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Efficacy of scent-detection dogs for locating bat roosts in trees and snags


Abstract and Figures

Conservation efforts for tree- and snag-roosting bats are challenging because roost sites are difficult and costly to locate. We assessed the ability of scent detection dogs to locate bat roosts using controlled field experiments conducted at 2 sites in northern Arizona, USA, during July and August of 2007, with small bags of bat guano and known bat roosts. Scent detection dogs correctly detected 79% of guano bags and 29% of known bat roosts; but, when searching during shorter time periods for roosts only, dogs correctly detected 77% of known roosts. Factors affecting detection of guano bags included bag height and mass. Factors affecting detection of roosts included height, size of the bat colony, and air temperature. Rest breaks and competition between dogs apparently increased their success rate in finding roosts. Using a scent detection dog to locate roosts was similar in cost to radiotelemetry; however, the use of a scent detection dog was less invasive because the use of dogs precluded the need to capture and radiotag bats. Important considerations influencing the efficacy of using scent detection dogs include training and transportation costs, and skill level of dog handlers. Although some factors limit the ability of scent detection dogs to accurately locate roosts, dogs in our study approximated the roost location to within a 30-m radius, which may be sufficient to protect these areas during management activities. If managers have the ability within an area to retain all large-diameter snags that have bat roost characteristics, then scent detection dogs will likely not provide adequate added value to warrant their survey costs. However, scent dogs could be important for locating roosts of species that are imperiled or of conservation concern.
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Tools and Technology
Efficacy of Scent-Detection Dogs for Locating
Bat Roosts in Trees and Snags
School of Forestry, Northern Arizona University, Flagstaff, AZ 86011, USA
CHRISTINA D. VOJTA, Landscape Conservation Initiative, Northern Arizona University, Flagstaff, AZ 86011, USA
ELISABETH D. MERING, School of Forestry, Northern Arizona University, Flagstaff, AZ 86011, USA
BARBARA DAVENPORT, PackLeader Dog Training LLC, 14401 Crews Road KPN, Gig Harbor, WA 98329, USA
ABSTRACT Conservation efforts for tree- and snag-roosting bats are challenging because roost sites are
difficult and costly to locate. We assessed the ability of scent detection dogs to locate bat roosts using
controlled field experiments conducted at 2 sites in northern Arizona, USA, during July and August of 2007,
with small bags of bat guano and known bat roosts. Scent detection dogs correctly detected 79% of guano bags
and 29% of known bat roosts; but, when searching during shorter time periods for roosts only, dogs correctly
detected 77% of known roosts. Factors affecting detection of guano bags included bag height and mass.
Factors affecting detection of roosts included height, size of the bat colony, and air temperature. Rest breaks
and competition between dogs apparently increased their success rate in finding roosts. Using a scent
detection dog to locate roosts was similar in cost to radiotelemetry; however, the use of a scent detection dog
was less invasive because the use of dogs precluded the need to capture and radiotag bats. Important
considerations influencing the efficacy of using scent detection dogs include training and transportation costs,
and skill level of dog handlers. Although some factors limit the ability of scent detection dogs to accurately
locate roosts, dogs in our study approximated the roost location to within a 30-m radius, which may be
sufficient to protect these areas during management activities. If managers have the ability within an area to
retain all large-diameter snags that have bat roost characteristics, then scent detection dogs will likely not
provide adequate added value to warrant their survey costs. However, scent dogs could be important for
locating roosts of species that are imperiled or of conservation concern. Ó2015 The Wildlife Society.
KEY WORDS Arizona, Chiroptera, feces, field trials, forest, guano, Idionycteris phyllotis, radiotelemetry, roost.
Most conservation efforts for bats focus on conspicuous
species that aggregate in large numbers, are impacted by focal
threats (e.g., impacts to cave and mine roosts), and are easy to
observe (Weller et al. 2009). In contrast, inconspicuous
species that roost in small, dispersed colonies have received
fewer conservation actions because colonies are hard to locate
and the effects on these species from diffuse threats (e.g.,
changes in forest structure or land conversion) are difficult to
document (Weller et al. 2009). Moreover, species that roost
in crevices, snags, and trees tend to switch roost sites
frequently during the breeding season (e.g., Bernardos et al.
2004, Solvesky and Chambers 2009); this behavior creates
additional challenges for finding and protecting roosts.
Since the 1980s, resource managers and researchers have
used radiotelemetry to locate roosts, and the number of
telemetry studies has increased with the development of
micro-transmitters (Amelon et al. 2009). Nevertheless,
radiotelemetry presents challenges because the life of
micro-transmitters is generally <2 weeks (depending on
the size of the transmitter, which is conditioned by the mass
of the bat; Aldridge and Brigham 1988), and the task of
locating telemetered bats is labor-intensive and therefore
expensive. Moreover, bats can roost substantial distances
from their original points of capture (e.g., Corbett et al.
2008, Chambers et al. 2011), so roosts located through
radiotelemetry are often outside specific areas targeted for
management. In these situations, it is difficult to justify the
telemetry costs when there are no obvious benefits to
Scent detection dogs have successfully located live animals
(Vice and Engeman 2000, Nussear et al. 2008, Gsell et al.
2010), carcasses (Arnett 2006, Paula et al. 2011, Mathews
et al. 2013), and scat for species including North Atlantic
right whales (Eubalaena glacialis), bobcat (Lynx rufus), bears
(Ursus arctos and U. americanus), and bush dogs (Speothos
venaticus; Wasser et al. 2004, Harrison 2006, Rolland et al.
2006, Long et al. 2007b, DeMatteo et al. 2009). If scent
detection dogs (hereafter, dogs) could reliably locate bat
roosts, studies could target bat activity within specific areas
affected by land management or disturbance (e.g., timber
sales, housing developments, fires, mining) instead of an
Received: 25 August 2014; Accepted: 29 June 2015
Published: 22 October 2015
Wildlife Society Bulletin 39(4):780–787; 2015; DOI: 10.1002/wsb.598
780 Wildlife Society Bulletin 39(4)
emphasis on locations of telemetered individuals, which may
be outside areas of interest.
Early experiments showed that dogs could be trained to use
bat guano to locate roosts in short-statured woodlands of
pinyon pine (Pinus edulis) and juniper (Juniperus spp.;
A. Chung-McCoubrey, National Park Service, unpublished
data). Although these results were encouraging, the experi-
ments were not designed to evaluate use of dogs in forested
environments or quantify rates of success under specific
environmental conditions. To provide a quantitative assess-
ment of the efficacy of using dogs, we developed a set of
controlled field experiments using different dog–handler pairs
under measured environmental conditions, and with con-
trolled levels of guano and known roost sites. Our specific
objectives were to identify external factors affecting roost
detection (e.g., dog–handler pair, weather, size and height of
bat roost), generate cost estimates for using dogs as an
alternative to radiotelemetry, and develop recommendations
for using dogs in area-based studies of management activities.
We conducted the study at 2 sites on the Coconino National
Forest in northern Arizona, USA, during July and Au-
gust 2007: Fort Valley (358170N, 1118430W, elevation 2,160–
2,790 m) and Happy Jack (348400N, 1118230W, elevation
2,050–2,290 m). Slopes rangefrom 0% to 29%. Ponderosa pine
(Pinus ponderosa) dominated the areas, but other tree species
include Gambel oak (Quercus gambelii) below 2,250 m and
mixed conifer (Abiesand Picea spp.) above 2,400 m. Understory
vegetation was generally sparse and open. During summer
(June–August) 2007,mean temperature and total precipitation
in northern Arizona were 178C and 13.8 cm (Western
Regional Climate Center 2008). Specific sites used for trials
were in areas managed primarily for forest and wildlife values
and were not in proximity to major roads or trails or to
recreational sites or other human structures.
Two handlers (authors Chambers and Mering) were trained
and certified to work with 2 conservation dogs at the
PackLeader Dog Training facility (Gig Harbor, WA).
Because we wanted dogs to respond to all bat species they
detected and not to specific bat species, dogs were trained to
locate bats using a mixture of guano from 5 species (pallid bat
[Antrozous pallidus], big brown bat [Eptesicus fuscus], Arizona
myotis [Myotis occultus], Yuma myotis [M. yumanensis], and
Mexican free-tailed bat [Tadarida brasiliensis]) collected at
natural roosts in Arizona and New Mexico, USA. Training
occurred at the facility in Washington; dogs and handlers
received identical training at the same time.
Following their arrival in northern Arizona, dogs had a
week to acclimate to elevation and climatic conditions before
performing trials from mid-July through mid-August 2007.
During this acclimation period, we used preliminary trials in
which we introduced dogs to guano at known roosts of
individual bat species and our guano mixture and became
confident that dogs responded to both the mixture of guano
and to individual species. We also introduced dogs to novel
species not included in the guano mixture (e.g., Allen’s
lappet-browed bat [Idionycteris phyllotis]). Dogs proved
equally adept at identifying individual species and novel
species. Dogs and their handlers (dog–handler pairs)
remained the same throughout preliminary trials and the
formal study. When a handler was not working with a dog,
she served as the orienteer for the working dog–handler pair.
We used 2 approaches to test the ability of dogs in finding
bat roosts: 1) experimental trials with simulated bat roosts
(i.e., bags of guano); and 2) field tests to locate known bat
roosts (identified through radiotelemetry and exit counts)
that were currently or recently used (<1 month prior to field
tests) by bats. For experimental trials, we tested effects of
roost location (height above ground of a guano source) and
amount of guano on ability of dogs to locate roosts. We
mixed and measured guano, in 5-g or 20-g quantities, into
organza fabric bags (7.6 10.2 cm). We compared detection
of simulated high versus low roosts using guano bags placed
at 6 m and 2 m above ground, respectively. We hung bags
from natural branch stubs adjacent to the bole, using a pole to
reach the 6-m placements. Our large concentration of guano
(20 g) simulated a large bat colony; the 5-g small
concentration simulated a small colony. We used empty
fabric bags as controls (“null bags”) to test whether dogs used
human scent associated with hanging the bags as an incorrect
indicator of guano.
We used 26 natural roosts for 6 Allen’s lappet-browed bat,
8 Arizona myotis, and 12 long-legged myotis (Myotis evotis)
that were occupied during the summer of 2007 and identified
through radiotelemetry during concurrent studies (Johnson
2008, Solvesky and Chambers 2009). We randomly assigned
a 1-ha plot around each roost so the position of the roost
relative to plot boundaries differed for each plot to prevent
handler bias.
For the approaches described above, we used 4 tests
(Table 1). The first test (17–27 July) compared ability and
accuracy of a dog–handler pair in finding a 20-g guano
sample suspended 2 m above ground in a tree, a null bag (0 g
guano) as control, and known snag roosts. The second test
(30 July to 6 August) examined factors affecting the ability of
a dog–handler pair in finding a known snag roost for bats.
Because of the success of dogs in finding 20-g guano bags, we
decreased guano mass to 5 g for tests 3 and 4. This also better
simulated the small size of maternity colonies for roosts that
we used (xnumber of bats/roost was <20; Johnson 2008,
Solvesky and Chambers 2009). Thus our third test (7–13
August) compared ability of a dog–handler pair in finding a
5-g guano sample suspended 2 m above ground, a 5-g sample
suspended 6 m above ground, a null bag, and a known snag
roost used by bats. The fourth test (7–16 August) tested
accuracy of a dog–handler pair in finding 5-g guano samples
suspended at 2 heights (2 m or 6 m above ground).
For Tests 1 (n¼14) and 3 (n¼5), one dog–handler pair
searched in random order each of 3 1-ha plots containing
either a snag roost, guano bag, or null bag; and a trial
(sampling unit) was not complete until the dog–handler pair
searched all 3 plots. The orienteer randomly placed either a
guano or null bag in 2 of the 3 plots and the third plot
Chambers et al. Using Detection Dogs to Locate Bat Roosts 781
contained a snag roost whose position relative to the plot
boundary was unknown to the dog handler. We alternated
dog–handler pairs for each sequential trial. Average search
time per dog–handler pair per trial including rest breaks was
approximately 180 min.
Tests 2 (n¼36) and 4 (n¼16) involved only one 1-ha
plot/trial. We randomized which dog–handler pair started
the first search each day and then alternated dog–handler
pairs. Average search time per dog–handler pair was 40 min.
During all tests, we recorded temperature, humidity, and
wind speed to test effects of weather on the ability of each
dog to accurately locate roosts or guano samples.
For all tests, we selected a random start point at one of the
1-ha plot corners, then searched each plot by walking 5 100-m
transects spaced 20 m apart. Dogs were unleashed but directed
by their handler along fixed transect lines, and so were not
allowed to roam freely. The dog–handler pair focused on
searching with the handler closely observing the behavior of
the dog. The exposure of dogs to wind direction varied because
we used a random startlocation at one end of the 5 transectlines
and the direction of survey alternated between lines.
For tests 1, 3, and 4, dogs were correct if they indicated (sat
on their own, showing the handler that the dog had
concluded he found guano) 5 m from the known roost or
tree with the guano bag, and if they did not indicate a null
bag. Dogs were incorrect if they indicated >5 m from, or
failed to indicate, the known roost or tree with the guano
bag, or indicated on a null bag. For test 2, we compared poor
quality (imprecise and nondetections where the dog
indicated at >5 m or did not find the object) with high
quality detections (dog pinpointed or indicated at 5 m from
the snag roost).
We collected information to compare hypothetical costs of
locating roosts with a dog or with radiotelemetry over a
1-month period. We based costs on previous studies we
conducted. Published studies using telemetry typically identify
30 roosts to describe habitat use (e.g., Bernardos et al. 2004,
Solvesky and Chambers 2009, Poissant et al. 2010), so for the
purpose of our cost comparison, we budgeted acquisition of
telemetry equipment (i.e., receiver, antenna; Communication
Specialists, Inc., CA) and 30 transmitters (Holohil Systems
Ltd., ON, Canada) using prices from companies that we
commonly used. Some expenses were recurring (e.g.,leasing a
dog, buying transmitters); others were one-time costs (e.g.,
handheld Global Positioning System [GPS] unit, receiver).
For the telemetry approach, we assumed the need for 3
technicians to capture and radiotag bats at night and 1
technician to locate day roosts. For the dog approach, our
budget accounted for a technician and an orienteer. We
assumed one of the technicians for each survey approachwould
conduct exit counts with equal costs per approach. We
included a required, 3-week course to train one technician in
dog handling. We also includedlease, care, and maintenance of
a dog. We assumed similar on-site travel for both approaches
but included round-trip travel to a facility for training for the
dog-handler technician and round-trip transport of the dog to
the study site.
Statistical Analysis
To determine whether dogs were able to differentially detect
known roosts, 20-g guano samples, or null bags (test 1) and
accuracy of dogs in detecting 5-g guano samples at 2 heights
above ground (2 or 6 m; test 4), we used a comparison of
multiple proportions with all possible pairwise comparisons
(Goodman 1964, Fleiss et al. 2003). For test 2, we used
binary logistic regression to determine the best model(s) for
predicting correct identification of a known bat roost by dogs
(SAS 9.3; SAS Institute, Inc. 2002–2012). We hypothesized
that the probability of a dog–handler pair correctly detecting
a roost was influenced by weather and characteristics of the
roost itself. We tested effects of roost (height above ground
[m], number of bats [determined from an exit count at the
roost] and weather (wind speed [km/hr], relative humidity
[%], temperature [8C]). We included dog–handler pair in
models as a fixed effect but removed it if we detected no
difference between dog–handler pair. Because of small
sample sizes, we limited models to 3 variables and selected
P0.1 for the likelihood ratio chi-square statistic to test
significance of models. We used percent correct classification
(Percent Concordant) to compare accuracy of logistic
regression models. We assessed model fit using a Hosmer
and Lemeshow goodness-of-fit test (Hosmer and Lemeshow
2000). Sample size was small for test 3; therefore, we did not
statistically analyze data but instead presented descriptive
Because we found no differences between detection rates for
the 2 dogs (likelihood ratio chi-square ¼1.4, P¼0.2), we
combined trials across dogs. Dogs were more effective in
Table 1. Tests used to determine effectiveness of dog–handler pairs in locating known bat roosts (of variable ht above ground) and guano samples in
ponderosa pine forest, northern Arizona, USA, July–August 2007.
Test Objective N
No. of 1-ha
xtrial length
(min) Ht (m) 0g 5 g 20 g Roost
1 Ability to detect bat roosts and guano 14 3 180 2 X X X
2 Factors affecting ability to find bat roost 36 1 40 Varied X
3 Ability to detect roosts and guano at 2 ht 5 3 180 2, 6 X X X
4 Accuracy in detecting guano at 2 ht 16 1 40 2, 6 X
X indicates guano sample was used in the test, — indicates sample was not used.
782 Wildlife Society Bulletin 39(4)
detecting known bat roosts when dog–handler pairs alternated
searching a single 1-ha plot (test 2: 66% of roosts found within
5 m, 80% within 30m) than when they consecutively searched
3 1-ha plots (test 1: 29% of roosts found).
Test 1: Snag Roost, Guano Bag, or Null Bag
We completed 14 trials (7/dog). Dog–handler pairs correctly
avoided null bags 100% of the time, indicating that dogs were
not using human scent left during placement as a surrogate
for guano. Detection success rates were 79% for 20-g guano
bags and 29% for snag roosts (x
¼17.6, P<0.001; Table 2).
For 5 of the 10 incorrect detections for snag roosts, we noted
that dogs changed behavior or indicated a roost at a distance
>5 m. For the remaining 5 roosts we observed no change of
behavior for dogs.
Test 2: Factors Affecting Snag Roost Detection
Each dog–handler pair completed 17 or 19 trials (n¼36) for a
range of bat roost population sizes, heights, and weather
conditions (Table 3). High-quality detections (with the dog
pinpointing or within 5 m of a known roost) accounted for 64%
of trials. Imprecise detections included dogs identifying a roost
>5–20 m away (14%) or missing roosts entirely (22%). Roost
characteristics (number of bats that occupied the roost, height
of the roost) and roost characteristics in combination with
weather variables accurately predicted the ability of a dog to
locate a roost (Table 4). Wind speed, although statistically
significant, was too inaccurate by itself in predicting a true
positive response (P¼0.05, % correct classification ¼62.1).
The other weather variables (relative humidity, temperature)
did not contribute significant explanatory power in single-
variable models (P>0.2, % correct classification 64.8). All
weather variables were effective in increasing accuracy of
models when combinedwith roost height but onlywind speed
was effective with number of bats occupying a roost.
Combinations of temperature or relative humidity with
number of bats occupying a roost failed the Hosmer and
Lemeshow goodness-of-fit test (P<0.02). All reported
models (Table 4) met the Hosmer and Lemeshow good-
ness-of-fit test (P>0.05).
Models predicted strong, correct responses by dogs. The
model with greatest explanatory power was a 2-variable model
that included roost height and temperature. Dogs detected
roosts closer to the ground or with larger numbers of bats
(Fig. 1). Dogs also were more likely to detect roosts that were
close to the ground when temperatures were warmer(Table 4).
Tests 3 and 4: Amount of Guano and Height of Bag
Dogs were more accurate at detecting a smaller sample (5 g)
of guano when it was closer to ground level. They were
correct in finding guano samples placed 2 m high 60% of the
time but found guano samples placed 6 m high only 20% of
the time. They correctly detected a roost 60% of the time
(Fig. 2). In test 4, dogs were again more likely to find guano
when it was closer to the ground. Dogs correctly identified
69% (11 of 16) guano samples at 2 m but only 40% of guano
samples (6 of 15) at 6 m above ground (P¼0.06).
Other Identifications
On 35 occasions during our project, dogs gave an alert signal to
indicate the presence of guano at a site that was unknown to us
as a roost. Sites included 27 snags, 5 scats, 2 live trees, and 1 log
that could be false positives, previously used sites, or current
roosts. We suspect that 5 were misidentifications because dogs
alerted on scat of bobcat or coyote (Canis latrans) and we could
not visually confirm the remains of a bat in the scat.
Cost Comparison—Dogs and Telemetry
Costs for the dog approach were 7% greater than use of
radiotelemetry (Table 5) for a 1-month hypothetical
sampling period. Personnel costs were greater for use of a
dog (83% of costs) than telemetry (44%); however, telemetry
required greater expenditures in supplies and equipment
(56%) than use of a dog (2%). Travel accounted for 15% of
costs associated with the dog approach. Both methods
included initial, one-time project costs (e.g., handheld GPS
unit, telemetry equipment, training in dog handling if the
same handler is used) but other costs would recur (e.g.,
Table 3. Means, standard error, and ranges for variables included in
models predicting the probability of a dog–handler pair finding a known
tree or snag roost for bats in ponderosa pine forests, northern Arizona,
USA, July–August 2007.
Variable nxSE Range
Roost ht (m) 17 11.0 1.7 1.5–30.0
Bat count (no. of bats exiting roost) 18 10.4 2.6 1–39
Temp (8C) 34 21.0 0.5 14.3–26.1
Wind speed (km/hr) 34 1.6 0.3 0–5.8
Relative humidity (%) 34 69.0 2.3 42–96
Table 2. Accuracy of the dog–handler pairs in locating (within 3, 1-ha plots) a 20-g guano sample suspended 2 m above ground in a tree, a null bag (no
guano), and a known snag roost in northern Arizona, USA, July 2007. Different letters indicate significant differences in detection among samples (x
P0.009), the same letter indicates no detectable difference among samples (x
¼3.8, P¼0.2).
Response of dogs
Sample Correct
Percent correct Pairwise comparison
Guano 11 3 78.6 B
Null 14 0 100.0 B
Roost 4 10 28.6 A
Correct responses for Guano or Roost—The dog indicated on, or was 5m from, the tree or snag with guano bag or roost. Correct response for Null—The
dog ignored the bag with no guano.
Incorrect responses for Guano or Roost—Either the dog did not indicate, indicated on an incorrect location >5 m from tree or snag with the guano bag or
roost, or had a moderate to strong change of behavior but did not indicate a find. Incorrect responses for Null—Dog indicated on the bag with no guano (this
never occurred).
Chambers et al. Using Detection Dogs to Locate Bat Roosts 783
personnel, expenses for the dog, transmitters, airfare).
Recurring costs for the dog approach were lower (59% of
total expenses) compared with telemetry (93%). Cost for
using a dog could be reduced if the dog handler also served as
the orienteer (e.g., from US$14,650 to US$12,250).
Although dogs have proven to be an effective tool for locating
live animals, carcasses, and scats of many species (Dahlgren
et al. 2012), our studyindicated that dogs were less effective at
locating bat roosts in snags, most likely because of the arboreal
location of the search object. When dogs are trained to locate
terrestrial species, the dog can provide an alert signal on the
targeted animal, carcass, or scat because the object is literally
under its nose (Wasser et al. 2004, Harrison 2006, DeMatteo
et al. 2009, Dahlgren et al. 2012). In contrast, a snag roost does
not provide a definitive terrestrial spot for the dog to indicate a
find, unless there is guano below the roost. Werarely observed
guano below roosts, possibly because it was rapidly removed by
ants (Family Formicidae) and other insects. Height of snag
roosts increases the likelihood that guano scent will be carried
by the wind, which could confound the ability of the dog to
indicate the precise location of the scent. Dogs were most
successful at finding largeroosts and those closer to the ground.
Given that dogs showed a greater ability to detect guano
that was near the ground or in greater quantities, the species
of bat also may influence ability of dogs to detect roosts.
Larger bodied bats that roost closer to the ground (e.g.,
Allen’s lappet-browed bat, 12-g mass, with roosts typically
10 m above ground; Solvesky and Chambers 2009) or species
that aggregate in large colonies (e.g., Arizona myotis, Rabe
Table 4. Parameter estimates (b), standard errors (SE), and odds ratios (Exp(b)) for variables used in logistic regression models to predict probability of a
dog–handler pair finding a known tree or snag roost for bats in ponderosa pine forests, northern Arizona, USA, July–August 2007. Variables in models
included characteristics related to bats (bat count, ht of the roost) or weather (wind speed). The likelihood ratio tested significance of models, and the
c-statistic (area under the receiver operating characteristic curve) indicates a model’s ability to differentiate between outcome categories and the probability of
predicting a true positive response.
Likelihood ratio
Model n
bSE Exp(b)x
P% concordant
Single-variable models
Bat count (no. exiting) 28 0.155 0.086 1.167 5.686 0.02 71.3
Roost ht (m) 24 0.153 0.087 0.858 3.834 0.05 77.8
Two-variable models
Bat count, wind speed 26 7.168 0.03 83.5
Bat count 0.141 0.098 1.152
Wind speed (km/hr) 0.543 0.432 1.721
Roost ht, humidity 22 7.044 0.03 89.4
Roost ht 0.228 0.117 0.796
Relative humidity (%) 0.092 0.062 0.912
Roost ht, temp 22 6.623 0.04 92.9
Roost ht 0.241 0.123 0.786
Temp (8C) 0.377 0.257 1.458
Roost ht, wind speed 22 5.770 0.06 91.8
Roost ht 0.138 0.096 0.870
Wind speed (km/hr) 0.613 0.577 1.847
Sample size for characteristics related to bats varied because exit counts, ht of roost, or wind speed were unknown for some roosts.
Figure 1. Predicted probability of detection by a dog–handler pair for roost
height and number of bats occupying a roost in ponderosa pine forest,
northern Arizona, USA, July–August 2007.
Figure 2. Results of test 3 showing the percent correct (at or 5 m from
search object) or incorrect (no find, dog uncertain, or >5 m from object)
searches for dog–handler pairs in a ponderosa pine forest, northern Arizona,
USA, August 2007. Dogs searched 3 consecutive 1-ha plots: 1) null bag with
0 g of guano (Null); 2) known snag roost (Roost); and 3) a 5-g guano bag
hung 2 m above ground (Guano2M) and a 5-g guano bag hung 6 m above
ground (Guano6M).
784 Wildlife Society Bulletin 39(4)
et al. 1998; C. Chambers, unpublished data) produce more
scent and thus should be easier to detect by dogs.
The live trees and log where dogs indicated the presence of
guano scent could represent misidentifications (i.e., false
positives), although male bats will roost in branch stubs
protruding from downed logs (Bernardos 2001) and tree-
roosting bats such as hoary and silver-haired bats (Lasiurus
cinereus and Lasionycteris noctivagans, respectively) that are
commonly captured in our study area use live trees. Most
snags identified by dogs appeared likely to be roost habitat
because they were large ponderosa pines (xdiameter ¼66
cm, xheight ¼16 m; e.g., Rabe et al. 1998, Bernardos et al.
2004, Solvesky and Chambers 2009). We confirmed 8 as
current roosts because of the presence of guano or bats, but
we were unable to confirm roost status for other snags (e.g.,
no visual or sound of bats). Bats switch roosts frequently
(e.g., every 7–14 days; Bernardos et al. 2004, Solvesky and
Chambers 2009), and may use roosts only during part of a
season or every few years. This can allow buildup of scent of
guano that is detectable to a dog although bats are not
present. The problem of unconfirmed roost sites is unlikely
to be resolved easily. However this could be an advantage
because dogs can locate roost sites that have been used in
the recent past and have high potential for reuse even though
the roost might be currently unoccupied.
Weather conditions affect scent detection (Shivik 2002,
Cablk et al. 2008, Reed et al. 2011); however, dogs have been
used successfullyin a variety of environments including tropical
moist forest (DeMatteo et al. 2009), temperate forest (Long
et al. 2007b), and desert (Cablk et al. 2008). In general, warmer
temperatures can release scent, concentrating it at the source
and thus making it stronger and easier for dogs to detect
(Shivik 2002, Cablk et al. 2008, Reed et al. 2011). Our work
was conducted in the American Southwest during monsoon
season, when relative humidity was high compared with dry
seasons. We had better success when temperatures were
warmer, humidity was lower, and light breezes prevailed.
Moister and windier conditions can broadly disperse scent at a
source too high or far away for dogs to detect or detect
accurately (Shivik 2002, Cablk et al. 2008, Reed et al. 2011);
therefore, the optimal conditions in our study likely distributed
scent lower in the canopy near the roost.
The cost of using dogs was not prohibitive, and as with any
method, had advantages and tradeoffs (Table 6). We found
that using a dog was similar in cost to radiotelemetry, could
allow land managers or researchers to concentrate a search in
a focal area, and was noninvasive and independent of the
need to capture and radiotag bats, which is an activity that
can be difficult in some environments and particularly for
uncommon species.
Table 5. Comparison of cost for domestic (U.S.) use of dogs and radiotelemetry to locate 30 bat roosts during a 1-month period, during trials conducted at 2
sites on the Coconino National Forest in northern Arizona, USA, during July and August of 2007.
Technique cost
Category (cost US$) Dogs Telemetry
Telemetry technician ($120/day, 20 days/month, 1 month) $2,400
Mist-netting technicians (3 @ $120/day, 10 days/month, 1 month) $3,600
Dog handler ($15/hr, 40 hr/week, 1 month) $2,400
Orienteer ($15/hr, 40 hr/week, 1 month)
Training in dog handling (3 weeks)
Dog lease ($2,000/month) $2,000
Dog transport and equipment ($250/month) $250
Dog food ($60/month) $60
Dog health certificate ($100/flight for 2 flights) $200
Insurance for dog lease (15% of lease) $300
Equipment and supplies
Transmitters (30 at $180 each, Holohil Systems Ltd.) $5,400
Mist nets (4 18-m nets at $139.75 each, 2 12-m nets @ $110.25 each)
Mist-netting equipment (poles, stakes, ropes, lights)
Garmin GPSMAP 62St Handheld GPS Navigator
$340 $340
R-1000 Telemetry Receiver
Yagi type directional antenna
Nondirectional magnetic mount antenna
Dog cargo airfare
Dog transport to/from airports ($25/trip) $50
Dog handler room and board during training ($250/week) $750
Dog handler airfare to or from Seattle
Total costs $14,650 $13,664
With handler only (no orienteer), cost for dog approach would be $12,250.
Assumed one-time cost (nonrecurring).
Assumed cost is $500/flight for 2 trips to and from the study site.
Estimated cost for airplane ticket purchased 6 months in advance to and from central United States (Chicago) and Seattle, WA, for 2 weeks training at
PackLeader Dog Training facility.
Chambers et al. Using Detection Dogs to Locate Bat Roosts 785
Changing some cost assumptions could increase the cost of
telemetry over the use of dogs. We assumed a minimum
number of 30 transmitters to locate 30 roosts, which may be
underestimated depending on the study area and goals. We
assumed one-time costs for some equipment (e.g., receiver,
antenna); other equipment (e.g., mist nets) might need
replacement every 2–4 years. With dog surveys, the costs of
airfare, retraining for the dog handler (required when leasing
a dog after a hiatus in use), or hiring a professional handler
could all be much higher for certain survey locations. These
costs, however, could be avoided if the dog belongs to the
handler rather than a leasing service. Arnett (2006) provides
an example of a personally owned dog successfully trained to
detect scent.
Regardless of cost, land managers and researchers are
interested in the success rate of different survey methods
relative to sampling effort (e.g., Long et al. 2007a). A
comparison of success rates between radiotelemetry and dog
surveys in locating snag roosts is difficult, however, because
of high variability in environmental conditions that affect
survey outcomes for each method. With radiotelemetry,
success rate can approach 100%, and telemetry can provide
the ability to double the number of known roosts if bats
change roosts while radiotagged (e.g., Bernardos et al. 2004,
Solvesky and Chambers 2009). In our trials with dogs,
success rate varied with height of roosts and to a lesser extent,
weather conditions, and we predict that sampling effort
could also vary widely if dogs frequently indicate roosts that
are not active but require additional survey time, such as an
evening exit count, to verify.
Whereas radiotelemetry is useful in all forest types, dogs are
likely to be most effective in short-statured woodlands such
as pinyon pine and perhaps certain hardwood forests,
although their usefulness in forests of moderate height (e.g.,
ponderosa pine and mixed conifer) should not be out ruled.
Taller roosts, however, increase the likelihood that dogs will
provide inaccurate alert signals or completely miss the roost.
Additionally, dogs are more likely to locate large bat colonies
than small ones.
Our data indicate that the costs of dogs and telemetry are
similar; therefore, the choice of method will depend on the
specific research question or management objective (Table 6).
Dogs can increase the sample of known bat roosts because
many species of bats use the same roosts repeatedly over
multiple years (e.g., Solvesky and Chambers 2009) and
guano can accumulate and make roost locations easier to
detect. Dogs can be trained to differentiate between species
(e.g., Harrison 2006, DeMatteo et al. 2009) and thus could
search for species that are uncommon, rare, or listed as
threatened or endangered, unless the species roosts too high
for scent detection. Prior to using dogs for any targeted
species, we recommend 2 weeks of preliminary trials and
training, to ensure that dogs can differentiate the scent of the
target species from other bats in the survey area.
Dogs could be useful for other arboreal and patchily
distributed species as well. Hagell (2010) experimented with
using a dog to locate an arboreal and locally rare primate (the
Central American spider monkey [Ateles geoffroyi]) and
found the dog method produced a sample yield of monkey
detections similar to that of human searchers during a
2-week pilot project. However, the dog identified 7 samples
not detected by the human team. Additional training time
and field preparation beyond 2 weeks could have improved
performance of the dog. A minimum 2-week training period
is recommended when using dogs to acclimate them to a new
environment and to the local diet of the study organism.
Locating arboreal targets may require increased awareness of
scent movement, as might subterranean scent targets
(Reindl-Thompson et al. 2006).
Dogs can play a role in promoting awareness and
conservation of snag-roosting bats. At least 16 the 45
species of bats in Canada and the United States roost in
cavities or under bark (Barclay and Kurta 2007). If bat roosts
could be located in an area prior to forest management
activities (e.g., thinning or prescribed burning) or land use
changes (e.g., housing developments or ski area expansions),
managers could either protect existing roosts or provide
surrogate roosts as part of the mitigation strategy for the
planned activity (Mering and Chambers 2014). Although
dogs are not able to precisely locate all snag roosts, we found
they are generally within 30 m of the roost site, thereby
providing a targeted area for more concentrated searches or
immediate protection.
When managers have the latitude to retain all snags in a
management area that meet roost characteristics, neither
dogs nor telemetry will be needed. Under those circum-
stances, managers should identify roost characteristics from
the literature and set standards for retaining trees and snags
Table 6. Ability of dogs and radiotelemetry methods to meet different aspects of the overall objective of locating snag roosts of bats in a targeted area during
trials conducted the study at 2 sites on the Coconino National Forest in northern Arizona, USA, during July and August of 2007.
Aspects of objective Dogs Telemetry
No. of bat species Can simultaneously search for roosts of multiple species or be
trained to search for roosts of one species
In general, can only locate roosts for the species that is
Type of roost Can focus entire effort on snags Unfocused; includes all roost structures
Spatial extent All roosts will be within a targeted area Roosts could be outside of the targeted area
Temporal extent Can locate previous, reusable roosts in addition to current
Can only locate currently used roosts
Degree of accuracy Might be 30m from the actual roost Can identify exact location of roost (assuming roosts are
Verification of roost Requires follow-up exit survey to determine if roost is still in
Requires follow-up exit survey to determine ht of roost and
population size
786 Wildlife Society Bulletin 39(4)
that meet those characteristics. If only a subset of potential
roost sites can be retained in an area because of salvage
logging, hazard tree reduction, or other management
activities, dogs could be useful in identifying trees and
snags with the highest likelihood of current use. They could
also be used for postmanagement monitoring, to verify that
bats are indeed using retained structures as roost sites. In
comparison to radiotelemetry, dogs offer a less invasive
approach at a comparable price, which can be particularly
beneficial when locating roosts of species that are imperiled
or of conservation concern.
We thank the U.S. Department of Agriculture Forest Service
and U.S. Department of Interior National Park Service for
funding. A. Chung-MacCoubrey provided impetus for the
project. We thank R. King (U.S. Forest Service) and Roy St.
Laurent (Northern Arizona University) for statistical
consulting help. Associate Editor Arnett and 3 anonymous
reviewers provided comments that greatly improved the
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Chambers et al. Using Detection Dogs to Locate Bat Roosts 787
... In general, the use of dogs in nature conservation offers many advantages. For example, it can facilitate the location of target species in unreachable habitats (Chambers et al. 2015, Hoyer-Tomiczek et al. 2016, thus decreasing the risk of disturbance and performing non-destructive sampling (Chambers et al. 2015), with particular reference to saproxylic species with larvae living inside hollow trees (Hoyer-Tomiczek et al. 2016). Moreover, the use of dogs minimises the sampling effort, in terms of number of personnel involved in fieldwork and time spent in the field (Browne et al. 2006, Harrison 2006, Duggan et al. 2011, Paula et al. 2011) and reduces the bias in sampling (Wasser et al. 2004, Browne et al. 2006). ...
... In general, the use of dogs in nature conservation offers many advantages. For example, it can facilitate the location of target species in unreachable habitats (Chambers et al. 2015, Hoyer-Tomiczek et al. 2016, thus decreasing the risk of disturbance and performing non-destructive sampling (Chambers et al. 2015), with particular reference to saproxylic species with larvae living inside hollow trees (Hoyer-Tomiczek et al. 2016). Moreover, the use of dogs minimises the sampling effort, in terms of number of personnel involved in fieldwork and time spent in the field (Browne et al. 2006, Harrison 2006, Duggan et al. 2011, Paula et al. 2011) and reduces the bias in sampling (Wasser et al. 2004, Browne et al. 2006). ...
... This effect can be increased by the wind that can carry the target odour away from the source. Chambers et al. (2015) and Hoyer-Tomicek et al (2016) also reported that the scent of species living in trees was transported by wind. These two variables (high concentration of target odour and wind) can confound the results and lead to signalling of trees which do not contain the target, but which are close to trees with larvae of O. eremita. ...
Full-text available
One aim of the MIPP Project ( was to develop non-invasive monitoring methods for selected saproxylic beetles. In this paper, a method is proposed for monitoring the larvae of Osmoderma eremita in their natural habitat (i.e. hollow trees), using a conservation detection dog (CDD). Wood mould sampling (WMS), the standard method to detect hermit beetles and other saproxylic insects inside tree hollows, is time-consuming and exposes the target species and the whole saproxylic communities to some risks. In contrast, CDDs pose no risk to the species living inside trees while, at the same time, offer a powerful tool for surveying the insects. In this paper, the methods applied to train the dog are presented, together with the results for accuracy (the overall proportion of correct indications), sensitivity (the proportion of correct positive indications) and specifcity (the proportion of correct negative indications) obtained once the CDD had been fully trained. Results are presented for nitrocellulose flters with the odour of the target species, for larvae living inside hollow trees, for frass and for the remains of adults. A comparison of the efciency between CDD and WMS showed that employing the dog was much less time-consuming than WMS. Te literature on training CDDs for nature conservation tasks, with particular reference to cases involving Coleoptera, was also reviewed.
... since the 1890s when they were used to locate kiwi (Apteryx spp.) and kakapo (Strigops habroptilus) (Browne, Stafford, and Fordham, 2005). Dogs have been recognised for their ability to outperform human surveyors in locating and distinguishing between cryptic terrestrial species, especially in circumstances where visual searches are limited, for example in dense vegetation (Cablk & Heaton, 2006;Long et al., 2007;Savidge et al., 2011;Chambers et al., 2015). Some research has examined dogs' abilities to detect New Zealand's protected and invasive species. ...
... The ability of dogs to detect a novel scent must be examined robustly so that results cannot be contested. (Rebmann, David & Sorg, 2000;Sargisson et al., 2010;Savidge et al., 2011;Chambers et al., 2015). In general, warmer temperatures can release volatile organic compounds, concentrating them at the source and thus making it stronger and easier for dogs to detect; moister and windier conditions can broadly disperse scent at a source too high or far away for dogs to detect or detect accurately (Shivik, 2002;Cablk & Heaton, 2006;Reed et al., 2011). ...
... Increased evaporation enhances scenting conditions, and evaporation can be greater when air is dry, water temperature is high, salinity is high, air pressure is low, the surface area is great and there is increased wind velocity (Rebmann, David & Sorg, 2000;Sargisson et al., 2010;Savidge et al., 2011;Chambers et al., 2015). With the use of an automated apparatus in the current study, some of these factors could be controlled for. ...
Full-text available
Invasive species now dominate many aquatic landscapes in most parts of the world, displacing native plants and animals by disrupting and altering ecosystems. The brown bullhead catfish (Ameiurus nebulosus) has been significantly correlated with regime shifts from macrophyte‐dominated clear water states to de‐vegetated turbid states, population declines of endemic species, and the disruption of food webs in New Zealand lakes. Conventional detection methods (e.g., visual surveys, fyke netting, electrofishing, and eDNA) for catfish are limited by their cost, invasiveness, time- consumption, and potential to be prone to error. Given that scent detection dogs are a well-established tool across a variety of fields, it was hypothesised that domestic dogs (Canis familiaris) may be able to detect the presence of catfish from water samples that have contained these fish. This could provide a new potential biosecurity monitoring tool. In this study, five pet dogs were trained to operate an automated apparatus that presented water samples for evaluation. Water samples were presented to dogs from aquaria that had previously contained, catfish, goldfish (Carassius auratus), or no fish. Experiment 1 evaluated if dogs could discriminate between samples that had contained catfish or no fish. In Experiment 2, it was evaluated if dogs can discriminate between fish species (i.e., catfish and goldfish), and at what fish biomass concentrations they can do so. Experiment 3 evaluated if dogs could indicate the presence of catfish when samples were presented at two different biomass concentrations in the same session. It was found that dogs were able to correctly identify water that had contained catfish and largely reject water samples that had contained either no fish or goldfish at above 80% accuracy at biomasses equivalent to environmental biomasses of 4.6 x 1,000 kg/ha. Preliminarily investigations of lower detection limit thresholds were investigated in the study. These results suggest further investigation is warranted to confirm the dogs’ ability to detect catfish at biologically relevant concentrations comparable to real-world sample scenarios. However, these findings support the suggestion that dogs may have an important role to play in waterway conservation and management.
... Compared with high-frequency bat calls, chemical cues can potentially travel farther distances, especially in cluttered forests, and they remain over time [14]. Predators and dogs can use guano and urine cues to locate bat roosts [15][16][17]. In at least one bat species (Hipposideros speoris), males appeared to use urine to relocate roosting spots and establish territory boundaries within a cave [18]. ...
... Second, these species live within communal roosts that are often stained with guano and urine. Desmodus rotundus, in particular, often live in roosts that are uniquely odorous because their diet of blood leads to copious urine and tar-like guano such that their pungent roosts can be detected at a distance by dogs or humans [15,16]. All three species will also roost in anthropogenic structures, showing some plasticity in their roost choices. ...
Full-text available
Many animals use social cues to find refuges. Bats can find roosts using the echolocation and social calls of conspecifics, but they might also use scent cues, a possibility which is less studied. The entrances of bat roosts are often marked by guano and urine, providing possible scent cues. We conducted eight experiments to test whether bats use the scent of guano and urine to find potential roosts. In field experiments, we tested if Molossus molossus (velvety free-tailed bats) in Panama and Eptesicus fuscus (big brown bats) in Ohio would investigate artificial roost boxes that were scented with guano and urine more often than a paired unscented control. We did not detect any difference in flights near the scented versus unscented roosts, and we detected only one entrance into any artificial roost (scented). In six captive experiments, we tested for the attraction of Desmodus rotundus (common vampire bats) and Molossus molossus to areas scented with guano and urine, under several conditions. Results were mixed, but overall suggested that the scent of guano and urine does not act as a strong lure for the tested bat species. We suggest that further tests of olfaction-based roost choice in bats should manipulate existing scent cues on familiar roosts.
... This ten-year period is marked by an explosion of canine detection research resulting in a growing list of detectable human diseases by BMDDs and BMDDs able to detect virus [bovine viral diarrhea virus (10)], bacteria [C. difficile (7), Escherichia coli, Klebsiella pneumoniae, Enterococcus faecalis, and Staphylococcus aureus (9)], pests (brown tree snakes (22), palm weevils (23), gypsy moths (24), longhorn beetles (25), termites (26), bed bugs (27), and quagga and zebra mussels (28), fouling agents [catfight offflavoring compounds (29), microbial growth in buildings (30)], animals important to conservation efforts [grizzly and black bears (31), brown bears (32), geckos and tuataras (33), tortoises (34), quolls (35), jackals (36), giant bullfrogs (37), wolves (38), rabbits (39), rock ptarmigans (40), bats (41), koalas (42), kit foxes (43), tigers (44), cougars (45), cheetahs (46), bobcats (47), and gorillas (48)], and disease odor directly on humans [Parkinson's (49), epilepsy (50), diabetes (16,51)]. ...
Full-text available
Biomedical detection dogs offer incredible advantages during disease outbreaks that are presently unmatched by current technologies, however, dogs still face hurdles of implementation due to lack of inter-governmental cooperation and acceptance by the public health community. Here, we refine the definition of a biomedical detection dog, discuss the potential applications, capabilities, and limitations of biomedical detection dogs in disease outbreak scenarios, and the safety measures that must be considered before and during deployment. Finally, we provide recommendations on how to address and overcome the barriers to acceptance of biomedical detection dogs through a dedicated research and development investment in olfactory sciences.
... Despite the extensive scientific literature on the improvement and optimization of bat surveys (e.g. Flaquer, Torre & Arrizabalaga, 2007;Skalak, Sherwin & Brigham, 2012;Stahlschmidt & Bruhl, 2012;Froidevaux et al., 2014;Law et al., 2015;Froidevaux, Fialas & Jones, 2018;Richardson et al., 2019), specific recommendations regarding roost surveys are scarce (Fleming et al., 2013;Chambers et al., 2015) and mostly restricted to the estimation of colony size (Kloepper et al., 2016). ...
Full-text available
The disturbance, damage and destruction of roosts are key drivers of bat population declines worldwide. In countries where bats are protected by law, bat roost surveys are often required to inform ecological impact assessments. Yet, evidence-based information on survey methodology to detect bat roosts is crucially lacking, and failing to detect a roost can lead to serious errors during decision-making processes. Here, we assess the efficacy of bat roost surveys in buildings as implemented in the UK. These consist of a daytime inspection of buildings, followed by a series of acoustic surveys at dusk/dawn if during the daytime inspection evidence of bats is found, or if the absence of bats cannot be verified. We reviewed 155 ecological consultants' reports to (1) compare survey outcome between daytime inspection and acoustic surveys and (2) determine the minimum sampling effort required during acoustic surveys to be confident that no bats are roosting within a building. We focused on two genera of bats most frequently found in buildings in Europe-Pipistrellus (crevice roosting species with high-intensity echolocation calls that can be easily detected by ultrasound detectors) and Plecotus (species that roost in open spaces and which emit faint echolocation calls that are difficult to detect). Daytime inspections were efficient in detecting open-roosting species such as Plecotus species but were likely to miss the presence of crevice-dwelling ones (here Pipistrellus species) which may lead to erroneous conclusions if no acoustic surveys are subsequently prescribed to confirm their absence. A minimum of three and four acoustic surveys are required to be 95% confident that a building does not host a roost of Pipistrellus species and Plecotus species, respectively, thus exceeding current recommendations. Overall, we demonstrated that reports submitted as part of an ecological impact assessment provide suitable data to test and improve survey methods.
... The detection dog surveys, however, were completed in half the time and only required one site visit, whilst live-trapping required multiple (Duggan et al. 2011). Detection dog surveys for bat roosts were also reported to have similar costs to radiotelemetry, however, for the dog surveys the bats didn't require trapping or radio-tagging (Chambers et al. 2015). Similarly, detection dogs were also reported to have comparable costs to camera-trapping (3-week deployment of 80 cameras) when surveying nine search cells for feral cats (Camera-trapping = $5,100, detection dogs = $4,820; Glen et al. 2016). ...
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Detection dog success is dependent on the selected individuals. Thus, to investigate factors important to dog and handler selection, I trained 12 dogs from three breeds at detection work, experimentally assessing their training times and odour discrimination ability. My research determined there are multiple traits that create a successful dog-handler team, which are not specific to a certain breed or personality type. The dog-handler relationship was also significant in impacting team success and welfare. It is therefore crucial to continue challenging and advancing best practises, not only for animal welfare but also for the success of the working dog industry.
... Providing itemization and the rates used to calculate estimates is particularly useful when considering the global variation in prices for wages, equipment, and dog handlers. Only 4 studies reported all of the performance measures, costs, and comparison with alternative field methods (Reindl-Thompson et al. 2006;Duggan et al. 2011;Chambers et al. 2015;Clare et al. 2015). ...
Detecting rare species is important for both threatened species management and invasive species eradication programs. Conservation scent dogs provide an olfactory survey tool that has advantages over traditional visual and auditory survey techniques for some cryptic species. From the literature, we identified 5 measures important in evaluating the use of scent dogs: precision, sensitivity, effort, cost, and comparison with other techniques. We explored the scale at which performance is evaluated and examined when field testing under real working conditions is achievable. We also identified cost differences among studies. We examined 61 studies published in 1976-2018 that reported conservation dog performance, and considered the inconsistencies in the reporting of scent dog performance among these studies. The majority of studies reported some measure of performance; however, only 8 studies reported all 3 aspects necessary for performance evaluation: precision, sensitivity, and effort. Although effort was considered in 43 studies, inconsistent methods and incomplete reporting prevented meaningful evaluation of performance and comparison among studies. Differences in cost between similar studies were influenced by geographical location and how the dog and handler were sourced for the study. To develop consistent reporting for evaluation, we recommend adoption of sensitivity, precision, and effort as standard performance measures. We recommend reporting effort as the total area and total time spent searching and reporting sensitivity and precision as proportions of the sample size. Additionally, reporting of costs, survey objectives, dog training and experience, type of detection task, and human influences will provide better opportunities for comparison within and among studies. © 2019 Society for Conservation Biology.
... Hawkweed Hieracium ( Goodwin et al. 2010), 3) non-invasive surveys of fauna including scats [e.g. Javan rhinoceros Rhinoceros sondaicus annamiticus in Vietnam (Brook et al. 2012), Cross River gorilla Gorilla gorilla diehli in Cameroon ( Arandjelovic et al. 2015), bat guano in the USA ( Chambers et al. 2015)], urine and latrines Smith 2004, Kauhala andSalonen 2012) (Rolland et al. 2007)]. Detection dogs have also even been trained to recognise animals based on their identity [recognition of 25 known individual tigers Panthera tigris altaica (Kerley and Salkina 2007), see also Wasser et al. (2009)]. ...
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In conservation, consistent and extensive under-funding has necessitated creative thinking to address conservation issues on a low budget, and innovations are burgeoning as a result. One example is the use of dogs that, thanks to their heightened olfactory abilities and bond with humans, are trained to detect odours of interest to conservationists. Conservation dogs have proven to repeatedly outperform alternative survey methods in terms of accuracy, efficiency and/or cost. They have now been used for the detection of endangered and invasive species, fauna and flora, direct and indirect (e.g. scat) targets, on land and at sea, across every continent and most taxa from fire ants to whales. Here, we emphasise the versatility of detection dogs through their multiple uses applied to one species, the koala Phascolarctos cinereus . We selected, trained, tested and deployed five dogs; two for koala habitat (koala scats), one for genetic sampling (fresh scats only), one for the koala itself and one for koala disease ( Chlamydia spp. ) detection. Dogs enabled both large-scale and fine-scale survey design, with 2370 surveys performed, and 1479 genetic samples collected to date. Detection dogs are subject to similar (although sometimes much lower) limitations in terms of survey biases (e.g. individual or environmental conditions) and, importantly, detection dog/handler teams need to be tested regularly for accuracy. Nonetheless, detection dogs can, and are, helping researchers and land managers to collect more robust datasets and better inform conservation decisions. Alliances with unexpected partners in conservation (such as with police forces), citizen science, and timeshare use of dogs might improve the democratisation of their use and enable conservation detection dogs to fulfil their astonishing potential.
... The lack of a standardized and publicly available assessment tool for CDDs, along with a widespread failure in available literature to report on specific selection processes, is a significant omission, particularly given that several studies show that CDD performance may be impacted by many factors. For example, environmental terrain/vegetation density (16), specific search target (42), and whether the target is terrestrial, arboreal, or marine (32,39), all impact CDD effectiveness. Experience of the CDD team (40), handler characteristics (46), and the individuality of the dog selected (1,20) are also important factors in CDD success. ...
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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.
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A unique possibility for optimizing wildlife detection methods Feathers, hair and scat give us information about our wildlife. Using detection dogs could help find those kinds of evidence even better than conventional methods. A pilot study conducted by the Forest Research Institute of Baden-Württemberg (FVA) from 2018 to 2019 showed applications using dogs and the framework needed to apply this method. This has resulted in key fields of action for the use of detection dogs in wildlife research and in the long-term monitoring of target species according to the hunting and wildlife management law (JWMG) in Baden-Württemberg, Germany. The FVA already has several years of experience using detection dogs in research projects and monitoring tasks for wolf, lynx and capercaillie. In one research project, the reproduction success of grouse was systematically recorded over several years with the help of detection dogs. Moreover, a detection dog is regularly used in lynx and wolf monitoring to help search for evidence of their presence. Follow-up projects at the FVA benefit from this growing expertise: In a new pine marten project, common detection methods are being compared to the use of detection dogs – in this way the most effective method for evaluating pine marten density can be determined. There is also great potential for using detection dogs in forest conservation and forest protection, for example in detecting bats, amphibians, reptiles or various forest pests and invasive species. However, wherever detection dogs are used the potential of disturbance of wildlife, added value and comparison with existing methods need to be considered. According to project participants, a prerequisite for successfully establishing the sniffer dog method is the appropriate qualification of the human-dog teams. The required quality standards for suitability, professional training and certification are currently being developed by the non-profit association, Wildlife Detection Dogs e.V. In addition, nature, hunting and animal welfare requirements and any necessary permits for training and operation must be considered. The results of this pilot study show that the "wildlife detection dog" method brings with it work and need for action, but also the unique possibilities of optimizing collecting species evidence needed for monitoring, researching and managing wildlife.
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Ponderosa pine (Pinus ponderosa) forests in the southwestern United States, used by 16 species of bats, are managed with thinning and prescribed fire to restore tree densities and fire regimes to conditions that existed prior to Euro-American settlement. Using 2 approaches (roosting and foraging) to categorize forest habitat for bats, we evaluated how restoration treatments may affect habitat use. We hypothesized that more foraging activity would occur in thinned stands because more species are adapted to open forest, but that more roosts would occur in unthinned stands where snags were unaffected by mechanical treatments and prescribed fire. During the summers of 2006 and 2007, we used acoustic detectors to record call rates of bats as a measure of activity level and compared activity levels among stands that had undergone 3 thinning treatments (light, moderate, and heavy, with 245, 172, or 142 trees per hectare postthinning, respectively) and an unthinned stand as a control (1201 trees per hectare). With radiotelemetry, we located roosts used by reproductive females of 2 common species of forest-associated bats (long-eared myotis, Myotis evotis, and Arizona myotis, Myotis occultus) during summer 2007. We measured roost characteristics at 3 spatial scales (roost, microplot, and surrounding landscape) to contrast between roosts used by Myotis species and randomly selected comparison snags, microplots, and study area landscape. Among thinned and unthinned stands we did not detect a difference in activity levels for all bats (P = 0.2), nor a difference in call rates for Myotis spp. (P = 0.1). However, there was lower activity (P = 0.01) for non-Myotis bats in unthinned compared to thinned stands. This is probably because most non-Myotis species are better adapted to foraging in open forests. Of 24 roosts for long-eared myotis and Arizona myotis, only 31% and 25%, respectively, occurred in thinned stands. Bats selected large-diameter (>68 cm diameter at breast height) ponderosa pine snags with exfoliating bark. Roosts for Arizona myotis were in areas with elements of old-growth structure, whereas roosts for long-eared myotis occurred in areas similar to stratified, midsuccessional, even-aged forest. Managing for large-diameter ponderosa pine snags and a variety of tree densities and age classes will provide roosting and foraging habitat for bats. We found no distinct “best” treatment to recommend overall, likely because of species differences, with some bats better adapted to opencanopy and some to closed-canopy forest. Maintaining diverse habitat will support a diverse bat assemblage.
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Artificial roosts designed to attract bats have been used to increase populations, aid seed dispersal, and control insects. More important from a conservation perspective, artificial roosts provide habitat where natural roosts have been lost. Although artificial roosts have been widely used, much of the information on species that use artificial roosts, roost design, and placement is anecdotal and poorly reported. We reviewed the existing literature on artificial roosts to summarize current research and inform research and management decisions. From 47 publications and reports, we identified 48 types of structures used by 59 species. Roosts were constructed from wood (66.7%), concrete (8.3%), or other materials (25.0%) and varied in size and shape from small-volume wood boxes (0.002 m3) to large (6 m tall) free-standing structures. Variables most often considered in the context of attracting bats were aspect, substrate, and mount location; few studies measured height or microclimate. Colonization rates ranged from 7% to 100%. Bats commonly used structures as solitary (21 species) or social (breeding or maternity; 21 species) roosts. Most species documented to use artificial roosts are vespertilionids (73%), have the International Union for Conservation of Nature's designation of least concern (93%), and roost in tree cavities or buildings. Three species are designated as endangered (Myotis sodalis) or near threatened (M. bechsteinii, M. dasycneme). Artificial roosts should be constructed and installed to mimic natural roosts, emphasize requirements of target species, and exclude non-target species. Monitoring species composition and identifying effects of roost density will help determine conservation impacts of artificial roosts. © 2014 The Wildlife Society.
Bats spend more time roosting than in any other activity. Thus, it is not surprising that some researchers have argued that roost availability influences the diversity of bat communities (Humphrey 1975), that destruction of roosts is responsible for population declines (Evelyn et al. 2004; Lunney et al. 1988), or that, in this book, there are several chapters devoted to the roosting ecology and behavior of forest-dwelling bats. Whether roosts are used during the day or night, or during hibernation, they must provide protection from predators and ambient environmental conditions, as well as space for social interaction (O'Shea and Bogan 2003). To maximize their fitness, individual bats should select roosts that provide these features, although the relative importance of each feature may vary among species, populations, genders, and reproductive conditions. © 2007 by The Johns Hopkins University Press. All rights reserved.
This chapter presents analytic methods for matched studies with multiple risk factors of interest. We consider matched sample designs of two types, prospective (cohort or randomized) and retrospective (case-control) studies. We discuss direct and indirect parametric modeling of matched sample data and then focus on conditional logistic regression in matched case-control studies. Next, we describe the general case for matched samples including polytomous outcomes. An illustration of matched sample case-control analysis is presented. A problem solving section appears at the end of the chapter.
With the expansion of wind-energy generation, there is a growing need to develop accurate and efficient methods to detect bat casualties resulting from turbine collision and barotrauma. We conducted a formal blinded trial comparing the abilities of search dogs and human observers to locate bat carcasses. Dogs located 73% (46/63) of bats, whereas humans found 20% (12/60). We therefore recommend search dogs as an effective means of monitoring bat fatalities, particularly when a high degree of search accuracy is important. This includes surveys for rare species, or cases where searches are limited in extent or duration, because the application of correction factors is problematic where very few or no casualties are found. The dogs averaged 40 min to complete a survey, which was <25% of the time taken by humans. At large sites, the high initial set-up costs for search dogs can therefore be offset by the increased number of surveys that can be conducted within a given time. However, care must be taken with the selection and training of the dogs and handlers to produce consistent results. To allow fatality rates to be estimated from the number of casualties located, it is essential that assessments of the accuracy of the dog–handler team are made at each site. © 2013 The Wildlife Society.