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The Journal of Wildlife Management 1–13; 2020; DOI: 10.1002/jwmg.21863
Research Article
Dogs Detect Larger Wind Energy Effects
on Bats and Birds
K. SHAWN SMALLWOOD,
1
3108 Finch Street, Davis, CA 95616, USA
DOUGLAS A. BELL, East Bay Regional Park District, 2950 Peralta Oaks Court, Oakland, CA 94605, USA
SKYE STANDISH, Standish Ecological Services, 156 Franklin Street, Santa Cruz, CA 95060, USA
ABSTRACT As wind turbine‐caused mortality of birds and bats increases with increasing wind energy
capacity, accurate fatality estimates are needed to assess effects, identify collision factors, and formulate
mitigation. Finding a larger proportion of collision victims reduces the magnitude of adjustment for the
proportion not found, thus reducing opportunities for bias. We tested detection dogs in trials of bat and
small‐bird carcasses placed randomly in routine fatality monitoring at the Buena Vista and Golden Hills
Wind Energy projects, California, USA, 2017. Of trial carcasses placed and confirmed available before
next‐day fatality searches, dogs detected 96% of bats and 90% of small birds, whereas humans at a
neighboring wind project detected 6% of bats and 30% of small birds. At Golden Hills dogs found 71 bat
fatalities in 55 searches compared to 1 bat found by humans in 69 searches within the same search plots
over the same season. Dog detection rates of trial carcasses remained unchanged with distance from turbine,
and dogs found more fatalities than did humans at greater distances from turbines. Patterns of fatalities
found by dogs within search plots indicated 20% of birds and 4–14% of bats remained undetected outside
search plots at Buena Vista and Golden Hills. Dogs also increased estimates of carcass persistence by
finding detection trial carcasses that the trial administrator had erroneously concluded were removed.
Compared to human searches, dog searches resulted in fatality estimates up to 6.4 and 2.7 times higher for
bats and small birds, respectively, along with higher relative precision and >90% lower cost per fatality
detection. © 2020 The Authors. The Journal of Wildlife Management published by Wiley Periodicals, Inc.
on behalf of The Wildlife Society.
KEY WORDS Altamont Pass, bats, carcass detection trials, detection dogs, fatality monitoring, small birds,
wind farm.
As wind energy expands worldwide, a potential bat mortality
crisis lurks behind available estimates of fatality rates from col-
lisions at wind farms (Kunz et al. 2007). Based on bat fatalities
reported over 12 years through 2011, Arnett and Baerwald
(2013) predicted 196,190–395,886 bat fatalities at wind projects
in 2012 in the United States and Canada. With an installed
wind energy capacity of 51,630 MW in 2012, the estimate of
annual wind turbine‐caused bat fatalities in the United States
was 600,000 (Hayes 2013) to 888,000 bats (90% CI =384,643–
1,391,428; Smallwood 2013). By 2019, installed capacity had
increased to 100,125 MW (https://www.awea.org/wind‐101/
basics‐of‐wind‐energy/wind‐facts‐at‐a‐glance, accessed 6 Dec
2019). If vulnerability of bats to wind turbine collision increased
linearly with this increased wind energy capacity, if mean fatality
rates are restricted to those estimated from fatality search in-
tervals <10 days (Smallwood and Neher 2017), and if we as-
sume that monitored wind projects reasonably sampled regional
variation in installed capacity across the United States
(Smallwood 2013, Allison and Butryn 2018), then estimated
annual fatalities in 2019 would have increased to >3 million
bats, or more than the estimated nationwide mortality caused
by white‐nose syndrome, a fungal disease estimated to
have killed about 600,000 bats/year since 2007 (Hopkins and
Soileau 2018). The nationwide estimates cited above were based
on using human searchers at wind turbines, an approach prone
to large biases and sources of uncertainty due to variation in
fatality monitoring methods and poor detection of bat carcasses
(Smallwood 2007; Smallwood et al. 2010, 2013). Given the
potential magnitude of wind turbine effects on bats and
their possible contribution to regional population declines
(Rodhouse et al. 2019), it is important to improve estimates of
bat fatality rates to formulate realistic mitigation measures.
North America's avifauna has declined 29% in 48 years
(Rosenberg et al. 2019), and the magnitude of bird mortality
at wind farms is less clear, partly because of high uncertainty
in estimates based on human searchers and varying methods
to monitor fatalities (Smallwood 2007, 2013). The estimates
of wind turbine‐caused bird fatalities in the United States in
2012 were 214,000–368,000 (Erickson et al. 2014), 234,000
(Loss et al. 2013), and 573,000 birds (Smallwood 2013).
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.
Received: 26 March 2019; Accepted: 21 February 2020
1
E‐mail: puma@dcn.org
Smallwood et al. •Dog Detections of Fatalities 1
Projecting the estimates of Erickson et al. (2014) and
Smallwood (2013) to the 100,125 MW of installed wind
energy capacity in 2019 yields annual tolls of 415,010–
713,662 and 1,111,219 birds, respectively. Whether this
range of fatalities qualifies as a crisis for birds depends on the
accuracy of the estimates of Erickson et al. (2014) and
Smallwood (2013), their spatial representation of the 2012
wind energy capacity in the United States, and the extent to
which wind energy‐related mortality threatens particular
species or contributes cumulatively to other mortality factors.
Sources used to estimate nationwide bat and bird fatalities
are confounded by low carcass detection rates of human
searchers combined with relatively long intervals between
searches, 2 attributes typical of older studies. In a study of
2 overlapping fatality monitoring teams whose methods dif-
fered only in average search interval, the team with the shorter
search interval of 5 days yielded a small‐bird fatality estimate
numbering 2.3 times higher than the other team using a search
interval of 39 days (Smallwood 2017). Considering the effect
of long search interval alone, nationwide bird fatalities
estimated by Erickson et al. (2014) could be nearly doubled.
The accuracy of fatality estimates depends largely on de-
tecting as many of the available fatalities as possible, and
accurately adjusting for the proportion of fatalities not
found (Smallwood et al. 2018). Finding more of the actual
fatalities decreases the proportion of unfound fatalities,
thereby minimizing inaccuracy caused by biases and error in
the adjustment. Multiple steps can be taken to detect more
of the available fatalities, including searching to a maximum
radius around wind turbines that includes the majority of
deposited carcasses, searching along transects spaced closer
together, searching more frequently, and searching with
skilled detection dogs instead of only humans. Homan et al.
(2001), Arnett (2006), Paula et al. (2011), and Matthews
et al. (2013) reported that using skilled dogs greatly in-
creased carcass detection rates over human searchers, and
Reyes et al. (2016) reported that dogs improved searcher
efficiency and were more likely to detect fatalities of rarely
represented species.
Detecting as many fatalities as possible caused by a wind
turbine includes incorporating an appropriate maximum
search radius around the turbine, yet the scientific basis for
deciding on a maximum search radius has been scarce. Hull
and Muir (2010) proposed a method based on ballistics.
However, ballistics cannot account for the collider's pre‐
mortem contribution to deposition distance, including
staying aloft until farther from the turbine or continued
movement on the ground post‐deposition. An injured mo-
bile bat can defy predictions of deposition patterns based on
ballistics. Another approach is to observe the pattern of
outcomes: where bat carcasses finally wind up within the
wind project. Smallwood (2013) proposed such an outcomes
method based on modeling the pattern of carcass deposition
within previously searched areas but warned the observed
pattern might shift with increasing maximum search radius.
Huso and Dalthorp (2014) and Huso et al. (2017) also
proposed modeling the pattern of carcass deposition, but the
proposed metric consisted of the density of carcasses
(carcasses/m
2
) as opposed to Smallwood's (2013) cumu-
lative number of carcasses with increasing distance from the
turbine. Huso and Dalthorp (2014) and Huso et al. (2016)
further proposed that monitoring can be more efficient by
concentrating efforts near the turbine tower where carcass
densities were higher at one cited project site. Both the
Smallwood (2013) and Huso and Dalthorp (2014) and
Huso et al. (2017) approaches are also vulnerable to a po-
tential bias caused by human searchers finding fewer of the
available fatalities farther from the wind turbines, a pattern
that can result from decreasing ground visibility, searchers
struggling to remain on the intended transect, and searchers
shifting attention to navigating more difficult terrain farther
from the turbine. If use of dogs greatly improves carcass
detection (Arnett 2006, Mathews et al. 2013), then dogs
might reveal truer patterns of carcass deposition within the
maximum search radius around wind turbines.
Our objectives were to compare dog versus human searchers
at wind turbines for their detection rates of volitionally placed
trial carcasses of bats and small birds; patterns of found
fatalities around wind turbines; and cost‐effectiveness. To
further test the efficacy of using skilled dogs relative to human
searchers to find available fatalities, our fourth objective was
to test whether factors documented to affect human detection
rates of bat and small‐bird carcasses also affect dog detection
rates, including number of days since trial carcass placement,
relative visual occlusion of trial carcass by ground conditions,
and carcass size. We also examined conditions associated
with trial carcasses that dogs did not detect.
STUDY AREA
Our study involving dogs included 2 wind projects 8 km
apart in the Altamont Pass Wind Resource Area
(APWRA), California, USA, 2017. The Buena Vista Wind
Energy project (Buena Vista) consisted of 38 1‐MW
Mitsubishi wind turbines, 31 of which were accessible to
us on land owned by the East Bay Regional Park District,
Contra Costa County. Two Mitsubishi turbines were on
45‐m towers, 2 on 65‐m towers, and 27 on 55‐m towers.
The Golden Hills Wind Energy project (Golden Hills)
consisted of 48 1.79‐MW General Electric (GE) wind
turbines (GE, Boston, MA, USA), 32 of which were
accessible to us on privately held land in Alameda County.
All GE turbines were on 80‐m towers. Relying on data from
Brown et al. (2016), we compared the pattern of fatalities
reported by human searchers with distance from the wind
turbine at Vasco Winds Energy Project (Vasco Winds) to
the pattern found by dogs at Buena Vista and Golden Hills.
Vasco Winds neighbored Buena Vista in Contra Costa
County, and consisted of 34 2.3‐MW Siemens turbines
(Siemens, Munich, Germany) on 80‐m towers. All 3 proj-
ects were on steeply rolling hills covered by cattle‐grazed
annual grasses. California ground squirrel (Otospermophilus
beecheyi) is a keystone species of wildlife in the APWRA,
supporting coyotes (Canis latrans), American badgers
(Taxidea taxus), golden eagles (Aquila chrysaetos), and many
other species of mammalian Carnivora and raptors. Bats and
small birds migrate through APWRA with a distinct peak
2 The Journal of Wildlife Management
in nocturnal flight activity in late September and early
October (Smallwood and Bell 2020). Elevations ranged
41–280 m at Buena Vista, 115–477 m at Golden Hills, and
54–402 m at Vasco Winds.
METHODS
Carcass Detection Rates
We sought to maximize bat and small‐bird fatality finds by
performing dog searches for fatalities through fall migration
from 15 September through 15 November 2017, a period of
peak activity in our study area identified by nocturnal
surveys using a thermal‐imaging camera since 2012
(Smallwood 2016). During daylight morning hours 5 days/
week, dogs searched within 105 m of 2–3 turbines/day at
Golden Hills, and within 75 m of 3–5 turbines/day at Buena
Vista, completing 55 turbine‐searches at Golden Hills and
76 at Buena Vista. Dogs searched within the same search
boundary that were searched by humans in 2008–2011 at
Buena Vista (Insignia 2011) and concurrent with our study
at Golden Hills (H. T. Harvey & Associates 2018a,b). We
note that our reference to dogs includes human handlers as
part of a dog‐human fatality detection team. Use of animal
carcasses was authorized under permits from the United
States Fish and Wildlife Service (MB135520‐0) and the
California Department of Fish and Wildlife (SC‐00737).
Conservation Canines from the Center of Conservation
Biology, University of Washington, carefully selected dogs
from animal rescue facilities for their health, athleticism,
keenness to play with toys, and willingness to work with
human handlers. Conservation Canines trained dogs for
≥2 weeks before handling them in our study. Two dogs
worked 1 at a time with a trained handler and a data
collector. The handler, who used global positioning
system (GPS) and a Locus Map application on a phone to
track location, guided dogs by leash along transects ori-
ented perpendicular to the wind and separated by 10 m
over most of each search area (Fig. 1). Dogs selected their
pathswithin5moneithersideofthetransect,air‐
scenting for carcasses along the way. Although dogs could
detect scent far beyond the transect, they were usually
constrained from indicating a carcass location until a
transect intersected the carcass. Within a 90° arc between
210° and 300° from the turbine, which corresponds to
prevailing upwind directions in the APWRA, we allowed
dogs offleash for a more cursory search because in
our experience few bat and small‐bird fatalities are
found upwind of wind turbines (Brown et al. 2016,
Smallwood 2016). We mapped and photographed fatality
finds using a Trimble GeoExplorer 6000 GPS unit
(Trimble,Sunnyvale,CA,USA),andidentified carcasses
to species. Searches and carcass data collection lasted
about 2 hours/2.3‐MW turbine and 1.5 hours/1‐MW
turbine, and each dog was limited to working about
2.5 hours/day to maintain health and vigor.
We integrated carcass detection trials into fatality mon-
itoring, similar to Smallwood et al. (2018). The day before
each fatality search, our detection trial administrator
(KSS) deposited trial carcasses of bats and small birds at
randomized locations, nearly all within intensively searched
areas downwind of wind turbines (Table 1). Carcasses had
been frozen immediately post‐mortem. We weighed trial
carcasses prior to placements, removed 1 foot from bats, and
clipped offtips of flight feathers of birds. Human members
of our dog teams, who were blind to trials, reported found
trial carcasses in the same manner as turbine‐caused
Figure 1. Examples of fatality search transects followed by dogs on particular days (white lines) around 3 wind turbines at the Buena Vista Energy Project
(left) and around 1 turbine at the Golden Hills Wind Energy Project (right) in Contra Costa and Alameda Counties, California, USA, 2017. Wind turbines
appear as white, and their shadows are dark. Transect directions indicate wind was blowing from the south or north on the day of the depicted survey at
Buena Vista, and from the west on the day of the survey at Golden Hills (east winds are rare in fall).
Smallwood et al. •Dog Detections of Fatalities 3
fatalities except for additionally reporting carcasses that
were marked by removed foot or clipped flight feathers. At
Buena Vista, KSS checked trial carcass status as long as
carcasses persisted. At Golden Hills, KSS removed carcasses
of bats but not birds following the dog team's next search, as
required by the wind company.
We informed the Golden Hills monitor of our trial carcass
placements, but the monitor's human searchers and our
dog team were blind to each other's fatality finds until the
end of our study. Human searchers at Golden Hills re-
moved carcasses they found, except for our trial carcasses,
but we left dog‐detected carcasses in place to potentially
be discovered by human searchers. From 15 September
through 15 November 2017, we performed 55 searches with
dogs at the same 32 turbines where human searchers
working without dogs performed 69 searches. We later
compared fatality finds and estimated fatalities/MW
between human searchers and our dog team.
Patterns of Fatalities around Wind Turbines
Fatality rates are less comparable between wind projects un-
less one accounts for the proportion of fatalities not found
because they were located beyond the search boundary. This
proportion (d), which can be estimated (see below), varies
among wind projects with tower height, rotor diameter, wind
speed, flight direction, body mass of species flying through
the project, slope steepness around wind turbines, and
maximum fatality search radius (Hull and Muir 2010, Kitano
and Shiraki 2013, Loss et al. 2013, Smallwood 2013).
Also contributing to variation in carcass distribution are
Table 1. Carcasses placed in detection trials at Golden Hills and Buena Vista Wind Projects, Alameda and Contra Costa Counties, California, USA,
5 September–15 November 2017. Bat species are listed in order of number placed, then birds. Sample sizes were n
1
for placements of fresh‐frozen and
thawed carcasses the day before the search, n
2
for placements on randomized days within 2 weeks of the search, and n
3
for relocations of carcasses from
Golden Hills to Buena Vista the day before the search.
Placed Body mass (g)
Species n
1
n
2
n
3
x
¯Low High
Mexican free‐tailed bat (Tadarida brasiliensis) 71 17 7.5 1.9 15.6
Evening bat (Nycticeius humeralis) 25 11 6.0 1.7 11.4
Little brown bat (Myotis lucifugus) 6 5 2.2 1.0 3.5
Seminole bat (Lasiurus seminolus) 3 1 15.1 9.1 19.8
Eastern pipistrelle (Pipistrellus subvlafus) 2 5.2 4.6 5.8
Cliffswallow (Hirundo pyrrhonota) 12 1 15.1 10.7 19.0
Oak titmouse (Parus inornatus) 8 1 12.0 6.9 15.6
House finch (Carpodacus mexicanus) 5 4 19.9 15.6 23.9
Anna's hummingbird (Calypte anna) 5 3 3.6 2.5 5.7
Northern mockingbird (Mimus polyglottos) 4 3 38.0 32.2 47.0
Bushtit (Psaltriparus minimus) 4 3 4.3 3.7 5.0
Vaux's swift (Chaetura vauxi) 4 2 12.5 11.1 14.9
Wilson's warbler (Wilsonia pusilla) 3 2 5.9 4.9 7.7
Bewick's wren (Thryomanes bewickii) 5 7.4 3.7 8.6
Swainson's thrush (Catharus ustulatus) 3 2 54.0 38.1 69.0
Western bluebird (Sialia Mexicana) 3 1 20.6 17.8 25.5
Black‐headed grosbeak (Pheucticus melanocephalus) 3 1 39.7 34.2 50.8
Violet‐green swallow (Tachycineta thalassina) 2 2 14.2 11.6 18.0
Barn swallow (Hirundo rustica) 2 2 16.4 14.4 18.3
Western scrub‐jay (Aphelocoma coerulescens) 2 1 59.2 55.5 64.9
American robin (Turdus migratorius) 2 1 61.0 49.6 70.3
Black phoebe (Sayornis nigricans) 1 2 15.8 14.5 17.9
Eurasian collared‐dove (Streptopelia decaocto) 3 1 73.3 44.3 90.0
Cedar waxwing (Bombycilla cedrorum) 3 24.6 23.7 26.3
White‐breasted nuthatch (Sitta carolinensis) 2 14.0 13.6 14.3
Hooded oriole (Icterus cucullatus) 2 16.4 15.5 17.2
Golden‐crowned sparrow (Zonotrichia atricapilla) 2 14.9 7.7 22.0
California towhee (Piplio fuscus) 2 35.8 28.0 43.6
Acorn woodpecker (Melanerpes formicivorus) 2 69.3 57.6 81.0
Say's phoebe (Sayornis saya) 2 25.3 4.9 45.6
Chestnut‐backed chickadee (Parus rufescens) 2 5.4 5.4 5.4
Prairie falcon (Falco mexicanus) 1 57.4 57.4 57.4
Budgerigar (Melopsittacus undulatus) 0 1 20.3 20.3 20.3
American goldfinch (Carduelis tristis) 0 1 9.4 9.4 9.4
Mountain bluebird (Sialia currucoides) 0 1 26.0 26.0 26.0
Western flycatcher (Empidonax difficilis) 1 9.7 9.7 9.7
Hermit thrush (Catharus guttatus) 0 1 17.4 17.4 17.4
American crow (Corvus brachyrhynchos) 1 179.8 179.8 179.8
Mourning dove (Zenaida macroura) 1 107.9 107.9 107.9
White‐crowned sparrow (Zonotrichia leucophrys) 1 20.4 20.4 20.4
California quail (Callipepla californica) 1 184.5 184.5 184.5
Northern rough‐winged swallow (Stelgidopteryx serripennis) 1 13.9 13.9 13.9
Spotted towhee (Piplio erythrophthalmus) 1 27.8 27.8 27.8
Brewer's blackbird (Euphagus cyanocephalus)1
4 The Journal of Wildlife Management
pre‐mortem movements of mortally injured animals from
initial deposition sites and post‐mortem translocation of
carcasses by vertebrate scavengers. Given the variety of factors
that can affect carcass location, Smallwood (2013) asserted
that, other than searching farther from the turbine to find
more of the available fatalities beyond the typical maximum
search radius, inferences drawn from the spatial distribution
of found fatalities within the maximum search radius, an
outcomes‐based approach, should be more accurate than a
ballistics approach for predicting d. Smallwood (2013) also
warned that declining detection rates with distance from the
turbine could bias predictions of d. We quantified trial carcass
detection rates with distance from the turbine to reveal
whether detection rates change with distance for humans or
dogs, and we compared the pattern of human‐and dog‐found
fatalities around wind turbines.
Human searchers found insufficient bat fatalities at
Golden Hills for characterizing spatial pattern, so as a sur-
rogate we used data from 3 years of fatality monitoring,
May 2012–May 2015, at 34 turbines at Vasco Winds, where
80‐m tower heights, 105‐m maximum search radius, and
10‐m transect spacing equaled those at Golden Hills, and
where the detection trial protocol was similar. We used
Vasco Winds data to quantify searcher detection rates of
trial carcasses and fatality finds by distance from the turbine,
and we compared these human searcher‐derived spatial
patterns to those derived from dogs at Golden Hills.
We fit logistic models to the cumulative number of found
fatalities (C) with distance from the turbine to predict
number of fatalities within an estimated asymptotic distance
(u) beyond which no more fatalities would likely be found,
and from which the actual fatality count can be subtracted
to estimate the proportion of undetected fatalities due to an
insufficient maximum search radius (Smallwood 2013):
C
ab
1,
u
X
1
()
=
+×
where uwas the best‐fit upper bound value of the cumu-
lative number of found fatalities, Xwas carcass distance
from the wind turbine within 10‐m increments, and aand b
were best‐fit coefficients. We divided Cby uto obtain
proportions of cumulative fatalities within 10‐m distance
increments from the turbine (d).
Cost‐Effectiveness of Dogs
We compared the monitoring cost per hectare searched to
fatalities found, number of species represented by found
fatalities, and to the magnitude and precision of fatality
estimates. We measured these metrics from fatality searches
using dogs from 15 September through 15 November at
Golden Hills and Buena Vista in 2017, and from human
searchers over the same time period at Golden Hills (H. T.
Harvey & Associates 2018a,b). We also assessed these
metrics based on human searches and averaged yearly within
these same dates 2008–2011 at Buena Vista (Insignia 2011)
and 2012–2015 at Vasco Winds (Brown et al. 2016).
We estimated fatalities/MW (
F
ˆ) of bats and birds using
the Smallwood (2013) estimator:
F
F
RSd
,
C
ˆ=××
where Fwas number of fatalities found per MW, R
C
was
mean daily proportion of trial carcasses persisting at a time
interval corresponding with the average search interval in
days, and Swas searcher detection or proportion of trial
carcasses detected upon the next search following carcass
placement. We used 28‐day R
C
values to represent first
searches, and our average 27‐day R
C
values to represent
subsequent searches. We carried error through the fatality
adjustments using the delta method:
which we multiplied against the appropriate t‐value from a
t‐distribution to estimate 95% confidence intervals. We cur-
tailed the lower bound of the confidence interval at 0. We
measured relative precision as the coefficient of variation.
Factors Affecting Human Search Detection of Bat and
Bird Carcasses
Human searcher detection of wind turbine fatalities has
been documented to decline with smaller carcass size, time
since trial carcass placement, and reduced visibility of car-
casses on the ground (Smallwood et al. 2018). To test
whether dog searcher detection declined similarly, we tested
detection rates of dogs on carcass size. We transformed
measured body mass of placed carcasses to log
10
scale, which
was the measurement scale used in Smallwood et al. (2018),
and we deliberately placed 30 juvenile bats and 15 flightless
bird chicks to increase the size range of bats and small birds
used in the tests. To test whether dogs detect fewer older
carcasses, we deliberately placed older carcasses in some
trials. Because we were required to remove bat trial carcasses
from Golden Hills after our next search following place-
ment, we also relocated persisting carcasses to Buena Vista
to test dogs on carcasses that had endured an extra 1–4 days
in the field (Table 1). We also placed fresh‐frozen and
thawed bird carcasses on randomized days up to 2 weeks
prior to the next fatality search At Buena Vista, thereby
⎛
⎝
⎜
⎜
⎜
⎜
⎞
⎠
⎟
⎟
⎟
⎟
S
EF SR d SE F F
Sd R SE R F
Rd p SE S
F
RS d SE d
111
1
,
CC
C
C
C
2
2
2
2
2
2
2
()
()
()
()
()()
()
() ()
()
()
(ˆ)= ×××()+ ××−×()+ ××−×()
+××−×()
Smallwood et al. •Dog Detections of Fatalities 5
introducing controlled variation in time between placement
and the next search. To test whether visual occlusion of
carcasses reduces dog detections, we related detection rates
to an index of carcass visibility to searchers, which we
measured as distances to trial carcass occlusion (no longer
visible) from 3 standardized directions. Upon trial place-
ment we counted paces in 3 directions from each carcass
until the carcass was occluded because of vegetation or
terrain, and we related detection outcomes to mean number
of paces to carcass occlusion. One pacing direction was di-
rectly away from the turbine, and the other 2 directions were
perpendicular to the first direction.
RESULTS
From 15 September through 15 November 2017, dogs
found 24 bats and 26 birds during 76 turbine searches at
Buena Vista, and 71 bats and 63 birds during 55 turbine
searches at Golden Hills (Table 2). Based on carcass decay,
we estimated that 9 of those bats and 43 birds had died prior
to our study (Table 2). At Golden Hills, human searchers
found 0 of 71 bats found by dogs and left in place to be
potentially found again, and they found 11 (17%) of 63 bird
fatalities found by dogs. Some of the bats missed by humans
were likely removed by scavengers in the time between our
dogs finding them and the next human search (
x
¯=15 days;
range =1–28 days), but with 25% more turbine searches
over the same time period of our study, human searchers
had 25% more opportunities to find bat and bird fatalities
than did dog searchers.
Carcass Detection Rates
Of 278 trial carcass placements at Buena Vista and Golden
Hills, 214 were available to be found by dogs during
≥1 search. Of carcasses placed before next‐day fatality
searches and confirmed available, dogs detected 96% of bats
and 90% of birds. Dogs found 100% of 41 bats placed at
Golden Hills and 93% of 54 bats placed at Buena Vista.
They found 84% of 56 small birds placed at Golden Hills
and 91% of 32 small birds placed at Buena Vista. Of all
searcher exposures to placed carcasses, whether just placed
Table 2. Fatalities found by dogs at Buena Vista (BV) and Golden Hills (GH) Wind Energy Projects, Alameda and Contra Costa Counties, California,
USA, fall 2017, where old fatalities were judged to have pre‐dated our fatality searches, and new fatalities happened during the study.
Species name (scientific name)Old fatalities
New fatalities
BV GH
Western red bat (Lasiurus blossevillii)041
Myotis (Myotis spp.) 0 0 1
Mexican free‐tailed bat (Tadarida brasiliensis)3629
Hoary bat (Lasiurus cinereus)1213
Bat spp. 51227
Mallard (Anas platyrhynchos)001
Grebe (Podicipedidae) 1 0 1
Turkey vulture (Cathartes aura)202
Northern harrier (Circus cyaneus)110
White‐tailed kite (Elanus leucurus)110
Red‐tailed hawk (Buteo jamaicensis)003
Large raptor 1 0 1
American kestrel (Falco sparverius)241
Prairie falcon (Falco mexicanus)110
Rock pigeon (Columba livia)110
Barn owl (Tyto alba)010
Burrowing owl (Athene cunicularia)104
White‐throated swift (Aeronautes saxatalis)110
Pacific‐slope flycatcher (Empidonax difficilis)010
Horned lark (Eremophila alpestris)10210
Northern rough‐winged swallow (Stelgidopteryx serripennis)0 02
Bewick's wren (Thryomanes bewickii)001
House wren (Troglodytes aedon)001
Ruby‐crowned kinglet (Regulus calendula)002
American pipit (Anthus rubescens)102
Warbler (Parulidae) 0 0 1
Black‐throated gray warbler (Dendroica nigrescens)101
Townsend's warbler (Dendroica townsendi)010
Lincoln's sparrow (Melospiza lincolnii)001
Dark‐eyed junco ( Junco hyemalis)001
Blackbird (Icteridae) 1 0 1
Western meadowlark (Sturnella neglecta)677
Brown‐headed cowbird (Molothrus ater)101
Large bird 8 2 8
Small bird 3 3 11
All bats 92471
All small birds 27 19 47
All large birds 16 7 16
All birds 43 26 63
6 The Journal of Wildlife Management
or persisting through multiple searches, dogs found 95% of
132 bat trials and 91% of 101 bird trials between both
projects. To adjust the number of bats found for the pro-
portion not found because of searcher detection error, the
number of bat fatalities found by dogs required multi-
plication factors of 1 and 1.075 at Golden Hills and Buena
Vista, respectively, whereas those found by humans at Vasco
Winds required a multiplication factor of 17.2. To adjust
the number of small birds found for the proportion not
found because of searcher detection error, the number of
small‐bird fatalities found by dogs required multiplication
factors of 1.16 and 1.09 at Golden Hills and Buena Vista,
respectively, whereas those found by humans at Vasco
Winds required a multiplication factor of 3.37.
Predicted mean daily carcass persistence rates (R
C
)were
similar between bats and small birds when based solely on trial
administrator status checks (Fig. 2). Our best‐fit models for
daily carcass persistence based solely on trial admin-
istrator status checks were
R
Bats 1.0185 0.8998
Cday
s
[]= ×
(r
2
=0.98, root mean square error [RMSE] =0.11),
and
R
Small birds e1 3.0732 1
Cdays0.0996 log 1
[]=−×( −
)
−×( +)
(r
2
=0.99, RMSE =0.04), where days represented number of
days into the carcass persistence trial. Bat carcass persistence was
higher for bats placed immediately after thawing, and it was
higher for birds and bats when relying on dog detections instead
of only the trial administrator's status checks (Fig. 2) because
dogs found remains of trial carcasses the trial administrator er-
roneously determined had been removed. Compared to a trial
administrator checking on old carcasses typical of those found
during monitoring and redeployed in detection trials, dog de-
tections combined with trial administrator checks of fresh‐
frozenandthawedcarcassesattimesofplacementreduced
adjusted bat fatality rates by 28%, 40%, and 44% at 7‐,14‐,and
28‐day search intervals, respectively (Fig. 2). Adding dog
searches to trial administrator carcass checks reduced the
adjusted bird fatality rates by 16%, 20%, and 24% at 7‐,14‐,and
28‐day search intervals, respectively (Fig. 2).
Patterns of Carcass Detections around Wind Turbines
Regardless of distance from turbine, dogs found more of the
available trial carcasses at Golden Hills than did humans at
Vasco Winds, especially bat carcasses (Fig. 3; Table 3).
Neither dog nor human searcher detection rates (S) changed
significantly with increasing distance from the turbine, but
human searcher detection rates of birds tended to decline
with increasing distance (Fig. 3).
Human searchers at Golden Hills found 1 bat and 21 bird
fatalities during our study, so we could not infer a spatial
pattern of bat fatalities from human searches at Golden
Hills. To quantify the pattern of human‐found bat fatalities
around wind turbines, which served as our basis for pre-
dicting the proportion of fatalities occurring within the
search area, we used 3 years of fatality searches by humans at
Vasco Winds. Logistic models fit to the pattern of fatalities
found by humans predicted that 100% of bat fatalities and
92% of bird fatalities were located within the maximum
search radius of 105 m. Logistic models fit to the pattern of
fatalities found by dogs predicted that 86% of bat fatalities
and 80% of bird fatalities were located within the maximum
search radius of 105 m (Table 4). For dog and human
searchers, logistic models fit to the same fatality data found
within 3 different maximum search radii predicted 3 dif-
ferent asymptotic distances beyond which no more fatalities
should be found, and therefore different values for dused to
adjust fatality rates (Fig. 4). Numbers of fatalities found to
the 105‐m search radius confirmed that models fit to cur-
tailed maximum search radii of 50 m and 80 m inaccurately
predicted distance asymptotes; the most inaccurate pre-
dictions were based on fatality data within the curtailed
50‐m radius. For example, the pattern of 30 bat fatalities
Figure 2. Mean daily carcass persistence for bats (left) and small birds (right) and as determined by the trial administrator's carcass checks (circles) and both
the trial administrator's carcass checks and fatality searches using dogs (squares) for carcasses defrosted just before placement (large symbols) and those
having already persisted in the field 1–4 days (small symbols) at Golden Hills Wind Energy Project and Buena Vista Wind Energy Project in the Altamont
Pass Wind Resource Area, California, USA, fall 2017. Also shown are typical fatality search intervals of 7, 14, and 28 days for reference (vertical lines).
Smallwood et al. •Dog Detections of Fatalities 7
found after 3 years of human searches within the curtailed
50‐m radius at Vasco Winds resulted in a logistic model
prediction of 30.5 total available bats, 1.5 of which were
predicted outside the search radius. But 49 were found
within 100 m, so the model prediction based on the fatality
pattern within 50 m was 38% too low. For dog searches at
Golden Hills, the model fit to fatality finds within 50 m
predicted a total available number of bat fatalities that was
53% too low, as confirmed by dog searches within the entire
105‐m radius.
Cost‐Effectiveness of Dogs
Dogs finding more of the available fatalities than human
searchers translated into higher fatality estimates. Estimated
bat fatalities/MW were 6.4 times higher based on dog
searchers than on human searchers at Golden Hills, and
4.2 times higher at Buena Vista (Table 5). Estimated bird
fatalities/MW were 1.6 times higher based on dog searchers
than on human searchers at Golden Hills, and 2.7 times
higher at Buena Vista (Table 5).
Relative precision of fatality estimates was higher when
based on dog searches. At Golden Hills and Buena Vista,
respectively, estimates of coefficient of variation from dog
searches were 28% and 30% of those estimated from human
Figure 3. Searcher detection rates of bats (left) and birds (right) did not change significantly with increasing distance from the wind turbine whether the
searchers were humans or dogs at Vasco Winds Energy Project or Golden Hills Wind Energy Project, respectively, in the Altamont Pass Wind Resource
Area, California, USA, fall 2017. Searcher detection using dogs was higher than using humans for trial bird carcasses and higher for trial bat carcasses.
Table 3. Searcher detection rate (S) regressed on increasing 10‐m distance
increments from wind turbine for the dog team at Golden Hills Wind
Energy Project (fall 2017) and for humans at the Vasco Winds Energy
Project (2012–2015), Altamont Pass Wind Resource Area, California,
USA, where
S
abX,=+ and Xrepresents distance (m).
Searcher Trials
Model coefficients
r
2
SE Pab
Dog team Bats 1.000 −0.0000 0.00 0.00 1.00
Dog team Birds 0.970 −0.0020 0.04 0.16 0.28
Humans Bats 0.174 −0.0015 0.16 0.08 0.14
Humans Birds 0.612 −0.0031 0.21 0.15 0.10
Table 4. Logistic models of cumulative fatalities found in 10‐m distance increments from wind turbines to the maximum search radius at Vasco Winds
(VW), Golden Hills (GH), and Buena Vista (BV) Energy Projects, Altamont Pass Wind Resource Area, California, USA, fall 2017:
C,
ab
1
u
X
1
()
=
+× where
uwas the best‐fit upper bound value of the cumulative number of found fatalities, Xwas carcass distance from the wind turbine within 10‐m increments, and
aand bwere best‐fit coefficients. From the model we also predicted proportion of fatalities to occur within the maximum search radius:
d
C
u
=
.
Model coefficients Logistic model prediction
Searcher Site Radius (m)Taxon uabr
2
SE dDistance (m)to 99% of u
Human VW 105 Bats 45.39 0.29 0.937 0.96 0.012 1.00 99
Human BV 75 Bats 14.27 1.34 0.925 1.00 0.003 0.98 98
Human VW 105 Small birds 84.58 0.15 0.957 0.99 0.023 0.89 159
Human VW 105 Large birds 60.43 0.12 0.966 0.97 0.023 0.84 173
Human VW 105 All birds 155.05 0.06 0.964 0.99 0.005 0.84 189
Human GH 105 All birds 21.90 0.61 0.953 0.98 0.023 0.92 119
Human BV 75 All birds 63.82 0.21 0.947 0.99 0.004 0.88 132
Dog GH 105 Bats 78.86 0.16 0.962 0.98 0.018 0.86 177
Dog BV 75 Bats 25.96 1.22 0.915 0.99 0.008 0.96 76
Dog GH 105 Small birds 52.15 0.58 0.954 0.99 0.009 0.86 156
Dog BV 75 Small birds 21.63 3.36 0.936 1.00 0.001 0.74 110
Dog GH 105 Large birds 17.93 9.18 0.942 0.98 0.022 0.79 120
Dog BV 75 Large birds 7.91 18.74 0.917 0.98 0.018 0.89 80
Dog GH 105 All birds 73.89 0.48 0.956 0.99 0.009 0.80 173
Dog BV 75 All birds 28.79 3.13 0.929 1.00 0.006 0.80 108
8 The Journal of Wildlife Management
Figure 4. Proportions of bat (left graph) and bird (right graph) fatalities found within increasing 10‐m distance increments from the turbine at
Golden Hills Wind Energy Project, Alameda County, California, USA, fall 2017, based on dog (top graphs) and human (bottom graphs) searchers
covering maximum search radii curtailed to 50m and 80 m and to the full extent of 80 m (symbolized by radius and extended tics). We calculated
proportions of fatalities as cumulative numbers of fatalities divided by the fatality asymptote (u) both of which were predicted from logistic models fit
to the data. Also shown are the distances corresponding to 99% of ualong with arrows pointing to u, and estimated proportions of carcasses found
within each search radius (d).
Table 5. Estimated fatalities/MW (
F
ˆ
) of bats and small birds killed by wind turbines during our fall 2017 study at operational wind turbines in the Buena
Vista (BV) and Golden Hills (GH) projects in the Altamont Pass Wind Resource Area, California, USA, where we divided the number of carcasses/MW
found (F) by carcass persistence rate (R
C
), searcher detection rate (S), and maximum search radius bias (d), and calculated standard errors using the delta
method.
Taxa Site Searcher
F
̅(SE)
Adjustments
F
ˆ(95% CI)
R
C
Sd
x
¯SE x
¯SE x
¯SE
Bats BV Humans 0.01 (0.01) 0.43 0.11 0.06
a
0.025 0.97 0.325 0.44 (0.00–1.50)
Bats BV Dogs 0.71 (0.17) 0.43 0.11 0.93 0.001 0.96 0.008 1.85 (0.53–3.17)
Bats GH Humans 0.03 (0.03) 0.58 0.06 0.06
a
0.025 1.00
b
0.214 0.52 (0.00–1.68)
Bats GH Dogs 2.22 (0.38) 0.43 0.11 1.00 0.000 0.86 0.018 3.35 (1.24–5.46)
Small birds BV Humans 0.03 (0.02) 0.45 0.04 0.30
a
0.038 0.86 0.230 0.28 (0.00–0.65)
Small birds BV Dogs 0.23 (0.12) 0.45 0.04 0.91 0.002 0.74 0.004 0.75 (0.00–1.57)
Small birds GH Humans 0.38 (0.13) 0.45 0.06 0.30
a
0.038 0.89 0.023 1.76 (0.31–3.21)
Small birds GH Dogs 1.63 (0.30) 0.45 0.04 0.84 0.001 0.86 0.009 2.79 (1.61–3.97)
a
Estimated at Vasco Winds (Brown et al. 2016), where methods of human searches for fatalities were the same as at Golden Hills. No human searcher
detection trials were reported in H. T. Harvey & Associates (2018).
b
Estimated at Vasco Winds, where methods of human searches for fatalities were the same as at Golden Hills. We could not estimate dfrom a single
fatality find.
Smallwood et al. •Dog Detections of Fatalities 9
searches for bats, and were 51% and 84% of those estimated
from human searches for small birds.
Our dog team searched 298.22 ha at Golden Hills and
Buena Vista from 15 September through 15 November 2017,
and human monitors searched 238.74 ha at Golden Hills.
Humans searched 619.34 ha between the same dates in each
of 3 years, 2012–2015 at Vasco Winds. Our dog team aver-
aged US $99.95/ha, whereas human searchers at Vasco Winds
averaged $62.68/ha, a rate that would also apply to human
searchers at Golden Hills and Buena Vista assuming they were
paid about the same rate. On a per‐fatality detection basis,
dogs averaged $314/bat, $335/bird, and $162/fatality of birds
and bats pooled together, whereas humans averaged $5,545/
bat, $4,014/bird, and $2,329/fatality of birds and bats pooled
together at Vasco Winds, $14,964/bat, $680/bird, and $651/
fatality of birds and bats pooled together at Golden Hills, and
$16,555/bat, $5,519/bird, and $4,140/fatality of birds and bats
pooled together at Buena Vista. Per fatality detection, dogs
cost 7% of humans at Vasco Winds, 25% of humans at
Golden Hills, and 4% of humans at Buena Vista.
Assuming our dogs would have detected the 1 golden
eagle and 1 ferruginous hawk (Buteo regalis) that had been
found and removed by the Golden Hills monitor prior to
dog searches, dogs cost $827/species of birds and bats de-
tected as fatalities (19 bird and 4 bat species) at Golden
Hills and $770/species (11 bird and 3 bat species) at Buena
Vista. Human searchers cost $1,247/species of birds and
bats detected as fatalities (11 bird and 1 bat species) at
Golden Hills, and $3,311/species of birds and bats (8 bird
and 2 bat species) detected as fatalities at Buena Vista.
Human searchers cost more per species detected as fatalities
and discovered only half the species in fatality detections,
which imposed a greater cost in lost information that would
have been critical for impact assessment.
Factors Affecting Search Detection of Bat and Bird
Carcasses
Whereas dogs found nearly all of the trial bat carcasses
confirmed available to them at Buena Vista and Golden
Hills, human searchers found none of the bats weighting
≤5 g but found increasingly higher proportions of bats in
larger weight categories (Fig. 5). Bird fatality finds were
skewed towards larger birds among human searchers,
whereas dogs discovered most of the small birds (Fig. 5).
For bats, birds, and bats and birds pooled together, dog
detection trial outcomes did not differ significantly by mean
log
10
body mass (t‐tests, P>0.05).
Of 24 trial bat carcasses that we placed at Buena Vista that
had already persisted 1–4 days at Golden Hills (Table 1), and
of which we confirmed available for detection, dogs detected
87.5%, or only 5.5% lower than the fresh bat detection rate at
Buena Vista. Of the 36 bird carcasses we placed on random-
ized days at Buena Vista to vary the days since placement by
up to 2 weeks (Table 1), dogs detected 36%, but they detected
100% of the 13 that persisted through the next fatality search.
The 64% that were undetected had not persisted until the next
search, likely because scavengers removed them. For bats,
birds, and bats and birds pooled together, dog detection trial
outcomes did not differ significantly by mean distance to
carcass occlusion (t‐tests, P>0.05).
Of 7 bats missed by dogs, 3 had been relocated from
Golden Hills to Buena Vista to test dogs on older carcasses.
Dogs missed 3 bats on 31 October 2017. Dogs missed 1 bat
on a gravel turbine pad, 1 on a gravel access road, 1 in
restored grassland, and 4 in established grassland. Two of
the missed bats were near the edge of the maximum search
radius.
Dogs missed 8 birds ranging in size from a 3.7‐gBewick's
wren (Thryomanes bewickii) to an 87.6‐g Eurasian collared‐dove
Figure 5. Proportions of trial bat carcasses that were confirmed available by carcass status checks (n) and found by body mass category based on dogs
at Golden Hills and Buena Vista Wind Energy Projects and on humans at Vasco Winds Energy Project (left graph), and bird fatality finds by log
10
0.5 g‐increments based on dog and human searchers during concurrent monitoring efforts (right graph) at Golden Hills, Altamont Pass Wind Resource
Area, California, USA, fall 2017.
10 The Journal of Wildlife Management
(Streptopelia decaocto). Dogs missed 2 birds on 23 October 2017,
and 3 more on 13 November 2017. Dogs missed 2 birds on the
non‐gravel portions of turbine pads, 3 in reclaimed grassland,
and 3 in established grassland. Four were on very steep slopes,
and 2 were at the edge of the maximum search radius.
Of the 15 missed bat and bird trial carcasses, 4 bats and
6 birds (67% of misses) were missed on 8 (18%) search days
when the dog team was accompanied by the dog handler's
supervisor or a photographer. The misses occurred on
such days of distraction (i.e., addition of a supervisor
or photographer) nearly 4 times more often other than
expected. Another bat trial carcass was missed during the
dogs' first search of the study.
DISCUSSION
Skilled scent‐detection dogs found 95% of placed bats and
91% of placed birds, despite our deliberate placements of
carcasses of immature bats and birds, mostly small‐bodied
species, and some old carcasses, and despite inadvertent
placement of some carcasses beyond the search radius. Dogs
found 22 of 23 available immature bats averaging 3.46 g,
and a desiccated bat carcass of only 1 g. Dogs found most of
the relocated bats that had already decayed in the field for
≤4 days, and they found bats that disappeared into tall grass
when dropped from shoulder‐height, bats that human
searchers probably would not have found. Among birds,
dogs found hummingbirds and many chicks of various
songbird species. Dogs found all available birds placed
≤2 weeks prior to their next search. Overall, dogs found the
majority of trial carcasses, giving us confidence that they can
find the majority of available carcasses representing wind
turbine fatalities.
Our results were consistent with others who have used
scent‐detection dogs for fatality searches. At 2 wind proj-
ects, dogs found 71% and 81% of trial bat carcasses, whereas
humans found 42% and 14%, respectively (Arnett 2006). At
other wind projects, dogs found 96% of trial common quail
(Coturnix coturnix) carcasses compared to 9% found by
humans (Paula et al. 2011), and 73% of trial bat carcasses
compared to 20% found by humans (Mathews et al. 2013).
In another study using untrained dogs, dogs found 92% of
trial house sparrow (Passer domesticus) carcasses compared to
45% found by humans (Homan et al. 2001). Our findings
were similar to earlier comparisons between dogs and hu-
mans, although we note the disparity between dog and
human detection rates increased with smaller‐bodied ani-
mals. Where 55 of our dog searches overlapped 69 human
searches at the same wind turbines, our dogs found 71 bat
fatalities, whereas human searchers found 1; our dogs found
47 small birds, whereas human searchers found 11;
and our dogs found 16 large birds, whereas humans found
10 (4 were found by both dogs and humans). The 71‐fold
difference in found bats and 4‐fold difference in found small
birds represented substantial differences in searcher de-
tection between dogs and humans, differences that were
measured in actual concurrent fatality monitoring rather
than in separate trials. Our findings at Buena Vista also
differed largely from human searches over the same season
6 to 9 years earlier. Over only 17 days of surveys at operable
turbines, our dogs found more bat fatalities than Insignia's
(2011) human searchers found in 3 years, amounting to a
66‐fold difference in bats found per year.
Dogs finding more of the available fatalities translated into
fatality estimates up to 6.4 times higher for bats and up to
2.7 times higher for small birds; it also resulted in twice the
number of species represented in fatality estimates and
higher relative precision. Fatality estimates based on dog
searches also include more of the small‐sized species of bats
and birds that human searchers are prone to miss. Increased
fatality detection using dogs accounted for most of the
improvements in fatality estimation and cost‐effectiveness,
but the increased detection was not measured only in S.
Whereas human search detection tended to decline with
increasing distance from the turbine, dog detection of fa-
talities did not. Therefore, so long as the maximum search
radius truly encompasses the majority of available fatalities,
the spatial pattern of fatalities discovered by dogs should
result in more accurate predictions of how many were un-
detected beyond the search radius. Increased detection also
reduced error in detection trial administration. Dogs re-
vealed that our trial administrator, even knowing exactly
where he placed carcasses, nevertheless falsely determined
removals of 8.9% (11 of 123) of bird trial carcasses and 2.9%
(3 of 105) of bat trial carcasses. This type of error is difficult
to avoid because wind and animals move and diminish
carcass remains and some of the remains will be small and
hidden in vegetation. Finding feathers and bones a month
or 2 after a trial carcass was reported to have been removed
can result in erroneously counting trial remains as a fatality.
Acknowledging the potential error associated with in-
complete removals and false removal determinations, Brown
et al. (2016) and Smallwood et al. (2018) left carcasses
where found and relied on fatality photos and on tracking
when and where remains were found to prevent errors.
Dogs, however, find almost all remains, including small
pieces of bat wing or a few feathers of a small bird, and thus
nearly eliminate detection trial administration error so long
as the remains are identifiable or located where trial
carcasses were placed.
Even with the improvements to fatality monitoring using
skilled dogs, more research is needed to quantify the un-
detected portion of fatalities beyond the maximum search
radius. The most obvious method for satisfactorily quanti-
fying the undetected portion of fatalities occurring outsides
the search radius would be to extend dog searches well be-
yond the conventional search radius. Also, crippling bias
(Smallwood 2007) remains unquantified without detecting
collisions in some way other than searches within plots.
Background mortality also remains insufficiently quantified.
Scent‐detection dogs would more effectively test hypoth-
eses related to impact assessments and mitigation efficacy by
detecting more of the available bat and bird fatalities. They
would be more likely than human searchers to reveal
whether pre‐construction bat activity patterns can predict
post‐construction effects (Hein et al. 2013), and they should
find enough of the available bats to develop micro‐siting
Smallwood et al. •Dog Detections of Fatalities 11
strategies consistent with those developed for raptors
(Smallwood et al. 2017) and for testing operational cur-
tailment strategies in appropriate experimental designs
(Sinclair and DeGeorge 2016). Dogs could also facilitate
evidence of absence methods used for estimating the prob-
ability of fatalities of particular species (Huso et al. 2015).
We concur with Paula et al. (2011) and Mathews et al.
(2013) that fatality monitoring at wind turbines should be
performed using scent‐detection dogs and trained handlers,
and we further concur that dogs should be carefully selected
for the task (Beebe et al. 2016). Unlike humans, skilled dogs
find almost all of the available carcasses. Some of our
findings suggest that a skilled dog team might find even
more of the available carcasses if the dog team is left un-
disturbed by colleagues. The much more accurate fatality
estimates generated from dog searches can usually lead to
more cost‐effective monitoring and to insight about causal
factors of collisions and reasonable solutions. Cost‐
effectiveness of using dogs might prove lower than what we
report where dogs perform less effectively in higher heat or
on certain ground covers, and where costs are higher be-
cause of unavailability of dog teams, lack of appropriate
lodging, or increased need for treatment of injuries or par-
asitic infections. Where dogs can search for fatalities at
reasonable cost, monitoring and mitigation solutions can be
arrived at much more rapidly with the vastly superior data
that dogs and their handlers can collect at wind energy
projects.
MANAGEMENT IMPLICATIONS
Many of the available fatality monitoring reports likely
underestimated bat and small‐bird fatalities in North
America because they relied on human searchers. The ac-
curacy and precision of fatality estimates at wind projects
would greatly improve by using scent‐detection dogs guided
by trained handlers and applied to larger search areas than
typically used. Dog search teams should consider using
leashed dogs for greater precision of areal searches, and
should minimize distractions to the dogs. Dog searches can
reveal spatial and temporal patterns of fatalities that can
better support hypothesis‐testing of causal factors and wind
turbine micro‐siting strategies.
ACKNOWLEDGMENTS
We thank B. Maddock and Leeward Renewable Energy for
access and assistance at the Buena Vista Wind Energy project,
andR.C.CulverandNextEraEnergy Resources for access
and assistance at Golden Hills Wind Energy project. We
thank H. Smith and C. Yee for their skilled dog handling. We
also thank J. Smith and H. T. Harvey & Associates for as-
sistance at Golden Hills. Our study would not have been
possible without the generous donations of bird carcasses by
Native Songbird Care and bat carcasses by D. Cottrell. We
thankJ.Brown,C.Battistone,E.Burkett,J.GarciaandS.
Osborn for assistance with permitting. We are indebted to D.
Woollett for working with us to train a dog we ended up not
using, but this effort was important to our development. We
are also greatly indebted to K. Swaim for her generous
donation of living space for our dog handler and detection
dogs throughout this study. We thank 2 anonymous reviewers
of previous drafts of this manuscript. Lastly, we are grateful to
the spirited efforts given us by Captain and Jack. This research
wasfundedinpartbytheGordonandBettyMoore
Foundation, which was administered through the East Contra
Costa County Habitat Conservancy Science and Research
Grant Program (Conservancy Contract 2016‐03). We thank
these 2 organizations and also the East Bay Regional Park
District for additional funding and for assistance with access to
the Buena Vista Wind Energy project located on its property.
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