above ground (25 September
2011, at 07:05 a.m.). The rest of the group passed the tower on
both sides. At the time, there was no precipitation or wind, but
overcast weather (Falkdalen et al., 2013).
Willow ptarmigan has, due to low population size, been pro-
tected from hunting at Smøla from 2005 (Farstad pers. comm.). It
is a popular small game species, frequently hunted in Fennoscandia.
Due to reduction in population size in most of this species' cir-
cumpolar distribution, several restrictions have been introduced
on hunting in later years to reduce hunting mortality (Pedersen
& Karlsen, 2007; Pedersen & Storaas, 2013; Sandercock, Nilsen,
Brøseth, & Pedersen, 2011). The number of planned wind-power
plants is rapidly increasing, not only in coastal areas in Norway, but
also in alpine and subalpine areas in Scandinavia. Therefore, any ad-
ditional negative effects on willow ptarmigan associated with wind
turbines are important to assess.
Documenting mortality due to collisions with wind turbines is
clearly important, but the next step would be to find solutions to
reduce the risk of collisions. It is pivotal to understand why and
how birds are killed in order to adopt proper mitigation measures
(de Lucas, Ferrer, Bechard, & Muñoz, 2012; de Lucas, Ferrer, &
Janss, 2012; Martin, 2011; Wang et al., 2015), and then use this in-
formation to select the most efficient tools to reduce bird mortality
(Dai, Bergot, Liang, Xiang, & Huang, 2015; Marques et al., 2014; May,
Reitan, Bevanger, Lorentsen, & Nygård, 2015).
Norway's largest wind-power plant at the time was constructed
in the period 2002–2005 on the northwestern part of Smøla, an is-
land off the coast of central Nor way, consisting of 20 2.0 MW and 48
2.3 MW wind turbines distributed within an 18 km2 area (Bevanger
et al., 2010; Follestad, Flagstad, Nygård, Reitan, & Schulze, 2007;
May, Nygård, Dahl, & Bevanger, 2013). After having first docu-
mented the effects of wind turbines on birds within the BirdWind
research project (2006–2011; Bevanger et al., 2016), the main aim
of the INTACT (INnovative Tools to reduce Avian Collisions with
wind Turbines) project (2013–2017) was to advance one step and
experimentally test various mitigation measures at the Smøla wind-
power plant. One of these measures was painting of tower bases to
increase the contrast of the turbine base against the background,
thus making them more visible and easier to avoid for low-flying
ptarmigan (May, 2017).
2 | MATERIALS AND METHODS
2.1 | Study location
Smøla consists of a large main island together with about 5,500
smaller islands, islets, and skerries and is located off the coast of
Møre and Romsdal County, central Norway (63°24′N, 08°00′E).
The terrain is flat with the highest point only 64 m above sea level.
Habitats are dominated by moors of heather (Calluna vulgaris),
marshlands and low rocky outcrops (May et al., 2013).
2.2 | Search regime
Searche s for dead birds below t urbines star ted in August 200 6. Dogs
trained to find carcasses and remains (e.g., feathers) of birds were
used, as this has been shown to increase search efficiency (Paula
et al., 2011). An area of ca 120 m radius from turbines was searched.
The searches were done in a regular pattern of bands ca 30 m apart,
in a transverse pattern perpendicular to the wind direction. The dogs
marked the position of remains of birds by lying down on the spot
and were then rewarded. Altogether four different trained dogs
have been used, and the searcher was always the owner of the dog.
Simultaneously, the owners searched the area visually. When an ob-
ject was found, remains were collected, the presumed species, date,
turbine number, distance and direction from the turbine was noted,
and the GPS position taken.
5672 
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   STOKKE ET al.
Search intensity has varied over time to address the different re-
search questions of consecutive research projects (BirdWind August
2006—December 2010; searches not connected to projects January
2011—November 2012; INTACT March 2013—March 2017). During
August–December 2006, all 68 turbines were searched three out of
four weeks every month. In 20 07, 25 randomly chosen turbines were
searched during 47 weekly searches. During 2008–2012, weekly
searches were conducted at the same turbines as in 2007. In 2011,
five complete searches were conducted at all 68 turbines (January,
April, May, September, and November). In 2012–2013, six complete
searches were conducted each year (March, April, May, August,
September/October, and November). A new search regime was in-
troduced in the summer of 2014, after experimentally painting black
the lower 10 m of the t ower base at four turbi nes in mid-August 2014.
Adjacent turbines were included as control turbines in the searches.
Six more turbines had their bases painted black during mid-July 2015,
with neighboring turbines as controls (Figure 2). Searches from the
time of painting in 2014 through March 2017 were performed once
a month during March–May and August–October. In addition, a full
search round (all 68 turbines) was carried out at the end of spring
(end of May) and at the end of autumn (end of October). During the
winter months, (November–February), a monthly search under all
rotor-swept areas of the turbines was performed. Altogether, 9,424
individual turbine-searches were performed. The present study only
focuses on testing the efficacy of turbines with painted tower bases
in reducing collisions of ptarmigan.
2.3 | Statistical analyses
We tested for any effects of tower base painting on ptarmigan mor-
tality rates (i.e., carcasses found), before and after painting follow-
ing a Before-After-Control-Impact (BACI) approach. The analyses
were performed by grouping recorded number of carcasses per tur-
bine either by year (2006–2017) or by season (winter [December–
February], spring [March–May], summer [June–August] and autumn
[September–November]). For each turbine, the number of re-
corded carcasses was calculated as well as the number of searches
FIGURE 1 Willow ptarmigan found dead under wind turbine at
the Smøla wind-power plant, Norway in October 2015
FIGURE 2 Map of the Smøla wind-
power plant showing position and number
of the turbines. Ten turbines had painted
tower bases (red) with ten adjacent
control turbines (green)
  
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 5673
STOKKE E T al.
performed at each turbine. In the analyses, the number of recorded
carcasses at ten control turbines (Turbine number: 27, 29, 32, 34, 36,
38, 43, 45, 48, 51) was compared with the painted turbines (Turbine
number: 26, 30, 31, 33, 35, 37, 44, 46, 49, 52) before and after paint-
ing, while taking into account search effort by including an offset
term. To control for any potential effects of turbines and either year
or season, random effects were included in a generalized linear
mixed-effects model using the glmer function of the lme4 library
with a Poisson distribution (Bates, Machler, Bolker, & Walker, 2015)
in the statistical software program R 3.3.2 (R Core Team, 2016). To
control for potential overdispersion in the data, we also included an
observation-level random effect (Harrison, 2014). The distribution
of turbine distances of ptarmigan carcasses across time and treat-
ment was tested with the Levene's test for homogeneity, using the
leveneTest function in the car library (Fox & Weisberg, 2019). Using
a similar model structure as for the mortality rates, effects of paint-
ing on the average (log-transformed) distance where ptarmigan car-
casses were found were tested using linear mixed-effects using the
lmer function of the lme4 library.
3 | RESULTS
Altogether, in the period 2006–2017, 474 carcasses were found
within the wind-power plant, including feather heaps or fragmented
remains of birds. The dominating species found was willow ptarmi-
gan (N = 194), followed by white-tailed eagle (Haliaeetus albicilla)
(N = 73). Data on distance to turbine was collected for 342 carcasses,
138 willow ptarmigan, 41 white-tailed eagles, and 163 other species
combined (Figure 3).
When regressing distance (log-transformed, maximum cutoff
distance of 120 m) against species using linear regression, and con-
sidering all turbines for the whole study period, there were signifi-
cant species-specific differences at what distance from the turbine
base carcasses were found (F = 3.111, p = .046). Ptarmigan were
found significantly closer to turbines compared to eagles (t = −2.265,
p = .024). The variation among species falling within the grouping
“other species” (other than eagles or ptarmigan) led to a nonsignifi-
cant effect (t = −1.413, p = .16). For ptarmigan, 23.9% of all carcasses
were found within 10 m of the turbine tower, against 0.0% and 9.8%
for white-tailed eagles and other species, respectively (Figure 3).
When considering the 10 control turbines, there were 11 ptarmi-
gan carcasses found in the period before painting (1,400 searches)
and 19 carcasses found in the period after painting (505 searches).
Same numbers for the 10 painted turbines were 25 carcasses in the
period before painting (1,023 searches) and 14 carcasses in the pe-
riod after painting (523 searches).
The generalized linear model disclosed that the yearly number of
carcasses (across seasons) after painting was reduced at the painted
turbines (z = −2.884, p = .004, Table 1). Overall, there was a 48.2%
(95% confidence interval: 44.2%–52.0%) reduction in the annual
number of recorded carcasses per search at painted turbines rela-
tive to unpainted ones. This effect was mainly due to the relatively
large increase in fatalities per search at the control turbines (before:
0.005, after: 0.030), but lack of such a large increase at painted tur-
bines (before: 0.019, after: 0.023) (Figure 4a). We found no effect of
birds having a higher probability of collision at the neighboring con-
trol turbines due to painting. This was tested by comparing control
turbines to other untreated turbines before-after “treatment” within
the wind-power plant (z = 0.283, p = .78). The average distance of
ptarmigan carcasses from the turbine base increased significantly at
the painted turbines after painting (F = 6.535, p = .014). After paint-
ing, no ptarmigan carcasses were found within 30 m of the painted
turbines (Figure 5). However, the number of carcasses fluctuated
considerably between years (Figure 6a).
The seasonal number carcasses (across years) were significantly
reduced at t he painted turbines (z = −3.0 52, p = .002, Table 1), with an
overall reduction of 49.0% (95% confidence interval: 44.2%–53.2%).
FIGURE 3 Proportional distribution of
recorded carcasses at the Smøla wind-
power plant (2006–2017) by distance
from turbine
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   STOKKE ET al.
Also here, this seasonal effect was mainly due to the relatively large
increase in fatalities per search at the control turbines (before: 0.0 07,
after: 0.037), but lack of such a large increase at painted turbines
(before: 0.023, after: 0.027) (Figure 4b). The number of recorded car-
casses was higher during winter and spring (Figure 6b). Seasonally,
the relative reduction due to painting varied considerably (winter:
−31.1% [i.e., increased number of carcasses], spring: 82.9%, summer:
51.5%, autumn: 81.3%).
Testing the distribution of distances of ptarmigan carcasses
across time and treatment, there was no significant difference in
variances between the groups (F = 0.765, p = .52). For all bird species
taken together, a significant difference in variances was only found
when grouping by species (F = 11.462, p < .001). While the average
distance of carcasses at control turbines decreased by 51% (49.6–
24.2 m), the average distance at painted turbines increased by 31%
(15.0–34.6 m) (Figure 5). Relative to control turbines, carcasses at
impact turbines after painting were on average 10.4 m farther away
from the turbine base (t = 1.999, p = .051; Table 1, Figure 4c).
4 | DISCUSSION
Carcasses of willow ptarmigan were the most frequently observed
of all species close to wind turbines at the Smøla wind-power plant.
Ptarmigan carcasses were usually found closer to the turbines rela-
tive to other species . Together with the general finding s that (a) these
TABLE 1 Model estimates testing the effect of painting on the yearly (upper table) and seasonal (middle table) rate of ptarmigan
carcasses found at the Smøla wind-power plant using a Before-After-Control-Impact (BACI) design. The lower table provides the effect of
painting on distances from turbines where carcasses were found. The models controlled for search effort using an offset term
YEAR
Fixed effects Estimate SE z value p
Intercept −5.0 06 0.385 −12. 997 <.001
BA—After 1.434 0 .512 2.800 .005
CI—Impact 1.142 0.370 3.082 .002
BA:CI −1. 4 8 5 0. 519 −2 . 86 3 .004
Random intercepts Variance SD N
Record 0.078 0.279 261
Turbine 2.695 × 10−9 5.191 × 10−5 20
Year 0.306 0.554 13
SEASON
Fixed effects Estimate SE z value p
Intercept −4.868 0.324 −1 5.0 2 3 <.001
BA—After 1.569 0.378 4.155 <.001
CI—Impact 1.129 0. 361 3.130 .002
BA:CI −1. 475 0.503 −2 .9 31 .003
Random intercepts Variance SD N
Record 1.059 × 10−9 3.254 × 10−5 160
Turbine 2.476 × 10−10 1.573 × 10−5 20
Season 0.054 0.233 4
DISTANCE (log-transformed)
Fixed effects Estimate SE t value p
Intercept 3.904 0.634 6.156 <.0 01
BA—After −0.718 0.678 −1.0 6 0 .301
CI—Impact −1 .197 0.785 −1. 526 .136
BA:CI 1.556 0.778 1.999 .0 51
Random intercepts Variance SD N
Turbine 0.747 0.864 18
Year 0.158 0.397 8
Season 2.251 × 10−7 4.744 × 10−4 4
  
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STOKKE E T al.
carcasses often had injuries that comply with impact from hitting
the tower base instead of the turbine blades (Bevanger et al., 2010;
Pedersen, 2017), (b) ptarmigan carcasses were found closer to tur-
bines than other species (Figure 3), (c) number of carcasses found
close to turbines were lower after painting than before (Figure 3),
and (d) overall number of carcasses found declined after painting of
the tower bases, strongly indicates that turbine tower base collisions
are an important cause of death for this species at the wind-power
plant on Smøla. However, importantly, it is also probable that some
ptarmigan collide with the turbine blades, as there is also a peak
in the distribution of distance from turbine of carcass at 40–60 m
(Figure 3). In addition, predation by raptors such as golden eagles
(Aquila chrysaetos) and gyrfalcons (Falco rusticolus) is an important
source of mortality among ptarmigan on Smøla, especially during
winter (Bevanger et al., 2010; Brøseth, Nilsen, & Pedersen, 2012).
Hence, predation was likely the source of mortality for an unknown
proportion of the ptarmigan carcasses found. In a telemetry study
on ptarmigan at the Smøla wind-power plant (Bevanger et al., 2010),
collisions with wind turbines accounted for 35.7% of the mortali-
ties, while predation accounted for 42.9%–57.1% (N = 28). However,
there is no reason to assume that there should be difference in pre-
dation pressure at painted versus unpainted turbine towers.
Our results also show that there was a variation in collision risk
both among years and seasons (Ferrer et al., 2012; Martin, Perez-
Bacalu, Onrubia, Lucas, & Ferrer, 2018), which has also been found
in studies on other bird species colliding with man-made objects
(e.g., Avery, Springer, & Dailey, 1978; Barrios & Rodriguez, 2004;
Bevanger & Brøseth, 2000). Annual variation in collision risk in
FIGURE 4 Effect plots testing the
effect of painting on the yearly (a) and
seasonal (b) rate of ptarmigan carcasses
found at the Smøla wind-power plant
using a Before-After-Control-Impact
(BACI) design. Panel (c) provides the
effect of painting on distances from
turbines where carcasses were found.
Control = unpainted turbine towers,
Impact = painted turbine towers,
Before = period before painting,
After = period after painting. Estimates
are controlled for search effort using an
offset term
5676 
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   STOKKE ET al.
ptarmigan may be influenced by environmental factors such as vari-
ation in weather conditions. Spells of weather regimes resulting in
fog and rain, for instance, may result in poor visibility and hence a
greater danger of colliding with stationary objects (Bevanger, 1994;
Drewitt & Langston, 2006). Potentially, fluctuating population sizes
could also lead to variation in collision risk, as it has previously been
found that the ptarmigan population size on Smøla may vary sig-
nificantly from year to year (Bevanger et al., 2010). A higher win-
ter mortality can cause reduction in number of breeding pairs and
hence chick production and vice versa (Pedersen, 1984). Also, the
chick production can vary greatly from year to year due to weather
conditions and other environmental factors (Kvasnes, Pedersen,
Storaas, & Nilsen, 2014). In years with larger ptarmigan population
sizes, the probability of finding birds colliding with turbines could
increase simply due to more individuals using the air space in the
area. However, there is no indication that the population size on
Smøla has declined after the construction of the wind-power plant.
Furthermore, both the density of ptarmigan and chick production
inside the power plant has not been significantly different from out-
side (Bevanger et al., 2010).
Seasonal variation in collision risk may also be influenced by
weather since amount and nature (i.e., rain or snow) of precipita-
tion, wind speed, etc. may be connected to season. In addition, vari-
ation in light conditions and species-specific behavioral patterns
may explain seasonal variation in collision risk (e.g., Bevanger, 1994).
Bevanger (1995) found a peak of collisions with power lines for black
grouse in the autumn (September to October), while most collisions
in willow ptarmigan occurred in winter and early spring (November
to March). This fits well with the results from the Smøla wind-power
plant, where collisions most frequently occurred in winter and spring
(Figure 5). This is also supported by earlier findings of the same wil-
low ptarmigan population by Brøseth et al. (2012).
The effect of painting of the turbine tower bases was most pro-
nounced in spring and autumn. The lack of effect of painting during
winter could be due to generally poor light conditions, making tower
bases hard to observe no matter their appearance (Pedersen, 2017).
At 63°N, the daylight hours in the period November to March spans
4.5–10 hr, while at maximum in June it spans 20.5 hr (https://www.
timea nddate.no/astro nomi/sol/). Elevated collision risk during au-
tumn and spring compared to summer could be due to generally
higher flight activity during the former periods. During spring, much
territorial behavior includes frequent flying during dusk and dawn,
in autumn brood break up, flocking and movements between areas,
whereas in the summer time ptarmigan spend most of their time on
ground (Pedersen & Karlsen, 2007).
Failure to detect carcasses may obviously influence estimation
of collision frequencies. At the control turbines, there was an in-
crease in the number of carcasses found after painting than before
(Figure 4). This result is difficult to explain, but it could be due to
variation in search ef ficiency. In the present study, the search regime
was constant throughout the whole search period, and variation
in search intensity was controlled for in the analyses. In addition,
FIGURE 5 Proportional distribution of willow ptarmigan carcasses found at varying distances from the turbine base at the experimental
turbines (10 control and 10 impact turbines) before and after painting within the Smøla wind-power plant
  
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STOKKE E T al.
searches were only made by trained dogs and in accordance with
a standardized protocol. One person with a trained dog searched
for carcasses before painting, and another person with another dog
carried out the search after painting. However, if the post painting
search team was more efficient in finding carcasses, this should only
lead to an underestimation of the effect of painting and hence the
results are even stronger in favor of the positive effect of painting.
Another possible reason for the increase in number of carcasses
found at the control turbines before and after painting could be that
ptarmigan showed anticipator y evasion (cf. May et al., 2015) of the
painted turbines by changing flight paths, and were therefore more
likely to collide with the unpainted turbines. However, we found no
indications of ptarmigan being “forced into” neighboring turbines
due to an evasive response to the painted rotor blades. This possi-
bility, however, merits further investigations focusing on ptarmigan
movements within the study area.
Scavenger removal of collision victims may obviously influence
estimation of collision frequencies (e.g., Loss et al., 2015). The intro-
duced American mink (Neovison vison) is the only mammalian scaven-
ger observed within the Smøla wind-power plant. There are no foxes
(Vulpes spp.) or weasels (Mustela spp.) on the island. Therefore, the
only factors affecting the carcasses are scavenging birds (corvids),
mink, and insects (maggots) (Bevanger et al., 2010). Carcass removal
experiments were carried out on Smøla in November 2010. Twenty-
three ptarmigan carcasses were fitted with radio-transmitters and
a camera-trap was put up at all carcasses. Results showed that
26.1% of ptarmigan carcasses were removed within the first two
weeks after initiation of the experiment (Bevanger et al., 2010). As
for search bias, there is no reason to believe that scavenger removal
rates should vary significantly between years or between painted
and control turbines.
In summary, the present study represents the first case docu-
menting that painting of the wind turbine tower base reduces bird
collisions. This relatively simple and cost-effective mitigation mea-
sure should be considered in the planning of new wind-power plants,
especially in areas where Galliformes and other birds with relatively
poor vision and maneuverability, and that generally perform low al-
titude flights are occurring.
ACKNOWLEDGMENTS
This study was performed as part of the R&D project “Innovative
Mitigation Tools for Avian Conflicts with wind Turbines” (INTACT)
(co-)funded by the Research Council of Norway (grant 226241). We
would like to thank the co-funders of the INTACT project Statkraft,
Statoil, Vattenfall, Norwegian Water Resources and Energy
Directorate, Energy Norway and TrønderEnergi Kraft for their sup-
port. We would also like to thank Ole Reitan for collecting data on
bird carcasses, and personnel at the Smøla wind-power plant for
their logistical support during the experiment. We want to thank
two anonymous reviewers for their insightful and constructive com-
ments that significantly improved the quality of the manuscript.
CONFLICT OF INTEREST
The authors declare no conflict of interest.
AUTHOR CONTRIBUTION
Bård Gunnar Stokke: Investigation (equal); Supervision (equal);
Writing-original draft (lead); Writing-review & editing (lead). Tor ge ir
Nygård: Conceptualization (equal); Data curation (equal); Formal anal-
ysis (equal); Investigation (equal); Methodology (equal); Supervision
(equal); Writing-original draft (supporting); Writing-review & edit-
ing (supporting). Ulla Falkdalen: Investigation (equal); Methodology
FIGURE 6 Yearly (a) and seasonal (b) variation in number of
ptarmigan carcasses found per search per turbine at the Smøla
wind-power plant as derived from the conditional random
intercepts of the linear mixed-effects model explaining effects
of painting of tower bases. Above and below zero indicates,
respectively, more or less carcasses found compared to the overall
mean. Estimates are controlled for search effort using an offset
term
5678 
|
   STOKKE ET al.
(equal); Writing-original draft (supporting); Writing-review & editing
(supporting). Hans Christian Pedersen: Conceptualization (equal);
Investigation (equal); Methodology (equal); Supervision (equal);
Validation (equal); Writing-original draft (supporting); Writing-review
& editing (supporting). Roel May: Conceptualization (lead); Data
curation (equal); Formal analysis (lead); Funding acquisition (lead);
Investigation (lead); Methodology (lead); Project administration (lead);
Supervision (equal); Validation (lead); Visualization (lead); Writing-
original draft (supporting); Writing-review & editing (supporting).
DATA AVAIL ABI LIT Y S TATEM ENT
The data that support the findings of this study have been deposited
in Dryad with https://doi.org/10.5061/dryad.7wm37 pvq1.
ORCID
Bård G. Stokke https://orcid.org/0000-0001-5589-6738
Torgeir Nygård https://orcid.org/0000-0002-7259-9441
Hans C. Pedersen https://orcid.org/0000-0003-4086-4535
Roel May https://orcid.org/0000-0002-6580-4064
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How to cite this article: Stokke BG, Nygård T, Falkdalen U,
Pedersen HC, May R. Effect of tower base painting on willow
ptarmigan collision rates with wind turbines. Ecol Evol.
2020;10:5670–5679. https://doi.org/10.1002/ece3.6307
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Collision with turbines at wind farms is expected to have a greater impact on birds at particular sites where high concentrations of individuals occur, such as migration bottleneck areas. The Strait of Gibraltar (southern Spain) has long been recognized as the most important bottleneck in western Europe for soaring bird migration. Moreover, this area is within one of the most important potential areas for wind energy generation in Spain. Here, we examine monthly migratory soaring bird abundance in relation to long-term avian mortality rates at 21 wind farms located near the Strait of Gibraltar using zero-inflated hurdle negative binomial and gamma models. Best fit models included an effect of season in the collision mortality rates and in the proportion of adult individuals within the total deaths. However, monthly bird abundance was not directly related to the number of fatalities over the year. The accumulated fatalities during autumn migration constitute a small percentage (1%) of the total migrating population size. Moreover, mortality peak during autumn migration is largely attributable to juvenile birds. In contrast, the number of fatalities coinciding with the breeding period constitutes a substantial proportion (6%) of the local population, and it involved substantial losses among adult birds. Our results show that wind farms probably have an individually low impact on the migratory population of soaring birds. On the contrary, annual losses among adult local birds are remarkably high considering the small size of the local populations, and they may have population level effects.
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Energy infrastructure is widespread worldwide. Renewable energy technologies, which are expanding their footprint on the landscape and their contribution to energy availability, represent a different kind of infrastructure from extractive energy technologies. Although renewable energy sources may offer a 'greener alternative' to traditional extractive energy sources, mounting evidence suggests that renewable energy infrastructure, and the transmission lines needed to convey energy from renewable energy facilities to users, may impact birds. Peer-reviewed literature historically has focused on the direct effects of electrocution and, to a lesser extent, collisions with overhead power systems, and on avian collisions at wind energy facilities, with less consideration of indirect effects or other energy sectors. Here, we review studies that have examined direct and indirect effects on birds at utility-scale onshore windand solar-energy facilities, including their associated transmission lines. Although both direct and indirect effects appear site-, species-, and infrastructure-specific, generalities across energy sectors are apparent. For example, largebodied species with high wing loading and relatively low maneuverability appear to be especially susceptible to direct effects of tall structures, and the risk of collision is likely greater when structures are placed perpendicular to flight paths or in areas of high use. Given that all infrastructure types result in direct loss or fragmentation of habitat and may affect the distribution of predators, indirect effects mediated by these mechanisms may be pervasive across energy facilities. When considered together, the direct and indirect effects of renewable energy facilities, and the transmission lines serving these facilities, are likely cumulative. Ultimately, cross-facility and cross-taxon meta-analyses will be necessary to fully understand the cumulative impacts of energy infrastructure on birds. Siting these facilities in a way that minimizes avian impacts will require an expanded understanding of how birds perceive facilities and the mechanisms underlying direct and indirect effects.
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Understanding and reversing the widespread population declines of birds require estimating the magnitude of all mortality sources. Numerous anthropogenic mortality sources directly kill birds. Cause-specific annual mortality in the United States varies from billions (cat predation) to hundreds of millions (building and automobile collisions), tens of millions (power line collisions), millions (power line electrocutions, communication tower collisions), and hundreds of thousands (wind turbine collisions). However, great uncertainty exists about the independent and cumulative impacts of this mortality on avian populations. To facilitate this understanding, additional research is needed to estimate mortality for individual bird species and affected populations, to sample mortality throughout the annual cycle to inform full life-cycle population models, and to develop models that clarify the degree to which multiple mortality sources are additive or compensatory. We review sources of direct anthropogenic mortality in relation to the fundamental ecological objective of disentangling how mortality sources affect animal populations.
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There is increasing concern about the impact of the current boom in wind energy facilities (WEF) and associated infrastructure on wildlife. However, the direct and indirect effects of these facilities on the mortality, occurrence and behaviour of rare and threatened species are poorly understood. We conducted a literature review to examine the potential impacts of WEF on grouse species. We studied whether grouse (1) collide with wind turbines, (2) show behavioural responses in relation to wind turbine developments, and (3) if there are documented effects of WEF on their population sizes or dynamics. Our review is based on 35 sources, including peer-reviewed articles as well as grey literature. Effects of wind turbine facilities on grouse have been studied for eight species. Five grouse species have been found to collide with wind turbines, in particular with the towers. Fifteen studies reported behavioural responses in relation to wind turbine facilities in grouse (seven species), including spatial avoidance, displacement of lekking or nesting sites, or the time invested in breeding vs. non-breeding behaviour. Grouse were affected at up to distances of 500 m by WEF infrastructure, with indications of effects also at bigger distances. In six cases, a local reduction in grouse abundance was reported in areas with wind turbines, which possibly affected population size. Due to the differences in study duration and design, we cannot provide general conclusions on the effects of WEF on grouse populations. We advise applying the precautionary principle by keeping grouse habitats free of wind energy developments, in particular where populations are small or locally threatened. Future studies should preferably apply a long-term before-after-control-impact design for multiple areas to allow for more general conclusions to be drawn on the effects of WEF on rare and threatened wildlife species.
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The expansion of wind energy poses challenges to policy-and decision-makers to address conflicts with wildlife. Conflicts are associated with impacts of existing and planned projects on wildlife, and associated difficulties of prediction where impacts are subject to considerable uncertainty. Many post-construction studies have demonstrated adverse effects on individuals of various bird and bat species. These effects may come in the form of collision-induced mortality or behavioral or physiological changes reducing the fitness of individuals exposed to wind energy facilities. Upscaling these individual effects to population impacts provides information on the true value of interest from a conservation point of view. This paper identifies methodological issues associated when moving from individual effects to population impacts in the context of wind energy. Distinct methodological approaches to predict population impacts are described using published case studies. The various choices of study design and metrics available to detect significant changes at the population level are further assessed based on these. Ways to derive impact thresholds relevant for decision-making are discussed in detail. Robust monitoring schemes and sophisticated modelling techniques may inevitably be unable to describe the whole complexity of wind and wildlife interactions and the natural variability of animal populations. Still, they will provide an improved understanding of the response of wildlife to wind energy and better-informed policies to support risk-based decision-making. Policies that support the use of adaptive management will promote assessments at the population level. Providing information to adequately balance the development of wind energy with the persistence of wildlife populations.
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The construction and operation of wind-power plants may affect birds through collision mortality, reduced habitat utilization due to disturbance, barriers to movement and habitat modifications, with the nature and magnitude of those effects being site- and species-specific. Birds may however manage these effects through fleeing, activity shifts or changed habitat utilization; usually termed avoidance. Given the important role avoidance plays in estimating the impact wind-power development has on birds, there is a pressing need to formalizing the avoidance process. Crucial in this context is to identify the underlying mechanisms of behavioural responses by birds to wind-power plants and individual turbines. To provide a better basis for and improved understanding of the underlying mechanisms for avoidance a conceptual framework for wind-turbine avoidance is presented decomposing various forms of avoidance at different spatial scales. Avoidance behaviour includes displacement (macro-avoidance), anticipatory and impulsive evasion (meso-avoidance), and escape (micro-avoidance). For understanding why particular responses occur with regard to wind-turbine disturbance this concept is applied to predation risk theory. The risk-disturbance hypothesis elucidates possible trade-offs between avoiding perceived risk and fitness-enhancing activities. The four behavioural responses are related to, respectively, habitat selection, vigilance and fleeing (twice); from which specific predictions can be derived. Formalizing the different forms of avoidance facilitates design of effects studies, enhances comparisons among sites studied, and guide siting and mitigation strategies.