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Light pollution has been increasing around the globe and threatens to disturb natural rhythms of wildlife species. Artificial light impacts the behaviour of insectivorous bats in numerous ways, including foraging behaviour, which may in turn lead to altered prey selection. 2.In a manipulative field experiment, we collected faecal samples from six species of insectivorous bats in naturally dark and artificially lit conditions, and identified prey items using molecular methods to investigate effects of light pollution on prey selection. 3.Proportional differences of identified prey were not consistent and appeared to be species specific. Red bats, little brown bats, and gray bats exhibited expected increases in moths at lit sites. Beetle-specialist big brown bats had a sizeable increase in beetle consumption around lights, while tri-colored bats and evening bats showed little change in moth consumption between experimental conditions. Dietary overlap was high between experimental conditions within each species, and dietary breadth only changed significantly between experimental conditions in one species, the little brown bat. 4.Policy implications. Our results, building on others, demonstrate that bat-insect interactions may be more nuanced than the common assertion that moth consumption increases around lights. They highlight the need for a greater mechanistic understanding of bat-light interactions to predict which species will be most affected by light pollution. Given differences in bat and insect communities, we advocate biologists, land stewards, and civil planners work collaboratively to determine lighting solutions that minimize changes in foraging behaviour of species in the local bat community. Such efforts may allow stakeholders to more effectively craft management strategies to minimize unnatural shifts in prey selection caused by artificial lights. This article is protected by copyright. All rights reserved.
J Appl Ecol. 2017;1–9.  
© 2017 The Authors. Journal of Applied Ecology
© 2017 British Ecological Society
Illuminating prey selection in an insectivorous bat community
exposed to artificial light at night
Zachary M. Cravens1| Veronica A. Brown2| Timothy J. Divoll3| Justin G. Boyles1
Funding information
1. Lightpollutionhasbeenincreasingaroundtheglobeandthreatenstodisturbnatu-
2. Inamanipulativefieldexperiment,wecollectedfaecalsamplesfromsixspeciesof
items using molecular methods to investigate effects of light pollution on prey
3. Proportionaldifferencesinidentifiedpreywerenotconsistentandappearedtobe
speciesspecific.Redbats,little brown bats and grey bats exhibited expected in-
in beetle consumption around lights, while tri-coloured bats and evening bats
showed little change in moth consumption between experimental conditions.
Dietary overlap was high between experimental conditions within each species,
4. Policy implications.Ourresults,buildingonothers,demonstratethatbat–insectin-
tion increases around lights. They highlight the need for a greater mechanistic
understandingofbat–light interactions to predict whichspecieswill be most af-
lighting solutions that minimize changes in foraging behaviour of species in the
management strategies to minimize unnatural shifts in prey selection caused by
Journal of Applied Ecology
The biological world is orderedaround the natural rhythm of alter-
natingnightand day.Asareliablesignalovergeologictime, mostor-
ganismshaveevolvedinrelationto temporalcycles oflightanddark
periods (Gaston, Bennie, Davies, & Hopkins, 2013). However, fast-
paced urbanization beginning in the 20th centuryhas led to a dra-
matic increase in artificial light at night (ALAN; Holker, Moss, etal.,
2010). Global light pollution is increasing and has nearly doubled
overthe past25years(Holker,Moss,etal., 2010). Currently,almost
90%of Europeand halfthe United Statesexperiences light-polluted
skies (Falchi etal.,2016), but those levels have remained relatively
constantoverthelastseveraldecades(E. L.Koenetal.unpubl.data).
Conversely,developing regionswith above-averagespeciesrichness
to areas with low to moderate richness (E. L. Koen etal. unpubl.
data).This trendwill likelycontinueas the majority ofurbangrowth
isexpectedto occurnearcurrentlyprotected land (i.e. dark refugia;
and >60% of invertebratesare nocturnal and therefore likely to be
Most bats have evolved unique behavioural and morphological
adaptations (e.g. echolocation) to navigate in the absence of light
&Lewanzik,2011).This selectivepressureis strongenough thatbats
(Rydell,Entwistle, & Racey, 1996). Therefore,bats seem to prioritize
leading to roost abandonment, spatial avoidanceand delayed emer-
gence (reviewed in Rowse, Lewanzik, Stone, Harris,& Jones, 2016;
Stone,Harris, &Jones,2015). Impacts on bat foragingbehaviour are
experimentallylit environment (Lacoeuilhe, Machon, Julien, LeBocq,
& Kerbiriou, 2014; Schoeman, 2016; Stone,Jones, & Harris, 2009).
riskwithlitenvironments(Jones &Rydell, 1994).Conversely,numer-
ous species have been observed feeding at artificial lights (Acharya
&Fenton,1999; Clare, Fraser,Braid, Brock Fenton,& Hebert,2009;
Rydell,1992;Svensson&Rydell,1998).Artificial lightinterfereswith
sitiesaround lights (vanLangevelde, Ettema,Donners,WallisDeVries,
&Groenendijk,2011).Higherdensitiesalone maymakeaerialinsects
more vulnerable to predation from bats, but in some prey species,
Sole,& McKechnie,2015),wherestreetlightsarea consistentpart of
(Belwood & Fullard, 1984; Hickey & Fenton, 1990; Minnaar etal.,
isfoundinall membersofthiscommunity,thepatternis likelytobe
robust.To testthispattern,wemanipulatednaturallydarkareaswith
a short-term artificial light treatment. We collected faecal samples
frombatscapturedinbothlit andunlit environmentsandused next-
generationsequencing ofinsectDNAextracted fromfaecalsamples
lit conditions. We predicted bat consumption of moths (including
earedmoths) toincreaseand consumption ofbeetlestodecrease in
2.1 | Study site
Ourstudy was conducted in a 15-county region of western–south-
western Missouri, USA, during summer (May–August) 2016. The
eastern half of the study area is within the Ozark Highlands physi-
ographicregion, whichisa heavilyforestedlandscape dominatedby
oak-hickory forests. To the west, the land transitions to the Osage
Plains, a region historically dominated by prairie but now heavily
2.2 | Experimental design
We erected temporary lights along naturally dark forest roads or
(control) and lit (light pollution treatment). Distance between lit
and unlit sites was at least 2km to minimize overlap in foraging
andlandscape features.At litsites,we used50-WLED (Shenzhen
Lepower Opto Electronics Co., China) producing 4,200 lumens at
and powered by a 12-V lead acid battery. We used LED lighting
asitisbecoming morecommon inoutdoorlightingapplicationsas
Journal of Applied Ecology
batsat a nearbyunlitsiteas a control andonthe third night cap-
turedbats atlit sites(Minnaaretal., 2015).Delaying captureatlit
litcondition, aswellas provide timeforthem to choosetoforage
inthenewlylitenvironment.We makenoassumptionthatallbats
capturedatlit sites will necessarily be foraging around the lights;
moreover,weexpect some species may be less prone to foraging
atlights than others and thereforeshow less pronounced dietary
shifts.Nets were placed in flyways within 25mof the light in an
outthesummer.Weheldbatsinclothbagsfor30–45min, storedall
deposited faecal pellets in 1.5-ml microcentrifuge tubes with silica
2.3 | Molecular analysis
We extracted DNA from one to three pellets of guano from each
Wediscarded samples withinsufficientfaecal matter (<1fullpellet).
Redbat(Lasiurus borealis)samplesweretoonumeroussowesubsam-
pledbyrandomly selectinglit andunlit pairsfrom thesamesite.The
analytical methodology follows T. J. Divoll etal. (unpubl. data), and
2.4 | Data analysis
Sequences were analysed using the QIIME ( platform
(unpubl. data) (
withoneadditionalstepto only keep sequences within 10 bp of our
quenceswereclipped. Wefiltered outsequences smallerthan147bp
orgreater than 167bp. Sequences were clustered intomolecularop-
erationaltaxonomic units(MOTUs)using the SWARMmethodwith a
resolutionof2(Mahé,Rognes,Quince,deVargas,&Dunthorn, 2014).
not present at least 10 times in at least one sample. We performed
filteringusingacustom Pythonscriptemployingthe“pandas”package
byconsideringwithin-sampleMOTU occurrences<10aspotentialse-
quencingerrors and removing them.Weextracted representative se-
quences from each MOTU cluster, based on abundance, to compare
“bold”(Chamberlain, 2017)inr (R CoreTeam,2016).Weconsidered
onlythefirst40 recordsforeach representativeMOTUandthenfil-
tered recordswith <98% similarity and country of origin outside of
UnitedStatesand Canada.The entireoutput foreachrepresentative
was then separated into two groups:high quality with at least one
match(≥99.36% similarity)andlow qualitywith allmatches(>98.0%
but <99.36% similarity). We made taxonomic identifications based
onthese groupings, and in all cases where there was disagreement,
high-quality group, matches <99.36% did notchange the identifica-
variation in per cent match was not considered for identification,
onlydisagreement.Asanexample,agivenMOTUhas a100%match
fromtheBoldpackage outputforthemothAristotelia rubidella(fam-
ily:Gelechiidae),and a 98.92% match for the moth Hillia iris (family:
Noctuidae).Because the second match is less than 99.36% (a single
weidentified thepreyitemasA. rubidella. IftheH. iris had ≥99.36%
matchthen, because there wasdisagreementat the family level,we
wouldhaveidentified the item only as Lepidoptera.UniqueMOTUs
assignedto the same taxonomywere collapsedintoa single MOTU,
over or under split due to differences in genetic variation (Brown,
Chain, Crease, MacIsaac, & Cristescu, 2015); however, this should
notbias ourresults whenmeasuringwithin-specieschange between
2.5 | Statistical analysis
Wecalculatedpercent frequency of occurrence of insect prey or-
ders (number of samples containing an order divided by the total
occurrencesof allorders) foreachbat speciesin bothexperimental
We defined families Sphingidae, Noctuidae, Notodontidae,
Geometridae and Pyralidae as eared moths, as they are known to
havetympanateorgansused forpredatoravoidance(terHofstede &
yses,weusedthe collapsedsetofuniqueMOTUassumedto bebat
We used the EcoSimR 0.1.0 package (Gotelli, Hart, & Ellison,
2015)in r to determinedietaryoverlap amongthesixbat species
and to assess effects of artificial light. Nullmodels were used to
determinewhether extent of niche overlapwaslowerthan would
overlap and generated 1,000 bootstraprandomizations of MOTU
diet composition using the “ra3” algorithm. We conducted this
analysisincludingall MOTUs(all-preyanalysis)aswellas excluding
Brownetal., 2014;Clare,Symondson, Broders,etal., 2014; Clare,
No. of samples with eared moths
No. of eared moth occurrences in dataset
Journal of Applied Ecology
Symondson,&Fenton,2014).Weusedthe iNEXTpackage (Hsieh,
aswell as the chao2 asymptotic estimatorforthose numbers. Hill
numbershave been increasinglyusedforbiodiversityanalysisand
Wecaptured453batsfromsixspecies(bigbrownbats[Eptesicus fus-
cus];red bats;grey bats [Myotis grisescens];little brownbats[Myotis
lucifugus]; evening bats [Nycticeius humeralis]; and tri-coloured bats
[Perimyotis subflavus]) across both experimental conditions (n = 297
duringunlitandn=151duringlit) spanning61nights(n=42during
unlitand n=19 during lit).Lightdidnot appear to attractnewspe-
species distributions, at both lit and unlit sites. We analysed DNA
from 188 faecal samples from the six species (Table 3) and recov-
ered71,992,648sequencing reads. After performing bioinformatics
processing, these reads were clustered and filtered down to 3,078
MOTUs. Using representative sequences of the 3,078 MOTUs, we
tabase,belonging to 15 insectorders.After collapsing MOTUs with
monly identified orders and their combinedproportion was relatively
constant(range~69% to~83%)foreachbat speciesinboth treatment
groups. Specifically, Coleoptera were the most commonly identified
preyfor big brown and evening bats, and Lepidopterawere the most
common preyfor red and little brown bats in both treatmentgroups.
Dipterawerethemostcommon preyidentifiedin the diet of greyand
tri-coloured batsat unlit sites, but the most common-prey items atlit 
species with a significant shift between treatments (χ2=10.11,
p =.02), although significance is lost after a Bonferronicorrection
(Figure1).Further, this maybe relatedto our smallertotalsample
size for this species. Little overallvariation in prey selection was
detectedin anyotherspecies (p >.15).Analysisofdietaryoverlap
yseswere similar; therefore, all-preyvaluesarereported).Overlap
betweenlit and dark treatment groups exceeded0.6, thevalue at
conditions(Ojk0.906,p <.001).Theresultsweregenerallylesscon-
clusivewhenwelimited ourcomparisonofoverlapvaluesbetween
treatment groups toprey items identified as Lepidoptera, but red
batsstillhadasignificantdegreeofoverlap(Ojk0.9059,p <.001).In
Further,evenqualitativeshiftsinconsumptionofthetwomost im-
portantpreyitems, Coleopteraand Lepidoptera,variedacrossspe-
(p <.007),consumedfewerearedmothsinthelittreatment.
Diversityestimates showed that dietary breadth did not change
substantiallybetween experimentalconditionsformostspecies,and
FIGURE1 TheproportionofMOTUsidentifiedinthedietofsixspeciesofinsectivorousbatsunderexperimentallylitandnaturallydark
Proportion of MOTUs by Order
Big brown bat
Lit Unlit Lit Unlit
Lit Unlit Lit Unlit Lit Unlit Lit Unlit
Red bat Grey bat Little brown bat Evening bat Tri-coloured bat
Journal of Applied Ecology
noclearpattern existsin thedirection ofchange(Table3). Onlylittle
using the Chao2 estimation of incidence-based richness estimation
expectations,nospeciesinthiscommunity showeda significantshift
indiet as seen in another study using a similar experimental design.
experimentally lit conditions that would suggest an existing pattern
weare missing due tolowpower.Proportional differences in identi-
greybats followedtheexpected pattern atlit sites withhighermoth
beetlesidentifiedunder lit conditions. Evening bats and tri-coloured
betweentheexperimentalconditions(Ojk > 0.719forallspecies).This
callimitation as we areunableto determine true abundanceofeach
preyitemwithinanindividualbat,sotheamountof aparticular prey
itemmay change without a change intheproportionof unique prey
larbetweenlitandunlitsites,exceptforlittle brownandtri-coloured
diversityandbreadthestimates suggestbatswere notfeeding selec-
Pairwise comparisons between species, within each treatment
group,providefurtherevidence forspecies-specific changes indiet,as
atlitsites(Ojk =0.345)thanunlitsites(Ojk =0.536),suggestingincreased
brownbatsatunlitsites(Ojk =0.705),whichistobeexpectedasevening
All MOTUs Common- prey analysis
p (observed
p (observed
Alltreatmentsandspp. 0.70446 <.001 0.70968 <.001
Littreatmentallspp. 0.60420 <.001 0.61796 <.001
Controlallspp. 0.66239 <.001 0.66866 <.001
Bigbrownbat 0.85907 <.001 0.86922 <.001
Redbat 0.90643 <.001 0.91358 <.001
Greybat 0.71912 <.001 0.74098 <.001
Littlebrownbat 0.81780 <.001 0.83112 <.001
Eveningbat 0.82670 <.001 0.83715 <.001
Tri-colouredbat 0.74422 <.001 0.75555 <.001
Lepidopteraalltreatmentsandspp. 0.64481 <.001 0.66121 <.001
Lepidopteralitallspp. 0.45916 <.001 0.48400 <.001
Lepidopteracontrolallspp. 0.52352 <.001 0.54295 <.001
Bigbrownbat 0.48110 .250 0.50903 .190
Redbat 0.90586 <.001 0.91503 <.001
Greybat 0.56171 .570 0.60760 .470
Brownbat 0.59638 <.001 0.62704 .004
Eveningbat 0.56600 .083 0.57387 .099
Tri-colouredbat 0.45748 .766 0.49490 .713
TABLE1 Dietoverlapbetweenthesix
Journal of Applied Ecology
batstypically preferColeoptera (Feldhamer,Whitaker,Krejca,& Taylor,
presenceoflight(Ojk =0.544),becauseeveningbatswerenotexploiting
We found little evidence of increased consumption of eared
moths under artificially lit treatments; in fact, eared-moth propor-
tionsdecreased(althoughnot significantly) at lit sites for most spe-
cies.Conversely,Capeserotinebats(Neoromicia capensis)significantly
(92.9%)wasidentifiedas anearedmoth atthatstudysite,while the
siderably lower(Dodd, Lacki, & Rieske, 2008). Our results mayalso
beanartefactofouruseoftheBold Systemsdatabase asnumerous
potential eared moths had multiple family-level identifications and
were thus only identifiedto the ordinal level. This may be because
thesemothspeciesare notyetinthe BoldSystemsdatabaseorthat
Based on our currentwork and that of others, we propose four
specialists may take advantage of artificial light-induced phototaxis
(van Langevelde etal., 2011) to increaseprey consumption of their
ists(big brown and red bats) consumed proportionally more of their
preferredprey at lit sites. Big brown bats,with their powerful jaws,
TABLE2 Pairwisecomparisonofdietoverlapbetweensixspeciesofinsectivorousbatsinlitandnaturallyunlitexperimentaltreatments.
Big brown bat Red bat Little brown bat Grey bat Evening bat Tri-coloured bat
Bigbrownbat 0.037 0.001 0.073 0.022 0.001
Redbat 0.34471 0.001 0.001 0.001 0.001
Littlebrownbat 0.57593 0.65952 0.001 0.001 0.001
Greybat 0.46833 0.68382 0.77017 0.002 0.001
Eveningbat 0.54435 0.43585 0.63214 0.59877 0.001
Tri-colouredbat 0.64095 0.54714 0.76412 0.69536 0.70188
Bigbrownbat 0.001 0.001 0.001 0.001 0.002
Redbat 0.53586 0.001 0.001 0.001 0.001
Littlebrownbat 0.76932 0.6034 0.001 0.001 0.001
Greybat 0.64075 0.51874 0.81686 0.001 0.001
Eveningbat 0.70514 0.58402 0.76158 0.74654 0.001
Tri-colouredbat 0.54008 0.57741 0.67231 0.69197 0.77191
TABLE3 Diversityestimatesbetweenexperimentallylitandnaturallydarkconditionsinsixspeciesofinsectivorousbats
Bat species
n (samples
group Richness
q = 1, Shannon diversity
effective no. of MOTUs
q = 2, Simpson diversity
effective no. of MOTUs
Obs. Est. Obs. Est.
Bigbrownbat 7Lit 66 54.40 85.67 44.50 59.98
14 Unlit 100 69.19 97.66 52.36 59.34
Redbat 35 Lit 200 111.89 164.19 68.26 74.86
39 Unlit 213 119.98 157.49 74.33 80.70
Greybat 7Lit 107 89.76 148.73 74.57 107.04
9Unlit 108 81.69 134.30 61.59 77.21
Littlebrownbat 9Lit 119 89.51 176.47 65.47 83.73
29 Unlit 150 87.57 114.84 57.70 62.41
Eveningbat 6 Lit 73 60.29 101.71 49.63 67.52
16 Unlit 120 81.45 105.00 58.58 66.18
Tri-colouredbat 6 Lit 91 75.31 146.47 60.63 86.83
11 Unlit 95 72.87 95.91 55.64 66.89
Journal of Applied Ecology
nity, twogeneralist species (grey bat and little brown bat) exhibited
sucha pattern ofincreased mothconsumptionand decreasedbeetle
consumptionunder artificial light. Greybats had a 64.9% increase in
Twospecies(eveningbatandtri-colouredbats) exhibitedlittle differ-
ence in the proportion ofbeetles and moths under the two experi-
mentalconditions. Forthesespecies,thelack of dietary changemay
berelatedto their morphology.Tri-colouredbatsareclutter adapted
(Menzeletal.,2005), andwhile eveningbatsarenotcompletelyclut-
thesebatsmaybeavoidingthelightsto avoidpredation.Fourth,spe-
cialist species may decrease consumption of their preferredprey in
favourof moths around lights. No species in our study showedthis
eral,species with morphological adaptationsthatfavourfasterflight
tic prey aroundtemporally stable light sources, such as streetlights
(Schoeman, 2016). Conversely, slower flying species with greater
manoeuvrabilityto forageinand around cluttered habitats are con-
sideredlight-intolerant(Rowseetal., 2016).Thesespeciesareoften
avoidartificiallight,although presumablylight-intolerantMyotisspe-
ertenvironments(Bell, 1980;Fenton& Morris,1976). Itmaybethat
light-intolerantspeciesinnon-desert regionsarenot avoiding lights,
tolerantspecies seem to preferstreetlightsinrural areas overurban
ThespectralcompositionoftheLEDsused inthisexperimentmay
Tarmann, 2010),likelybecause LEDsdonotproducelightinthelower
UVspectrum (Stone etal., 2015). Other formsoflight which lack UV
light,suchashighpressuresodium, also attract fewer insects (Rydell,
batactivity (Blake,Hutson, Racey,Rydell, &Speakman,1994);in fact,
batactivitycanchangebyasmuchas anorderofmagnitudedepend-
ingon lighting technology(Rydell,1992). Interestingly,light-intolerant
batsdonotappearasaverseto LEDsas othertechnologies (Lewanzik
gestslight-intolerantbatsareavoiding UVlightspecifically (Gorresen,
Cryan,Dalton,Wolf,&Bonaccorso,2015).The lackofUVin LEDlight
& Fenton, 1990; Minnaar etal., 2015; Rydell, 1992; Schoeman, 2016),
and some of these studies havecompared differences in diet with unlit
sitesto determine adietaryshift (Hickey& Fenton,1990; Minnaaretal.,
2015).A patternhasemergedthat bats generally consumemoremoths,
oftheworkon effectsofartificial lightonforagingbatsinNorthAmerica
has focused on hoary,red and Hawaiian hoary bats (Acharya & Fenton,
1992,1999; Belwood &Fullard,1984;Fullard,2001;Hickey,Acharya,&
Pennington,1996;Hickey& Fenton,1990;Jacobs,1999).Hoaryandred
bats are generallyconsidered moth specialists; therefore, an increase in
auniversalresponsein dietaryshiftsaroundlights forallspecies.Theoft-
citedpattern, which isquicklybecoming a paradigm,thatALAN leads to
increasesinmothconsumptionininsectivorousbatsmaynotbethe case
FIGURE2 Interpolation(rarefaction)andextrapolationofdietaryspeciesrichnessforeachexperimentalconditioninsixspeciesof
Species diversity
Interpolation Extrapolation (95% CI)
Unlit (actual sample size)
Number of sampling units
Big brown bat
Grey bat
Evening bat
Red bat
Tri-coloured bat
Little brown bat
Journal of Applied Ecology
forall species. Our results underscorethe need forabettermechanistic
We thank the Missouri Department of Conservation (MDC) for fi-
nancialsupportandwithinMDC,KellyRezac,Tony ElliottandShelly
Colatskie for logistical support. Jenna Holub provided assistance in
thefield. Gary McCracken provided laboratory space and materials.
WealsothankThomas Lilley and one anonymous reviewer for pro-
wereapproved bytheAnimal Care andUse Committee ofSouthern
Z.M.C. and J.G.B. conceived the idea and experimental methodol-
Underlyingdata are available in the Dryad DigitalRepository https://(Cravens,Brown,Divoll,&Boyles,2017).
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Additional Supporting Information may be found online in the
How to cite this article:CravensZM,BrownVA,DivollTJ,
communityexposedtoartificiallightatnight.J Appl Ecol.
... Despite their predominantly acoustic interaction, both bats and moths are also strongly affected by artificially introduced light sources. While some bats may profit from artificial light because they are able to exploit the resulting accumulation of prey animals [233,234], other species are negatively affected because they are unable to commute without interruption to new habitats [124][125][126]. Generally, all moths are negatively affected by light. ...
... Light also increases moths' predation risk in two ways. First, because the accumulation of moths around lights attracts bats, the predation pressure on moths increases [233,234]. Second, light impedes moths' anti-predator flight behaviour. Several studies compared the soundtriggered anti-predator flights of moths under lit and unlit conditions, and reported that light reduces anti-predator flight behaviours. ...
... Increasing light pollution [114,115], however, severely impacts both bats and moths (e.g. [124,234,236], and has potentially cascading effects on their predator-prey-interactions, population dynamics and ecosystems [212,226]. Light reduces the acoustically triggered last-ditch manoeuvres in eared moths, which in turn makes them more vulnerable to nearby predating bats. ...
... A field experiment in Connecticut, USA, found that no bat species responded positively to ALAN when LED floodlights illuminated a dark nature preserve [24]. Similarly, another field experiment in the forest in Missouri, USA also found that most species avoided experimentally lit areas regardless of their foraging strategies except for the eastern red bat (Lasiurus borealis, species abbreviation LABO, [36,37]). So far, few studies have been conducted in urban areas to specifically study bats and ALAN in North America. ...
... Our insect sampling method might not capture the complete profile of prey. For example, we collected very few lepidopterans, which are known prey under ALAN [13,37,88]. Future studies should use more comprehensive prey sampling methods to better understand the prey availability and further investigate how prey preference might alter predator-prey relationships [89]. ...
Full-text available
Predators respond to the increase of prey by aggregation in space or foraging more often. However, foraging habitat suitability limits predators’ responses. For nocturnal insectivorous bats, artificial light at night (ALAN) can trigger insect prey aggregation. It is not clear how ALAN might affect predator-prey relationships in the urban setting, where urban bats could have adapted to the city, and novel spatial complexity introduced by man-made objects might alter foraging habitat suitability. We strategically selected sites to represent different levels of ALAN and spatial complexity. We recorded bat commuting and foraging activities and collected aerial insects to examine how ALAN and spatial complexity affected bat-insect relationships. We found that insect biomass was positively correlated with ALAN, but was not affected by spatial complexity. Large-sized big brown bats and hoary bats positively responded to change of prey in open sites whereas small-sized eastern red bats and silver-haired bats positively responded in cluttered sites, suggesting that the impact of ALAN could vary when ALAN is coupled with urban spatial complexity. Our study demonstrates that foraging habitat suitability can alter which species might benefit from ALAN. Predator-prey relationships in cities are complex, but general ecological principles still apply in novel urban ecosystems.
... We analyzed sequences using the QIIME platform [43] and the workflows outlined in Divoll et al. [42] and Cravens et al. [44], with an additional step to eliminate potentially chimeric sequences. Briefly, we demultiplexed samples and pooled sequences in the forward and reverse direction into one fasta file with the same orientation. ...
... We ran the representative set of sequences through the COI database in the Barcode of Life Database (BOLD; [45]) using the package "bold" [46] in R [47]. We considered the first 40 records for each representative OTU and removed records with ≤ 99% similarity and country of collection outside of the U.S. and Canada [42,44]. Where more than one identification for an OTU was present at ≥ 99%, we deferred to the next highest level of taxonomy for identification (i.e., multiple species within an order, we deferred to the order). ...
Full-text available
Temperate bat species use extended torpor to conserve energy when ambient temperatures are low and food resources are scarce. Previous research suggests that migratory bat species and species known to roost in thermally unstable locations, such as those that roost in trees, are more likely to remain active during winter. However, hibernating colonies of cave roosting bats in the southeastern United States may also be active and emerge from caves throughout the hibernation period. We report what bats are eating during these bouts of winter activity. We captured 2,044 bats of 10 species that emerged from six hibernacula over the course of 5 winters (October–April 2012/2013, 2013/2014, 2015/2016, 2016/2017, and 2017/2018). Using Next Generation sequencing of DNA from 284 fecal samples, we determined bats consumed at least 14 Orders of insect prey while active. Dietary composition did not vary among bat species; however, we did record variation in the dominant prey items represented in species’ diets. We recorded Lepidoptera in the diet of 72.2% of individual Corynorhinus rafinesquii and 67.4% of individual Lasiurus borealis. Diptera were recorded in 32.4% of Myotis leibii, 37.4% of M. lucifugus, 35.5% of M. sodalis and 68.8% of Perimyotis subflavus. Our study is the first to use molecular genetic techniques to identify the winter diet of North American hibernating bats. The information from this study is integral to managing the landscape around bat hibernacula for insect prey, particularly in areas where hibernating bat populations are threatened by white-nose syndrome.
... Since the beginning of the 20th century, rapidly increasing urbanisation and industrialisation have led to dramatic increases in the global coverage of artificial light at night (ALAN) (Stone et al., 2015a;Cravens et al., 2018). There is currently a global shift from older lighting typessuch as mainly yellow-orange high pressure sodium (HPS) and virtually monochromatic orange low pressure sodium (LPS) lamps -to more modern, broad-spectrum 'white' forms of lighting such as light-emitting diodes (LEDs) (Mathews et al., 2015;Stone et al., 2015a). ...
... Further studies are required to ascertain whether predation is indeed the main factor explaining the response of light-averse bats to lighting. While protecting dark refugia (Cravens et al., 2018) and implementing lighting management methods (Azam et al., 2015) should be a priority, altering the colour of LEDs may be necessary to reduce impacts on light-averse bats as increasing urbanisation brings a proliferation of this lighting type. ...
... An unintended consequence, however, is that bats foraging near artificial lighting sources have altered unnatural diet structures. An earlier study found that in artificially lit areas, bats ingested substantially more moths and far less beetles compared with those foraging in naturally dark areas (Cravens et al. 2017). ...
Full-text available
Where did the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) come from? Did it spread to ‘patient zero’ through proactive human-animal contact? Why did humans faced an increasing number of zoonotic diseases in the past few decades? In this article, we propose a new theory by which human pollution such as artificial lighting and noise accentuate pathogen shedding from bats and other wild habitants in urban environments. This theory differs from the current hypothesis that wildlife trades and bushmeat consumption largely contribute to the spillover of zoonotic pathogens to humans. As natural reservoirs, bats harbor the greatest number of zoonotic viruses among all mammalian orders, while they also have a unique immune system to maintain functioning. Some bat species roost in proximity with human settlements, including urban communities and surrounding areas that are potentially most impacted by anthropogenic activities. We review the behavioral changes of wild habitants, including bats and other species, caused by environmental pollution such as artificial lighting and noise pollution, with focus on the spillover of zoonotic pathogens to humans. We found that there is a strong positive correlation between environmental stress and the behavior and health conditions of wild species, including bats. Specifically, artificial lighting attracts insectivorous bats to congregate around streetlights, resulting in changes in their diets and improved likelihood of close contact with humans and animals. Moreover, many bat species avoid lit areas by expending more energies on commuting and foraging. Noise pollution has similar effects on bat behavior. Bats exposed to chronic noise pollution have weakened immune functions, increased viral shedding, and declined immunity during pregnancy, lactation, and vulnerable periods due to noised-induced stress. Other wild species exposed to artificial lighting and noise pollution also show stress-induced behaviors and deteriorated health. Overall, evidence supports our hypothesis that artificial lighting and noise pollution have been overlooked as long-term contributors to the spillover of zoonotic pathogens to humans in urban environments.
... Vulnerability to sensory pollution 7 species avoids areas affected by lighting (Cravens et al. 2018). Reduced light pollution can be realized by decreasing lumen output (or eliminating lights), better control over the spatial extent of lighting, limiting lighting to portions of the spectrum to which the bats and their prey are less sensitive, and limiting the seasonal and diel scheduling of lighting. ...
Full-text available
Synopsis Global expansion of lighting and noise pollution alters how animals receive and interpret environmental cues. However, we lack a cross-taxon understanding of how animal traits influence species vulnerability to this growing phenomenon. This knowledge is needed to improve the design and implementation of policies that mitigate or reduce sensory pollutants. We present results from an expert knowledge survey that quantified the relative influence of 21 ecological, anatomical, and physiological traits on the vulnerability of terrestrial vertebrates to elevated levels of anthropogenic lighting and noise. We aimed not only to quantify the importance of threats and the relative influence of traits as viewed by sensory and wildlife experts, but to examine knowledge gaps based on the variation in responses. Identifying traits that had less consensus can guide future research for strengthening ecologists’ and conservation biologists’ understanding of sensory abilities. Our findings, based on 280 responses of expert opinion, highlight the increasing recognition among experts that sensory pollutants are important to consider in management and conservation decisions. Participant responses show mounting threats to species with narrow niches; especially habitat specialists, nocturnal species, and those with the greatest ability to differentiate environmental visual and auditory cues. Our results call attention to the threat specialist species face and provide a generalizable understanding of which species require additional considerations when developing conservation policies and mitigation strategies in a world altered by expanding sensory pollutant footprints. We provide a step-by-step example for translating these results to on-the-ground conservation planning using two species as case studies.
... These effects depend on the light intensity [36,37] and less so on the light spectrum [38,39], but there can be an interaction between the two [40]. Dietary shifts around the lights are also species-specific, with some bats increasing their consumption of moths or beetles while others show little change compared to unilluminated sites [41]. Artificial lighting near rivers can reinforce the trophic interactions between insects, insectivorous birds and top predators, for example Nankoo [42] found that bridge illumination increased the local abundance of insects (mainly Diptera) resulting in increased foraging by cliff swallows (Petrochelidon pyrrhonota), which was followed by arrival of peregrine falcons (Falco peregrinus). ...
Artificial light at night (ALAN) is globally increasing, posing a threat to biodiversity. The impact of nocturnal illumination on individual insects has been relatively well documented. Recent studies show that ALAN also impacts species interactions, including intraspecific communication, trophic interactions and plant-pollinator interactions, with cascading effects in the ecosystem and impacts on ecosystem functioning that extend beyond nocturnal communities and illuminated areas. Reduced population sizes and changes in community composition because of exposure to ALAN have been reported but the understanding of the impacts of ALAN on insect communities is currently limited to few groups and ecosystems. The theoretical framework on how ALAN impacts insect communities and populations is poorly developed, limiting our understanding and the formulation of relevant hypotheses.
... Previous work has demonstrated sympatric bat species partition space horizontally-at coarse (Arlettaz, 1999;Nicholls & Racey, 2006) and fine scales (Saunders & Barclay, 1992)and vertically (Kalcounis et al., 1999;Müller et al., 2013). Sympatric species also partition prey by size (Dodd et al., 2015), behavior (Mata et al., 2018), and taxa (Cravens et al., 2018;Whitaker, 2004), although spatial and dietary partitioning need not be mutually exclusive (Roswag et al., 2015;Saunders & Barclay, 1992). ...
Full-text available
Abstract Diverse species assemblages theoretically partition along multiple resource axes to maintain niche separation between all species. Temporal partitioning has received less attention than spatial or dietary partitioning but may facilitate niche separation when species overlap along other resource axes. We conducted a broad‐scale acoustic study of the diverse and heterogeneous Great Smoky Mountains National Park in the Appalachian Mountains. Between 2015 and 2016, we deployed acoustic bat detectors at 50 sites (for a total of 322 survey nights). We examined spatiotemporal patterns of bat activity (by phonic group: Low, Mid, and Myotis) to test the hypothesis that bats partition both space and time. Myotis and Low bats were the most spatially and temporally dissimilar, while Mid bats were more general in their resource use. Low bats were active in early successional openings or low‐elevation forests, near water, and early in the evening. Mid bats were similarly active in all land cover classes, regardless of distance from water, throughout the night. Myotis avoided early successional openings and were active in forested land cover classes, near water, and throughout the night. Myotis and Mid bats did not alter their spatial activity patterns from 2015 to 2016, while Low bats did. We observed disparate temporal activity peaks between phonic groups that varied between years and by land cover class. The temporal separation between phonic groups relaxed from 2015 to 2016, possibly related to changes in the relative abundance of bats or changes in insect abundance or diversity. Temporal separation was more pronounced in the land cover classes that saw greater overall bat activity. These findings support the hypothesis that niche separation in diverse assemblages may occur along multiple resource axes and adds to the growing body of evidence that bats partition their temporal activity.
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Artificial light at night (ALAN) is closely associated with modern societies and is rapidly increasing worldwide. A dynamically growing body of literature shows that ALAN poses a serious threat to all levels of biodiversity - from genes to ecosystems. Many “unknowns” remain to be addressed however, before we fully understand the impact of ALAN on biodiversity and can design effective mitigation measures. Here, we distilled the findings of a workshop on the effects of ALAN on biodiversity at the first World Biodiversity Forum in Davos attended by several major research groups in the field from across the globe. We argue that 11 pressing research questions have to be answered to find ways to reduce the impact of ALAN on biodiversity. The questions address fundamental knowledge gaps, ranging from basic challenges on how to standardize light measurements, through the multi-level impacts on biodiversity, to opportunities and challenges for more sustainable use.
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Insectivorous bats provide ecosystem services in agricultural and urban landscapes by consuming arthropods that are considered pests. Bat species inhabiting cities are expected to consume insects associated with urban areas, such as mosquitoes, flying termites, moths, and beetles. We captured insectivorous bats in the Federal District of Brazil and used fecal DNA metabarcoding to investigate the arthropod consumed by five bat species living in colonies in city buildings, and ascertained whether their predation was related to ecosystem services. These insectivorous bat species were found to consume 83 morphospecies of arthropods and among these 41 were identified to species, most of which were agricultural pests. We propose that bats may roost in the city areas and forage in the nearby agricultural fields using their ability to fly over long distances. We also calculated the value of the pest suppression ecosystem service by the bats. By a conservative estimation, bats save US$ 94 per hectare of cornfields, accounting for an annual savings of US$ 390.6 million per harvest in Brazil. Our study confirms that, regardless of their roosting location, bats are essential for providing ecosystem services in the cities, with extensive impacts on crops and elsewhere, in addition to significant savings in the use of pesticides.
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iNEXT (iNterpolation and EXTrapolation) Online is the R-based interactive online version of iNEXT available via the link or Clicking these links, you will be directed to the online interface window. Users do not need to learn/understand R to run iNEXT Online. The interactive web application was built using the Shiny (a web application framework). iNEXT features two statistical analyses (non-asymptotic and asymptotic) for species diversity based on Hill numbers: (1) A non-asymptotic approach based on interpolation and extrapolation iNEXT computes the estimated diversities for standardized samples with a common sample size or sample completeness. This approach aims to compare diversity estimates for equally-large (with a common sample size) or equally-complete (with a common sample coverage) samples; it is based on the seamless rarefaction and extrapolation sampling curves of Hill numbers for q = 0, 1 and 2. See Colwell et al. (2012), Chao and Jost (2012) and Chao et al. (2014) for pertinent background and methods. (2) An asymptotic approach to infer asymptotic diversity iNEXT computes the estimated asymptotic diversity profiles. It is based on statistical estimation of the true Hill number of any order q ≥ 0; see Chao and Jost (2015) for the statistical estimation detail.
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Artificial lights raise night sky luminance, creating the most visible effect of light pollution-artificial skyglow. Despite the increasing interest among scientists in fields such as ecology, astronomy, health care, and land-use planning, light pollution lacks a current quantification of its magnitude on a global scale. To overcome this, we present the world atlas of artificial sky luminance, computed with our light pollution propagation software using new high-resolution satellite data and new precision sky brightness measurements. This atlas shows that more than 80% of the world and more than 99% of the U.S. and European populations live under light-polluted skies. The Milky Way is hidden from more than one-third of humanity, including 60% of Europeans and nearly 80% of North Americans. Moreover, 23% of the world's land surfaces between 75°N and 60°S, 88% of Europe, and almost half of the United States experience light-polluted nights.
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While artificial lighting is a major component of global change, its biological impacts have only recently been recognised. Artificial lighting attracts and repels animals in taxon-specific ways and affects physiological processes. Being nocturnal, bats are likely to be strongly affected by artificial lighting. Moreover, many species of bats are insectivorous, and insects are also strongly influenced by lighting. Lighting technologies are changing rapidly, with the use of light-emitting diode (LED) lamps increasing. Impacts on bats and their prey depend on the light spectra produced by street lights ; ultraviolet (UV) wavelengths attract more insects and consequently insectivorous bats. Bat responses to lighting are species-specific and reflect differences in flight morphology and performance ; fast-flying aerial hawking species frequently feed around street lights, whereas relatively slow-flying bats that forage in more confined spaces are often light-averse. Both high-pressure sodium and LED lights reduce commuting activity by clutter-tolerant bats of the genera Myotis and Rhinolophus, and these bats still avoided LED lights when dimmed. Light-induced reductions in the activity of frugivorous bats may affect ecosystem services by reducing dispersal of the seeds of pioneer plants and hence reforestation. Rapid changes in street lighting offer the potential to explore mitigation methods such as part-night lighting (PNL), dimming, directed lighting, and motion-sensitive lighting that may have beneficial consequences for light-averse bat species .
Given a site by species interaction matrix, users can make inferences about species interactions by performance hypothesis comparing test statistics against a null distribution. The current package provides algorithms and metrics for niche-overlap, body size ratios and species co-occurrence. Users can also integrate their own algorithms and metrics within these frameworks or completely novel null models. Detailed explanations about the underlying assumptions of null model analysis in ecology can be found at
1. Light pollution is rapidly increasing and can have deleterious effects on biodiversity, yet light types differ in their effect on wildlife. Among the light types used for street lamps, light-emitting diodes (LEDs) are expected to become globally predominant within the next few years. 2. In a large-scale field experiment, we recorded bat activity at 46 street lights for 12 nights each and investigated how the widespread replacement of conventional illuminants by LEDs affects urban bats: we compared bat activity at municipal mercury vapour (MV) street lamps that were replaced by LEDs with control sites that were not changed. 3. Pipistrellus pipistrellus was the most frequently recorded species; it was 45% less active at LEDs than at MV street lamps, but the activity did not depend on illuminance level. Light type did not affect the activity of Pipistrellus nathusii, Pipistrellus pygmaeus or bats in the Nyctalus/Eptesicus/Vespertilio (NEV) group, yet the activity of P. nathusii increased with illu-minance level. Bats of the genus Myotis increased activity 4Á5-fold at LEDs compared with MV lights, but illuminance level had no effect. 4. Decreased activity of P. pipistrellus, which are considered light tolerant, probably paral-leled insect densities around lights. Further, our results suggest that LEDs may be less repelling for light-averse Myotis spp. than MV lights. Accordingly, the transition from conventional lighting techniques to LEDs may greatly alter the anthropogenic impact of artificial light on urban bats and might eventually affect the resilience of urban bat populations. 5. Synthesis and applications. At light-emitting diodes (LEDs), the competitive advantage – the exclusive ability to forage on insect aggregations at lights – is reduced for light-tolerant bats. Thus, the global spread of LED street lamps might lead to a more natural level of competition between light-tolerant and light-averse bats. This effect could be reinforced if the potential advantages of LEDs over conventional illuminants are applied in practice: choice of spectra with relatively little energy in the short wavelength range; reduced spillover by precisely directing light; dimming during low human activity times; and control by motion sensors. Yet, the potential benefits of LEDs could be negated if low costs foster an overall increase in artificial lighting.
Echolocation in bats and high-frequency hearing in their insect prey make bats and insects an ideal system for studying the sensory ecology and neuroethology of predator-prey interactions. Here, we review the evolutionary history of bats and eared insects, focusing on the insect order Lepidoptera, and consider the evidence for antipredator adaptations and predator counter-adaptations. Ears evolved in a remarkable number of body locations across insects, with the original selection pressure for ears differing between groups. Although cause and effect are difficult to determine, correlations between hearing and life history strategies in moths provide evidence for how these two variables influence each other. We consider life history variables such as size, sex, circadian and seasonal activity patterns, geographic range and the composition of sympatric bat communities.We also review hypotheses on the neural basis for antipredator behaviours (such as evasive flight and sound production) in moths. It is assumed that these prey adaptations would select for counter-adaptations in predatory bats. We suggest two levels of support for classifying bat traits as counter-adaptations: traits that allow bats to eat more eared prey than expected based on their availability in the environment provide a low level of support for counter-adaptations, whereas traits that have no other plausible explanation for their origination and maintenance than capturing defended prey constitute a high level of support. Specific predator counter-adaptations include calling at frequencies outside the sensitivity range of most eared prey, changing the pattern and frequency of echolocation calls during prey pursuit, and quiet, or 'stealth', echolocation.