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Dogs Detect Larger Wind Energy Effects on Bats and Birds: Dog Detections of Fatalities


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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. Searching for fatalities at wind turbines, skilled scent‐detection dogs improved carcass detection rates over human searchers 17‐fold for bats and 3‐fold for birds, and in concurrent, overlapping fatality monitoring, human searchers found none of the 71 bat fatalities and 17% of the bird fatalities found by dogs. Findings of dogs increased fatality rate estimates over those of human searchers 6.4‐ and 2.7‐fold, respectively, along with higher relative precision and >90% lower cost per fatality detection.
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The Journal of Wildlife Management 113; 2020; DOI: 10.1002/jwmg.21863
Research Article
Dogs Detect Larger Wind Energy Eects
on Bats and Birds
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 turbinecaused mortality of birds and bats increases with increasing wind energy
capacity, accurate fatality estimates are needed to assess eects, 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
smallbird 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 conrmed available before
nextday 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 414% of bats remained undetected outside
search plots at Buena Vista and Golden Hills. Dogs also increased estimates of carcass persistence by
nding 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 196,190395,886 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 turbinecaused 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 (
basicsofwindenergy/windfactsataglance, 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 whitenose 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 eects 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 turbinecaused bird fatalities in the United States in
2012 were 214,000368,000 (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
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 qualies 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 energyrelated 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 smallbird fatality estimate
numbering 2.3 times higher than the other team using a search
interval of 39 days (Smallwood 2017). Considering the eect
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
eciency 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 scientic 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 postdeposition. 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 nally 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
) 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 ecient by
concentrating eorts 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 nding 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 dicult 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 costeectiveness. To
further test the ecacy of using skilled dogs relative to human
searchers to nd available fatalities, our fourth objective was
to test whether factors documented to aect human detection
rates of bat and smallbird carcasses also aect 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.
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 1MW
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
45m towers, 2 on 65m towers, and 27 on 55m towers.
The Golden Hills Wind Energy project (Golden Hills)
consisted of 48 1.79MW 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 80m 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 2.3MW Siemens turbines
(Siemens, Munich, Germany) on 80m towers. All 3 proj-
ects were on steeply rolling hills covered by cattlegrazed
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 ight activity in late September and early
October (Smallwood and Bell 2020). Elevations ranged
41280 m at Buena Vista, 115477 m at Golden Hills, and
54402 m at Vasco Winds.
Carcass Detection Rates
We sought to maximize bat and smallbird fatality nds 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 identied by nocturnal
surveys using a thermalimaging camera since 2012
(Smallwood 2016). During daylight morning hours 5 days/
week, dogs searched within 105 m of 23 turbines/day at
Golden Hills, and within 75 m of 35 turbines/day at Buena
Vista, completing 55 turbinesearches at Golden Hills and
76 at Buena Vista. Dogs searched within the same search
boundary that were searched by humans in 20082011 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 doghuman fatality detection team. Use of animal
carcasses was authorized under permits from the United
States Fish and Wildlife Service (MB1355200) and the
California Department of Fish and Wildlife (SC00737).
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
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 oleash for a more cursory search because in
our experience few bat and smallbird fatalities are
found upwind of wind turbines (Brown et al. 2016,
Smallwood 2016). We mapped and photographed fatality
nds using a Trimble GeoExplorer 6000 GPS unit
(Trimble,Sunnyvale,CA,USA),andidentied carcasses
to species. Searches and carcass data collection lasted
about 2 hours/2.3MW turbine and 1.5 hours/1MW
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 postmortem. We weighed trial
carcasses prior to placements, removed 1 foot from bats, and
clipped otips of ight feathers of birds. Human members
of our dog teams, who were blind to trials, reported found
trial carcasses in the same manner as turbinecaused
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 ight 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 nds until the
end of our study. Human searchers at Golden Hills re-
moved carcasses they found, except for our trial carcasses,
but we left dogdetected 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 nds 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, ight direction, body mass of species ying 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 September15 November 2017. Bat species are listed in order of number placed, then birds. Sample sizes were n
for placements of freshfrozen and
thawed carcasses the day before the search, n
for placements on randomized days within 2 weeks of the search, and n
for relocations of carcasses from
Golden Hills to Buena Vista the day before the search.
Placed Body mass (g)
Species n
¯Low High
Mexican freetailed 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
Cliswallow (Hirundo pyrrhonota) 12 1 15.1 10.7 19.0
Oak titmouse (Parus inornatus) 8 1 12.0 6.9 15.6
House nch (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
Blackheaded grosbeak (Pheucticus melanocephalus) 3 1 39.7 34.2 50.8
Violetgreen swallow (Tachycineta thalassina) 2 2 14.2 11.6 18.0
Barn swallow (Hirundo rustica) 2 2 16.4 14.4 18.3
Western scrubjay (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 collareddove (Streptopelia decaocto) 3 1 73.3 44.3 90.0
Cedar waxwing (Bombycilla cedrorum) 3 24.6 23.7 26.3
Whitebreasted nuthatch (Sitta carolinensis) 2 14.0 13.6 14.3
Hooded oriole (Icterus cucullatus) 2 16.4 15.5 17.2
Goldencrowned 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
Chestnutbacked 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 goldnch (Carduelis tristis) 0 1 9.4 9.4 9.4
Mountain bluebird (Sialia currucoides) 0 1 26.0 26.0 26.0
Western ycatcher (Empidonax dicilis) 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
Whitecrowned sparrow (Zonotrichia leucophrys) 1 20.4 20.4 20.4
California quail (Callipepla californica) 1 184.5 184.5 184.5
Northern roughwinged 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
premortem movements of mortally injured animals from
initial deposition sites and postmortem translocation of
carcasses by vertebrate scavengers. Given the variety of factors
that can aect carcass location, Smallwood (2013) asserted
that, other than searching farther from the turbine to nd
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
outcomesbased 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 quantied 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 humanand dogfound
fatalities around wind turbines.
Human searchers found insucient bat fatalities at
Golden Hills for characterizing spatial pattern, so as a sur-
rogate we used data from 3 years of fatality monitoring,
May 2012May 2015, at 34 turbines at Vasco Winds, where
80m tower heights, 105m maximum search radius, and
10m 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 nds by distance from the turbine,
and we compared these human searcherderived spatial
patterns to those derived from dogs at Golden Hills.
We t 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
insucient maximum search radius (Smallwood 2013):
where uwas the bestt upper bound value of the cumu-
lative number of found fatalities, Xwas carcass distance
from the wind turbine within 10m increments, and aand b
were bestt coecients. We divided Cby uto obtain
proportions of cumulative fatalities within 10m distance
increments from the turbine (d).
CostEectiveness 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 20082011 at Buena Vista (Insignia 2011)
and 20122015 at Vasco Winds (Brown et al. 2016).
We estimated fatalities/MW (
ˆ) of bats and birds using
the Smallwood (2013) estimator:
where Fwas number of fatalities found per MW, R
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 28day R
values to represent rst
searches, and our average 27day R
values to represent
subsequent searches. We carried error through the fatality
adjustments using the delta method:
which we multiplied against the appropriate tvalue from a
tdistribution to estimate 95% condence intervals. We cur-
tailed the lower bound of the condence interval at 0. We
measured relative precision as the coecient of variation.
Factors Aecting 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
scale, which
was the measurement scale used in Smallwood et al. (2018),
and we deliberately placed 30 juvenile bats and 15 ightless
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 14 days
in the eld (Table 1). We also placed freshfrozen and
thawed bird carcasses on randomized days up to 2 weeks
prior to the next fatality search At Buena Vista, thereby
Rd p SE S
RS d SE d
() ()
(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 rst direction.
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 nding them and the next human search (
¯=15 days;
range =128 days), but with 25% more turbine searches
over the same time period of our study, human searchers
had 25% more opportunities to nd 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 nextday fatality
searches and conrmed 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 predated our fatality searches, and new fatalities happened during the study.
Species name (scientic name)Old fatalities
New fatalities
Western red bat (Lasiurus blossevillii)041
Myotis (Myotis spp.) 0 0 1
Mexican freetailed 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
Whitetailed kite (Elanus leucurus)110
Redtailed 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
Whitethroated swift (Aeronautes saxatalis)110
Pacicslope ycatcher (Empidonax dicilis)010
Horned lark (Eremophila alpestris)10210
Northern roughwinged swallow (Stelgidopteryx serripennis)0 02
Bewick's wren (Thryomanes bewickii)001
House wren (Troglodytes aedon)001
Rubycrowned kinglet (Regulus calendula)002
American pipit (Anthus rubescens)102
Warbler (Parulidae) 0 0 1
Blackthroated gray warbler (Dendroica nigrescens)101
Townsend's warbler (Dendroica townsendi)010
Lincoln's sparrow (Melospiza lincolnii)001
Darkeyed junco ( Junco hyemalis)001
Blackbird (Icteridae) 1 0 1
Western meadowlark (Sturnella neglecta)677
Brownheaded 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
smallbird 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
similar between bats and small birds when based solely on trial
administrator status checks (Fig. 2). Our bestt models for
daily carcass persistence based solely on trial admin-
istrator status checks were
Bats 1.0185 0.8998
[]= ×
=0.98, root mean square error [RMSE] =0.11),
Small birds e1 3.0732 1
Cdays0.0996 log 1
×( +)
=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
adjusted bat fatality rates by 28%, 40%, and 44% at 7,14,and
28day 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
28day 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
signicantly 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 humanfound 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 t 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 t 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 t to the same fatality data found
within 3 dierent maximum search radii predicted 3 dif-
ferent asymptotic distances beyond which no more fatalities
should be found, and therefore dierent values for dused to
adjust fatality rates (Fig. 4). Numbers of fatalities found to
the 105m search radius conrmed that models t 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
50m 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 eld 14 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
50m 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 t to fatality nds within 50 m
predicted a total available number of bat fatalities that was
53% too low, as conrmed by dog searches within the entire
105m radius.
CostEectiveness of Dogs
Dogs nding 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 coecient 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 signicantly 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 10m 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 (20122015), Altamont Pass Wind Resource Area, California,
USA, where
abX,=+ and Xrepresents distance (m).
Searcher Trials
Model coecients
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 10m 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:
uwas the bestt upper bound value of the cumulative number of found fatalities, Xwas carcass distance from the wind turbine within 10m increments, and
aand bwere bestt coecients. From the model we also predicted proportion of fatalities to occur within the maximum search radius:
Model coecients Logistic model prediction
Searcher Site Radius (m)Taxon uabr
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 10m 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 t
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 (
) 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
), searcher detection rate (S), and maximum search radius bias (d), and calculated standard errors using the delta
Taxa Site Searcher
ˆ(95% CI)
¯SE x
¯SE x
Bats BV Humans 0.01 (0.01) 0.43 0.11 0.06
0.025 0.97 0.325 0.44 (0.001.50)
Bats BV Dogs 0.71 (0.17) 0.43 0.11 0.93 0.001 0.96 0.008 1.85 (0.533.17)
Bats GH Humans 0.03 (0.03) 0.58 0.06 0.06
0.025 1.00
0.214 0.52 (0.001.68)
Bats GH Dogs 2.22 (0.38) 0.43 0.11 1.00 0.000 0.86 0.018 3.35 (1.245.46)
Small birds BV Humans 0.03 (0.02) 0.45 0.04 0.30
0.038 0.86 0.230 0.28 (0.000.65)
Small birds BV Dogs 0.23 (0.12) 0.45 0.04 0.91 0.002 0.74 0.004 0.75 (0.001.57)
Small birds GH Humans 0.38 (0.13) 0.45 0.06 0.30
0.038 0.89 0.023 1.76 (0.313.21)
Small birds GH Dogs 1.63 (0.30) 0.45 0.04 0.84 0.001 0.86 0.009 2.79 (1.613.97)
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).
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 nd.
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, 20122015 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 perfatality 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 Aecting Search Detection of Bat and Bird
Whereas dogs found nearly all of the trial bat carcasses
conrmed 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 nds 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 dier signicantly by mean
body mass (ttests, P>0.05).
Of 24 trial bat carcasses that we placed at Buena Vista that
had already persisted 14 days at Golden Hills (Table 1), and
of which we conrmed 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 dier signicantly by mean distance to
carcass occlusion (ttests, 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
Dogs missed 8 birds ranging in size from a 3.7gBewick's
wren (Thryomanes bewickii) to an 87.6g Eurasian collareddove
Figure 5. Proportions of trial bat carcasses that were conrmed 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 nds by log
0.5 gincrements based on dog and human searchers during concurrent monitoring eorts (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
nongravel 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' rst search of the study.
Skilled scentdetection dogs found 95% of placed bats and
91% of placed birds, despite our deliberate placements of
carcasses of immature bats and birds, mostly smallbodied
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 eld for
4 days, and they found bats that disappeared into tall grass
when dropped from shoulderheight, 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 condence that they can
nd the majority of available carcasses representing wind
turbine fatalities.
Our results were consistent with others who have used
scentdetection 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 ndings
were similar to earlier comparisons between dogs and hu-
mans, although we note the disparity between dog and
human detection rates increased with smallerbodied 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 71fold
dierence in found bats and 4fold dierence in found small
birds represented substantial dierences in searcher de-
tection between dogs and humans, dierences that were
measured in actual concurrent fatality monitoring rather
than in separate trials. Our ndings at Buena Vista also
diered 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
66fold dierence in bats found per year.
Dogs nding 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 smallsized 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 costeectiveness,
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 dicult
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, nd 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 identiable 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 unquantied without detecting
collisions in some way other than searches within plots.
Background mortality also remains insuciently quantied.
Scentdetection dogs would more eectively test hypoth-
eses related to impact assessments and mitigation ecacy by
detecting more of the available bat and bird fatalities. They
would be more likely than human searchers to reveal
whether preconstruction bat activity patterns can predict
postconstruction eects (Hein et al. 2013), and they should
nd enough of the available bats to develop micrositing
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 scentdetection 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
nd almost all of the available carcasses. Some of our
ndings suggest that a skilled dog team might nd 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 costeective monitoring and to insight about causal
factors of collisions and reasonable solutions. Cost
eectiveness of using dogs might prove lower than what we
report where dogs perform less eectively 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
Many of the available fatality monitoring reports likely
underestimated bat and smallbird 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 scentdetection 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 hypothesistesting of causal factors and wind
turbine micrositing strategies.
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
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 eort 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 eorts given us by Captain and Jack. This research
Foundation, which was administered through the East Contra
Costa County Habitat Conservancy Science and Research
Grant Program (Conservancy Contract 201603). 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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Smallwood et al. Dog Detections of Fatalities 13
... Our results support our hypothesis that CDD teams improve detection of prey remains at carnivore clusters during the summer over technician teams. Previous studies also indicated that CDDs outperform humans when searching for other objects of conservation interest which are visually cryptic but traceable by scent (Smallwood et al. 2020). In our study, CDD teams detected small prey remains at clusters at 2.6 times the rate of technician teams under similar conditions. ...
... In our study, CDD teams detected small prey remains at clusters at 2.6 times the rate of technician teams under similar conditions. Greater detection rates of CDD teams in our study are similar to improvements reported for locating bats (6.4 times greater) and songbirds (2.7 times greater) at wind turbines as compared to human-led searches (Smallwood et al. 2020 Rolland et al. 2007). Detection of prey remains by individual technician teams in the current study required 6-times more Table 1. ...
... Occurrence of prey remains at clusters was unknown before investigation and probability of detection of prey remains for CDD teams and technician teams cannot be estimated. However, studies at wind turbines suggest CDDs may achieve >95% detection probability (Smallwood et al. 2020). High detection probability is further supported by estimates of CDD accuracy at detecting mammalian scats (75-100%; Smith et al. 2003, Reindl 2004, Leigh and Dominick 2015, bumble bee nests (Bombus spp., 100%; Waters et al. 2011), and reptile skins (95%; Browne et al. 2015). ...
Combining carnivore movements with site visits to investigate predation events can inform investigators of carnivore diets, kill rates, and risk factors for prey. However, detecting remains of prey can be challenging when prey is small or when vegetation conceals prey. Conservation detection dogs (CDDs) have assisted with wildlife surveys to locate objects of conservation interest, often improving detection over human counterparts. We hypothesized that CDDs would improve efficacy for detection of prey remains at kill locations compared to human searchers. We compared the efficacy of CDD teams (1 dog, 1 human handler) and technician teams (2 humans) for locating prey remains at 729 carnivore cluster (potential predation) sites in the Upper Peninsula of Michigan, USA, during May to August of 2015. Carnivore species included gray wolves (Canis lupus), coyotes (C. latrans), bobcats (Lynx rufus), and American black bears (Ursus americanus). Overall, CDD teams identified prey remains at 2.3 times more clusters, required 42% less search time, and handlers traveled 83% less distance per detected prey remain compared to technician teams. Within carnivore species, CDD teams detected small prey remains at a greater rate than technician teams (4.0–4.3 times greater) for all carnivores except for bobcat which had similar detection rate. Detection of large prey remains (e.g., adult ungulates) was similar between CDD teams and technician teams. Our study supports CDDs ability to outperform humans when searching for objects of conservation interest which are visually cryptic but traceable by scent. Where logistics allow, we recommend use of CDDs over human searchers when it is a priority to locate remains of small prey and when vegetation is dense and may obscure even larger prey items. © 2021 The Wildlife Society. Conservation detection dogs improved detection of remains of small prey and search efficiency as compared to humans. Where logistics allow, we recommend use of conservation detection dogs over human searchers when it is a priority to locate remains of small prey and when vegetation is dense and may obscure even larger prey items as these objects are traceable by scent.
... Furthermore, the results vary strongly depending on the search habits of the human or dog, meaning searches are difficult to compare and hardly reproducible. While the detection rate was shown to be better using dogs rather than humans [15], there is still the risk of missing fatalities if the carcasses are carried away by scavengers before the search takes place [16]. According to [17], this effect becomes more obvious with longer search intervals. ...
... Brinkmann et al. [28] documented a human search efficiency of 75% in open space and 66% in high grass (without quantitatively defining the grass height). Smallwood et al. [15] report about a human search efficiency of 6% and 96% for dogs, Mathews et al. [29] of 20% for humans and 73% for dogs, Arnett et al. [30] of 14%/42% for humans and of 71%/81% for dogs and Dominguez et al. [31] of 20% for humans and 80% for dogs. From this we can infer that the resulting efficiency is dependent on many factors and very inconsistent among different studies. ...
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The number of collision fatalities is one of the main quantification measures for research concerning wind power impacts on birds and bats. Despite being integral in ongoing investigations as well as regulatory approvals, the state-of-the-art method for the detection of fatalities remains a manual search by humans or dogs. This is expensive, time consuming and the efficiency varies greatly among different studies. Therefore, we developed a methodology for the automatic detection using visual/near-infrared cameras for daytime and thermal cameras for nighttime. The cameras can be installed in the nacelle of wind turbines and monitor the area below. The methodology is centered around software that analyzes the images in real time using pixel-wise and region-based methods. We found that the structural similarity is the most important measure for the decision about a detection. Phantom drop tests in the actual wind test field with the system installed on 75 m above the ground resulted in a sensitivity of 75.6% for the nighttime detection and 84.3% for the daylight detection. The night camera detected 2.47 false positives per hour using a time window designed for our phantom drop tests. However, in real applications this time window can be extended to eliminate false positives caused by nightly active animals. Excluding these from our data reduced the false positive rate to 0.05. The daylight camera detected 0.20 false positives per hour. Our proposed method has the advantages of being more consistent, more objective, less time consuming, and less expensive than manual search methods.
... Dogs can discriminate between individuals within a species (Wasser et al., 2009) and have special benefits such as the ability to generalize across odours of common and closely related cryptic species (Rutter et al., 2021a) or be trained on inert-frozen plant material for live sample detection (Needs et al., 2021). They consistently outperform traditional survey methods in the search for invasive plants (Goodwin et al., 2010), wind farm mortality surveys (Smallwood et al., 2020), scat detection (Thompson et al., 2020;Grimm-Seyfarth et al., 2019) and live animal detection (Cristescu et al., 2015); however, dogs may not be the most cost-effective detection tool if targets are abundant or easy to detect using other methods (Brook et al., 2012). ...
... estimates from collisions with wind turbines are relatively low, causing an estimated 234,000 mortalities in the U.S. annually (Loss et al. 2013a). However, small-bird fatalities at wind turbines are likely underestimated in many monitoring reports (Smallwood et al. 2020). Furthermore, this type of mortality is expected to grow, as the number of wind facilities is projected to increase by 20% in the next decade, and wind turbine height is increasing at these facilities (Loss et al. 2013a). ...
... To date, the most common metric of efficacy for fatality reduction tests has been to compare the number of dead bats found beneath wind turbines following nights with and without applied treatments (e.g., curtailment, acoustic deterrents [20,21,[25][26][27]109,110]). This gold standard of counting carcasses to judge if a method works is fully justified and supported by robust statistical measures and laboratory techniques to enhance the quality, precision, and reliability of such data [111][112][113][114][115][116][117][118][119][120][121]. Had we relied on fatality ground searches as a metric of bat response to dim-UV treatment, we would not have been able to statistically test for treatment effects, by either attraction or deterrence, simply (and fortunately) due to the low sample size. ...
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Wind energy producers need deployable devices for wind turbines that prevent bat fatalities. Based on the speculation that bats approach turbines after visually mistaking them for trees, we tested a potential light-based deterrence method. It is likely that the affected bats see ultraviolet (UV) light at low intensities. Here, we present the results of a multi-month experiment to cast dim, flickering UV light across wind turbine surfaces at night. Our objectives were to refine and test a practical system for dimly UV-illuminating turbines while testing whether the experimental UV treatment influenced the activity of bats, birds, and insects. We mounted upward-facing UV light arrays on turbines and used thermal-imaging cameras to quantify the presence and activity of night-flying animals. The results demonstrated that the turbines can be lit to the highest reaches of the blades with “invisible” UV light, and the animal responses to such experimental treatment can be concurrently monitored. The UV treatment did not significantly change nighttime bat, insect, or bird activity at the wind turbine. Our findings show how observing flying animals with thermal cameras at night can help test emerging technologies intended to variably affect their behaviors around wind turbines.
... In our study, we could only compare carcass detection probabilities between dogs and humans for areas with intermediate ground visibility, however the dog-human differential is likely to increase even more in low visibility areas like tall and dense grasslands (Arnett, 2006;Domínguez del Valle et al., 2020). It is undeniable that dog-handler teams increase carcass detection probabilities, with great impact on the accuracy of bird fatality estimates, and also improve search efficiency as dogs can survey larger areas per unit of time (Paula et al., 2011;Reyes et al., 2016;Smallwood et al., 2020). However, the selection, purchase and training of scent detection dogs, as well as the maintenance of their search skills, heath care and housing may be still financially and logistically demanding (Beebe et al., 2016;Mathews et al., 2013), which inhibits their more widespread use in bird fatality assessments. ...
Environmental impact assessment (EIA) follow-up monitoring in energy projects, such as wind farms, solar facilities and power lines, frequently encompasses bird fatality surveys based on regular carcass searches. Since a large number of bird carcasses are often not found, field experiments to determine carcasses persistence (CP) and searcher efficiency (SE) biases in fatality surveys are typically performed for every single project. These data are, however, rarely used beyond the scope of each original project. We compiled data from CP and SE trials performed under 36 independent monitoring programs aiming to assess bird mortality at transmission lines in Portugal, whose results were until now unavailable or dispersed in grey literature. We used survival analysis and generalized linear mixed-effects models to investigate the ecological and methodological factors influencing CP times and SE rates. Bird carcass size was a key driving factor of both CP times and SE rates of human observers, which were consistently out-performed by scent detection dogs. Season and habitat interactions had also an important role in CP patterns, while variations in SE rates by human observers were largely influenced by ground visibility (i.e., a combination of ground cover and vegetation height). Our results reinforce previous studies indicating that CP and SE biases are site-specific and determined by a wide range of ecological and methodological factors not always accounted in standard trial designs. Overall, our study demonstrates that data routinely collected under bird monitoring programs from multiple projects can be combined to identify broad ecological patterns, limitations of current studies and, ultimately, improve EIA follow-up practice.
... D was carcass detection probability estimated from the outcomes of carcass detection trials that were integrated into routine fatality monitoring and then logit-regressed on the log 10 body mass (g) of the placed carcasses [19,20,22]. d was the probability that the carcass would be found within the search area [21], the data for which were updated by the pattern of carcass distances from turbines that was discerned from more recent use of leashed scent-detection dogs in fatality monitoring [24]. We estimatedF/MW/year for each monitored wind turbine, and we extrapolated the mean among turbines to each wind energy project to which the turbines belonged. ...
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Loggerhead shrike (Lanius ludovicianus) has declined across most or all of its geographic range. The species’ raptorial behavior requires maintenance of large territories, which means populations of breeding shrikes require large areas of habitat and are therefore sensitive to habitat loss and habitat fragmentation. We estimated breeding densities of loggerhead shrikes in the Altamont Pass Wind Resource Area (APWRA), California, where annual shrike mortality caused by wind turbine collisions was high until just before our study began in 2016. Based on surveys across an annual average 50 randomized sampling plots in 2016–2019, we estimated an average 129 breeding pairs/year across the 167.6-km2 APWRA. Relative to the size of the study area, density in the APWRA was relatively high compared to densities reported from other study sites across North America. It was higher than predicted by application of the Partners in Flight estimator, which was based on Breeding Bird Surveys along roads. We also found that loggerhead shrikes in the APWRA were limited by the availability of nest substrate and by California ground squirrels (Otospermophilus beecheyi) and their burrow complexes, which have keystone effects on vegetation and wildlife in the APWRA. To most effectively conserve loggerhead shrikes in the APWRA, wind turbine mortality should be minimized, ground squirrels conserved instead of eradicated as pests, and appropriate trees and shrubs cultivated where they are needed.
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Wind energy is a rapidly expanding renewable technology with massive global investments; however, operating turbines are associated with bat strikes globally, and evidence suggests that without intervention, wind farm collisions could drive some common species to extinction. One widely regarded method for reducing strike mortality is operational mitigation, or curtailment, where turbine operation is restricted at low wind speeds. Despite an increasing number of studies in the Northern Hemisphere demonstrating curtailment effectiveness, no empirical studies have yet been conducted in Australia. This paper reports the findings of a curtailment study implemented at the Cape Nelson North wind farm in southwest Victoria, Australia. Conservation detection dog teams conducted mortality surveys between January and April in 2018 (before; pre‐curtailment) and 2019 (after; during curtailment). Results were consistent with similar studies in the USA and Europe, as curtailment significantly reduced pooled species mortality by 54%. Bat calls did not decline during the study period, and thus were not an explanation for the reduction in fatalities. This study demonstrates that curtailment is a valid method for reducing bat turbine collision in south‐eastern Australia. Consideration should be given to curtailment as a means to reduce bat turbine impacts in Australia, particularly at sites with known endangered and threatened populations, as we act to reduce anthropogenic climate change and its time‐sensitive negative consequences.
To reduce carbon emissions from fossil fuel combustion, United States government agencies, including those in California, initiated aggressive programs to hasten development of utility‐scale solar energy. Much of California's early development of solar energy occurred in deserts and annual grasslands, much of it on public land. Measurement of solar energy's impacts to wildlife has been limited to mortality caused by features of solar facilities, and has yet to include impacts from habitat loss and energy transmission. To estimate species‐specific bird and bat fatality rates and statewide mortality, I reviewed reports of fatality monitoring from 1982 to 2018 at 14 projects, which varied in duration, level of sampling, search interval, search method, and carcass detection trials. Because most monitors performed carcass detection trials using species of birds whose members were larger than birds and bats found as fatalities, I bridged the monitors' onsite trial results to offsite trial results based on the same methods but which also measured detection probabilities across the full range of body sizes of species represented by fatalities. This bridge preserved the project site's effects on detection probabilities while more fully adjusting for the effects of body size. My fatality estimates consistently exceeded those reported. Projected to California's installed capacity of 1,948.8 MW of solar thermal and 12,220 MW of photovoltaic (PV) panels in 2020 (14,168.8 MW total), reported estimates would support an annual statewide fatality estimate of 37,546 birds and 207 bats, whereas I estimated fatalities of 267,732 birds and 11,418 bats. Fatalities/MW/year averaged 11.61 birds and 0.06 bats at PV projects and 64.61 birds and 5.49 bats at solar thermal projects. Fatalities/km/year averaged 113.16 birds and zero bats at generation tie‐ins, and 14.44 birds and 2.56 bats along perimeter fences. Bird fatality rates averaged 3 times higher at PV projects searched by foot rather than car. They were usually biased low by insufficient monitoring duration and by the 22% of fatalities that monitors could not identify to species. I estimated that construction grading for solar projects removed habitat that otherwise would have supported nearly 300,000 birds/year. I recommend that utility‐scale solar energy development be slowed to improve project decision‐making, impacts assessment, fatality monitoring, mitigation efficacy, and oversight. California's utility‐scale solar energy projects kill many birds and bats, representing an emerging environmental crisis. Habitat loss from construction of solar projects cause equal if not larger impacts than mortality of collisions with operable project facilities. It would be prudent to pause develop to improve decision‐making frameworks over which forms of renewable energy to develop and how to measure and respond to their impacts to wildlife.
The comparison of alternatives is a requirement of all ESIA guidelines. While this is certainly justified, it is not always an easy thing to do, since very often there is one project to be studied, with no real alternatives, especially in the later stages of project development like feasibility study or detailed design. Some of the possibilities that may exist are presented below, and discussed on the basis of suitable examples. While project-specific alternatives like different dam sites or project dimensions may be under discussion only exceptionally, two potential alternatives can—and should be—discussed in any case, namely (i) the possibility of generating the same amount of electricity with a different energy source, and (ii) the no-project alternative, meaning the solution of not doing anything.
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Wind energy siting to minimize impacts to bats would benefit from impact predictions following pre-construction surveys, but whether pre- or even post-construction activity patterns can predict fatalities remains unknown. We tested whether bat passage rates through rotor-swept airspace differ between groups of wind turbines where bat fatalities were found and not found during next-morning dog searches for fatalities. Passage rates differed significantly and averaged four times higher where freshly killed bats were found in next-morning fatality searches. Rates of near misses and risky flight behaviors also differed significantly between groups of turbines where bats were found and not found, and rate of near misses averaged eight times higher where bat fatalities were found in next-morning searches. Hours of turbine operation averaged significantly higher, winds averaged more westerly, and the moon averaged more visible among turbines where and when bat fatalities were found. Although dogs found only one of four bats seen colliding with turbine blades, they found many more bat fatalities than did human-only searchers at the same wind projects, and our fatality estimates were considerably higher. Our rates of observed bat collisions, adjusted for the rates of unseen collisions, would predict four to seven times the fresh fatalities we found using dogs between two wind projects. Despite markedly improved carcass detection through use of dogs, best estimates of bat fatalities might still be biased low due to crippling bias and search radius bias.
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Species extinctions have defined the global biodiversity crisis, but extinction begins with loss in abundance of individuals that can result in compositional and functional changes of ecosystems. Using multiple and independent monitoring networks, we report population losses across much of the North American avifauna over 48 years, including once common species and from most biomes. Integration of range-wide population trajectories and size estimates indicates a net loss approaching 3 billion birds, or 29% of 1970 abundance. A continent-wide weather radar network also reveals a similarly steep decline in biomass passage of migrating birds over a recent 10-year period. This loss of bird abundance signals an urgent need to address threats to avert future avifaunal collapse and associated loss of ecosystem integrity, function and services.
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Strategic conservation efforts for cryptic species, especially bats, are hindered by limited understanding of distribution and population trends. Integrating long-term encounter surveys with multi-season occupancy models provides a solution whereby inferences about changing occupancy probabilities and latent changes in abundance can be supported. When harnessed to a Bayesian inferential paradigm, this modeling framework offers flexibility for conservation programs that need to update prior model-based understanding about at-risk species with new data. This scenario is exemplified by a bat monitoring program in the Pacific Northwestern United States in which results from 8 years of surveys from 2003 to 2010 require updating with new data from 2016 to 2018. The new data were collected after the arrival of bat white-nose syndrome and expansion of wind power generation, stressors expected to cause population declines in at least two vulnerable species, little brown bat (Myotis lucifugus) and the hoary bat (Lasiurus cinereus). We used multi-season occupancy models with empirically informed prior distributions drawn from previous occupancy results (2003-2010) to assess evidence of contemporary decline in these two species. Empirically informed priors provided the bridge across the two monitoring periods and increased precision of parameter posterior distributions, but did not alter inferences relative to use of vague priors. We found evidence of region-wide summertime decline for the hoary bat ( λ ^ = 0.86 ± 0.10) since 2010, but no evidence of decline for the little brown bat ( λ ^ = 1.1 ± 0.10). White-nose syndrome was documented in the region in 2016 and may not yet have caused regional impact to the little brown bat. However, our discovery of hoary bat decline is consistent with the hypothesis that the longer duration and greater geographic extent of the wind energy stressor (collision and barotrauma) have impacted the species. These hypotheses can be evaluated and updated over time within our framework of pre-post impact monitoring and modeling. Our approach provides the foundation for a strategic evidence-based conservation system and contributes to a growing preponderance of evidence from multiple lines of inquiry that bat species are declining.
Technical Report
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Bats collide with wind turbines resulting in fatalities, and much has been learned about the pattern and magnitude of this mortality in the U.S. and Canada (Kunz et al. 2007, Arnett et al. 2008, Arnett and Baerwald 2013, Barclay et al. 2017). Previously, cumulative assessments of this mortality have relied almost entirely on data gleaned from publicly available studies of bat collision fatalities at wind energy facilities (e.g., Arnett and Baerwald 2013). In this report we describe and summarize the bat fatality rate and fatality incident data contained in the American Wind Wildlife Information Center (AWWIC: pronounced “A-wic”), which includes both publicly available and confidential bat collision fatality data from wind energy facilities. We focus on describing the patterns of bat fatalities at wind farms across regions of the U.S. as represented in AWWIC. It is our intention that this report will focus future research evaluating the patterns observed in the data thus furthering our understanding of the variation in risk to bats from wind energy development among species and regions. The current report focuses on data from U.S. wind energy facilities, but we intend to include available data from wind facilities in Canada in future reports. In the process described below, we continue to add data as studies become available and this report will be updated on a regular basis. (25) (PDF) A Summary of Bat Fatality Data in a Nationwide Database. Available from: [accessed Dec 03 2019].
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Dogs are widely used for scent detection work, assisting in searches for, among other things, missing persons, explosives, and even cancers. They are also increasingly used in conservation settings, being deployed for a range of diverse purposes. Although scent detecting dogs have been used in conservation roles for over 100 years, it is only recently that the scientific literature has begun to document their effectiveness and, importantly, how suitable dogs should initially be selected by organizations wanting to develop a detection program. In this paper, we review this literature, with the aim of extracting information that might be of value to conservation groups considering whether to invest in the use of dogs. We conclude that selection of appropriate dogs is no easy task. While olfactory ability is critical, so also are a range of other characteristics. These include biological, psychological, and social traits. At present, no validated selection tools have been published. Existing organizations have adapted selection instruments from other contexts for their use, but very little published information is available regarding the effectiveness of these instruments in a conservation setting. In the absence of clear guidelines, we urge those wanting to invest in one or more dogs for conservation purposes to proceed with extreme caution and, preferably, under the watchful eyes of an experienced professional.
Fatality monitoring at wind projects requires carcass detection trials to adjust fatality estimates for the proportion of fatalities not found. However, detection trials vary greatly in metric, duration, carcass monitoring schedule, species, number placed, state of decomposition, whether placed within or outside search areas, and other factors. We introduce a new approach for estimating fatalities by quantifying overall detection rates rather than separate rates for searcher detection error and carcass persistence, and by leaving placed and found fatality carcasses undisturbed throughout monitoring. We placed 2 fresh‐frozen bird carcasses weekly at random sites within fatality search areas and on randomized days Monday–Friday at Sand Hill and Santa Clara wind projects, Altamont Pass Wind Resource Area, California, USA. To estimate detection rates, we used logit regression to fit detection outcomes on body mass, which served as an axis of similitude between placed trial carcasses and fatality finds. Adjusted carcass placement rates among species detected by searchers regressed on true placement rates with a slope of 1.0 so long as sufficient numbers of trial carcasses were placed, thus validating our approach as an unbiased estimator. Our approach generally estimated lower fatality rates than did conventional approaches, the latter of which demonstrated biases in searcher detection rates and carcass persistence rates whether based on proportion of carcasses remaining or mean days to removal. Our approach also revealed detection errors that highlight the difficulty of finding and identifying the remains of dead animals, and which warrant routine reporting. Despite averaging only a 5‐day search interval on intensively grazed annual grasslands where ground visibility was usually high, our experienced fatality monitors averaged 4.3 searches/first carcass detection, failed to detect 25% of 75 species represented by placed carcasses, and misidentified carcasses to species among 44% of species detected. Estimates of time since death also suffered bias and large error. Our approach more realistically simulates carcass detection probabilities associated with fatality monitoring, is less costly, facilitates hypothesis testing, eliminates multiple sources of error and bias suspected of conventional methods, and enables quantification of errors in estimated time since death, species identifications, and false negative findings. © 2018 The Wildlife Society. We present an approach for accurately estimating fatalities at wind energy projects that avoids multiple unrealistic assumptions related to carcass detection rates, heightens awareness of the need for more careful field methods, and introduces opportunities for needed hypothesis‐testing.
Bird and bat fatality estimates based on scientific monitoring are used to assess and compare impacts among wind energy projects. Fatality estimates are influenced by multiple factors, including variation in methodology. Variation in the interval between fatality searches exemplifies a monitoring decision that can potentially confound comparison of fatality estimates. A study at the Sand Hill portion of the Altamont Pass Wind Resource Area, California, USA, provided the first opportunity to compare fatality-rate estimates derived from 2 independent, experienced monitoring teams searching the same wind turbines at 2 different periodic intervals. Over 30 months of monitoring the same wind turbines, April 2012–October 2014, searches averaging 5-day intervals detected 308 additional fatalities (of 431 fatalities total) representing 20 additional species (of 32 species total) compared with the searches averaging 39-day intervals. Body mass explained most of the variation in discrepant fatality detections between the 2 search intervals, with the 39-day interval searches detecting only 10% of the bats and birds of 10–40 g that were found by the 5-day interval searches. The 39-day search interval produced an estimate of annual bird fatalities/MW that was 39% lower than the estimate produced from the 5-day search interval. The 39-day search interval also resulted in many more species identification errors and greater errors in estimated time since death. The average search interval used in fatality monitoring strongly influences fatality estimates; long intervals can contribute to false impressions that wind projects have small or negligible effects on small birds and bats.
Studies at renewable energy sites often attempt to estimate avian and bat fatalities or fatality rates (e.g., fatalities/megawatt [MW]/year). However, searcher efficiency and level of survey effort among sites are variable. We evaluated how searcher efficiency and proportion of area surveyed affected precision of fatality estimates and probability of detecting rare fatalities (e.g., fatalities of an endangered species). We measured searcher-efficiency rates of human and dog-handler teams for 3 fatality types: feather spots, small carcasses, and large carcasses. We also created high and low searcher-efficiency scenarios to evaluate effects of searcher efficiency across a broader range. Model selection on a set of logistic regression models for our empirical trials supported search team and fatality type as important predictors of searcher-efficiency rates, and demonstrated that dog-handler teams had higher searcher efficiency for all fatality types than human search teams. We used model simulations to evaluate fatality estimates obtained across the 4 searcher-efficiency scenarios and 10 levels of survey coverage: 10–100%, in increments of 10%. At each level of survey coverage, width of confidence intervals decreased as searcher efficiency increased; however, as survey coverage increased, width of the confidence intervals stabilized, and further increases in coverage did not lead to increases in precision. Average fatality estimates were biased positively and this bias increased with lesser searcher efficiency. The survey coverage necessary to achieve 80% detection probability for rare fatalities (defined as 1, 5, or 15 fatalities) decreased as searcher efficiency increased for all fatality types. When a rare fatality was defined as a single fatality out of 1,000, an 80% detection probability was achieved only by dog-handler teams and the high searcher-efficiency scenario, and only for large carcasses. Our results emphasize the need for managers and agencies to consider study objectives and site characteristics when selecting level of survey coverage, type of search team, and other options to maximize searcher efficiency.
Monitoring fatalities at wind energy facilities after they have been constructed can provide valuable information regarding impacts of wind power development on wildlife. The objective of this monitoring is to estimate abundance of a super-population of carcasses that entered the area within a designated period of time. By definition, the population is not closed and carcasses can enter as they are killed through collision with turbines, and leave as they are removed by scavengers or decompose to a point where they are not recognizable. In addition, the population is not inherently mobile, but can only change location through some external force. A focus on number of animal carcasses comprising the super-population, combined with peculiar traits that resist classic assumptions, distinguish fatality estimation at wind-power facilities from more classic abundance estimates that can be addressed through mark-recapture techniques or other well-known abundance estimators. We review the available methods to estimate the super-population of carcasses at wind power facilities. We discuss the role of these estimates in determining appropriate levels of minimization and mitigation of impacts to individual species of concern. We discuss the potential to extrapolate these measurements to reflect the cumulative effect of the industry on individual species. Finally, we suggest avenues of research needed to strengthen our understanding of the effect wind power development has, and might have in the future, on wildlife on this continent and worldwide.