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RESEARCH ARTICLE

Audience Effects, but not Environmental Influences, Explain Variationin Gorilla Close Distance Vocalizations — A Test of the AcousticAdaptation Hypothesis

DANIELA HEDWIG1*, ROGER MUNDRY2, MARTHA M. ROBBINS1, AND CHRISTOPHE BOESCH1

1Department of Primatology, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany2Department of Primatology and Department of Developmental and Comparative Psychology, Max Planck Institute forEvolutionary Anthropology, Leipzig, Germany

Close distance vocalizations are an integral part of primate vocal communication. They exhibit largeacoustic variationwhich has been suggested to constitute flexible responses to the highly variable socialsetting of group living animals. However, a recent study suggested that acoustic variation in closedistance calls of baboons may also arise from acoustic adaptations to environmental factors in order tocounteract sound degradation. We tested whether the variation in calling rate and acoustic structure ofgorilla close distance vocalizationsmay serve to counteract distorting effects of vegetation during soundpropagation. Using focal animal sampling we recorded the vocal behavior of 15 adult individuals livingin two groups: one group of western lowland gorillas Gorilla gorilla gorilla and one group of mountaingorillas Gorilla beringei beringei. We considered the distance between the caller and its nearestneighbor as the minimum transmission distance of calls; while vegetation density was quantifiedthrough measures of visibility. Our analysis revealed vocal plasticity in gorilla close calls in relation tochanges in visibility and nearest neighbor distance. However, the observed changes in fundamentalfrequency and calling rate are unlikely to counteract degrading effects of vegetation, but rather seem toreflect reactions to variation in spatial and visual separation from other group members, similar to theaudience effects demonstrated in a range of other species.We propose that vocal plasticity to counteractdistorting environmental effectsmay not be prevalent across taxa and perhaps confined to species livingin heterogeneous habitats with highly variable transmission conditions. Am. J. Primatol. 77:1239–1252, 2015. © 2015 Wiley Periodicals, Inc.

Key words: acoustic adaptation hypothesis; audience effect; close distance calls; gorilla; syntacticstructure

INTRODUCTIONThe fundamental notion behind communication

is that information contained in a signal is reliablytransferred from a sender to a receiver. In vocalcommunication, this transfer can be impeded assound experiences reverberation and absorptionduring propagation, leading to the attenuation, anddistortion of the acoustic signal. The strength of suchdegrading effects depends on frequency-related andtemporal features of vocalizations in relation toenvironmental characteristics and the distance thesound travels. Therefore, the acoustic adaptationhypothesis (AAH hereafter) predicts that the acous-tic characteristics of vocal signals and calling rateshould be adjusted to environmental features toenhance sound propagation, particularly if calls needto travel far distances [Morton, 1975; Waser &Brown, 1986, extended to call usage by Ey & Fischer,2009]. Previous studies providing support for theAAH were mainly based on inter- or intra-specific

cross-site comparisons of long distance vocalizationsused in populations living in densely vegetated (e.g.,forest) and open habitats (e.g., grassland). However,a more recent study on baboons [Ey et al., 2009]suggested that environmental conditions also havean impact on the production of close distancevocalizations. In particular, their study indicated

Contract grant sponsor: Leakey Foundation; contract grantsponsor: Max Planck Society

�Correspondence to: Daniela Hedwig, Department of Primatol-ogy, Max Planck Institute for Evolutionary Anthropology,Deutscher Platz 6, 04103 Leipzig, Germany E-mail:[email protected]

Received 15 January 2015; revised 5 June 2015; revisionaccepted 12 August 2015

DOI: 10.1002/ajp.22462Published online 9 September 2015 in Wiley Online Library(wileyonlinelibrary.com).

American Journal of Primatology 77:1239–1252 (2015)

© 2015 Wiley Periodicals, Inc.

that baboons exhibit a vocal plasticity that enablesthem to modify the acoustic structure of their gruntsand calling rate when moving between forest andgrassland areas within their home ranges. Thisis surprising because, given the generally shortdistances such calls need to travel, transmissionconditions would not be expected to exhibit strongselective pressures on their production.

Close distance vocalizations are an integral partof primate vocal communication as they mediatethe social interactions between individuals [e.g.,Boinski, 1993; Boinski & Campbell, 1996; Cheneyet al., 1995; Silk et al., 2000; Whitham et al., 2007].They exhibit a large acoustic variation [e.g., Bouchetet al., 2012; Elowson & Snowdon, 1994; Lemasson& Hausberger, 2011; Sugiura, 2007] which hasbeen suggested to constitute flexible responsesto the highly variable social environment of groupliving animals [e.g., Bouchet et al., 2012; Snowdonet al., 1997]. While the acoustic variation withinclose distance calls can be driven by variabilityin underlying emotional states [e.g., Bayart,1990; Rendall, 2003], they can encode informationabout the caller‘s identity [Rendall, 2003], group[Townsend, 2010], activity [Rendall, 1999; Radford& Ridley, 2008; Townsend, 2011], and social context[Rendall, 1999; Radford & Ridley, 2008]. Investigat-ing to what extent the acoustic variation withinclose distance calls constitutes an adjustment tovarying environmental conditions to counteractsignal degradation will lead to a more comprehen-sive understanding of the functioning of closedistance vocalizations.

Close distance vocalizations constitute a crucialaspect of gorilla vocal behavior [Fossey, 1972;Harcourt et al., 1986, 1993; Harcourt & Stewart,1996, 2001; Schaller, 1963; Seyfarth et al., 1994;Stewart & Harcourt, 1994; Salmi et al., 2013]. Theseso called close calls are variable vocalizationsranging from short grunts to longer grumbles andhums which typically consist of one or more acousticunits [e.g., Harcourt et al., 1986, 1993; Harcourt &Stewart, 1996, 2001; Hedwig et al., 2014 Seyfarthet al., 1994; Salmi et al., 2013]. In a previous studywedemonstrated that the gorilla close calls are built offive intergraded types of acoustic units (low pitchedunit types: atonal grunt a1, tonal grunt t2, grumblet4; higher pitched unit types: short hum t1, long humt3) which were flexibly, yet, non-randomly arrangedinto more than 150 combinations [Hedwig et al.,2014]. Acoustic, and particularly syntactic, variationwithin close calls, and calling rate appeared tocorrelate with the callers’ activity, its role in vocalexchanges, that is whether calls were given as areply, or spontaneously, as well as the proximity toother individuals [Harcourt et al., 1993; Hedwiget al., 2015; Seyfarth et al., 1994; Salmi et al., 2013].Results of our previous study [Hedwig et al.,2015] suggest that parts of the syntactic variation

within gorilla close calls may be adaptive in order toenhance signal transmission when communicatingover large distances, by using combinations consist-ing of long unit types, which may increase signaldetectability [Klump & Maier, 1990; Nemeth et al.,2006]. Gorillas are highly terrestrial, forest dwellingspecies that typically inhabit areas with denseground vegetation [Bermejo, 1999; Nkurunungiet al., 2005; Tutin & Fernandez, 1984; Yamagiwa&Basabose, 2006]. Since absorption and reflection ofsound is particularly strong when propagating closeto the ground [“ground effect”, Wiener & Keast,1959] modifications of their close calls in responseto such distorting environmental conditions areplausible.

Based on this, we investigated the influence ofvegetation density and transmission distance oncalling rate as well as duration and fundamentalfrequency of gorilla close calls, which we sampledfrom 15 adult individuals living in two groups: onegroup of western lowland gorillas Gorilla gorillagorilla and one group of mountain gorillas Gorillaberingei beringei. We quantified vegetation densitythrough measures of visibility and inferred theminimum transmission distance of calls from thedistance to the caller’s nearest neighbor. Accordingto the acoustic adaptation hypothesis, we predictedthat with increasing nearest neighbor distance anddecreasing visibility the gorillas will: (i) emit moreclose calls since this will increase the likelihood ofthe signal to be detected by a recipient [Ey &Fischer, 2009]. Concerning the acoustic structure,we expected that increasing nearest neighbordistance and decreasing visibility the gorillas willlead to calls having a (ii) lower fundamentalfrequency since high frequencies are particularlyaffected by attenuating influences [Bradbury &Vehrencamp, 2011] and (iii) a longer duration,which increases transmission distance and thedetectability of a signal [Klump & Maier, 1990;Nemeth et al., 2006]. In particular, since theimportance of degrading environmental effectsincreases with increasing transmission distance,we expected an interaction between visibility andnearest neighbor distance. Alternatively, we mayfind correlations of calling rate and/or acousticvariation with visibility and/or nearest neighbordistance, which may reflect reactions to changes invisual and spatial separation to other groupmembers similar to audience effects demonstratedin numerous other species [e.g., Betta splendens:Doutrelant et al., 2001; Taeniopygia guttata: Pollicket al., 2005; Cebus paella: Schel et al., 2013; Pantroglodytes: Vignal et al., 2004]. Given the syntacticstructure of gorilla close calls [Hedwig et al., 2014],changes in their acoustic structure can happen ontwo levels. First, the gorillas may alter the unit typecomposition of their calls and hence use differentcombination types, and, secondly, the gorillas may

Am. J. Primatol.

1240 / Hedwig et al.

use the same combination types but modify theacoustic structure of the constituent unit types.In order to account for this we investigated theeffects of visibility and nearest neighbor distance onthe unit type composition of calls as well as theacoustic variation within calls with similar unittype composition (Table I).

METHODSStudy Sites and Subjects

We observed one group of mountain gorillas inBwindi Impenetrable National Park (0°53–1°08N,29°35–29°50E), Uganda. Data collection focused on10 adult individuals (one silverback, five females,and four blackbacks) of the habituated “Kyagurilo”group [Robbins, 2008]. The study site consists ofafromontane rainforest (altitude 1160–2600m)which is characterized by a dense understory ofherbaceous vegetation, interspersed with patches ofclosed-canopy forest. Due to regulations of theUganda Wildlife Authority, observations were re-stricted to approximately four hours per day. Datacollection was conducted usually in the mornings, on312 days during a total of 12 months from Octo-ber 2007 through October 2008.

One group of habituated western lowlandgorillas was observed at the Bai Hokou study site(2°51 N, 16°28 E) which is located in the Dzanga–Ndoki National Park, Central African Republic(altitude 340–615m). Data were collected on fiveadult individuals (one silverback, three females,and one blackback) of the “Makumba” group[Masi et al., 2009]. The habitat is a low altitudemixed-species semi-evergreen rainforest, inter-spersed with areas of Gilbertiodendron dewevrei(Caesalpiniaceae) closed-canopy forest and patches ofopen-canopy forest with dense terrestrial herbaceousvegetation.Datawere collected in themornings (7:00–12:00) and/or afternoons (12:00–17:00) on 124 daysover a period of eight months from April toNovember 2009.

Data CollectionWe used focal animal sampling [Altmann,

1974] during which we conducted continuous audiorecordings of the focal animal’s vocal behavior.For each vocalization the following contextual datawere recorded: (i) the activity of the focal animal,which we categorized into resting (sleeping, sitting,grooming, nursing), and foraging (preparation andingestion of food, locomotion between feedingspots), (ii) the distance of the focal animal to itsnearest neighbor, which also included all non-adultindividuals. We used this as a proxy for transmissiondistance. We thereby assumed that the nearestneighbor distance reflects the minimum distancethe call had to travel in order to be received. It ispossible that calls were directed to individualsfurther away than the nearest neighbor, whichwould result in an underestimation of the actualtransmission distance, and an overestimation ofacoustic adaptation given the nearest neighbordistances. To measure nearest neighbor distancewe used the following categories: 0: physical con-tact, 1: >0–2m, 2: >2–5m, 3: > 5–10m, 4: >10–20m, 5: > 20m. (iii) We recorded whether thevocalization was given spontaneously or in reply toanother individual’s call. A reply was defined asany vocalization given within 3 sec after anotherindividual’s call [based on Seyfarth et al., 1994]. Ouranalyses focused on close calls given spontaneouslyby the focal animal excluding those given in reply toanother individual’s call. We did so for two reasons:first, our sample size did not allow us to statisticallycontrol for potential acoustic differences betweencalls given spontaneously and in reply, as known forgorilla double grunts [Seyfarth et al., 1994], andsecondly, to prevent ambiguity in our measure ofminimum transmission distance, as for reply callswe did not have enough measurements of thedistance to the first caller. Additionally, we usedinstantaneous sampling [Altmann, 1974] to recordthe focal animal’s activity and its nearest neighbordistance at 5min intervals.

TABLE I. Overview of Predictions of the Acoustic Adaptation Hypothesis on Calling Rate and the AcousticStructure of Gorilla Close Calls (See Figure 1 for Details on the Syntactic Structure)

Calling rate

Acoustic structure

Call compositionAcoustic variation within

combination types

With decreasing visibility andincreasing nearestneighbor distance

Call morefrequently

Combination types comprising long unit types (t4 and t3) and/orunit types of low fundamentalfrequency (t4 and t2) will beused more frequently

Constituent unit types willhave a longer durationand/or a lower fundamentalfrequency

Given the syntactic structure of gorilla close calls, predictions concerning their acoustic structure weremade on two levels: first, the unit type composition ofcalls and, secondly, the acoustic variation within calls with similar unit type composition (see methods section for details on how such combination typeswere defined).

Am. J. Primatol.

Acoustic Adaptations in Gorillas / 1241

Data on vegetation density were collected bymeasuring visibility every 10min for the westerngorillas and every 15min for the mountain gorillas.We used different time intervals for the two studygroups because the western gorillas changed theirlocation more frequently compared to the mountaingorillas. To measure visibility, the first authorkneeled down to a level that was approximately atthe eye-height of a gorilla at roughly the locationwhere the focal animal had been and estimated thefarthest distance she could see using the followingcategories: 1: 0–5m, 2: >5–10m, 3: >10–15m, 4:> 15–20m, 5:> 20m.We validated these estimationsby comparing them with actual measurements. Wefirst estimated visibility as above and then subse-quently moved with a bright orange cardboard sheet(measurements 26�17 cm) held waist-high in astraight line away from the observer. Once the sheetwas no longer visible we measured its distance tothe observer. Estimated and measured visibilityrecords were strongly correlated (Spearman’s rankcorrelation: P¼0.83, n¼201, P< 0.0001).

We used one category (category 5) for all callswith a nearest neighbor distance or visibility of> 20m since distance estimations were likely tobecome inaccurate with increasing distance. Toinclude visibility and nearest neighbor distance asquantitative rather than ordinal predictor variablesinto our analyses, we transformed them to intervalscale by using the mid-point value of each category,as defined above, instead of the categories itself.Since mid-points cannot be derived for distance andvisibility category 5 (>20m), we only analyzed callsgiven within up to 20m of nearest neighbor distanceand visibility, respectively.

AnalysisCall rate

We segmented each focal period into 5minintervals according to the instantaneous samplingand calculated the number of calls given by thefocal animal during each time interval (see supple-mentary material S1 for an overview of calling ratesmeasured for the different study individuals). Visi-bility estimates for each time interval were obtainedfrom each interval’s temporarily closest visibilitymeasurement.

We used a Generalized Linear MixedModel withPoisson error structure and log link function forthe analysis [GLMM; Baayen et al., 2008]. We havechosen GLMM for our statistical analysis as itenabled us to test the interacting influences ofvisibility and nearest neighbor distance on call ratewhile controlling for other possible factors influenc-ing vocal production (e.g., Ey & Fischer, 2009). TheGLMM additionally allows for taking random effectssuch as caller into account. In addition to visibilityand nearest neighbor distance the model included

their interaction since the importance of degradingenvironmental effects increases with increasingtransmission distance. Furthermore, we includedthe following control predictors as fixed effects(Table II): (i) activity (foraging/resting) because thebehavioral context is known to correlatewith the rateat which gorillas give close calls [e.g., Harcourt et al.,1986], (ii) group (western/mountain gorilla group) inorder to control for differences in vocal behaviorbetween the individuals of the two groups, potential-ly due to differences in social behavior [Gustisonet al., 2012; Robbins, 2010; Salmi et al., 2013], (iii)time of day and a squared term of time of day tocontrol for potential changes in calling rate through-out the day [e.g., Schneider et al., 2008], and finally,an autocorrelation term to account for temporalinterdependence between data points (see supple-mentary material S2 for information on how theautocorrelation term was derived). Lastly, to controlfor pseudoreplication (i.e., data points from the sameindividual are statistically non-independent andhence specific individuals may drive an effect whenin fact there is actually no effect), we incorporated“caller” as a random effect into the model [Bolkeret al., 2009; Jaeger, 2008; Laird & Ware, 1982].Following Schielzeth & Fortsmeier [2009] andBarr et al. [2013] we included random slopes forall fixed effects predictor variables except group, andthe autocorrelation term to keep type I error rate atthe nominal level of 5% (Table II). We could notaccount for the possibility of the random slopesbeing correlated with the random intercept sincethe respective models did not converge anymore.However, as shown by Barr et al. [2013] notaccounting for such correlations does not severelyaffect type I error rate.

Acoustic structureAnalyseswere conducted on a subset of calls used

in a previous study in which we demonstrated thesyntactic properties of gorilla close calls [Hedwiget al., 2014, Fig. 1]. We measured the meanfundamental frequency of calls semi-automaticallywith the custom-made software LMA developedby Kurt Hammerschmidt [Hammerschmidt, 1990;Schrader &Hammerschmidt, 1997] on spectrogramswith a 4Hz frequency and 4ms temporal resolution.If the close calls consisted of multiple acoustic unitsthe mean frequency of the call was calculated as themean of the average frequencies calculated per unit.Atonal units (i.e., for which no fundamental frequen-cywas detectable)were not included into the analysissince they were not recorded frequently enough toallow for a meaningful statistical analysis of theiracoustic parameters. Call duration was measuredmanually on spectrograms with a 20Hz frequencyand 1ms temporal resolution using Avisoft SASlabPro (see supplementary material S1 for an overviewof the fundamental frequency and duration of close

Am. J. Primatol.


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Am. J. Primatol.


callsmeasured for the different study individuals). Inorder to account for the fact that gorillas may adjustthe fundamental frequency or duration of calls tonearest neighbor distance and/or visibility throughaltering the unit type composition of their callsand/or, modifying the acoustic structure of theconstituent unit types we categorized combinationsinto “combination types” based on their unit typecomposition. Specifically, we defined combinationtypes such that they were invariant with regard tothe relative proportion of unit types they comprised.For instance, all combinations comprising twoparticular types (e.g., t1 and t3) with the samerelative frequencies of occurrence were considered tobe of the same combination type. To avoid problemsresulting from small sample sizes per combinationtype we restricted our analysis to combination typeswith more than ten observations, resulting in a totalof ten combination types (Table III).

We used General Linear Mixed Models withGaussian error structure and identity link [GLMM;Baayen et al., 2008] for analyses. In addition tocontrolling for possible other factors influencing vocalproduction and taking into account random effectssuch as caller, the GLMM allowed us to test theinteracting influences of visibility and nearest neigh-bordistanceonunit typecompositionof callsaswell asthe acoustic structure of unit types simultaneously.With regard to the fixed and random effects thesemodels were largely identical to that used for call rate(see above), but lacked the control variable daytime.To investigate whether the gorillas modify the unittype composition of calls and/or adjust the acousticstructure of unit types in response to changes invisibility and nearest neighbor distance we repre-sented both nearest neighbor distance and visibilityby two fixed effects using “within-subjects centering”[van de Pol & Wright, 2009]. First, we included theaverage distance and visibility per each combinationtype (“bw.dist”, “bw.vis”) to represent their variation

betweencombination types.Secondly,we included thedifferences between each calls’ nearest neighbordistance and visibility and its combination type’saverage distance and visibility, respectively, in orderto represent their variation within combinationtypes (“w.dist”, “w.vis”). If the average distance oraverage visibility of combination types have a signifi-cant effect on the mean fundamental frequency orduration of calls this suggests that the contextualvariable (distance or visibility, respectively) lead tochanges in theunit typecompositionof callsandhencethe use of different combination types. If distancevariation or visibility variation within combinationtypes reveal significance this suggests that therespective contextual variable leads to changes inthe fundamental frequencies or durations within theconstituent unit types. Since the importance ofdegrading environmental effects increases with in-creasing transmission distance, we included theinteraction between average distance and averagevisibility as well as distance variation and visibilityvariation within combination types.

In the model to investigate the influence ofvisibility and nearest neighbor distance on thefundamental frequency we included as controlvariables: age-sex class since age- and sex-relatedmorphological variation is known to correlate withfrequency-related acoustic characteristics [e.g.,Ey et al., 2007], as well as activity because thebehavioral context is known to correlate with theacoustic structure of vocalizations [e.g., Hauser &Marler, 1993; Morton, 1977; Owren et al., 1997]. Wealso included the control variable group (western/mountain gorilla group) in order to control fordifferences in acoustic structure between the indi-viduals of the two groups, potentially due to differ-ences in body size [Bergmann, 1847; Ey et al., 2007;Taylor, 1997], social behavior [Gustison et al., 2012;Robbins, 2010; Salmi et al., 2013] or differenthabitat characteristics [Doran & McNeilage, 1998;

Fig. 1. Spectrograms illustrating typical examples of gorilla close calls, their syntactic structure, and classification according toprevious studies [Harcourt et al., 1993, Hedwig et al., 2014]. Close calls usually consist of one or a series of acoustic units separatedby periods of silence of at most two seconds (a, d). These units in turn often can be subdivided into subunits based on abrupt changesin the distribution of energy across frequencies (c). Based on temporal and frequency-related characteristics these units can beclassified into five unit types, which can be arranged into combinations, defined as unique sequences of unit types. Grunts andgrumbles usually consist of unit types of low fundamental frequency: atonal grunt a1, tonal grunt t2, or grumble t4 (a, b); humsconsist of unit types of high fundamental frequency: short hum t1 and long hum t3 (d), while mixed calls consist of unit types of bothhigh and low fundamental frequency (c) [Hedwig et al., 2014].

Am. J. Primatol.


Linsksens et al., 1976]. In addition to “caller”we alsoincluded “combination type” as a random effectsvariable into the model and random slopes for both(Table II). The model to investigate the influence ofvisibility and nearest neighbor distance on callduration was largely identical to the one we usedfor the mean fundamental frequency, but lacked thecontrol variable age-sex class (Table II). We excludedthis predictor because close call duration is unlikelyto be correlated with body size (e.g., Ey et al., 2007).

ImplementationModels were fitted using the functions “glmer”

(call rate) or “lmer” (fundamental frequency and callduration) provided by the lme4 package [Bates et al.,2013] in the statistical software environment R,version 3.0.2 [R Core Team, 2013]. To fulfil theassumptions of the Gaussian models (fundamentalfrequency and call duration) of normally distributedand homogeneous residuals, we visually inspectedhistograms of the quantitative predictors and re-sponses as well as QQ-plots of the residuals plottedagainst fitted values. In order to achieve theseassumptions being fulfilled we log-transformedmean fundamental frequency and square root trans-formed call duration, visibility and nearest neighbordistance. For the Poisson model investigating callingrate overdispersion was not an issue (dispersionparameter D¼1.19). For all models we tested forcollinearity among the predictor variables by calcu-lating Variance Inflation Factors [VIF, Field,2005] using the function “vif” of the R package“car” [Fox andWeisberg, 2011] in combination with astandard linear model excluding the random effects,interactions and day time squared (R function “lm”).A maximum VIF¼ 2.1 across all models and pre-dictors indicated that collinearity was not an issueand that calculated estimates reflect the indepen-dent effects of the predictors [Field, 2005].

To rule out significant effects of our test variablesdue to multiple testing, we first tested their overallsignificance by comparing the full model with allpredictor variables, to a null model only includingthe control variables and the random interceptsand slopes [Forstmeier & Schielzeth, 2011], usinga likelihood ratio test [Dobson, 2002] and the Rfunction “anova”. In case the interactions did notreveal significance, we excluded them to obtain easierinterpretable P-values for the respective main effects[Schielzeth, 2010].We derivedP-values for the effectsof thepredictors in theGaussianmodels by comparingthe full model including all predictor variables to areduced model without the predictor of interest usinglikelihood ratio tests [Barr et al., 2013; Dobson, 2002].

To check model stability we reran each modelwhile excluding subjects, as well as combinationtypes for the fundamental frequency and call dura-tionmodels, one at a time and compared the obtainedcoefficients with those derived from the model basedT

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Am. J. Primatol.


on all data. Differences between coefficients wereminimal for the calling rate model, so we concludedthat our data set contained no influential subjects.Regarding the fundamental frequency model wefound no indications for instabilities in the significanteffects of visibility and nearest neighbor distance.However, the effect of activity and age-sex class onthe fundamental frequency appeared to stronglydepend on which subjects and combination typeswere included into theanalysis.We found instabilitiesin the non-significant call duration model sincethe effect of themean visibility per combination types(bw.vis) strongly depended on which combinationtypes were included into the analysis.

Ethics StatementThis research complies with the American

Society of Primatologists principles for the ethicaltreatment of animals aswell as the ethical guidelinesof the Department of Primatology of the Max PlanckInstitute for Evolutionary Anthropology and wasconducted in accordance with the animal careregulations and national laws of Uganda, CentralAfrican Republic and Germany.

RESULTSCall Rate

Visibility and nearest neighbor distance had asignificant effect on calling rate (likelihood ratio test,x2¼14.09, df¼ 3, P¼0.003). More specifically, wefound a significant interaction between the effects ofvisibility and distance to the nearest neighbor on thecalling rate (Table IV). However, in contrast to thepredictions of the AAH, individuals appeared to callat the highest rates when visibility and nearestneighbor distance where both at large but also at lowvalues (Fig. 2).

Acoustic StructureVisibility and nearest neighbor distance had a

significant effect on themean fundamental frequencyof close calls (x2¼22.67, df¼ 6, P< 0.001), however,the effects were contrary to what we expectedaccording to the AAH. First, the average visibilityand distance of combination types (bw.vis and bw.dist) had a significant effect on the fundamentalfrequency of calls indicating that visibility andnearest neighbor distance lead to changes in theunit type composition of calls and hence the use ofdifferent combination types. After removal of themarginally non-significant interaction between aver-age visibility (bw.vis) and average distance percombination type (bw.dist) (estimate¼�0.102�SE0.095, P¼0.07), it appeared that combination typesconsistingof thehighpitchedunit types t1andt3were

more frequent when the nearest neighbor was far aswell as when visibility was low (Figs. 3, 4; Table V).Secondly, thevariationof visibilityanddistance to thenearest neighbor within combination types (w.dist.andw.vis) had a significant effect on the fundamentalfrequency, indicating that visibility and distance tothe nearest neighbor also affected the fundamentalfrequency of the unit types constituting their calls(TableV). In particular, the fundamental frequencyincreased both with decreasing visibility when thenearest neighbor was close and with increasing

TABLE IV. Summary of the GLMM for Effects onCalling Rate

Number of close calls per 5min

Estimate SE P-value

Intercept �2.010 0.153 d

Distance �0.177 0.063 a

Visibility 0.068 0.048 a

Distance�Visibility 0.105 0.039 0.007Activityb <0.001 0.065 0.997Groupc 0.883 0.250 <0.001Daytime 0.012 0.066 0.854Daytime2 0.033 0.066 0.612Autocorrelation term 0.298 0.016 <0.001

Distance, visibility and daytime were Z-transformed, “�” denotes interac-tion between predictors.aNot shown because of having no meaningful interpretation in thepresence of a significant interaction.b0¼ foraging, 1¼ resting.c0¼mountain gorilla; 1¼western gorilla.dNot shown because of having no meaningful interpretation.

Fig. 2. Influence of visibility and distance to the nearestneighbor on the number of close calls given per 5min. Thesurface represents the fitted values derived from the model. Theelevation of the circles represents the mean number of calls percell of the surface (filled circles depict mean values that exceedthe fitted values; open circles represent mean values that fallbelow the fitted values). The volume of the circles indicates thenumber of data points per cell. Note that the gorilla producedmost calls when both nearest neighbor distance and visibilitywere at large values, but also when the nearest neighbor andvisibility were both at low values.

Am. J. Primatol.


distance to the nearest neighbor when visibility washigh (Fig. 5). Moreover, the control predictoractivity appeared to explain variation in fundamen-tal frequency: when resting the gorillas used callswith lower fundamental frequency as compared toforaging (Table V). Finally, we found that westerngorilla close calls were of lower fundamentalfrequency compared to those of the mountain gorillaindividuals (Table V).

Overall, visibility and nearest neighbor distancehad no significant effect on call duration (x2¼7.263,df¼6, P¼ 0.297). However, the control predictoractivity appeared to explain variation in call

duration: when resting compared to foraging thegorillas used calls with shorter overall duration(Table VI).

DISCUSSIONContrary to what we predicted, we found no

modifications of calling rate, or the acoustic structureof gorilla close calls that could counteract degradingeffects of vegetation during sound propagation.Our results are therefore in contrast to a previousstudy demonstrating acoustic adaptations to envi-ronmental changes in baboon grunts [Ey et al., 2009].

Fig. 3. Effect of nearest neighbor distance on the variation in fundamental frequency between combination types. Combination typesgiven at higher nearest neighbor distances frequently included the unit types t1 and t3, which are of high fundamental frequency. Thepositions of the vertical lines along the x-axis indicate the average nearest neighbor distance per combination type. Horizontal linesindicate themedian fundamental frequency and boxes the quartiles. The lower and upper end of the vertical lines indicate the 2.5 and the97.5 percentile. The area of the boxes indicates the number of calls per combination type, and the dashed line indicates the fitted model.

Fig. 4. Effect of visibility on the variation in fundamental frequency between combination types. Combination types given at lowvisibility frequently included the unit types t1 and t3, which are of high fundamental frequency. The positions of the vertical lines alongthe x-axis indicate the average visibility per combination type. Horizontal lines indicate the median fundamental frequency and boxesthe quartiles. The lower and upper end of the vertical lines indicate the 2.5 and the 97.5 percentile. The area of the boxes indicates thenumber of calls per combination type, and the dashed line indicates the fitted model.

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Instead, the observed effects of nearest neighbordistance and visibility on calling rate and acousticstructure may reflect responses to variation inspatial and visual separation from the nearest

neighbor. Individuals appeared to increase theircalling rate when they were able to see their nearestneighbor being far away, but also when they wereunable to see their nearest neighbor being close-by.Moreover, the gorillas appeared to alter the unit typecomposition of their calls, and hence used differentcombination types, but also adjusted the acousticstructure of unit types constituting their calls inrelation to visibility and nearest neighbor distance.First, the gorillas were more likely to producecombinations consisting of unit types of highfundamental frequency, the short and long hum t1and t3, when they were far from their nearestneighbor andwhenvisibilitywas restricted.Secondly,within combination types, the fundamental frequencyappeared to increase when the animals were ableto see their nearest neighbor being far away, butalso when they could not see their nearest neighborclose by.

Similar modifications of vocal (and other) behav-ior in reaction to the proximity of other individualsare widespread among social vertebrate species[“audience effects”, Doutrelant et al., 2001; e.g.,Betta splendens: Pollick et al., 2005; Taeniopygiaguttata: Schel et al., 2013;Cebus paella: Vignal et al.,2004; Pan troglodytes: Zuberb€uhler, 2008] wherebymost previous studies demonstrated audience effectson calling rate [e.g., Pollick et al., 2005; Townsendand Zuberb€uhler, 2009]. However, similar to audi-ence effects on the vocal behavior of chimpanzees, our

TABLE V. Summary of the GLMM for Effects on theMean Fundamental Frequency of Gorilla Close Callsafter Removal of Non-Significant Interactions

Mean fundamental frequency

Estimate SE P-value

Intercept 4.096 0.124 d

Bw.dist 0.373 0.094 <0.001Bw.vis �0.209 0.070 <0.001W.dist 0.022 0.015 a

W.vis 0.002 0.020 a

W.dist�W.vis 0.035 0.013 0.024Age-sex class SB vs BB 0.038 0.079 0.001Age-sex class BB vs AF �0.088 0.056 <0.001Age-sex class SB vs AF �0.050 0.072 <0.001Activityb �0.005 0.022 <0.001Groupc �0.227 0.054 0.001Autocorrelation term 0.008 0.009 <0.001

Bw.dist and bw.vis are the average distance and visibility per combinationtype.W.dist and w.vis are the differences between each calls’ distance andvisibility and it’s combination type’s average distance and visibility.P-valueswere obtained using likelihood ratio tests.“�”Denotes interactionbetween predictors.aNot shown because of having no meaningful interpretation in thepresence of a significant interaction.b0¼ foraging, 1¼ resting.c0¼mountain gorilla; 1¼western gorilla.dnot shown because of having no meaningful interpretation.

Fig. 5. Influence of visibility and distance to the nearestneighbor on the fundamental frequency within combinationtypes. Visibility and distance are indicated as the divergence-from the mean visibility and distance at which a givencombination type was produced. The surface represents thefitted values obtained from themodel. The elevation of the circlesrepresents the mean fundamental frequency of calls per cell ofthe surface (filled circles depict mean values that exceed thefitted values; open circles represent mean values that fall belowthe fitted values). The volume of the circles indicates the numberof data points per cell. Note that the fundamental frequency waslowest when visibility was high and the nearest neighbor close tothe caller and increased both with decreasing visibility when thenearest neighbor was close and with increasing distance to thenearest neighbor when visibility was high.

TABLEVI. Resultsof theFinalModel investigatingtheEffects of Visibility and Nearest Neighbor Distance onthe Duration of Gorilla Close Calls after Removing theNon-Significant Interaction between Mean Visibility(bw.vis) and Mean Distance per Combination Type(bw.dist) (estimate¼0.07, SE¼0.055,P¼0.21) aswell asthe marginally Non-Significant Interaction betweenthe Variation of Visibility and Nearest NeighborDistance within Combination Types (w.vis and w.dist)(Estimate¼0.053, SE¼0.026, P¼0.052)

Call duration

Estimate SE P-value

Intercept 1.095 0.078 c

Bw.dist 0.027 0.057 0.840Bw.vis �0.034 0.042 <0.001W.dist �0.01 0.012 0.530W.vis 0.022 0.024 0.476Activitya �0.08 0.035 0.026Groupb 0.128 0.088 0.160Autocorrelation term 0.041 0.011 <0.001

The significant main effect of the average visibility per combination type(bw.vis) might be due to multiple testing given the non-significant full-null model comparison (Forstmeier and Schielzeth, 2011). P-values wereobtained using likelihood ratio tests.a0¼ foraging, 1¼ resting.b0¼mountain gorilla; 1¼western gorilla.cNot shown because of having no meaningful interpretation.

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results also suggest, first, an effect of the presence ofother group members on the acoustic structure ofvocalizations [Slocombe & Zuberb€uhler, 2007] and,secondly, that modifications of vocal behavior inrelation to the distance to the nearest neighbor wereconditional on what callers could see [Townsend &Zuberb€uhler, 2009].

As such, while pioneering studies on gorilla vocalbehavior highlighted the prominent role of close callsin mediating the interactions between individualswithin 5m of each other [e.g., Harcourt et al., 1986,1993], our results emphasize that spatial and visualseparation from other group members also have animportant influence on gorilla close calling behavior.Given that combinations including the higherpitched unit types t1 and t3 were particularly usedin situations of restricted visibility and increasedinter-individual distances, they may have somefunction in group coordination and maintaininggroup cohesion as proposed for some close calls byHarcourt et al. [1993]. This coordinative function ofclose calls was further suggested by an increasedcalling rate when individuals where able to see thattheir nearest neighbor was far away or unable to seetheir nearest neighbor close by. Our results suggestthat the observed increase in calling rate was drivenby the increased use of combinations containing highpitched unit types.While an increase in fundamentalfrequency may enhance signal detectability, since anincrease in fundamental frequency corresponds to anincrease of sound amplitude in a number of animalspecies [e.g., frogs: Cardoso & Atwell, 2011; dogs:Hsiao et al., 1994; humans: Li�enard & Di Benedetto,1999; birds: Lopez et al., 1988], changes in funda-mental frequency are indicative of the caller’s state ofarousal across many primate species, includinghumans [e.g., Fichtel et al., 2001; Fischer et al.,2004; Murray & Arnot, 1993; Rendall, 2003]. Hence,the observed increased use of combination typescomprising unit types of high fundamental frequencymay reflect increased arousal and as such involun-tary reactions in situations when group coordinationis crucial. Similar arousal based mechanisms appearto drive syntactic variation in a number of other non-human primates’ vocalizations, including the syn-tactic close call system of Diana monkeys Cercopi-thecus diana [Candiotti et al., 2012] or alarm callcombinations that are given in alleviated alarmsituations [Saguinus oedipus: Cleveland&Snowdon,1982; Cercopithecus diana: Ouattara et al., 2009;Zuberb€uhler, 2002].

The lack of evidence for modifications of theacoustic structure of calls and call rate that couldcounteract degrading effects of the vegetation in thisstudy is an important finding. An explanation couldbe that the gorilla close calls function sufficientlywithin their forest habitat given the relatively shortdistances they have to travel and their generallylow pitch. Previous studies that demonstrated

modifications in individual vocal behavior inrelation to environmental conditions [e.g., Ey et al.,2009] were conducted on baboon species whosegeographic as well as home ranges encompass avariety of habitat types from savanna-like grasslandto lowland rainforest [Kingdon, 1997]. Hence, ba-boons seem to be exposed to a larger spectrum ofdifferent transmission conditions than gorillas, whoreside entirely in forest habitats. This differencesuggests that a vocal plasticity functioning tocounteract distorting environmental effects mayonly be selected for in animal species living in highlyheterogeneous habitats.

However, our results point to some potentialdifferences in the vocal repertoire of western andmountain gorillas. Different habitats have specificfrequency windows in which calls can functionoptimally and acoustic masking of ambient soundis avoided [e.g., Linskens et al., 1976; Nemeth andBrumm, 2009; Snowdon & Hodun, 1981; Schneideret al., 2008; Waser & Brown, 1984]. In line with this,one could argue that the average higher fundamentalfrequency in calls we found for the mountain gorillacompared to the western gorilla group might reflectadaptations to such different sound windows, be-cause larger body size [Bergmann, 1847; but seeTaylor, 1997] and the overall denser vegetation in thehabitat of mountain gorillas [Nkurunungi et al.,2005] cannot explain their higher fundamentalfrequency compared to the western gorillas. Detailedmeasurements of ambient sound in the two groups’habitats would be necessary to explain the observeddifferences.

To conclude, our analysis revealed vocal plasticityin gorilla close calls in relation to changes in visibilityand nearest neighbor distance. However, the mod-ifications of acoustic structure, and calling rate wefound are unlikely to counteract degrading effects ofvegetation, but rather seem to reflect reactions tovariation in spatial and visual separation from othergroup members, similar to the audience effectsdemonstrated in a range of other species [e.g., Bettasplendens: Doutrelant et al., 2001; Taeniopygiaguttata: Pollick et al., 2005; Cebus paella: Schelet al., 2013; Pan troglodytes: Vignal et al., 2004]. Wehypothesize that habitat heterogeneity may be adriving force on the evolution of a vocal plasticityemployed for counteracting distorting environmentaleffects. Further studies similar to the one presentedhere and by Ey et al. [2009] would facilitate acomparative analysis to test this hypothesis.

ACKNOWLEDGMENTSWe thank theUgandaWildlife Authority and the

UgandaNational Council for Science andTechnologyfor permission to conduct our research in BwindiImpenetrable National Park and the Ministry ofEducation and Water and Forests of the government

Am. J. Primatol.


of CAR for permission to work in Dzanga-NdokiNational Park. We also thank the Institute ofTropical Forest Conservation in Uganda, as well asthe Dzanga-Sangha Project in CAR, for logisticalsupport. We are grateful for useful comments on themanuscript by two anonymous reviewers. Specialthanks go to the local Ba’Aka trackers of the PrimateHabituation Program at Bai Hokou camp, Dzanga-Ndoki NP, and all ITFC field assistants for theirirreplaceable help, great humor, and courage. Thisresearch was financially supported by the LeakeyFoundation and the Max Planck Society.

REFERENCESAltmann J. 1974. Observational study of behavior: sampling

methods. Behaviour 49:227–267.Baayen RH, Davidson DJ, Bates DM. 2008. Mixed-effects

modelling with crossed random effects for subjects anditems. Journal of Memory and Language 59:390–412.

Barr DJ, Levy R, Scheepers C, Tily HJ. 2013. Random effectsstructure for confirmatory hypothesis testing: keep itmaximal. Journal of Memory and Language 68:255–278.

Bates D, Maechler M, Bolker B, Walker S. 2013. Lme4: linearmixed-effects models using Eigen and S4. R package version1 0–4.

Bayart F, Hayashi KT, Faull KF, Barchas JD, Levine S. 1990.Influence of maternal proximity on behavioral and physio-logical responses to separation in infant rhesus monkeys.Behavioral Neuroscience 104:98–107.

BergmannC. 1847. €Uber die Verh€altnisse derW€arme€okonomieder Thiere zu ihrer Gr€osse. G€ottinger Studien 3:595–708.

Bermejo M. 1999. Status and conservation of primates inOdzala National Park, Republic of Congo. Oryx 33:323–331.

Boinski S. 1993. Vocal coordination of troop movement amongwhite-faced capuchinmonkeysCebus capuchinus. AmericanJournal of Primatology 30:85–100.

Boinski S, Campbell AF. 1996. The huh vocalization of white-faced capuchins: a spacing call disguised as a food call?Ethology 102:826–840.

Bolker BM, Brooks ME, Clark CJ, et al. 2009. Generalizedlinear mixed models: a practical guide for ecologyand evolution. Trends in Ecology and Evolution 24:127–135.

Bouchet H, Blois-Heulin C, Pellier A, Zuberb€uhler K,Lemasson A. 2012. Acoustic variability and individualdistinctiveness in the vocal repertoire of red-cappedmangabeys (Cercocebus torquatus). Journal of ComparativePsychology 126:45–56.

Bradbury JW, Vehrencamp SL. 2011. Principles of animalcommunication. Sunderland MA: Sinauer Associates.

Candiotti A, Zuberb€uhler K, Lemasson A. 2012. Context-related call combinations in female Diana monkeys. AnimalCognition 15:327–339.

Cardoso GC, Atwell JW. 2011. On the relation betweenloudness and the increased song frequency of urban birds.Animal Behaviour 82:831–836.

Cheney DL, Seyfarth RM, Silk JB. 1995. The role of grunts inreconciling opponents and facilitating interactions amongadult female baboons. Animal Behaviour 50:249–257.

Cleveland J, Snowdon CT. 1982. The complex vocal repertoireof the adult cotton-top tamarin (Saguinus oedipus oedipus).Ethology 58:231–270.

DobsonAJ. 2002. An introduction to generalized linearmodels.Baton Rouge: CRC Press.

Doran D, McNeilage A. 1998. Gorilla ecology and behavior.Evolutionary Anthropology 6:120–131.

Doutrelant C,McGregor PK,Oliveira RF. 2001. The effect of anaudience on intrasexual communication in male Siamesefighting fish, Betta splendens. Behavioural Ecology12:283–286.

Elowson AM, Snowdon CT. 1994. Pygmy marmosets, Cebuellapygmaea, modify vocal structure in response to changedsocial environment. Animal Behaviour 47:1267–1277.

Ey E, Pfefferle D, Fischer J. 2007. Do age- and sex-relatedvariations reliably reflect body size in non-human primatevocalizations? A review. Primates 48:253–267.

Ey E, Rahn C, Hammerschmidt K, Fischer J. 2009. Wildfemale olive baboons adapt their grunt vocalizations toenvironmental conditions. Ethology 115:493–503.

Ey E, Fischer J. 2009. The ’acoustic adaptation hypothesis’-areview of the evidence from birds, anurans and mammals.Bioacoustics 19:21–48.

Fichtel C, Hammerschmidt K, Jurgens UWE. 2001. On thevocal expression of emotion. A multi-parametric analysis ofdifferent states of aversion in the squirrel monkey. Behav-iour 138:97–116.

Field AP. 2005. Discovering statistics using SPSS. London:SAGE.

Fischer J, Kitchen DM, Seyfarth RM, Cheney DL. 2004.Baboon loud calls advertise male quality: acoustic featuresand their relation to rank, age, and exhaustion. BehavioralEcology and Sociobiology 56:140–148.

Forstmeier W, Schielzeth H. 2011. Cryptic multiple hypothe-ses testing in linear models: overestimated effect sizes andthe winner’s curse. Behavioural Ecology and Sociobiology65:47- 55.

Fossey D. 1972. Vocalizations of the mountain gorilla (Gorillagorilla beringei). Animal Behaviour 20:36–53.

Fox FJ, Weisberg S. 2011. An {R} Companion to appliedregression, second edition. Thousand Oaks CA: Sage.

Gustison ML, le Roux A, Bergman TJ. 2012. Derived vocal-izations of geladas (Theropithecus gelada) and the evolutionof vocal complexity in primates. Philosophical Transactionsof the Royal Society B67:1847–1859.

HammerschmidtK. 1990. Individuelle Lautmuster bei Berber-affen (Macaca sylvanus): Ein Ansatz zum Verst€andnis ihrervokalen Kommunikation. Freie Universit€at Berlin:Dissertation.

Harcourt AH, Stewart KJ. 1996. Function andmeaning of wildgorilla ’close’ calls 2. Correlations with rank and related-ness. Behaviour 133:827–845.

Harcourt AH, Stewart KJ. 2001. Vocal relationships of wildmountain gorillas. In: Robbins MM, Sicotte Stewart PKJ,editors. Mountain Gorillas. Three decades of research atkarisoke. London: Cambridge University Press. p 241–262.

Harcourt AH, Stewart KJ, Harcourt DE. 1986. Vocalizationsand social relationships of wild gorillas: A preliminaryanalysis. In: Taub DM, King FA, editors. Current perspec-tives in primate social dynamics. Co. New York: VanNostrand Reinhold. p 346–356.

Harcourt AH, Stewart KJ, Hauser M. 1993. Functions of wildgorilla close calls. I. Repertoire, context, and interspecificcomparison. Behaviour 124:89–122.

Hauser MD, Marler P. 1993. Food-associated calls in rhesusmacaques (Macaca mulatta): I. socioecological factors.Behavioural Ecology 4:194–205.

Hedwig D, Hammerschmidt K,Mundry R, et al. 2014. Acousticstructure and variation in mountain and western gorillaclose calls: a syntactic approach. Behaviour 151:1091–1120.

Hedwig D, Mundry R, Robbins MM, Boesch C. 2015.Contextual correlates of syntactic variation in mountainandwestern gorilla close-distance vocalizations: Indicationsfor lexical or phonological syntax? Animal Cognition18:423–435.

Hsiao TY, Solomon NP, Luschei ES, et al. 1994. Effect ofsubglottic pressure on fundamental frequency of the canine

Am. J. Primatol.


larynx with active muscle tensions. Annals of Otology,Rhinology, and Laryngology 103:817–821.

Jaeger TF. 2008. Categorical data analysis: Away fromANOVAs (transformation or not) and towards logit mixedmodels. Journal of Memory and Language. 59:434–446.

Kingdon J. 1997. TheKingdon field guide to Africanmammals.London: Academic Press.

Klump GM, Maier EH. 1990. Temporal summation in theEuropean starling (Sturnus vulgaris). Journal of Compara-tive Psychology 104:94–100.

Laird NM, Ware JH. 1982. Random-Effects Models forLongitudinal Data. Biometrics 38:963–974.

Lemasson A, Hausberger M. 2011. Acoustic variability andsocial significance of calls in female Campbell’s monkeys(Cercopithecus campbelli campbelli). Journal of the Acous-tical Society of America 129:3341–3352.

Li�enard JS, Di Benedetto MG. 1999. Effect of vocal effort onspectral properties of vowels. Journal of the AcousticalSociety of America 106:411–422.

Linskens HF, Martens MJM, Hendriksen HJGM, et al. 1976.The acoustic climate of plant communities. Oecologia23:165–177.

Lopez PT,Narins PM,Lewis ER,Moore SW. 1988. Acousticallyinduced call modification in the white-lipped frog Lepto-dactylus albilabris. Animal Behaviour 36:1295–1308.

Masi S, Cipolletta C, Robbins MM. 2009. Western lowlandgorillas (Gorilla gorilla gorilla) change their activitypatterns in response to frugivory. American Journal ofPrimatology 71:91–100.

Morton ES. 1975. Ecological sources of selection on aviansounds. American Naturalist 109:17–34.

Morton ES. 1977. On the occurrence and significance ofmotivation-structural rules in some bird and mammalsounds. American Naturalist 111:855–869.

Murray IR, Arnot JL. 1993. Toward the simulation of emotionin synthetic speech: a review of the literature on humanvocal emotion. Journal of the Acoustical Society of America93:1097–1108.

Nemeth E, Dabelsteen T, Pedersen SB, Winkler H. 2006.Rainforests as concert halls for birds: are reverberationsimproving sound transmission of long song elements?Journal of the Acoustical Society of America 119:620–626.

Nemeth E, Brumm H. 2009. Blackbirds sing higher-pitchedsongs in cities: adaptation to habitat acoustics or side-effectof urbanization? Animal Behaviour 78:637–641.

Nkurunungi JB, Ganas J, Robbins MM, Stanford CB. 2005.A comparison of two mountain gorilla habitats in BwindiImpenetrable National Park, Uganda. African Journal ofEcology 42:289–297.

Ouattara K, Lemasson A, Zuberb€uhler K. 2009. Campbell’smonkeys use affixation to alter call meaning. PLoS ONE 4:e7808.

Owren MJ, Seyfarth RM, Cheney DL. 1997. The acousticfeatures of vowel-like grunt calls in chacma baboons (Papiocynocephalus ursinus): implications for production process-es and functions. Journal of the Acoustical Society ofAmerica 101:2951–2963.

Pollick AS, Gouzoules H, deWaal FBM. 2005. Audience effectson food calls in captive brown capuchin monkeys, Cebuspaella. Animal Behaviour 70:1273–1281.

R Core Development Team. 2013. R: a language and environ-ment for statistical computing. Vienna, Austria: R Founda-tion for Statistical Computing.

Radford AN, Ridley AR. 2008. Close calling regulates spacingbetween foraging competitors in the group living piedbabbler. Animal Behaviour 75:519–527.

Rendall D, Seyfarth RM, Cheney DL, Owren MJ. 1999. Themeaning and function of grunt variants in baboons. AnimalBehaviour 57:583–592.

Rendall D. 2003. Acoustic correlates of caller identity andaffect intensity in the vowel-like grunt vocalizations of

baboons. Journal of the Acoustical Society of America113:3390–3402.

Robbins MM. 2008. Feeding competition and agonisticrelationships among Bwindi Gorilla beringei. InternationalJournal of Primatology 29:999–1018.

RobbinsMM. 2010. Gorillas: diversity in ecology and behavior.In: Campbell CJ, Fuentes A, MacKinnon KC, Bearder S,Stumpf R, editors. Primates in perspective. Oxford: OxfordUniversity Press. p 326–339.

Salmi R, Hammerschmidt K, Doran-Sheehy DM. 2013.Western gorilla vocal repertoire and contextual use ofvocalizations. Ethology 119:831–847.

Schaller GB. 1963. The mountain gorilla. Chicago: Universityof Chicago Press, Chicago.

Schel AM, Machanda Z, Townsend SW, Zuberb€uhler K,Slocombe KE. 2013. Chimpanzee food calls are directed atspecific individuals. Animal Behaviour 86:955–965.

Schielzeth H, Forstmeier W. 2009. Conclusions beyondsupport: overconfident estimates in mixed models. Behav-ioural Ecology 20:416–420.

Schielzeth H. 2010. Simple means to improve the interpret-ability of regression coefficients. Methods in Ecology andEvolution 1:103- 113.

Schneider C, Hodges K, Fischer J, Hammerschmidt K. 2008.Acoustic Niches of Siberut Primates. International Journalof Primatology 29:601–613.

Schrader L, Hammerschmidt K. 1997. Computer-aided analy-sis of acoustic parameters in animal vocalizations: a multi-parametric approach. Bioacoustics 7:247–265.

Seyfarth RM, Cheney DL, Harcourt AH, Stewart KJ. 1994.The acoustic features of gorilla double grunts and theirrelation to behavior. American Journal of Primatology33:31–50.

Slocombe KE, Zuberb€uhler K. 2007. Chimpanzees modifyrecruitment screams as a function of audience composition.Proceedings of the National Academy of Science 104:17228–17233.

Snowdon CT, Hodun A. 1981. Acoustic adaptation in pygmymarmoset contact calls. Locational cues vary with distancesbetween conspecifics. Behavioural Ecology and Sociobiology9:295–300.

Snowdon CT. 1997. Affiliative processes and vocal develop-ment. Annals of the NewYork Academy of Sciences807:340–351.

Stewart KJ, Harcourt AH. 1994. Gorillas’ vocalizations duringrest periods: signals of impending departure?. Behaviour130:29–40.

Silk JB, Kaldor E, Boyd R. 2000. Cheap talk when interestsconflict. Animal Behaviour 59:423–432.

Sugiura H. 2007. Effects of proximity and behavioralcontext on acoustic variation in the coo calls of Japanesemacaques. American Journal of Primatology 69:1412–1424.

Taylor AB. 1997. Relative growth, ontogeny, and sexualdimorphism in gorilla (Gorilla gorilla gorilla and G. g.beringei): evolutionary and ecological considerations. Amer-ican Journal of Primatology 43:1–31.

Townsend S, Zuberb€uhler K. 2009. Audience effects inchimpanzee copulation calls. Communicative and Integra-tive Biology 2:155–157.

Townsend SW, Holl�en LI, Manser MB. 2010. Meerkat closecalls encode group-specific signatures, but receivers fail todiscriminate. Animal Behaviour 80:133–138.

Townsend SW, Z€ottl M, Manser MB. 2011. All clear?Meerkats attend to contextual information in close calls tocoordinate vigilance. Behavioral Ecology and Sociobiology65:1927–1934.

Tutin CEG, Fernandez M. 1984. Nationwide census of gorilla(Gorillag. gorilla) and chimpanzee (Pan t. troglodytes)populations in Gabon. American Journal of Primatology6:313–336.

Am. J. Primatol.


Waser PM, Brown CH. 1984. Is there a “sound window” forprimate communication? Behavioural Ecology Sociobiology15:73–76.

Waser PM, Brown CH. 1986. Habitat acoustics andprimate communication. American Journal of Primatology10:135–154.

Wiener FM, Keast DN. 1959. Experimental study of thepropagation of sound over ground. Journal of the AcousticalSociety of America 31:724–733.

Whitham JC, Gerald MS, Maestripieri D. 2007. IntendedReceivers and Functional Significance of Grunt and GirneyVocalizations in Free-Ranging Female Rhesus Macaques.Ethology 113:862–874.

van de PolM,Wright J. 2009. A simplemethod for distinguish-ing within-versus between-subject effects using mixedmodels. Animal Behaviour 77:753–758.

Vignal C, Mathevon N, Mottin S. 2004. Audience drives malesongbird response to partner’s voice. Nature 430:448–451.

Yamagiwa J, Basabose AK. 2006. Diet and seasonal changes insympatric gorillas and chimpanzees at Kahuzi-BiegaNational Park. Primates 47:74–90.

Zuberb€uhler K. 2002. A syntactic rule in forest monkeycommunication. Animal Behaviour 63:293–299.

Zuberb€uhler K. 2008. Audience effects. Current Biology 18:189–190

Supporting InformationAdditional supporting information may be found inthe online version of this article at the publisher’sweb-site.

Am. J. Primatol.


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