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Ecology and Evolution. 2022;12:e8657.
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1 of 15
https://doi.org/10.1002/ece3.8657
www.ecolevol.org
Received:27August2021
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Revised:31J anuar y2022
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Accepted :3Februa ry2022
DOI: 10.1002/ece 3.8 657
REVIEW ARTICLE
“Ecology of fear” in ungulates: Opportunities for improving
conservation
M. Colter Chitwood1 | Carolina Baruzzi2,3 | Marcus A. Lashley2,4
Thisisanop enaccessarti cleundertheter msoftheCreativeCommonsAttributionL icense,whichpe rmitsuse,dis tribu tionandreprod uctioninanymed ium,
provide dtheoriginalwor kisproperlycited.
© 2022 The Author s. Ecolog y and EvolutionpublishedbyJohnWiley&S onsLtd.
1Depar tmentofNaturalResourceEcolog y
andManagement ,Oklah omaState
University,Still water,Okla homa,USA
2Depar tmentofWildlife,Fisheries,and
Aquaculture,MississippiStateU niversity,
Starkville,Mississippi,USA
3SchoolofForest ,Fisheries,and
Geomat icsSci ences,UniversityofFl orida ,
Gaines ville,Florida,USA
4Depar tmentofWildlifeEcolog yand
Conser vation,Unive rsit yofFlorida,
Gaines ville,Florida,USA
Correspondence
M.Colte rChitwood,De part ment
ofNatura lResourceEcolog yand
Managem ent,Oklahom aStateUniversity,
Stillwater,OK,USA .
Email:colter.chitwood@okst ate.edu
Abstract
Becauseungulatesareimportantcontributorstoecosystemfunction,understanding
the“ecologyoffear”couldbeimportanttotheconservationofecosystems.Although
studyingungulate ecology offear is common, knowledge from ungulatesystemsis
highly contested among ecologists. Here, we review the available literature on the
ecologyoffearinungulatestogeneralizeourcurrentknowledgeandhowwecanlev-
erageitforconservation.Fourgeneralfocusareasemergedfromthe275papersin-
cludedinourliteraturesearch(andsomepaperswereincludedinmultiplecategories):
behaviora l responses to predat ion risk (79%), physiologic al responses to pre dation
risk(15%),trophiccascadesresultingfromungulateresponsestopredationrisk(20%),
and manipulation of predation risk (1%).Of papers focused onbehavior, 75%were
about movementand habitatselection. Studies were biasedtoward North America
(53%),tendedtobefocusedonelk(Cervus canadensis;29%),andweredominatedby
graywolves(40%)orhumans(39%)aspredatorsofinterest.Emergingliteraturesug-
geststhatwecanutilizepredationriskforconservationwithtop-down(i.e.,increasing
predationrisk)andbottom-up(i.e.,manipulatinglandscapecharacteristicstoincrease
risk or risk pe rception) approache s. It is less clear whe ther fear-related changes in
physiology have population-level fitness consequences or cascading effects, which
couldbefruitfulavenuesforfutureresearch.Conflictingevidence oftrait-mediated
trophic cascadesmight be improved with better replicationacross systems andac-
counting for confounding effectsof ungulatedensity.Improvingour understanding
ofmechanismsmodulatingthenatureoftrophiccascadeslikelyismostimportantto
ensure desirable conservationoutcomes.Werecommend future work embrace the
complexityofnaturalsystemsbyattemptingtolinktogetherthefocalareasofstudy
identifiedherein.
KEYWORDS
antipredatorbehavior,predationrisk,predator,prey,trait-mediatedef fects,vigilance
TAXONOMY CLASSIFICATION
Behaviouralecology
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CHITWOOD eT al .
1 | INTRODUC TION
The ecolo gy of fear was co nceptualize d by Brown et al. (1999) as
the “melding of the prey and predator's optimal behaviors with
theirpopulationandcommunity-levelconsequences.”The ecology
of fear conce pt synthes ized the two ap proaches t o predator–prey
interac tions (Hunter & Pr ice, 1992; Paine, 1980; Peck arsky et al. ,
2008;Polisetal.,2000):(1)predatorskillpreyforfood(Lima,1998;
Schmitz et al., 1997; Taylor, 1984); and (2) predators scare their
prey(Lima&Dill,1990;Peckarskyetal.,2008;Preisseretal.,20 05;
Schmitzetal.,2004;Trusselletal., 2006).These direct(i.e., lethal)
andindirect(i.e.,non-lethal,non-consumptive)effect sof predation
combinetoaffectpreyandtheirinteractionswiththebroaderfood
web,which can generateindirecteffec ts throughprocessesinand
across ecosystems (Hawlena & Schmitz, 2010a, 2010b; Hawlena
etal.,2012;Peckarskyetal.,2008;Schmit zetal.,2010;Teckentrup
etal.,2018).
Theecologyoffearhasgainedmomentuminrecentyears,hav-
ingbeenappliedtovariousterrestrialandaquaticsystems(Dudeck
etal.,2018;Michaudetal.,2016;Nunesetal.,2018).Aplethoraof
literaturehasfocusedonungulateresponsestopredationrisk,likely
becauseungulates andtheir vertebrate predators are oftencharis-
matic(e.g.,graywolves[Canis lupus]andelk[Cervus canadensis])and
thusgarnerthemostattentionfromabroadanddiverse audience,
particularly when set in well-known locations (e.g., Yellowstone
National Park, USA; African savannas). Moreover, ungulates are
widespread globally,important economically and ecologically,and
areoftensympatricwithlarge,apexpredatorsthatareofconserva-
tionconcern(i.e.,threatened,endangered,rare,reintroduced).Thus,
broad rev iew and under standing of t he state of res earch into the
ecologyoffearis warranted, particularlygiventheinterestinusing
theecologyoffearforconser vation(Gaynoretal.,2021).
Recently,researchershavebeguntosummarizeresearchtopics
related tothe ecology offear, including non-consumptive effects
ofpredation(Say-Sallazetal.,2019),theroleoflargecarnivoresin
restorationecology (Alston etal.,2019),methodologicalvariation
inchar ac te rizin gpred ationrisk(Mol let al.,2017),andimprovingin-
ferenceinst udiesofp redatio nrisk(Pr ughetal.,2019).I mp or tant ly,
these studies are highlighting shortcomings andbiases that could
affectconservationandmanagementdecisions.Forexample,Say-
Sallaz et al. (2019)highlighted astrongtaxonomicandgeographic
bias ass oci at edw it hre s ea r ch onn on-co nsu mpt iveef f ect sof pre da-
tioni nl ar geterres tr ialm am ma ls ,n ot in gt ha tgraywo lvesan dN or t h
America dominated the peer-reviewed literature. Likewise, they
determi ned that antipred ator behavioral r esponses of prey com -
prisedthemajorityoftheliteratureonnon-consumptiveeffectsof
predati on (Say-Sallaz et a l., 2019). Other recen t work highlighte d
atendencyamongresearcherstosimplifyotherwisecomplexsys-
tems by focus ing on one carn ivore and one ung ulate when mos t
systems b eing studied h ad multiple spe cies of carnivore s and/or
ungulates(Mont gomeryetal.,2019).St udydesignswit houtexper i-
mentalandlongitudinalcomponentslikelyoversimplifyresultsand
could bemisleadingortoogeneralto be appliedtoother systems
(Montgomery et al.,2019). Thoughthese reviews identify biases
that could af fect large mammal conser vation and management,
none of them summarized the myriad research topics and results
alreadypublishedonungulatesundertheecologyoffearconcept.
Toaddress biases,improvefuture studydesignsonpredationrisk,
andultimatelyimproveourunderstandingof how tousetheecol-
ogy of fear inconservation,wesought to compile and summarize
thecurrentbodyofworkfromwhichfuture studiescoulddevelop
increasinglycomplexquestionsintofeareffectsandtheirrelevance
toecology,evolution,conservation,andmanagement.
2 | METHODS
We conducte d a literature se arch for arti cles using the key words
“ungulate”and“ecologyoffear”or“landscapeoffear”inthesearch
engineGoogleScholar.Wepurposelykeptoursearchtermsgeneral
toallowresearchthemestoemergefromthepublishedrecord,and
weusedeachpaper'sliteraturecitedtosnowballsampleotherrele-
vantwork.Wenotedthatmoststudiesonungulatesandtheecology
offearfailtofullydisentangledirectandindirecteffect s(Peersetal.,
2018);however,wecontendstudiesrelatedtobehaviorandphysiol-
ogy are more well disentangled than those documenting other in-
direct e ffect s in ecosystem s. Thus, we consi dered the ar ticles we
found to be valuable research onthe ecology of fearinungulates,
withthecaveatthatthemechanismsbehindthoseeffects maynot
bedefinitiveinallarticlescited.Also,thoughwereferto“ungulates”
broadlythroughoutthispaper,ourfocuswasonungulatesforwhich
fear-basedpublishedworkappearedinoursearch.Thus,wedidnot
conductsearchesforspecificungulatespecies(commonorscientific
names)orgroups.Wesearchedforstudiesbetween1999(whenthe
ecologyoffearconceptwaspublished)andJuly2018.Additionally,
weestablished aG oogle ScholarAlertthatflaggedpapers indexed
on Googl e Scholar af ter our searc h and before we com pleted our
reviewofallthepapers.Thisapproachallowedustoincludeseveral
paperspublishedin2018a nd2 019,aftertheconclusionofourman-
ual search. Though many ungulate-focused predator–prey papers
before 1999 could also be nested under the ecology offear para-
digm,wechosetofocusonmorerecentliteraturewhereinterestin
the topic a mong acade mics has inc reased, as in dexed by citat ions
peryearofBrownetal.(1999;Figure1).
Aftersurveyingtheliterature,wegroupedpublicationsintofour
areasoffocus,withsomepublicationsf ittingundermult ipl ecatego -
ries.Theareasoffocuswerebehavioralresponsestopredationrisk,
physiologicalresponsestopredationrisk,trophiccascadesresulting
fromungulateresponsestopredationrisk,andmanipulationofpre-
dationrisk.Wedefinedabehavioralresponseasanyreactiveorpro-
active r esponse of ung ulates to pre dation risk s, includin g changes
at fine-scal e (e.g., vigilance) or br oad-scal e (e.g., habitat use). We
definedphysiologicalresponsesas any change inthephysiologyof
ungulatesas a result of predation risks, including changes in body
chemistry (e.g., stresshormones)or diseaserisk. Wedefined atro-
phiccascadeasoccurringwhenpredatorsalteredungulatebehavior,
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CHITWO OD eT al .
resultingintherelease ofplants from herbivory (Polisetal.,20 00);
thiscouldincludeanychangeintheplantcommunity(i.e.,plantdis-
tribut ion, abunda nce, or stru cture) resu lting from th e influence of
predationriskonungulates.Also,trophiccascadesincludedcascad-
ingef fectsofungulateresponsestopredation riskon otheranimal
taxaorecosystemprocesses.Wedefinedmanipulationofpredation
riskasanyactiontakenorthat could betaken byhumanstointen-
tionallycausefear(i.e.,increasingperceivedoractualpredationrisk
viatop-downorbottom- upmanagementappr oaches)toevokeade-
sirableecologicalconsequence.
3 | RESULTS AND DISCUSSION
Theliteraturesearchyielded275studiesrelevant totheecologyof
fear in ungulates (Appendix S1). While most paperscovered multi-
pletopics,themoststudiedareaoffocuswasbehavioralresponses
topredation risk (e.g., habit at selection,space use, vigilance; 79%;
n =216;Figure2a).Somestudieswerefocusedontrophiccascades
(20%;n =56),whilefewerfocusedon physiologicaleffects offear
(15%;n =41)and only three(1%)on manipulation ofpredation risk
for wildlifemanagement (Figure2a). More than half of the studies
tookplaceinNorthAmerica(53%;n =145;Figure2b),mainlyinthe
GreaterYellowstoneEcosystem(n =60;22%of all studies;41%of
NorthAmericanstudies). Fewer studies were conducted in Europe
(20%; n = 56), Sub-Sahar an Africa (16%; n = 45), and othe r world
regions (11%;n =29; Figure2b). Overall,81ungulatespecieswere
studiedsince thefear concept was first published, with studies of
elkcomprisingthelargest proportion(29%;n = 79;Figure 3a).The
majorityofresearchwasfocusedonjustafewpredators,dominated
bygraywolves(40%;n=111;Figure3b)andhumans(39%;n = 107;
Figure3b)thattogetheraccountedfor79%ofthestudies(n =218).
3.1 | Behavioral responses to predation risk
Inthepresenceofpredators,prey generally alter theirbehaviorto
becomemoredifficulttocapture,detect,orencounter.Antipredator
behaviorsare acomplexsuite ofinnate andlearnedbehavioralre-
sponses, which can be individual or species-specific (Chamaillé-
Jammes et a l., 2014; Thurfjel l et al., 2017). They can b e affected
by predator s pecies and hab itat charac teristic s. For example, a m-
bush pred ators make animals m ore fearful of com plex vegetative
struc ture with poor vis ibility likely be cause of uncert ainty in the
FIGURE 1 Thenumberofcitationsperyear(accordingto
GoogleScholar)ofBrownetal.(1999),whoconceptualizedthe
ecologyoffear
20
40
60
80
100
2000 2005 2010 2015 2020
Year
Number of citations
FIGURE 2 Proportionofresearchpapersfocusedoneachoffourmajortopicareasofstudy(a)andpropor tionofresearchpapersby
geographicareaoffocus(b).Becausepaperscouldcovermultipletopics,proportionsinAdonotsumto1
0.4%
0.4%
0.4%
1%
3%
3%
3%
16%
20%
53%
Central Asia
North Africa
Oceania
South Asia
Latin America
Middle East
East Asia
Sub Saharan Africa
Europe
North America
0% 20%40% 60% 80%
1%
15%
20%
79%
Manipulation of Risk
Physiological Responses
Trophic Cascades
Behavioral Responses
0% 20%40% 60%80%
(a) (b)
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CHITWOOD eT al .
predator l ocation (Lone et a l., 2014), whereas curso rial predators
makeanimalsmorefearfulofareaswithhighvisibilityand poor es-
capability(Riginos&Grace, 2008;Ripple &Beschta,2003,2006a).
Additio nally, human ac tivities c an elicit fea rful res ponses in un gu-
lates and, in human-dominated landscapes, human presence and
activ ity can af fect ungu late behavior a nd predator–prey d ynamics
(Ciuti et al., 2012; Shannon et al.,2014).Humanhunting couldop-
pose adaptive responses to nat ural and sexual selection through
exploit ation-induced evolutionary change (Ciuti et al., 2012). We
separatedthestudiesofungulatebehaviorinresponsetopredation
risk (n = 216) into two subtopics: movement and habitat selection
(75%;n =161)andvigilanceandherding(32%;n =70).
3.1.1 | Movementandhabitatselection
Habitatqualit yisimportantto howungulatesreducepredationrisk
(Bleicher,2017).Infact, animalscanmitigatepredation risk in vari-
ouswayssuchasreducing the time spent foraging, foraginginless
riskyareasoratlessriskytimes,orincreasingvigilancewhenforag-
ing in risk y places (Brow n, 1999; Gehr, Hofer, Ryser, et al., 2018).
Inthisway,animalsmovearound the landscape adjusting theirbe-
havior to accommodate spatiotemporal variation in predation risks
(Basilleetal.,2015).
Spatial avoidance is commonly reported in ungulates to reduce
predationrisk, but less workhasdocumentedtemporalchanges to
avoidrisk. Severalspecies suchas muledeer(Odocoileus hemionus;
Laundré,2010),elk(Bacon&Boyce,2016; Fortinetal.,2005), and
hartebeest (Alcelaphus buselaphus; Ng’we no et al., 2017) exhi bit a
negative relationship in spatial distribution with predation risk.
However, avoidance c an be mediated by r esource availab ility. For
example , hartebees t, plains zebra (Equus quagga), an d Grant's ga-
zelle (Nanger granti) prefer a reas with high g rass biomass t o areas
ofhighvisibilit yduringdroughts(Riginos,2015).Astudyofac tivit y
patternsinSundacloudedleopard(Neofelis diardi)showsthatinthe
absenceofcloudedleopards,beardedpigs(Sus barbatus)weremore
nocturnalthanwhenleopardswerepresent,perhapsindicatingthe
beardedpigs altertheir activity pattern to decrease predation risk
(Rosseta l. ,2013) .O nes tud yl ookedatro ed eer (Capreolus capreolus)
spatialandtemporalbehaviorreportingthatroedeeravoidareasof
highchronicpredationby Eurasian lynx (Lynx lynx)at nightbutnot
duringthedayinsummerbecauselynxactivityislowduetohuman
disturbanceduringtheday(Gehr,Hofer,Pewsner,etal.,2018).
Thedecisionofwhereandwhentoforageorseekcoveroccurs
across spatiotemporal scales (Lima & Dill, 1990) and even small
habitat changes can playan import antrole in prey habitat selec-
tion because they affect prey cost oflocomotion (Gallagher etal.,
2017). Altend orf et al. (2001) con cluded that mule de er respond
topredation risk from mountain lions (Puma concolor)by changing
their foraging decisions at the scales of vegetation types and spe-
cific featuresofthevegetationt ype such as edges.Atfiner scales,
many studies have documented behavioral responses to predation
riskrelatedtoforageselectionandquality.Forexample,bison(Bison
bison)reducedselectionofhigh-qualit yforagingsites(i.e.,siteswith
abundantCarex atherodes)aswolfriskincreasedinwinter(Fortin&
Fortin,2009).HamelandCôté(2007)repor tedthatfemalemountain
goat s(Oreamnos americanus)tradedoffforageabundance(andsome
forage quality) for safetycover.Similarly, some studies have linked
behavioraleffectsofpredationrisktofine-scalelandscapefeatures
and vegetative cover. For example, Nubian ibex (Capra nubiana)
FIGURE 3 Proportionofresearchpapersfocusedondifferentungulatetaxa(a)andproportionofresearchpapersfocusedondifferent
predatortaxa(b).Becausepaperscouldincludemultipleungulateandpredatortaxa,proportionsdonotsumto1
3%
4%
4%
5%
5%
5%
5%
5%
6%
11%
39%
40%
Lynx lynx
Acinonyx jubatus
Ursus americanus
Lycaon pictus
Panthera pardus
Ursus arctos
Crocuta crocuta
Canis latrans
Puma concolor
Panthera leo
Homo sapiens
Canis lupus
0% 10% 20% 30% 40%
3%
3%
3%
3%
3%
3%
4%
4%
4%
5%
6%
7%
7%
7%
7%
7%
8%
8%
29%
Alcelaphus buselaphus
Giraffa camelopardalis
Nanger granti
Taurotragus oryx
Phacochoerus africanus
Sus scrofa
Tragelaphus strepsiceros
Bison bison
Syncerus caffer
Connochaetes taurinus
Aepyceros melampus
Odocoileus hemionus
Rangifer tarandus
Alces alces
Capreolus capreolus
Cervus elaphus
Equus quagga
Odocoileus virginianus
Cervus canadensis
0% 10%20% 30%40%
62 other species of ungulates each comprise
less than 2% of research papers
19 other species of predators each comprise
less than 2% of research papers
(b)(a)
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CHITWO OD eT al .
perceivedgreater risk of predation as their distance fromcliff and
slope edgesincreased, and theirperception of risk decreasedwith
vegetativecover (Iribarren& Kotler, 2012). Likewise, Kuijper et al.
(2013)lin kedco ar se woodydebristofine-sc al eriskef fectsonungu-
latesinthepresenceofwolves.
Movement,spaceuse,andhabitat selection also likely relateto
predatorhuntingmode.Forexample,astudyinSouthAfrica(Thaker
etal., 2011)using seven ungulates andfive largec arnivores deter-
minedthatmostof thesmallerprey species(e.g.,impala[Aepyceros
melampus])avoidedthespaceuseofallpredatorstoreduceprobabil-
ityofencounter.Concomitantly,largerspecies(e.g.,bluewildebeest
[Connochaetes taurinus])onlyavoidedareasofintensespaceuseby
lions(Panthera leo)andleopards(Panthera pardus).Theauthorscon-
cludedthatungulates usedasimplebehaviorrule:avoid areasused
bysit-and-pursuepredators(lionandleopard)butincreasewariness
inareasusedbycursorialpredators(e.g.,cheetah[Acinonyx jubatus]
and African wild dog [Lycaon pictus]).Similarly,otherstudiesusing
predator excrementatforaging areasmonitored withcamera traps
demonstrated red deer (Cervus elaphus) were not only app arently
able todiscernhunting modefromthe typeofexcrement present,
but also us ed different ant ipredator behavio rs to mitigate risk of
each thr eat (Wikenro s et al., 2015). Red de er spent less t ime for-
aging at sites whenthreatened by ambush-style predation riskbut
onlyadjustedvigilanceundercursorial-stylepredationrisk.Multiple
decision rulescombine to affect ungulatespace use (and otheran-
tipredator behaviors), especially in multi-predator systems where
predatorsdifferinhuntingmode(Thakeretal.,2011).
Some stu dies have repor ted weak eviden ce for behavior al re-
sponsestopredationrisk.Forexample,Nicholsonetal.(2014)found
littlesuppor tthatmoose(Alces alces)habitatusewasdependenton
predationriskfromwolves, thoughtheyacknowledged severalun-
derlyingexplanationsthatcouldhavebeenconfounding(i.e.,intense
harvestbyhumans, no time to adaptto recolonizingwolves, adap-
tation mayoccur atfiner scalesthanmeasured).Similarly,Samelius
et al. (2013) conc luded that recol onizing lynx (Lynx lynx) had lim-
itedef fect son habit atselectionofroedeer(Capreolus capreolus)in
Sweden.Theauthorssuggested theirresultsprovided evidencefor
the compl exity of prey r esponses to r isk and that suc h responses
li ke lywer eva ria ble bet w eenec osy s tem sa n dp red ato r–p reyco nst el-
lations(Sameliusetal.,2013).ResultsfromHernándezandL aundré
(2005) may support this premise,astheyconcludedthatpredation
pressurefrom reintroduced wolvesshiftedelkhabitatuse thereby
decreasingtheirdietqualitybutdidnotresultinasimilarchangein
spaceuseordietqualityofbison.Theweakevidenceforbehavioral
responsesto predation risk inthese studies, coupledwithdiffering
responsesofsympatricungulates,maybelinkedtopredatorhunting
mode(Thakeret al., 2011),antipredatorstrategiesoftheungulates
(Ebyetal.,2014),sizediscrepanciesbetweenpredatorandprey(Eby
etal., 2014),a lackofa response, or failure to detectitwith study
designorsamplesize.
One intere sting behavioral concept that relates to movement
and habit at select ion is the idea th at ungulates ar e using intragu -
ild intera ctions to me diate the land scape of fea r by concentrat ing
activity in proximity to humans as a shield to other predators
(Berger, 2007; Schmitz et al ., 2004). Beca use humans are preda-
tors of ungu lates, situat ions where hum ans are used as sh ields to
otherpredators representaninteresting twist, whereby ungulates
apparen tly perceive h umans as les s threatenin g than other p reda-
tors.Thus, ungulatesmayactuallyuseacarnivore'sfearofhumans
totheirownbenefit.For example, Berger(2007) documented syn-
chronyinmooseparturition,whichinvolvedchangesinmoosespace
usecommensuratewithcarnivorerecolonization.Mothersinareas
free of brown bears(Ursus arctos) and non-parous females did not
alterspaceuse,whilethosegivingbirthdidsonearertopavedroads
avoidedbybrownbears(Berger,2007).Similarly,muledeerfemales
appear tocompensateforgreaterexposuretopredationriskby in-
creasing theirac tivit yandherbivoryintensit yclosetoa remotebi-
ological field station, presumably because they could forage more
selectively in areas coyotes avoided due tohuman activit y (Waser
etal.,2014).Suchresultsindicatethatshift sinspaceuselikelyhave
occurredin other mammalian taxa in the presence of humans and
thatresearchersshould accountfor indirect anthropogeniceffects
on species distributions, behavior, and interactions (Berger,2007).
Fearofthehuman“superpredator”mayberelevantforlargecarni-
vores(Smithetal.,2017)andungulates(Crawfordetal.,2022)alike,
buttheextenttowhichsuchfearvariesacrosslandscapesandtaxa
isunknown.Forexample,predatorssuchascoyotesmayberesilient
tourbanization,andthus,initiateevenmorecomplexpredator–prey
interactionsinurbanareas(Jonesetal.,2016).
3.1.2 | Vigilanceandherding
Vigilanceofpreyspeciesisoneoft hemoststudiedaspect sofan-
tipredatorbehaviorbecauseitisoneofthemostcommonadapta-
tio nsusedb yanimalsforeva lu atingpr ed at ionrisk an disre lativel y
easy to mea sure (Benois t et al., 2013). Time sp ent scanning f or
predatorsgenerallypreventsanimalsfromotheractivities(butsee
Périquetetal.,2012andBergvalletal.,2016),suchasforagingor
grooming,sothatanimalsmustcarefullytradebetweenreducing
riskandacquiringenergy (Creel,2018;Illius& Fitzgibbon,1994).
Theamountoftimeallocatedinvigilancedependsonriskpercep-
tion.Forinstance,Drögeetal.(2017)showthatAfricanungulates
(i.e.,ha rte be est ,plai nzeb ra,an do ribi[Ourebia oribi])increasevigi-
lancewhenclosetopredatorsinplaceswherepredatorencounter
probabi lity is high. V igilance als o depends on h erd size beca use
herdingungulates generallyrelyon group vigilancesothatindi-
viduals can spendless time scanningfor predators as groupsize
increases(Lima& Dill,1990). As such,herdsizeis also relatedto
riskperception.Forinstance,Molletal.(2016)repor tedthatherd
sizeinsever alAfricanun gu lates pe ciesdepends onpreda torhunt-
ing mode anddurationofpredation risk.However,vigilanceand
herd size are not alwaysdirectlyrelated,astheyalso dependon
other fa ctors affec ting individ ual risk such as rep roductive s ta-
tus(Lietal.,2012),sex(Barnieretal., 2016;Benoistetal.,2013),
offsp ring presen ce (Blanchar d et al., 2017; Lashley et a l., 2014),
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CHITWOOD eT al .
intraspecific competition (Biggerstaffetal.,2017;Fattorini etal.,
2018), habitat features (Pays et al., 2012), cover and visibility
(Iranzoetal .,20 18;Paysetal .,20 12 ),preyfora gi ng st rateg y( Cr eel
etal.,2014),andpredatorpresence(Iranzoetal.,2018).
We still do not fully understand the nuances of antipredator
behaviorslikevigilance andherding (Beauchamp, 2019).Forexam-
ple,Creel et al. (2008)determined that Gallatinelkweremore vig-
ilantthanNorthernRange elk despitelowerbackgroundriskin the
Gallatin C anyon. Ind eed, Le Sao ut et al. (2015) prov ided eviden ce
thatvigilancebehavior probably persists atsome level,evenin the
absence of predation risk. Pre sumably, the costs ass ociated with
overt vigilancearetoolow in some casesto generatestrong selec-
ti o npre s s u ref o rnon - v igil a ntp h e n ot ypes, p a r t icul a r l ygi v ent h e con-
sequencesofbeingunequippedtoavoidpredationinthefuture(Le
Saoutetal.,2015).Likewise,thelevelofriskmayinteractwithgroup
size to affec t vigilance re sponse in some c ases but not in oth ers,
andvigilancemayalsobeusedtomonitorconspecifics,especiallyin
low-risksituations(Beauchamp,2019).Olfactory andauditor ycues
areusedtoassessrelativerisk,buttheyarealsounderstudied(Lynch
et al., 2014). For example,the odor of wolves and lynx cancreate
fine-scal e risk facto rs for red dee r (Kuijper et al., 2 014;Wi kenros
etal.,2015). As noted earlier,reddeer apparentlydiscernbet ween
thepredatorhuntingmodebasedonodorsfromexcrement,adjust-
ingtheir antipredator strategyaccordingly(Wikenroset al., 2015).
However,ourunderstandingofhowolfac toryandauditor ycuesare
usedin avoiding predationriskisrudimentary,andweneedfurther
researchtoevaluatetheuseofolfactor ycuesindifferentspecies.
3.2 | Physiological responses to predation risk
Ungulatesmustbalanceforageacquisitionandriskavoidance,which
necessitatesinterplaybetweenphysiologyandbehavior(McAr thur
etal.,2014).Ascantamountofresearchgoesevenfurther,likening
ungulatep hysiologic alre sp on se st opar as it is manddiseaseto th er e-
sponsesdocumentedunderfearofpredation.Behavior,asdiscussed
intheprevioussection,isaninterfacethatenablesungulatestouse
orleaveforage patches depending on theirphysiological tolerance
torisk (McArthuret al., 2014).By default,these behavioralchoices
inresponsetopredationriskca nberelatedtodietqualityandnutri-
tionalcosts,andwechosetoincludedietqualityandnutritioninthis
section,whilerecognizingthattheyaretopics arguably sortedinto
“behavior”aswell.Weseparatedstudies on ungulatephysiological
responsestopredationrisk(n =41)intotwosubtopics:dietquality
andnutrition(71%;n =29)andfitnessandphysiolog y(32%;n =13).
3.2.1 | Dietqualityandnutrition
Behavioral responses adopted by prey species under threat of
predation induce import ant risk effects on the prey, especially
nutrit ionally-me diated risk eff ects. As p reviously ment ioned, prey
mayswitchtolowerqualityfoodpatchesifriskisdecreasedenough
towarrant the cost toforagingor ungulates mayreduce theirfood
intaketoincreasevigilance.Forexample,plainszebrasincloseprox-
imity tolions had a lower quality diet,indicating that adjustments
in behavio r when near lion s carry nu tritional cos ts (Barnie r et al.,
2014). White-t ailed deer (O. virginianus) switche d to an abundant
low-quality food (i.e.,oak Quercus spp.) in responsetostressfrom
coyotes(Cherry,Warren,et al., 2016).Similarly,predationpressure
fromreintroducedwolvesintheGreaterYellowstoneEcosystemin-
ducedshiftsinelkhabitatuse,whichloweredthequality oftheelk
diet(Hernández&Laundré,2005).However,nutritionally-mediated
riskeffectsarenotnecessarilyubiquitousinallpredator–preyrela-
tionships,asHernándezandLaundré(2005)alsoreportedthatbison
didnotdisplayasimilarchange inhabitatuseanddietaryqualityto
whattheyobservedinelk.
An emerg ing literature bas e also indicates th at predation risk
cancausephysiologicalchangesthataltertheperceivedrelativeim-
portanceofnutrients,which mayaffectdietarychoicesandhealth
(Hawlena & S chmitz, 2010b). Th is has been well de monstrated i n
an arth ropod syste m where spide rs change diet se lection of pr ey
by changing i ts physiologic al demands for c arbohydrates (B arton,
2010;Beckermanetal.,1997;McMahonetal.,2018;Rothleyetal.,
1997; Schmitz, 1998). Interestingly, similar results have been re-
portedinvertebratetaxa(Carmassietal.,2015;Clinchyetal.,2013;
Klingamanetal.,2016;Leaver&Daly,2003),butexamplesfromun-
gulateshavenot beenrepor ted.Althoughdemonstratingpredation
risk inducingphysiological changes that manifest in health and be-
haviorisinherentlydifficult,thisnewfrontierofmergingnutritional
ecologywithpredationrisktheoryhasthepotentialtoadvanceour
understandingoftheecologyoffear.
3.2.2 | Fitnessandphysiology
Boonstra (2013) suggested that several ungulate species that
evolved with largepredatorsare adaptedtocoping with predation
pressureandthereforethey sufferfrom acutestress (i.e.,elevated
glucocor ticoidsblood levelfor minutestohours). Onthe contrary,
othermam ma ls pecie ssuc ha ss no ws hoehareorarct icgroun ds qu ir-
rel may suf fer from chronic s tress showing elev ated chronic (i.e.,
daystoweeks)glucocorticoidsbloodlevel,whichmayhavenegative
fitnessconsequences(Boonstra,2013),evenforfuturegenerations
(Sherif f et al., 2010). Some research investigating glucocorticoid
stresshormonesstudyingungulatesreportedsimilarpatterns(Creel
et al., 20 09; Le Saout e t al., 2016; Pecore lla et al., 2016; Pér iquet
etal.,2017;but seeZwijacz-Kozicaetal., 2013),but further inves-
tigationonungulatehormonalresponsetopredationanditsfitness
consequencesareneeded.Infact,predationhasbeenrelatedtode-
creased fecundity in hartebeest (Ng’weno et al., 2017)and white-
taileddeer(Cherr y,Morgan,etal.,2016,butseeMicheletal.,2020)
andcontrastingresultshavebeenreportedinelk(Creeletal.,2011;
Middleton et al., 2013). Predator-induced stress and selection of
low-qualityforagetoavoidpredationhavebeensuggestedtocause
decreas ed fecundity (C hristianson & Cre el, 2010; Ng’weno et al .,
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2017),butthespecificpathwaysthroughwhichpredationindirectly
affectindividualfitnessstillhavetobedefined.
3.3 | Trophic cascades resulting from ungulate
responses to predation risk
Ungulatesrepresenttheintermediatetrophic level,potentiallylink-
ing apex predators to changes in plantcommunities. Thus, trophic
cascades are caused via behavioral adjustments and density re-
sponsesofungulatestopredationriskthat,inturn,affectthedistri-
butionsandrelativeabundancesofplantsandmayindirectlyaffect
other biota and ecological processes as well (Beschta & Ripple,
2009;Estesetal.,2011;Ripple&Beschta,2012;Ritchie&Johnson,
2009). Two type s of trophic ca scades have be en describ ed in the
literature: (1) density-mediated, and (2) trait-mediated (Werner &
Peacor,2003).Density-mediatedtrophic cascades occur asa result
ofungulatepopulationregulationbyapexpredators,whichrelease
palatable plant species fromherbivory.Trait-mediatedtrophiccas-
cadesresultfromungulateantipredatorbehaviorsinresponsetothe
perceptionofpredationrisksthatareinvokedbypredators(seepre-
vioussectionsonbehavior and physiology for examples ofspecific
traitmodifications).
Trait-mediatedtrophic cascades could releaseplantsfromher-
bivory d ue to spatial avoida nce or decrease s in foraging ra te due
topredatorpresence(Ripple etal.,2016).Studieson trait-mediated
trophic c ascades generally entail systems with a single prey and
predator,whichcreatesaknowledgegapregardingtrophiccascades
inmorediversepredatororpreycontexts(Flageletal.,2016;Ripple
et al., 2015). Many historical ecosystems had multiple predators
with each hunting mo de, making the behavioral decisions of the
ungulatemorecomplicatedandthe resulting trophic cascadepre-
sumablymorecomplex;thus,thetri-trophiccasc adegenerallystud-
iedmight not represent all complex situations (Norumetal.,2015;
Schmitz et al., 200 4; Thaker et al., 2011). For example, Ford et al.
(2015)repor tedthatthereintroductionofAfricanwilddogs(Lycaon
pictus)suppresseddikdik (Madoqua guentheri) populations but did
notresultintrophiccascadestotheplantcommunity,likelybecause
ofherbivorediversity inthesystem.Furthermore, surrogatepred-
ators, ei ther introduced o r invading, may or may not c ause trait-
mediated trophiccascadessimilar to that ofnative predators, even
iftheyhavethesamegeneralhuntingmode.Asanexample,coyotes
have recently expanded their range acrosseastern North America
(Hody&Kays,2018),andstudiesinthesoutheasternUnitedStates
haveimplicated themas an importantpredatorand primary cause
of sharp population declines of white-tailed deer in some areas
(Chitwo od et al., 2014; Chit wood, Lash ley,K ilgo, Moorma n, et al.,
2015; Chitwo od, Lashley, Kilgo, Pol lock, et al., 2015; Kil go et al.,
2012). Thoug h they are coursin g predators sim ilar to the primar y
historical predator(i.e., red wolf [Canis rufus]),recentliterature has
repor ted coyote selec tion agains t behavioral t raits of whit e-taile d
deer that h ad presuma bly evolved as an a daptive res ponse to red
wolves(Chitwoodetal.,2017).Moreover,coyotesaremoreresilient
thanwolves tourbanization,so they may exertgreater controlson
ungulate s in urbanized lands capes (Jones et a l., 2016). That said,
coyotescanhavecascadingeffectsonplantcommunitiesbyaltering
traitsofwhite-taileddeer(Cherry,Warren,etal.,2016).Considering
the rapidly changing climate and burgeoning human urbanization,
theex pec tati on sofpredator se xp andingranges intonewar ea sisre-
alis ticandt heeffe ct sofnewpredatorsandnewpredator–preycon-
texts may becomeanincreasingly impor tant areaof focus.Indeed,
trait-mediated trophiccascadescan be mediatedbyseveral poten-
tially interactingfactors, leading to debateonthe actual existence
ofthe trophic cascades. Many observations have been scrutinized
andcontrastingresultshave beenpresented (Creel&Christianson,
2009;Kauffmanetal.,2010),bringingintoquestionwhetherornot
trait-mediatedindirecteffectsareimportantpartsofecosystemsor
rather ju st the resul t of research fa iling to disent angle them f rom
density-mediatedmechanisms.
Predic ting the stren gth of trophi c cascades (i .e., how far they
reachacrosstaxaandecologicalprocesses,aswellasthemagnitude
of their ef fects) is com plicated bec ause a multit ude of factor s af-
fectsthis phenomenon(Schmitzet al., 200 4).ShurinandSeabloom
(2005)r epo r te dth es t re ngthofcascad eswasre lated to sizedis cr ep-
ancybetweenherbivoresandplants,whereaspredatorbodysizein
relation to the ungulatehadnoeffect.Contrastingly,DeLong et al.
(2015)reportedthatpredatorbodysizewasimportantindetermin-
ingthestrengthofresultanttrophiccascadesbecausethestrength
ofpredator-preyinteractionsgenerallyincreaseswithpredatorsize.
Also,predatordensitymightbeimportantinthestrengthofthere-
sultingtrophicc ascades.Forexample,BeschtaandR ipple(2010 )re-
po rte dt herei nt rod uc t io no fM exi canwolv es (C. lupus baileyi)didnot
resultinatrophiccascadeonaspeninArizona,perhapsbec ausethe
densityofwolveswastoolowrelativetoelkdensities(i.e.,3wolves
per100elk).
There are t hree ways trophic cascades are gener ally studied:
(1)p redator rem oval or exclusio n, (2) predato r reintrodu ction, an d
(3)ungulate exclusion(Sheltonet al.,2014).The first two methods
are fundamentally dif ferentin that predator removals are measur-
ing the tro phic cascad es leading to what is cons idered ecologi cal
degradation (Côté et a l., 2004), and predator reintroduc tions are
measuri ng trophic casc ades presum ed to be leading to e cological
restoration(Ripple&Beschta,2004).Thethirdapproach(i.e.,ungu-
lateexclusion)maystudytrophiccascadesfromeitherpointofview,
andthemethodsmaybepairedtoyieldstrongerinferences(Ford&
Goheen,2015).
3.3.1 | Predatorremoval
Predator removal experiments have been conducted to measure
the cascadingeffects inmany systems dominated by avian, lizard,
and ant predators (Schmitz et al., 2000). However, large preda-
tor removal expe riments are more di fficult to co ntrol at the sc ale
needed to stud y ungulate sys tems. The wi despread e xtirpat ion of
apexpredatorshasgivenrisetoseveralopportunities,albeitusually
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with poor replication, to study how ungulates af fect ecosyste ms
without p redation risks (Ritchie et al., 2012). In systems with out
predators,ungulatepopulationsmayincreasesubstantially,degrad-
ingtheplantcommunityasaresultofintenseunimpededherbivory
(Côté et al., 20 04). Seve ral exampl es exist to cor roborate th is no-
tion.Bergeretal.(2001)foundthatthelossofgrizzlybearsandgray
wolvesledtothedegradationofriparianareasviadensity-mediated
moose herbivory,which erodedthe bird community in the Greater
Yellowstone Ecosystem. Ripple and Beschta (2006a) repor ted a
density-mediatedtrophiccascadelinkingincreasedhumanpresence
tocougardeclines,increasedmuledeerdensity,decreasedcotton-
wood regen eration, incr eased soil erosi on, and decreas ed aquatic
and terrestrial diversit y in Yellowstone National Park. Likewise,
Wallach et al.(2010) reported that predator control of dingoes (C.
lupus dingo)resultedinpopulationincreasesininvasive herbivores
anddecreases inbiodiversity.Finally,inareview,Estesetal.(2011)
detailedmanytrophiccascadesthroughdifferenttrophiclevelsand
ecologicalprocessesresultingfromtheextinctionofapexpredators,
includingalterationsofdiseasedynamics,wildfireonthelandscape,
carbonsequestrationpatterns,invasivespeciesinvasionsandpreva-
lence,andbiogeochemicalcycles.
Interestingly,recent evidence has indicated that ungulate den-
sitiesmayexceednutritionalcarryingcapacityfor decadeswithout
nutritionalfeedbackonthepopulation(LeSaoutetal.,2014).That
sameresearchalsohighlightsthedisparitybetweenstablestatesof
ungulatepopu la ti on sw it ha ndwitho ut pr edatorsan dhowdr as tica l-
ternativestablestatesinungulatepopulationsmayaffectecosystem
process es. The ext ensive herbi vory pres sure may result i n natural
selectionfavoringplantspecieswithheightenedherbivorydefenses
(Strauss &Agrawal, 1999) or induce plant defenses within species
(Stotzetal.,2000).However,top-downcontrolslikelywilllimitver-
teb ratep opulationstoalowerdensitythanb ot tom-upcontr ols,c re-
atingthedisparityinstablestatesoftenobser vedbetweenpredator
andpredator-freeenvironment s(Terborghetal.,20 01).
3.3.2 | Predatoraddition
ThereintroductionofwolvestoYellowstoneNationalParkhaspro-
vided thestandard example of how fearaffects ungulates in ways
thatc ascadeto plant communities,dependentwildlifespecies,and
other ecological processe s (Beschta & Ripple, 2009; Estes et al.,
2011; Ripple & Be schta, 2006 b, 2012; Ritchie & John son, 2009).
Wecommonlythinkofthescenarioasrestoringecosystemfunction
because the predator rever ts ungulate populations and behavior
fromthealternativestablest atebacktothehistoricalstablestate.
These“naturalexperiments”providetheopportunitytoevaluatethe
resilien ce of an ecosyste m to the altern ative stabl e state bec ause
wecanobserve the recover yofecologicalprocesses.For example,
Ripple andBeschta(2003)monitored cottonwoodrecovery follow-
ing reintroduction of wolves and noted that riskier sites had taller
trees an d greater ann ual growth , and height w as signific antly cor-
related to gu lly depth, whic h is linked to escap ability or risk iness
of the area . Those areas we re most susce ptible to her bivory con-
sequences following the extirpation of wolvesbut also were more
resilient b ecause of a fas ter recovery ti me. The reintro duction of
pre dator smayprovisi ono there cosyste mser vicesthatarenotread-
ily anticipated. For example, wolves affect grazing by ungulates in
waysthatcascadestoalte re dmicr ob ialac tivityan dnutrient dy nam-
icsofgrasslands(Frank,2008).Rippleetal.(2014)reportedanother
examplewherewolfpresencemodulatedgrizzlybeardietindirectly
byaffecting fruit production through the regulationofelk density
andforagingbehavior.Eventhegeomorphologyofriversmaybeaf-
fectedbyherbivorydifferentlydependingonwhethertheungulates
areforagingundertheriskofpredation(Beschta&Ripple,2012).
3.3.3 | Ungulateexclusion
Ungulate h erbivory c an have ecosystem w ide and long-te rm con-
sequences. For example, Nuttle et al. (2011) demonstrated in a
long-termungulateexclusionexperimentthathighwhite-taileddeer
densityatstand initiation resulted in century-long changes in eco-
system func tion, includingsimplifiedforest structureandcomposi-
tion,decreasedcanopy foliage density,decreased insect diversity,
and decreased bird diversity. Similarly, Shelton etal. (2014) used
ungulate exc losures to show t hat white-t ailed deer ha d cascadi ng
effects onplantcommunities in allforageclasses, whichindirectly
affectedsmall wildlife species. Ford et al. (2015)reportedthat the
recover yofwilddogsfo llowingreintroductioninKe nyalimitedden-
sities of dik dik but did nottrigger a trophic cascade,possibly be-
causeofthediversityofbrowsersoratimelaginindirectef fects.
3.4 | Manipulation of predation risk
Recently,researchersandpractitionershavecometotherealization
thatmanagementstrategiescanpotentiallyusefearofpredationas
abasisformanagementdecisions(Cromsigtetal.,2013;Suracietal.,
2016).Indeed,humanshaveusedfeartodeterwildlifedamagesince
thedawnofagriculture.Forexample,theuseofascarecrowiscom-
monplaceandservesasavisualcuetowardoffdepredatingwildlife
incropfields.Likewise,farmershaverecommendedtheuseofhuman
hair asa scent cue to deter deerfrom gardens. These household
remediesfordepredationbyungulatesarerootedintheecologyof
fearconcept and provideclassicexamplesof howthelandscapeof
fearcanbemanipulatedasamanagementtool.Generally,theland-
scape offearcanbe managedbypassive(e.g.,predatorreintroduc-
tions)andactive(e.g.,hunting, predatorcues,habitatmanipulation)
means,withatop-downorbottom-upapproach.
3.4.1 | Top-downapproaches
Berger et al. (2001) suggested the potential for usinghuman hunt-
ing to invoke the t rophic casc ades provide d by wolves to restor e
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ecosystemfunction.Cromsigt etal.(2013)embraced thisidea with
th ec on cep to f“ hu nti ng forfe ar,”w he ret he yprop ose du sin gh untin g
asatop-downapproachtomanagingundesiredeffectsofungulates.
Otherpotentialmethodssuchastrainingdomesticatedpredatorsto
deterprey (Atkinsetal., 2017)are being usedincreasinglytomiti-
gate human-wildlifeconflic ts, butthese likelyare less practical for
ungulates.An importantconsiderationwhen designing and study-
ing thesemanagement approaches ishow the natural apex preda-
tor of the system affects ungulatebehaviorand how the resulting
behaviorscascadetoothertrophiclevels.Thetrophic cascadesare
oftencontextdependentbecausethesameungulatesmayusedif-
feringmethodstoavoiddifferentpredators,differentungulatesmay
use diff erent strate gies to avoid the sam e predator, and dif ferent
environm ental contex t may make the sam e ungulate use di ffering
methodstoavoidthesamepredator(seeprevioussectionontrophic
cascades).Moreover,strategies of usinghumans to reestablish the
landscapeoffearmayonlyworkafteralagtimefortheungulateto
establishthatthepredatorisindeedathreat(LeSaoutetal.,2014).
Additionally,theymayhavelimitedeffectiveness(ornotworkatall)
if anthrop ogenic stim uli cause mis matched perce ption and be hav-
ioralresponsesinthe targetedanimals(Smith etal.,2021).Itisthis
contextdependencythatmaymakeusingatop-downapproachdif-
ficulttoapply,particularlyasecologicalobjectivesbecomenarrower.
3.4.2 | Bottom-upapproaches
Fewstudieshavedirectlymeasuredthepotentialtoapplyabottom-
upapproachofmanagingungulateswithfear.However,severalex-
amples existfrom othertaxa. For example, Fernández-Juricic et al.
(2001) sug gested that u nderst anding anim al response s to humans
couldaidinthedesignofparkstodecreasestress-relatedfearfrom
human ac tivity. Alte rnatively, that s ame concept co uld be used to
cause an imals to behavioral ly avoid sensitive are as. For example,
Blackwell et al.(2013) proposed a frameworkto reduceavian col-
lisions withaircrafts by utilizing concepts in the ecology of fearto
guide habitat management surrounding landing strips on airports.
Clearly,vegetationstructureandcompositionandthedistributionof
coverandfoodsalsoaffectungulatebehavioratleastinpartbecause
thosefactorsaf fectpredationrisk.Becauselandmanagementprac-
tices ca n drastical ly alter the land scape chara cteristic s associated
with veget ation, using mana gement practi ces to augment troph ic
cascadesforpurposesofrestorationmaybepossible.Insupportof
thisnotion,Hebblewhiteetal.(2009)reportedthat loggingincom-
bination with fire increasedthe amountof forage biomass, but elk
avoidedtheseareasbecauseofincreasedpredationriskfromwolves
intheCa nadianRock ies .Th us,thedramaticchangeinplantcommu-
nitystructurealteredtheungulateperceptionofthearea'sriskiness,
whichcausedthemtoshif tbehaviortoavoidthoseareas.Similarly,
RiginosandGrace(2008)reportedthatvisualobstructionfromtree
densityincreasesfearinsomeungulates,whichcascadestotheforb
communit y in open are as. Contras tingly, Lashl ey,Chi twood, Kay s,
et al. (2015) demonstrated that white-tailed deer avoided areas
withpoorvisualobstruction,eventhoughthoseareasoftenhadthe
greatestavailablenutrition(Lashley,Chitwood,Harper,etal.,2015).
Inallofthose cases, perception of predation risk drovetheanimal
decisionsdespite foragepatchquality,but theantipredatorbehav-
iors of the u ngulate dict ated what lands cape chara cteristic s were
actuallyavoided.Landscape structure may drive theperception of
risk,meaningthatmanipulatinglandscape structuretodrivea de-
sirable trophic cascade could be possible, thoughmanylife-histor y
factorsoftheungulateinvolvedmayconfounddesirableoutcomes.
4 | CONCLUSIONS
Understanding ungulate ecology of fear and its system-wide ef-
fectswouldhelpustobetterinterpretungulateecology,improve
wildlifeconservationandmanagementprograms,andunderstand
communit y dynamics (Teckentrupet al., 2018). Ourreview dem-
onstratedthatmost studiesoftheecologyoffear canbelumped
into three c ategories of in quiry: be havioral resp onses to pred a-
tion risk , physiological re sponses to preda tion risk, and tro phic
cascades resulting from ungulate responses to predation risk.
A fourt h categor y,man ipulation of p redation ri sk, has bee n less
studiedbutnonethelessrepresentsaninterestingopportunityto
takeresearchresultsandincorporatethemintoconservationand
managementplanning(e.g.,Gaynor etal.,2021).Importantly,our
review suggeststhat collaboration across researchfoci (e.g., be-
havioral effectsonphysiologyandhowtheyscaleto population-
levelconsequences) presents an opportunity to design complex
research questions that have otherwise, more often than not,
beentreateddisparately.
OurreviewalsoconfirmsrecentworkbySay-Sallazetal.(2019),
who reported a biasinthe taxabeing studied andthe locations in
theworldinwhichtheyarestudied.Suchbiaspresentsaproblemon
multiplefronts.First,itappears thatcharismatictaxa and locations
or events (e. g., wolf reintrod uction to Yellowston e National Park )
dominatetheliterature,meaningotherpredator–preyrelationships
andsystemsarenotcontributingproportionallytoourscientificun-
derstandingoftheecolog yoffear.Second,manystudiesarelimited
intaxonomicscope,evenwhenmultiplepredatorandungulatespe-
ciesare availableatagivenstudy site,which ignoresthe complex-
ity associated withmany predator–prey systems(Moll et al.,2017;
Montgomery et al.,2019)andlikely limit sinference. Third,studies
on movement a nd habitat sel ection domi nated the topic s studied
under the ecologyof fearparadigm, but we do notbelieve habitat
selectionalonewillbeenoughtomechanisticallyexplainecologyof
fear.Manyradiotag-basedstudiesareobservationaloropportunistic
innature.Rigorousexperimentalandreplicatedstudiesarerequired
formechanisticunderstandingofhowfearscalestopopulation-level
processes(seePeersetal.,2018;Prughetal.,2019).
Ungulate responses to predationriskdependonenvironmental
features, life-histor y traits, and social structure (Ford & Goheen,
2015).However,themajorityof research into “ecologyof fear”fo-
cusesonelk.Additionalresearchonless-studiedungulates,coupled
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CHITWOOD eT al .
withpredatorswith differenthunting techniques,willbeimportant
to under standing th e effect s of fear on ungula tes. We know that
thetwotypesofpredationrisk,individuallyorcombined,mayhave
differenteffectsonungulateresponses(Creeletal.,2014,Wikenros
et al., 2015, but see Dröge et al., 2017). However, the majorit y of
researchfocusesoncursorialpredators,andlittleresearchevaluates
theeffectsofambushpredatorsortheeffectsofcursorialandam-
bushcombined.Moreover,interindividualvariationintraitssuchas
boldnessorshynessmightplayanimportantroleaffectingungulate
perceptionrisk(Bleicher,2017),buttheyarelargelyunstudiedinthe
ecologyoffearcontext.
Therelationshipofdiseaseandparasitismtotheecologyoffear
could haveimport antecological, economic, or human health con-
sequences, but the relationships between infection risk and fear
respons es are still la rgely unexpl ored (only 5 pape rs [<2%] in our
reviewwereexplicitlyconnectedtodiseaseorparasitism).Predators
may limit disease spread by reducing host densities or selecting
infected individuals (Packer et al., 2003), but they could simulta-
neouslyincreasetransmissionriskatlowerungulatedensitiesifun-
gulatesincreasegroupsizeinresponsetopredationrisk.Also,given
thathost–parasiteinteractionspotentiallyinfluencetheprevalence
ofvector-bornediseases,incorporatingindirecteffectsofparasites
onungulate hosts couldhaveimplications on mitigation of disease
risk (Al lan et al., 2010). Unders tanding how non- consumptive ef-
fectsof parasitismaffec thostpopulationdynamicsandpotentially
cascadethroughfoodwebsisimportant(Daversaetal.,2021).With
numerous zoonotic pathogens transmitted via parasites, how they
contributetotheecologyoffearcouldhaveimplicationsforhuman
healthandeconomies.
Duetothelackofreplicationanddifficultyofisolatingtrait-
mediated f rom density-me diated factors , there is contrast ing
evidence regarding trait-mediated trophic cascade effects on
communities, ungulate populations, and ungulate physiology.
Moreover, recent work highlighted concerns with sampling
design th at affected t he strengt h of a trophic cas cade in the
Greater YellowstoneEcosystem(Briceetal.,2022).Studies on
trait-mediated trophic cascades in particular suffer from the
taxonomic and regional biases mentioned previously because
they tendto be focused on cursorial predators in the Greater
Yellowstone Ecosystem, likely due to the natural experiment
provided by the reintroduction of wolves (Bleicher, 2017).
Meanwhil e, we know very litt le about trophic c ascades gen-
erated by am bush predators (M oll et al., 2016; Thaker et a l.,
2011;Wikenros et al.,2015). Overcoming such biasshould be
fundamental to increasing ourknowledgeoftrophicc ascades.
Iftheecologyoffearhas broad importance in causingtrophic
cascades, avoidingbiasshould be fundamentalto thestudy of
its effects as well asits application to conservation andman-
agement.Giventhat allofthestrategies wecurrentlyembrace
tomanipulatefearforconser vationpurposesarerootedinelic-
itingdes ir ablet ro ph iccas ca des ,t hi sm aybe th em ostimpo r tant
fo c ala reaf orf utur ere s ear c hif we a ret ou s eth eeco log y off ear
successfullyinconservation.
If the ecology of fear is a valuable ecological paradigm, we
must look beyond wolves and elk in North America and toward
studies that embr ace complexity i n research design (as noted by
Montgom ery et al., 2019, Prugh et al. , 2019, a nd Say-Salla z et al.,
2019). Though resu lts of studies h ighlighted here in often provide
conflictingdirectionalit yormagnitude ofef fect,theyprovidevalu-
ablebuildingblocksforimprovingfuturestudiesofecologyoffearin
ungulates.Thethreepredominateareasofresearchfocusweiden-
tified overlapwithoneanotherextensively; recognizingtheyoccur
inanincreasingly anthropogenicworld (Bergeretal., 2020) willbe
importanttoconsider.Someauthorshavearguedthatgiventheper-
vasiveeffectsofhumansonear th,quantifyinghumandisturbanceis
ahighpriorit yfor conservationandthat understanding the fitness
costs ofhumanactivities (e.g., hiking,hunting)is animportant area
forfutureresearchdespitethechallengeforfieldstudies(Ciutietal.,
2012,butseeSchuttleretal.,2017).Onlybyembr aci ng“m ess ypro-
jectio ns” (Berger et al ., 2020) will we be a ble to predic t how fear
might aff ect popula tion dynami cs and ecolo gical proce sses across
systems, accounting for multiple predators of varying sizes and
hunting m odes, with nu merous prey opt ions. We believe the c ur-
rentbodyofliteratureonecologyoffearcomesupshortonbroadly
explaining predator–prey dynamics in complex systems. However,
thesheernumberofpapersonthetopicdemonstrateclearinterest
amongecologists,makingfutureworkonecologyoffearthatmuch
more valuable ifit embraces complexity and expands beyond the
few species and systems that have driven the development of the
conceptthusfar.Theareasofresearchfocusidentifiedinthisreview
compriseafoundationforfutureresearch tolinkbehavior,physiol-
ogy,trophic cascades, and management alltogether as one,rather
thanthinkingofeachinavacuum.
ACKNOWLEDGEMENT
We thank the A ssociate Edit or and two ano nymous review ers for
thought fulcommentsthatimprovedthemanuscript.
CONFLICT OF INTEREST
Authorsdeclarenoconflictofinterest.
AUTHOR CONTRIBUTIONS
M. Colter Chitwood: Conceptualization (equal); Investigation
(equal);Methodolog y(equal);Writing–originaldraft(lead).Carolina
Baruzzi: Data curation (lead); Investigation (equal); Methodology
(equal); Visualization (lead); Writing – original draft (supporting).
Marcus A. Lashley:Conceptualization(equal);Investigation(equal);
Methodology(equal);Writing–originaldraft(supporting).
DATA AVAIL AB ILI T Y STAT E MEN T
DataareprovidedaspartofthemanuscriptandAppendixS1.
ORCID
M. Colter Chitwood https://orcid.org/0000-0001-7240-7430
Carolina Baruzzi https://orcid.org/0000-0003-1796-9355
Marcus A. Lashley https://orcid.org/0000-0002-1086-7754
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CHITWO OD eT al .
REFERENCES
Allan,B.F.,Varns,T.S.,&Chase,J.M.(2010).Fearofparasites:lonestar
ticksincreasegiving-updensitiesinwhite-taileddeer.Israel Journal
of Ecology & Evolution, 56, 313–324. https://doi.org/10.1560/
IJEE.56.3-4.313
Alston,J. M.,Maitland,B.M.,Brito,B.T.,Esmaeili,S.,Ford,A .T.,Hays,
B.,Jesmer,B.R.,Molina,F.J.,&Goheen ,J.R.(2019).Reciprocityin
restorationecology:whenmightlargecarnivorereintroductionre-
store ecosystems? Biological Conservation,234,82–89.https://doi.
org/10.1016/j.biocon.2019.03.021
Altend orf, K. B. , Laundr é, J. W., López G onzález , C. A., & B rown, J. S.
(2001).Assessingeffectsof predationriskonforagingbehaviorof
muledeer.Journal of Mammalogy,82,430–439.
Atkins,A .,Redpath,S.M.,Little,R.M.,&Amar,A.(2017).Experimentally
manipul ating the landsc ape of fear to manage p roblem animals .
The Journal of Wildlife Management, 81, 610–616. ht tp s: //doi .
org/10.1002/jwmg.21227
Bacon, M. M.,& Boyce,M.S.(2016).Landscape of fear fornaïve prey:
Ungulate s flee protected area to avoid a re-established predator.
Canadian Wildlife Biology Management,5,1–9.
Barnier,F.,Duncan,P.,Fritz,H.,Blanchard,P.,Rubenstein,D. I., &Pays,
O.(2016).Between-genderdifferences invigilancedo notneces-
sarilyleadtodifferencesinforaging-vigilancetradeoffs.Oecologia,
181, 7 5 7 –7 6 8 . h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 0 0 4 4 2 - 0 1 6 - 3 6 1 4 - 5
Barnier, F., Valeix, M., Dunc an, P., Chamaillé-Jammes, S., Barre, P.,
Loveridge,A .J.,Macdonald,D.W., &Fritz, H. (2014).Dietqualit y
inawild grazerdeclinesunder thethreat of anambush predator.
Proceedi ngs of the Royal Society of London B: B iologic al Sciences,281,
20140446.https://doi.org/10.1098/rspb.2014.0446
Barton, B. T. (2010). Climate warming and pre dation risk during
herbivore ontogeny. Ecology, 91, 2811–2818. ht tps://doi.
org /10.189 0/09-2278.1
Basille,M.,Fortin,D.,Dussault, C., Bastille-Rousseau,G., Ouellet, J. P.,
&Courtois, R. (2015).Plastic response of fearfulprey tothe spa-
tiotemporal dynamics of predatordistribution.Ecology, 96,2622–
2631 .https://doi.o rg /10.18 90/14-170 6.1
Beauch amp, G. (2019). On how risk an dgroup size interac t to influ-
ence vigilance. Biological Reviews, 94, 1918–1934. ht tps://doi.
org /10.1111/b rv.125 40
Beckerman,A .P.,Uriarte, M.,&Schmitz, O.J.(1997).Experimentalevi-
denceforabehavior-mediatedtrophiccasc adeinaterrestrialfood
chain.Proceedings of the National Academy of Sciences,94,10735–
10738.ht tps://doi.o rg/10.1073/pnas.94.20.10735
Benoist,S., Garel,M .,Cugnasse,J.M.,& Blanchard,P.(2013).Human
disturbances, habitat characteristics and social environment
generate sex-specific responses in vigilance of Mediterranean
mouflon. PLoS One, 8, e82960. https://doi.org/10.1371/journ
al.pone.0082960
Berger,J.(2007).Fear,humanshieldsandtheredistributionofpreyand
predators in protec ted areas. Biology Letters,3,620–623. ht tps://
doi.org/10.1098/rsbl.2007.0415
Berger,J.,Stacey,P.B.,Bellis,L .,& Johnson,M .P.(2001).Amammalian
predato r–prey i mbalance: gri zzly bear and wo lf extinc tion affect
avianneotropicalmigrants.Ecological Applications,11,947–960.
Berger, J., Wangc huk, T., Briceñ o, C., Vil a, A., & L ambert , J. E. (2020) .
Disassembled food websandmessy projec tions:modernungulate
communi ties in the f ace of unabatin g human popu lation grow th.
Frontiers in Ecology and Evolution, 8, 128. ht tps://doi.org/10.3389/
fevo.2020.00128
Berg vall, U. A., Sven sson, L., & Kj ellander, P. (2016). Vigilance ad just-
ments in r elation to lon g-and sh ort term ris k in wild fallow d eer
(Dama dama). Behavioural Processes, 128, 58–63. ht tps://doi.
org/10.1016/j.beproc.2016.04.005
Beschta, R. L.,&Ripple, W. J. (2009).Large predatorsandtrophiccas-
cades in terrestrial ecosystems of the western United States.
Biological Conservation,142,2401–2414.https://doi.org/10.1016/j.
biocon.2009.06.015
Beschta,R .L.,&R ipple,W.J.(2010).Mexican wolves ,elk ,and aspenin
Arizona:isthereatrophiccascade?Forest Ecology and Management,
260,915–922.https://doi.org/10.1016/j.foreco. 2010.06.012
Bescht a, R. L., & Rip ple, W. J. (2012). The role of la rge predators in
maintaining riparian plant communities and river morphology.
Geomorphology, 157, 88–98. ht tps://doi.org/10.1016/j.geomo
rph.2011.04.042
Biggerstaf f, M. T., Lashley, M. A ., Chitwood, M . C., Moorman, C . E.,
& DePerno, C. S. (2017). Sexual segregation of forage patch
use: support for the social-factors and predation hypotheses.
Behavioural Processes, 136, 36–42. https://doi.org/10.1016/j.
beproc.2017.01.003
Blackwell,B.F.,Seamans,T.W.,Schmidt,P.M.,Vault,T.L.,Belant,J.L.,
Whitt ingham, M. J. , Martin, J . A., & Ferná ndez-Jurici c, E. (2013).
A framework for managing airport grasslands and birds amidst
conflictingpriorities. Ibis, 155, 199–20 3. ht tps ://doi.o rg/10 .1111/
ibi.12011
Blanchard,P.,Pays,O.,&Fritz,H.(2017).Ticksorlions:tradingbetween
allogroomingandvigilanceinmaternalcare.Animal Behaviour,129,
269–279.https://doi.org/10.1016/j.anbehav.2017.05.005
Bleicher, S. S. (2017). The landsc ape of fear conceptual framework :
definitionandreviewofcurrentapplic ations andmisuses.Pe erJ ,5,
e3772.https://doi.org/10.7717/peerj.3772
Boonstra,R.(2013).Realityastheleadingcauseofstr ess:rethinki ngthe
impac t of chronic str ess in nature. Functional Ecology, 27,11–23.
https ://doi.or g/10.1111/1365 - 2435.12 00 8
Brice,E.M.,Larsen, E.J.,&MacNulty,D.R. (2022).Samplingbiasexag-
gerates atextbook example of a trophic cascade. Ecology Letters,
25,177–188.ht tps://doi.org/10.1111/ele.13915
Brown, J. S. (1999).Vigilance,patch use and habitat selection: for aging
underpredationrisk.Evolutionar y Ecology Research,1,49–71.
Brown, J. S.,Laundré, J. W.,&Gurung,M. (1999).Theecolog yoffear:
optimalforaging,gametheory,andtrophicinteractions.Journal of
Mammalogy,80,385–399.https://doi.org/10.2307/1383287
Carma ssi, C., Ber telloni, C. A ., Massimet ti, G., Miniat i, M., Stratt a, P.,
Rossi, A ., & Dell, L. (2015 ). Impact of DSM-5 PTSD a nd gender
on impaired eating behaviors in 512 Italian earthquake survivors.
Psychiatry Research, 225, 64–69. https://doi.org/10.1016/j.psych
res.2014.10.008
Chamail lé-Jamme s, S., Malcu it, H., Le S aout, S., & M artin , J. L. (2014).
Innate threat-sensitive foraging: black-tailed deer remain more
fearf ul of wolf than of t he less danger ous black bea r even after
100yearsofwolfabsence.Oecologia,174 ,1151–1158 . ht tp s://doi.
org /10.10 07/s00 44 2- 013- 2843- 0
Cherr y,M. J., Morgan, K. E., Rutle dge, B. T.,Conner, L. M., & Warren,
R. J. (2016). Ca n coyote predati on risk induc e reproduc tion sup-
pression in white-tailed deer? Ecosphere, 7, e01481. https://doi.
org /10.10 02/ecs2 .1481
Cherr y,M . J., Warren, R. J.,& Conner,L. M. (2016). Fear,fire, and be-
haviora lly mediated tro phic cascad es in a frequent ly burned sa-
vanna.Forest Ecology and Management,368, 133–139.ht tps://doi.
org/10.1016/j.foreco.2016.03.011
Chitwood,M.C.,Lashley,M.A.,Kilgo,J.C.,Moorman,C.E.,&DePerno,
C. S. (2015). White-tailed deer p opulation dynamics and adult
female su rvival in th e presence of a novel p redator. The Journal
of Wildlife Management, 79, 211–219. ht t p s: //d oi. o rg/ 10 .1 0 02/
jwmg.835
Chitwood,M.C.,L ashley,M.A.,Kilgo,J.C.,Pollock,K.H.,Moorman,C.
E.,& DePerno, C.S.(2015).Dobiologicalandbedsitecharacteris-
ticsinfluencesurvivalofneonatalwhite-taileddeer?PLoS One,10,
e0119070.https://doi.org/10.1371/journal.pone.0119070
Chit wo od ,M .C . ,L as hl ey, M.A .,Mo or ma n,C .E ., &DeP er no ,C .S .( 20 14) .
Confirmationofcoyotepredationonadultfemalewhite-t aileddeer
12 of 15
|
CHITWOOD eT al .
in the southeastern United States. Southeastern Naturalist, 13,
N30–N32.https://doi.org/10.1656/058.013.0316
Chitwood,M.C.,Lashley,M.A.,Moorman,C.E.,&DePerno,C.S.(2017).
Settinganevolutionarytrap:couldthehiderstrategyb emaladap-
tiveforwhite-taileddeer?Journal of Ethology,35,251–257.https://
d o i . o r g / 1 0 . 1 0 0 7 / s 1 0 1 6 4 - 0 1 7 - 0 5 1 4 - z
Christianson, D., & Creel, S. (2010). A nutritionally me diated risk ef-
fect of wolves on elk. Ecology, 91, 1184 –1191 . ht tps: //doi.
org /10.189 0/09- 0221.1
Ciuti, S., Nor thrup, J. M., Muhly, T. B., Simi, S., Musiani, M., Pitt, J. A.,
&Boyce,M .S .(2012).Effects ofhumans on behaviour ofwildlife
exceedthoseofnaturalpredatorsinalandscapeoffear.PLoS One,
7,e50611.https://doi.org/10.1371/journal.pone.0050611
Clinchy,M.,Sherif f,M.J.,&Zanette,L.Y.(2013).Predator-inducedstress
andtheecolog yoffear.Functional Ecology,27,56–65.ht tps://doi.
org /10.1111/1365- 24 35.120 07
Côté, S. D.,Rooney, T.P.,Tremblay, J. P.,Dussault, C ., & Waller,D. M.
(2004).Ecological impacts of deer overabundance. Annual Review
of Ecology, Evolution, and Sys tematics, 35, 113–147. https://doi.
org/10.1146/annurev.ecolsys.35.021103.105725
Crawford,D.A.,Conner,L.M.,Clinchy,M.,Zanette,L.Y.,&Cherry,M.J.
(2022).Preytells,largeherbivoresfearthehuman‘superpredator’.
Oecologia, 198( 1 ) , 9 1 – 9 8 . h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 0 0 4 4 2 - 0 2 1 -
05080 - w
Creel,S .(2018).T hecontr olofriskhypothesis :react ivev s.proacti vean-
tipredatorresponsesandstress-mediatedvs.food-mediatedcosts
ofresponse.Ecology Letters,21, 947–956. ht tps: //doi.org/10 .1111/
ele.12975
Creel,S.,&Christianson,D.(2009).Wolfpresenceandincreasedwillow
consumptionbyYellowstoneelk:implicationsfortrophiccascades.
Ecology,90,2454–2466 .https://doi.org/10.1890/08-2017.1
Creel, S.,Christianson,D. A ., &Winnie,J. A .Jr(2011).A survey of the
effec ts ofwolfpredationriskonpregnancyrates and calf recruit-
ment in elk . Ecological Applications, 21, 2847–2853. https://doi.
org /10.1890/11- 0768.1
Creel, S ., Schuett e, P., & Christ ianson, D. (2014). Effe cts of pred ation
risk on gro up size, vigila nce, and for aging behavi or in an Afric an
ungulatecommunity.Behavioral Ecology,25, 773–784.https://doi.
org/10.1093/beheco/aru050
Creel, S., Winnie, J.A., &Christianson,D. (2009).G lucocorticoidstress
hormon es and the effe ct of predation ri sk on elk reproduc tion.
Proceedi ngs of the National Ac ademy of Sciences,106 ,12388–12393.
https://doi.org/10.1073/pnas.0902235106
Creel, S.,Winnie,J.A. Jr,Christianson, D., &Liley, S. (2008). Timeand
space in general mo dels of antipredator response: tes ts with
wolves and elk. Animal Behaviour, 76, 1139–1146. ht tp s://doi .
org/10.1016/j.anbehav.2008.07.006
Cromsig t, J. P., Kuijper, D. P., Adam, M., Beschta, R. L ., Churski, M.,
Eycott, A ., Kerley, G. I., Mysterud, A ., Schmidt, K., & West, K .
(2013). Hunting for fear: innovating management of human–
wildlifeconflicts.Journal of Applied Ecology,50, 544–549.https://
doi .org/10.1111/1365 - 266 4.12076
Daversa,D.R.,Hechinger,R.F.,Madin,E.,Fenton,A.,D ell,A .I.,Ritchie,
E.G.,Rohr,J.,Rudolf,V.H.W.,&Laffer ty,K.D.(2021).Broadening
theecolog yoffear:non-lethaleffectsarisefromdiverseresponses
topredationandparasitism.Proceedings of the Royal Society B,288,
20202966.https://doi.org/10.1098/rspb.2020.2966
DeLong, J. P., Gilbert , B., Shurin, J. B., Savage, V. M., Barton, B. T.,
Clements,C.F.,Dell, A. I., Greig,H.S.,Harley,C. D.,Kratina,P.,&
McCan n, K. S. (2 015). The bod y size depend ence of trop hic cas-
cades.The American Naturalist,185,354–366.
Dröge,E.,Creel,S.,Becker,M.S.,&M ’soka,J.(2017).R iskytimesandrisky
placesinteracttoaffectpreybehaviour.Nature Ecology & Evolution,
1, 1 1 2 3 – 1 1 2 8 . h t t p s : / / d o i . o r g / 1 0 . 1 0 3 8 / s 4 1 5 5 9 - 0 1 7 - 0 2 2 0 - 9
Dudeck ,B.P.,Clinchy,M.,Allen,M.C.,&Zanette,L.Y.(2018).Fearaffects
parentalcare,whichpredic tsjuvenilesurvivalandexacerbatesthe
totalcostoffearondemography.Ecology,99,127–135.https://doi.
org /10.1002/ec y.2050
Eby,S .L .,A nd ers on,T.M ., Ma ye mba ,E .P.,&R i tc hi e,M .E .( 20 14) .T heef-
fectoffireonhabitatselec tionofmammalianherbivores:theroleof
bodysizeand vegetationcharacteristics.Journal of Animal Ecology,
83,1196–1205.https://doi.org/10.1111/1365-2656.12221
Estes,J. A., Terborgh,J.,Brashares,J. S., Power,M.E.,Berger,J., Bond,
W.J.,Carpenter,S.R.,Essing ton,T.E.,Holt,R.D.,Jackson,J.B.C.,
Marquis,R.J., Oksanen, L., Oksanen, T.,Paine,R .T.,Pikitch, E.K.,
Ripple,W.J.,Sandin,S.A.,Scheffer,M.,Schoener,T.W.,…Wardle,
D. A. (2011). Trophic do wngrading of p lanet Ear th. Science, 333,
301–306.https://doi.org/10.1126/science.1205106
Fattorin i, N., Lovar i, S., Brun etti, C ., Baruzzi , C., Cot za, A., Ma cchi, E.,
Pagliar ella, M. C ., & Ferret ti, F.( 2018). Age, se asonalit y,a nd cor-
relates of aggression in female Apennine chamois. Behavioral
Ecology and Sociobiology, 72, 171. https://doi.org /10.1007/s0026
5- 01 8- 2 58 4 - 5
Fernández-Juricic, E., Jimenez,M.D.,& Lucas,E.(2001). Alert distance
asan alternative measureofbirdtolerance tohuman disturbance:
implicationsforparkdesign.Environmental Conservation,28,263–
269.htt ps://doi.or g/10.1017/S037689 29010 0 0273
Flagel, D.G., Belovsky,G .E.,&Beyer,D.E.(2016).Natural and experi-
mentaltes tsoftrophiccascades:graywolvesandwhite-t aileddeer
in a Great L akes forest. Oecologia, 180, 118 3–1194. htt ps://doi.
o r g / 1 0 . 1 0 0 7 / s 0 0 4 4 2 - 0 1 5 - 3 5 1 5 - z
Ford, A . T.,& G oheen, J. R . (2015). Trophic ca scades by l arge carn i-
vores: a case for strong inference and mechanism. Tren ds in
Ecology & Evolution, 30, 725–735. https://doi.org/10.1016/j.
tree.2015.09.012
Ford,A .T.,Goheen,J.R.,Augus tine,D.J.,Kinnaird,M .F.,O'Brien,T.G.,
Palmer,T.M., Pringle, R. M., &Woodroffe,R.(2015). Recover yof
Af r i c a n w i l ddo g s s u p p r e ssesp r e y b u td o e s n o ttrig ge r a t rophi c c a s -
cade.Ecology,96,2705–2714.https://doi.org/10.1890/14-2056.1
Fortin,D.,Beyer,H.L.,Boyce,M.S.,Smith,D.W.,Duchesne,T.,&Mao,
J. S. (20 05). Wolves infl uence elk mo vements: b ehavior sh apes a
trophiccascade in Yellows tone National Park. Ecology, 86, 1320–
1330.https://doi.org/10.1890/04-0953
Fortin, D., & Fortin, M. E. (2009). Group-size-dependent association
between food profitability, predation risk and distribution of
free-ranging bison. Animal Behaviour, 78, 887–892. ht tps://doi.
org/10.1016/j.anbehav.2009.06.026
Frank, D. A . (2008). Evidence for top predator control of a
grazing ecosystem. Oikos, 117, 1718–1724. https://doi.
org /10.1111/j .1600 -0706.20 08 .1684 6. x
Gallagher,A.J. ,C re el ,S .,Wilson ,R .P.,&Co ok e,S.J.(2017).En er g yland-
scapesand the landscape offear.Trends in Ecology & Evolution,32,
88–96.htt ps: //doi.or g/10.1016/j.tre e. 2016 .10.010
Gaynor, K. M ., Cherry, M. J., G ilbert, S . L., Kohl, M. T., La rson, C. L .,
Newsome,T.M.,Prugh,L.R.,Suraci,J. P.,Young,J.K.,&Smith,J.
A.(2021).Anappliedecologyoffearframework:linking theoryto
conservationpractice. Animal Conservation, 24, 3 08–321. https://
doi .org/10.1111/acv.1262 9
Gehr, B., Hofer,E. J., Pewsner, M., R yser, A., Vimercati,E., Vogt , K., &
Keller,L .F.(2018).Hunting-mediatedpredatorfacilitation and su-
peradditivemor talityinaEuropeanungulate.Ecolog y and Evolution,
8,109–119.https://doi.org/10.1002/ece3.3642
Gehr, B., Hofe r,E . J., Ryser, A., Vi mercati, E. , Vogt, K., & Kelle r, L. F.
(2018).Evidencefornonconsumptiveeffectsfromalargepredator
in an ungul ate prey? Behavioral Ecology, 29,724–735. ht tps://doi.
org/10.1093/beheco/ary031
Hamel,S.,&Côté,S.D.(2007).Habit atusepatternsinrelationtoescape
terrain:arealpineungulatefemalestradingoffbetterforagingsites
for safet y?Canadian Journal of Zoology,85, 933–943. ht tps://doi.
org/10.1139/Z07-080
Hawlena,D.,& Schmitz,O. J.(2010a). Herbivorephysiologicalresponse
topredationriskandimplicationsforecosystemnutrientdynamics.
|
13 of 15
CHITWO OD eT al .
Proceedi ngs of the National Academy of Sciences,107,15503–15507.
htt ps://doi.org/10.1073/pna s.10 093 00107
Hawlena , D., & Schmitz , O. J. (2010b). Physiolo gical stre ss as a fun-
damental mechanism linking predation to ecosystem func-
tioning. The American Naturalist, 176 , 537–556. https://doi.
org /10.1086/656495
Hawlena,D., Strickland,M.S .,Bradford, M.A., & Schmitz, O.J.(2012).
Fear of predationslows plant-litter decomposition. Science, 336,
1434–1438.https://doi.org/10.1126/science.1220097
Hebble white, M., Munro, R . H., & Merrill, E. H. (20 09). Trophic con -
sequences of postfire logging in a wolf–ungulate system.
Forest Ecology and Management, 257, 10 53–10 62. htt ps: //doi.
org /10.1016/ j.fore co. 20 08 .11.0 09
Hernández,L.,&Laundré,J.W.(2005).Foraginginthe‘landscapeoffear’
and its i mplicat ions for hab itat use an d diet qual ity of elk Cervus
elaphusandbisonBison bison. Wildlife Biology,11,215–220.
Hody,J.W.,&Kays,R.(2018).Mappingtheexpansionofcoyotes(Canis
latrans)acrossNort handCentralAmerica.ZooKeys,759,81 . ht t p s ://
doi.org/10. 3897/zookeys .759.15149
Hunter,M. D.,&Price,P.W.(1992).Playingchutesandladders: hetero-
geneityandtherelativerolesofbottom-upandtop-downforcesin
naturalcommunities.Ecology,73,724–732.
Illius, A. W., & Fit zgibbon, C. (1994).Costs ofvigilance in foraging un-
gulates. Animal Behaviour, 47, 481–4 84. https://doi.or g/10.100 6/
anbe.1994.1067
Iranzo, E . C., Wittmer,H . U., Traba, J., Acebes, P.,Mata, C ., & Malo, J.
E.(2018).Predatoroccurrenceandperceivedpredationriskdeter-
minegroupingbehavioringuanaco(Lama guanicoe).Ethology,124 ,
281–289.ht tps: //doi.org/10.1111/et h.1 2727
Iribarren,C.,&Kotler,B.P.(2012).Foragingpatternsofhabitatusereveal
landscapeoffearofNubianibexCapra nubiana. Wildlife Biology,18,
194–201.https://doi.org/10.2981/11-041
Jones,B.M.,C ove,M.V.,Lashley,M.A .,&Jackson ,V.L.(2016).Docoy-
otes Canis latransinfluenceoccupancy of prey in suburbanforest
fragments? Current Zoology, 62, 1–6 . ht tps ://doi .o rg/10.10 93 /cz/
zov00 4
Kauf fman, M. J., B rodie, J. F., & Jules , E. S. (2010). Are w olves saving
Yellowstone's aspen? A landscape-level test of a b ehaviorally
mediated trophic casca de. Ecology, 91, 2742–2755. htt p s: //do i.
org /10.189 0/09-1949.1
Kilgo, J. C ., Ray, H. S., Vukovich , M., Good e, M. J., & Ruth, C . (2012).
Predation by coyotes on white-tailed deer neonates in South
Carolina. The Journal of Wildlife Management, 76, 1420–1430.
https://doi.org/10.1002/jwmg.393
Klingaman, E. A ., Hoerster,K. D., Aakre, J.M., Viverito, K. M.,Medoff,
D.R.,&Goldberg, R. W.(2016).Veterans with PTSDreportmore
weight los s barriers tha n Ve terans with no me ntal health dis or-
ders. General Hospital Psychiatry,39,1–7.https://doi.org/10.1016/j.
genhosppsych.2015.11.003
Kuijper, D. P. J., de Kleine , C., Chur ski, M., van H ooft, P., Bubnic ki, J.,
& Jędr zejewska, B. (2013). L andscape of fe ar in Europe: wolve s
affect spatial patterns of ungulate browsing in Białowieża
Primeval Forest , Poland. Ecography, 36, 1263–1275. https://doi.
org /10.1111/j .1600 -0587.2013.00266 .x
Kuijper, D. P.J., Verwijmeren, M., Churski, M., Zbyry t, A ., Schmidt, K .,
Jędr zejewska, B ., & Smit, C . (2014). What cues d o ungulates u se
to assesspredation risk in dense temperate fores ts? PLoS One, 9,
e84607.https://doi.org/10.1371/journal.pone.0084607
Lashley, M. A., Chitwood, M. C., Biggerstaf f, M. T., Morina, D. L.,
Moorma n, C. E., & D ePerno, C . S. (2014). White -tail ed deer vig i-
lance:theinfluenceofsocialandenvironmentalfactors.PLoS One,
9,e90652.https://doi.org/10.1371/journal.pone.0090652
Lashley, M. A., Chitwood, M. C., Harper, C. A., DePerno, C . S., &
Moorman,C .E.(2015).Variabilityin fire prescriptionstopromote
wildlifefoodsinthe longleaf pine ecosystem. Fire Ecology,11 ,62–
79.https://doi.org/10.4996/fireecology.1103062
Lashley,M.A., Chitwood, M.C., Kays, R., Harper,C.A.,DePerno, C. S.,
& Moorma n, C. E. (2015). Prescribed fire affects female white-
tailed deer habitat use during summer lac tation. Fores t Ecology
and Management, 348, 220–225. https://doi.org/10.1016/j.
foreco.2015.03.041
Laund ré, J. W. (2010). Behaviora l response race s, predator-p rey shell
games,ecologyof fear,andpatchuseofpumasandtheirungulate
prey.Ecology,91,2995–30 07.https://doi.org/10.1890/08-2345.1
Le Saout , S., Marti n, J. L., Blanch ard, P., Cebe, N., Mark H ewison, A.
J., Rame s, J. L., & Chamai llé-Ja mmes, S. (2015). Se eing a ghost?
Vigilanceand its driver sinapredator-freeworld.Ethology,121,1–
10. htt ps://doi. or g/10 .1111/eth.1237 7
LeSaout ,S.,Massouh,M.,Martin,J.L .,Presseault-Gauvin,H.,Poilvé,E.,
Côté,S.D.,Picot,D.,Verheyden,H.,&Chamaillé-Jammes,S.(2016).
Levels of fecal glucocorticoid metabolites donot reflect environ-
mental contrasts across islands in black-tailed deer (Odocoileus
hemionus sitkensis) populations. Mammal Research, 61, 391–398.
h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 1 3 3 6 4 - 0 1 6 - 0 2 9 4 - 9
LeSaout,S.,Padié,S.,Chamaillé-Jammes,S.,Chollet,S.,Côté,S.,Morellet,
N.,Pat tison,J.,Harris,E.,&Martin,J.L.(2014).Short-termeffects
ofhuntingon naïve black-tailed deer (Odocoileus hemionus sitken-
sis):behaviouralresponseandconsequencesonvegetationgrowth.
Canadian Journal of Zoology,92,915–925.https://doi.org/10.1139/
c j z - 2 0 1 4 - 0 1 2 2
Leaver,L.A.,&Daly,M.(2003).Effectofpredationriskonselectivityin
heteromyidrodents.Behavioural Processes,64, 71–75. ht tps://doi.
o r g / 1 0 . 1 0 1 6 / S 0 3 7 6 - 6 3 5 7 ( 0 3 ) 0 0 1 0 8 - 6
Li, C., J iang, Z., Li , L., Li, Z., Fan g, H., Li, C ., & Beaucham p, G. (2012).
Effec ts of Reprodu ctive Stat us, Social R ank, Sex and G roup Size
onVigilance PatternsinPrzewalski'sGazelle.PLoS One, 7,e32607.
https://doi.org/10.1371/journal.pone.0032607
Li ma ,S.L.(19 98 ). Non le t ha le f fe c tsi nt he eco lo g yo fp re d at or- p re yi nt er-
actions.BioScience,48,25–3 4.https://doi.org/10.2307/1313225
Lima,S.L.,&Dill,L.M.(1990).Behavioraldecisionsmadeundertherisk
ofpredation:areviewandprospec tus.Canadian Journal of Zoology,
68,619–640.https://doi.org/10.1139/z90-092
Lone,K .,Loe,L.E.,Gobakken,T.,Linnell,J. D.,Odden,J.,Remmen,J.,&
Mysterud,A.(2014).Livinganddyinginamulti-predatorlandscape
offear :roe deer aresqueezedbycontrastingpatternofpredation
riskimposedbyly nxandhumans.O ikos,123,641–651.https://doi.
org /10.1111/j .1600 -0706.2013.00 938.x
Lynch,E.,Nor thrup,J.M.,McKenna,M.F.,Anderson,C.R.Jr,Angeloni,
L.,& Wittemyer,G. (2014).Landscapeandanthropogenicfeatures
influen ce the use of auditor y vigilance by mu le deer. Behavioral
Ecology,26,75–82.ht tps://doi.org/10.1093/beheco/aru158
McAr thur, C., Banks, P.B., Boonstra,R., & Forbey,J. S.(2014).The di-
lemmaofforagingherbivores:dealingwithfoodandfear.Oecologia,
176, 6 7 7 – 6 8 9 . h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 0 0 4 4 2 - 0 1 4 - 3 0 7 6 - 6
McMahon , J. D., Lashley, M. A ., Brooks , C. P.,& Bar ton, B. T. (2018).
Covariance between predation risk and nutritional preferences
confounds interpretations of giving-up density experiments.
Ecology,99,1517–1522.ht tps://doi.org/10.1002/ecy.2365
Michaud,J.P.,Barbosa,P.R.,Bain,C.L.,&Torres,J.B.(2016).Extending
the“EcologyofFear”beyondprey:Reciprocalnonconsumptiveef-
fectsamongcompetingaphidpredators.Environmental Entomology,
45,1398–1403.https://doi.org/10.1093/ee/nvw133
Michel,E. S., Strickland, B. K., Demarais, S., Belant, J. L., Kaut z, T. M.,
Duquet te, J. F., Beyer, D. E. Jr, Chamberl ain, M. J., Mille r, K. V.,
Shuman, R. M., Kilgo, J. C., Diefenbach, D.R., Wallingford, B. D.,
Vreeland , J. K., Ditchkof, S. S. , DePerno, C. S ., Moorman, C . E.,
Chitwo od, M. C., & L ashley, M. A. (202 0). Relative rep roductive
phenologyandsynchronyaffect neonate survival in anonpreco-
cial ungulate. Functional Ecology, 34, 2536–2547. https://doi.
org /10.1111/1365- 24 35.13680
Middlet on, A. D., Kauf fman, M. J., McW hirter, D. E., Jimene z, M. D.,
Cook, R . C., Coo k, J. G., Alb eke, S. E., Saw yer, H., & White, P. J.
14 of 15
|
CHITWOOD eT al .
(2013). Linking anti-pre dator behaviour to p rey demography re -
veals limited risk ef fects of an actively hunting la rge carnivore.
Ecology Letters,16,1023–1030.https://doi.org/10.1111/ele.12133
Moll,R .J.,Killion ,A.K.,Montgomery,R.A., Tambling,C.J.,&Hayward,
M.W. (2016).Spatial pat terns ofAfricanungulate aggregationre-
vealcomplexbutlimitedriskeffec tsfromreintroducedc arnivores.
Ecology,97,1123–1134.https://doi.org/10.1890/15-0707.1
Moll,R.J.,Redilla,K.M.,Mudumba,T.,Muneza,A.B.,Gray,S.M.,Abade,
L.,Hayward,M .W.,Millspaugh,J.J., &Montgomery,R .A .(2017).
Themanyfacesoffear:asynthesisofthemethodologicalvariation
incharacterizingpredationrisk.Journal of Animal Ecology,86,749–
765. htt ps: //doi. org/10 .1111/13 65- 2656.126 80
Montgomery,R.A.,Moll,R.J.,Say-Sallaz,E.,Valeix,M.,&Prugh,L.R.(2019).
A tendency tosimplify complex systems. Biological Conservation,
233,1–11.https://doi.org/10.1016/j.biocon.2019.02.001
Ng’weno,C.C .,Maiyo, N. J.,Ali, A. H., Kibungei, A.K .,&Goheen, J. R.
(2017).Lionsinfluencethedeclineandhabit atshiftofhartebeestin
asemiaridsavanna.Journal of Mammalogy,98,1078–1087.https://
d o i . o r g / 1 0 . 1 0 0 7 / s 0 0 4 4 2 - 0 1 4 - 3 0 0 4 - 9
Nichols on, K. L., Mi lleret, C., M ånsson, J., & San d, H. (2014). Testing
the risk of predation hypothesis: the influence of recolonizing
wolvesonhabitatusebymoose.Oecologia,176,69–80.https://doi.
o r g / 1 0 . 1 0 0 7 / s 0 0 4 4 2 - 0 1 4 - 3 0 0 4 - 9
Norum,J.K.,Lone,K.,Linnell,J.D.,Odden,J.,Loe,L.E.,&Mysterud,A.
(2015). Landscapeofr isk to roe deerimposedbylynx and differ-
enthumanhuntingtactics.Europ ean Journal of Wildlife Research,61,
8 3 1 – 8 4 0 . h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 1 0 3 4 4 - 0 1 5 - 0 9 5 9 - 8
Nunes, J . A. C., C osta, Y., Blu mstein, D. T., Led uc, A. O. , Dorea, A . C.,
Benevides, L. J., Sampaio, C.L .,&Barros,F.(2018).Globaltrends
onreeffishes’ecologyoffear:Flightinitiationdistanceforconser-
vation. Marine Environmental Research, 136, 153–157. https://doi.
org/10.1016/j.marenvres.2018.02.011
Nuttl e, T.,Yerge r,E. H ., Stoleso n, S. H., & Ris tau, T. E. (2011). Lega cy
oftop-downherbivorepressurericochetsbackupmultipletrophic
levelsinfores tcanopiesover30years .Ecosphere,2,1–11.https://
doi.org/10.1890/E S10- 0010 8.1
Packer, C., H olt, R. D., Hud son, P.J. , Laffer ty, K. D., & Dobso n, A. P.
(2003).Keeping the herdshealthy and alert: implicationsofpred-
ator control for infectious disease. Ecology Letters, 6, 797–802.
https://doi.org/10.1046/j.1461-0248.2003.0 0500.x
Paine,R.T.(1980).Foodwebs:link age,inte rac tio nstrengthandco mmu-
nityinfrastructure.Journal of Animal Ecology,49,667–685.htt ps://
doi.org/10.2307/4220
Pays, O., Blanchard, P., Valeix, M., Ch amaillé-Jamme s, S., Duncan, P.,
Périqu et, S., Lomb ard, M., Nc ube, G., Taraki ni, T., Makuwe, E., &
Fritz,H.(2012).Detectingpredatorsandlocatingcompetitorswhile
foraging:anexperimentalstudyofamedium-sizedherbivoreinan
Africansavanna.Oecologia,169,419–430.https://doi.org/10.1007/
s0 0 4 4 2- 011- 2218 - 3
Peckarsky, B. L.,Abrams, P.A.,Bolnick, D. I., Dill, L. M.,Grabowski,
J. H., Lut tbeg, B., Orrock, J. L ., Peacor, S. D., Preisser, E. L.,
Schmit z, O. J., & Trussell, G . C. (200 8). Revisitin g the classic s:
considering nonconsumptive effects in textbook examples of
predator–preyinteractions. Ecology,89,2416–2425.https://doi.
org /10.189 0/07-1131.1
Pecorella, I., Fer retti, F.,Sforzi, A ., & Macchi, E. (2016). Effects ofcull-
ing on vigilance behaviour and endogenous stress response of
female fallow deer. Wildlife Research, 43, 189–196. https://doi.
org /10.1071/ WR15118
Peers,M . J., Majchrzak , Y.N.,Neilson, E., Lamb, C. T., Hämäläinen,A.,
Haines,J.A .,Garland,L., Doran-Myers,D.,Broadley,K.,Boonstra,
R., & Bou tin, S. (2018). Q uantify ing fear ef fects on p rey demog-
raphy in nature. Ecolog y,99, 1716–1723 . https://doi.o rg /10.10 02 /
ec y.2 381
Périqu et, S., Rich ardson, P., Camer on, E. Z., Ga nswindt , A., Belto n, L.,
Loubser,E.,&Dalerum,F.(2017).Effec tsoflionsonbehaviourand
endocrine stressinplains zebras. Ethology, 123, 667–674.https://
doi .org/10.1111/eth .126 38
Périquet,S.,Todd-Jones,L.,Valeix,M.,Stapelkamp,B.,Elliot,N.,Wijers,
M., Pays , O., Fortin , D., Madzikan da, H., Frit z, H., Macd onald, D.
W.,&Loveridge,A .J.(2012).Influenceofimmediatepredationrisk
bylionsonthe vigilanceofpreyofdifferentbody size. Behavioral
Ecology,23,970–976.https://doi.org/10.1093/beheco/ars060
Polis, G. A.,Sears, A. L.,Huxel, G. R., Strong,D.R .,&Maron, J.(2000).
When is a trophic cascade a trophi c cascade? Trends in Ecolog y
& Evolution, 15, 47 3–475. ht tp s://doi .or g/10.1016/S0169
- 5 3 4 7 ( 0 0 ) 0 1 9 7 1 - 6
Preisser,E.L.,Bolnick,D.I.,&Benard,M.F.(2005).Sc aredtodeat h?The
effec ts ofintimidation and consumption in predator–prey inter ac-
tions.Ecology,86,501–509.https://doi.org/10.1890/04-0719
Prugh, L . R., Si vy, K. J., Ma honey, P.J., Ga nz, T. R., Ditm er,M . A., van
deKerk, M., Gilbert, S. L.,& Mont gomer y,R.A .(2019).Designing
studies of predation risk for improved inference in carnivore-
ungulate systems. Biological Conservation, 232, 194–207.h ttps://
doi.org/10.1016/j.biocon.2019.02.011
Riginos , C. (2015). Climate and the landscap e of fear in an African
savanna. Journal of Animal Ecology, 84, 124–133. https://doi.
org /10.1111/1365- 2656.12262
Riginos ,C.,& Grace,J.B. (2008).Savannatreedensity,herbivores, and
the herbaceous community: bottom-up vs. top-down effects.
Ecology,89,2228–2238.
Ripple , W.J. , & Beschta, R . L. (2003). Wol f reintroduc tion, predat ion
risk,andcottonwoodrecoveryinYellowstoneNationalPark.Forest
Ecology and Management,184, 299–313 . ht tps://doi. org /10.1016/
S 0 3 7 8 - 1 1 2 7 ( 0 3 ) 0 0 1 5 4 - 3
Ripple,W.J.,&Beschta,R.L.(2004).Wolvesandtheecologyoffear:can
predationriskstructureecos ystems?AIBS Bulletin,54,755–766.
Ripple , W.J. , & Beschta, R . L. (2006 a). Linking a coug ar decline, tr o-
phic cascade, and catastrophic regimeshift inZion NationalPark.
Biological Conservation, 133, 397–408. https://doi.org/10.1016/j.
biocon.2006.07.002
Ripple,W.J.,&Beschta,R.L.(20 06b).Linkingwolvestowillowsviarisk-
sensiti ve foragin g by ungulate s in the nor thern Yellow stone eco -
system.Forest Ecology and Management,230, 96–106. https://doi.
org/10.1016/j.foreco.2006.04.023
Ripple , W.J. , & Beschta, R . L. (2012). L arge predato rs limit herb ivore
densities in northern forest ecosystems. European Journal of
Wildlife Research, 58, 733–742. https://doi.or g/10.1007/s1034
4- 012- 0623- 5
Ripple,W.J.,Beschta,R.L.,For tin,J.K.,&Robbins,C.T.(2014).Trophic
casca des from wolve s to grizzly bea rs in Yellowstone. Journal of
Animal Ecology,83,223–233.
Ripple,W.J.,Beschta,R.L.,&Painter,L.E.(2015).Trophiccascadesfrom
wolves to al ders in Yellowsto ne. Forest Ecology and Management,
354,254–260.https://doi.org/10.1111/1365-2656.12123
Ripple,W.J.,Estes,J.A.,Schmitz,O.J.,Constant,V.,Kaylor,M.J.,Lenz,
A.,Motley,J.L.,Self,K.E.,Taylor,D.S.,&Wolf,C.(2016).Whatisa
trophiccascade?Trends in Ecol ogy & Evolution,31,842–849.https://
doi.org/10.1016/j.tree.2016.08.010
Ritchie, E. G., Elmhagen, B., Glen, A. S., Letnic, M., Ludwig, G ., &
McDonal d, R. A. (2 012). Ecosystem r estoratio n with teeth: w hat
role for predators? Trends in Ecology & Evolution, 27, 265–271.
https://doi.org/10.1016/j.tree.2012.01.001
Ri tc hie ,E .G . ,& Jo hns on ,C. N.(20 0 9).P re dat or in te r ac t ion s, mes op red a-
torreleaseandbiodiversityconservation.Ecology Letters,12,982–
998 .htt ps://doi. org/10 .1111/j.1461-024 8. 200 9.013 47.x
Ross,J.,Hearn,A.J.,Johnson,P.J.,&Macdonald,D.W.(2013).Activity
patter ns and temporal avoidance by prey in response to Sunda
clouded leopard predation risk.Journal of Zoology, 290, 96–106.
https ://doi.or g/10.1111/ jzo.12 018
Rothley, K. D., S chmitz, O. J., & Co hon, J. L. (1997). Forag ing to bal-
ance conflicting demands: novel insights from grasshoppers
|
15 of 15
CHITWO OD eT al .
under pr edation risk. Behavioral Ecology, 8, 551–559. ht tps://doi.
org /10.1093/be heco/8. 5.551
Samelius,G., Andrén, H., Kjellander, P.,&Liberg,O. (2013). Habitat se-
lect io na nd ri sk ofpr ed at io n: re -c ol on iz ationbyl ynxh adli mite di m-
pactonhabitatselectionbyroedeer.PLoS One,8,e75469.https://
doi.org/10.1371/journal.pone.0075469
Say-Sallaz, E., Chamaillé-Jammes, S., Fritz,H.,& Valeix, M. (2019).Non-
consumptive effects of predation in large terres trial mammals:
mapping our knowledge and revealing the tip of the iceberg.
Biological Conservation, 235, 36–52. htt ps://doi.or g/10.1016/j.
biocon.2019.03.044
Schmitz,O.J.(1998).Directandindirec teffectsofpredationandpreda-
tionriskinold-fieldinteractionwebs.The American Naturalist,1 51,
327–342.https://doi.org/10.1086/286122
Schmit z, O. J., Beckerman, A . P.,& O’Brien, K.M. (1997). Behaviorally
mediatedtrophic cascades:effec ts of predation risk on foodweb
interactions.Ecology,78,1388–1399.
Schmit z,O.J.,Hambäck,P.A ., &Beckerman, A. P.(20 00).Trophiccas-
cades i n terrest rial syste ms: a review of th e effect s of carni vore
removalsonplants.The Americ an Naturalist,155,141–153.https://
doi.org/10.10 86/3 03311
Schmit z, O. J., Hawlena , D., & Trussell, G. C . (2010). Predator c ontrol
of ecosys tem nutrient d ynamics. Ecology Letters, 13, 1199–1209.
https ://doi.or g/10.1111/ j.14 61-0248 .2 010.01 511.x
Schmit z,O.J.,Krivan,V.,&Ovadia,O.(200 4).Trophiccascades:thepri-
macyoftrait-mediatedindirectinteractions.Ecology Letters,7,153–
163.https://doi.org/10.1111/j.1461-0248.2003.00560.x
Schuttler,S.G.,Parsons,A.W.,Forrester,T.D.,Baker,M.C.,McShea,W.
J.,Costello,R .,&Kays,R. (2017). Deer on the lookout: how hunt-
ing,hikingandcoyotesaf fectwhite-taile ddeervigilance.Journal of
Zoology,301,320–327.https://doi.org /10.1111/jzo.12416
Shanno n, G., Cor des, L. S ., Hardy, A. R ., Angel oni, L. M ., & Crooks , K.
R.(2014).Behavioralresponsesassociatedwithahuman-mediated
predator shelter. PLoS One, 9, e94630. https://doi.org/10.1371/
journal.pone.0094630
Shelton , A. L., H enning, J. A ., Schul tz, P.,& C lay,K . (2014). Effec ts of
abundant white-tailed deer on vegetation, animals, mycorrhi-
zal fung i, and soils. Forest Ecology and Management, 320, 39–49.
https://doi.org/10.1016/j.foreco.2014.02.026
Sherif f,M. J., Krebs, C. J., & Boonstra, R. (2010).The ghos ts of preda-
torspast:populationc yclesandtheroleofmaternalprogramming
underfluctuatingpredationrisk.Ecology,91, 2983–2994. https://
doi.org/10.1890/09-1108.1
Shurin , J. B., & Seablo om, E. W. (2005). Th e strength of t rophic cas-
cades across ecosystems: predictions from allometr y and en-
ergetics. Journal of Animal Ecology, 74, 102 9–103 8. https://doi.
org /10.1111/j .136 5-265 6. 20 05 .0 0999.x
Smith,J.A.,Gaynor,K.M.,&Suraci,J.P.(2021).Mismatchbetweenrisk
andresponse mayamplif ylethalandnon-lethaleffec tsofhumans
onwildanimalpopulations.Frontie rs in Ecology and Evolu tion,9,140.
https://doi.org/10.3389/fevo.2021.60 4973
Smith, J.A.,Suraci,J.P.,Clinchy,M.,Craw ford,A.,Rober ts,D.,Zanette,
L. Y.,& Wilmers, C.C .(2017). Fear of the human‘super predator’
reduces f eeding ti me in large c arnivore s. Proceedings of the Royal
Society B: Biological Sciences, 284(1857), 201704 33. ht tps://doi.
org /10.1098/r sp b.2017.0 43 3
Stotz, H . U., Pittend righ, B. R ., Kroymann , J., Weniger, K., Frit sche, J.,
Bauke, A ., & Mitchell- Olds, T. (20 00). Induce d plant defense r e-
sponses agains t chewing insect s. Ethylene signa ling reduces re-
sistance of Arabidopsis against Egyptian cotton worm but not
diamondbackmoth.Plant Physiology,124, 1007–1018 . ht tps://doi.
org /10.1104/pp.124.3 .1007
Str auss,S.Y.,&Agra wal,A .A .(1999).Theeco logya ndevolut ionofp lant
tolerancetoherbivory.Trends in Ecology & Evolution, 14, 179–185.
h t t p s : / / d o i . o r g / 1 0 . 1 0 1 6 / S 0 1 6 9 - 5 3 4 7 ( 9 8 ) 0 1 5 7 6 - 6
Suraci, J. P., Clinchy, M., Dill, L. M., Roberts, D., & Zanette, L. Y.
(2016). Fear of lar ge carnivo res caus es a trophic casc ade. Nature
Communications,7,10698.h ttps://doi.org/10.10 38/ncomms10698
Taylor,R.J.(1984).Predation.ChapmanandHallInc.
Teckentrup, L ., Grimm, V., Kramer-Schadt, S., & Jeltsch, F. (2018).
Community consequences of foraging under fear. Ecological
Modelling, 383, 80–90. https://doi.org/10.1016/j.ecolm
odel.2018.05.015
Terborgh, J. , Lopez, L ., Nuñez, P., Rao, M., S hahabudd in, G., Or ihuela,
G.,Riveros,M .,A scanio,R ., Adler,G.H.,Lambert,T.D., & Balbas,
L. (2001). Ecological meltdown in predator-free forest frag-
ments. Science, 294, 1923–1926. https://doi.org/10.1126/scien
ce.1064397
Thaker,M., Vanak, A.T., Owen,C .R., Ogden,M.B., Niemann, S. M., &
Slotow,R .(2011).Minimizingpredationriskinalandscapeofmul-
tiple pr edators: ef fects on t he spatial dis tributio n of African un-
gulates.Ecolog y,92,398–4 07.https://doi.org/10.1890/10-0126.1
Thur fjell, H., Ciut i, S., & Boyce, M. S. ( 2017). Learning fro m the mis-
takes of others:Howfemale elk (Cervus elaphus)adjust behaviour
with age to avo id hunters. PLoS One, 12, e01780 82. https://doi.
org/10.1371/journal.pone.0178082
Trussell,G.C.,Ewanchuk,P.J.,&Matassa,C.M.(2006).Thefearofbeing
eaten reduces energy transfer in a simple food chain. Ecology,87,
2979–2984.
Wallach, A . D., Johnson, C . N., Ritchie, E. G ., & O’Neill, A . J.
(2010). Predator control promotes invasive dominated eco-
logical states. Ecology Letters, 13, 1008–1018. ht tps://doi.
org /10.1111/j .1461- 024 8. 2010.01492 .x
Waser,N.M.,Price,M.V.,Blumstein,D.T.,Arózqueta,S.R.,Escobar,B.D.
C.,Pickens,R.,&Pistoia,A.(2014).Coyotes,deer,andwildflowers:
diverseevidencepointstoatrophiccascade.Naturwissenschaften,
101, 4 2 7 – 4 3 6 . h t t p s : / / d o i . o r g / 1 0 . 1 0 0 7 / s 0 0 1 1 4 - 0 1 4 - 1 1 7 2 - 4
Werner,E.E.,&Peacor,S.D.(2003).Areviewoftrait-mediatedindirect
interac tionsinecologicalcommunities.Ecolog y,84,1083–1100 .
Wikenros,C.,Kuijper,D.P.,Behnke,R.,&Schmidt,K.(2015).Behavioural
responses of ungulates to indirect cues of an ambush preda-
tor. Behaviour, 152, 1019–104 0. https://doi.org/10.116 3/15685
39X-00003266
Zwijacz-Kozica,T.,Selva,N.,Barja,I.,Silvàn,G.,Martìnez-Fernàndez,L.,
Illera,G. C., & Jodlowski, M. (2013). Concentration of fecal corti-
sol metabolites in chamois in relationto tourist pressure in Tatra
National Park (south Poland). Acta Theriologica, 58, 215–222.
https://doi.org/10.1007/s1336 4- 012- 0108- 7
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versionofthearticleatthepublisher ’swebsite.
How to cite this article:Chitwood,M.C.,Baruzzi,C.,&
Lashley,M.A.(2022).“Ecologyoffear”inungulates:
Opportunitiesforimprovingconservation.Ecology and
Evolution,12,e8657.https://doi.org/10.1002/ece3.8657
