CEC Research | https://doi.org/10.21973/N3CM19 Spring 2019 1/9

HabitatpartitioningofbatcommunitiesinNorthernCalifornia

PaigeKlotz1,VanessaLundsten2,NicMorat3,KennaSherman4

1UniversityofCalifornia,Merced,2UniversityofCalifornia,SanDiego,3UniversityofCalifornia,Riverside,4UniversityofCalifornia,SantaBarbara

ABSTRACT

The theory of niche partitioning states that species coexisting at equilibriumwithin astablecommunitymustsharelimitedresources(Hutchinson1957).Thistheoryhasbeenwidelystudied indiversecommunityassemblages,but fewstudieshaveappliednichepartitioning to bat communities. Specifically, little is known about how bat speciesoccupy differentmicrohabitats in order to coexist. Our study aims to understand theeffectofhabitatonbatdiversityandabundancewithinthescopeofnichepartitioning.Toobservethedifferenceinbatassemblagesacrossvaryinghabitats,weidentifiedbatspecies diversity and abundance using acoustic detection in three different habitats(meadow,forest,andriver).Weusedlighttrapstosurveyinvertebratesasameasureofabundancethroughoutthenight.Batcallsweremostfrequentattheriver,whereYumamyotis (Myotis yumanensis)dominated.Hoarybats (Lasiurus cinereus)dominated themeadow.Overall,batactivitywaslowestintheforest.Astimeprogressedthroughthenight,batactivitydecreasedatallsites,particularly inthemeadow.Wealsoobservedtentimesmoreinvertebratesinthemeadowcomparedtotheothersites.Althoughthediet of generalist foraging bat species may overlap, species appear to partition intodifferenthabitats,possiblytoavoidcompetitionandcoexist.Understandingmoreaboutbatcommunitycompositionandactivitymaybeusefulinprotectingthisdecliningguildofmammals.

Keywords: niche partitioning, echolocation, Echo Meter 2, invertebrate, Myotisyumanensis,Lasiuruscinereus

INTRODUCTION

The theoryof nichepartitioning suggeststhat species limit the negative effects ofcompetition in a community by dividingresources (Hutchinson 1957). Understandinghow animals segregate into smallercommunities provides insight into trophiclevels and diet preferences. To limitcompetition for homogenous resources,similar speciesoftenpartition resourcesbytaking advantage of different habitats and

microhabitats. For example, two sympatricbumble bee species in Colorado sharenectarresourcesbyspecializingondifferentflowerspecies,decreasingcompetitionandincreasing foraging efficiency (Graham andJones1996).Nichepartitioningisaprimaryfactor in many species interactions,allowingforsimilarspeciestocoexist.In species-rich communities, bat

assemblages are a model for nichepartitioning.Manyspecieswithin thesamerange have similar morphological and

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dietary traits but are seen in distincthabitats (Norberg & Rayner 1987).However, research has primarilyconcentrated on morphology (Findley &Black1983)andecholocation (Kalko1995),which have been shown to partition batspecies into different habitats. Little isknown about the habitat ranges ofgeneralist bat species as well as how thisdrivesresourcepartitioning.Understandingtheinteractionbetweendietandhabitatofgeneralistbatspeciescan leadtoagreaterunderstandingofhowspeciescoexistusingniche partitioning. Additionally, batpopulations around the world areexperiencing elevated mortality dueprimarily to anthropogenic factors (O’Sheaet al. 2016). Research into how these batssegregate resources would informconservation ecologists on how to bestcombatpopulationdecline.Marjorie and Heath Angelo Coast Range

Reserve, located along the coast ofNorthern California, facilitates varyingenvironments and is along the springmigration route of several bat species.Additionally, non-migratory bats native tothe area are preparing to pup, makingspring an ideal time of year to study batabundance.Therichdiversityofbatspeciesin this area makes this system a primelocation to measure shifts in batcommunities in different habitats. AtAngelo Coast Range Reserve, 8 generalistbat species have been observed. Many ofthese are species of concern in Californiaduetoalackofresearchonbatpopulationdeclines (Gervais 2016). In addition,migratory bats, such as the hoary bat(Lasiuruscinereus)arecommontoNorthernCaliforniabutnotincludedonthespecieslist.Understanding how migratory bats temporally

andcompetitively fillniches isessential forconservingknownspeciesofconcern.We seek to understand how diverse bat

speciesassemblagescoexistbypartitioningresources spatially and temporally.Furthermore, we tested how bat speciesdiversity and abundance varies betweenhabitats. We also investigated whetherinsectabundanceaffectsbatactivityacrossdifferent habitats. We hypothesized thatvaryinghabitatswould support diversebatcommunities, and the level of bat activitywould be positively correlated withinvertebrate abundance. Bat diversity invarying habitats in relation to invertebrateabundance is important information tobetter understand bat ranges andinteractions of similar diet-based species.This knowledge can further explain theinfluenceofhabitatandfoodabundanceonnichepartitioning,whichmaybeveryusefulintheconservationofsensitivespecies.

METHODS

2.1NaturalHistoryofStudySystem

Our study was conducted at Heath andMarjorie Angelo Coast Reserve May 7 toMay 12, 2019. This University of Californiareserve,locatedinMendocinoCountyalongthe coast of Northern California (elevation378–1290 m), contains diverse habitats,including mixed conifer and broadleafforests, terracemeadows,chaparralbands,tributary watersheds, and 5 km of theupper South Fork Eel River. These diversehabitats cater to the needs of manydifferentbatspecies(Table1).

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Species Common Name Meadow Forest River Total

Antrozous pallidus* Pallid bat 2 0 0 2

Eptesicus fuscus* Big brown bat 2 1 15 18

Lasionycteris noctivagans Silver-haired bat 6 1 40 47

Lasiurus blossevillii Western Red bat 1 0 16 17

Lasiurus cinereus* Hoary bat 212 0 13 225

Myotis californicus California myotis 35 3 93 131

Myotis ciliolabrum* Western Small-footed myotis 17 3 2 22

Myotis evotis Long-eared myotis 0 2 0 2

Myotis lucifugus Little brown myotis 5 1 46 52

Myotis thysanodes* Fringed myotis 0 2 0 2

Myotis volans* Long-legged myotis 0 0 15 15

Myotis yumanensis Yuma myotis 8 6 1010 1024

Parastrellus hesperus* Canyon bat 1 0 1 2

Tadarida brasiliensis Mexican free-tailed 24 0 6 30

Total

313 19 1257 1589

Table1.Speciesabundanceanddistribution.Weobserved14differentbatspeciesandrecorded1,589batcallsfromMay 7–12, 2019 at Angelo Coast Range Reserve. We recorded calls at a meadow, stream and forest todeterminehowspeciesdiversityandabundancediffersbetweenthethreehabitats.* indicatesaspeciesnotonthespecieslist.

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2.2ResearchDesign

Todeterminehowbatcommunitiesdifferbetween habitats at Angelo Coast RangeReserve, we conducted bat andinvertebratesurveysinthreehabitattypes:a meadow, forest and river bank. Alllocations were within a 1 km radius. Ourmeadow site, South Meadow (39.7393,-123.6312), was an approximately 0.5 km2

meadow. Our forest site, dominated byDouglas fir (Pseudotsuga menziesii) andmadrone (Arbutus menziesii), was locatedapproximately 500 meters south of themeadow (39.73595, -123.6302). Lastly, ourstreamsitewaslocatedonasandybeach,3m from the edge of the South Fork of theEel River, and about 500 meters north ofthemeadow(39.74168, -123.6344) flankedbya cobblebaronone sideandbroadleaftreesontheother.We surveyed bat communities using the

EchoMeterTouch2modulewiththeEchoMeter application. This tool allowed us tomeasure bat call abundance but not theactual abundance of individual bats. Theapplication accounts for differences in callfrequencies, making activity a good proxyfor abundance. We analyzed the bat callsusing the waveform, spectrogram andfrequencies given by the Echo Meterapplication. We cross referenced these totheHumboldtStateBatLab’s2011trainingson the acoustic identification of bats todetermine the species of each call(Szewczak 2011). In addition, we analyzedthe spectrograms for feeding buzzes.Presenceoffeedingbuzzeswasdeterminedbased on increased patterns of steep andshort calls within the spectrogram of thecallofa singlebat (Figure1).Werecordedbat calls between 8:30 PM and 11:30 PMovertwonightsateachsite.

Figure 1. Spectrogram of Myotis californicus callincluding a feeding buzz. Using the Echo MeterTouch 2,wewere able to record echolocation callsofbatsthroughoutthenight.Thisimagedepictsthecall of a feeding M. californicus. A feeding buzz(circledinred)isasuddenclusterofsteepandshortcallsthatismadeinordertofocusonatargetasthebatapproachesprey.

In order to measure invertebratecommunities within the three sites, weattracted invertebrates to one area withlight traps. At each site (meadow, forestand stream), we hung three white sheets(approximately 4 m2 total), each markedwith a 0.5m2 quadrat.We projected bothwhite and UV lights to attract as manyinvertebratesaspossible.Every15minuteswecounted thenumberof spiders,moths,beetles, flies and other insects within thethree quadrats as a relative estimate ofinsect abundance in the area. During ourbat call recording on the second night ateach site, we measured invertebrateabundance in 15-minute intervals andidentifiedtheorderofallindividuals.

2.3StatisticalAnalysis

All statistical analyses were conductedusingJMPstatisticalsoftwarev14.0.Totestthe effect of bat abundanceonnumber offeedingcalls,we rana linear regression. Inordertocalculatethespeciesevenness(EH)we divided the Shannon Diversity Index ofcommunitiesateachsitebythenaturallogofspeciesrichness.Evennessvariesfrom0–

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1,with0beingacommunitydominatedbya few species, and 1 being a communitywithrelativelyequalnumbersofallspecies.Totestwhetherbatabundancevariedwithtime, and whether this was site-specificrelationship, we ran a multiple linearregression.Thispredictedbatabundancebytime,site,andtheinteractionbetweentimeand site. To test the effects of site oninvertebrate abundance, we used anANOVA and post-hoc Tukey-Kramer tests.To test the effect of site on types ofinvertebrates,weranat-test.

RESULTS

In totalwe identified 14 bat species and1,589calls(Table1).Ingeneral,therewasapositive relationship between batabundanceandfeedingcalls(n=454,R2=0.9,F=98.7,P<0.0001).Thefourmostabundantspecies in our study were Yuma myotis(Myotis yumanensis), hoary bat (Lasiuruscinereus), California myotis (Myotiscalifornicus),andtheWesternsmall-footedbat (Myotis ciliolabrum). Less abundantspecies include the pallid bat (Antrozouspallidus) and little brown myotis (Myotislucifugus). On nights where we used trapsforinvertebrates,thedominantbatspeciesateachlocationdidnotchange.Therefore,wecombinedallofourdataforeachsiteastoincreasereplication.TheriverwasdominatedbyYumamyotis

(ntotal=1257, nYuma=1110, EH=0.33, Fig. 2)(EH=evenness).Themeadowwasdominatedbythe hoary bat (ntotal=313, nHoary=212, EH=0.5). The forest had the most evendistributionofspecies(ntotal=19,EH=0.86),

Figure 2. Bat species abundance and diversity bylocation. Our forest site, at Angelo Coast RangeReserve, was dominated by Yuma Myotis(ntotal=1257, nYuma=1110, EH=0.33) (EH=evenness).South Meadow was dominated by the Hoary bat(ntotal=313, nHoary=212,EH=0.5). The forest was moreevenlydistributed(ntotal=19,EH=0.33).Weidentified14 different species in total, however, differentspecies assemblages were present at eachlocation. The forest also had the least speciesdiversity,withonly8speciesidentified.Themeadowandriverbothhad11speciespresent.

Figure 3. Effect of time and location on bat callabundance. We recorded bat calls at a stream,meadow, and forest atAngeloCoastRange reserveon two nights (each from 8:30 to 11:30 PM). Callsweremostabundantattheriver(n=1257),followedbythemeadow(n=313).Therewereonly19callsatthe forest. As the night progressed, all threelocations showed a decrease in bat call abundance(n=72, R2=0.9, FTime=11.4, Fsite=279.8, Fsite*time=4.0,PTime=0.0012, Psite<0.0001, Psite*time=0.023,). Theeffect of time on abundance was greatest at themeadow.

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Figure4.Effectoflocationoninvertebrateabundance.Therewasthehighestabundanceofinvertebratesatthemeadow light traps (mean=212). The forest and river had equal numbers of invertebrates (mean=25) (n=12,F=52.06mP<0.0001).Verticalbarsrepresent+/-1S.E.M(left).Batcallsweremostabundantattheriver,followedbythemeadow,andwereleastcommonintheforest(right).

but had the least diversity with only eightbat species. The meadow and river bothhad11speciespresent(Table1).Calls were most common at the river

(n=1257),followedbythemeadow(n=313)and least abundant in the forest (n=19)(Fsite=279.8,Psite<0.0001).Atalllocations,asthenightprogressed,batcallsbecame lessfrequent (n=72, FTime=11.4, PTime=0.001). Theeffect of time on call abundance wasdependent on site, with the largestdecreases in the meadow (Fsite*time=4.0,Psite*time=0.02,Fig.3).Invertebratesweremostabundant inthe

meadowanddidnotdifferbetween forestandriver (n=12,F=52.06,P<0.0001,Fig.4).Both the total invertebrate abundance(n=2934, F=34.12, P<0.0001) andunknown/small invertebrate abundance(n=2700, F=37.15, P<0.0001) differedbetweensites,butmothabundancestayedthesame(n=52,F=1.54,P<0.23).

DISCUSSION

Different habitats support differentabundances and assemblages of bats,suggesting that there is niche partitioningbetween bats at Angelo Coast RangeReserve. Within these ecosystems,invertebrate abundance and bat activityvaried. Our results support our hypothesisthat different habitats are occupied bydifferent assemblages, despite thegeneralist foraging behavior of all speciesfound. The river was dominated by YumaMyotis,which are known to primarily feedonsmallaquatic insects inthespringwhentheseinvertebratesemergefromthewater(Longetal.2009).Incontrast,themeadowcommunity was dominated by the hoarybat, one of the largest bats in the UnitedStates (0.9oz) (Brigham2002). FentonandBogdanowicz (2002) found that batphysiology affects foraging behavior, inwhich larger bats are more likely to eat

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largerprey.ThesizedifferencebetweentheYuma (0.18 oz) (Brigham 2002) and hoarybatslikelyallowthemtofilldifferentnichesandlocalizeindifferentmicrohabitats.Additionally, we found support for our

hypothesis that bat call abundance variesbetween habitats. The forest had thefewest calls, while the river had themost.Kalko (1995) found that echolocation callsvary in structure with respect to habitat.The cluttered forest may make it hard tomaneuver and locate insects throughecholocation, creating an unfavorablehabitatforbatstoforagein.Wedidnotfindanyspeciesthatwereuniquetotheforest,suggesting that bats may just be passingthrough on the way to their final foragingdestination.Inafuturestudy,wewouldliketosetupmistnetsatthethreesitestotrapbats and get a better measure ofabundance.Whilebatcallsareagoodproxyfor activity, there is no way to determinetheactualnumberofbatspresentwithoutcapturingthem.Finally, we did not find support for our

hypothesis that bat call abundanceincreases in areas of high invertebrateabundance. Instead, we found that therewere the most invertebrates in themeadow, which had an intermediatenumberofcalls.Wealsofoundthatfeedingbuzzabundanceismoredependentontotalbat abundance rather than invertebrateabundance. Moreover, bat body size isknown to indicate dietary needs, withbigger bats requiring more food (Brigham2002).Thehighabundanceofinvertebratesin the meadow likely attracts larger batswho need more prey and are able tooutcompete smaller bats. The dominantspecies in themeadow is the hoary bat, amorphologically large, migratory species.Hoary bats likely target the insect rich

meadow inorder tosatiate their increaseddemand for prey, before continuing theirmigration.Moreover,hoarybatsareknownto feed largely on moths (Valdez & Cryan2009),whichdecreaseinabundanceasthenight progresses (Edwards 2008). Theobserved decrease in bat activity in themeadowis likelycausedbythehoarybat’sresponse to an absence of prey. However,therewasnodifferenceinmothabundancebetweenhabitats.Thissuggeststhathabitatcharacteristics,combinedwithecholocationrestraints, may limit hoary bats to themeadow (Brigham 2002). Subsequentinvestigation should look at speciesinteractionswhenthehoarybatsarenotinthe area.Wewould predict that a smallernon-migratory bat fills this niche andassumethefunctionofthehoarybatinthemeadowecosystem.The river and forest, which had the

highest and lowest number of calls,respectively, had an equal (butcomparatively lower) abundance ofinvertebrates. We observed lessinvertebrates at the stream likely becausetheydidnot respond toour light traps. Tomore accurately survey the invertebratecommunity, we would set up traps witheither blacklights or regular lights. Thiswould ensure that the use of both lightswas not acting as a repellent. Additionally,we would set emergence traps and flightintercept traps at ground level and in thecanopy to capture invertebrates emergingfrom the river and flying above the river.Although generalist bat species may havesimilar diets, species diversity andabundance varied dramatically betweenmicrohabitats. Understanding nichepartitioning and localization of bat speciesgives insight into how bats are able tocoexist without competition. Specifically,

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studying areas with both migratory andnon-migratory species is important inunderstanding how niches are filledthroughouttime.Angelo Coast Range Reserve provides a

unique opportunity to study animalbehavior and interactions in extremelydiverse microhabitats within a small area.We identified six species that were notpreviously on the species list for AngeloCoast Range Reserve. One of these, thepallid bat (Antrozous pallidus), isexperiencing decline, and their preferredhabitat and distribution are becomingpatchier (Gervais 2018). Similarly, the littlebrown myotis (Myotis lucifugus), a knownresident of Angelo, has been experiencingwidespread population collapse due towhitenosesyndrome(Fricketal.2010)andwasrecentlyputontheendangeredspecieslist. Understanding how migrating speciesmay affect competition and put increasedstressonthe littlebrownmyotisandpallidbat increases our ability to protect andpreserve bats in Angelo Coast RangeReserve and other ranges. Furthermore,studyingnichepartitioningofbatspeciesindifferent microhabitats allows for a betterunderstanding of species’ interactions andmoreeffectiveconservation.

ACKNOWLEDGMENTS

This work was performed at theUniversity of California’s Angelo CoastRange Reserve, doi:10.21973/N3R94R.Special acknowledgements to courseprofessorsTimMiller,KrikorAndonian,andAnaMiller-TerKuile.

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