Biological Conservation 236 (2019) 17–28

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Biological Conservation

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Light pollution at the urban forest edge negatively impacts insectivorous T ⁎ Joanna K. Haddocka, , Caragh G. Threlfalla,b, Bradley Lawc, Dieter F. Hochulia a School of Life and Environmental Sciences, Heydon-Laurence Building, Science Road, The University of Sydney, NSW 2006, Australia b School of Ecosystem & Forest Sciences, The University of Melbourne, Richmond, VIC 3121, Australia c Department of Primary Industries, Level 12, 10 Valentine Avenue, Parramatta, NSW 2124, Australia

ABSTRACT

Connectivity and quality of vegetation in cities, including urban forests, can promote urban biodiversity. However the impact of anthropogenic pressures at the forest-matrix edge, particularly artificial light at night (ALAN), on connectivity has received little attention. We assessed the influence of artificial light at forest edges on insectivorous bats. We acoustically surveyed 31 forest edges across greater Sydney, Australia, half with mercury vapour streetlights and half in ambient darkness, and compared the assemblage and activity levels to urban forest interiors. We also sampled the flying insect community to establish whether changes in insect densities under lights drive changes in insectivorous bat activity. We recorded 9965 bat passes from 16 species or species groups throughout our acoustic survey. The activity of all bats, and bats hypothesised to be sensitive to artificial light, was consistently higher in forest interiors as opposed to edges. We found that slower flying bats adapted to cluttered vegetation or with a relatively high characteristic echolocation call frequency; Chalinolobus morio, Miniopterus australis, Vespadelus vulturnus, and Nyctophilus spp., were negatively affected by artificial light sources at the forest edge. The emergence time of Vespadelus vulturnus was also significantly delayed by the presence of streetlights at the forest edge. Conversely, generalist faster flying bats; Chalinolobus gouldii, ridei, Austronomous australis, Saccolaimus flaviventris, and Miniopterus orianae oceanensis, were unaffected by artificial light at the edge of urban forest, and used light and dark forest edges in a similar way. Insect surveys showed that larger lepidopterans seemed to be attracted to lit areas, but in low numbers. Artificial light sources on the edges of urban forest have diverse effects on bats and insects, and should be considered an anthropogenic edge effect that can reduce available habitat and decrease connectivity for light- sensitive species.

1. Introduction diversity (Aguilar et al., 2008) of native across a degraded urban landscape. Over the last few decades, research has focused on Urbanisation is one of the leading causes of biodiversity loss quantifying the characteristics of habitat remnants that maximize their worldwide (Czech et al., 2000; McKinney, 2006). Habitat fragmentation value to native plants and animals, including their size (Evans et al., (Fischer and Lindenmayer, 2007), along with noise pollution (Ortega, 2009), shape (Hawrot and Niemi, 1996), and connectedness (Keitt 2012), air pollution (Leonard and Hochuli, 2017), reduced water et al., 1997; McGarigal et al., 2002; Beninde et al., 2015). Calculating quality (Blakey et al., 2018), reduced vegetation cover and structure the amount of viable habitat existing in urban areas is a more complex (Threlfall et al., 2016; Threlfall et al., 2017) and artificial light (Hölker process. It must incorporate not only structural elements of forest areas, et al., 2010) all contribute to degrading natural habitat for urban such as their size and shape, but also functional connectivity (Kupfer, wildlife. Although only taking up a small percentage of the planet's 2012), and whether structural habitat features are actually used. An- terrestrial surface, urbanized areas are predicted to grow by 1.2 mil- thropogenic pressures, such as ALAN, may impact functional con- lion km2 by 2030, impacting many global biodiversity hotspots (Seto nectivity (Hale et al., 2012) by narrowing wildlife corridors and redu- et al., 2012). Hence, investment in the conservation of urban biodi- cing functional patch sizes, however, the extent to which this occurs is versity is essential for many reasons (Dearborn and Kark, 2010). poorly understood currently. Providing “stepping stones and corridors” of forests and native ve- ALAN is a growing problem, escalating by 6% each year (Hölker getation is a commonly suggested conservation action for urban bio- et al., 2010). It is caused by illumination from anthropogenic lighting, diversity (Dearborn and Kark, 2010; Beninde et al., 2015). Connecting and is most prevalent in urban areas (Falchi et al., 2016). Only rela- forest habitat in cities can mitigate species loss and biotic homo- tively recently has ALAN been widely discussed as a global threat to genisation (Lindenmayer and Nix, 1993; Fischer and Lindenmayer, biodiversity (Rich and Longcore, 2013; Gaston et al., 2015). Streetlights 2007) by facilitating movement (Dearborn and Kark, 2010) and genetic disrupt migration patterns (La Sorte et al., 2017), breeding cycles

⁎ Corresponding author. E-mail address: [email protected] (J.K. Haddock). https://doi.org/10.1016/j.biocon.2019.05.016 Received 18 September 2018; Received in revised form 5 May 2019; Accepted 14 May 2019 0006-3207/ © 2019 Elsevier Ltd. All rights reserved. J.K. Haddock, et al. Biological Conservation 236 (2019) 17–28

Fig. 1. Map showing location and distribution of forest patch sites (red triangles; n = 15 pairs of control interior and edge sites) and connected forest sites (yellow circles; n = 16 pairs of control interior and edge sites) relative to Sydney, Australia (inset). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

(Navara and Nelson, 2007) and predator-prey interactions (Gorenzel may be constrained by lights at the patch edge, spending a majority of and Salmon, 1995). Streetlights may also have an effect on the func- their foraging time within dark patches (Threlfall et al., 2013; Hale tional value and connectivity of proximal urban forests and vegetation. et al., 2015), and therefore reducing their functional urban habitat. Streetlights positioned along edges of urban wildlife corridors nega- Artificial light also markedly delays some species' emergence times tively affect some species whilst attracting others (Azam et al., 2018). from roosts (Jones and Rydell, 1994; Downs et al., 2003; Boldogh et al., The effects of artificial light at the forest edge for nocturnal wildlife 2007), meaning that their foraging time is reduced and the health of the may be significant; light may penetrate dark vegetation anywhere from population may at risk (Boldogh et al., 2007). There is a global pattern 50 m (Kempenaers et al., 2010) to 380 m (Pocock and Lawrence, 2005). emerging that ALAN negatively affects species adapted to foraging in Dark habitats are currently at risk from the edge effects of ALAN. either cluttered vegetation or along habitat edges, like Rhinolophus Insectivorous bats are an ecologically diverse group, and respond in hipposideros (Stone et al., 2012), Eptesicus serotinus (Azam et al., 2018), a variety of ways to urbanisation (Russo and Ancillotto, 2015). Some and Nyctophilus gouldi (Threlfall et al., 2013). The mechanistic drivers faster flying open-space adapted bat species find roosts in buildings of this light phobia in bats are not completely understood (Stone et al., (Kunz, 1982) and can commute across urbanized landscapes (Jung and 2015a, 2015b, Rowse et al., 2016) but could include predator avoid- Kalko, 2011). Conversely, other slower flying clutter-adapted bat spe- ance (Speakman, 1991; Stone et al., 2009; Lima and O'Keefe, 2013), cies commonly avoid urban areas, they cannot adapt to changes in roost morphology that leaves slower flying bats less able to exploit airborne availability and instead are reliant on networks of urban forest to sur- insect prey at lights compared with faster flying bats like Pipistrellus vive in cities (Basham et al., 2011). Artificial light is one anthropogenic pipistrellus (Haffner and Stutz, 1985) sensitivity to ultraviolet radiation pressure driving these diverse responses to urban areas. Ultraviolet emitted by some streetlights (Gorresen et al., 2015), or a combination radiation attracts high numbers of insects (van Grunsven et al., 2014) of these. Bats with many of these traits are declining in cities (Jung and and could offer urban feeding grounds for faster flying bat species Threlfall, 2016; Jung and Threlfall, 2018) hence research on the impact adapted to exploit this resource (Rydell, 1992; Rydell and Racey, 1995). of public lighting on this group is urgently required. These bats may be able to dive through the light cone when foraging We hypothesised that permanent streetlights along the forest edge (Blake et al., 1994) and perhaps able to evade any aerial predators that would reduce the activity of some insectivorous bats due to a decline in use the lit areas as hunting grounds. Conversely, slower flying clutter- habitat quality. We predicted that the activity of bats with slow flight adapted species often avoid artificially lit areas (Stone et al., 2012) and speed would be lower at forest edges with streetlights than edges with

18 J.K. Haddock, et al. Biological Conservation 236 (2019) 17–28 no lights. We also predicted that the activity of faster flying, light-ex- to sample the bat assemblage at 31 edge sites, and 31 dark interior ploiting bats would either be unaffected or be higher at edges with control sites, leading to 62 sites in total. We sampled between No- streetlights than edges with no lights. Finally, we predicted that total vember and December of 2016, the maternity season for bats when bat activity, and the activity of bats with slow flight speed, would both resource requirements and activity levels are highest. The light in- be higher in the forest interiors than the forest edges. tensity (lux) at each site was measured using a lux meter (QM1587; Reduction Revolutions Pty Ltd., Parramatta, Australia). We also mea- 2. Method sured insect biomass at all forest patches, at both the interior and edge site, using a black light intercept traps (Australian Entomological Sup- 2.1. Site selection plies, Murwillumbah, Australia, see Appendix A).

Our survey was carried out in Greater Sydney, a sub-tropical city 2.3. Bat recording with a population of over 4.5 million, on the east coast of New South Wales, Australia. Sydney has much remnant native forest abutting the The acoustic survey was carried out using Anabat II detectors (Titley urban matrix, both in continuous national parks and in smaller isolated Electronics, Ballina, Australia) placed on the ground with the high patches surrounded by housing (Benson and Howell, 1995). Two main frequency microphone positioned 1 m above the ground and pointing geologies in the Sydney region, shale and sandstone, have led to dif- upwards at a 45° angle to record all echolocation calls of passing bats. ferent levels of primary productivity and soil fertility across the city, We used one detector per site, and predicted to still record high flying fl and these have been shown to in uence insect prey and bat diversity in bats to be recorded due to louder calls from those species (Jung and this region (Threlfall et al., 2011, Threlfall et al., 2012a, 2012b). Hence, Kalko, 2011). At artificially lit edges the detector was placed no further we only included sites on full or majority sandstone with transitional than 3 m from the base of the streetlight pole, no > 3 m away from the ff soil type to control for this e ect of geology. edge of the forest. At both the edge and interior sites, the microphone was pointed parallel down the forest edge and down the interior track 2.2. Experimental design or path, respectively, to optimise the amount of habitat sampled (Law et al., 1998; Threlfall et al., 2012a, 2012b). Each of the 62 sites were We conducted an acoustic survey along 31 forest edge sites (Fig. 1); sampled between 3 and 5 consecutive nights (average 4.35 nights ± s.e. 16 of these sites were at the edges of connected forest (forest connected 0.19, due to unexpected equipment failure we did not manage to record to large natural areas, Fig. 2a), and 15 were on the edges of isolated for 5 nights at each site), totaling 270 recording nights across the entire forest patches (Fig. 2b), > 30 ha in size, but surrounded on all sides by survey. A maximum of eight sites were surveyed on the same night, urban matrix. Of all connected patch edge sites, half the sites (n = 7) where the edge and its respective interior control were concurrently had 80 W mercury vapour streetlights along the edges (light intensity of sampled. The detectors passed the data through a Zero-Crossings In- 10.65 lx ± 1.89) and half of the sites (n = 8) were dark (light intensity terface Module (ZCAIM; Titley Electronics). The acoustic files collected of 0.52 lx ± 0.34). Of all forest patch edge sites, half the sites (n = 8) during the survey were processed using Anascheme and a bat call had 80 W mercury vapour streetlights along the edges (light intensity of identification key developed for Sydney bats (Adams et al., 2010). For a 10.20 lx ± 1.23) and half of the sites (n = 8) were dark (light intensity bat call to be identified to species level, three or more pulses were re- of 0.97 lx ± 0.52). All edge sites were defined as roads or pathways quired and have characteristics that fall within the program's para- over 4 m in width with dense vegetation on only one side. Dark edges meters for that species. A pass was defined as at least three valid pulses were defined as 30 m of uninterrupted dark conditions (artificial light with a minimum of 6 pixels per pulse. Successful species identifications levels comparable to ambient darkness and no external light sources on were made only when a minimum of 50% of pulses within a pass were nearby houses). Artificially lit edges were defined as 30 m of 80 W identified as the same species (Adams et al., 2009; Threlfall et al., mercury vapour lights along one side of the road, with the streetlights 2012a, 2012b). The calls identified as Chalinolobus dwyeri, Falsistrellus at a median distance apart of 12.1 m. Usual low-level urban lighting tasmaniensis, Nyctophilus spp., Saccolaimus flaviventris, Scoteanex ruep- from houses in the surrounding matrix was present at both dark and pellii and Scotorepens orion are known to be complex or rare and were light edges. We additionally located control sites in the dark interior of manually checked against known parameters and confirmed or re- all 31 sites (lux of 0.55 ± 0.20), which were located along an internal identified (Adams et al., 2010). In addition, calls were run through a edge comprising a pathway or track (2 m typical width) between 400 m species filter in AnaScheme which is specifically designed to identify and 1 km perpendicular from the sampled forest edge. This allowed us calls of Chalinolobus gouldii with alternating frequency. The call

Fig. 2. Images taken from Google Earth of two of the sites in this study demonstrating the distinction between the patch and connected sites, with the green marker showing the position of the detector at the forest interior site and the blue marker showing the position of the detector at the forest edge site, a) Patch site: Cumberland State Forest, Sydney, b) Connected site: St Ives, Garigal National Park. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

19 J.K. Haddock, et al. Biological Conservation 236 (2019) 17–28

Table 1 taking an average of the percentages across all the nights sampled. All bat and insect response variables included in generalized linear mixed Although we avoided surveying on full moon, logistical limitations models. meant that we could not control for the moon cycle completely. Category Measurement Response variable 2.6. Statistical analysis Bat activity Average activity; All bats The light-exploiting group All analyses were carried out in SPSS (version 22, SPSS Inc., Chalinolobus gouldii Ozimops ridei Chicago, USA). For each of the 31 sites and their dark interior urban The light-sensitive group forest controls, average activity and total species richness was calcu- Nyctophilus spp. lated for the bat assemblage, for the light-exploiting functional group, Vespadelus vulturnus for the light-sensitive functional group and for each individual species. Bat species richness Average species richness; All bats For light-exploiting group Average activity was calculated by summing the total number of For light-sensitive group identified passes detected at that site during the recording time, and Bat emergence times Average time until first All bats then dividing by the number of sampling nights at that site. Total activity; species richness was calculated by counting the number of species de- For the light-exploiting tected at that site over the recording time. To calculate the time until group fi For the light-sensitive group rst activity, and therefore potential delay or disturbance to the bats, Chalinolobus gouldii we located the earliest call for a functional group or species at a par- Ozimops ridei ticular site and then subtracted that time from the time of sunset that Nyctophilus spp. day (EST), leaving the numbers of minutes after sunset that the call was Vespadelus vulturnus Insect abundance Averages; Number of Lepidoptera recorded. When discussing the comparison of a response variable across collected light treatments, we are including light edges, dark edges and dark Biomass of Lepidoptera interiors. Generalized linear models (GLMs) were used to establish statistical differences in both lux level and vegetation extent between the three ff characteristics of Nyctophilus gouldi and Nyctophilus geo royi are indis- light treatments, with the habitat treatment (connected or patch) and tinguishable using the AnaScheme method and so were pooled as one light treatment (light edge or dark edge) as fixed effects. fi taxon; Nyctophilus spp. Only species that were positively identi ed A series of correlations were used to assess whether average moon fi using the key, lters and manual checking were included for further illumination across recording time, or the percentage of sandstone soil fi analysis to eliminate any bias caused by using partially identi ed spe- within a 250 m radius of each site were significant predictors of bat cies. activity or species richness. As none were significant predictors of species richness or total bat activity, they were omitted from further 2.4. Assignment to functional groups models. A series of GLMs were used to assess if emergence times of C. gouldii, O. ridei, V. vulturnus and Nyctophilus spp. (the two most com- Assignment of each species to a functional group was based on monly detected of each response group) were affected by moon illu- morphological traits and foraging styles (Rhodes, 2002, Haddock et al. mination, moon illumination has been linked to emergence of bats. As in press). Chalinolobus gouldii, Ozimops ridei, Austronomous australis, no response variables were significantly affected by any environmental Saccolaimus flaviventris, and Miniopterus orianae oceanensis were cate- or weather variables, all were omitted from further models. gorised as light-exploiting due to their open-space foraging area pre- We then used a series of GLMMs to compare bat and insect response ference, or edge-space foraging area preference with low or medium variables (Table 1) across light treatments. We only included sites echolocation call frequency (Rhodes, 2002). Light-exploiting bats may where both the edge and interior had a record for that species. Other tend to use the well-lit areas to forage around or commute past. The sites were excluded from this analysis. The GLMMs allowed us to in- light-sensitive group consisted of both maneuverable edge-space fora- clude the site (which contained both the edge and dark interior pair) as ging species with high echolocation call frequency (Chalinolobus morio, a random effect, and the habitat treatment (connected or patch) and Miniopterus australis, Vespadelus vulturnus; Adams et al., 2009) and also light treatment (light edge or dark edge) as fixed effects. We considered species adapted to cluttered vegetation with a slower flight pattern a variety of response variables (Table 1). We then also carried out (Rhinolophus megaphyllus and Nyctophilus spp., consisting of two species analyses on the two most commonly recorded light-exploiting species; Nyctophilus gouldi and Nyctophilus geoffroyi that have echolocation calls C. gouldii and O. ridei, and the two most commonly recorded light- indistinguishable from the other) that may avoid lit areas. We based sensitive species; V. vulturnus and Nyctophilus spp. as activity of other these groupings on known response groups found in previous studies, species was too low or too patchy in distribution to allow for adequate however we acknowledge that there may be species that do not ne- analysis. cessarily fit this trend. We used Poisson distribution models with a log link function and robust variance estimates for all but two of the GLMMs as the data did 2.5. Measurement of environmental variables not follow a normal distribution (Yau and Kuk, 2002), the exceptions were light-sensitive bat activity and Nyctophilus spp. activity. Light- The percentage of native vegetation cover (> 3 m tall) within a sensitive bat activity was low across all treatments and so a negative radius of 250 m of each site was calculated using Arc Map (ESRI, binomial distribution with a log link function with robust variance es- Redlands, USA, ver. 10.2) and was calculated through intersecting GPS timates was used in the GLMM. Soft-calling Nyctophilus spp. were re- points of our sites with the GIS layer ‘The Native Vegetation of the corded in such low numbers that activity of this taxa was converted to Sydney Metropolitan Area - Version 3, VIS_ID 4489’ (NSW Office of presence-absence data, and a GLMM was run using a binomial dis- Environment and Heritage, Sydney). This area has been found to be tribution with a probit link function, again with robust variance esti- indicative of local habitat as shown in previous studies (Lacoeuilhe mates. All post hoc tests were Fisher's Least Signi ficant Difference. et al., 2014). The same method was used to calculate the percentage of When light-sensitive or light-exploiting bats were detected at a site, sandstone and transitional sandstone soil type within the 250 m radius we wanted to know what proportion of the calls were detected along of each site. Average moon illumination was calculated by noting the the edge compared to the interior for that site, as an indicator of percentage of the moon's face visible each night, and then for each site whether edges or interior were more preferred by each bat group. For

20 J.K. Haddock, et al. Biological Conservation 236 (2019) 17–28 each edge and interior site pair, we therefore calculated the proportion Table 2 of calls recorded at the forest edge compared that site's interior control Results of GLMM with habitat type and light treatment as fixed effects, and site for both light-sensitive and light-exploiting functional groups. A one as a random effect, with response variables listed on the far left column, and the way ANOVA was used to compare the proportion of calls recorded at dark interior control treatment and patch treatment as the reference categories. light edges and at dark edges for both light-exploiting and light-sensi- Parameter Estimate Standard t value p value tive groups. error

Total bat activity 3. Results Intercept 2.834 0.3099 9.145 < 0.001 Connected forest versus 0.079 0.4288 0.185 0.854 We recorded 9965 bat passes throughout our acoustic survey, with patch 62.4% identified to species or species group level. We detected 16 Light edge versus interior −0.814 0.0765 −10.642 < 0.001 − − species or species groups, seven of which have a conservation status of Dark edge versus interior 0.604 0.0791 7.629 < 0.001 Average bat species richness vulnerable under the NSW Biodiversity Conservation Act 2016; Intercept 4.475 0.5258 8.511 < 0.001 Chalinolobus dwyeri, Falsistrellus tasmaniensis, Miniopterus orianae ocea- Connected forest versus 0.330 0.6009 0.550 0.585 nensis, Miniopterus australis, Micronomous norfolkensis, Scoteanex ruep- patch − − pellii, Saccolaimus flaviventris. Light edge versus interior 0.518 0.7435 0.696 0.489 − − fi ff Dark edge versus interior 0.577 0.7277 0.793 0.431 Arti cially lit edges, dark edges and interiors all di ered sig- Average light-sensitive species nificantly from each other in the amount of vegetation cover within richness 250 m of each site. Interior control sites had greater vegetation extent Intercept 2.256 0.3569 6.319 < 0.001 than dark edges (p < 0.005), and light edges had greater vegetation Connected forest versus −0.044 0.3951 −0.112 0.911 extent than dark edges (p < 0.05). Forest patches had significantly less patch Light edge versus interior −1.475 0.4515 −3.268 0.002 vegetation cover within a 250 m radius of each site than connected Dark edge versus interior −1.133 0.3953 −2.865 0.007 forest (p < 0.001). Artificially lit edges were significantly brighter Average light-sensitive species

(F2,59 = 157.9, p < 0.005) than dark edges (p < 0.005) and dark in- activity teriors (p < 0.005). Intercept 1.379 0.5022 2.745 0.009 Connected forest versus −0.262 0.6275 −0.417 0.679 Echolocation calls of bats were recorded at all sites. Light-exploiting patch bat species were detected at 95% of sites; with 96% of edge sites and Light edge versus interior −2.790 0.4203 −6.638 < 0.001 93% of interior sites. Light-sensitive bat species were detected at 51% of Dark edge versus interior −0.305 0.1991 −1.531 0.134 sites, including 41% of edge sites, and 61% at interior sites. Average Nyctophilus spp. Total bat activity was significantly different among light treatments, activity fi Intercept 1.872 0.6269 2.985 0.005 with light edges and dark edges having signi cantly lower activity than Connected forest versus −0.854 0.5699 −1.498 0.144 dark interior sites (Table 2). Total bat activity was not significantly patch different between light and dark edges (p > 0.05; Fig. 3a). Species Light edge versus interior −2.053 0.6654 −3.086 0.004 − − richness was not significantly affected by light treatment (Table 2). Dark edge versus interior 1.540 0.5836 2.639 0.013 Average V. vulturnus activity Intercept 1.282 0.6090 2.105 0.043 3.1. Light-sensitive group responses Connected forest versus −0.533 0.7454 −0.714 0.480 patch Dark interior sites supported higher light-sensitive species richness Light edge versus interior −3.100 0.5899 −5.256 < 0.001 − − (Table 2), with no difference between light edges and dark edges Dark edge versus interior 0.061 0.2235 0.272 0.787 Average light-exploiting species (p > 0.05). Similarly, dark interior sites supported the highest light- richness sensitive bat activity (Table 2), but then dark edges supported higher Intercept 2.139 0.2016 10.610 < 0.001 activity that light edges (p = 0.037, Table 2, Fig. 3b). A similar pattern Connected forest versus −0.019 0.2304 −0.084 0.934 was seen for the most commonly recorded light-sensitive species; Ves- patch Light edge versus interior 0.338 0.2851 1.185 0.241 padelus vulturnus activity was highest at dark interior sites, lower at Dark edge versus interior 0.058 0.2790 0.208 0.836 dark edges, and lowest at light edges (p = 0.02, Table 2; Fig. 3f). The Average light-exploiting species activity of Nyctophilus spp. was again highest at the dark interior sites, activity and significantly lower at both dark and light edges (Table 2). There Intercept 2.581 0.3339 7.730 < 0.001 − − was no significant difference between the Nyctophilus spp. activity at Connected forest versus 0.004 0.4623 0.008 0.994 patch light and dark edges (p > 0.05). Light edge versus interior −0.630 0.0824 −7.653 < 0.001 A higher proportion of the light-sensitive group's echolocation calls Dark edge versus interior −0.740 0.0902 −8.208 < 0.001 were recorded at the dark edges than at the light edges, when compared Average C. gouldii activity with the proportion recorded at that site's dark interior site Intercept 2.214 0.4017 5.512 < 0.001 Connected forest versus −0.130 0.5573 −0.232 0.817 (F = 4.96, p = 0.038; Fig. 4). Where light-sensitive species were 1,23 patch present, they were more likely to be active at the edge if it was dark Light edge versus interior −0.736 0.0886 −8.308 < 0.001 than if it was artificially lit. Dark edge versus interior −0.823 0.1071 −7.680 < 0.001 Average O. ridei activity 3.2. Light-exploiting group responses Intercept 0.040 0.4916 0.082 0.935 Connected forest versus −0.182 0.6445 −0.282 0.779 patch The species richness of the light-exploiting group was not affected Light edge versus interior 0.644 0.3634 1.772 0.082 by light treatment (Table 2). Dark interior sites supported higher light- Dark edge versus interior −0.489 0.1863 −2.626 0.011 exploiting bat activity than light and dark edges (Table 2, Fig. 3c), and there was no difference between dark and light edges (p > 0.05). The activity of C. gouldii followed a similar pattern, with activity highest at edges (Table 2, Fig. 3e), lower at dark edges, and lowest at dark interior fi ff dark interior sites (Table 2, Fig. 3d), with no difference between light sites (p = 0.007). There was no signi cant di erence in the proportion and dark edges (p > 0.05). However, the activity of O. ridei followed a of the light-exploiting group's echolocation calls recorded at light edges different pattern (Fig. 3e); activity of this species was highest at light and dark edges, when compared with the proportion recorded at that

21 J.K. Haddock, et al. Biological Conservation 236 (2019) 17–28

a a b a b c

a a b a a b

e) Ozimops ridei activity f) Vespadelus vulturnus activity

a b c a b b )

g) Species richness of light-sensitive group g h) Biomass of lepidopterans

a a b a b b pidopteran biomass (m e le Average species richness Averag

(caption on next page)

22 J.K. Haddock, et al. Biological Conservation 236 (2019) 17–28

Fig. 3. Plots showing marginal means ( ± 1 s.e.) after controlling for site. Panel a. Bat activity compared across light treatments; panel b. Activity of the light- sensitive group compared across light treatments; panel c. Activity of the light-exploiting group compared across light treatments; panel d. Activity of C. gouldii compared across light treatments; panel e. Activity of O. ridei compared across light treatments; panel f. Activity of V. vulturnus compared across light treatments; panel g. Species richness of the light-sensitive group compared across light treatments; panel h. Lepidopteran biomass (mg) compared across light treatments. Statistically significant differences when comparing variable measurements between treatments are depicted using differing letters (a, b and c).

70 Table 3 Results of GLMM with habitat type and light treatment as fixed effects, and site 60 as a random effect, with response variables listed on the far left column, and the dark interior control treatment and patch treatment as the reference categories. 50 Parameter Estimate Standard t value p value 40 error

Minutes until first bat activity 30 Dark edges Intercept 4.967 0.1635 30.383 < 0.001 Light edges Connected forest versus patch −0.089 0.2312 −0.386 0.700 20 Light edge versus interior −0.010 0.0289 −0.352 0.726 Dark edge versus interior 0.021 0.0278 0.744 0.460 10 Minutes until first light-sensitive group activity

Percentage of bat calls recorded at site edges at site recorded calls of bat Percentage 0 Intercept 5.386 0.1347 39.973 < 0.001 Light tolerant Light sensitive Connected forest versus patch −0.013 0.1718 −0.077 0.939 Functional group Light edge versus interior 0.265 0.0397 6.687 < 0.001 Dark edge versus interior 0.232 0.0380 6.092 < 0.001 Fig. 4. Average percentage ( ± se) of light-sensitive and light-exploiting func- Minutes until first Nyctophilus tional group echolocation calls recorded at light edge sites and at dark edge spp. activity sites. Calculated by combining calls for each site with calls from associated Intercept 5.500 0.1772 31.047 < 0.001 interior control site and then calculating the percentage of the total calls re- Connected forest versus patch 0.147 0.2225 0.659 0.518 Light edge versus interior 0.465 0.0615 7.563 < 0.001 corded at the edge. Dark edge versus interior 0.462 0.0591 7.825 < 0.001 Minutes until first V. vulturnus activity site's dark interior site (F1,2 = 1.08, p > 0.05; Fig. 4). Intercept 5.413 0.1748 30.962 < 0.001 Habitat type, whether the forest was an isolated patch or connected Connected forest versus patch 0.151 0.2275 0.664 0.514 fi ff to other forested areas, had no signi cant e ect on the activity or the Light edge versus interior 0.252 0.0482 5.228 < 0.001 species richness of the bat assemblage, the light-sensitive group, or the Dark edge versus interior 0.023 0.0559 0.411 0.685 light-exploiting group (Table 2). Minutes until first light- exploiting group activity Intercept 5.064 0.0813 62.273 < 0.001 Connected forest versus patch −0.045 0.1027 −0.442 0.660 3.3. Temporal activity patterns Light edge versus interior 0.054 0.0974 0.557 0.580 Dark edge versus interior 0.050 0.0975 0.517 0.607 Overall, there was no difference in first recording time between Minutes until first C. gouldii light treatments across species (Table 3), however differences were activity Intercept 202.150 16.7063 12.100 < 0.001 found between functional groups. Connected forest versus patch −53.183 20.6049 −2.581 0.013 The light-sensitive functional group was active significantly earlier Light edge versus interior −15.014 23.1303 −0.649 0.519 at interior sites when compared with dark and light edges (Table 3). Dark edge versus interior 26.846 24.3959 1.100 0.276 fi There was no significant difference between the first recordings at light Minutes until rst O. ridei activity and dark edges (p > 0.05). Nyctophilus spp. showed the same pattern Intercept 5.272 0.1409 37.419 < 0.001 (Table 3), again with no difference between first recordings at light and Connected forest versus patch −0.129 0.1919 −0.672 0.506 dark edges (p > 0.05). There was no difference between first recording Light edge versus interior 0.176 0.0333 5.291 < 0.001 times of Vespadelus vulturnus at both dark interior sites and dark edges Dark edge versus interior 0.376 0.0419 8.961 < 0.001 (Table 3). However, first recording time was significantly later at light edges than at dark interior sites (Table 3) and dark edges (p = 0.008). 3.4. Insect responses Overall, the first activity of the light-exploiting functional group was not significantly different across light treatments (Table 3), but Lepidoptera biomass was significantly affected by light treatment there were species-specific responses. First activity of the light-ex- (Fig. 3h); biomass was higher at light edges than dark interior sites ploiting C. gouldii was not significantly different across light treatments, (Table 4) and posthoc tests showed that biomass at light edges was however it was first recorded significantly earlier in the night in con- higher than at dark edges also (p < 0.001). The average number of nected forest than in patches (Table 3). Emergence time in connected Lepidoptera caught at dark interior sites did not differ from the number forest averaged 151.9 ± 9.1 min after sunset, versus caught at dark edges (Table 4). However, the number of Lepidoptera 203.1 ± 16.9 min after sunset in isolated forest patches. The time of caught at light edges was significantly lower than dark interior sites first activity for O. ridei was significantly earlier at dark interior sites (Table 4), and posthoc tests showed that the number of Lepidoptera at than at both light and dark edges (Table 3). O. ridei was also recorded light edges was lower than at dark edges also (p = 0.012). significantly earlier at light edges than at dark edges (p = 0.001). Throughout the night, the difference in the activity of the light- sensitive group between light and dark edges was not as pronounced as 4. Discussion the difference between interior sites and pooled edge sites. The activity of the light-sensitive group was higher at interior sites throughout the Our study demonstrates the disruptive effects of artificial light at the night, and was at its highest just after sunset (Fig. 5). edges of urban forest on light-sensitive and light-exploiting in- sectivorous bats. Our findings are consistent with research that artificial

23 J.K. Haddock, et al. Biological Conservation 236 (2019) 17–28

Fig. 5. Activity of light-sensitive bats throughout the night. This is calculated by noting sunset and sunrise each night of the survey and calculating what percentage of the night had elapsed when each call was recorded. The graph shows the number of calls recorded within each 10% increment throughout the night. The bottom graph shows the combined data from the edge sites compared with the data from the interior sites.

Table 4 Whether the forest was connected to other forest or in an isolated Results of GLMM with habitat type and light treatment as fixed effects, and site patch, had little influence on the effects of artificial light at the forest as a random effect, with response variables listed on the far left column, with edge. Chalinolobus gouldii were recorded earlier in the night in con- patch and dark edge treatment as reference categories. nected forest than in isolated patches, suggesting that as well as C. ff fi Parameter Estimate Standard t value p value gouldii being una ected by arti cial lights at the forest edge, this spe- error cies may be more likely to roost in connected forest and hence emerge earlier there. Our findings suggest that the bat assemblage appears re- Biomass of Lepidoptera latively similar across all forest habitat in this city, and this needs Intercept 5.731 0.0955 60.003 0.000 Connected forest versus patch 0.143 0.3798 0.375 0.710 further investigation as it would inform urban conservation strategy. Light edge versus interior 0.244 0.0309 7.896 0.000 Recent multi-taxa research concluded that large connected patches Dark edge versus interior −0.104 0.0262 −3.979 0.000 of vegetation are critically important for urban biodiversity (Beninde Average number of Lepidoptera et al., 2015). Our data supports this, showing that total bat activity, the caught Intercept 3.209 0.1598 20.080 0.000 activity of the light-sensitive species and C. gouldii were consistently Connected forest versus patch −0.533 0.6323 −0.843 0.407 higher on forest interiors when compared with edges. Nyctophilus gouldi Light edge versus interior −0.546 0.1289 −4.239 0.000 were rarely recorded anywhere but bushland interiors, demonstrating Dark edge versus interior 0.126 0.0845 1.495 0.146 the importance of forest interiors for bat diversity in cities. With regards to insect trapping, Lepidoptera numbers were lowest at light edges, suggesting that the biomass was made up of fewer but light has a negative effect on certain species in ecologically sensitive larger individuals. We conclude that our findings are consistent with habitat (Straka et al., 2016) and that artificial light at the urban forest others (Pintérné and Pödör, 2017), and may have been due to street- edge contributes to a loss of functional connectivity (LaPoint et al., lights in the lit conditions outshining our light traps, and attracting 2015). Streetlights at the forest edge negatively affected the activity of most of Lepidoptera away from the trap. In future studies, suction traps the putative light-sensitive group of bats. Sydney's smallest species, V. (Shortall et al., 2009), sticky traps, malaise traps (Hosking, 1979; vulturnus was particularly negatively affected by light, being less active Hallmann et al., 2017) or camera traps (Rydell, 1992) may be better and emerging later at artificially lit edges when compared with dark alternatives for sampling phototactic insects in artificially lit condi- edges. Despite light edges having greater vegetation cover with 250 m, tions. bat activity and richness was still lower here than at dark edges. Available functional habitat in urban forests is reduced by artificial 4.1. Mechanisms driving light sensitivity in insectivorous bats light, and with some species unable to cross lit areas (Hale et al., 2015), urban biodiversity may continue to decline unless the degrading im- In line with our predictions, V. vulturnus was light sensitive, using pacts of ALAN are addressed. forest edges less so when they were lit. Thus ALAN may be contributing Species predicted to be light-exploiting were either unaffected by to edge effects and habitat loss for this species within cities (Gonsalves streetlights along the forest edge, such as C. gouldii, or increased in and Law, 2017). Of all V. vulturnus calls, 27% were recorded at dark activity, such as O. ridei. Ozimops ridei showed the strongest positive edges, and only 2% were recorded at artificially lit edges. This species response to artificial light at the forest edge, with higher activity and was active significantly later at lit edges than at dark edges. Vespadelus earlier emergence time at artificially lit edges than dark edges, con- vulturnus is an edge-space foraging bat, although it is quite maneuver- sistent with previous findings (Threlfall et al., 2013). The species-spe- able and so may not be as dependent on edges and flyways as other cificdifferences within the a priori fast flying functional group suggest edge-space foraging bats (Law et al., 2011). Vespadelus vulturnus also that responses to ALAN may be more complex than basic guild-related flies closer to the ground in thinned as opposed to unthinned under- responses. Our data implies that other aspects of the urban environment storey, perhaps for cover and protection (Adams, 2012). Despite these way exert more influence on those species. flight preferences, our data shows that this bat uses forest edges in

24 J.K. Haddock, et al. Biological Conservation 236 (2019) 17–28 cities, and is negatively impacted by light sources along those edges. Its environmental niches that allow bat species to co-exist. edge-space foraging preference makes V. vulturnus, and other slower- flying edge-space foragers, susceptible to habitat loss and decline from 4.4. Light as an edge effect streetlights at the forest edge. This is consistent with previous research that failed to detect V. vulturnus in small pockets of urban forest in Artificial light as an edge effect has been studied in combination highly urbanized parts of Sydney (Gonsalves and Law, 2017). with traffic noise, mostly in the context of road ecology. In this context In comparison, 92% of calls identified as Nyctophilus spp., the spe- it has strong negative effects on many nocturnal taxa (Kempenaers cies group adapted to foraging in cluttered vegetation, were recorded at et al., 2010; Hale et al., 2015; Azam et al., 2018). species interior sites. Although Nyctophilus spp. have been observed using open richness increases at the point where light levels return to ambient and edge habitat in woodland (Brigham et al., 1997), our study con- darkness, and bird diversity increases with distance from the road firms low activity of this species at the urban forest edge, regardless of (Pocock and Lawrence, 2005). Small and narrow urban forest could be whether streetlights were present or not. Artificial light at the forest highly light-impacted habitat (Azam et al., 2018). In our study, artifi- edge did not further reduced the low activity of Nyctophilus spp. at these cial light at the forest edge negatively impacted species that may al- locations. Our findings are consistent with a previous study that found ready be struggling to survive in cities. Functional diversity in im- that movements of these taxa were mostly restricted within the bounds portant urban forest patches and corridors may be significantly of an urban forest remnant (Threlfall et al., 2013). These taxa appear to impacted, driven by an alteration of the artificial lighting regime. In- be light-sensitive (Threlfall et al., 2013), but the lack of edge habitat use vestigation into the zone of influence from permanent artificial light suggests both habitat fragmentation and disruption in the connectivity sources on other taxa is a research priority. of dark vegetation across cities have critically impacted the urban survival of this group. Some bats, including Nyctophilus spp., could have 4.5. Lunar phobia and light phobia retained a sensitivity to ultraviolet light (Gorresen et al., 2015), and this may cause these species to avoid streetlights emitting ultraviolet, like Light phobia could be driven by an innate lunar phobia, with the ones in this study. changing moon phase and the brightness of the moon linked to the emergence time and behaviour of some light-sensitive species such as V. 4.2. The importance of dark connected forest for urban bats vulturnus and others (Law, 1997; Saldaña-Vázquez and Munguía-Rosas, 2013). Lunar phobia is linked to morphological traits associated with Our study reveals that total bat activity was higher at dark interior foraging strategy; slow-flying bats respond more negatively to bright sites than at either light or dark forest edges, confirming previous re- moonlight (Saldaña-Vázquez and Munguía-Rosas, 2013). These species search that dark forest is crucial for the persistence of some in- are also more likely to emerge later in the evening (Jones and Rydell, sectivorous bats in cities (Threlfall et al., 2013; Hale et al., 2015; Straka 1994), theoretically because they are adapted to hunting prey available et al., 2016; Azam et al., 2018), Haddock et al., in press). Activity at in the darkest part of the night and so avoid crepuscular predator peaks. these dark forest interior sites peaks early in the night, suggesting that Our data confirms this trend, that slow flying bat species avoid artificial this is where most bats roost in hollow trees. Throughout the course of light. This morphological group may be responding negatively to arti- the night, the majority of calls were recorded at interior sites, whether ficial light as they have evolved to respond negatively to moonlight. looking at light-sensitive or light-exploiting functional groups. Our The species-specificdifferences here warrant further research. Faster findings provide support for the conservation of dark forest in cities, flying bats, those that appear more exploiting of artificial light, are less and reconfirm the importance of connectivity between natural areas affected by moonlight (Saldaña-Vázquez and Munguía-Rosas, 2013). (Dearborn and Kark, 2010; Goddard et al., 2010; Hale et al., 2012; These species may be pre-adapted, or at least resilient, to artificially lit Beninde et al., 2015), particularly dark corridors for light-sensitive environments. However much like the drivers of light phobia in bats, species (Bolívar-Cimé et al., 2013; Hale et al., 2015; Straka et al., 2016). the mechanisms driving lunar phobia are difficult to pinpoint. Periods of bright moonlight are associated with reduced levels of insect prey 4.3. Artificial light altering the competition for resources (Lang et al., 2006), and may leave bats more vulnerable to predation (Law, 1997), particularly important for slow flying bats. Very few stu- Niche differentiation between bat species can sometimes be subtle dies have provided evidence that predation risk for bats increases under (Krüger et al., 2014) as bats exploit slightly different insect prey in si- moonlit skies, even though it is discussed frequently in the literature milar habitat. Clutter-adapted bats will glean moths and beetles from (Saldaña-Vázquez and Munguía-Rosas, 2013; Stone et al., 2015a, the ground and from leaves, whereas open-space adapted bats will 2015b). Future studies teasing apart the causes of artificial light phobia, pursue prey on the wing (Denzinger and Schnitzler, 2013). Artificial changes in food availability or predation risk, would elucidate the light sources are known to attract insect prey out of dark habitat and mechanisms influencing lunar and light phobia in bats. deplete foraging grounds for light-sensitive species (Rydell, 1992; Rydell and Racey, 1995; Arlettaz et al., 2000). Our data supports this 4.6. Future directions and conclusions effect, where overall moth biomass was significantly higher at lit edges compared to dark edges and interior sites. Overall moth numbers did In urbanized Sydney, five species are at particular risk of ALAN not follow the same pattern, suggesting that larger insects dominated degrading viable habitat. Elsewhere the impact may be greater, for near streetlights. This potential “vacuum cleaner effect”, where pho- example; locations like tropical Barro Colorado Island in Panama are totactic insects migrate out of dark forest and towards artificial light, home to a much higher proportion of slower flying bat species may be decreasing the amount of available prey to bats restricted to (Denzinger et al., 2017). If the parameters of light sensitivity discussed dark areas, making it harder for them to persist in cities (Arlettaz et al., here are applied to other bat communities, many more species could be 2000). Investigation is needed into the extent of this depletion of dark identified as at risk of habitat loss due to urban lighting at the edges of foraging grounds for light-sensitive bats. Our data shows that light- natural forest. This is an issue for particular consideration in expanding sensitive bats are less likely to use artificially lit edges, and would cities and peri-urban areas. Lighting near ecologically important areas, therefore be less able to access the increased insect biomass there. Si- like drinking troughs, is already established as having a disruptive ef- milar to previous experiments, artificial light sources could be creating fect on bat drinking behaviours (Russo et al., 2017; Russo et al., 2018). foraging areas that mainly light-exploiting bats can exploit (Arlettaz Foraging by many bats species is affected also, and like others et al., 2000; Stone et al., 2015a, 2015b). ALAN, particularly artificial (Spoelstra et al., 2015; Straka et al., 2016), we recommend avoiding the light sources at forest edges in cities, may be disrupting the important installation of streetlights near ecologically sensitive areas in cities,

25 J.K. Haddock, et al. Biological Conservation 236 (2019) 17–28 such as native forests and wetlands. Other mitigation strategies, such as interior control sites, consistent with previous research (Eisenbeis and part night lighting, may be an alternative to constant lighting (Azam Eick, 2010; Barghini and Souza de Medeiros, 2012; van Grunsven et al., et al., 2015); but need to be turned off early enough in the night to 2014; Plummer et al., 2016). However secondly, Lepidoptera numbers successfully mitigate the impact on vulnerable species. If lighting near were lowest at light edges, suggesting that the biomass was made up of ecologically important forest is necessary, red lights (usually between fewer but larger individuals. For light-exploiting, larger aerial-hawking 620 and 750 nm) have been shown to have minimal effect on a variety bats, moths attracted to artifi cially lit areas may therefore comprise an of mammal taxa (Spoelstra et al., 2015; Spoelstra et al., 2017), although energy-rich food source of larger insect prey. Our result of lower their suitability as a bat-friendly alternative is controversial (Voigt numbers of moths around lights has been found in another study et al., 2018) and needs further testing. LED technology allows lights to (Pintérné and Pödör, 2017), which found a higher number of lepi- be manufactured to emit specific spectra, which has recently been dopteran in dark, semi-rural areas than in well-lit, urban areas. Our found to be useful for minimising disruption for bats (Haddock et al., in data may have been due to streetlights in the lit conditions outshining press). Research could be used to help manufacturers create lights with our light traps, and attracting most of Lepidoptera away from the trap the least disruptive spectra for nocturnal biodiversity. However, con- (Pintérné and Pödör, 2017). Although it seems illogical to sample the serving dark forested areas in cities remains crucial for the persistence difference between light and dark conditions using an additional light of nocturnal biodiversity such as light-sensitive insectivorous bats. source, this method is standard practice in studies of light (Spoelstra et al., 2015; Pintérné and Pödör, 2017). Role of the funding source References This research was financially funded by the Holsworth Wildlife Research Endowment (grant numbers: HOLSW2015-2-F147 and Adams, M.D., 2012. Vertical Stratification of Insectivorous Bats (Microchiroptera) in HWRE2016R2063CONT). Harvested Forests: Assessing the Role of Structural Clutter in Shaping Patterns of Flight Activity. Doctor of Philosophy thesis. 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