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The impact of artificial lighting on bats along native
coastal vegetation
Grant D. Linley
Ecological Insights, Black Rock, Vic., Australia. Email: grant.linley@gmail.com
Abstract. Anthropogenic light pollution is increasing rapidly within urban areas around the world, causing a raft
of ecological issues, including species loss. I used echolocation detectors to uncover the impact of artificial lighting on
insectivorous bat (Chiroptera) species in Melbourne’s south-east. Surveys were undertaken in native vegetation at a lit
treatment, which was illuminated by a street light, and an unlit treatment, which was dark. Bat activity and species richness
at unlit treatments was significantly higher when compared with lit treatments. The temperature at which the greatest
activity occurred was ~2C higher at unlit treatments than lit treatments. Bat activity at both the lit and unlit treatments
increased rapidly after sunset. Bat activity moderately decreased during the night at lit treatments until sunrise, whilst
activity at unlit treatments remained steady throughout the night before rapidly decreasing two hours before sunrise. The
negative effect of artificial lighting on bat activity and species in urban areas may have major long-term implications on
the ecology of urban areas.
Additional keywords: echolocation, insectivorous bats, lighting, urban ecology.
Received 10 November 2015, accepted 31 August 2016, published online 7 October 2016
Introduction
There is a direct link between the impacts of humans and the
loss of biodiversity in urban areas (McKinney 2002,2008). As
urbanisation rapidly increases anthropogenic light pollution has
serious impacts on the functioning of ecosystems (Longcore and
Rich 2004; Hölker et al.2010). Much of the earth is now affected
by light pollution in some way, and this is thought to be increasing
by 6% per year (Elvidge et al.2001; Longcore and Rich 2004).
Over time, synergistic stressors place further pressure on these
heavily degraded and modified systems (Longcore and Rich
2004; Hölker et al.2010).
Landscape modification as a result of urban sprawl has
accelerated species loss in Australia (Fischer and Lindenmayer
2007), especially in coastal environments in or near urban areas
(Schlacher et al.2014). However, certain species, such as
insectivorous bats (hereafter bats), are able to persist in specific
urban areas (Avila-Flores and Fenton 2005; van der Ree and
McCarthy 2005; Hourigan et al.2010; Threlfall et al.2011).
Bats are nocturnal and play an important role in keeping urban
invertebrate species in balance (Hill and Smith 1984; Aldridge
and Rautenbach 1987; Gonsalves et al.2013). Each bat species
has specific foraging preferences that are associated with their
flight characteristics and mobility (Aldridge and Rautenbach
1987). Roosting sites are predominantly small dark spaces,
including tree hollows or small man-made hollows such as roof
holes (Tidemann and Flavel 1987; Lumsden et al.2002).
Anthropogenic lighting regimes affect bat feeding and
roosting behaviour (Scanlon and Petit 2008b; Lacoeuilhe et al.
2014;Day et al.2015). In one of Australia’s only studies on the
effects of light pollution on bats, Scanlon and Petit (2008b)
suggested that Nyctophilus geoffroyi and Chalinolobus morio
avoided all lit sites while Chalinolobus gouldii and Mormopterus
spp. prefer lighting. Some rare and cryptic bat species, including
Nyctophilus gouldi have been found to avoid light (Threlfall et al.
2013). Preference for lit areas is generally a result of higher
concentrations of insects and moths (Lepidoptera), which are
key components of the bat diet (Scanlon and Petit 2008a;
Lacoeuilhe et al.2014; Day et al.2015). The type of lighting
itself also determines what bats will be present. For example,
mercury vapour lamps attract moths and other insects more
than low pressure sodium lamps, whist LED lighting is known
to negatively impact certain species of bats (Rydell 1992; Blake
et al.1994; Stone et al.2012).
While there have been some studies of the effects of
artificial lighting on bats (Rydell 1992; Scanlon and Petit
2008b;Stoneet al.2009;Threlfallet al.2013), there is no
information for the rapidly expanding Melbourne region. As
the local population and housing density increases, light
pollution increases (Cinzano et al.2001; Elvidge et al.2001).
It is essential to understand the effects of lighting on
insectivorous bats within urban environments in order to
mitigate them. With limited biodiversity remaining in urban
areas, preservation of what remains is key to maintaining
ecological processes (Fischer and Lindenmayer 2007). In this
study, I aimed to quantify the impacts of artificial lighting on
bat species richness and activity.
The Author 2016 www.publish.csiro.au/journals/am
CSIRO PUBLISHING
Australian Mammalogy
http://dx.doi.org/10.1071/AM15047
Methods
Study area
The study was conducted in the municipality of Bayside in
Melbourne’s south-eastern suburbs (Fig. 1). The area is highly
urbanised and predominantly consists of housing and roads. The
population is currently estimated to be 103 110 and in 2006 there
were 33 325 houses spread over 37 km
2
(Bayside Council 2007).
Small patches of remnant vegetation are scattered throughout
the area; most have lost their connectivity but may still be
functionally connected for most bat species. The municipality
includes a large strip of connected native vegetation along the
foreshore that has been only slightly modified through the
introduction of small numbers of non-native plants, walking
tracks and small fences. The local climate is characterised by
warm summers (maximum average temperature 25.2C) and
cool winters (maximum average temperature 14.3C) and an
average annual rainfall of 708.8 mm (Bureau of Meteorology
2015).
Bat surveys
Bat echolocation calls (hereafter calls) were recorded once
a month between December 2014 and March 2015 using Anabat
Express detectors (Titley Electronics, Ballina, NSW). Three
recording sites were established along a connected strip of
vegetation on the foreshore, and each was divided into two
treatments, lit and unlit. Lit treatment areas were illuminated
by mercury vapour street lights of 3–4 lx between sunset
and sunrise, while unlit treatment areas were not subject to any
artificial lighting and illumination was less than 0.5 lx. All
treatments at each site had identical vegetation height and
structure, so the only discernible difference was the presence
of light. All sites were classed as coastal heathland scrub
(Ecology Australia 2008) and the dominant vegetation at each
site was coastal banksia (Banksia integrifolia), drooping sheoak
(Allocasuarina verticillata) and coastal tea tree (Leptospermum
laevigatum) with heights of 2–4 m. Sites were located at least
100 m from busy roads and major disturbances, including noise
pollution, and at least 50–100 m from the ocean. At each site
treatments were 150–250 m apart to ensure that bats could
access both the lit and unlit treatments. Each site was sampled
for three consecutive nights, using one Anabat detector in each
treatment, giving a total of nine sampling nights per month.
Sampling started 30 min before sunset and concluded 30 min
after sunrise. Surveys were not conducted on nights when rain
fell, when the temperature was below 10C or when wind
speeds were over 15 km h
–1
. Surveys were not conducted within
five days of a full moon, as moonlight affects bat activity and
detection (Basham et al.2011; Threlfall et al.2011).
The Anabat detectors where placed ~2–2.5 m off the ground
next to a flyway to ensure consistency and accuracy when
sampling bats. In lit treatments the detector was located directly
below the light source. The omnidirectional microphone faced
horizontally to ensure that all calls in the vicinity of the unit
were detected. When a call was detected, the detector also
logged time and ambient temperature.
Call identification
Recordings were downloaded onto Analook (Titley Electronics,
Ballina, NSW), which allows the calls to be visualised and
identified. The principal parameters used for call identification
were frequency range and shape. Additionally, two guides
were used to assist in the identification of pulse characteristics
(Pennay et al.2004; Bat Sense 2010). Calls were analysed only if
they consisted of at least three pulses of a similar frequency
(Pennay et al.2004), and if there was any uncertainty about a call
it was not used in the analysis. Two species of little free-tailed
bats (Mormopterus sp. 2 and Mormopterus sp. 4) and two species
Melbourne
Geelong
0510 km
Fig. 1. The locations of the three study sites (black squares) in relation to Australia (insert) and
Melbourne.
BAustralian Mammalogy G. D. Linley
of long-eared bats (N. geoffroyi and N.gouldii) occur in this
area, but their calls could not be identified to species level
(Pennay et al.2004; Bat Sense 2010).
In addition to checking calls against guides, unknown calls
were sent to experts. It is not possible to identify all calls:
unrelated species may have similar calls and many bats vary
their calls in different habitats, so it is possible that a small
number of calls may be misidentified.
Statistical analysis
Mann–Whitney U-tests were used to determine the difference
between treatments for the total activity of all species identified
and differences between each individual’s species at each
treatment. Resulting Pvalues were not corrected as species are
not correlated and the trade-off between decreasing Type 1 error
and increasing Type 2 error was deemed to be too great. A t-test
with unequal variance was used to test species richness between
the treatments over the sampling period. Single-factor ANOVAs
were used to determine if any differences existed between
months at each treatment and between sites over the whole
sampling period. The statistical program EstimateS was used to
produce sample-based rarefaction curves using a sample that
was randomised 100 times (Gotelli and Colwell 2001). Using
analysis software that allowed for the extraction of temperature
and time data from calls, the resulting differences in bat activity
of these variables for both lit and unlit treatments were
compiled and compared. To test for differences in activity levels
of both the temperature and time at treatments, two-sample
Kolmogorov–Smirnov tests were used.
Results
Activity of bats
A total of 13 002 bat calls were recorded from 54 498 recordings,
the majority of recordings being insect calls and background
noise from wind. Of these calls, 10 112 (77.8%) were identified.
The total activity of bats was highest at unlit treatments, with
an overall 5905 identified calls compared with 4207 from the lit
treatments (Table 1). Over the whole study the average number
of calls per species at lit sites was 382.45 (284.01) compared
with 536.81 at unlit (352.38) (d.f. = 10, P= 0.046) (Table 1).
No significant differences for C. gouldii,C. morio,Vespadelus
vulturnus,Austronomous australis,Miniopterus schreibersii
oceanensis. Saccolaimus flaviventris was found between
treatments. For Mormopterus spp., Myotis macropus,Nyctophilus
spp., Vespadelus darlingtoni and Vespadelus regulus the total
numbers of calls in lit treatments were significantly lower than in
unlit treatments (Table 1).
No differences were found to occur between the monthly
total for each species for both the lit (F
3,40
= 0.37, P= 0.77)
and unlit (F
3,40
= 0.05, P= 0.99) treatments. There were no
significant differences in species totals between the three sites:
lit (F
2,33
= 0.33, P= 0.72), unlit (F
2,33
= 0.37, P= 0.69).
Difference in species richness
In total, 11 species were detected at the study area, 5 at lit
treatments and 11 at unlit treatments. Species richness was
significantly lower at lit treatments (5 0.00) compared with
unlit treatments (10.33 0.67) at each site (d.f. = 2, P<0.01).
Sample-based rarefaction curves show the disparity in richness
between the lit and unlit treatments over the sampling period
(Fig. 2). As both curves reach an asymptote the findings are
sufficiently robust to compare (Gotelli and Colwell 2001;
Colwell et al.2004).
The effect of temperature on bat activity
Bat activity was strongly influenced by ambient temperature
(Fig. 3). During the study period, nocturnal ambient temperature
varied from 10Cto32
C, and 81% of identified calls were
detected when ambient temperatures were 1323C. There were
no differences in ambient temperatures between the lit and unlit
treatments, but bat activity at lit treatments peaked between 13C
and 17C, while in the unlit treatments activity peaked between
14C and 19C (Fig. 3)(D
23
= 0.25, P= 0.01).
The influence of time since sunset on bat activity
In all, 92% of calls from identified bat species were recorded
in the first hour after sunset. Nocturnal bat activity was much
higher at unlit treatments compared with lit treatments (Fig. 4).
Table 1. The median calls and the total number of identified bat calls (in parentheses) for each species per treatment
over the study period
Results of Mann–Whitney U-tests are shown for each species between treatments
Unlit Lit Mann–Whitney U-tests
Austronomous australis (white-striped free-tailed bat) 63 (475) 47 (112) U=2,n
1
=n
2
=3,P= 0.14
Chalinolobus gouldii (Gould’s wattled bat) 1435 (4011) 530 (3143) U=4,n
1
=n
2
=3,P= 0.41
Chalinolobus morio (chocolate wattled bat) 32 (182) 33 (99) U=4,n
1
=n
2
=3,P= 0.41
Miniopterus schreibersii oceanensis (eastern bentwing-bat) 1 (33) 0 (0) U= 1.5, n
1
=n
2
=3,P= 0.10
Mormopterus spp. (free-tailed bats) 100 (332) 35 (97) U=0,n
1
=n
2
=3,P= 0.02
Myotis macropus (large-footed myotis) 1 (3) 0 (0) U=0,n
1
=n
2
=3,P= 0.02
Nyctophilus spp. (long-eared bats) 1 (11) 0 (0) U=0,n
1
=n
2
=3,P= 0.02
Saccolaimus flaviventris (yellow-bellied sheath-tailed bat) 2 (6) 0 (0) U= 1.5, n
1
=n
2
=3,P= 0.10
Vespadelus darlingtoni (large forest bat) 25 (120) 0 (0) U=0,n
1
=n
2
=3,P= 0.02
Vespadelus regulus (southern forest bat) 61 (156) 0 (0) U=0, n
1
=n
2
=3,P= 0.02
Vespadelus vulturnus (little forest bat) 256 (576) 30 (756) U=3,n
1
=n
2
=3,P= 0.26
Total unidentified calls 324 (1197) 583 (1693) U=3,n
1
=n
2
=3,P= 0.26
Total identified calls 5905 4207
Impacts of artificial lighting on bats Australian Mammalogy C
Activity at both the lit and unlit treatments increased rapidly after
sunset; however, activity at the lit treatments quickly diminished
while activity at the unlit treatments remained high throughout
the night, and then declined before sunrise (Fig. 4). The difference
between the time in which bat activity occurred at lit and unlit
treatments was found to be significantly different (D
11
= 0.08,
P<0.01).
Discussion
Artificial lighting reduced both activity and species richness
of bats in the study area. The ambient temperature and time at
which peak activity occurred were also affected by lighting.
These results are in agreement with previous studies that found
that artificial lighting reduced species richness and diversity
of bats (Scanlon and Petit 2008a,2008b; Stone et al.2009;
Lacoeuilhe et al.2014; Day et al.2015), but differ from other
studies that concluded artificial lighting generally increased bat
activity (Blake et al.1994; Avila-Flores and Fenton 2005). This
suggests that the effect of artificial light on bats is more complex
than anticipated and can vary between regions and species.
Loss of bat activity and richness
The species identified in this study are widespread throughout
south-eastern Australia (Pennay et al.2004; Bat Sense 2010)
and have previously been found to show little preference between
lit and unlit areas (Scanlon and Petit 2008a). Overall, in the
present study unlit treatments had significantly higher bat
activity than lit treatments (Table 1). Of the species identified,
C. gouldii,S. balstoni,V. darlingtoni and V. vulturnus were
found to be generalist species with similar activity at both lit
and unlit treatments.
At lit treatments A. australis,C. morio,M. schreibersii
oceanensis,Mormopterus spp., M. macropus,Nyctophilus spp.,
S. flaviventris,V. darlingtoni and V. regulus were not recorded,
and it is known that all are sensitive to both artificial lighting
and urbanisation (Lumsden et al.2002; Scanlon and Petit 2008a;
Threlfall et al.2012). My results contrast with those of a
previous study in New South Wales that showed higher activity
of A. australis,S. flaviventris and V. regulus at lit treatments
(Adams et al.2005). These species are believed to avoid lit
areas due to feeding requirements and morphology (Aldridge
and Rautenbach 1987; Furlonger et al.1987). All species
affected by artificial lighting on the foreshore have large bodies
that are less manoeuvrable, except V. regulus (Bat Sense 2010).
The lack of manoeuvrability may force these species away from
lit areas as they are not able to capture their prey that are attracted
to the lights (Aldridge and Rautenbach 1987; Rydell 1992).
The impact of artificial lighting on species richness within
the reserve is demonstrated by the sample-based rarefaction
curve comparison (Fig. 2). Both curves reached an asymptote so
it is reasonable to assume that all species within the area were
0
1
2
3
4
5
6
7
8
9
10
11
12
250
Species
Number of samples
Unlit
Lit
0 50 100 150 200
Fig. 2. Sample-based rarefaction curves calculated from all identified
species within the lit and unlit treatments over the study period.
0
200
400
600
800
1000
1200
32
Number of calls
Temperature (°C)
Unlit
Lit
10 12 14 16 18 20 22 24 26 28 30
Fig. 3. Number of identified calls plotted against ambient temperature for
the lit and unlit treatments.
0
100
200
300
400
500
600
700
800
900
100
Number of calls
Percenta
g
e of ni
g
ht
0 102030405060708090
Unlit
Lit
Fig. 4. The total activity of all identified bat species during the sampling
period over the percentage of the night between lit and unlit treatments.
Note that 0 corresponds to sunset and 100 corresponds to sunrise.
DAustralian Mammalogy G. D. Linley
detected (Gotelli and Colwell 2001). The results demonstrate
that anthropogenic light in urban areas can result in lower bat
species richness within and around illuminated areas (Scanlon
and Petit 2008b; Hourigan et al.2010). By limiting the use of the
foreshore area by some bat species, lighting may lead to local
declines.
The effect of temperature
The relationships between temperature and the nocturnal activity
seen in bats around the foreshore (Fig. 3) have been previously
noted in other studies (Avery 1985; Rydell 1991; Milne et al.
2005; Milne 2006). Optimal ranges for bat activity during this
study are similar to those found by previous studies (Milne et al.
2005), but the differences in activity peaks between treatments
have not been reported on (Fig. 3). The difference between the
optimal temperature for the activity of bats at lit and unlit
treatments is likely to be caused by artificial lighting having
an effect on the availability and activity of insects at lower
temperatures (Rydell et al.1996; Milne et al.2005). Artificial
sources of light interfere with insect navigation systems, causing
phototaxis (Scanlon and Petit 2008a), which causes high densities
of insects to congregate around light sources (Danthanarayana
and Dashper 1986; Rydell 1992; Blake et al.1994). It is possible
that artificial lighting causes insects to become active at a lower
temperature which then attracts bats.
Bat activity is influenced by the availability of prey, which is
regulated by temperature (Rydell 1992); hence, both bats and
prey are most active during the warmer months (Scanlon and
Petit 2008a). This coincides with bat breeding cycles as young
must accumulate fat before the cooler months (Tidemann 1993;
Van Dyck and Strahan 2008). Certain bat species decrease their
activity over the winter periods (Turbill et al.2003; Milne et al.
2005), and studies in Adelaide have found that C. gouldii and
Mormopterus spp. are less active during the cooler months
whereas A. australis and C. morio remained active (Scanlon and
Petit 2008a).
Activity throughout the night
Bat activity is commonly observed to increase rapidly after
sunset and then steadily decrease throughout the night, similar
to what was observed at lit treatments (Taylor and Oneill 1988;
Adams et al.2005; Milne et al.2005;Turbill2008). This
pattern of bat activity is largely driven by the activity of
insects, which are known to be most active after sunset in lit
areas before dispersing throughout the night (Swift 1980;
Danthanarayana and Dashper 1986; Taylor and Oneill 1988;
Richards 1989; Milne et al.2005). The activity profiles at unlit
treatments appear to be very different from those found in
previous studies as the peak in activity occurs after sunset and
remains constant throughout the night before rapidly declining
before sunrise. The high activity at unlit treatments throughout
the night may be caused by the activity and density of insects
decreasing at lit treatments throughout the night due to
increased predation by bats or natural activity cycles of insects.
Bats that are not able to make use of increased insect densities
in lit areas may be forced to go in search of their prey in unlit
areas.
Conclusion
There have been several studies on the effects of artificial lighting
on bats, but these have produced contradictory results. Artificial
lighting reduced bat activity and species richness at all lit
treatments compared with unlit treatments, as has been observed
in some previous studies, whilst other studies have concluded that
lighting increases bat activity and species richness. All studies in
Australia have suggested that urbanisation and human-induced
disturbances have major implications for bat species richness.
Further increases in lighting installation will exacerbate the
existing negative impacts on bats. Where practicable and safe,
consideration should be given to sensor-activated lighting.
Councils should also consider minimising the use of mercury
vapour lighting, which attracts larger insect loads than low-
pressure sodium lamps. Caution must also be taken when
installing LED lighting as the impacts of this lighting type are not
fully understood. In areas of remnant vegetation in urban areas
that have lost connectivity to larger native areas, maintaining
unlit areas to allow for sufficient movement and exchange of
bats through the environment should be considered. Further
management and investigation should address the potential for
technological changes in the automatic illumination of public
areas, particularly patches of remnant vegetation, with the aim
of aiding the urban persistence of bats and their important
ecological functions.
Acknowledgements
Thanks to Bayside Friends of Native Wildlife, especially Elizabeth Walsh,
Anne Jessel and Michael Norris for their support and use of equipment.
Thanks to Denis Linley for help during fieldwork. Thanks to Lindy Lumsden
and Tanja Straka for their help with bat identification. Anne Jessel provided
software to help with the analyses of bats. Thanks to Tristan O’Brien, Calum
Cunningham, Tanja Straka, Caragh Threlfall, Rodney van der Ree, David
Marneweck, Professor Stewart Nicol and two anonymous reviewers who
provided helpful comments on improving this paper.
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