RESEARCH ARTICLE

Determinants of Daily Path Length in Black and Gold Howler Monkeys(Alouatta caraya) in Northeastern Argentina

MARIANA RA ~NO1*, MARTIN M. KOWALEWSKI1, ALEXIS M. CEREZO2, AND PAUL A. GARBER3

1Estaci�on Biol�ogica de Usos M�ultiples de Corrientes (EBCo), Museo Argentino de Ciencias Naturales-CONICET,Corrientes, Argentina2Facultad de Agronom�ıa, Departamento de M�etodos Cuantitativos y Sistemas de Informaci�on, Universidad de BuenosAires, Buenos Aires, Argentina3Department of Anthropology, University of Illinois Urbana-Champaign, Urbana, Illinois

Models used to explain the social organization of primates suggest that variation in daily path length(DPL) is a response to variation in resource distribution and the intensity of intragroup feedingcompetition. However, daily path length may be affected by a number of other factors including theavailability anddistributionof nutritionally complementary food items, temperaturewhich can influenceactivity budget, patterns of subgrouping, and the frequencyand function of intergroup encounters. In this6-month study (total 495hr of quantitative data), we examined daily path lengths in two neighboringgroups of black and gold howlermonkeys (Alouatta caraya) inhabiting a semi-deciduous gallery forest inSanCayetano (27° 300S, 58° 410W), in thenorthwest province ofCorrientes, Argentina. Both study groupswere of similar size and composition. We identified relationships across groups between time spentfeeding on fruits, leaves, and flowers, the number of trees visited, group spread, frequency of intergroupencounters,meandaily temperature, andDPL.Our results suggest that variation in foodavailability hada significant impact on howler ranging behavior by increasing DPL under conditions of high immatureand mature fruit availability, and by decreasing DPL with increased availability and increased timeinvested in feeding onmature leaves. These results do not support the contention that a reduction in foodavailability or an increase in within-group feeding competition increased DPL in black and gold howlermonkeys. DPL in black and gold howlers is influenced by several interrelated factors. In this regard wesuggest that models of socio-ecology and ecological constraints need to reconsider how factors such asindividual nutritional requirements, social tolerance and group cohesion, and the spatial and temporalavailability of preferred and nearby food resources influence primate ranging behavior. Am. J. Primatol.78:825–837, 2016. © 2016 Wiley Periodicals, Inc.

Key words: Alouatta caraya; black and gold howler monkey; daily path lengths; use of space;Argentina

INTRODUCTIONDaily path length (DPL), or the linear distance

traveled during a single day, is commonly used as ameasure of a primate’s use of space, and the costs intime and energy of defending a territory andobtaining access to resources [Arrowood et al.,2003; Chapman & Chapman, 2000; Chapmanet al., 1995; Clutton-Brock & Janson, 2012; Majoloet al., 2008;Milton, 1980; Pollard&Blumstein, 2008;Strier, 2000]. In this regard, models of primatesocioecology predict that, in response to increasedfeeding competition associated with an increase ingroup size and/or a decrease in food availability,groups and their constituent members should oftentravel greater distances per day to encountersufficient resources. As further or alternative waysof mitigating the costs of intragroup feeding

competition, animalsmay also increase group spreador break into smaller subgroups that travel andforage independently [Chapman & Chapman, 2000;

Contract grant sponsor: The Cleveland Zoological Society;contract grant sponsor: Cleveland Metroparks Zoo;contract grant sponsor: PIP IU 355/CONICET-Argentina

�Correspondence to: Mariana Ra~no, Estaci�on Biol�ogicaCorrientes-Museo Argentino de Ciencias Naturales, RutaPvcial. 8 Km 7 s/n, 3401 Corrientes, Buenos Aires, Argentina.E-mail: marianarano@gmail.com

Received 4 May 2015; revised 9 March 2016; revision accepted12 March 2016

DOI: 10.1002/ajp.22548Published online 4 April 2016 in Wiley Online Library(wileyonlinelibrary.com).

American Journal of Primatology 78:825–837 (2016)

© 2016 Wiley Periodicals, Inc.

Clutton-Brock & Harvey, 1977; Clutton-Brock &Janson, 2012; Gillespie & Chapman, 2001; Isbell,1991; Janson & Goldsmith, 1995; Snaith &Chapman, 2008].

However, there exists a growing body of evidencein several primate species, that group size is not astrong predictor of DPL [Arrowood et al., 2003;Chhangani & Mohnot, 2006; Chapman & Valenta,2015; Fan et al., 2014; Gillespie & Chapman, 2001;Isbell, 1991; Sussman &Garber, 2011; Struhsaker &Leland, 1987], and that other factors such as dietaryselectivity, intergroup interactions in response tomate and resource defense, predation and infanticiderisk, and extra-group mating opportunities play amore prominent role in determining rangingpatterns and DPL [Cowlishaw, 1997; Peres, 2000;Willems & Hill, 2009]. For example, in the case ofwestern lowland gorillas (Gorilla gorilla gorilla),Doran-Sheehy et al. [2004] reported that DPL waspositively correlated with the availability of fruits inthe group’s home range (fruit productivity explained36% of variation in DPL in a multiple regressionanalysis). In a related study of the same species,Cipolletta [2004] found that the average monthlyDPL was positively correlated with the percentage offruit in gorilla fecal samples (rs¼ 0.71, P< 0.05)(during this period DPL wet season—fruits: 1,595m,n¼177, SD¼642; dry season—no fruits: 1,326m,n¼149, SD¼432). Similarly, using a multipleregression model to predict ranging patterns,Stevenson [2006] identified a positive relationshipbetween DPL and both group size and fruit produc-tion in woolly monkeys (Lagothrix lagothricha).However, in a different population of woollymonkeys, Di Fiore [2003] found a nonsignificantrelationship between (ripe) fruit production andDPL(i.e., DPL was not predicted by ripe fruit production,although in that study, ripe fruit consumption waspredicted by ripe fruit availability). In contrast, DPLdecreased with increased time spent fruit feeding incrested black macaques (Macaca nigra) [O’Brien &Kinnaird, 1997], and in the case of Eastern black andwhite colobus monkeys (Colobus guereza), Fashing[2001] reported thatDPLwas neither correlatedwithgroup size nor with time spent feeding on anyparticular food type.

Howler monkeys offer an instructive model forstudying the relationships between daily pathlength, diet, changes in food availability, groupcohesion, changes in food availability, andsocioecology in nonhuman primates. Howlers arefound to exploit a range of forest types includinghighly seasonal habitats and those severely modifiedby anthropogenic disturbance, and consume a dietprincipally composed of fruits, leaves, and flowers[Garber et al., 2015]. In addition, average group sizewithin a species tends to varyminimally (6–18 exceptfor Alouatta palliata). Groups generally contain only2–4 adult females and 2–4 adult males and therefore

the potential effects of group size on feeding ecologyare minimized [Di Fiore et al., 2011]. In all howlerspecies intergroup encounters associated withhowling bouts and collective action involving severalmales and in some cases females are common, andare reported to influence ranging patterns, groupmovement, and within-group social bonds [Garber &Kowalewksi, 2011; Kitchen, 2004; Kowalewski &Garber, 2010, 2015; van Schaik & Janson, 2000].

Knopff&Pavelka [2006] studied the relationshipbetween group size and two proxies of feedingcompetition—DPL and activity budget in threegroups of black howler monkeys (Alouatta pigra) inBelize. After controlling for food availability, homerange area, and group size, they found no significantdifferences in DPL or time spent feeding, foraging,traveling, or resting. Similarly, in a study of fourgroups of black howlers at another site in Belize,Arrowood et al. [2003] reported that group size hadno effect on DPL, and that the strongest predictors ofincreasing DPL were increased group dispersion andincreased time spent feeding on leaves. In contrast,in an 8 month study of two similar sized groups ofAlouatta caraya on islands of continuously floodedforests in Northern Argentina, Bravo & Sallenave[2003] found that DPL was positively related tothe frequency of intergroup encounters although thenumber of encounters was low during their 8 monthstudy (n¼ 14 encounters). In this later study,however, the degree to which changes in foodavailability or female reproductive condition affectedthe frequency or location of intergroup encounterswas not evaluated [Brown, 2013]. At this same site,Kowalewski [2007] conducted a 12 month study oftwo howler groups and reported that the bestpredictor of DPL was daily maximum temperature.Individuals in this study traveled greater distanceson days in which temperatures exceeded 30°C,although during this same period the howlers werefound to increase both time spent fruit eating andthe number of different species of fruit consumed.Finally, although well documented cases ofinfanticide in howler monkeys are limited, it ispossible that patterns of range use and DPL areinfluenced by the presence or proximity of lone adultmales attempting to takeover a group. Thus, severalfactors may contribute to intra-annual variation inDPL in howlers.

In thepresent study,weexaminedfactorsaffectingDPL in two neighboring groups of black and goldhowler monkeys that were similar in group size andcomposition, and the effects that seasonal changes infood availability and distribution had on feedingcompetition and ranging behavior. Our goals were asfollows: (i) to calculate each group’s DPL during thespring (3 months) and summer (3 months). Acomparison across this 6-month period enabled us tominimize the effects of day length on seasonal changesinactivitybudgetandDPL(day lengthat our studysite

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varies from 14hr in summer to 10hr in winter) and (ii)to examine how variation in diet, patch size anddistribution, frequency of intergroup encounters, andmean daily temperature affected DPL. We predictedthat: (P1) DPL will increase as the time spent feedingon discontinuous or scattered food patches increases,andDPLwill decrease as the time spent feeding in foodpatches that exhibit a uniform or clumped distributionincreases; (P2) DPL will increase as the availability ofdiscontinuous or scattered food patches increases, andDPL will decrease as the availability of continuous orclumped food patches decreases; (P3) when exploitingfood resources distributed within the crown of a singletree, group spread in howlers is expected to decreaseand aggression over food increase, whereas whenexploiting resources distributed across the crowns ofseveral neighboring trees, group spread is expected toincrease and opportunities for feeding competition areexpected to decrease; (P4) on days in which groupsengage in intergroup encounters in response to thehowling of neighboring groups, DPL is expected toincrease as individuals travel to the borders of theirhome range; and (P5) under conditions of high daytimetemperatures (heat stress), howlers are expected toincrease time spent resting and decrease DPL as anenergy conservation strategy.

METHODSStudy Area and Subjects

We conducted this study in a semi-deciduousgallery forest in San Cayetano (27° 300S, 58° 410W),located in the basin of the Riachuelo River, in the

northwestern part of the province of Corrientes,Argentina (Fig. 1). The study area has 24 identifiedforest fragments that contain black and gold howlermonkeys. Fragment size averages 9.24 ha, SD¼ 7.62(N¼24 fragments), ranging in area from 1.4 to29.3 ha. The average distance between fragments is1,763.1m, SD¼538.7 (N¼11 fragments) [Oklanderet al., 2010]. The average annual temperature is21.7°C. During this study the average dailytemperature was 22.7°C (range 17.4–29.4°C). Thelowest daytime temperature recorded was 6.9°C inSeptember (minimum temperature average17.4� 4.4°C) and the maximum temperature was35°C in December (maximum temperature average29.4� 5.3°C). Rainfall is approximately 1.230mmper year [Zunino et al., 2007]. Daily rainfall andtemperature were obtained from the NationalWeather Service at the Aero Corrientes station,which is located 17kmN of the study site. We presentdata obtained from two fully habituated groups ofblack and gold howler monkeys (Ar and Ta groups).Home range overlap between these two groups wasapproximately 42%. In addition, the home range ofAr overlapped approximately 25% with that ofneighboring group Ali. The home range of Taoverlapped approximately 50% with neighboringgroups Ali and Le. Overall, approximately 90% ofTa’s home range overlapped with the home ranges ofother howler groups.

Individuals in our study groups were recognizedby differences in body size, pelage coloration, scars,and artificial marks (ear tags and colored anklets)placed on the howlers during a program of trappingand marking, which was part of a previous study

Fig. 1. Location of our study groups relative to EBCo (Biological Field Station Corrientes), the relativeposition of the forest fragmentsand the 20�20m2 quadrats that the study groups used during this study(Ar: quadrats used only by group Ar, Ta: quadrats used only byTa, and Ar/Ta: quadrats used by the twogroups).

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conducted at this field site. The age and sexcomposition of each groupwere determined followingthe classification of Rumiz [1990]. Group Ar (fiveindividuals) was composed of one adult male, onesubadult male, one adult female, one juvenile male,and one infant male. Group Ta (six individuals) wascomposed of one adult male, one subadult male, twoadult females, one juvenile female, and one infantfemale.

The two study groups were followed from sunriseto sunset for three complete consecutive days permonth, from September 2007 to February 2008,completing a total of 463hr of observations (230hr ofAr and 233hr of Ta). Spring (September–November)and summer (December–February) data collectionensured the inclusion of two seasons that differedsignificantly in the availability of fruits, flowers, newleaves, mature leaves, and buds. Each group wasfollowed for between 13 and 14hr/day. Behavioraldata collection began when group members awoke intheir sleeping tree in the early morning and endedwhen the monkeys entered a sleeping tree in theearly evening, adopted their sleeping positions, andthe following morning the group was found at thesame tree.

Ecological Data, Phenology and Analysis ofSeasonality of Resources

An area of approximately 10ha, located in part ofthe forest that overlapped the home ranges of bothstudy groups was selected for vegetation analysis(home range Ta¼ 6ha, home range Ar¼5ha). Thisarea was subdivided into quadrats of 20�20m2 (110of these quadrats were located in the home range ofAr and 170 were located in the home range of Ta),with 80 quadrats located in the area of home rangeoverlap between the two study groups. Within thisarea a total of 3,015 treesweremapped and identifiedwith numbered plates. In each 20� 20m2 quadrat,we collected data on each tree, shrub, and vine with adiameter at breast height (DBH) �10 cm, thescientific name, DBH, maximum height (estimatedusing a clinometer), diameter and height of thecrown, crown volume (calculated depending on crownshape using the geometric formulae for sphere, cone,quadrat, cylinder, hemisphere), and its preciselocation within the quadrat (each quadrat wassubdivided into 16¼5�5m2 subquadrats toconstruct an accurate map of tree distributions).Based on these data, we calculated several ecologicalindices to characterize the habitat including treespecies density (calculated as number of individualsof one species/unit area), frequency of that specieswithin the group’s home range, basal area ordominance (calculated as area at DBH/unit area),and importance value index (IVI, calculated as sumof relative density, relative dominance and relativefrequency). The importance value index (IVI) varies

form 0 to 100 with 0 indicating the least commonspecies in the forest used by each study group and100 indicating the most common plant species in theforest used by each study group [Dallmeier, 1992].We also estimated the availability and seasonality ofresources including ripe fruits, unripe fruits, youngleaves, mature leaves, and flowers once permonth bycalculating phenological scores for plant speciesidentified as food items in the diet of each groupduring the study. Each month, we monitored tentrees from each of the 25 plant species fed in byhowlers for the presence and abundance of fruit, leaf,flower, and shoot phenophases. Each crown wassubdivided into four parts, and the abundance of eachphenophase (flowers, new and mature leaves, fruits)was ranked on a relative scale of 0–4, where 0 is theabsence of that phenophase and 4 is when the crownis 100% in that phenophase (0¼0%, 1¼25%,2¼ 50%, 3¼ 75%). The phenological values of theindividuals of each species were averaged to obtain aPhenological Index for that Species (PISp) for eachmonth and for each phenophase. This value wasweighted to calculate an index of abundance usingBasal area (area of the tree at DBH/area unit) of thetrees to determine seasonal variation of eachphenophase (availability) [Kowalewski, 2007;Zunino, 1989]. An index of relative abundance(RAph index) was calculated for each plant speciesand phenophase per month. We estimated RAphusing the formula: RAph¼S(PIsp�BAsp), whereBAsp¼ basal area of species i/total basal area� 100.The RAph index was used to calculate the monthlyvariation in resource availability and seasonaldifferences in the availability of fruits, flowers, andleaves of individual plant species [Placci, 1995].Given the amount of home range overlap acrossgroups, these data were pooled in all analyses.

Definition and Distribution of Food PatchesIn this study, we consider a food patch as one or

more interdigitated tree crowns that offer similar fooditems such as fruits, flowers, or leaves that was visitedby the howlers during a feeding session. A food patch isthen a unit of food type (fruits, flowers, or leaves)without considering the species of food consumed. Afeeding session was considered a period of the dayduring which feeding was the predominant activity ofall group members. Feeding sessions ranged induration from 20 to 80min (Group Ta 45� 17min,Group Ar 47�17min). During this study, howlergroupsaveraged four feeding sessionsperdayandeachfeeding session concentrated principally on a singletype of food item, either fruits (including mature andimmature), flowers, or leaves (including mature, andimmature leaves, and shoots). We analyzed thedistribution of these patches within the howler homeranges using several indices of dispersion. To assesspatch distributionwe calculated an Index of dispersion

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(ID) of fruit, flower, and leaf patches as the ratiobetween the mean number of patches and its variancefor each quadrat. An ID >1 indicates a clumped patchdistribution, an ID<1 indicates a uniform distributionand an ID¼1 indicates a random distribution. Thefrequency distribution for each food patch type wascompared to a Poisson distribution and tested forsignificanceusingaStudent’s, t-test (using the formulat¼│s2/�1│/√2/(n�1)). We also calculated Morisita’sID (MID) to assess patch dispersion. A MID¼ 1indicates a random distribution, a MID >1 indicatesa clumped distribution, and a MID <1 indicates auniform distribution. To test for a significant deviationfrom 1 (random), a chi-square test was used.

Behavioral DataEvery 10min, we recorded a 2min scan sample

[Altmann, 1974], in which we scored for each groupmember his or her vertical height in the canopy(measured using a clinometer), location (quadratwithin the home range), tree/food patch ID, andactivity (travel, movement within the crown of a treeor between the crowns of trees whose immediate goalin not to consume a food item or to interact sociallywith a conspecific; rest, a period of inactivity lastingat least 60 sec; feed, when an individual wasmanipulating or ingesting a food item or drinkingwater from a site located in a tree or small stream;and social interactions, which include play, groom-ing, displacement, fighting, chasing, threatening, orhowling). During each scan sample, we recorded theidentity and distance of the nearest neighbor in sucha way that we could construct a “map” of the positionif each individual in the group. We calculated groupspread with this “map” every 10min, which wasdefined as the area of a circle (pr2) with a radius (r)that was estimated as the distance between thefarthest individual to the imaginary center positionof the group. In addition, during each observationminute we identified the location of the tree in whichmost of the group was located (more than 50% of thegroup) and plotted that tree on amap of the field site.If individuals were spread out such that notree contained more than 50% of the group weidentified a point as the estimated center location toall group members and plotted that point onto thefieldmap. DPLwas calculated directly bymeasuring,with a meter tape, the horizontal straight-linedistance (trunk to trunk at breast height) betweensequentially visited trees. Measurements weretaken the day after the 3-day behavioral datacollection period was completed. To estimate theamount of each food type consumed (in grams), wefirst converted the data on percentage of the activitybudget devoted to feeding into feeding minutesfollowing van Doorn et al. [2010]. Second, followingGarber et al. [2015], we used the average feedingrates for each food type (e.g., ripe fruits, unripe fruits,

immature leaves, mature leaves, flowers) based onpublished studies of A. seniculus and A. pigra totransform the data on time spent feeding into anestimate of the amount (in grams) of each fresh foodtype consumed. We used a Spearman’s correlation toidentify an association between DPL and the amountof each food type consumed.

Statistical AnalysisWe used linear mixed modeling [Package: nlme,

version 3.1–120, Pinheiro & Bates, 2000; Pinheiroet al., 2014] to evaluate the relationship betweenDPL and variables associated with feeding behavior,diet, activity budget, group spread, intergroupencounters, mean daily temperature, and indices offood availability and distribution (see Table I for adetailed description of predictive ecological varia-bles). This method offers advantages over moretraditional data analysis methods by quantifyingthe variation among sampling units, such asvariation among individuals (when multipleresponses are measured per individual, for example,the survival of multiple offspring or sex ratios ofmultiple broods) [Bolker et al., 2009; Zuur et al.,2009]. The random effect was group identity(two groups, Ar and Ta). The response ordependent variable was DPL (Table I), which waslog-transformed to meet model assumptions (normaldistribution of errors and homogeneity of variances).

In order to detect and minimize problemsassociated with multicollinearity, correlations

TABLE I. Description of Variables Used in the LinearMixed Model. DPL, Is the Response or DependentVariable; the Other Behavioral and Ecological Varia-bles Were Associated With DPL Based on the Resultsof PCA and Linear Modeling

Variables Description

DPL DPL (meters)Tmean Mean daily temperature (°C)Tmax Maximum daily temperature (°C)Tmin Minimum daily temperature (°C)Trange Daily temperature amplitude (°C)RAphShoot Relative abundance of shootRAphNL Relative abundance of new leavesRAphML Relative abundance of mature leavesRAphFlower Relative abundance of flowerRAphIF Relative abundance of immature fruitRAphMF Relative abundance of mature fruitTshoot Time invested feeding on shootstNL Time invested feeding on new leavestML Time invested feeding on mature leavestflower Time invested feeding on flowerstIF Time invested feeding on leavestMF Time invested feeding on mature leavesNencounters Number of encounters between two groupsDispersion Group dispersion (cm)

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between ecological variables were evaluated via thePearson correlation coefficient. Because many ofthese variables were highly correlated (r� 0.6 or��0.6, Appendix 1), we used principal componentsanalysis (henceforth, PCA) to obtain independentmeasures of predictive variables, and to reduce thenumber of predictive variables in the statisticalmodel. PCA is a multivariate ordination techniquethat represents a data set containing severalvariables (Table I) as a data set with a smallernumber of composite variables, the components oraxes of the PCA. These axes are orthogonal, that is,they are uncorrelated, and represent the strongestcovariation patterns among the variables in theoriginal data set [McCune et al., 2002] (Table II).Based on these criteria, principal components 1–8were chosen to represent variation in the originalecological parameters and as predictive variables inthe linear mixed model. To evaluate modelassumptions of normality we used a modifiedShapiro–Wilks test, and this assumption was met(W¼ 0.95, P¼ 0.36). To test for homogeneity ofvariances, we inspected a residual plot (predictedvalues vs. residuals), and this plot showed homoge-neity of variances. All analyses were conducted inInfostat [Di Rienzo et al., 2011] and R Version 3.0.3[R Development Core Team, 2014]. This research ispart of larger populational study of the behavior,ecology, and demography of A. caraya in NorthernArgentina and compliedwith theAmerican Society ofPrimatologists principles for the ethical treatment ofhuman primates, the University of Illinois, Urbanaguidelines for animal research, and the laws ofArgentina (IACUC protocol 06207).

RESULTSDiet and Activity Patterns

Over the course of 36 complete observation days,we obtained 5,138 focal animal scans for Group Arand 6,365 focal animal scans for Group Ta (total11,503 scans, and 463hr of observation). Both groupshad similar activity patterns (Resting Ar¼53%Ta¼60%, Traveling Ar¼ 12% Ta¼ 13%, FeedingAr¼ 27% Ta¼21%, Social Interactions Ar¼ 8% Ta¼6%). Within each group, we found no evidence ofseasonal changes in activity budget (Fig. 2)(Kruskal–Wallis ANOVA test: H¼ 1, P>0.05,N¼12).

Figure 3 indicates the percentage of each foodphenophase ingested per month for members of eachgroup, and reveals a similar dietary emphasis(Kruskal–Wallis ANOVA test: H¼ 1, P>0.05,N¼12). Combining data on feeding time for bothhowler groups during the 6-month study period,individuals devoted 35% of feeding time to consum-ing mature fruits, 16% to immature fruits, 31% tonew leaves, and 13% to mature leaves. However,there was evidence of marked seasonal differences inhowler feeding patterns. Combining the data fromboth groups, in spring new leaves (33%), matureleaves (17%), immature fruits (16%), mature fruits(17%), and flowers (10%) were the most commonitems in the howler diet, whereas during the summer(Fig. 3) howlers increased time devoted to theconsumption of mature fruits (54%) and decreasedtheir consumption of new leaves (29%), matureleaves (10%), immature fruits (7%), and flowers(0%) (Fig. 3). New leaves were eaten during all

TABLE II. Results of the Principal Components Analysis. The Values Are Pearson Correlation CoefficientsBetween the Original Ecological Variables and Principal Components

% explained variance 0.33 0.18 0.16 0.08 0.07 0.05

Variables PC1 PC2 PC3 PC4 PC5 PC6

Tmean 0.57 0.71 �0.34 0.05 �0.01 0.02Tmax 0.46 0.81 �0.18 0.21 �0.07 0.18Tmin 0.66 0.58 �0.39 �0.13 �0.05 �0.11Trange �0.14 0.58 0.24 0.55 �0.05 0.47RAphShoot 0.50 0.04 0.60 �0.23 0.36 0.01RAphNL 0.56 0.25 0.72 �0.03 0.07 �0.06RAphML 0.73 �0.48 �0.37 0.08 0.12 0.16RAphFlower �0.46 0.54 0.64 �0.09 �0.09 �0.04RAphIF 0.80 �0.31 0.05 0.04 0.33 �0.03RAphMF 0.81 �0.34 �0.20 0.06 �0.01 0.13tshoot �0.55 �0.36 �0.06 0.12 0.33 0.52tNL �0.44 0.36 �0.63 �0.11 0.26 �0.19tML �0.69 0.18 �0.43 �0.22 0.25 0.03tflower �0.61 �0.23 0.34 �0.21 -0.30 0.12tIF 0.11 0.28 0.44 �0.18 0.63 �0.01tMF 0.69 �0.12 0.26 �0.24 �0.44 0.06Nencounters 0.27 �0.32 0.12 0.75 0.08 �0.29Dispersion �0.59 0.06 0.20 0.50 0.06 �0.31

Variables in bold have correlations higher than or equal to � 0.6, and variables in italics have correlations higher than � 0.55 and lower than � 0.60.

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months of the study, accounting for approximately30% of feeding time per month. A Spearmancorrelation examining the IVI (Importance valueindex) of food species and the percentage of eachspecies in the diet indicated no clear association(N¼17,R¼0.26,P¼0.32). Thus, the howlers did notconsume the most highly available food resources intheir home range. Rather, both the plant speciescomposition of the howler diet and the food typesconsumed indicate a pattern of selectivity withplant species such as Eugenia uniflora (fruits),

Ficus luschnathiana (fruits), and Clorophoratinctoria (fruits) serving as preferred taxa.

The average group spread for Tawas 120� 80m2

and for Ar was 80�40m2, suggesting that during allmonths of the year and across all activities, groupswere highly cohesive. During the entire study period,we recorded a total of only four instances of within-group agonistic interactions during feeding. In eachcase the event occurred in a fruit patch and involvedonly adult males. This resulted in a rate of 0.03agonistic interactions/hr/indiv during feeding.

Fig. 2. Seasonal diet composition of each howler group (September 2007 to February 2008).

Fig. 3. Seasonal variation in the activity budget of each howler group (September 2007 to February 2008).

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Patch DistributionBased on two indices of resource dispersion, ID

(Index of Dispersion) and MID (Morisita’s Index ofDispersion), fruit patches and flower patchesexploited by the howlers exhibited a scattereddistribution compared to leaf patches, whichexhibited a more uniform distribution across eachgroup’s home range (IDfruit patches¼ 1.22,IDflower patches¼ 1.37, and IDleaf patches¼ 0.44(P<0.05) and MIDfruit patches¼1.1, MIDflowerpatches¼2.24, and MIDleaf patches¼ 0.75(P<0.05). This also is supported by data oninterpatch distance. The distance between fruitpatches (average¼300�90m, N¼25) and the dis-tance between flower patches (average¼225�40m,N¼4) was considerably greater than distance be-tween leaf patches (average¼ 139� 67m, N¼12)exploited by the howlers. We found that DPL variedbetween seasons (greater in summer when ripe fruitsdominated the diet and lower in spring when leavesdominated the diet) but were similar between groups(DPLTa-Spring¼ 673�177m; DPLAr-Spring¼ 673�172m; DPLTa-Summer¼850� 117m; DPLAr-Summer¼870�106m) (Mann–Whitney: U¼151,50, P¼0.739, N1,2¼18, 18) (Fig. 4).

Predictive Variables of DPLThe predictive variables in the linear models

were the first six PCA axes, which accounted forapproximately 94% of the variance in the originaldata matrix. In each model, there was a correlation� 0.4 with at least one of the original ecologicalvariables (Table II). Our model accounted for 82% ofvariance in the response variable (R2¼ 0.82) and theresults are shown in Table III. The principalcomponents (PCs) that were significantly associatedwith DPL (data for both groups combined) were PC1,

PC2, and PC3 (a¼0.05; P for PC1¼<0.0001; P forPC2¼ 0.007; P for PC3¼0.03). PC1 (33% explainedvariance) described a contrast between variableswith high values (>0.6) of RAphMF, RAphIF,RAphML, RAphNL, tMF, Tmin, and Tmean, andlow values (<�0.6) of tML, tflower, and groupdispersion (see Table I for a definition of thesevariables). Overall, these results indicate that underconditions of high immature and mature fruitavailability the howlers increased DPL whereasthe increased availability and increased timeinvested in feeding on mature leaves resulted in adecrease in DPL. This is consistent with theexpectations of Prediction 1 and Prediction 2, namelythat DPL will increase when exploiting scatteredfood patches (fruit) and decrease when exploitingclumped or uniformly distributed food patches(leaves). In addition, we found that group spreadincreased up to 4,000m2 when howlers exploited leafpatches (a single leaf patch included 4–10 quadrats)compared to fruit patches (0.5–4 quadrats).However,given the limited instances of contest competition atfeeding sites (N¼4) there was no evidence ofincreased aggression when feeding on clumpedresources. Thus Prediction 3 was not supported.Moreover, with increased group spread, there was adecrease in DPL (Table II) providing further supportfor our observations that with an increase in leafeating, howlers traveled shorter distances per day.

We found that PC3 (16% explained variance) waspositively associated with RAphNL, RAphFlower,RAphShoot, and negatively associated with tNL.Thus, DPL increased with an increase in theavailably of new leaves, shoots and flowers, anddecreased when the time spent feeding on new leaveswas highest. Given that time spent feeding is not adirect measure of the amount of food consumedbecause it includes both time devoted to handlingand processing (manually and orally) each item, weexplored the association between the estimatedamount of each food type ingested and DPL. We

Fig. 4. Relationship between DPL (data for both groupscombined) and spring and summer.

TABLE III. Results of the Linear Mixed Model.Principal Components One With Three Were Signifi-cantly Associated to DPL (a¼0.05)

Value Std. error t-value P-value

PC1 0.086 0.009 9.24PC2 �0.037 0.013 �2.92 0.007PC3 0.031 0.013 2.36 0.026PC4 0.035 0.019 1.89 0.071PC5 0.014 0.020 0.67 0.509PC6 0.040 0.025 1.61 0.119

Note: Specification of model in R (nlme package): modelo.003_LN_DDm_REML<lme(LN_DDm�1þCP.1þCP.2þCP.3þCP.4þCP.5þCP.6þCP.7þCP.8, random¼ list(grupo¼pdIdent(�1)), method¼ “REML,”control¼ lmeControl(msMaxIter¼ 200), na.action¼na.omit, data¼R.data03, keep.data¼FALSE). Our model accounted for 82% of variance in the responsevariable (R2¼ 0.82).In bold significant Principal Component axes.

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832 / Ra~no et al.

found a positive association between DPL and theamount of mature fruits consumed (N¼ 36, r¼ 0.6,P< 0.05), and a negative association between DPLand the amount of new leaves (N¼ 36, r¼�0.4,P< 0.05) and mature leaves (N¼36, r¼�0.5,P< 0.05) consumed. Thus using measures of timespent feeding per food type multiplied by the amountconsumed per unit time from the published literatureon howlers, offers additional support that DPLdecreased with an increase in the amount of leavesin the howler diet and DPL increased with anincrease in the amount of fruit consumed by thehowlers.

PC4 through PC8 were not significant.Therefore, we found no statistical support forPrediction 4. An increase in intergroup encounterswas not associated with an increase in DPL (see PC4in Tables II and III). However, we note that on daysin which howlers engaged in intergroup encounters,day range increased approximately 220m (averageDPLdays with encounters¼850�120m, N¼15 days;average DPLdays without encounters¼630�195m,N¼21 days). Given that 50% (N¼ 15) of intergroupencounters in our howler study groups occurredduring the breeding season, it appears thatadditional factors such as female fertility are likelyto have contributed to DPL.

We also explored the possibility that tempera-ture affected howler DPL. PC2 (18% explainedvariance) was strongly associated with daily Tmean,Tmax, Tmin, and Trange, indicating that on days inwhich maximum, minimum, mean daily temper-atures were high, DPL increased. For example, ondays inwhich theminimum temperaturewas greaterthan 20°C (N¼12), DPL was 790�181m, whereason days in which the minimum temperaturewas below 10°C (N¼ 5), DPL was 562�120m.These results failed to support Prediction 5 thatthese howlers were using an energy conservationstrategy on very hot days. The positive associationbetween temperature and DPL also is supported byPC1, and we suggest that this relationship is bestexplained in terms of food availability driving howlermovement and ranging patterns and temperaturepossibly associated with season affecting foodavailability.

DISCUSSIONModels of primate socioecology have tended to

emphasize the importance of feeding competition inshaping many aspects of grouping patterns, within-group social interactions, and ranging behavior[Clutton-Brock & Janson, 2012; Snaith & Chapman,2007; Sterck et al., 1997]. However recent critiques ofthese models indicate that evidence of feedingcompetition resulting in fitness costs is limited inmany populations, and that under a wide range ofsocial and ecological conditions individuals are able

to flexibly adjust their activity budget, foragingstrategies, ranging patterns, and social interactionsto obtain sufficient resources [Chapais, 2006; Dias &Strier, 2003; Fan et al., 2014; Janson, 2000; Sussman&Garber, 2011; Thierry, 2008]. In the present study,we examined the set of factors that affect daily pathlength (DPL) in black and gold howler monkeys(Alouatta caraya). In this howler population bothpredation risk and infanticide risk appear to berelatively low. Based on observations of our studypopulation conducted over the past 9 years, we havedocumented ten cases of observed or suspectedinfanticide in 22 howler groups (220 group years).This represents less than 2.5% of infants born duringthis period (N¼387 infants born). Each of these tencases was associated with a male takeover, and intwo cases we found the dead infant. In contrast mostinfant deaths over the same period wereattributable to other causes (maternal condition,droughts—spring-summer 2007, predators—twocases in which a dog attacked a mother carryingher infant while traveling on the ground, parasiticinfections, although the cause of most infant deathsremains unknown). Thus, although infanticideoccurs occasionally in our population and we haveno evidence to support the contention thatinfanticide risk was a primary factor in howler rangeuse and movement patterns.

Increased DPL has previously been used as aproxy for increased feeding competition and the coststo individuals of traveling to additional feeding sites[Gillespie & Chapman, 2001; Janson & Goldsmith,1995; Stevenson, 2006]. Our two study groups weresimilar in size (5–6 individuals), had overlappinghome ranges, and based on observations collectedover the course of 6 months, aggressive contests atfeeding sites were rare and occurred at a rate of 0.03events/individual per hour of feeding. This low rateof within-group aggression at feeding sites is consis-tent with other howler studies. In this regard,Kowalewski [ 2007] reported a rate of 0.003 agonisticinteractions per individual per day in a study of twogroups ofA. caraya during a period of 12months, anda rate of<0.004 aggressive interactions per hour perindividual during feeding. Similarly low rates ofwithin-group aggression have been reported inA. palliata (0.007 aggressive interactions perindividual per hour [Jones, 1980]) and A. seniculus(0.0005 aggressive interactions per individual perhour [Rumiz, 1992]). Given small group size andlimited evidence for feeding competition in thepresent study, we examined how patch distribution,patch availability, food type, group spread, inter-group encounters, and temperature affected DPL.

Our results indicated that an increase in theavailability of ripe fruits, time invested in feeding onfruits, and the amount of fruits consumed had thestrongest effect on increasing DPL in black and goldhowlers. This appears to reflect the fact that within

Am. J. Primatol.

Determinants of Day-Range in Howlers / 833

the home ranges of our study groups, fruit patcheswere discontinuous and more widely scattered(greater interpatch distance) than flower or leafpatches exploited by howlers. DPL also waspositively correlated with the availability of newand mature leaves (PC1). However we did not find astrong association between DPLs and number of leaffeeding trees visited per day (Spearman N¼ 36,r¼�0.15, P> 0.05). Thus, although the howlersfrequently switched among different leaf species,possibly in an attempt to minimize the accumulatedingestion of secondary compounds present in a givenleaf species [Dai et al., 2014; DeGabriel et al., 2009],the relatively uniform distribution of leaf patches didnot result in an increase in DPL. We did find apositive association between the number of treesexploited for leaves and the number of trees exploitedfor fruits on the same day (SpearmanN¼36, r¼ 0.4,P<0.05) suggesting that the scattered distributionof fruit trees contributed to increased distancetraveled [Garber et al., 2015].

PC1 and PC3 indicated a positive relationshipbetween DPL and the availability of flowers but anegative relationship with time spent feeding onflowers. We also found a negative associationsbetween time spent feeding on flowers and theestimated amount of flowers ingested (SpearmanN¼36, r¼�0.35, P<0.05) with DPL. Given thescattered distribution (average interpatch distanceof 225m) of neighboring flower feeding sites,we expected that howlers would travel greaterdistances on days in which flower consumptionincreased. This was not the case. We note, however,that the howlers consumed flowers on only 10 of 18observation days during the spring and did not feedon flowers during the summer. On days in whichflowers were exploited, they visited an average of3� 1.7 trees per day (and between 2 and 3 vinepatches). The most common flower species consumedwas Myrcianthes pungens. An average of 5�1M. pungens trees were visited on each of 6 days.This species was characterized by an interpatchdistance of only 70� 25m, and this may help explainwhy DPL did not increase during days of increasedflower feeding.

The positive association between DPL and theavailability of new leaves (but not mature leaves)appeared to be driven principally by the relationshipbetween DPL and fruit availability (See PC1 inTable II, Fig. 5). Seasonal variation in the amount oftime spent feeding on immature leaves was minimal(33% of feeding time in spring vs. 29% of feeding timein the summer), and DPL was negatively associatedwith both time spent feeding on new leaves and withthe estimated amount of new leaves ingested.Therefore increased DPL during the summerappears to have been driven primarily by the howlerpreference to exploit fruit patches that werediscontinuous and scattered across their range.

Fig. 5. Relationship between day range (m) and significant PC1scores (a), PC2 scores (b), and PC3 scores(c). Numbers inparentheses are Pearson correlations between each variable andPC1, PC2, and PC3 scores.Variables in bold have correlationshigher than or equal to �0.6, and variables in italics havecorrelationshigher than �0.55 and lower than �0.60.

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834 / Ra~no et al.

Predictions 3–5 were not supported. We did notfind an increase in aggression or a change in groupspread when the howlers exploited foods located in asingle tree crown (P3), nor did DPL increase on daysin which groups engaged in intergroup encounters(P4). In addition, our results indicated that underconditions of high daytime temperatures (potentialheat stress), howlers did not increase time spentresting nor did DPL decrease as a means to conserveenergy during high summer temperatures. However,even on hot days in which the howlers increasedDPL, the additional distances traveled were onthe order of only 50–200m per day. Data on theenergetic cost of travel in both arboreal andterrestrial primates indicate that traveling anadditional 50–200m accounts for less than0.05–0.2% of total daily energy [Steudel, 2000]. Weconclude, therefore, that monthly variation in DPLduring our study was not of sufficient magnitudeto result in a significant increase in energyrequirements or a noticeable change in activitybudget.

Fruits represent an easily processed food that,in addition to contain simple sugars, may berelatively high in lipids (lipids contain twice themetabolizable energy per unit than protein orcarbohydrates) [Conklin-Brittain et al., 2006]. Ina detailed study of the nutritional composition offood items consumed by howlers at our site,Fern�andez [2014] found that although the lipidcontent present in leaves, flowers, and ripe fruitswas generally low (1.5–2.7%), immature fruitscontained 8.6% lipids. Similarly, Righini et al.[2016] found that the lipid content of ripe (11.1%)and immature fruits (5.4%) consumed by blackhowlers (A. pigra) in Mexico was greater than thelipid content of young leaves (1.9%) and matureleaves (2.4%). Thus, the relatively small energeticcosts of traveling an additional 200m per day toacquire fruit during the summer, even whendaytime temperatures reached 35°C, appeared tobe compensated by increased access to a highenergy resource.

Finally, opportunities for scramble competitionhave been argued to increase during periods ofresource scarcity, as individual group membersspread out to locate and consume small and scatteredfood patches. This is expected to result in a decreasein group cohesion and an increase in DPL ifindividuals visit additional feeding sites to satisfytheir nutritional and energy requirements [Chap-man & Chapman, 2000; Snaith & Chapman, 2007].However, this was not the case in black and goldhowlers. Group spread averaged only 200�152m2

across all feeding conditions was smaller during fruitfeeding than during leaf feeding and did not increasewhen exploiting feeding sites of lower productivity.

In conclusion, our results suggest that DPL inblack and gold howlers is influenced by several

interrelated factors. An increase in DPL in ourstudy was primarily driven by fruit availability andfruit consumption. During periods when fruits weremost available (summer) the howlers increasedtime spent feeding on mature fruits (from 17% offeeding time in spring to 54% of feeding time insummer and from 1,006.0� 753.6 g fresh weightin spring to 1,675.8� 802.8 g fresh weight insummer) resulting in an average increase in DPLof approximately 200m. Although many research-ers have characterized howlers as folivores andhighlighted their ability to exploit difficult to digestfoods when fruits and flowers are unavailable[Glander, 1981; Milton, 1980], a recent review byGarber et al. [2015] indicates that many species ofhowlers consume both a fruit-enriched or balancedfruit and leaf diet [Amato & Garber, 2014;Fern�andez, 2014; Righini, 2014]. Thus, as is thecase for other atelines, fruits represent a criticalcomponent of the howler diet accounting for 50%or more of the total amount of food ingested[Garber et al., 2015]. Given evidence that feedingcompetition plays a relatively limited role in thefeeding ecology and social interactions of A. carayaand several other howler species [Wang & Mil-ton 2003], models of socioecology and ecologicalconstraints [Chapman & Chapman, 2000;Clutton-Brock & Janson, 2012; Reichard & Nowak,2010; Snaith & Chapman, 2008; Sterck et al., 1997;Sussman & Garber, 2004, 2007] need to reconsiderhow factors such as individual nutritional require-ments, social tolerance and group cohesion, and thespatial and temporal availability of preferred andnearby food resources influence primate social andranging behavior.

ACKNOWLEDGMENTSWe thank Anthony Di Fiore and two anonymous

reviewers for their comments that help to improvethismanuscript. We thank the support of Dr. GabrielZunino during the field work and for stimulatingdiscussions on the topic. We thankMariaWollnik forconstructive comments on earlier drafts of thismanuscript. We also thank our field assistants andcollaborators: Mariela Martinez, Cecilia Allen,Marina Maiden Ferrucci, Valeria Colombo, GabrielaBallesteros, and RamonMartinez. We finally thanksto Mariana Garcia, for her help with the changes inthemap of thismanuscript. This workwas supportedby the Scott Neotropical Fund of The ClevelandZoological Society and Cleveland Metroparks Zoo(MK) and PIP IU 355/CONICET-Argentina (MK).The study complied with the current laws andpermission of the United States and Argentina(IACUC protocol 06207), and adhered to the ASPprinciples for the ethical treatment of nonhumanprimates. PAG thanks Chrissie, Sara, and Jenni fortheir love and support.

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