LONG CALL FREQUENCY VARIATION IN MANTLED HOWLER MONKEYS (Alouatta palliata)

by

James Wheeler

A Thesis Submitted to the Faculty of

The Dorothy F. Schmidt College of Arts and Letters

in Partial Fulfillment of the Requirements for the Degree of

Master of Arts

Florida Atlantic University

Boca Raton, Florida

December 2013

LONG CALL FREQUENCY VARIATION IN MANTLED HOWLER MONNKEYS By

James Wheeler

This thesis was prepared under the direction of the candidate's thesis advisor, Dr. Doug Broadfield, Department of Anthropology, and has been approved by the members of his supervisory committee. It was submitted to the faculty of the Dorothy F. Schmidt College of Arts and Letters and was accepted in partial fulfillment of the requirements for the degree of Master of Arts.

SUPERVISORY COMMITTEE:

Andrew Halloran, Ph.D. ~l>D(!~A. Kate Detwiler, Ph.D.

Heather Cottman, DMA Interim Dean, Dorothy F. Schmidt College of Arts and Letters ~-r.~.-.

11 ACKNOWLEDGMENTS

I would like to acknowledge the efforts of others in the culmination of this thesis for it was not the effort of one person, but many. I would like to thank Dr. Andrew

Halloran for his help in Nicaragua, both with field research methods and teaching me

PRAAT. I would like to thank Dr. Douglas Broadfield for his assistance both throughout school and throughout the lengthy pursuit of this document. Renee Molina and family were incredibly welcoming and hospitable, and I would like to encourage others to get in touch with them for all that they offer, from tourism to conservation; specifically, the

Maderas Rainforest Conservancy is an incredible resource and benefit to the world. I would like to thank Leonel Ruiz for his assistance throughout my stay and his help in the forest; without him I truly would have been lost and lonely. I would like to thank the towns of San Ramon and Merida. I would like to thank the students of each of the primate field classes. I would also like to thank my family and friends for encouraging me to pursue this path and to stick with it.

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ABSTRACT

Author: James D. Wheeler

Title: Long Call Frequency Variation in Mantled Howler Monkeys (Alouatta palliata)

Institution: Florida Atlantic University

Thesis Advisor: Dr. Douglas Broadfield

Degree: Master of Arts

Year: 2013

The long call frequency of male mantled howler monkeys (Alouatta palliata) varies across individuals. In a forest environment where visual contact is impossible at greater distances the long call is utilized for inter-group spacing and for male-male communication. As lower frequencies are capable of traveling longer distances, it is quite possible that there is a correlation between group size and long call frequency. This link lies in the premise that smaller groups have fewer individuals thus fewer males, and spread out less over the course of each day while obtaining food resources, thus the distance these males call over their lifespan is generally less than the males in a larger group. This thesis investigates the relationship between group size and long call frequency in mantled howler monkeys (Alouatta palliata) on Isla de Ometepé, Nicaragua.

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LONG CALL FREQUENCY VARIATION IN MANTLED HOWLER MONKEYS (Alouatta palliata)

List of Tables………………………………………………………………………….….vi

List of Figures………………………….……….………………………………….……viii

Introduction………………………………………...…….………………………………..1

Feeding Ecology……………………….………….………………………………2

Vocalizations………………………………………………………………………4

Group Size………….……………………………………………………………11

Thesis Statement……………………………………..……………………....…..13

Materials & Methods………….…………..………………………..…………....………14

Study Area…………………..……...….….……………………….……………14

Group Size……………………………….………………………………………19

Long Call Frequency……………………...……...………….…………………..21

Long Call Frequency Analysis………………………………..…………………22

Statistical Analyses………………………....…..……….……………………….31

Results……………………………………………………………………………………57

Discussion……………………………………………………………………………..…62

References……………………………….……………………………………………….66

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TABLES

Table 1. Most Abundantly Utilized Trees Observed in Coffee Forest……………..…19

Table 2. Coffee Forest Howler Monkey Troop Demography…………………...…….20

Table 3. Coffee Forest Troop Size as Compared to Other Studies and Species……....20

Table 4. Coffee Forest Group Demographics as Compared to Clarke and Zucker

(1994) Table 2 and Fedigan et al. (1998) Tables II & III……………...... 21

Table 5. General Distribution of Large Group’s (LG) Bark Frequencies…….……….32

Table 6. General Distribution of Large Group’s (LG) Roar Frequencies……………..32

Table 7. Statistical Analyses of Large Group Calls………………………………...…33

Table 8. Statistical Analyses of Very Large Group Calls……………………………..34

Table 9. Mean and Standard Variation Frequencies for VLG’s P1 & P2 Emphasized

Frequencies…………………………………………………………………..52

Table 10. Mean and Standard Variation Frequencies for LG’s P1 & P2

Emphasized Frequencies……………………………………………………..52

Table 11. First Major Emphasized Frequency in each group’s P3……………………..53

Table 12. Second Major Emphasized Frequency in each group’s P3……………...... 53

Table 13. Relationship of Peak 1 and Peak 2 frequencies in both groups….…………..54

Table 14. Peak 1 by vocalization type………………………………………………….54

Table 15. Peak 2 vocalizations by type…………………………………………………55

vi

Table 16. Both Coffee Forest groups’s roars compared to Whitehead’s (1995)

emphasized frequencies…………………………………………………...…56

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FIGURES

Figure 1. Drawing of apparatus used by Riede et al. to test simulated howler

vocalizations ...... 9

Figure 2. Satellite Image of Ometepé with approximate location of the Coffee

Forest...... 16

Figure 3. Coffee Forest Map (modified version of the original - by Falk Huettmann,

2009) ...... 17

Figure 4. Crude map of the Coffee Forest based on GPS coordinates acquired during

walk-through ...... 18

Figure 5. Audiospectrogram of 3 barks ...... 25

Figure 6. Spectral slice from 0 Hz to 104 Hz (abscissa) and relative decibel level

(dB) (ordinate)… ...... 26

Figure 7. Relationship of bands in spectrogram (left) and peaks in spectral slice

(right, rotated counterclockwise 90°)…………………….……….……...... 27

Figure 8. Spectrum from Figure 5 - isolating frequencies from 0 to 5,000 Hz……...... 27

Figure 9. Spectral slice from previous spectrogram figures that isolates frequencies

from 0 to 1,000 Hz………………………………………………...... 28

Figure 10. Close-up of Peak 2 (P2) from previous figures; abscissa ranges from

376.0 Hz to 391.7 Hz…………………………….………… ...... 28

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Figure 11. Peak 2 (P2) fully magnified with the highest part of the peak selected

(380.881593 to 386.254339 Hz) providing 383.567966 Hz as the center

of the tip of the peak………………………………………… ...... 29

Figure 12. Frequency pairings between corresponding P1 and P2 values from Large

Group calls (ordered from lowest P1 value to highest)……… ...... 30

Figure 13. Simple graph demonstrating how Peak 1 freq.’s differ between groups ...... 35

Figure 14. Histogram of Large Group’s Peak 1 Vocalization Freq.’s (Hz – abscissa) .....36

Figure 15. Histogram of Very Large Group’s Peak 1 Vocalization Frequencies (Hz –

abscissa)…………………………………………………………… ...... 37

Figure 16. Histogram comparing the distributions of long call frequencies for each

group’s first peak frequencies………………………………… ...... 38

Figure 17. Histogram comparing the distributions of long call frequencies for each

group’s second peak frequencies…………………………………… ...... 39

Figure 18. Histogram comparing the distributions of long call frequencies for each

group’s third peak frequencies………………………………… ...... 40

Figure 19. P1 and P2 distribution of Large Group long call frequencies

(300 – 650 Hz)…………………………………………………… ...... 41

Figure 20. P1 and P2 distribution of Large Group long call frequencies

(650 – 3,000 Hz)…………………………………………… ...... 42

Figure 21. Distribution of Large Group’s third peak frequencies (by type)

(0 – 3,000 Hz)…………………………………………………… ...... 43

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Figure 22. Distribution of Large Group’s third peak frequencies (by type)

(3,000 – 6,500 Hz)………………………………………………………...…44

Figure 23. Distribution of VLG’s P1 emphasized frequencies (by type)………………..45

Figure 24. Distribution of VLG’s P2 emphasized frequencies (by type)…………….….46

Figure 25. Distribution of LG’s P1 emphasized frequencies (by type)……………….…47

Figure 26. Distribution of LG’s P2 emphasized frequencies (by type)……………….…48

Figure 27. At all markers VLG P1 has higher frequencies……………………………...49

Figure 28. VLG and LG are fairly similar throughout the distribution of

frequencies for P2…………………………………………………...……….50

Figure 29. General distribution of P3 frequencies for both groups…………….………..51

Figure 30. Map showing location of Beach Forest……………………………….……..64

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INTRODUCTION

The mantled howling monkey (Alouatta palliata) is a relatively large arboreal and diurnal New World primate belonging to the family Atelinae (Rowe, 1996; Fleagle,

1999). “A. palliata is placed as the sister taxon to all other Alouatta species” (Villalobos,

2004). Cortés-Ortiz et al. (2003) indicate that the Mesoamerican howler monkeys (A. palliata and A. pigra) split from the South American howler monkeys at about 6.8 million years ago, then the split between A. pigra and A. palliata followed at approximately 3 million years ago. There are five “sub-species” listed under the species

A. palliata: A. p. palliata, A. p. mexicana, A. p. aequatorialis, A. p. coibensis, and A. p. trabeata (The Species 2000 and ITIS Catalogue of Life; Cuarón et al., 2008). They are reported as threatened (Crockett and Eisenberg, 1987), but groups can be found in many types of forest from primary to regenerating rainforest, dry deciduous, riparian, coastal lowland, mangrove, and cloud forest (Wolfheim, 1983), even in “habitats ranging from closed-canopy wet evergreen forest to highly seasonal deciduous woodlands and riverine forests” (Cortés-Ortiz et al., 2003). They can be found in coffee plantations in Nicaragua and do no damage to the coffee crops, so are easily tolerated there. Shade coffee plantations cover much of the remaining forest on Nicaragua’s Pacific coast (McCann et al., 2003). Estación Biológica de Ometepé (Ometepé Biological Field Station) is located on the southern side of Isla de Ometepé in the town of San Ramón at approximately 11˚

24’ 58” N, 85˚ 32’ 24” W. This field station is in the process of marking populations of

1 howler monkeys on the island for the purposes of studying demography, migratory patterns, and reproduction (maderasrfc.org). The area surrounding the field station is dry deciduous tropical forest “crosscut by agricultural fields or trails and heavily fragmented by land use and deforestation (Winkler et al., 2004). Furthermore, Illes (2005) indicates that “it is estimated that Nicaragua has lost half of its rainforests to slash and burn agriculture and logging activities since 1950” and that when farmers would suffer from poor crop seasons they “abandoned their land and moved farther into the forest

(Nicaragua Network 2005).” The wet and dry seasons are each approximately six months long; there is an annual rainfall of 1500 mm (1200-1800 mm: Salas Estrada, 1993) and the mean annual temperature is 27.3˚C (Cavers et al., 2003).

Feeding Ecology

Nagy and Milton (1979), calculated that “an average-sized howler monkey

(approximately 6.5 kg) should ingest 348 g dry food each day. This is equivalent to about 1 kg fresh food, or, stated another way, A. palliata should eat about 15% of its body mass in fresh food each day in the field during the dry season.” Nagy and Milton conducted a census in March of 1977; supplemented by census data from Carpenter

(1934), which determined that the average adult male mantled howler is 8.5 kg, the average adult female is 6.4 kg, the average juvenile is 4.0 kg, and the average infant is 1 kg (Nagy and Milton, 1979). From prior research (see Estrada and Trejo, 1978; Estrada,

1981a, b), Estrada (1982) affirms that the howlers at Los Tuxtlas are extremely selective in their choice of trees to use as food sources. He stated that the howlers at that site use

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36 species of plants to eat leaves and fruit. Fruit makes up 51% of their diet, leaves constitute 45%, vines contribute 2%, and flowers and petioles each contribute 1% to their total diet. Milton (1980) states that the mantled howlers on Barro Colorado Island,

Panama, spend 21.9 to 74.5 percent of their overall feeding time on leaves, 16.0 to 68.2 percent of their overall feeding time on fruit, and 0.0 to 22.9 percent of their overall feeding time on flowers, all and each depending upon the season. Also, the mean percent of daily time spent eating (overall) ranges from 11.92 percent to 20.56 percent, again, depending upon the season (Milton, 1980). However, Estrada agrees with other authors

(Rickwood and Kenneth, 1979; Milton, 1980) that, as a generalist herbivore, most mantled howlers feed primarily on young leaves. The young leaves, as well as mature fruits, are highly seasonal food items for which the howlers at Los Tuxtlas display a great preference, as they spend large portions of their time eating those particular items.

Altmann observed a preference for fig fruits and leaves with a wide variety of other fruits, leaves, and nuts in their diet (1959). Based on at least Milton (1980) and Milton et al. (1982), howlers have a relationship with the fig fruits of Ficus spp. According to

Milton et al. (1982):

Both F. yoponensis and F. insipida . . . were selected because they have by far the highest relative densities of any Ficus species on the island (Knight 1975, Milton 1980) and are the most important species in the diets of many animals, particularly howler monkeys (Alouatta palliata) and various species of fruit bat (Altmann 1959, Hladik and Hladik 1969, Morrison 1978, Bonaccorso 1979, Milton 1980) . . . In addition, both species appear to have ties with certain seed dispersal agents, particularly howler monkeys and fruit bats. Since figs are lower in nutritional quality than most fleshy fruits on Barro Colorado (Milton 1980, 1981), they may be relatively inferior competitors for seed dispersal agents. Few frugivores actually seem to prefer fig fruit. One exception is the howler monkey (Alouatta palliata), which eats considerable fig fruit at all times of year (Hladik and Hladik 1969, Milton 1980). Howlers have an energetically conservative

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lifestyle, which helps to explain how they sustain them-selves on fruits lower in energy than those eaten by more active primates such as capuchin (Cebus capucinus) or spider (Ateles geoffroyi) monkeys (Milton 1978, 1981, Milton et al. 1979, Nagy and Milton 1979).

At least on BCI the howlers focus on figs from Ficus spp. of the Moraceae family.

Milton (1980) notes specifically that “In percent of overall feeding time, the families used most by howlers were the Moraceae (51.54 percent) and the Leguminosae (15.80 percent). It can be seen that together these two families accounted for about two-thirds of overall feeding time and therefore played a major role in the howler diet.” It should be noted that the Leguminosae family is also known as Fabaceae.

Vocalizations

Fitch and Hauser (1995) elucidate many general aspects of nonhuman primate vocalization and point to literature for further review on the general topics of human vocalization, sound production, harmonics, and so forth. The main aspects of nonhuman primate vocalization from their article are as follows:

The lungs produce the source of power for vocalizations, a pressurized airstream. This is modulated by the larynx to produce a source of sound. In phonation, this source is a periodic series of air puffs, which repeat at a rate known as the fundamental frequency (F0)…The sound source is channeled through the supralaryngeal vocal tract, a resonant tube of air including the pharyngeal, oral, and nasal cavities. The length and some aspects of the shape of this tube determine the frequencies of resonances (called formants in human speech). The vocal tract might directly influence laryngeal behavior (resulting in a feedback system, like many wind instruments), or be relatively independent of the larynx, acting simply as a filter that removes certain frequencies from the laryngeal source (as in human speech)…The anatomical configuration of the larynx and vocal tract constrain primate communication systems in different ways. Converging evidence suggests that the size of the larynx is relatively independent of total body size, making F0 a poor cue to body size for adults

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within most species. The resonant frequencies of the vocal tract may provide a more ‘honest’ cue to body size, because they are determined by skull size and mandible length, and thus may be more tightly coupled to body size. Although a number of observations are consistent with the idea that animals use resonant frequencies as cues to body size, no research has directly evaluated this hypothesis…Furthermore, anatomical specializations, such as laryngeal air sacs or the modified hyoid bone of the howler monkey Alouatta (Kelemen, 1960; Schön Ybarra, in press), may result in unusual phonation modes or other additions to the basic acoustic principles outlined above.

The authors conclude by stipulating that there was still a minimal amount of data on nonhuman primate vocalizations, suggesting much more extended research in the field of study. Owren and Rendall (2001) define formants as “resonance of the supralaryngeal vocal tract that passes energy in a particular frequency region. Energy outside these resonance areas is weakened, especially in regions of anti-resonances.” So, the basic level/frequency at which the vocal tract itself vibrates is the fundamental frequency off which all other frequencies are based. The resonance of the different cavities above the larynx accentuate some frequencies while attenuating others as the reverberated air passes through the vocal tract acting as a filter to the source of sound. These filters are also referred to as “transfer functions” meaning that they alter the produced sound by transferring energy through resonance, masking some frequencies completely out of the resulting sound while enhancing others (Owren and Rendall, 2001). Whitehead (1995) cautions against using the same terminology as is used with human vocalizations

[formant and resonant, following Schön (1986)], instead adopting the terms “emphasized frequency” (EF) 1 and 2 to describe the greatest band of energy seen in spectrogram analysis.

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Unlike some cavities that are inflatable and can change in volume, such as the air sacs of some mammalian species, some are “non-inflatable because they are surrounded partially or completely by the cartilaginous or bony material, for instance, the Bulla hyoidea in howler monkeys (Alouatta spec.) (Starck and Schneider, 1960)” (Riede et al.,

2008). Furthermore, the enlarged hyoid bone of the genus is a specialized structure that allows howlers to resonate and amplify sounds. This bone and the associated hyoid bulla are key characteristics in identifying these species, however, little is known about the evolution of these structures (Villalobos, 2004). “Howler monkeys (Allouatinae) are the most prominent examples with a large Bulla hyoidea (Starck and Schneider, 1960;

Schön-Ybarra, 1995). It is interesting to note that howler monkey vocalization is characterized by a source spectrum with many bifurcations (Whitehead, 1995)” (Riede et al., 2008). Not only do Alouatta species have the medially located Bulla hyoidea bone structure, but additionally there are two lateral air sacs (Riede et al., 2008; Starck and

Schneider, 1960). “Laryngeal sacs and laryngeal specializations, like those found in howlers. . .are especially good for producing loud, low-pitched acoustic signals (Hewitt et al., 2002; Hohmann, 1989; Marler, 1972; MacKinnon, 1974; Ybarra, 1986)” (Delgado,

2006).

A. palliata has the least complex hyoid bone of the Alouatta species and produces barks and roars at lower frequencies than A. seniculus and A. caraya ([Eisenberg, 1976;

Thorington et al., 1984; Schön-Ybarra, 1986] in Villalobos, 2004). The range of palliata group’s “emphasized frequencies” is from 300-1000 Hz, whereas most other species range from 300-2000 Hz, and the duration for which they vocalize is usually much

6 shorter compared to those other species as well (Whitehead, 1995). Whitehead

(unpublished data) estimates that the A. palliata fundamental frequency ranges from 75 to

130 Hz, yet insists that more investigation and analysis are required (Whitehead, 1995).

Whitehead (1995) separates howlers into two groups based on relative duration of roar sequences: the palliata group (all palliata subspecies), which produces roars of limited duration, and the non-palliata group, which produces roars of extended duration. The palliata group averages roars around 3.5 seconds long while the non-palliata group (all remaining members of the genus) “often sustains roars for extended periods of time.

Sekulic and Chivers (1986) report that the median call duration in A. seniculus is 19.0 sec, and Schön (1986) measured male call around 8.0 sec. In addition, some forms are capable of sustaining loud calls continuously for around 2 min,” which A. palliata cannot produce. Furthermore, this could indicate differing modes of vocal production

(Whitehead, 1995).

Oliveira (2004) suggested that “it is possible that brief roaring is an ancestral pattern of roaring, preceding the evolution of long, continuous roaring.” With respect to genetic and morphological data, which places A. palliata as a basal and sister species with a simple hyoid bone, this could help explain why this species’ calls last for mere seconds while other species call continuously for minutes.

Riede and colleagues (2008) conducted an experiment that demonstrated the variability to the vocal tract to which mammalian air sacs added, via physical and computational models. For understanding how air sacs alter the sounds produced by howler monkey species, these results have been especially helpful. In this article, VT

7 referred to vocal tract, PTP to phonation threshold pressure (“the minimum subglottal pressure required to initiate and sustain the vocal fold oscillations. Functionally, it provides an index for the vocal effort”), SPL to sound pressure level (in decibels, dB), F0 to fundamental frequency, SB to side branch, and pole/zero pair referred to the region where F0 and vocal tract resonance are in close proximity. The main aspects of the experiment and results, as they pertain to howler vocalizations, are as follows:

Experiments and computer simulations were carried out to investigate the questions on whether mammalian air sacs or bulla-like cavities affect formant position and/or SPL. Four vocal tract configurations were investigated: (1) a uniform tube-like main vocal tract without any attachment, (2) a vocal tract with open or closed uniform tube-SB, (3) a vocal tract with a tube-SB plus a rigid cavity air sac, and (4) a vocal tract with a tube-SB plus an inflatable air sac… A rigid cavity added to the tube-SB, which models the bulla hyoidea most prominent in Allouatinae, added a pole/zero pair in the range between 80 and 150 Hz. Again, the neighboring formants were shifted somewhat, where the first formant was shifted by up to 70%... Of particular interest is the region where F0 and vocal tract resonance (pole/zero pair) are in close proximity. Near this region, the vocal tract impedance is quite variable and may produce dramatic changes in the source-filter interaction. This has been most impressively demonstrated here by the low frequency pole/zero pair introduced by the cavity. As the cavity resonance crosses F0, the interaction becomes so strong that the vocal folds stop vibrating. The experimental results suggest that the effect of the source-filter interaction is asymmetric about both sides of the filter resonance. For instance, SPL was higher when F0 was on the right side of the resonance than when it was on the left side. This suggests that a perfect matching between vocal tract resonance and F0 is not as desirable, as previously considered (e.g., Riede et al., 2006), but F0 slightly off the resonance is more beneficial for energy feedback to the sound source (Titze, 2008)… we have recognized two acoustic effects of the air sacs. First, the air sac can increase the dynamic range of the sound emission within a given subglottic pressure range, both at the upper and lower limits… In the case of noninflatable air sacs, they extend the frequency range, in which voice instability and nonlinear phenomena are induced by source-tract coupling. This provides additional vocal variability. The formants of the main vocal tract are shifted by a pole/zero pair introduced by air sac. Our experiments suggest that such formant shifts are most prominent on the first formant and less on the higher formants (Riede et al., 2008).

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The feedback due to the addition of certain side branches led to the impedance of sound in such a way that amplified the overall sound in an observable pattern. The rigid cavity added to the side branch in this experiment showed that the overall pressure needed to produce sound was lower than necessary for a tube without a side branch, as well as the fact that the sound produced with this cavity was quite louder than that which was produced without a side branch. In one particular experiment to demonstrate the relationship between the size of the rigid cavity and the sound pressure level, it was determined that there is an optimal size based on the relationship between the resonance frequency (F0) and the impedance of the first pole/zero pair. As this relationship was demonstrated in such a manner, the exploitation of this relationship might exist in the wild in such a way that howlers have taken advantage of this relationship somehow.

Figure 1: Drawing of apparatus used by Riede et al. (2008) to test simulated howler vocalizations

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Apart from intra-group communication, howlers vocalize to defend “a territory within their home ranges against intrusion by other members of the same species. The territories were maintained primarily by means of loud, deep roaring vocalizations given by the adult males” (Altmann, 1959). In what Sekulic (1982) calls the “dawn chorus”, and as others describe similarly, males vocalize excessively around dawn, which has been attributed to this territorial nature and spatial distribution. Furthermore, howlers use loud calls in response to distant calls, yet “for New World monkeys, there is no evidence for mate attraction or rallying group members via long-distance vocalizations” (Delgado,

2006). Altmann (1959) described 10 distinct vocalizations from his observations of a single group of monkeys on Barro Colorado Island, which then brought the total known vocabulary for the species at the time to 20 distinct vocalizations. Sekulic (1982) adds that “the loud call, howl, or roar” referred to in many papers “is a continuous sound produced by troop members which appears to result from a fusion of the bark syllable as described for Alouatta palliata by Eisenberg (1 976). The term ‘howling’ has also been used for repeated short, loud calls (barks) which occur infrequently in undisturbed A . seniculus. Barks are heard occasionally at the beginning and/or the end of continuous calls and are here treated separately from howling.”

Animals that use auditory means of communication must overcome varying obstacles depending upon the environment which they inhabit. In particular, predominately arboreal primates indubitably encounter many trees while typically maintaining a safe distance from the ground. The height at which the howler monkeys call from in the trees changes how the sound propagates through the air, leaves, and

10 branches. Some sound is lost as it moves outward from the caller, whether it is traveling up through the top of the canopy, scattered by the leaves and branches, or being impeded, reflected, or refracted by differing gradients of atmosphere, which each change temporally and spatially (Wiley and Richards, 1978).

Group Size Estrada’s (1982) census in Mexico of 17 troops of mantled howlers yielded a mean troop size of 9.12 individuals with a range of 5-16 animals per troop. The mean troop composition was 3.0 adult males per troop, 4.12 adult females, 1.56 juveniles, and

1.54 infants. The mean adult sex ratio, adult males to females (M:F) was 1:1.37 (see

Estrada, 1982: Table I for a further breakdown of troop characteristics). Similar censuses of mantled howler populations (e.g., Fedigan et al., 1985; Freese, 1976; Rodriguez, 1985;

Milton and Mittermeier, 1977; Baldwin and Baldwin, 1972; Clarke et al.,1986; Heltne et al.,1976; Fishkind and Susman, 1987; Carpenter, 1934, 1962; Chivers, 1969; Smith,

1977; Mittermeier, 1973; Milton, 1982; Bernstein, 1964; Altmann, 1959) have been conducted and compiled as a literature review as per Chapman and Balcomb (1998).

This table (Chapman and Balcomb, 1998, Table III) compares group sizes and average group sizes from several groups at each study site to help compare population statistics at the species and genus level. Their table, compiled from many censuses for several

Alouatta spp. over decades, indicates that A. palliata has larger groups than other howler species (approximately 14.6 members per troop; ranging from 5.2 to 23.0), as well as a lower proportion of males per female than other Alouatta spp. (Chapman and Balcomb,

1998, Table IV.). Crockett and Eisenberg (1987), also report that mantled howlers have 11 different group sizes and compositions than other Alouatta spp., typically having 10 to 20 individuals per group and differing group dynamics. Other species of Alouatta, including

A. seniculus, A. caraya, and A. fusca, tend to have 6-8 individuals per group; A. pigra tends to have smaller groups as well (Clarke and Zucker, 1994). Those on Ometepé have been recorded as demonstrating a “fission fusion foraging pattern (Bezanson et al., 2002;

Winkler et al., 2002) in which subgroups, (comprising ≥ 1 male and ≥ 1 female) of larger groups forage and sleep separately from each other, in some cases for days at a time. This provides reproductive opportunities for males other than the dominant male”

(Winkler et al., 2004). “The number of male howlers per group appears to be more strictly limited and less variable than the number of females is” (Fedigan et al., 1998).

Thesis Statement

As group size increases, the long call frequency of its male members is expected to decrease.

H0: Long call frequency does not correlate with group size.

H1: Long call frequency decreases with increased group size (negative correlation).

H2: Long call frequency increases with increased group size (positive correlation mentioned in Derby and DiFiore: “In addition, we have found that daily path lengths are shorter, group sizes are larger and the frequencies of long call vocalizations are greater at the high-density versus the low-density site (P < 0.05). The fertility of the soil and the

12 forest structure play a large role in affecting the density as well as the behavior of the red howler monkeys in Ecuador.”

Group size – higher

Long call frequency - higher

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MATERIALS & METHODS

Study Area Research was conducted in the Coffee Forest section of Estación Biológica de

Ometepé on Isla de Ometepé, Nicaragua. The field station itself was established in

January of 1997, in the hopes of learning about, protecting, conserving, and managing the

Nicaraguan plant and animal life (maderasrfc.org). This Coffee Forest site is not directly adjacent to or encompassed by the main property of the field station (the forest is property owned and maintained by the Estación Biológica de Ometepé), however, it is a

30 to 35 minute walk away, part of which is along a road on the southwest edge of the island, while the other part is from the road into the forest. All field data was collected between 04:30h and 18:00h daily between May 25, 2010 and July 30, 2010. Data was collected to distinguish troops from one another (e.g. troop size, age and sex composition, markings) ad libitum. Calls were recorded (in stereo/two channels) in the field, when presented, using an Olympus WS-300M Digital Voice Recorder, which saved the recordings as WAV files. The recordings were sampled at a frequency rate of 44.1 kHz.

Certain points were mapped using a Garmin eTrex Legend HCx Global Positioning

System device. The approximate area of the main part of the Coffee Forest was calculated to be 35,246.3 m2 (approximately 8.71 acres or 3.52 hectares) based on these

GPS coordinates (see Figures 1-3).

Within this study area there were many different types of trees, but the trees 14

predominantly used by the monkeys were noted and further investigated. Based on the trees identified and given local names, genus and species for these trees were identified. All of these trees were from the class Magnoliopsida, and all were perennial dicots. From the family Anacardiaceae came the Spondias purpurea, or “Jocote”; from the Annonaceae family came the Annona purpurea, or “Annona”; from the Boraginaceae family came the Cordia alliodora, or “Laurel (hembra)”; from the Calophyllaceae family there was the Calophyllum candidissimum, or “Madroño”; from the family Cecropiaceae came the Cecropia peltata, known as “Guarumo”; from the Fabaceae family came

Albizia niopoides, or “Guanacaste,” Albizia saman, or “Genizaro,” Gliricidia sepium, or

“Madero negro,” and Hymenaea courbaril, or “Guapinol”; from the Moraceae family there were Ficus spp., known as “Matapalo”; from the family Myrtaceae came Psidium guajava, or “Guayabo”; the Olacaceae family brought Heisteria longipes, known as

“Coloradito”; the Rosaceae family brought Prunus salicifolia, or “Capulín”; from the

Sapotaceae family Chryssophylum cainito, known as “Caimito”; from the family

Simaroubaceae came Simarouba glauca, or “Aceituno”; and from the Sterculiaceae family came Guazuma ulmifolia, known as “Guacimo.” The only species that was not further identified was known as “Fosforo,” however, it is quite possible that this is actually Rollinia/Annona pittieri from the Annonaceae family. During this time of year

C. peltata was observed yielding yellowish-green to green colored fruits which were eaten by the monkeys to some degree as they typically do not eat the entire fruit. It is documented that Howler monkeys do eat the leaves of this species of tree, but they were not observed doing so during this study. The Ficus trees also yielded fruit which were

15 observed on the ground, haven been eaten to some degree, however, these fruits did not appear to be fully ripe. The Ficus leaves were observed being eaten on several occasions.

On one occasion the monkeys were observed eating the leaves and even the ants from an

Acacia cornigera (Bullhorn Acacia), but this was not common due to the trees’ mutualistic relationship with acacia ants (Pseudomyrmex ferruginea), which sting and bite herbivorous predators (Janzen, 1967). Most other tree species mentioned were used for their leaves. R. salicifolia, like other cherry trees, yielded a small, edible fruit that was eaten. The leaves of this species of tree were also eaten.

Figure 2: Satellite Image of Ometepé with approximate location of the Coffee Forest

Photo credit: Spot Image, Toulouse, France http://www.spotimage.com/ 16

Figure 3: Coffee Forest Map

(modified version of the original - by Falk Huettmann, 2009)

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Figure 4: Crude map of the Coffee Forest based on GPS coordinates acquired during walk-throughs. Thick lines represent outer borders of property and pathways, while thinner lines represent inner pathways through the forest.

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Table 1: Most Abundantly Utilized Trees Observed in Coffee Forest Organized

Alphabetically by Order (Class – Magnoliopsida)

Order Family Genus species Local Name Clusiaceae Calophyllaceae Calycophyllum candidissimum “Madroño” Ebenales Sapotaceae Chryssophylum cainito “Caimito” Fabales Fabaceae Acacia cornigera “Cornizuelo” Albizia niopoides “Guanacaste” Albizia saman “Genizaro” Gliricidia sepium “Madero negro” Hymenaea courbaril “Guapinol” Lamiales Boraginaceae Cordia alliodora “Laurel hembra” Magnoliales Annonaceae Annona purpurea “Annona” Rollinia/Annona pittieri “Fosforo” Malvales Sterculiaceae Guazuma ulmifolia “Guacimo” Myrtales Myrtaceae Psidium guajava “Guayabo” Rosales Rosaceae Prunus salicifolia “Capulín” Santalales Olacaceae Heisteria longipes “Coloradito” Sapindales Anacardiaceae Spondias purpurea “Jocote” Simarubaceae Simarouba glauca “Aceituno” Urticales Cecropiaceae Cecropia peltata “Guarumo” Moraceae Ficus spp. (obtusifolia) “Matapalo”

Group Size There are approximately five groups in the Coffee Forest study area. Two of those groups were located and identified based on individually distinguishing demography and approximate location. The group characteristics were important in the relocation of each troop from day to day, so as not to mistake one from another and cause a pseudoreplication of data. A group with a higher number of males should be able to defend a larger area based on the adult males’ ability to make calls. Lastly, there are a

19 fairly consistent proportion of males to females in mantled howler monkey troops such that an increase in the number of adult males in one troop usually indicates the addition of several adult females. On the other hand, adult females can join a group in small numbers before the addition of another adult male.

Table 2: Coffee Forest Howler Monkey Troop Demography

Adult Adult M:F F:imm Juveniles Infants Total Troop Males Females Ratio Ratio

Very Large Group 5 5 1:1 1:1.2 2 4 16

Large Group 3 4 1:1.33 1:1 1 3 11

Total 8 9 3 7 27

Percent of Total 30 33 11 26

Table 3: Coffee Forest Troop Size as Compared to Other Studies and Species (via Chapman and Balcomb, 1998)

A. palliata A. pigra A. caraya A. seniculus Coffee Forest Range 5.2-23.0 4.2-6.3 2.0-8.05 3.3-19.0 11.0-16.0 Average 14.63 5.39 5.98 7.63 13.5

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Table 4: Coffee Forest Group Demographics as Compared to Clarke and Zucker (1994) Table 2 and Fedigan et al. (1998) Tables II & III

Clarke and Fedigan et Fedigan et al., Coffee Zucker, al., 1998 1998 Forest 2010 1994 (Data: Santa (Tables II & III) (1991 Rosa Natl. Complete) Park, 1992) # of Groups 27 21 2

Mean group size 12.6 14.8 13.7 13.5 Range, group size 2-45 8 - 20.8 11-16

Mean males per group 2.5 3.9 2.7 4 Mean females per 6.8 5.4 6.7 4.5 group Mean immatures per Inf: 3.1; Juv: Inf: 2.49; Juv: 3.1 5 group 2.6 2.46

Adult females per adult 2.8 1.5 2.58 1.125 male Adults per immature 3.0 1.7

Immatures per adult 0.5 0.84 0.7 1.11 female

Density (per/km^2) 103.3 7.9 46.35 --

Long Call Frequency Derby and Di Fiore (unpublished) allude to a positive relationship between adult male biomass and the oscillation frequency at which those males make long calls. These observations are based on red howler monkeys (Alouatta seniculus) in Ecuador, but this thesis paper has attempted to record the long calls of the adult males in each group to analyze the presence and strength of this proposed correlation between these two factors.

Mitani and Stuht (1998) add that “sound attenuates over distance due to three frequency- dependent factors, atmospheric absorption, scattering, and interference due to the ground

(review in Wiley & Richards, 1982). Atmospheric absorption and scattering produce 21 attenuation that increases with sound frequency.” This is such that sound waves are weakened closer to the ground as the waves interact with one another based on the height from which they were emitted, which becomes less problematic as many primates propagate their calls from several meters above the ground, however, at this height in the vegetation of forests the atmospheric absorption becomes more problematic. As considered, these factors “lead to the prediction that primates should produce loud calls at relatively low frequencies to minimize their attenuation” (Mitani and Stuht, 1998).

“Signalers will radiate sound energy most efficiently near their characteristic resonant frequencies. In general, these resonant frequencies will vary inversely with linear dimensions of the resonator (Kinsler & Frey, 1962)” (Mitani and Stuht, 1998).

Long Call Frequency Analysis

Digital recordings of long calls were uploaded to iTunes in order to be used by the program PRAAT© acoustic analysis software (Boersma and Weenink, 2010; Version

5.1.43). Analyses of these vocal recordings were done using this phonetics computer program. The raw recordings were individually selected and manipulated so that they could be represented graphically one at a time. The recordings were sampled and listened to so that noise disturbances and multiple callers could be distinguished and selected against. In the initial analysis window spectrogram of the audio to visual component of the analyses the time (in seconds) was represented on the x-axis and frequency (from 0 Hz to 104 Hz) on the y-axis. Once a call was highlighted, selected, and extracted, a spectrogram of the call was created, which “turns the selected Sound into a

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Spectrum by an over-all spectral analysis, a Fourier transform.” The setting “Fast” checked “determines whether zeroes are appended to the sound such that the number of samples is a power of two. This can appreciably speed up the Fourier transform”

(Boersma and Weenink, 2010). To identify spectral peaks in each call Linear Predictive

Coding (LPC smoothing) was utilized to make the spectral peaks readily apparent and distinguishable from one another; this method is often used to identify broad spectral peaks in human speech (Digweed et al., 2005; Markel and Gray, 1976). The number of peaks for each spectrogram was always set and examined at 40 peaks, and the pre- emphasis from 50.0 Hz that was preset was utilized; “An object of type LPC represents filter coefficients as a function of time. The coefficients are represented in frames with constant sampling period” (Boersma and Weenink, 2010). Each of these rendered a spectrogram with the frequency (in Hz) on the x-axis and decibel level (dB) on the y-axis.

Decibel levels per recording were relative, as interference played some part. For each individual call, the interference would not be a factor in comparing the peaks as one call from one individual from one location was examined at a time, so peaks were consistently accurate relative to one another within the same spectral analysis. Decibel levels were not recorded. For each call, the three loudest frequencies were examined more closely. The peaks were highlighted and were then magnified to identify the exact frequencies at the peaks. Because the peaks were set at a specific number and smoothing was utilized, the tips of each peak had a lower end point of the tip of the peak and a higher end point of the tip of the peak. To account for this factor, the middle of this line was determined with the equation: ((A-B)/2)+B, where A stands for the higher end point

23 of the peak and B stands for the lower end point of the peak. These mid-points were used in calculations as the actual frequencies for the peaks themselves. These values were recorded such that “P1” (Spectral Peak 1) corresponds to the middle of the top of the tallest peak in that spectrum, “P2” (Spectral Peak 2) corresponds to the middle of the top of the second tallest peak in that spectrum, and “P3” (Spectral Peak 3) corresponds to the middle of the top of the third tallest peak in that spectrum. This was repeated for each spectrum for each call to which it corresponded. All calls registered between 0 and 9,000

Hz, however, all of the main peaks were below 7,000 Hz. Any interference above 7,000

Hz was ignored as it did not interfere with the analysis of the howler calls. The program provided the analysis of all sounds that the microphone recorded during the selected time splice for the duration of the recording between the aforementioned frequencies. Any calls where an interference with the microphone created problems with the sound analysis were not used. Any calls where bird calls interfered with the howler call because of timing and overlapping frequencies were not used. Any howler calls that overlapped with one another were not used because the program was unable to distinguish between two separate callers. For clarity, “Time start”, “Time end”, “Duration”, “P1”, “P2, and

“P3” were recorded in an Excel file.

For the smaller of the two groups “Large Group (LG)” 9 files (32 min 11 sec) were analyzed for 172 calls, each averaging 0.349 seconds in length. Of these 172 calls

147 are “barks” and 25 are “roars” or roar variants. The larger of the two groups “Very

Large Group (VLG)” 6 files (1 hr 8 min 29 sec) were analyzed for 172 calls, each averaging 0.438 seconds in length.

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P3

P1 P2

Figure 5: Audiospectrogram of 3 barks - window length of 2.0 seconds (abscissa) and height of 104 Hertz (ordinate). It is important to note broad band from roughly 7,500 Hz (indicated by dotted line) and higher indicating static and insects. Peaks 1, 2, and 3 (within darker frequency bands) pointed out with arrows and labels. First bark (left): P1 occurs at 725.9 Hz; P2 at 389.6 Hz; P3 at 3176.1 Hz. Second bark (middle): P1 occurs at 714.6 Hz; P2 at 383.6 Hz; P3 at 3348.1 Hz. Third bark (right): P1 occurs at 740.3 Hz; P2 at 398.4 Hz; P3 at 3317.5 Hz.

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Figure 6: Spectral slice from 0 Hz to 104 Hz (abscissa) and relative decibel level (dB) (ordinate)

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Figure 7: Relationship of bands in spectrogram and peaks in spectral slice (rotated 90°)

Figure 8: The same spectrum from Fig 5. isolating frequencies from 0 to 5,000 Hz.

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Figure 9: Spectral slice from previous spectrogram figures that isolates frequencies from 0 to 1,000 Hz. Peak 1 (P1) is on the right and Peak 2 (P2) is on the left (in the middle of the figure).

Figure 10: Close-up of Peak 2 (P2) from previous figures; x-axis ranges from 376.0 Hz to 391.7 Hz.

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Figure 11: Peak 2 (P2) fully magnified with the highest part of the peak selected (380.881593 to 386.254339 Hz) providing 383.567966 Hz as the center of the tip of the peak.

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Statistical Analyses

Anderson-Darling tests for normality were done on each group’s three peak data sets. All P values were < 0.001. For the smaller of the two groups, Peak 1’s A2 =

13.980; Peak 2’s A2 = 11.506; Peak 3’s A2 = 17.492; when all peaks were combined for all calls from this group A2 = 59.064. For the larger of the two groups, Peak 1’s A2 =

7.839; Peak 2’s A2 = 17.599; Peak 3’s A2 = 5.795; when all peaks were combined for all calls from this group A2 = 52.859. Accordingly, all sets of data were rejected for normality, so nonparametric tests were used past this point.

The smaller and larger groups’s median first peak (P1) frequencies were

674.262247 Hz and 747.783295 Hz, respectively; distributions of the two groups differed significantly (Mann-Whitney U = 24079.5, n1 < n2, α = 0.05 one-tailed, P = 0.0000). The smaller and larger groups’s median second peak (P2) frequencies were 485.174899 Hz and 471.377055 Hz, respectively; distributions of the two groups did not differ significantly (Mann-Whitney U = 29247.0, n1 < n2, α = 0.05 one-tailed, P = 0.3234). The smaller and larger groups’s median third peak (P3) frequencies were 3249.164487 Hz and 3143.910768 Hz, respectively; distributions of the two groups did not differ significantly (Mann-Whitney U = 30952.0, n1 > n2, α = 0.05 one-tailed, P = 0.0823).

Also, the distribution for the first peak (P1) of the smaller group and the second peak (P2) of the smaller group differed significantly (Mann-Whitney U = 28034.0, n1 < n2, α = 0.05 one-tailed, P = 0.0381). The distributions of P1 and P2 for the larger group also differed significantly, but in the opposite relationship (Mann-Whitney U = 33662.0, n1 > n2, α =

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0.05 one-tailed, P = 0.0381). Lastly, the distribution of the smaller group’s P1 frequencies differed from the distribution of the larger group’s P2 frequencies (Mann-

Whitney U = 26035.0, n1 < n2, α = 0.05 one-tailed, P = 0.0000).

Table 5: General Distribution of Large Group’s (LG) Bark Frequencies

P1 P2 P3 Average 389.9 395.0 1403.6 Range (count) 318.0-429.1 (75) 360.7-437.4 (72) 1298.8-1481.8 (28) Average 728.0 776.4 2156.1 Range (count) 678.3-928.2 (72) 648.7-920.9 (72) 2102.2-2180.9 (5) Average 3290.9 Range (count) 3098.1-3473.6 (105) Average 4765.5 Range (count) 4751.7-4793.4 (3) Outliers (1527.5, 2169.5, (3921.7, 5272.9, 5403.5, 3331.1) 5585.2, 6064.3, 6145.0) Total 147 147 147

Table 6: General Distribution of Large Group’s (LG) Roar Frequencies

P1 P2 P3 Average 392.3 419.5 1391.0 Range (count) 366.1-431.3 (7) 332.4-508.7 (17) 1278.5-1515.4 (19) Average 794.9 723.7 3305.5 Range (count) 659.5-904.7 (17) 702.5-734.8 (4) 3248.2-3365.2 (5) Average 832.4 Range (count) 792.0-890.9 (4) Outliers 516.4 2196.1

Total 25 25 25

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Table 7: Statistical Analyses of Large Group Calls

LG P1 LG P2 LG P3 N (calls) 172 172 172 Minimum Frequency (Hz) 318.982490 332.446534 1298.790940 First Quartile (Hz) 389.285371 394.329978 1467.045999 Median Frequency (Hz) 674.262247 485.174899 3249.164487 Third Quartile (Hz) 729.104893 771.250662 3328.230114 Maximum Frequency (Hz) 928.171118 3331.103876 6145.036492 Mean Frequency (Hz) 571.213362 609.633563 2845.466552 Standard Deviation 177.969364 304.310690 1013.903180 Skewness 0.064382 4.481085 0.095469 Kurtosis -1.702426 36.791798 0.440098

A2 (A-D) P-Value <0.001 13.980 11.506 17.492 Lower/Upper Lower/Upper Lower/Upper 95% CI Mean - Lower 544.43 563.83 2692.90 - Upper 598.00 655.44 2998.50 95% CI Median - Lower 431.18 417.70 3235.50 -Upper 694.53 714.75 3269.90 95% CI Standard Deviation - 160.94 275.19 916.90 Lower - Upper 199.06 340.37 1134.10 95% CI Mean 544.43/598.00 563.83/655.44 2692.90.2998.50 95% CI Median 431.18/694.53 417.70/714.75 3235.50/3269.90 95% CI Standard Deviation 160.94/199.06 275.19/340.37 916.90/1134.10

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Table 8: Statistical Analyses of Very Large Group Calls

VLG P1 VLG P2 VLG P3 N (calls) 172 172 172 Minimum Frequency (Hz) 341.506858 360.686172 452.208939 First Quartile (Hz) 498.209047 409.137763 1457.201234 Median Frequency (Hz) 747.783295 471.377055 3143.910768 Third Quartile (Hz) 808.589649 754.257063 3363.559428 Maximum Frequency (Hz) 995.911784 3353.795692 6271.565260 Mean Frequency (Hz) 674.398100 617.850835 2781.298134 Standard Deviation 179.389196 394.678145 1298.361647 Skewness -0.501440 4.503948 0.529732 Kurtosis -1.120283 26.748439 -0.441218

A2 (A-D) P-Value <0.001 7.839 17.599 5.795

95% CI Mean - Lower 647.4 558.45 2585.90 - 701.4 677.25 2976.70 Upper 95% CI Median - Lower 711.2 454.45 2313.90 -Upper 766.89 509.61 3186.90 95% CI Standard Deviation - 162.22 356.91 1174.10 Lower - Upper 200.65 441.45 1452.20 Lower/Upper Lower/Upper Lower/Upper 95% CI Mean 647.4/701.4 558.45/677.25 2585.90/2976.70 95% CI Median 711.2/766.89 454.45/509.61 2313.90/3186.90 95% CI Standard Deviation 162.22/200.65 356.91/441.45 1174.10/1452.20

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RESULTS

The groups (troops) of the Coffee Forest were apprehended on a daily basis.

Their locations in relation to one another were fairly constant, but their relationship to the observable study area was far from constant. On the southwestern side of the Coffee

Forest there is a stone wall topped with barbwire that borders Finca Mystica, a hostel run by an American couple. Along the adjacent northwestern wall there remains a similar boundary between the Coffee Forest and a privately owned field used for farming. In the northeast and southeast there’s property owned by the Molina family (who own the

Coffee Forest and Field Station), however, much farther past the boundary of the Coffee

Forest in these directions lies natural boundaries, such as agricultural fields, that the howlers often avoid crossing. The Coffee Forest is more an arbitrary boundary designed to designate land use and permits those observing monkeys in the Coffee Forest to remain within those boundaries while the howlers cross these boundaries daily, sometimes many times, through the canopy. The group demographics explored in Table 2 fall well within the ranges exemplified by the studies depicted in Tables 3 and 4. The troops observed for this study exhibited the fission fusion grouping and subgrouping system described by

Winkler et al. (2004) through Bezanson et al. (2002) and Winkler et al. (2002). It was rare to find an entire group together at once. Because of this foraging pattern and the boundaries presented by the property lines and fencing, it was difficult to consistently see and follow the same individual for extended periods on some occasions. Certain portions

57 of the Very Large Group rarely presented themselves beyond the boundaries of Finca

Mystica until the last few days of data collection. It is possible that they spent most of their time as a subgroup west of that boundary. There is dense forest west of that boundary and several fruit and nut trees on the Finca Mystica property. Also, along the pathway from the road to the Coffee Forest there were several instances where howlers were observed occupying some of the larger trees in the agricultural fields as well as some smaller trees along the path itself. It is possible that these individuals were part of the VLG and simply separated from the other subgroups at the time. What the relationship of this group to the Beach group described in Illes (2005) and Garber et al.

(1999), also as per personal observations, is currently unclear. Through speaking with the owners of Finca Mystica and others, some have observed howlers crawling on the ground to cross small distances of either field or road, so it is possible that these two groups connect at some point. Likewise, individuals were heard to the far north and east of the Large Group in the Coffee Forest, so there could be either another group or subgroup nearby that mingles with that group. The dirt roads and trails are much more definitive than are the boundaries between howler groups present in this area. The two groups observed inhabited overlapping territory near the middle of the Coffee Forest, closer to the southwestern wall, however, there were no instances where the two groups were seen to be in close proximity. While standing at the northwestern gate of the Coffee

Forest during the dawn chorus howlers could be heard in nearly every direction. Soon after the dawn chorus it returned to near silence for awhile as some individuals lazily spread out from the group and slowly got a start to the days with simple foraging. On

58 this part of the island it did not seem as though the howler groups were competing for resources with many, or even any, other animals on a daily basis. There were a few predatory birds that flew overhead from time to time, but they did not seem to agitate the howlers much, if at all. The magpie-jays present, seemingly everywhere, did not appear to compete with the howlers for fruit, but they did make recording problematic at times.

The capuchins (Cebus capucinus) present on the island seemed to inhabit different parts of the forests on the island, only entering the Coffee Forest on a few occasions during observations. There were small spats with howlers on those occasions, but there did not appear to be any serious problems between the species. As mentioned by the owners of the adjacent Finca Mystica, they and the local farmers remain fairly tolerant of the howlers since they rarely come to take fruit or leaves from their plants used for agriculture, most likely due to the abundance of resources deeper in the forest.

The possibility for error arises while recording in a dense forest with wild specimens, albeit they were somewhat habituated to the presence of humans. The proximity to the callers and their location with respect to the recording device did not remain constant throughout all recordings. The fact that the forest was so dense and there were times when retrieving recordings from less than 30 meters away meant that, over the course of the distance between the caller and the recording device, there was certainly some acoustic interference. The interference increases with distance, as there are (and certainly were) more trees and air to interfere with the sounds produced by the animals.

As previously mentioned, birds, insects, and conspecific monkeys were producing sounds at various points throughout recording, however, these have been accounted for

59 accordingly: the insect sounds were generally out of the range of the howler call range and could therefore be ignored (consistently higher frequency); the bird and conspecific calls that directly interfered with calls caused those calls to be neglected or “thrown out” since the frequencies overlapped, rendering them virtually indecipherable once analyzed on a spectrogram (slice) since all frequencies are analyzed simultaneously.

Despite obstacles and inconsistencies, several total hours of recordings were rendered and analyzed for the 172 total calls for each of the two groups. The general attributes surrounding the group size and demographics, as well as the calls produced, were quite similar to those mentioned in similar studies. As is noted in Figures 13 and

27, the calls, in most aspects, for the Very Large Group were higher in frequency than those of the Large Group, which follows H2 and the relationship mentioned by Derby and

DiFiore. If the group sizes could be coupled with a density of animals it would be a more meaningful relationship, but since it is difficult to measure the full home range of each group this measurement is unaccounted for thus far. The distributions for Peak 2 and for

Peak 3 for both groups were quite similar, as demonstrated in Figures 13b, 13c, 17, and

18. The distribution of each group’s long call frequencies is explored in more depth in

Figures 23-26 and highlighted in Tables 9-12.

The group demographics were mostly within normal ranges, as compared to

Clarke and Zucker (1994) and Fedigan et al. (1998) as displayed in Table 13. It will be important to get demographic (and vocalization) data on more groups in the area, as well as the rest of the island (the other studies had more than ten times the number of groups).

Mean group size was similar to these studies and the range of group sizes fell within

60 those found in the groups of the other studies. The mean males per group was higher and the mean females per group was lower than in other studies. The immature howlers per group was higher in the Coffee Forest groups than in the other studies. As described earlier, the density of monkeys in a given range, as well as their full home ranges, was not determined, nor would it be fairly easy to determine given the unnatural boundaries discussed.

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DISCUSSION

This particular thesis was originally part of a much larger thesis project with several component parts. Much of the vocal component was done in tandem with these other parts. However, due to constraints of time and resources, these other parts were laid aside for another possible study involving the “Ecological-constraints model.” As a study on Howler monkey species, and vocalizations in general, this is not an entirely new study except in the specifics that were examined; as Cornick and Markowitz (2002) note

“The preponderance of the literature on howler monkey vocalizations describes 2 species in the genus-Alouatta palliata (Baldwin and Baldwin 1976; Carpenter 1934; Chivers

1969) and A. seniculus (Braza et al. 1981; Drubbel and Gautier 1993; Schön Ybarra

1986; Sekulic 1982a, 1982b, 1983).” This observation aside, this study may shed some light onto the possibility for further research in the comparison of individual monkeys’s vocalizations, as well as the comparison between and among groups of howlers and other monkeys. Future studies on this topic in particular should hopefully focus on the anatomical apparatus of the monkeys producing the calls even more so than this study was able to do. If possible, more research should be done in the forests of the Island of

Ometepé. There were several other groups present on the island that were not observed and incorporating this data into all of the current research available should aid in the investigation of howler monkey vocalizations as a whole. One aspect in particular that this study did not approach was the differences in vocalizations among groups (and

62 within groups) at differing altitudes; there were, and presumably still are, howlers present on the island that have been observed near the top of Volcan Maderas, so such a study comparing the vocalizations of these monkeys to others on the island would not only help with the understanding of primate acoustics but the possible differences between the troops that inhabit lower altitudes and those that inhabit the higher altitudes on the island.

As the specific acoustic disturbances of the sub-tropical forest were not incorporated into any data calculations, the differences in forest type throughout the island could have a profound effect on the acoustics of the vocalizations themselves and how they are perceived to recording data and especially to conspecifics. The inhabitance of differing forest types for single species could alter the method or outcome of howler long calls, which could ultimately lead to the alteration of the calls themselves or how they are perceived by others, or possibly both. Since the current study only focused on the frequency at which male howlers were vocalizing for long calls in one forest type, the addition of information on other groups in the surrounding areas could aid with understanding both the vocalizations of the current study, the groups on the island, and the species as a whole; such studies would place the current investigation into perspective within the scope of similar types of primate vocalization data. Howlers were seen in the

Beach forest, along trails between the field station and the waterfall behind it, along a hiking path up the side of the Maderas volcano, and heard elsewhere as well. Further investigation is required to apprehend and record information and vocalizations for these other howlers. The forest type, available food resources, and group demographics, along with adequate recordings of better quality than those already obtained could provide the

63 information needed to get a better idea of the diversity in the howler population on the island.

Figure 30: Location of the Beach Forest – small peninsula southwest of Coffee Forest

Also, since this was originally only a smaller part of a whole study, not as much time and effort was spent focusing on making many quality recordings. Too many were done in passing rather than as the primary focus. Since this was the case many of the calls that were recorded were done so from too far away from the source, were not made

64 carefully enough, so the microphone was not plugged in appropriately for some portion of the recording, and some recordings were either mislabeled or unlabeled. In the future it is necessary to take more time and care in focusing on the recordings and labeling of such. I would like to go back for a second opportunity to focus on these attributes and possibly record cleaner, longer, and better files of long distance calls for as many howlers on Ometepé. It would also be important to compare these to comparable calls at other locations of known mantled howler activity, such as La Suerte Biological Field Station in

Costa Rica and those previously mentioned. If one could gather thousands of calls from each then compare them all at the same time the results would be very informative of what roles these calls play or help to play, plus one could finally see the minute differences within and between sites.

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REFERENCES

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