|
| |
|
|
|
|
||||
| Home Help Feedback Subscriptions Archive Search Table of Contents | ||||
First published online September 19, 2008
Journal of Experimental Biology 211, 3174-3180 (2008)
Published by The Company of Biologists 2008
doi: 10.1242/jeb.022863
Foraging bats avoid noise
1 Zoological Institute, Department of Animal Physiology, University of
Tübingen, Auf der Morgenstelle 28, 72076 Tübingen, Germany
2 Max Planck Institute for Ornithology, Sensory Ecology Group,
Eberhard-Gwinner-Strasse, 82319 Seewiesen, Germany
* Author for correspondence (e-mail: siemers{at}orn.mpg.de)
Accepted 14 August 2008
 |
Summary |
|---|
 TOP Summary INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
|---|
Key words: environmental noise, anthropogenic noise, traffic noise, foraging, road ecology, Myotis myotis, gleaning bats, passive listening, echolocation, masking
|
INTRODUCTION |
|---|
|
TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
|---|
;
Patricelli and Blickley, 2006;
Slabbekoorn and Ripmeester,
2008) because noise can mask relevant acoustic signals to
potential receivers. Some species of birds, amphibians and dolphins shift the
frequency range of their communication signals in an effort to avoid strong
overlap with ambient noise (Slabbekoorn
and Peet, 2003; Narins et al.,
2004; Morisaka et al.,
2005; Feng et al.,
2006; Slabbekoorn and den
Boer-Visser, 2006; Bee and
Swanson, 2007). Moreover, some birds also increase their call
amplitude when singing in noisy environments, such as a big city
(Brumm and Todt, 2002;
Brumm, 2004), or shift singing
time to less noisy periods (Fuller et al.,
2007). Such behavioural flexibility and evolutionary plasticity
has allowed individuals and populations, respectively, to cope with natural
environmental noise. Indeed, it has enabled them to adapt their communication
systems to anthropogenic noise, at least to some degree. However, there are
clear indications that noise pollution can negatively affect wild animals
(Forman and Alexander, 1998;
Forman and Deblinger, 2000;
Jaeger et al., 2005). Roadless
space is becoming scarce in many places on our planet
(Watts et al., 2007) and road
influence on wildlife is an important issue. Traffic noise has been suggested
to decrease the occurrence, breeding density and breeding success of birds
(Brotons and Herrando, 2001;
Fernandez-Juricic, 2001). In
marine environments, noise can affect ranging and acoustic behaviours of
whales, porpoises and seals (Morton and
Symonds, 2002; Koschinski et
al., 2003).
Surprisingly, the degree to which noise can influence another crucial
behaviour – foraging – has been entirely neglected. Except for a
study on noise-increased predator vigilance, which could result in reduced
foraging efficiency in chaffinches (Quinn
et al., 2006), the present study is the first to address the
effects of noise on foraging ability. It is likely that ambient noise does
impact an animals' ability to use acoustic information for foraging because a
variety of birds and mammals use sound to find their prey. For example, owls
(Konishi, 2003) and
insect-eating primates (Goerlitz and
Siemers, 2007) listen for rustling sounds produced by moving
animals to detect and localize food. Bats represent a special case. While many
bats detect and intercept flying insects using echolocation
(Griffin, 1958;
Kalko, 1995;
Siemers and Schnitzler, 2000),
others find prey by listening for prey-produced sounds
(Marimuthu and Neuweiler,
1987; Faure and Barclay,
1992; Arlettaz et al.,
2001; Siemers and Swift,
2006). This strategy of `passive listening' is adopted by bat
species specialized to glean arthropods from vegetation or the ground where
prey echoes are masked by overlapping, strong background echoes. For such
`passive listening' bats, it is conceivable that environmental noise
interferes with the detection of prey. As these bats use echolocation for
spatial orientation, the reception of relevant echoes could potentially be
impaired by noise as well (Griffin and
Grinnell, 1958; von Frenckell
and Barclay, 1987; Mackey and
Barclay, 1989; Rydell et al.,
1999; Spanjer,
2006; Gillam and McCracken,
2007).
In the present study, we assessed the reaction of bats to both
anthropogenic and natural ambient noise in a foraging context. The greater
mouse-eared bat (Myotis myotis Borkhausen 1797) was used as a model
species because it belongs to the group of bats that find prey by listening to
their rustling sounds (Kolb,
1961; Arlettaz et al.,
2001). This species is therefore potentially vulnerable to noise
impact on both `passive listening' and echolocation. Furthermore, greater
mouse-eared bats are a highly protected species (European Habitats Directive,
Annex II). They are widely distributed
(Güttinger et al., 2001;
Dietz et al., 2007) and have
expansive home ranges (Audet et al.,
1991; Arlettaz,
1999; Zahn et al.,
2005); therefore, they are highly relevant in virtually all
environmental impact assessments for larger highway or railway projects in
central and southern Europe. Most projected traffic routes in Europe will
cross M. myotis foraging areas. The greater mouse-eared bat can serve
as a model species to assess noise impact on foraging behaviour in the large
and, from a conservation perspective, especially vulnerable
(Safi and Kerth, 2004) group
of `passive listening', gleaning bats.
Greater mouse-eared bats roost in caves in southern Europe and typically in
large attics in central Europe
(Güttinger et al., 2001;
Dietz et al., 2007). Colony
size ranges from a handful of reproductive females to several thousands of
bats. At nightfall, the colony members disperse into individual foraging areas
at a distance of 17 km or more from the communal day roost
(Güttinger et al., 2001).
They listen for ground-running (epigaeic) arthropods by low search flight in
habitats with open, accessible ground
(Arlettaz, 1996;
Güttinger et al., 2001;
Pereira et al., 2002). Greater
mouse-eared bats land briefly to glean their prey off the ground; carabids and
other ground-running beetles, mole-crickets, spiders and lithobiids are
important constituents of their diet
(Bauerova, 1978;
Arlettaz, 1996;
Pereira et al., 2002;
Siemers and Güttinger,
2006). Siemers and Güttinger recently showed that arthropod
taxa and size classes that produce relatively loud rustling sounds when
crawling are strongly overrepresented in the diet of greater mouse-eared bats
(Siemers and Güttinger,
2006). This finding indicates that acoustic conspicuousness of
potential prey could limit the bats' sensory access to food. As acoustic
conspicuousness is probably determined by signal-to-noise-ratio, both rustling
amplitude and background noise level will influence foraging success, provided
they cover the same frequency range. Arthropod rustling sounds are a series of
broadband clicks; they contain frequencies of up to 100 kHz and above. The
main energy is concentrated between 3 and 40 kHz, however
(Goerlitz and Siemers, 2007;
Goerlitz et al., 2008).
Environmental noise is generally measured only in the frequency range of human hearing. Often an A-weighting filter is applied, which results in units of dBA sound pressure level and accounts for the frequency response of human hearing. While this approach is obviously correct to assess noise pollution as perceived by humans, it is not appropriate when it comes to other mammals whose hearing ranges extend beyond human range. In the present study, we therefore took `a bat's perspective' and recorded the frequency spectrum of traffic noise up to 60 kHz.
We then conducted a choice experiment to test whether bats avoid noisy environments. In a large flight room, we constructed two equally profitable foraging compartments. In each trial, noise was played back in one of the compartments. We then measured whether and to what degree it affected foraging effort and foraging success of the bats in this compartment. The aim of this research was to test: (1) if bats will avoid foraging areas with strong noise impact (hypothesis one); and (2) if the frequency–time structure of the noise will affect its deterring effect (hypothesis two).
|
MATERIALS AND METHODS |
|---|
|
TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
|---|
Flight room and setup
Bats were tested in a large flight room with dimensions of 13 mx6
mx2 m (lengthxwidthxheight); walls and ceiling were covered
with sound-absorbing foam to reduce echoes and reverberations. Two equally
sized compartments [2.5 mx3 mx2 m
(lengthxwidthxheight)] were constructed by erecting a dividing
wall made from PVC and sound-absorbing foam
(Fig. 1). Each compartment was
equipped with six cylindrical landing platforms (diameter, 40 cm; height, 10
cm). The platforms were arranged in two rows of three, 20 cm apart. Mealworms,
as food reward, could be offered on a plastic Petri dish inserted on the
centre of the platforms.
|
Experimental procedure
In each trial, one compartment was the `stimulus compartment' where sound
was played back and the other compartment was the `silent compartment' where
the loudspeaker was activated but an empty file was played. Sound played back
in the stimulus compartment was also audible in the silent compartment. Due to
the dividing wall, it was attenuated by 17 dB in comparison with the stimulus
compartment (measured at the two platform fields; SdB02 sound level meter,
01dB-Stell, MVI technologies group; Villeurbanne, France). We used four
different stimulus types of playback: (1) silence – the loud speaker was
activated and an empty file was played back. The silence treatment was a
control and served to measure the baseline of the bats' search effort
allocation in the two compartments; (2) broadband, digitally generated noise,
which served as a broadband control; (3) traffic noise recorded 7.5 m from a
highway [30.7±2.5 passing vehicles min–1
(mean±s.d.)]; and (4) noise recorded from strongly moving reed
vegetation (reed bed running alongside a river, which flows across M.
myotis foraging habitats; bats are known to hunt on meadows adjacent to
these reeds; B.M.S., personal observation).
The experiments were divided into three periods of eight days. Different
stimuli were used for each period. Each of the four stimuli was presented once
on the left side and once on the right side for each bat, resulting in eight
experimental conditions per period (i.e. one a day). To factor out day or
sequence effects, each bat received a different experimental condition on a
given test day (Latin square design). Two out of the six platforms per
compartment were continuously baited with 4 g of mealworms, which corresponded
to approximately 40 individual larvae. The mealworms produced faint rustling
noises with main energy between 3 and 20 kHz, with stronger clicks of up to 50
kHz and above. Measured at 10 cm distance, the loudest peaks ranged from
approximately 45 to 62 dB SPL. The mealworm rustling was thus roughly similar
to the sounds produced by a carabid beetle (typical greater mouse-eared bat
prey) walking on soil, meadow or moist leaf-litter
(Goerlitz et al., 2008).
Rewards were not placed on the same platform location (front, middle, back)
within the two compartments to achieve a homogeneous distribution of the
rewarded dishes within the sound field of the speakers. As a result, there
were 12 different combinations to choose from. For a balanced design, we used
each combination twice within the 24 experimental days, avoiding repeating a
dish combination within any of the 8 day periods. The two rewarded dishes of
each side were always unrewarded dishes the following day to avoid place
conditioning. The assignment of rewarded dishes was independent between the
two sides to deter the bats from extracting information from the rewarding
scheme of the stimulus compartment from the silent compartment. Platform
positions were exchanged between consecutive experiments in order to avoid
olfactory labelling on the currently rewarded platforms (scent left from bats
of previous session of the day).
Data acquisition started after a 15 day training phase without noise playback in which the bats were accustomed to the flight room. The bats learned to search for prey in the two compartments without much training effort. Bats were tested individually during their natural activity period. After 15 capture events (brief landing on a baited platform, followed by in-flight smacking sounds, which indicate that the bat was chewing food) at a given platform, we removed the remaining prey from this platform. With two baited platforms per compartment, the bats could thus retrieve a maximum of 30 mealworms from a single compartment per session. The bats were prevented from perching inside the compartments by slowly approaching and gently touching them. To ensure sustained foraging motivation throughout data acquisition, the session was stopped when 45 mealworms had been eaten or 15 min had elapsed. The bats maintained or slightly increased their weight with a daily supply of 45 to 50 mealworms, which was a naturalistic amount of food.
Acquisition and analysis of behavioural data
Experiments were run in the dark and filmed (Sanyo BW CCD camera VCB-3572
IRP, Munich, Germany; Computar lens M0518, Düsseldorf, Germany; Sony
recorder GVD1000E, Berlin, Germany) under IR-illumination (custom made
IR-strobes) for online display and videotaped for later off-line analysis. For
off-line analysis, we used an event-recorder software (Department of Animal
Physiology, University of Tübingen) to extract the following parameters:
(A) flight time spent in each compartment; (B) number of flights into each
compartment. Capture events were counted online and subdivided into; (C)
capture events per compartment; and (D) capture events per compartment for the
25 first capture events. The latter measure was introduced because each bat in
every session performed at least 25 capture attempts. As a maximum of 30 were
allowed per compartment, these first 25 events could be allocated entirely to
one compartment, i.e. noise avoidance could be especially pronounced.
The data were normalized and expressed as percentages for display and
statistical analysis. Performance of each individual bat was averaged over the
three replicas (experimental periods) for a given experimental condition
(combination of stimulus type and stimulus compartment position, e.g. `traffic
noise' played in the `left' compartment) for the statistical analysis. To
account for possible individual differences, we used repeated-measures
analysis of variance (ANOVA) and post hoc paired t-tests
with sequential Bonferroni correction to test for the influence of playback
treatment on the bats' behaviour. To test for possible preferences of the bats
for one of the two test compartments, we included stimulus compartment
position (left or right) as a factor into the ANOVAs. For testing, percentage
data was transformed following Zar (Zar,
1999) (p'=arcsin 
p). Tests were run in SPSS 15.0.0 for
Windows (SPSS, Inc., Chicago, IL, USA).
Recording, generation and playback of acoustic stimuli
Traffic noise was recorded at a distance of 7.5 m from the centre of the
right lane of a highway and 1.5 m in height (Autobahn A8, Stuttgart-Munich,
Germany recording location at 48 deg. 37'53.79N and 9 deg. 32'22.36 E). We
recorded only when it was not raining and when the asphalt was dry. Recordings
were taken on windless days; therefore, no wind guard was used (which would
have acted as an unwanted low pass filter). Passing vehicles were videotaped
to determine vehicle type (car or truck) and to roughly estimate speed. The
sound of the cars was picked up with a sensitive, broadband condenser
measurement microphone for playback purposes (1/2'' low noise Microphone
System Type 40HH, G.R.A.S., Holte, Denmark; frequency response ±1dB
between 0.5 and 10kHz; ±8 dB between 10 and 50 kHz, internal noise
floor 6.5 dBA re. 20µPa). To ensure a quantitative, broadband analysis of
traffic noise, we used a slightly less sensitive but more broadband
measurement microphone (G.R.A.S. 1/4'' 40BF free field microphone). The
microphones were oriented perpendicular to the highway, i.e. we obtained
on-axis recordings from passing vehicles. Signals were digitized via
a custom-built external A/D-converter (`PCTape'; Animal Physiology, University
of Tübingen, 16 bit depth, 8xoversampling, digital anti-aliasing;
sampling rate 192 kHz) and recorded online onto a laptop computer and stored
as wav-files (custom-made recording software). From recordings of the passes
of 50 cars and 50 trucks at speeds of approximately 80 km
h–1, we selected the loudest 500 ms window (maximum root
means square (RMS) amplitude) with a custom Matlab (TheMathWorks, Inc.,
Natick, MA, USA) routine. To measure the energy distribution over frequency,
we computed power spectral densities (PSDs, FFT 256) in Matlab on these 500 ms
windows. The average PSDs for these 50 cars and 50 trucks
(Fig. 2) show that traffic
noise has its main energy clearly within the human audio range but does
contain ultrasonic components up to 50 kHz.
|
|
Files were played in a continuous loop throughout a trial. They were played back from a laptop through an external D/A-converter (RME Fireface 800 Interface, sampling rate 192 kHz, Haimhausen, Germany), broadband amplifiers (WPA-600 Pro, Conrad Electronics, Hirschau, Germany) and the above mentioned speaker.
|
RESULTS |
|---|
|
TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
|---|
|
The percentage of prey capture events that occurred in the stimulus compartment was affected by the noise treatment. This applies when analysing all capture events per session (maximally 45 per bat) (Fig. 4C) (factor stimulus type, F3,18=35.41, P<0.0001; factor stimulus compartment position, F1,6=0.07, P=0.805; interaction, F3,18=0.50, P=0.685) and even more pronounced when only considering the first 25 capture events per bat and session (Fig. 4D) (factor stimulus type, F3,18=76.40, P<0.0001; factor stimulus compartment position, F1,6=0.02 P=0.893; interaction, F3,18=0.09, P=0.962). The order of stimulus types by effect magnitude was the same as for the two above behavioural measures.
|
DISCUSSION |
|---|
|
TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
|---|
In the present study, we specifically assessed noise impact on foraging
activity. Therefore, we are unable to draw conclusions on the role
environmental noise will play for other bat activities. Bat colonies,
including those of greater mouse-eared bats, roost in church towers close to
the belfry and sometimes in road and railway bridges
(Güttinger et al., 2001).
If a church has functional bells, they are in use only for a small proportion
of the time. When found in bridges, they typically roost inside the structure
of the bridge where high frequency components of traffic noise will be
strongly attenuated. This might reduce traffic noise impact on the bats.
Nevertheless, bell tower and bridge-roosting are anecdotal evidence for the
ability of bats to cope with considerable background noise in non-foraging
situations.
Influence of noise structure
The deterring effect differed between stimuli; it increased from traffic to
vegetation to broadband noise. It is interesting to note that the vegetation
noise, although set 12 dB below the traffic noise amplitude (still unnaturally
loud), had a greater repellent effect than the traffic noise. This supports
our second hypothesis, predicting that the frequency–time structure of
the noise will affect its deterring intensity. The vegetation noise consisted
of a series of transient, broadband signals, not unlike the clicks produced by
walking arthropods (Goerlitz and Siemers,
2007; Goerlitz et al.,
2008). This similarity to prey sounds might render the vegetation
noise an effective masker that reduces the bats' ability to detect insects.
Unless shaken by a storm, sounds of naturally wind-moved vegetation will be
much less intense than that created in the present study and, hence, will be
of less impact for wild bats. Nevertheless, natural noise is likely to affect
the foraging efficiency of bats. Behaviour observation and playback
experiments suggested that noise from turbulent water could interfere with
echo-based prey detection in bats that forage close to, as well as several
meters above, water surfaces (von
Frenckell and Barclay, 1987;
Mackey and Barclay, 1989;
Rydell et al., 1999).
The artificial broadband noise in our experiments contained higher
frequencies than the traffic noise. It was continuous whereas both traffic and
vegetation noise contained short intervals of less intense sound. Both its
continuous nature and its content of higher frequencies might in part explain
why the broadband noise treatment had the strongest deterrent effect on the
bats (see also Huebner and Wiegrebe,
2003).
Reasons for noise avoidance
An unspecific aversive character of noise
(Beerda et al., 1998) could be
part of the reason why greater mouse-eared bats avoided noisy foraging
patches. As these bats do roost in noisy places (see above), it appears more
likely, however, that a specific noise-impairment on perception of prey sounds
(Huebner and Wiegrebe, 2003;
Goerlitz et al., 2008), on
echolocation (Griffin and Grinnell,
1958; Rydell et al.,
1999; Spanjer,
2006; Gillam and McCracken,
2007) or on both were the reason. Impairment could be caused by
the masking of relevant sounds or echoes and by the difficulty of processing
several auditory streams simultaneously
(Barber et al., 2003). The fact
that we did not observe any change in flight ability or landing accuracy
argues against a relevant impairment of echolocation. Calls of greater
mouse-eared bats are broadband sweeps from between 120 and 70kHz down to
approximately 27kHz (Boonman and
Schnitzler, 2005), i.e. they contain considerable energy above the
frequency band covered by the noise playbacks in the present study. The strong
effect of the click-like vegetation noise, despite its reduced amplitude,
points in the direction of an impairment of the perception of prey
rustling-clicks. Further experiments will be needed to verify this explanation
and to quantify the conceivable reduction of the ability of bats to detect
prey by natural and anthropogenic noise.
Conclusions
Data from the present study suggest that foraging areas very close to
highways and presumably also to other sources of intense broadband noise are
degraded in their suitability as foraging areas for the greater mouse-eared
bat. The situation, which mimicked the traffic noise treatment, corresponds to
a distance of 10–15 m from a highway. Noise intensity and, hence, noise
impact will level off with distance. However, it is likely that bats foraging
50 m away from the highway will still be impacted by traffic noise (B.M.S. and
A.S., unpublished data). Relatively large areas will be affected and a fitness
relevance for natural populations is likely. In addition to distance, the
number of passing vehicles will affect the intensity of acoustic habitat
degradation. In addition to the greater mouse-eared bats, many other species
of bat find their prey predominantly by listening to prey sounds. We therefore
assume that acoustic habitat degradation will affect these species in a
similar way. This group is especially vulnerable to extinction and is,
therefore, of special conservation concern
(Safi and Kerth, 2004). In
Europe, the potential vulnerable bat species include the lesser mouse-eared
bat (Myotis blythii/oxygnathus), Bechstein's bat (Myotis
bechsteinii) and all long-eared bats (genus Plecotus)
(Arlettaz et al., 2001;
Swift and Racey, 2002;
Siemers and Swift, 2006). In
North America, species such as the pallid bat (Antrozous pallidus),
the long-eared bat (Myotis evotis), the Northern long-eared bat
(Myotis septentrionalis) and possibly the big-eared bats (genus
Corynorhinus) as well as the little-known spotted bat (Euderma
maculatum) might also be affected by acoustic habitat degradation
(Faure and Barclay, 1992;
Fullard and Dawson, 1997;
Lacki and Ladeur, 2001;
Leslie and Clark, 2002;
Barber et al., 2003;
Ratcliffe and Dawson, 2003).
Interestingly, the reluctance of bats to forage in very noisy environments
potentially also brings about conservation benefits. If bats indeed allocate
little foraging time to noisy highway margins and highways themselves, the
number of potential traffic casualties
(Kiefer et al., 1994;
Lesinski, 2007) could be
reduced. By contrast, aerial hawking bats that detect and track insects by
echolocation can be attracted by the high prey abundance associated with
anthropogenic habitat alterations, such as streetlights alongside roads
(Arlettaz et al., 2000;
Avila-Flores and Fenton, 2005)
or garbage dumps (Kronwitter,
1988). While this might indicate some dichotomy in how bats from
different ecological groups deal with human impact, previous playback
experiments indicate that in addition to `passive listening' bats as shown in
the present study, aerial hawking species are also affected and deterred by
broadband noise (Mackey and Barclay,
1989; Spanjer,
2006; Szewczak and Arnett,
2006). In the course of environmental impact assessments for
highway planning, appropriate preventive measures (noise reduction) or
compensatory measures (amelioration of alternative bat foraging habitats)
will, according to the respective applicable national and international law,
have to be considered. Further research is needed to mechanistically
understand the impact of anthropogenic noise on both `passive listening'
gleaning bats and aerial hawking bats, which find prey by echolocation.
|
Acknowledgments |
|---|
|
References |
|---|
|
TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
|---|
Arlettaz, R. (1996). Feeding behaviour and foraging strategy of free-living mouse-eared bats, Myotis myotis and Myotis blythii. Anim. Behav. 51, 1-11.[CrossRef]
Arlettaz, R. (1999). Habitat selection as a major resource partitioning mechanism between the two sympatric sibling bat species Myotis myotis and Myotis blythii. J. Anim. Ecol. 68,460 -471.[CrossRef]
Arlettaz, R., Godat, S. and Meyer, H. (2000). Competition for food by expanding pipistrelle bat populations (Pipistrellus pipistrellus) might contribute to the decline of lesser horseshoe bats (Rhinolophus hipposideros). Biol. Conserv. 93,55 -60.[CrossRef]
Arlettaz, R., Jones, G. and Racey, P. A. (2001). Effect of acoustic clutter on prey detection by bats. Nature 414,742 -745.[CrossRef][Medline]
Audet, D., Krull, D., Marimuthu, G., Sumithran, S. and Singh, J. B. (1991). Foraging behavior of the Indian false vampire bat, Megaderma lyra (Chiroptera, Megadermatidae). Biotropica 23,63 -67.[CrossRef]
Avila-Flores, R. and Fenton, M. B. (2005). Use of spatial features by foraging insectivorous bats in a large urban landscape. J. Mammal. 86,1193 -1204.[CrossRef]
Barber, J. R., Razak, K. A. and Fuzessery, Z. M. (2003). Can two streams of auditory information be processed simultaneously? Evidence from the gleaning bat Antrozous pallidus.J. Comp. Physiol. 189,843 -855.[CrossRef]
Bauerova, Z. (1978). Contribution to the trophic ecology of Myotis myotis. Folia Zool. 27,305 -316.
Bee, M. A. and Swanson, E. M. (2007). Auditory masking of anuran advertisement calls by road traffic noise. Anim. Behav. 74,1765 -1776.
Beerda, B., Schilder, M. B. H., van Hooff, J., de Vries, H. W. and Mol, J. A. (1998). Behavioural, saliva cortisol and heart rate responses to different types of stimuli in dogs. Appl. Anim. Behav. Sci. 58,365 -381.[CrossRef]
Boonman, A. and Schnitzler, H. U. (2005). Frequency modulation patterns in the echolocation signals of two vespertilionid bats. J. Comp. Physiol. 191, 13-21.[CrossRef]
Brotons, L. and Herrando, S. (2001). Reduced bird occurrence in pine forest fragments associated with road proximity in a Mediterranean agricultural area. Landsc. Urban Plan. 57, 77-89.[CrossRef]
Brumm, H. (2004). The impact of environmental noise on song amplitude in a territorial bird. J. Anim. Ecol. 73,434 -440.[CrossRef]
Brumm, H. and Slabbekoorn, H. (2005). Acoustic communication in noise. Adv. Study Behav. 35,151 -209.[CrossRef]
Brumm, H. and Todt, D. (2002). Noise-dependent song amplitude regulation in a territorial songbird. Anim. Behav. 63,891 -897.[CrossRef]
Dietz, C., von Helversen, O. and Nill, D. (2007). Handbuch der Fledermäuse Europas und Nordwestafrikas. Stuttgart: Franckh-Kosmos Verlags GmbH.
Faure, P. A. and Barclay, R. M. R. (1992). The sensory basis of prey detection by the long-eared bat, Myotis evotis, and the consequences for prey selection. Anim. Behav. 44, 31-39.[CrossRef]
Feng, A. S., Narins, P. M., Xu, C. H., Lin, W. Y., Yu, Z. L., Qiu, Q., Xu, Z. M. and Shen, J. X. (2006). Ultrasonic communication in frogs. Nature 440,333 -336.[CrossRef][Medline]
Fernandez-Juricic, E. (2001). Avian spatial segregation at edges and interiors of urban parks in Madrid, Spain. Biodivers. Conserv. 10,1303 -1316.[CrossRef]
Forman, R. T. T. and Alexander, L. E. (1998). Roads and their major ecological effects. Annu. Rev. Ecol. Syst. 29,207 -231.[CrossRef]
Forman, R. T. T. and Deblinger, R. D. (2000). The ecological road-effect zone of a Massachusetts (USA) suburban highway. Conserv. Biol. 14,36 -46.[CrossRef]
Fullard, J. H. and Dawson, J. W. (1997). The echolocation calls of the spotted bat Euderma maculatum are relatively inaudible to moths J. Exp. Biol. 200,129 -137.[Abstract]
Fuller, R. A., Warren, P. H. and Gaston, K. J. (2007). Daytime noise predicts nocturnal singing in urban robins. Biol. Lett. 3,368 -370.[CrossRef][Medline]
Gillam, E. H. and McCracken, G. F. (2007). Variability in the echolocation of Tadarida brasiliensis: effects of geography and local acoustic environment. Anim. Behav. 74,277 -286.[CrossRef]
Goerlitz, H. R. and Siemers, B. M. (2007). Sensory ecology of prey rustling sounds: acoustical features and their classification by wild Grey Mouse Lemurs. Funct. Ecol. 21,143 -153.
Goerlitz, H. R., Greif, S. and Siemers, B. M.
(2008). Cues for acoustic detection of prey: insect rustling
sounds and the influence of walking substrate. J. Exp.
Biol. 211,2799
-2806.
Griffin, D. R. (1958). Listening in the Dark. New Haven: Yale University Press.
Griffin, D. R. and Grinnell, A. D. (1958).
Ability of bats to discriminate echoes from louder noise.
Science 128,145
-147.
Güttinger, R., Zahn, A., Krapp, F. and Schober, W. (2001). Myotis myotis-Großes Mausohr, Großmausohr. In Handbuch der Säugetiere Europas, vol. 4/I: Fledertiere I (ed. F. Krapp). Wiebelsheim: Aula-Verlag.
Huebner, M. and Wiegrebe, L. (2003). The effect of temporal structure on rustling-sound detection in the gleaning bat, Megaderma lyra. J. Comp. Physiol. A 189,337 -346.[Medline]
Jaeger, J. A. G., Bowman, J., Brennan, J., Fahrig, L., Bert, D., Bouchard, J., Charbonneau, N., Frank, K., Gruber, B. and von Toschanowitz, K. T. (2005). Predicting when animal populations are at risk from roads: an interactive model of road avoidance behavior. Ecol. Modell. 185,329 -348.[CrossRef]
Kalko, E. K. V. (1995). Insect pursuit, prey capture and echolocation in pipistrelle bats (Microchiroptera). Anim. Behav. 50,861 -880.[CrossRef]
Kiefer, A., Merz, H., Rackow, W., Roer, H. and Schlegel, D. (1994). Bats as traffic casualties in Germany. Myotis 32-33,215 -220.
Kolb, A. (1961). Sinnesleistungen Einheimischer Fledermaeuse Bei Der Nahrungssuche Und Nahrungsauswahl Auf Dem Boden Und In Der Luft. Z. Vgl. Physiol. 44,550 -564.[CrossRef]
Konishi, M. (2003). Coding of auditory space. Ann. Rev. Neurosci. 26,31 -55.[CrossRef][Medline]
Koschinski, S., Culik, B. M., Henriksen, O. D., Tregenza, N., Ellis, G., Jansen, C. and Kathe, G. (2003). Behavioural reactions of free-ranging porpoises and seals to the noise of a simulated 2 MW windpower generator. Mar. Ecol. Prog. Ser. 265,263 -273.[CrossRef]
Kronwitter, F. (1988). Population structure, habitat use and activity patterns of the noctule bat, Nyctalus noctula Schreb., 1774 (Chiroptera: Vespertilionidae) revealed by radio-tracking. Myotis 26, 23-85.
Lacki, M. J. and Ladeur, K. M. (2001). Seasonal use of lepidopteran prey by Rafinesque's big-eared bats (Corynorhinus rafinesquii). Am. Midl. Nat. 145,213 -217.[CrossRef]
Lesinski, G. (2007). Bat road casualties and factors determining their number. Mammalia 71,138 -142.
Leslie, D. M. and Clark, B. S. (2002). Feeding habits of the endangered Ozark big-eared bat (Corynorhinus townsendii ingens) relative to prey abundance. Acta Chiropt. 4, 173-182.
Mackey, R. L. and Barclay, R. M. R. (1989). The influence of physical clutter and noise on the activity of bats over water. Can. J. Zool. 67,1167 -1170.
Marimuthu, G. and Neuweiler, G. (1987). The use of acoustical cues for prey detection by the Indian false vampire bat, Megaderma lyra. J. Comp. Physiol. 160,509 -515.[CrossRef]
Morisaka, T., Shinohara, M., Nakahara, F. and Akamatsu, T. (2005). Effects of ambient noise on the whistles of Indo-Pacific bottlenose dolphin populations. J. Mammal. 86,541 -546.[CrossRef]
Morton, A. B. and Symonds, H. K. (2002).
Displacement of Orcinus orca (L.) by high amplitude sound in British
Columbia, Canada. ICES J. Mar. Sci.
59, 71-80.
Narins, P. M., Feng, A. S., Lin, W. Y., Schnitzler, H. U., Denzinger, A., Suthers, R. A. and Xu, C. H. (2004). Old World frog and bird, vocalizations contain prominent ultrasonic harmonics. J. Acoust. Soc. Am. 115,910 -913.[CrossRef][Medline]
Patricelli, G. L. and Blickley, J. L. (2006). Avian communication in urban noise: causes and consequences of vocal adjustment. Auk 123,639 -649.[CrossRef]
Pereira, M. J. R., Rebelo, H., Rainho, A. and Palmeirim, J. M. (2002). Prey selection by Myotis myotis (Vespertilionidae) in a Mediterranean region. Acta Chiropt. 4,183 -193.
Quinn, J. L., Whittingham, M. J., Butler, S. J. and Cresswell, W. (2006). Noise, predation risk compensation and vigilance in the chaffinch Fringilla coelebs. J. Avian Biol. 37,601 -608.[CrossRef]
Ratcliffe, J. M. and Dawson, J. W. (2003). Behavioural flexibility: the little brown bat, Myotis lucifugus, and the northern long-eared bat, M. septentrionalis, both glean and hawk prey. Anim. Behav. 66,847 -856.[CrossRef]
Rydell, J., Miller, L. A. and Jensen, M. E. (1999). Echolocation constraints of Daubenton's bat foraging over water. Funct. Ecol. 13,247 -255.[CrossRef]
Safi, K. and Kerth, G. (2004). A comparative analysis of specialization and extinction risk in temperate-zone bats. Conserv. Biol. 18,1293 -1303.[CrossRef]
Siemers, B. M. and Güttinger, R. (2006). Prey conspicuousness can explain apparent prey selectivity. Curr. Biol. 16,R157 -R159.[CrossRef][Medline]
Siemers, B. M. and Schnitzler, H. U. (2000). Natterer's bat (Myotis nattereri Kuhl, 1818) hawks for prey close to vegetation using echolocation signals of very broad bandwidth. Behav. Ecol. Sociobiol. 47,400 -412.[CrossRef]
Siemers, B. M. and Swift, S. M. (2006). Differences in sensory ecology contribute to resource partitioning in the bats Myotis bechsteinii and Myotis nattereri (Chiroptera: Vespertilionidae). Behav. Ecol. Sociobiol. 59,373 -380.[CrossRef]
Slabbekoorn, H. and den Boer-Visser, A. (2006). Cities change the songs of birds. Curr. Biol. 16,2326 -2331.[CrossRef][Medline]
Slabbekoorn, H. and Peet, M. (2003). Ecology: birds sing at a higher pitch in urban noise-Great tits hit the high notes to ensure that their mating calls are heard above the city's din. Nature 424,267 -267.
Slabbekoorn, H. and Ripmeester, E. A. P. (2008). Birdsong and anthropogenic noise: implications and applications for conservation. Mol. Ecol. 17, 72-83.[CrossRef][Medline]
Spanjer, G. R. (2006). Responses of the big brown bat, Eptesicus fuscus, to a proposed acoustic deterrent device in a lab setting: a report submitted to the Bats and Wind Energy Cooperative and the Maryland Department of Natural Resources. Austin, Texas, USA: Bat Conservation International. http://www.batsandwind.org/pdf/detlab2006.pdf
Swift, S. M. and Racey, P. A. (2002). Gleaning as a foraging strategy in Natterer's bat Myotis nattereri. Behav. Ecol. Sociobiol. 52,408 -416.[CrossRef]
Szewczak, J. M. and Arnett, E. B. (2006). An acoustic deterrent with the potential to reduce bat mortality from wind turbines. Bat Res. News 47,151 -152.
von Frenckell, B. and Barclay, R. M. R. (1987). Bat activity over calm and turbulent water. Can. J. Zool. 65,219 -222.
Watts, R. D., Compton, R. W., McCammon, J. H., Rich, C. L.,
Wright, S. M., Owens, T. and Ouren, D. S. (2007). Roadless
space of the conterminous United States. Science
316,736
-738.
Zahn, A., Haselbach, H. and Guttinger, R. (2005). Foraging activity of central European Myotis myotis in a landscape dominated by spruce monocultures. Mamm. Biol. 70,265 -270.[CrossRef]
Zar, J. H. (1999). Biostatistical Analysis. Upper Saddle River, NJ: Pearson Education.
Related articles in JEB:
This article has been cited by other articles:
|
|
 |
|
  K. Phillips BATS PICK UP RUSTLES AGAINST HUMAN NOISE J. Exp. Biol., October 1, 2008; 211(19): i - ii. [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
