Cercopithecus Diana) in Côte D’Ivoire’S Taï National Park

Home , Diana monkey, Jackson Zoo, Xylopia aethiopica

Socioecology, stress, and reproduction among female Diana monkeys (Cercopithecus diana) in Côte d’Ivoire’s Taï National Park

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Erin Elizabeth Kane

Graduate Program in Anthropology

The Ohio State University

2017

Dissertation Committee:

Professor Debra Guatelli-Steinberg

Professor Dawn Kitchen

Professor W. Scott McGraw, Advisor

Professor Barbara Piperata

Copyrighted by

Erin Elizabeth Kane

2017

Abstract

Socioecological models have been used to explore the relationship between female sociality and feeding ecology for nearly 40 years. Models typically distinguish between species eating ubiquitously distributed resources (e.g., leaves) in which females do not exhibit strong social bonds, engage in minimal feeding competition, and minimal territorial defense. These are contrasted with species relying on patchily distributed resources (e.g., ripe fruit) in which females do exhibit social bonds, engage in feeding competition, and defend group territories. Although these models have been critiqued and extended, these basic predictions have been widely used to develop hypotheses about the relationship between ecology and sociality among primates. Much of this research has focused on open-habitat and/or terrestrial primates, while relationships between ecology and sociality remain unexamined in many forest-dwelling and/or arboreal taxa. This is detrimental to our ability to develop unifying models of primate sociality and ecology, and problematic considering the arboreal, forest-dwelling niche filled by the earliest primates and primates in their evolutionary environment.

This dissertation examines the relationship between ecological variables and diet, social behavior, reproduction, and stress in arboreal, forest-dwelling guenons. Previous research has demonstrated that Diana monkeys (Cercopithecus diana) exemplify many predictions of socioecological; models: they are ripe fruit specialists, females are philopatric and socially bonded, and feeding competition both within and between groups ii is relatively high compared to closely related taxa. Here, I use socioecological data collected between July 2013-August 2015 on habituated adult female Diana monkeys living in the Taï Forest, Côte d’Ivoire, and fecal samples collected over the same period to test the hypothesis that fluctuations in food availability have significant consequences for Diana monkeys in terms of their diet, social relationships while foraging, the timing of reproduction, and metabolic stress.

Diana monkeys preferentially fed at very large, relatively rare trees, supplementing this diet with invertebrates and fruits from less-preferred trees that tend to be smaller but ubiquitously distributed. Diana monkeys timed birth and lactation for periods with of relatively high fruit availability; however, there was no relationships between fluctuations in food availability, diets, and fecal glucocorticoid concentrations.

While fecal glucocorticoid concentrations did fluctuate interannually, concentrations never reached pathological levels. Instead, I argue that these fluctuations allow Diana monkeys to cope with the normal strains of the life of wild primates. Diana monkeys are thus able to maintain their fruit-rich diet with minimal competition and few serious stressors. This has implications for socioecological models of primate behavior that derive primate sociality from resource distribution, with particular emphasis on competition over access to resources. Diana monkeys complicate these models because, although they eat high-value, discontinuously distributed resources, feeding competition does not drive their social behavior and there is little evidence that they experience negative consequences during periods of low food availability. This affirms the need to test not just the causes of primate behavioral ecology, but also its consequences.

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This dissertation is dedicated to my undergraduate advisors, Tab Rasmussen and Bob

Sussman. You helped set me on this path. Thank you.

Acknowledgments

Thank you to my advisor, Scott McGraw, and all my committee members – Dawn

Kitchen, Barbara Piperata, and Debbie Guatelli-Steinberg. You have all been patient, interested, helpful, and constructive, and I appreciate the time you have spent reading, rereading, writing, rewriting, and discussing more than I can say. Scott, thank you for sharing the monkeys of the Taï Forest with me, and supporting me throughout fieldwork and writing. Thank you also to Mark Hubbe, Mark Moritz, Kris Gremillion, and Julie

Field for immeasurably enhancing my graduate education. Thank you to Dr. Larsen for department leadership, and to Wayne Miller, Jean Whipple, and Elizabeth Freeman for keeping the anthropology department functioning.

Thank you to all funders of this research, including Sigma Xi, the OSU Office of

International Affairs, the Graduate School, the Department of Anthropology, and the

American Society of Primatologists. For permission to work in the Taï Forest, I thank the

Ministere d’Enseignment Superireur et Recherche Scientifique, the Ministere d’Agriculture et Resources Animales, and the Centre Suisse de Recherches Scientifiques.

Without the help of Dr. Anderson Bitty, conducting this research would have been much more of a challenge!

I am hugely indebted to the Reproductive Endocrinology lab at the Smithsonian

Conservation Biology Institute, notably Dr. Janine Brown, Nikki Haley, Dr. Natalia

Prado-Ovieda, Juthapathra Dechanupong, Morgan Maly, Deanna Moore, and Arianna

Bond. Thank you for welcoming me, training me, and sharing resources, ideas, and fun in

Front Royal! Thank you to my field friends in Taï for their camaraderie – Claudia

Stephan, Fredy Quintero, Martina Magria, Sonia Touistiti, and Adam van Casteren made time in the field enriching, enjoyable, and manageable.

Thank you to all the friends who have supported me in Columbus, especially my

Artisan family (especially Sarah Dorn, Aisha Bradshaw, Jessica Kehn) and Triceratops. I am so grateful for the close social bonds I’ve formed with the other primatology graduate students at Ohio State. Dara Adams, Noah Dunham, Tim Sefczek, Alex Wilkins, Ashley

Edes, Jessica Walz, Michelle Rodrigues, and Cathy Cooke – thank you! I am also grateful for the warm and collegial environment of the anthropology graduate program, with particular gratitude to Lisa Beiswenger, Barbara Betz, Erin Blankenship-Sefczek,

Abby Buffington, Addy Cary, Ana Casado, Melissa Clark, Aaron Comstock, Jesse

Goliath, Sarah Holt, Daryin Hummel, Katy Marklein, Leigh Oldershaw, Brian Padgett,

Genevieve Ritchie-Ewing, Marissa Stewart, Gordon Ulmer, and Andrew Weiland.

Thank you to my family – grandparents, great grandparents, aunts, uncles, cousins

– who love and support me in my wild dream to go chase monkeys, despite the many missed family occasions. Thank goodness for my little brother, Brendan, who has always been there to make me feel short, capable, and loved. My parents, Jessica and Derek, have not once balked at what I do with my life (well, OK. Maybe the second and third times I called to say I had malaria, they may have wished I made slightly different choices). Their unconditional support and love have kept me going.

Finally, this wouldn’t have been possible without the skilled, wonderful employees of the Taï Monkey Project and their families. Nasuo, aséo, merci beaucoup à vous! Frederic Gnépa, Ferdinand Belé, Richard Pého, Gerard Gah, Bertin Dioré, and

Paterson Kalo kept me alive, sane, and sciencing in Taï National Park. They welcomed me into their communities, villages, families with incredible kindness and generosity. I know that when I go back to Côte d’Ivoire and arrive in Ponan, Daobly, Tai, Gouliyako, or Paulioula, I’ve made it back home.

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Vita

June 2006 ...... Central High School

2009...... B.A. Anthropology and Environmental

Studies, Washington University in St. Louis

2012...... M.A. Anthropology, The Ohio State

University

2010 to present ...... Distinguished University Fellow,

Department of Anthropology, The Ohio

State University

Publications

Dunham NT, Kane EE, McGraw WS. 2017 Humeral correlates of forelimb elevation in four West African cercopithecid monkeys. American Journal of Physical Anthropology 162: 337-349.

Dunham NT, Kane EE, Rodriguez-Saona L. 2016. Quantifying soluble carbohydrates in tropical leaves using a portable mid-infrared sensor: implications for primate feeding ecology. American Journal of Primatology. 78: 701-706.

Kane EE, Gnepa F. 2016. An infanticide attempt after male takeover in Diana monkeys (Cercopithecus diana diana) in Taï, Côte d’Ivoire. African Primates. 11: 37-40. viii

Watsa M, Erkenswick G, Halloran D, Kane E, Porier A, Klonoski K, Cassalet S, Maciag E, Mangalea M, Dinsmore M, McCready H, Boughan B, Parker C, Hickmott A, Nole Bazán I, Zuñig A.2015. A field protocol for the capture and release of callitrichids. Neotropical Primates 22: 59-68.

Dunham NT, Kane EE, McGraw WS. 2015. Scapular morphology and forelimb use during foraging in four sympatric cercopithecids. Folia Primatologica 86: 474- 489.

McGraw WS, van Casteren A, Kane EE, Geissler E, Burrows B, Daegling DJ. 2015. Ingestive and oral processing behaviors of two colobine monkeys in Tai Forest, Ivory Coast. Journal of Human Evolution 98: 90-102.

Fields of Study

Major Field: Anthropology

Table of Contents

Abstract ...... ii

Acknowledgments...... v

Vita ...... viii

List of Tables ...... xvi

List of Figures ...... xx

Chapter 1: Socioecological models, typical primates, and Diana monkeys ...... 1

INTRODUCTION ...... 1

Sociological Models ...... 1

Looking Beyond the “Typical Primate” ...... 4

The Guenons ...... 5

The Diana Monkeys...... 8

This Study ...... 10

REFERENCES ...... 19

Chapter 2: Dietary Variation in Diana Monkeys ...... 27

INTRODUCTION ...... 27

METHODS...... 31

Study Site and Subjects ...... 31

Ecological and Statistical Methods ...... 32

RESULTS...... 36

The Diana Monkey Diet ...... 36

Dietary Overlap between Groups ...... 38

Fruit Availability and Diets ...... 40

Habitat Characterization ...... 40

Food Preference ...... 41

DISCUSSION ...... 42

Diana Monkey Diets ...... 42

Diana Monkey Groups’ Ecological Priorities? ...... 45

Conclusions and Further Directions ...... 48

TABLES ...... 51

FIGURES ...... 80

REFERENCES ...... 83

Chapter 3: Food site residence time and social interactions do not reflect dietary preference among wild Diana monkeys ...... 88

INTRODUCTION ...... 88

METHODS...... 92

Data Collection ...... 93

Data Analysis ...... 96

RESULTS...... 97

Focal observations ...... 97

Fruit availability and foraging behavior ...... 97

Food type, fruit preference, and foraging behavior ...... 99

Social behavior and food type ...... 100

DISCUSSION ...... 101

TABLES ...... 108

FIGURES ...... 110

REFERENCES ...... 119

Chapter 4: Diana monkeys’ fecal glucocorticoid responses to stressful events ...... 123

INTRODUCTION ...... 123

METHODS...... 128

Captive Data Collection ...... 128

Enzyme Immunoassay Protocol ...... 132

Statistical Analysis ...... 135

RESULTS...... 136

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Captive samples ...... 136

Wild samples ...... 136

FGCs from individual samples ...... 137

DISCUSSION ...... 138

Fecal glucocorticoids and acute stress ...... 138

Guenon endocrinology ...... 139

Methodological Considerations ...... 141

FIGURES ...... 143

REFERENCES ...... 150

Chapter 5: Reproductive endocrinology and ecology in wild female Diana monkeys: a preliminary analysis ...... 156

INTRODUCTION ...... 156

METHODS...... 159

Data Collection ...... 159

Statistical Methods ...... 162

RESULTS...... 162

Reproductive Endocrinology ...... 163

DISCUSSION ...... 165

Diana Monkeys’ Reproductive Strategies ...... 165

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Diana Monkey Reproductive Endocrinology ...... 168

TABLES ...... 174

FIGURES ...... 176

REFERENCES ...... 182

Chapter 6: Assessing the relationship between stress, ecology, and female behavior ... 188

INTRODUCTION ...... 188

METHODS...... 191

Behavioral and Ecological Methods ...... 191

RESULTS...... 194

Diana Monkey Feeding Ecology and Food Availability ...... 194

Fecal Glucocorticoid Concentrations ...... 196

Diet, Food Availability, and Fecal Glucocorticoids ...... 196

Social Behavior and Fecal Glucocorticoids ...... 198

Reproductive Status and Fecal Glucocorticoids ...... 199

Modeling FGCs, Ecology, Reproduction, and Social Stress ...... 200

DISCUSSION ...... 200

Diana Monkeys and the Reactive Scope of the Stress Response ...... 202

TABLES ...... 206

FIGURES ...... 211

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REFERENCES ...... 266

Chapter 7: Diana monkey socioecology, reproduction, and stress: a synthesis ...... 270

CONCLUSIONS ...... 270

Diana Monkeys and Sociecological Models...... 272

REFERENCES ...... 277

References ...... 279

List of Tables

Table 2.1. The relative dietary contributions of invertebrates, fruits, fruit species, leaves, leaf species, and other material to the diet of two Diana monkey groups, and the pooled group diet, between July 2013-August 2015...... 51

Table 2.2. Overall contributions of fruit species, leaf species, and other material to the diets of two Diana monkey groups, and the pooled diet, between July 2013-August 2015.

...... 53

Table 2.3. Monthly contributions of fruit, invertebrates, and leaves to the diets of two

Diana monkey groups between July 2013-August 2015, and shared dietary proportions of these two groups...... 55

Table 2.4. Monthly contributions of species-specific plant parts to the diets of two Diana monkey groups, monthly diversity (H), and monthly evenness (J) between July 2013-

August 2015...... 57

Table 2.5. Mean monthly fruit availability (A) and monthly fruit consumption (C, percent of monthly diet) by the pooled Diana monkey group between July 2013-April 2014

(2.5a), and October 2014-August 2015 (2.5b)...... 66

Table 2.6 Monthly fruit availability for all trees on phenology transects, and monthly fruit consumption by Diana 1, Diana 2, and the pooled Diana monkey group data...... 69

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Table 2.7. Spearman’s rank correlations between mean monthly fruit availability and consumption; bold indicates two-tailed significance at the 0.05 level...... 70

Table 2.8. Number, relative density, and proportion of total basal area of trees in the entire study area and the home range of Diana 1 and 2...... 71

Table 2.9. Food items, their rates of consumption, density, mean DBH, and relative preference (L) for the pooled Diana monkey sample, and both groups. Positive preference values (bold) indicate preferred foods eaten more frequently than their abundance ...... 75

Table 2.10. Studies of the Diana monkey (Cercopithecus diana) and Roloway monkeys

(C. roloway) diet...... 77

Table 2.11. Dietary proportions of the top ten plant species contributing to the diet of

Diana monkeys at Taï in three different studies...... 78

Table 2.12. Activity budgets of Diana monkeys at Taï between 2000-2001, 2004-2009, and 2013-2015 ...... 78

Table 2.13. Intergroup dietary comparisons between guenon groups in the same site. ... 79

Table 3.1. Food site residence time, rate of intake, and the number of individuals within

5m of the focal individual while foraging on different food types (N=1806 focals)...... 108

Table 3.2. Preference, dietary proportion, mean site residence time, mean rate of intake, and mean number of individuals within 5m while foraging on twelve species of ripe fruit.

...... 108

Table 3.3. Mean food site residence time, rate of ingestion, and number of individuals within 5m of the focal individual (± standard deviation) during the long wet season

(April-June), short dry season (July-August), short wet season (September-November),

xvii and the long dry season (December-March). Variables with significant seasonal differences are indicated with an asterisk (*)...... 109

Table 5.1. Mean concentrations of fecal progesterone and fecal glucocorticoids (μg/g fecal dry weight; difference from baseline) when females are pregnant, in early stages of lactation, late stages of lactation, and cycling...... 174

Table 5.2. Intra-individual comparisons of mean fecal progesterone and fecal corticosterone concentrations (μg/g fecal dry weight; difference from baseline) during different reproductive stages ...... 174

Table 5.3 Income vs. Capital Breeders: Diana monkeys’ place on the continuum

[Adapted from Brockman and van Schaik, 2005 and van Noordwijk, 2011] ...... 175

Table 6.1. Mean FGC concentrations of both groups and the entire sample across the entire study period, between July 2013-March 2014, and between May-August 2015. 206

Table 6.2. Pearson’s correlation coefficients (R) between fecal glucocorticoid concentrations and monthly fruit availability, fruit consumption, leaf consumption, leaf availability invertebrate consumption, rates of affiliation, rates of aggression across the entire study period, from July 2013-March 2014, and from May 2015-August 2015, pooling and separating group data...... 207

Table 6.3. Spearman’s correlation coefficients (ρ) of the fecal glucocorticoid concentrations of 19 adult females, and monthly fruit availability, fruit consumption, invertebrate consumption, leaf consumption, leaf availability, rates of affiliation, and rates of agonism...... 208

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Table 6.4. Spearman’s correlation coefficients (ρ) between females’ fecal glucocorticoid concentrations during different reproductive stages and monthly fruit availability, fruit consumption, invertebrate consumption, leaf consumption, and leaf availability...... 209

Table 6.5. Factors in a univariate general linear model testing the main effects of ecological and behavioral variables on FGC concentrations for the pooled data set, Diana

1, and Diana 2...... 210

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List of Figures

Figure 1.1. The general predictions of Wrangham’s [1980] socioecological model of female-bonded primates ...... 14

Figure 1.2. An adult female Diana monkey (Cercopithecus diana) foraging for invertebrates in Côte d'Ivoire's Taï National Park...... 15

Figure 1.3. Distribution of Diana monkeys (Cercopithecus diana) is limited to some primary rainforest in the yellow zone across Liberia, Sierra Leone, Côte d’Ivoire, and

Guinea [From IUCN Red List, April 1 2017]. The red circle indicates the approximate location of my study site in Taï National Park, Côte d’Ivoire...... 16

Figure 1.4. Taï National Park is located in southwestern Côte d’Ivoire (a) in West Africa

(b), about 5 km from the border with Liberia. Research was conducted close to the

Station du CRE de IET near the western border of the park (c)...... 17

Figure 1.5. Example sheet for identifying females in one of my study groups ...... 18

Figure 2.1. Home range of Diana 1 (in yellow) and Diana 2 (in blue), with overlapping territory in green, with the location of the botanical transects and identified and measured trees indicated by colored circles. Blue circles indicate trees in Diana 2’s home range, orange in Diana 1’s, and green in overlapping territory...... 81

Figure 2.2. Distribution of 31 species of feeding trees along transects in the home ranges of Diana 1 and 2. Different colored circles indicate different species...... 82

Figure 3.1. Mean food site residence times of the main foods eaten by Diana monkeys.

...... 111

Figure 3.2. Mean food site residence time of twelve important fruit species consumed by

Diana monkeys. Significant differences are indicated by asterisks (*); preferred fruit species are indicated by a solid bar while non-preferred fruits are indicated by a dashed bar...... 112

Figure 3.3. Mean rate of consumption (per minute) vs. mean food site residence time

(seconds) for the four main food types...... 113

Figure 3.4. Mean rate of consumption (per minute) vs. mean food site residence time

(seconds) for twelve important fruit species...... 113

Figure 3.5. Mean number of individuals within 5 meters of the focal individual while she foraged on different types of food...... 114

Figure 3.6. The mean number of individuals within 5m of the focal animal while she foraged on different fruit species...... 115

Figure 3.7. The proportion of focal observations, per food type, in which the focal animal engaged in social behavior...... 117

Figure 3.9. Monthly contribution of fruit to the diet of Diana monkeys during this study period, and mean monthly fruit availability over the same period...... 117

Figure 3.10. An adult female Diana monkey carrying Sacoglottis gabonensis fruit in her mouth and hand (a) moves to an isolated spot in the understory to eat the fruit she collected (b)...... 118

xxi

Figure 4.1. The reactive scope model, indicating the normal range of fluctuations in physiological responses to stress (“Predictive Homeostasis”) and the impact of stressors

(“Reactive Homeostasis”) [adapted from Romero et al., 2009]...... 143

Figure 4.2. Kumasi in his enclosure at the Tulsa Zoo (courtesy of Pat Murphy)...... 144

Figure 4.3. Corticosterone concentrations of Kumasi, Hoy, and Elvis the week before and after their veterinary exams. The date of their veterinary exam is marked with the red arrow; the black line indicates baseline concentrations...... 145

Figure 4.4. Mean fluctuation in FGC concentrations in the days before, the day of and after, and at least two days after their veterinary exam...... 147

Figure 4.5. Mean FGC concentrations on days where there was no stressful event, and on days when there was a stressful event that day or the previous day...... 148

Figure 4.6. Mean fluctuation from baseline in FGC concentrations from samples collected 1-2 days before, or 2 days after, a stressful event; and collected the day of or the day after a stressful event...... 149

Figure 5.1. Mean fluctuation of fecal progesterone concentrations from baseline during different reproductive stages (Pregnancy, Early Lactation, Late Lactation, and Cycling).

...... 177

Figure 5.2. Mean fluctuation of fecal corticosterone concentrations from baseline during different reproductive stages (Pregnant, Early Lactation, Late Lactation, and Cycling).

...... 178

Figure 5.3. Intra-individual comparisons of fecal progesterone concentrations at different reproductive stages...... 179

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Figure 5.4. Intra-individual comparisons of fecal glucocorticoid concentrations at different reproductive stages...... 180

Figure 5.5. Monthly fruit consumption (green line), fruit availability (purple line), and timing of births (blue stars) in the two Diana monkey groups...... 181

Figure 6.1. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) of Diana groups 1 and 2, during the first (July 2013-March 2014) and second (May-

August 2015) field seasons...... 216

Figure 6.2 Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly fruit availability of Diana 1 from August 2013-March 2014 and May-August

2015...... 232

Figure 6.3. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly fruit availability of Diana 2 between July 2013-March 2014, and May 2015-

August 2015...... 234

Figure 6.4. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly fruit consumption of Diana 1 from August 2013-March 2014 and May-

August 2015...... 236

Figure 6.5. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly fruit consumption of Diana 2 from July 2013-March 2014, and May-August

2015...... 238

Figure 6.6. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly invertebrate consumption of Diana 1 from August 2013-March 2014 and

May-August 2015...... 240

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Figure 6.7. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly invertebrate consumption of Diana 2 from July 2013-March 2014 and May-

August 2015...... 242

Figure 6.8. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly leaf consumption of Diana 1 from August 2013-March 2014 and May-

August 2015...... 244

Figure 6.9. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly leaf consumption of Diana 2 from July 2013-March 2014 and May-August

2015...... 246

Figure 6.10. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly young leaf availability of Diana 1 from August 2013-March 2014 and May-

August 2015...... 248

Figure 6.11. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly leaf availability of Diana 2 from July 2013-March 2014 and May-August

2015...... 250

Figure 6.12. Diana 1’s mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly rate of affiliation from August 2013-March 2014 and May-August

2015...... 252

Figure 6.13. Diana 2’s mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly rate of affiliation from August 2013-March 2014 and May-August

2015...... 254

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Figure 6.14. Diana 1’s mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly rate of aggression from August 2013-March 2014 and May-

August 2015...... 256

Figure 6.15. Diana 2’s mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly rate of aggression from August 2013-March 2014 and May-

August 2015...... 258

Figure 6.16. Mean fecal glucocorticoid concentrations during different reproductive stages...... 260

Figure 6.17. Mean monthly FGC concentrations during (a) pregnancy, (b) early lactation,

Figure 6.18. The reactive scope model of the Diana monkey stress response, indicating the normal range of fluctuations in physiological responses to stress (“Predictive

Homeostasis”) and the impact of stressors such as the presence of predators, reproductive status, fluctuations in food availability, and intergroup encounters...... 265

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Chapter 1: Socioecological models, typical primates, and Diana monkeys

INTRODUCTION

Sociological Models

Classic conceptions of primate social structure correlated group size, morphology, and social behaviors with ecological characteristics: frugivorous species generally live in larger troops than folivorous species [Hall and DeVore, 1965; Crook and Gartlan, 1966;

Struhsaker, 1969; Eisenberg et al., 1972; Clutton-Brock & Harvey, 1977]. However, these classic models neglected the fact that the sexes experience different consequences from local ecology based on their social and reproductive strategies [Trivers, 1972].

Socioecological models attempt to correct this by examining the basic ecological characteristics of primates’ subsistence base, and cascading effects of dietary strategies and ecology on social organization, differentiating between ecological consequences for males and females [Wrangham, 1980; van Schaik, 1989]. These models recognize that males and females have different reproductive strategies: females’ reproductive success relies on their ability to consume enough food to support the energetic requirements of pregnancy, and lactation, while males are limited in their reproductive success by access to reproductively active females [Trivers, 1972]. In these socioecological models, consequences of local ecology are filtered through female behavior in service of their

1 reproductive strategy, and indirectly influence males’ social structure through their responses to females’ interactions with the environment.

Wrangham’s [1980] socioecological model explained the tendency for females to form female philopatric, socially bonded groups by proposing that females accept a degree of intra-group feeding competition in return for the ability to cooperatively out- compete other groups of bonded females, defending group territories. This model (Figure

1.1) predicts that primates relying on spatially continuous, ubiquitous resources (e.g., leaves and foliage) live in groups with loosely bonded females, exhibiting little to no territorial defense and experiencing minimal competition for resources within and between groups. The ubiquity of these resources, and perhaps their low quality, should minimize competition and the need for females to bond together to defend resources from other groups. Conversely, primates relying on discontinuous, patchily distributed resources (e.g., ripe fruit) are predicted to live in groups where females exhibit strong intragroup social bonds, actively defend food patches, and experience competition for resources within and between groups. Because these high quality, defensible resources provoke competition between individuals and groups, females form social bonds to defend those patches against other groups of socially bonded females.

Wrangham’s model has been refined and extended since its original publication in growing recognition of the more complex and less dichotomous relationship between resource distribution and sociality [e.g., van Schaik 1983, 1989; Isbell, 1991; Sterck et al., 1997]. For instance, van Schaik [1983] proposed that primate group sizes were a compromise between the need to reduce the risk of predation (favoring larger groups) and

2 minimize intra-group resource competition (favoring smaller groups). This model still derives social dynamics (e.g., dominance hierarchies) through the balance of competition within and between groups [van Schaik, 1989]. If between-group competition is intense, females should maintain relatively egalitarian within-group relationships – otherwise subordinates, who would lose out to dominant females in competitive interactions, would leave the group [van Schaik, 1989]. Intensive within group competition, by contrast, promotes more despotic social hierarchies.

Isbell [1991] found that generally, in taxa where intergroup aggression between females occurs, home ranges tend to increase as groups increase in size, and that among taxa with strong female dominance hierarchies, day ranges tend to increase as groups increase in size. She suggests that, “When resources are limiting in abundance, females should be aggressive toward other groups regardless of the distribution of resources, but they should be aggressive within groups only when those limiting resources are clumped”

(150). Therefore, when females are limited by their resources, and these resources are clumped, we should expect inter- and intra-group aggression, dominance hierarchies, and increased home range and group size as group sizes increase. Sterck and colleagues

[1997] summarized these models by categorizing variation in females primates’ social relationships within and between groups along three axes: egalitarian-despotic, individualistic-nepotistic, and tolerance-aggression.

These socioecological models have been thoroughly critiqued in the intervening years since their development [e.g., Rowell, 1993; Thierry, 1997; Thierry, 2008; Clutton-

Brock and Janson, 2012]. In addition to the above refinements and extensions, further

3 variables such as infanticide risk and dispersal have been added to clarify and improve predictive models [Isbell and Young, 2002]. However, there are fears that relying on these socioecological models limits the scope of research on wild primates; that these heuristics have outlived their usefulness and are stymying new and exciting research on primate socioecology [Thierry, 2008]. Though some researchers propose giving up “the lost dream of ecological determinism,” others argue that socioecological models provide a useful starting point for testable hypotheses about primate ecology and behavior

[Thierry, 2008; Koenig and Borries, 2009; Clutton-Brock and Janson, 2012].

Looking Beyond the “Typical Primate”

It is from the latter perspective that I begin my dissertation research. Though current iterations of socioecological models cannot thoroughly explain the complexities of feeding ecology and social relationships, most research from this perspective confirms that resource distribution, diet composition, and dietary selection are fundamental to understanding the social relationships of female bonded primates [Koenig and Borries,

2009; Clutton-Brock and Janson, 2012]. These models, therefore, provide a starting point for developing hypotheses about female feeding ecology, reproduction, and sociality

[Wrangham, 1980; van Schaik, 1989; Sterck et al., 1997; Isbell and Young, 2002]. This is particularly useful in taxa whose behavior or ecology are poorly known because the models provide a testable baseline of expectations for the relationship between sociality and ecology. Considering the narrow scope of research on primate behavioral ecology when Wrangham developed his model relative to the vast phylogenetic, ecological, and social diversity of primates, it is clear that there are many open questions regarding the

4 application of these models to primates who are not baboons, macaques, or chimpanzees

[Wrangham, 1980; Strier, 1994]. Even critiques of this tendency focus primarily on baboons and macaques as representative of cercopithecines, to the exclusion of forest- dwelling papionins and guenons [Strier, 1994].

Indeed, “for a long time, African guenons were, together with the New World

Monkeys, the left-overs of the primate world… This is indeed an undeserved judgment, as most members of supergenus Cercopithecus are graceful animals; far from looking ugly or dull, some of them even rank among the most elegant and colourful monkeys”

[Gautier-Hion et al., 1988a: 1]. The guenons are not only elegant and colorful, but their broad distribution across the African continent, tendency to form polyspecific associations with sympatric guenons, and fruit-rich diets make them a particularly interesting genus in which to examine the evolution of primate sociality and ecology

[Gautier-Hion, 1988; Rowell, 1988b; Butynksi, 1990, 2002; Chapman et al., 2002]. This is particularly relevant because the primate radiation originated and diversified in arboreal niches in tropical rainforest environments, and old world monkeys and apes evolved in primate communities in tropical rainforests [e.g., Bown et al., 1982; Bloch and

Boyer, 2002; Rose, 2006].

The Guenons

The guenons comprise the monkeys of the tribe Cercopithecini: members of the genera Allenopithecus Cercopithecus, Chlorocebus, Erythrocebus, and Miopithecus, organized in between twenty-three and thirty-six species [Glenn and Cords, 2002; Grubb et al., 2002]. The Cercopithecini, like the papinons (macaques, baboons, mangabeys,

5 mandrills), are in the subfamily Cercopithecinae [Butynski, 2002]. Like all cercopithecines, the guenons have cheek pouches made of specialized, amylase-secreting glandular tissue that they use to store food, particularly when feeding on contestible foods or when predation risk is elevated [Lambert, 2005; Buzzard, 2006a]. The Cercopithecini, however, are distinguished from the Papionini by their four-cusped third lower molar which lacks a hypoconulid, and by their diploid chromosome number (always greater than 42 for the Cercopithecini; always 42 for the Papioinini) [Groves, 2001; Butynski,

2002].

The guenons are a widespread group, ranging across sub-Saharan Africa from

Mauritania to South Africa; from Senegal to Ethiopia [Butynski, 2002]. They are found in a diversity of habitats; from savannah woodlands and arid desert edges to swamp and mangrove forests, and tropical and montane rainforests [Butynski, 2002]. While the guenons are generally arboreal, semiterrestrial and terrestrial adaptations are also relatively common (e.g., patas monkeys, Erythrocebus; l’Hoesti’s monkey,

Cercopithecus lhoesti) and there are even some guenons who swim (Allen’s swamp monkeys, Allenopithecus nigroviridis; talapoin monkeys, Miopithecus) [Mcgraw, 2002].

The guenons can be broadly characterized as frugivorous, but supplement their diets with arthropods, foliage, and a diversity of other food items including gum, flowers, mushrooms, eggs, and pith [Gautier-Hion, 1988; Chapman et al., 2002].

Research on the behavior, ecology, and endocrinology of the guenons has especially focused on the blue monkeys (Cercopithecus mitis stuhlmanni) and redtail monkeys (C. ascanius schmidti) in East African forests including Kakamega, Kenya, and

Kibale, Uganda [e.g., Buxton, 1952; Haddow, 1952; Marler, 1973; Struhsaker, 1977;

Rudran 1978; Cords, 1984, 1986, 1987; Rowell, 1988a; Struhsaker, 1988; Butynski,

1990; Lambert, 1999; Chapman et al., 2005; Pazol and Cords, 2001; Cords and

Chowdhury, 2010; Foerster et al., 2012]. Among the many insights this research has yielded is recognition of the vast capacity for intra-specific variation in diet, behavior, and social organization among the guenons [Gautier-Hion et al., 1988b; Rowell, 1988b,

1993; Chapman et al., 2002; Glenn and Cords 2002]. Research on Kenyan blue monkeys

(C. m. stuhlmanni, C. m. albogularis) has also highlighted areas where forest-dwelling guenons conform to or diverge from behaviors predicted by socioecological models. For example, female blue monkeys are more frequent participants in intergroup territorial encounters than males, as sociecological models predict [Cords, 2007]. However, higher- ranking females participated more frequently than lower-ranking females, a finding unexplained by socioecological models [Cords, 2007]. Similarly, while higher-ranking females had preferential access to ripe fruit, as predicted by socioecological models, higher ranking females did not consistently have lower concentrations of stress hormones

[Foerster et al., 2011]. Socioecological models predict some aspects of blue monkey social behavior and feeding ecology, but cannot account for many of their behavioral nuances.

Long-term research on East African guenons is complemented by work in West

African forests, including Lopé and Mokokou, Gabon [Gautier and Gautier-Hion, 1969;

Gautier-Hion, 1975, 1980; Gautier-Hion et al., 1981, 1983; Tutin et al., 1997], Tiwai,

Sierra Leone [Whitesides, 1989; Oates and Whitesides, 1990; Hill, 1994; Stephan and

Zuberbühler, 2008], and the Taï Forest, Côte d’Ivoire [Galat and Galat-Luong, 1985;

McGraw et al., 2007]. However, research on these taxa has focused primarily on aspects of feeding ecology, morphology, and cognition. Consequently, what we know about guenon socioecology and social behavior is derived primarily from the East African guenons. Some behaviors commonly observed among East African red-tail and blue monkeys, including male influxes, linear dominance hierarchies, and hybrid social groups, are yet to be reported from West or Central Africa [Cords, 2000a, 2000b;

Detwiler, 2002; Buzzard and Eckardt, 2007; Candiotti et al., 2015; Klass and Cords,

2015]. The socioecology of West and Central African guenons studied to date seems to differ from East African guenons, underscoring the flexibility of these taxa. This also suggests that a broader understanding of guenon socioecology can help untangle the relationship between behavior and ecology in female-bonded primates.

The Diana Monkeys

Diana monkeys (Cercopithecus diana diana), like the East African guenons studied to date, are female-bonded primates eating large amounts of ripe fruit (Figure 1.2)

[Buzzard, 2006; Buzzard and Eckardt, 2007; Candiotti et al., 2015]. They are noisy, conspicuous, and notably charismatic and elegant [Butynski, 1988; McGraw and

Zuberbühler, 2007]. Diana monkeys are generally restricted to Ivorian, Liberian, and

Sierra Leonean primary rainforests with closed, continuous canopies, perhaps as a consequence of their fruit-rich diet (Figure 1.3) [Booth, 1956, 1958; Oates, 1988;

Whitesides, 1989; McGraw and Zuberbühler, 2007; Kane and McGraw, in review].

Closely related Roloway monkeys (until recently, C. diana roloway, now C. roloway) are

8 found to the east of the Sassandra river in Côte d’Ivoire and Ghana; Diana monkeys are found only to the west of this river [McGraw and Zuberbühler, 2007; Koné et al., 2017].

Because of their limited distribution, Diana monkeys are considered vulnerable with decreasing populations across their range, and endangered within Côte d’Ivoire

[McGraw, 2007; Bi et al., 2012; Oates, 2016]. Diana monkeys exhibit female philopatry, living in one-male units with multiple related females in groups that average 24 individuals [Buzzard and Eckardt, 2007]. Though Diana monkeys are sexually dimorphic, females have canines that are larger than expected for their body size [Oates et al., 1990; McGraw et al., 2002].

Diana monkeys in Tiwai Island, Sierra Leone, and the Taï Forest are nearly always found in mixed-species associations with other monkeys [Whitesides, 1989; Oates and Whitesides, 1990; Bshary and Noe, 1997b; Korstjens et al., 2002; Buzzard, 2004].

When participating in mixed-species groups, Diana monkeys dominate the other guenons present. They expand their strata use and consume as much or more fruit when they are in association, as when they are on their own [Wolters and Zuberbühler, 2003; Eckardt and

Zuberbühler, 2004; Buzzard 2006a, 2006b, 2010; Kane and McGraw, in review]. They are found at higher densities and in larger groups than sympatric guenons, with lower rates of intra-group affiliation, higher rates of intra-group agonism, and higher rates of inter-group encounters than the other guenon species in Taï [Buzzard and Eckardt, 2007].

Female Diana monkeys have also been observed engaging in lethal coalitionary violence, attacking and killing a stranger female with their relatively large canines [McGraw et al.,

2002]. Furthermore, female Diana monkeys are the primary participants in territorial

9 defense; males are peripheral to these intergroup encounters and indeed peripheral to group behavior more generally [Hill, 1994; McGraw et al., 2002; Buzzard and Eckardt,

2007; Candiotti et al., 2015]. However, female Diana monkeys maintain differentiated social bonds through preferences in grooming and proximity, though there is no evidence that kinship drives these preferences [Candiotti et al., 2015].

This Study

What we know about Diana monkeys suggests that they exemplify many of the broad predictions laid out by socioecological models. They are female-bonded primates consuming patchily distributed resources, engaging in relatively frequent intra- and intergroup competitive interactions, forming polyspecific associations to cope with predation pressure [Wachter et al. 1997; McGraw et al., 2002; Wolters and Zuberbühler, 2003;

Eckardt and Zuberbühler, 2004; Buzzard 2004; Buzzard and Eckardt, 2007; Kane and

McGraw, under review]. This study takes the predictions of socioecological models as a starting point in order to examine the consequences of Diana monkeys’ fruit-rich diet on their social behavior, reproduction, and physiology.

To do this, I collected data on Diana monkey socioecology from July 2013-

August 2015 in the study grid of the Taï Monkey Project in Côte d’Ivoire’s Taï National

Park (Figure 1.4). Taï National Park has been protected in some form since 1927, but remains an area of significant conservation concern due to the pressures of a growing human population around the park and associated activities including illegal poaching, logging, forest clearing, and mining [Refisch and Koné, 2005]. Monkeys in the Taï Forest have been the focus of research on behavior and ecology since the mid-1970s [Galat and

Galat-Luong, 1985]. With the inception of the Taï Monkey Project, founded by Ronald

Noë and Bettie Sluijter in 1989, research on the socioecology of these monkeys focused on a study grid located near the field station of the Institute d’Ecologie Tropicale about

20 km from the western border of Taï National Park (Figure 1.4) [McGraw and

Zuberbühler, 2007a]. Monkeys in the study grid have been under regular observation since 1989 through the Taï Monkey Project [McGraw et al., 2007]. The forest is home to eight species of monkeys: four guenons, three colobines (Piliocolobus badius,

Procolobus verus, and Colobus polykymos), and one mangabey (Cercocebus atys). The primate community in Taï also includes Pan troglodytes verus, the Western subspecies of the common chimpanzee, and several prosimians: Perodicticus potto and Galago demidoff [McGraw et al., 2007].

Intensive research on the four guenons – Diana monkeys (Cercopithecus diana),

Campbell’s monkeys (C. campbelli), lesser spot-nosed guenons (C. petaurista) and putty- nosed guenons (C. nictitans) – began in 1991 with the habituation of Diana monkeys to examine their participation in mixed-species associations [Bshary and Noë 1997a, 199b;

Noë and Bshary, 1997; McGraw and Zuberbühler, 2007a]. Much of the work that has been done in the Taï Forest has focused on the formation, maintenance, and function of polyspecific associations between Diana monkeys and other monkeys, including red colobus monkeys [Holenweg et al., 1996; Bshary and Noë 1997a, 1997b; Noë and

Bshary, 1997; Kane and McGraw, in revision], sooty mangabeys [McGraw and Bshary,

2002], and sympatric guenons [Wolters and Zuberbühler, 2003; Eckardt and Zuberbühler,

2004; Buzzard 2004; 2006a, 2006b, 2010; Kane and McGraw, in review]. Other research

11 on the Taï guenons includes work on locomotor and positional behavior [McGraw, 1996,

1998; Bitty and McGraw, 2007], anti-predator strategies, vocalizations, and cognition

[Zuberbühler et al., 1997, 1999; Zuberbühler, 2000a, 200b; Bshary, 2001; Kone and

Refisch, 2007; Arnold and Zuberbühler, 2008; Ouattara et al., 2009; Coye et al., 2016;

Stephan and Zuberbühler 2016], and sociality [Buzzard and Eckardt, 2007; Candiotti et al., 2015]. Research at Taï over the past 30 years has shown that socioecological models provide a useful set of expectations for the relationship between sociality and resource distribution, but that divergence from these models are to be expected [McGraw and

Zuberbühler, 2008].

Working with Frederic Gnépa, Ferdinand Belé, Roman Djobely, Gerard Gah, and

Paterson Kalo, I collected systematic data on feeding ecology, social behavior, food availability and habitat composition of two adjacent habituated groups of Diana monkeys, and opportunistic data on social behavior, intergroup dynamics, and fecal samples from adult females. All adult females were identifiable based on tail shape, nipple size, and/or vocalizations (Figure 1.5). Data on social behavior and feeding ecology were collected during all-day group follows lasting from approximately 7:00-17:00; data on food availability and habitat composition were collected during twice-monthly phenological sampling along an established fruit trail and botanical censuses I conducted through the study grid [Chapman et al., 1994].

I predicted that Diana monkeys’ diets vary over the course of the year and between groups; that Diana monkeys experience more intra-group competition and aggression while eating more patchily distributed, monopolizeable resources; that Diana

12 monkeys time reproduction for periods when food is most abundant, and that they experience metabolic and social stress when fruit availability is lowest. In chapter 2, I report the diet of two adjacent groups of Diana monkeys in relation to forest composition and food availability in order to understand how seasonal fluctuations in food availability relate to feeding ecology, and whether there are observable disparities between groups. In chapter 3, I assess Diana monkeys’ social behavior during feeding in order to examine how feeding on foods of different values and preferences affect within-group dynamics.

Specifically, I examine the assertion that foods that are easier to monopolize will elicit stronger within-group competition than ubiquitously distributed foods. In chapter 4, I validate non-invasive methods to monitor fecal metabolites of glucocorticoids in wild

Diana monkeys, and determine whether acute stressors such as intergroup encounters and the presence of predators result in elevated concentrations of glucocorticoids. In chapter

5, I validate non-invasive endocrine methods for monitoring Diana monkeys’ reproductive status, and I assess females’ reproductive strategies to determine whether the timing of reproduction is correlated with seasonal shifts in food availability. In chapter 6, I examine whether diet, food availability, reproduction, and social dynamics impact glucocorticoid concentrations in order to determine whether Diana monkeys experience pathological levels of stress, and whether all groups and individuals cope with variation in these independent variables in the same way. Finally, in Chapter 7 I synthesize these findings, evaluate them light of the predictions of socioecological models, and discuss directions for future research.

FIGURES

Food Distribution

Not defensible Defensible Continuous, ubiquitous Patchy, discontinuous (e.g., leaves) (e.g., ripe fruit)

Minimally bonded females Socially bonded females

No territorial defense of Territorial defense of food food patches patches

Minimal competition within Competition within and and between groups between groups

Figure 1.1. The general predictions of Wrangham’s [1980] socioecological model of female-bonded primates.

2. Figure 1.2. An adult female Diana monkey (Cercopithecus diana) foraging for invertebrates in Côte d'Ivoire's Taï National Park. Photo by Erin Kane.

3. Figure 1.3. Distribution of Diana monkeys (Cercopithecus diana) is limited to some primary rainforest in the yellow zone across Liberia, Sierra Leone, Côte d’Ivoire, and Guinea [From IUCN Red List, April 1 2017]. The red circle indicates the approximate location of my study site in Taï National Park, Côte d’Ivoire.

a. b.

4. Figure 1.4. Taï National Park is located in southwestern Côte d’Ivoire (a) in West Africa (b), about 5 km from the border with Liberia. Research was conducted close to the Station du CRE de IET near the western border of the park (c).

5. Figure 1.5. Example of an identification sheet for females in Diana 2, noting the unique physical characteristics I used to identify females, including tail shape, nipple shape and size, vocalizations, and pelage characteristics.

REFERENCES

Arnold K, Zuberbühler K. 2008. Meaningful call combinations in a non-human primate. Current Biology 18: R202-R203. Bi GS, Koné I, Bitty AE, Koffie JCB, Akpatou B, Zinner D. 2012. Distribution and conservation status of catarrhine primates in Côte d’Ivoire (West Africa). Folia Primatologica 83: 11-23. Bitty EA, McGraw WS. 2007. Locomotion and habitat use of Stamplfii’s putty-nosed monkey (Cercopithecus nictitans stampflii) in the Taï National Park, Ivory Coast. American Journal of Physical Anthropology 134: 383-391. Booth AH. 1956. The Cercopithecidae of the Gold and Ivory Coast: geographic and systematic observations. Annals and Magazine of Natural History, 9th Series 9: 476- 480. Booth AH. 1958. The zoogeography of West African primates: a review. Bulletin de l’Institut Français d’Afrique Noire 20: 587-622. Bown TM, Kraus MJ, Wing SL, Fleagle JG, Tifney BH, Simons EL, Vondra CF. 1982. The Fayum primate forest revisited. Journal of Human Evolution 11: 603-632.

Bshary R. 2001. Diana monkeys, Cercopithecus diana, adjust their anti-predator response behaviour to human hunting strategies. Behavioral Ecology and Sociobiology 50: 251-256. Bshary R, Noë R. 1997a. Anti-predation behavior of red colobus monkeys in the presence of chimpanzees. Behavioral Ecology and Sociobiology 41: 321-333. Bshary R, Noë R. 1997b. Red colobus and Diana monkeys provide mutual protection against predators. Animal Behavior 54: 1461-1474. Butynski TM. 1990. Comparative ecology of blue monkeys (Cercopithecus mitis) in high- and low-density subpopulations. Ecological Monographs 60: 1-26. Butynski TM. 2002. The guenons: an overview of diversity and taxonomy. In, Glenn ME, Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. Chicago: University of Chicago Press. 3-13. Buxton AP. 1952. Observations on the diurnal behaviour of the redtail monkey (Cercopithecus ascanius schmidti Matschie) in a small forest in Uganda. Journal of Animal Ecology 21: 25-58. Buzzard PJ. 2004. Interspecific competition among Cercopithecus campbelli, C. petaurista, and C. diana at Taï Forest, Côte d’Ivoire. PhD Dissertation: Columbia University.

Buzzard PJ. 2006a. Cheek pouch use in relation to interspecific competition and predator risk for three guenon monkeys (Cercopithecus spp.). Primates 47: 336-341. Buzzard PJ. 2006b. Ecological partitioning of Cercopithecus campbelli, C. petaurista, and C. diana in the Taï Forest. International Journal of Primatology 27: 529-558. Buzzard PJ. 2006c. Ranging patterns in relation to seasonality and frugivory among Cercopithecus campbelli, C. petaurista, and C. diana in the Taï Forest. International Journal of Primatology 27: 559-573. Buzzard PJ. 2010. Polyspecific associations of Cercopithecus campbelli and C. petaurista with C. diana: what are the costs and benefits? Primates 51: 307-314. Buzzard PJ, Eckardt W. 2007. The social systems of the guenons. In, McGraw WS, Zuberbühler K, Noë R, eds. Monkeys of the Taï Forest: An African Primate Community. Cambridge: Cambridge University Press. 51-71. Candiotti A, Coye C, Ouattara K, Petit EJ, Vallet D, Zuberbühler K, Lemasson A. 2015. Female bonds and kinship in forest guenons. International Journal of Primatology 36: 332-352. Chapman CA, Wrangham RW, Chapman LJ. 1994. Indices of habitat-wide fruit avundance in tropical forests. Biotropica 26: 160-171. Chapman CA, Chapman LJ, Cords M, Gathua JM, Gautier-Hion A, Lambert JE, Rode K, Tutin CEG, White LJT. 2002. Variation in the diets of Cercopithecus species: differences within forests, among forests, and across species. In, Glenn ME, Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. Chicago: University of Chicago Press. 325-350. Chapman CA, Struhsaker TT, Lambert JE. 2005. Thirty years of research in Kibale National Park, Uganda, reveals a complex picture for conservation. International Journal of Primatology 26: 539-555. Clutton-Brock TH, Harvey PH. 1977. Primate ecology and social organization. Journal of Zoology 183: 1-39. Clutton-Brock T, Janson C. 2012. Primate socioecology at the crossroads: past, present, and future. Evolutionary Anthropology 21: 136-150. Cords M. 1984. Mating patterns and social structure in redtail monkeys (Cercopithecus ascanius). Zeitschrift für Tierpsychologie 64: 313-339. Cords M. 1986. Interspecific and intraspecific variation in diet of two forest guenons, Cercopithecus ascanius and C. mitis. Journal of Animal Ecology 55: 811-827. Cords M. 1987. Mixed species association of Cercopithecus monkeys in the Kakamega Forest, Kenya. University of California Publications in Zoology 117: 1-109. 20

Cords M. 2000a. Agonistic and affiliative relationships in a blue monkey group. In, Whitehead PF, Jolly CJ, eds. Old World Monkeys. Cambridge: Cambridge University Press. 453-479. Cords M. 2000b. The number of males in guenon groups. In, Kappeler PM, ed. Primate males: causes and consequences of variation in group composition. Cambridge: Cambridge University Press. 84-96. Cords M. 2007. Variable participation in the defense of communal feeding territories by blue monkeys in the Kakamega Forest, Kenya. Behaviour 144: 1537-1550. Cords M, Chowdhury S. 2010. Life history of Cercopithecus mitis stuhlmanni in the Kakamega Forest, Kenya. International Journal of Primatology 31: 433-455. Coye C, Zuberbühler K, Lemasson A. 2016. Morphological structured vocalizations in female Diana monkeys. Animal Behaviour 115: 97-105. Crook JH, Gartlan JS. 1966. Evolution of primate societies. Nature 210: 1200-1203. Detwiler KM. 2002. Hybridization between red-tailed monkeys (Cercopithecus ascanius) and blue monkeys (C. mitis) in East African forests. In, Glenn ME, Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. Chicago: University of Chicago Press. 79-97. DeVore I. 1965. Primate Behavior: Field Studies of Monkeys and Apes. New York: Holt, Rinehart, and Winston. Eckardt W, Zuberbühler K. 2004. Cooperation and competition in two forest monkeys. Behavioral Ecology 15: 400-411. Eisenberg JF, Muckenhirn NA, Rudran R. 1972. The relationship between ecology and social structure in primates. Science 176: 873-874. Foerster SF, Cords M, Monfort SL. 2011. Social behavior, foraging strategies, and fecal glucocorticoids in female blue monkeys (Cercopithecus mitis): potential fitness benefits of high rank in a forest guenon. American Journal of Primatology 73: 870- 882. Foerster SF, Cords M, Monfort SL. 2012. Seasonal energetic stress in a tropical forest primate: proximate causes and evolutionary implications. PLoS ONE 7: e50108. Galat G, Galat-Luong A. 1985. La communauté de primates diurnes de la forêt de Taï, Côte d’Ivoire. La Terre et la Vie 40: 3-32. Gautier JP, Gautier-Hion A. 1969. Les associations polyspecifiques chez les cercopithecidae du Gabon. La Terre et La Vie 2: 164-201.

Gautier-Hion A. 1975. Dimorphisme sexuel et organization sociale chez les cercopithecines forestiers Africains. Mammalia 39: 365-374. Gautier-Hion A. 1980. Seasonal variations of diet related to species and sex in a community of Cercopithecus monkeys. Journal of Animal Ecology 49: 237-269. Gautier-Hion A. 1988. The diet and dietary habits of forest guenons. In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J. 1988a. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J. 1988b. General introduction: why study African guenons? In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. 1-3. Gautier-Hion A, Gautier JP, Quris R. 1981. Forest structure and fruit availability as complementary factors influencing habitat use by a troop of monkeys (Cercopithecus cephus). La Terre et La Vie 35: 511-536. Gautier-Hion A, Quris R, Gautier JP. 1983. Monospecific vs. polyspecific life: a comparative study of foraging and antipredatory tactics in a community of Cercopithecus monkeys. Behavioral Ecology and Sociobiology 12: 325-335. Glenn ME, Cords M. 2002. The Guenons: Diversity and Adaptation in African Monkeys. Chicago: University of Chicago Press. Groves CP. 2001. Primate Taxonomy. Smithsonian Institution Press, Washington, DC. Haddow AJ. 1952. Field and laboratory studies on an African monkey, Cercopithecus ascanius schmidti Matschie. Proceedings of the Zoological Society of London 122: 297-394. Hill CM. 1994. The role of female Diana monkeys, Cercopithecus diana, in territorial defence. Animal Behaviour 47: 425-431. Holenweg AK, Noë R, Schabel M. 1996. Waser’s gas model applied to associations between red colobus and Diana monkeys in the Taï National Park, Ivory Coast. Folia Primatologica 67: 125-136. Isbell LA. 1991. Contest and scramble competition: patterns of female aggression and ranging behavior among primates. Behavioral Ecology 2: 143-155.

Isbell LA, Young TP. 2002. Ecological models of female social relationships in primates: similarities, disparities, and some directions for future clarity. Behaviour 139: 177- 202. Klass K, Cords M. 2015. Agonism and dominance in female blue monkeys. American Journal of Primatology 1299-1315. Koenig A, Borries C. 2009. The lost dream of ecological determinism: time to say goodbye? ... Or a White Queen’s proposal? Evolutionary Anthropology 18: 166-174. Koné I, Gonedelé Bi S, Osei D, Wiafe E, Dempsey A, McGraw WS, Oates JF. 2017. Cercopithecus roloway. IUCN 2017, IUCN Red List of Threatened Species. Koné I, Refisch J. 2007. Can monkey behavior be used as an indicator for poaching pressure? A case study of the Diana guenon (Cercopithecus diana) and the western red colobus (Procolobus badius) in the Taï National Park. In, McGraw WS, Zuberbühler K, Noë R, eds. The Monkeys of the Taï Forest: an African Primate Community. Cambridge: Cambridge University Press. 257-289.126: 183-192. Korstjens AH, Sterck EHM, Noë R. 2002. How adaptive or phylogenetically inert is primate social behavior? A test with two sympatric colobines. Behaviour 139: 203- 225. Lambert JE. 1999. Seed handing in chimpanzees (Pan troglodytes) and redtail monkeys (Cercopithecus ascanius): implications for understanding hominoid and cercopithecine fruit-processing strategies and seed dispersal. American Journal of Physical Anthropology 109: 365-386. Lambert JE. 2005. Competition, predation, and the evolutionary significance of the Cercopithecine cheek pouch: the case of Cercopithecus and Lophocebus. American Journal of Physical Anthropology 126: 183-192. Marler P. 1973. A comparison of vocalizations of red-tailed monkeys and blue monkeys, Cercopithecus ascanius and C. mitis, in Uganda. Zeitschrift für Tierpsychologie 33: 223-247. McGraw WS. 1996. Cercopithecid locomotion, support use, and support availability in the Taï Forest, Ivory Coast. American Journal of Physical Anthropology 100: 507- 522. McGraw WS. 1998. Comparative locomotion and habitat use of six monkeys in the Taï Forest, Ivory Coast. American Journal of Physical Anthropology 105: 493-510. McGraw WS. 2007. Vulnerability and conservation of the Taï monkey fauna. In, McGraw WS, Zuberbühler K, Noë R, eds. The Monkeys of the Taï Forest: an African Primate Community. Cambridge: Cambridge University Press. 290-316.

McGraw WS, Bshary R. 2002. Association of terrestrial mangabeys (Cercocebus atys) with arboreal monkeys: experimental evidence for the effects of reduced ground predator pressuer on habitat use. International Journal of Primatology 23: 311-325. McGraw WS, Plavcan JM, Adachi-Kanazawa KA. 2002. Adult female Cercopithecus diana employ canine teeth to kill another adult female C. diana. International Journal of Primatology 23: 1301-1308. McGraw WS, Zuberbühler K. 2007. The monkeys of the Taï Forest: an introduction. In, McGraw WS, Zuberbühler K, Noë R, eds. The Monkeys of the Taï Forest: an African Primate Community. Cambridge: Cambridge University Press. 1-48. Noë R, Bshary R. 1997. The formation of red colobus-Diana monkey associations under predation pressure from chimpanzees. Proceedings of the Royal Society of Biological Sciences 264: 253-259. Oates JF. 1988. The distribution of Cercopithecus monkeys in West African forests. In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. 79-103. Oates JF, Gippoliti S, Groves CP. 2016. Cercopithecus diana. The IUCN Red List of Threatened Species 2016: e.T425A92376689. Oates JF, Whitesides GH. 1990. Associations between olive colobus (Procolobus verus), Diana guenons (Cercopithecus diana), and other forest monkeys in Sierra Leone. American Journal of Primatology 21: 129-146. Oates JF, Whitesides GH, Davies AG, Waterman PG, Green SM, Dasilva GL, Mole S. 1990. Determinants of variation in tropical forest primate biomass: new evidence from West Africa. Ecology 71: 328-343. Ouattara K, Lemasson A, Zuberbühler K. 2009. Anti-predator strategies of free-ranging Campbell’s monkeys. Behaviour 146: 1687-1708. Pazol K, Cords M. 2005. Seasonal variation in feeding behavior, competition, and female social relationships in a forest dwelling guenon, the blue monkey (Cercopithecus mitis stuhlmanni), in the Kakamega Forest, Kenya. Behavioral Ecology and Sociobiology 58: 566-577. Rowell TE. 1988a. Beyond the one-male group. Behaviour 104: 189-201. Rowell TE. 1988b. The social system of guenons, compared with baboons, macaques, and mangabeys. In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. 439-451.

Rowell TE. 1993. Reification of social systems. Evolutionary Anthropology 2: 135-137. Rudran R. 1978. Socioecology of the blue monkeys (Cercopithecus mitis stuhlmanni) of the Kibale Forest, Uganda. Smithsonian Contributions to Zoology 249: 1-88. Stephan C, Zuberbühler K. 2008. Predation increases acoustic complexity in primate alarm calls. Biology Letters 4: 641-644. Stephan C, Zuberbühler K. 2016. Social familiarity affects Diana monkey (Cercopithecus diana diana) alarm call responses in habitat-specific ways. Royal Society Open Science 3: 150639. Sterck EHM, Watts DP, van Schaik CP. 1997. The evolution of female social relationships in nonhuman primates. Behavioral Ecology and Sociobiology 41: 291- 309. Strier K. 1994. The myth of the typical primate. Yearbook of Physical Anthropology 37: 233-271. Struhsaker TT. 1969. Correlates of ecology and social organization among African cercopithecines. Folia Primatologica 11: 80-118. Struhsaker TT. 1977. Infanticide and social organization in the redtail monkeys (Cercopithecus ascanius schmidti) in the Kibale Forest, Uganda. Ethology 45: 75-84. Struhsaker TT. 1988. Male tenure, multi-male influxes, and reproductive success in redtail monkeys (Cercopithecus ascanius). In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. 340-363. Thierry B. 1997. Adaptation and self-organization in primate societies. Diogenes 180: 39- 71. Thierry B. 2008. Primate socioecology, the lost dream of ecological determinism. Evolutionary Anthropology 17: 93-96. Trivers RL. 1972. Parental investment and sexual selection. In, Campbell B, ed. Sexual Selection and the Descent of Man 1871-1971. Chicago: Aldine Press. 139-179. Tutin CEG, Ham RM, White LJT, Harrison MJS. 1997. The primate community of the Lopé Reserve, Gabon: diets, responses to fruit scarcity, and effects on biomass. American Journal of Primatology 42: 1-24. Van Schaik CP. 1983. Why are diurnal primates living in groups? Behaviour 87: 120- 144. Van Schaik CP. 1989. The ecology of social relationships amongst female primates. In, Standen V, Foley RA, eds. Comparative Socioecology: The Behavioural Ecology of Humans and Other Mammals. Oxford: Blackwell Scientific Publications. 195-218. 25

Wachter B, Schabel M, Noë R. 1997. Diet overlap and polyspecific associations of red colobus and Diana monkeys in the Taï National Park, Ivory Coast. Ethology 103: 514-526. Whitesides GH. 1989. Interspecific associations of Diana monkeys, Cercopithecus diana, in Sierra Leone, West Africa: biological significance or chance? Animal Behavior 37: 760-776. Wrangham RW. 1980. An ecological model of female-bonded primate groups. Behaviour 75: 262-300. Wolters S, Zuberbühler K. 2003. Mixed-species associations of Diana and Campbell’s monkeys: the costs and benefits of a forest phenomenon. Behaviour 140: 371-385. Zuberbühler K. 2000a. Causal knowledge of predators’ behavior in wild Diana monkeys. Animal Behaviour 59: 209-220. Zuberbühler K. 2000b. Interspecies semantic communication in two forest primates. Proceedings of the Royal Society of London B: Biological Sicences 267: 713-718. Zuberbühler K, Jenny D, Bshary R. 1999. The predator deterrence function of primate alarm calls. Ethology 105: 477-490. Zuberbühler K, Noë R, Seyfarth RM. 1997. Diana monkey long-distance calls: messages for conspecifics and predators. Animal Behaviour 53: 589-604.

Chapter 2: Dietary Variation in Diana Monkeys

INTRODUCTION

Much of what we know about the relationship between primate sociality and ecology comes from work on a few cercopithecine species living in terrestrial and open habitats, particularly baboons, macaques, and vervet monkeys [e.g., Altmann, 1980;

Strier, 1994; Isbell and Pruetz, 1998]. These species are typically female-philopatric, with males dispersing from their natal groups and females forming social bonds along matrilines [Cords, 2011]. In these taxa, females tend to maintain formal linear dominance hierarchies through dyadic agonistic encounters, female offspring tend to inherit their place in the dominance hierarchy from their mothers, within-group competition between females for access to resources tends to be significant, and between-group competition tends to be minimal [Sterck et al., 1997]. By contrast, the few arboreal and forest- dwelling cercopithecines whose sociality has been studied in depth display a resident- egalitarian social structure generally lacking strict linear female dominance hierarchies, but maintaining strong competition between groups [Cords, 1987; Rowell, 1988; Sterck et al., 1997; Foerster et al. 2011; Candiotti et al., 2015; Klass and Cords, 2015].

Inattention to arboreal and forest-dwelling cercopithecines makes it challenging to tease apart the relationship between ecology and sociality in more complex forest ecosystems.

The ecological pressures on open-habitat and terrestrial cercopithecines are very different from those on arboreal, forest-dwelling cercopithecines including the guenons.

In her influential review of guenon ecology, Annie Gautier-Hion stated that “a relatively homogeneous dietary pattern is found among all forest guenons studied, fruit being their staple diet. The relative percentage of non-fruit material and of animal matter mostly depends on fruit availability” [1988a: 282]. This general characterization of feeding habits has been borne out by nearly all subsequent studies of Cercopithecus spp. inhabiting forest habitats, albeit with growing evidence that forest guenons supplement fruit-rich diets with varying amounts of leaves, invertebrates, vertebrates, flowers, seeds, and other material [Chapman et al., 2002; Lambert, 2007; Jaffe and Isbell, 2011]. The focus of field research now is not just to establish the brackets of dietary variation, but more importantly to understand its determinants and consequences.

Long-term research at several sites highlights not only the magnitude of dietary variation between species, but also the scale of variation within and between sites, and within and across seasons and years [Cords, 1986; Butynski, 1990; Tutin, 1997; Tutin,

1999; Gathua, 2000; Chapman et al., 2002; Pazol and Cords, 2005]. Given mounting evidence that guenons are capable of significant interdemic and intraspecific dietary variation, it is clear that studies of one or even several groups of a species for an annual cycle may not adequately capture the breadth of that species’ diet [Chapman et al., 2002;

Struhsaker, 2010]. Because seasonal and/or annual fluctuations in forest productivity and food availability may result in highly variable diets over different time intervals, accurate characterization of a species’ dietary repertoire may not be possible until multiple seasons

28 or years of data are available [Clutton-Brock, 1977; Struhsaker, 1997; Chapman and

Chapman, 1990; Chapman et al., 2002].

Dietary variation can be significant even between contiguous groups, in part because heterogeneous forest composition (e.g., different species composition, distribution, and availability), and differences in group ranging behavior may lead to dietary differences [Tutin, 1999; Harris and Chapman, 2004]. However, factors not directly related to habitat productivity also influence primate diets. Groups may focus on the most profitable foods available based on nutritional composition, plant secondary compounds, and the suite of plant parts present at a given time [Chapman and Fedigan,

1990]. Food profitability may thus differ between groups even if all group home ranges have similar species composition. For example, during periods of low fruit availability, only one of three neighboring groups of capuchin monkeys in Santa Rosa National Park in Costa Rica ate the fruit of Acacia collinsii although it was abundant in all groups’ home ranges [Chapman and Fedigan, 1990]. Dietary differences between groups were attributed to differences in profitability rather than availability: the complexities of food choice (e.g., relative nutritional value, handling time, distribution, availability, secondary compounds, etc.) made resources in other groups’ home ranges more profitable for them

[Martin, 1985; Chapman and Fedigan, 1990]. Local traditions and cultural differentiation may also influence diet, such as between neighboring chimpanzee communities, or in cases where there are “mismatches” between tree species abundance and consumption among neighboring groups [Nishida et al., 1983; Whiten et al., 1999; Tournier et al.,

2014].

Diana monkeys (Cercopithecus diana diana) are an endangered West African guenon restricted to forests in Sierra Leone, Liberia, and western Côte d’Ivoire [Refisch and Koné, 2005; Gonedelé Bi et al., 2012; Bitty et al., 2015]. The diet of Diana monkeys has been well-studied in Taï National Park in Côte d’Ivoire over several annual cycles: they are highly frugivorous primates supplementing their diet primarily with invertebrates and, to a lesser degree, foliage [Galat and Galat-Luong, 1985; Wachter et al., 1997;

Eckardt and Zuberbühler, 2004; Buzzard, 2006; Kane and McGraw, in review]. Diana monkeys engage in relatively frequent intergroup aggression [Buzzard and Eckardt,

2007]. In fact, female Diana monkeys at Taï engage in lethal coalitionary behavior and drive territorial defense both in the Taï Forest and at Tiwai Island [Hill, 1994; McGraw et al., 2002]. Despite this, rates of intragroup agonism are quite low (particularly compared to papionins) and female Diana monkeys may have particular non-kin “friends” with whom they preferentially groom and vocalize [Rowell, 1988; Cords, 2011; Candiotti et al., 2015]. Though female Diana monkeys are under significant pressure to defend territory from neighboring groups, they do not engage in significant contest competition within groups. The social dynamics allowing females to minimize competition over presumably patchy, defensible resources are unclear.

Here, I build on previous studies of Taï guenon feeding ecology to examine the ecological context of two neighboring Diana monkey, assessing their diet relative to food availability and habitat composition. I use data collected between May 2013-August 2015 on the foraging behavior, food availability, and home range composition of two neighboring groups of Diana monkeys in the Taï National Park to examine the influence

30 of ecological factors on dietary choice and variation between groups. Specifically, I characterize the Diana monkey diet during this period, including dietary evenness and diversity. I assess dietary overlap between groups. I examine the degree to which diets reflect monthly changes in food availability, predicting that consumption of ripe fruit will correspond to phenological availability of those species. I next compare group habitat composition, and examine whether differences between group diets and habitats result in different dietary preferences. I predict that, because these two groups are contiguous, they will eat diets which are similar in consumption of broad dietary categories (e.g., fruit, leaves, invertebrates) and species composition of fruit and leaves.

METHODS

Study Site and Subjects

Data were collected in Taï National Park located in southwestern Côte d’Ivoire.

The park receives an average of 1830 mm of rain annually during a long dry season

(November-February), a long wet season (March-May), a short dry season (June-

August), and a short wet season (September-October) [Anderson et al., 2005]. This study focused on adult, subadult, and juvenile members of two habituated Diana monkey groups in the core study area of the Taï Monkey Project, located approximately 20 km from the nearest village, and 25 km from the border with Liberia [McGraw and

Zuberbühler, 2007]. These groups of Diana monkeys have been habituated and under regular observation since 1991. Groups consisted of one-male units with 7-13 adult females, 2-5 subadults, and associated juveniles and infants. Adult males and all adult females were individually identifiable; some subadults were also individually recognized.

Group membership shifted during this study period: both groups experienced male transfers, an adult female disappeared from Diana 1, six sub-adult females matured to adult status in Diana 2, and one infant disappeared (likely as a result of an attempted infanticide and chimpanzee predation attempt, after a male transfer) [Kane and Gnepa,

2016]. Group home ranges were determined using GPS tracks collected during 40 full- day follows of Diana 1, and 44 full-day follows of Diana 2. Group home range area and overlap were calculated using the Minimum Convex Polygon function in ArcGIS 22.0.

Data collection met the guidelines of the American Society of Primatologists’ principles for the ethical treatment of non-human primates, the IACUC of the Ohio State

University, and all requirements of permit-granting bodies in Côte d’Ivoire.

Ecological and Statistical Methods

Data were collected between May 2013-August 2015, with feeding data collected from July 2013-April 2014, and October 2014-August 2015. Each group was followed for four days every two weeks. Every morning, the focal group was located in its sleeping tree and followed until entering a sleeping tree for the night. Dietary profiles were generated through scan samples conducted every 60 minutes; each scan lasted up to 15 minutes due to constraints of group spread and visibility [Altmann, 1974]. It is important to note that this sampling method – and the sampling methods of all studies conducted on

Diana monkeys at Taï since 1992 – report time spent foraging on different food items rather than rates of consumption and intake [Wachter et al., 1997; Chivers, 1998;

Buzzard, 2004; Eckardt and Zuberbühler, 2004; Kane and McGraw, in preparation]. This may overestimate consumption of some foods with low rates of intake (such as

32 invertebrates) while underestimating the relative dietary proportions of other food items.

During scans, Frederic Gnepa and I walked underneath the group, recording individual identity, age and sex-class, behavior, and strata of all visible juveniles, subadults, and adults. Where sex and age could not be determined, individuals were included in the scan, but classified as indeterminate sex. If individuals were foraging, we recorded food type (e.g., ripe fruit, young leaf, invertebrate, and other) and species. We also recorded the presence of other species spatially comingled with the focal Diana monkey group.

To minimize the effect of different numbers of individuals in each scan sample

(range = 3-19), I treated each scan sample as a single data point and calculated the proportion of individuals feeding on different food types and items for each scan. I calculated dietary proportions across the entire study period by summing the proportions of each food category and species-specific plant part and dividing that by the total number of scan samples. I also calculated monthly dietary proportions by summing the monthly proportions of each food category or species-specific plant parts, and dividing that by the number of scans each month. I calculated dietary proportions for each group

(Diana 1 and Diana 2) and for an “overall” Diana monkey group for which I pooled group dietary data.

I assessed groups’ dietary diversity in terms of species-specific plant parts for the entire study period, and per month, using the Shannon-Wiener index of diversity and

Pielou’s measure of evenness [Pielou, 1966]. Diversity (H) is calculated as:

퐻 = ∑ 푝푖 ∗ 푙푛(푝푖), where pi is the proportion of the ith species-specific plant part [Pielou, 1966]. It is a

33 measure of both the number of species-specific plant items composing a diet, and the evenness of each item’s relative contributions. Evenness (J) is assessed by calculating the ratio of a group’s dietary diversity relative to its maximum possible dietary diversity:

퐻 퐽 = , and 퐻푀푎푥 = ln(푛푢푚푏푒푟 표푓 푠푝푒푐푖푒푠 푠푝푒푐푖푓푖푐 푝푙푎푛푡 푝푎푟푡푠). 퐻푀푎푥

An even diet (J approaches 1) is one in which each food item contributes an equal proportion to the total diet; an uneven diet (J approaches 0) is one in which some foods dominate.

I calculated dietary overlap in two ways [Holmes and Pitelka, 1968]. First, I calculated dietary overlap by summing shared dietary contributions of fruit, invertebrates, and leaves, independent of species composition. That is, I determined the shared amount a food category contributed to the diets of two groups, regardless of the specific items within each category. I also calculated overlap in consumption of species-specific plant parts by summing shared dietary contributions of species-specific plant items. In this way, I consider the specific plant parts that contribute to a food category, an important distinction since groups could overlap greatly in a category (e.g., fruit) but differ dramatically in the species-specific contributions to that category. I removed invertebrates from the latter analysis to examine only the relative contributions of different plant species to Diana monkey diets.

To assess forest productivity in home ranges, field assistants conducted phenological surveys every two weeks along an established fruit trails that cut through these groups’ home ranges [Chapman et al., 1994]. This trail included 289 individual trees representing 58 species, or approximately 5 trees per species, separated by at least

100 m from other sampled individuals of the same species. Trees were assessed for fruiting, leaf flushing, and flowering on a 0-3 scale (0=0-25% full; 1=25-50% full; 2=50-

75% full; 3=75-100% full) [Buzzard, 2004]. The score reflects how much of a tree’s maximum (100%) production of fruit, flower, or leaves was present on the day of the survey. For each species, I calculated a mean monthly score for fruiting, leaf flushing, and flowering, and used Spearman’s rank test to assess the relationship between consumption and phenological abundance.

To determine habitat composition, I conducted vegetation surveys along eleven transects between May 2013 and January 2014, covering 3.0 ha in the home range of

Diana 1, 3.4 ha in the home range of Diana 2, and 5.4 ha overall. Working with Roman

Djobely, a local botanist, I recorded the position of trees on the transect with a hand-held

Garmin 64s GPS, and measured and identified all trees with a diameter at breast height

(DBH) >6.4 cm (i.e., all trees with a circumference at breast height of 20 cm or greater).

This is a smaller DBH than customary because Diana monkeys regularly consume fruit from trees with DBH<10 cm, including Diospyros soubreana, Diospyros manni, and

Maesobotria batteri [Buzzard, 2004]. Excluding those individuals would have significantly underestimated the number of food trees. DBH was then used to calculate relative densities, and total basal areas for different species, using the following formula

[DaSilva, 1994]:

퐷퐵퐻 퐵푎푠푎푙 퐴푟푒푎 = 휋 × ( )2. 2

I used two-tailed, paired sample t-tests with alpha-levels set at 0.05 to test for differences in tree species distribution between group home ranges. I used Ivlev’s

Electivity Index (I) to calculated dietary preferences for tree species consumed by Diana monkeys during this study period [Ivelev, 1961; Lechowicz, 1982]. This index ranges from 1 to -1 and compares species’ dietary proportion to their species’ relative density:

(퐶표푛푠푢푚푝푡푖표푛 − 퐷푒푛푠푖푡푦) 퐼 = (퐶표푛푠푢푚푝푡푖표푛 + 퐷푒푛푠푖푡푦)

Positive values (preferred foods) indicate that foods are eaten more frequently than their abundance predicts; negative values (non-preferred foods) indicate that foods are eaten less frequently than their abundance predicts. I assessed selectivity for each group based on their consumption and habitat characteristics, and for the pooled Diana monkey group with habitat data from the entire home range.

RESULTS

The Diana Monkey Diet

Dietary data are derived from 2,589 scan samples collected on two groups over a period of 17 months between July 2013-August 2015, equivalent to 258 full day follows.

During this study period, Diana monkeys feeding time primarily consisted of foraging for invertebrates (63.5%), followed by fruit (32.8%), leaves (3.7%), and other material

(0.5%) (Table 2.1). Monkeys foraged for invertebrates opportunistically while resting or traveling or by systematically unrolling leaves in tree canopies and eating invertebrates found there. They were also observed feeding on swarms of flying ants on three occasions, and readily descended to the ground to catch African giant millipedes

(Archispirostreptus gigas), which they ate by snapping them in half and sucking out their internal organs. They also spent significant time in the upper canopy of Parkia bicolor

36 when these trees were flowering (November-February, TMP unpublished data), opening the flowering pods and eating larvae found inside.

Diana monkeys consumed plant foods from at least 39 tree species and 1 liana species, with an additional 4.1% of plant-based foods from unidentified tree and liana species (Table 2.2). The pooled Diana monkey group ate fruit from 35 tree species, and unidentified tree and liana species, leaves from 6 tree species, and flowers from 1 species.

Particularly important foods include ripe fruit of Sacoglottis gabonensis (20.8%),

Dialium aubrevillei (14.0%), Diospyros soubreana (9.9%), Oldfieldia africanum (5.0%), and Pycnanthus angolensis (4.8%), and mature leaves of Craterispermum caudatum

(6.0%). With the exception of those mature leaves of C. caudatum, Diana monkeys consumed only young leaves. Other items, including fungus, caches of frog eggs from the

African foam-nest tree frog (Chiromantis rufescens), and Piptadenastrium africanum flowers, were very rarely consumed [Rödel et al., 2002].

Diana 1 ate fruit from 26 species, leaves from 5 species, and additional 4.6% of their plant-based diet from unidentified tree and liana species (Table 2.2). Their overall dietary diversity (H) was 2.77; dietary evenness (J) was 0.77. Diana 2 at fruit from 33 species, leaves from 7 species, and 1 liana species, with an additional 3.5% of the plant- based diet from unidentified tree and liana species (Table 2.2). Their diet was slightly more diverse than Diana 1 (H=2.91), but dietary evenness was comparable (J=0.76).

Although several species were more frequently consumed than others, group diets were not dominated by a single species.

Monthly diets were highly variable (Table 2.3, Table 2.4). Fruit comprised between 12.8-52.7% per month, and invertebrates between 39.7-85.3% per month.

Leaves were not eaten every month, but composed as much as 20.6% of the monthly diet

(Diana 2, July 2015). There were several fruit species of particular importance, including ripe fruit of Diospyros soubreana, the most consumed plant part during January and

February; Dialium aubrevillei, the most consumed plant part during March and April, and

Sacoglottis gabonensis, the most consumed plant part during May, August, September,

October, and November.

Dietary Overlap between Groups

It was possible to compare group diets during 17 months between July 2013 and

August 2015. Table 2 presents the monthly contributions of fruit, invertebrates, and leaves to the diets of Diana 1 and 2, and the proportion of these contributions that are shared by two groups. For example, during July 2013, Diana 1 and Diana 2 had a shared resource base of 78.4%, including a diet composed of at least 36.9% fruit, 39.8% invertebrates, and 1.7% leaves. Monthly dietary convergence in food categories between groups ranged from 78-98%.

However, groups with equivalent intake rates of a food category (e.g., fruit) can have dissimilar diets if the species-specific components of that category differ. This appears to be the case with Diana monkeys at Tai: despite high overlap in contributions of food categories to each group, species composition of each food category varied considerably between groups (Table 2.4). Considering the entire study period, overlap in consumption of species-specific plant parts was 68%, and on a monthly basis dietary

38 overlap ranged from 15-98% of groups’ monthly diets (Table 2.4). Thus, although Diana monkey groups consumed diets broadly similar in the relative contributions of fruit, invertebrates, and leaves, species composition of those categories was quite variable

(Table 2.3, 2.4). Diana monkeys utilized an array of fruits and foliage beyond the shared species that compose two-thirds of their plant-based diet.

Diana 1 had the lowest dietary diversity in April 2014 (H=0.42) when they ate foods from two tree species and unknown lianas. Dialium aubrevillei fruit dominated their diet that month (Table 2.4). They had the highest dietary diversity during February

2015 (H=2.16), when they ate foods from 13 tree species and unknown liana species.

Dietary diversity was highest during the long wet season (H=1.71), and lowest during the short dry season (H=1.12). Mean monthly dietary diversity was 1.19; mean evenness was

0.72. Diana 2 also had the lowest dietary diversity during April 2014 when they ate foods from two tree species, as well as unknown lianas and frog eggs (H=0.45). Like Diana 1, their diet during April 2014 was primarily the fruit of Dialium aubrevillei. During July

2015, they ate foods from 12 tree species and unknown liana species; this was the month in which they had the highest dietary diversity (H=2.27). Diana 2 had the highest dietary diversity during the long wet season (H=1.89), and the lowest dietary diversity during the short wet season (H=0.61). Mean monthly dietary diversity was 1.42; dietary evenness was 0.73.

Across the study duration, Diana 2 had significantly higher dietary diversity than

Diana 1 (paired-samples t-test, t=-2.31, df=16, p=0.03), but there was no significant difference in dietary evenness (paired-samples t-test, t=-0.311, df=16, p=0.76).

Fruit Availability and Diets

Phenological surveys conducted through the home ranges of these two groups included 21 fruit species that compose 67.8% of Diana monkeys’ plant-based diet. Mean monthly food availability and consumption, per species, are presented in Table 2.5. There were no significant correlations between overall mean monthly fruit availability and monthly consumption of fruit by Diana 1 (ρ=0.45, p=0.06), Diana 2 (ρ=0.45, p=0.05), or the pooled data set (ρ=0.30, p=0.20) (Figure 2.1, Table 2.6). Although all species included on phenological transects produced fruit during our study period, representative trees on the phenology trail for three species (Dacryodes klaineana, Spondianthus preussi, and Uapaca esculenta) did not fruit. These species were removed from further analyses, and I assessed correlations between each species’ monthly fruit availability and dietary contributions for the 18 remaining species (Table 2.7). Monthly species consumption for the pooled Diana monkey group was significantly, positively correlated with mean monthly availability of Diospyros manni, Oldfieldia africanum, Parinari excelsa, and Sacoglottis gabonensis. Sacoglottis gabonensis was the only fruit for which

Diana 1’s consumption positively, significantly correlated with its monthly availability.

Diana 2’s monthly consumption of fruit of Coelycarion oxycarpum, Diospyros manni,

Oldfieldia africanum, and Sacoglottis gabonensis correlated significantly with their monthly availability.

Habitat Characterization

Diana 1 had a home range of 43.0 ha, while the home range of Diana 2 was 48.4 ha (Figure 2.2). Home ranges overlapped 12.4 ha. I conducted eleven 10m wide transects

40 through the home ranges of these two groups, covering an area of 5.4 ha. Roman Djobely and I measured and identified 5,786 trees on these transects with a DBH greater than 6.4 cm (a circumference at breast height > 20 cm), including trees from 89 species and additional 660 trees from unidentified species. These transects included 3,203 trees within the home range of Diana 1, and 3,354 tree species in the home range of Diana 2

(Figure 2.3). There were no significant differences in the basal areas of all identified tree species in the groups’ home ranges (paired t-test: t93=-1.13, p=0.263) (Table 2.5).

Transects included 3,105 trees from 31 species that accounted for 85.0% of the pooled, plant-based Diana monkey diet, 82.4% of the plant-based diet of Group 1 (1,935 trees), and 85.1% of the plant-based diet of Group 2 (1,998 trees). There were no significant differences in the relative basal areas of these 31 tree species in the two groups’ home range, (paired t-test: t33=-1.651, p=0.108).

Food Preference

I used data on tree species density to calculate preference for 33 plant items that accounted for 83.8% of the pooled, plant-based diet, including fruit, flowers, and young leaves from 31 species (Table 2.9). Diana monkeys eat most species-specific plant foods more frequently than their abundance predicts, suggesting that Diana monkeys are selective foragers. Eighteen foods (72.3% of the plant-based diet) were more frequently consumed than their abundance predicted (i.e., were preferred); 13 foods (9.5% of the plant-based diet) were less frequently consumed than their abundance predicted (i.e., were not preferred). Most preferred foods were ripe fruit, with the exception of young leaves of Xylopia quintasi and Maesobotria batteri. Diana 1 ate 26 of these plant items.

Fifteen foods were preferred (65.1% of the plant-based diet), including fourteen species of fruit and one leaf species; 11 were not preferred (7.5%). Diana 2 ate 29 of these plant items. They preferred 18 foods (72.5% of the plant-based diet), including one species of leaves and 17 fruit species, and did not prefer 11 (12.4% of the plant-based diet). Diana 1 and Diana 2 classified 19 food items (68% of both groups’ diets) in the same way, including thirteen preferred foods, and six non-preferred foods.

I tested the relationship between electivity and mean DBH for fruit trees.

Electivity was significantly, positively correlated with mean DBH for the pooled data set

(ρ= 0.40, p=0.04), Diana 1 (ρ= 0.59, p= 0.04) and Diana 2 (ρ= 0.41, p=0.04). On the other hand, there was a significant, negative correlation between electivity of fruit species and the number of trees of that species for the pooled data set across the study area (ρ= -

0.56, p<0.01), and in the home ranges of Diana 1 (ρ= -0.67, p<0.01) and Diana 2 (ρ= -

0.55, p< 0.01). Foods eaten more than their abundance in the habitat would predict tended to be large and rare, while foods eaten less than their abundance predicted tended to be small and ubiquitous.

DISCUSSION

Diana Monkey Diets

During this study, Diana monkeys spent nearly twice as much time foraging for invertebrates than for fruit, foliage, and other material. This division of foraging time –

63.5% invertebrates, 32.8% fruit, 3.7% leaves, 0.5% other material, is very different from previously reported Diana monkey diets from the Taï Forest (Table 2.10). Diana monkeys in the Taï Forest are consistently characterized as ripe fruit specialists; previous studies

42 record diets of 52-71% fruit and 16-38% invertebrates [Galat and Galat-Luong, 1985;

Wachter et al., 1997; Buzzard, 2004; Eckardt and Zuberbühler, 2004; Kane and McGraw, in preparation]. There are several possible explanations for these discrepancies.

One possibility is that Diana monkeys shifted their diets dramatically in response to changes in forest productivity and food availability. However, several lines of evidence lead me to conclude this is not the case. Over this 20-month study of two group diets, I recorded consumption of 42 species-specific plant items from identified tree and liana species, with fruit and foliage from unidentified tree and liana species composing 4.1% of the plant-based diet. Comparatively, during a 61-month study of four groups at Taï,

Diana monkeys consumed 63 species-specific plant items [Kane and McGraw, in review]. Dietary diversity is expected to be lower in the shorter study because of fewer opportunities to observe consumption of rare foods. However, 9 of the 10 most frequently eaten leaf and fruit species during this study were among the most frequently eaten species between 2000-2001, and 2004-2009, suggesting that groups continue to rely on the same plant-based resources (Table 2.11) [Buzzard, 2004; Kane and McGraw, in preparation]. Relative contributions of most species of fruit and foliage to the non- invertebrate diet were consistent across studies. Diana monkeys’ plant-based diet did not change dramatically between 2000 and 2015.

Though some inter-annual dietary variation between studies is to be expected, disparities between observers may better explain the dramatic differences between studies in time spent foraging on invertebrates than dietary variation [Chapman et al., 2002].

Ferdinand Belé was the primary field assistant involved in data collection for studies

43 between 1992 and 2009; Frederic Gnépa and I collected scan samples for this study. F.

Gnépa and I classified “foraging for invertebrates” more broadly than F. Belé did, leading to an overestimation of invertebrate consumption. Because Diana monkeys tend to forage opportunistically for invertebrates while traveling or resting, it is quite likely that some of the individuals we classified as “Foraging for invertebrates” in our scan samples would have been classified as “resting” or “traveling” by F. Belé. This is borne out by differences in activity budgets between studies: during this study, Diana monkeys spent more time foraging and much less time resting or traveling than previous reports (Table

2.12). Furthermore, McGraw [1998] found that Diana monkeys spent 61.5% of their time feeding and foraging, and 28.5% traveling, but noted that Diana monkeys climb frequently while foraging. This further complicates cross-study comparisons of Diana monkey activity budgets, particularly between observers. Comparing Diana monkeys from this study to other studies of Diana monkeys and guenons in terms of relative dietary contributions of fruit, invertebrates, and leaves may be misleading because of inconsistencies in definitions of feeding, foraging, and travel. This underscores the importance of calculating rates of ingestion in addition to time spent feeding or foraging on a food item. Despite this (significant) caveat, my data on the relative contributions of different species to the plant-based diet are comparable to previous studies. Conducting tests of inter-observer reliability to enable clear comparisons between studies will be a priority for future work on guenon feeding ecology at Taï.

Diana Monkey Groups’ Ecological Priorities?

During this 17-month period, the two study groups were remarkably consistent in dietary contributions of fruit, invertebrates, leaves, and other material, with 93% overlap across the study period. Monthly diets were also consistent between groups, with shared contributions of fruit, invertebrates, leaves, and other material between 78-98%.

However, similarities in the contributions of food categories did not necessarily correspond with similarities in species consumption. Dietary overlap in this sense may be better conceptualized as a shared base of common resources – the species composing that shared base will almost certainly vary. For example, between November 2013 and

January 2014, both groups relied on a few important fruit species including Pycnanthus angolensis, Dacryodes klaineana, and several species from the genus Diospyros. Though both groups ate these fruit, they exploited these fruit species to different degrees, and supplemented their diet with fruit and foliage from other species so that the monthly contributions of shared resources were fairly low (51-60%). Across the entire study period, groups shared 68% of their species-specific plant parts, meaning that about 1/3 of the plant-based diet was unique to each group. On a month-by-month basis, groups shared 15-91% of resources, meaning that every month as much as 85% or as little as 9% of group diets were unique.

Overlap in species-specific plant part consumption was both higher and lower for

Diana monkeys than other guenons (Table 2.13) [Rudran 1978; Gathua, 2000]. In some months, Diana monkey groups eat diets which are virtually identical to each other in the contribution of food categories. In other months, group diets diverge completely, with

45 very few shared resources. By contrast, consistent, relatively low monthly rates of dietary overlap among C. mitis and C. ascanius suggest that neighboring groups rely on a common resource base supplemented by a diverse and disparate array of fruit and foliage every month [e.g, Butynski, 1990; Gathua, 2000]. While Diana monkeys use this strategy of broad dietary diversity during times of the year when particular fruit species are not productive, when valuable resources such as Sacoglottis gabonensis or Dialium aubrevillei are fruiting, they are exploited extensively by all groups.

Difference in dietary preferences between groups may account for some of the intergroup variation on a month-by-month basis, but they cannot account for all the variation. Habitat differences also cannot account for this variation: there were no significant differences between home ranges in species composition, the total basal area of each tree species, and the relative basal areas of food trees in the two group’s home ranges. To date, I am aware of no evidence suggesting that Diana monkeys exhibit group- level traditions or cultural behavior, so I find this an unconvincing explanation for intergroup dietary differences in this context [McGrew, 1998; Perry and Manson, 2003;

Tournier et al., 2014]. I observed that, while group diets can converge to high degrees, they did not always. Evidence of both extreme dietary convergence and divergence in

Diana monkeys across this study suggests that dietary differences at certain periods may be in response to local fluctuations in food availability, or to differences in resource profitability between groups [Chapman and Fedigan, 1990]. In other words, despite overall home range similarities, local patterns of availability and tree species distribution may make it more profitable for one group to focus on, for instance, the fruit of Uapaca

46 guinensis, while another group may focus more intensively on Diospyros soubreana during the same period.

Contextualizing these results with other reported Diana monkey diets shows that

Diana monkeys at Taï generally consumed a diet richer in fruit than conspecifics and closely allied species in other forests, who incorporate more invertebrates, leaves, seeds, flowers, and exudates (Table 2.10). Although Diana monkeys in this study consumed a diet which incorporated much less fruit than previous studies have reported, their diet was still richer in fruit than that of Diana monkeys studied at Tiwai Island, Sierra Leone and

Roloway monkeys at Bia National Park, Ghana [Table 2.10]. This may be because the relatively high species diversity and productivity of the Taï Forest allows groups to sample widely from an array of fruiting trees at any given time [Anderson, 2001]. Non- fruit plant parts are important dietary components for Diana monkeys at Sierra Leone’s

Tiwai Island and Roloway monkeys (Cercopithecus roloway; until recently

Cercopithecus diana roloway) in Ghana’s Bia National Park (Table 2.10) [Oates and

Whitesides, 1990; Whitesides, 1991; Curtin, 2002: Koné et al., 2017].

Though direct comparisons of diets are challenging because of methodological idiosyncrasies, differences in study scope, etc., an examination of available data suggests that dietary overlap in food categoires across Diana and Roloway monkey sites is 34%.

Fruit composes at least a quarter of all Diana monkey diets studied to date and invertebrates compose at least 10%. Although Diana and Roloway monkeys outside of

Taï consume diets lower in ripe fruit than previously-reported diets of Taï’s Diana monkeys, it may be that Diana monkeys prefer some baseline amount of ripe fruit. All

47 groups at Taï consumed fruit-rich diets, though the species composition varied considerably.

Spatial proximity and forest heterogeneity may affect dietary overlap based on local availability of foods and differences in group preference or relative profitability.

The abundant, fruit rich, relatively homogenous habitat at Taï may enable groups to consume a fruit-rich diet and to select from a wide array of species while foraging

[Anderson, 2001]. Even in highly homogenous habitats, adjacent groups of guenons can exhibit marked dietary variation [Chapman et al., 2002]. Meanwhile, a history of habitat disturbance including extensive logging and the consequent loss of many large primary forest trees at both Tiwai Island and Bia National Park has resulted in differences in forest structure, which in turn have almost certainly influenced fruit availability both seasonally and in general [Whitesides, 1991; DaSilva, 1994; Hill, 1994; Curtin 2002;

McGraw and Zuberbuhler 2007]. Diana and Roloway monkeys at Tiwai and Bia use flowers, exudates, and seeds as dietary buffers in less productive forests [Whitesides,

1991; Curtin, 2002]. Diana monkeys have largely been extirpated from forest fragments and small protected areas in Côte d’Ivoire, perhaps because neither large quantities of ripe fruit nor these dietary buffers are available [McGraw, 2007; Gonedelé Bi et al.,

2012; Bitty et al., 2015].

Conclusions and Further Directions

Despite methodological issues that hamper my ability to compare relative contributions of fruit, leaves, invertebrates and other material to reported diets for other guenons, these data corroborate much of the previous research on the plant-based diets of

Diana monkeys in the Taï Forest [e.g., Buzzard, 2004; Buzzard, 2006; Kane and McGraw in review]. Diana monkeys in Taï eat a diet that is consistent between studies in species composition and the relative contributions of these species to the plant-based diet

[Wolters and Zuberbühler, 2003; Buzzard, 2004; Eckardt and Zuberbühler, 2004; Kane and McGraw, in review]. Intergroup variation between neighboring groups of Diana monkeys during this study was comparable to previous studies of neighboring Diana monkeys at Taï and elsewhere, and is broadly comparable to other guenons [Oates and

Whitesides, 1990; Chapman et al., 2002; Kane and McGraw in review]. However, Diana monkeys have a more expansive range of intergroup variation: group overlap in contribution of particular species to the diet ranges from as little as 15% to as much as

98%. Dietary variations are not attributable to habitat differences: habitats are highly consistent between groups. These two groups also tend to have similar dietary preferences.

The fact that neighboring groups rely on a common resource base, and exhibit significant overlap in their home ranges, suggests that groups have ample opportunities for intergroup competition over access to important, mutually-preferred feeding trees. In fact, Diana monkeys engage in more inter-group aggression than sympatric guenons, including female participation in lethal coalitionary defense against stranger females

[McGraw et al., 2002; Buzzard and Eckardt, 2007]. However, groups’ relatively broad resource base and dietary diversity may allow individuals to minimize intragroup competition by feeding from multiple fruiting trees.

Diana monkeys at Taï exhibit high dietary homogeneity in terms of broad dietary categorizations. In this sense, their diet exemplifies Gautier-Hion’s characterization of the diets of the forest guenons as homogenous and generally frugivorous [Gautier-Hion,

1988]. Diana monkeys at Taï exhibit high dietary homogeneity in terms of broad dietary categorizations, despite fluctuating pressures from polyspecific associations with sympatric guenons. In this sense, these monkeys embody Gautier-Hion’s characterization of forest guenons as predominantly frugivorous [Gautier-Hion, 1988a]. However, while

Gautier-Hion emphasized the homogeneity of forest guenon diets, these findings reinforce the point that broad categorical labels can mask dramatic dietary differences, even between neighboring groups of the same species. These findings suggest that even selective frugivores like Diana monkeys can exhibit remarkable dietary variability. Diana monkeys have managed to get the better of their complex competitive and ecological situation by sampling broadly from an array of ripe fruit species available to them, maintaining their fruit-rich diet through significant intraspecific flexibility.

TABLES

Species Pooled Diana 1 Diana 2 Invertebrates 63.5% 67.2% 60.0% Fruit 32.8% 30.3% 35.2% Angelae sp. 0.1 0.2 Anthonota fragrans 0.1 0.2 Caloncoba brevipes 0.1 Canthium tecbe 0.5 0.2 0.2 Chrysophylum taiensis 0.5 0.4 0.7 Coelecaryon oxycarpum 0.4 0.5 0.4 Dacryodes klaineana 0.5 1.0 0.2 Dialium aubrevillei 5.1 4.9 4.2 Diospyros ivoriensis 0.4 0.8 0.0 Diospyros manni 0.2 0.4 0.0 Diospyros sanza-minika 0.7 0.6 0.8 Diospyros soubreana 3.6 2.4 4.9 Landolphia 0.5 0.8 0.2 Liana (unknown) 0.9 1.0 0.7 Maesobotria batteri 0.3 0.1 0.5 Memecylon lateriflorum 0.7 0.2 1.3 Musanga cercopioides 0.7 0.8 0.6 Napoleona leonensis 0.1 0.2 Nauclea pobeguini 0.1 Oldfieldia africanum 1.8 2.2 1.4 Pachypondathium staudti Pancovia bijuga 0.2 0.4 Parinari excelsa 0.7 0.2 1.2 Parkia bicolor 0.3 0.4 0.1 Polyathia olivieri 0.1 0.0 0.2 Pycnanthus angolensis 1.8 1.9 1.5 Continued

Table 2.1 continued

Sacoglottis gabonensis 7.6 6.5 8.7 Sal. awa Scottelia chevalieri 1.1 1.1 1.0 Scytopetalum tieghemmi 1.0 0.5 1.6 Spondianthus preussi 0.1 Syzygium rowlandi 0.3 0.7 Tetracera potateria 0.1 0.2 Uapaca esculenta 0.6 0.7 0.5 Uapaca guinensis 0.6 0.3 0.9 Unknown 0.1 0.1 Spondianthus preussi 0.1 Syzygium rowlandi 0.3 0.7 Tetracera potateria 0.1 0.2 Uapaca esculenta 0.6 0.7 0.5 Uapaca guinensis 0.6 0.3 0.9 Xylopia taiensis 0.1 0.1 Leaves 3.7% 2.5% 4.9% Craterispermum caudatum 2.1 1.2 3.0 Cersalia afzeli 0.1 0.2 Dialium aubrevillei 0.1 0.2 Diospyros canaliculata 0.1 Diospyros soubreana 0.1 0.2 Liana (unknown) 0.4 0.4 0.4 Maesobotria batteri 0.8 0.3 1.3 Unknown Xylopia quintasii 0.1 0.2 Other 0.5% 0.6% 0.6% Frog eggs 0.1 Mushrooms 0.4 0.3 0.5 Piptadenastrium africanum 0.1 0.2 0.0 flowers

Species Pooled Diana 1 Diana 2 Fruit Angelae sp. 0.2% 0.4% Anthonota fragrans 0.2% 0.4% Caloncoba brevipes 0.1% 0.2% Canthium tecbe 1.4% 0.6% 0.4% Chrysophylum taiensis 1.4% 1.1% 1.8% Coelecaryon oxycarpum 1.1% 1.4% 0.9% Dacryodes klaineana 1.4% 3.1% 0.5% Dialium aubrevillei 14.0% 14.9% 10.4% Diospyros ivoriensis 1.1% 2.3% 0.0% Diospyros manni 0.6% 1.3% 0.1% Diospyros sanza-minika 1.8% 1.7% 1.9% Diospyros soubreana 9.9% 7.3% 12.2% Landolphia sp. 1.3% 2.4% 0.4% Liana 2.4% 3.0% 1.8% Maesobotria batteri 0.8% 0.3% 1.2% Memecylon lateriflorum 2.0% 0.7% 3.2% Musanga cercopioides 2.0% 2.5% 1.5% Napoleona leonensis 0.3% 0.1% 0.6% Nauclea pobeguini 0.1% 0.2% 0.0% Oldfieldia africanum 5.0% 6.6% 3.6% Pachypondathium staudti 0.1% 0.1% Pancovia bijuga 0.6% 1.1% Parinari excelsa 2.0% 0.6% 3.1% Parkia bicolor 0.7% 1.3% 0.2% Polyathia olivieri 0.3% 0.5% Pycnanthus angolensis 4.8% 5.9% 3.8% Sacoglottis gabonensis 20.8% 19.7% 21.7% Continued Table 2.2. Overall contributions of fruit species, leaf species, and other material to the diets of two Diana monkey groups, and the pooled diet, between July 2013-August 2015.

Table 2.2 Continued Species Pooled Diana 1 Diana 2 Sal. awa >0.1% 0.1% Scottelia chevalieri 2.9% 3.5% 2.4% Scytopetalum tieghemmi 2.8% 1.4% 4.0% Spondianthus preussi 0.1% 0.2% Syzygium rowlandi 0.9% 1.7% Tetracera potateria 0.2% 0.4% Uapaca esculenta 1.7% 2.2% 1.2% Uapaca guinensis 1.7% 1.0% 2.2% Unknown 0.3% 0.4% 0.1% Spondianthus preussi 0.1% 0.2% Syzygium rowlandi 0.9% 1.7% Tetracera potateria 0.2% 0.4% Uapaca esculenta 1.7% 2.2% 1.2% Uapaca guinensis 1.7% 1.0% 2.2% Xylopia taiensis 0.2% 0.3% Leaves Craterispermum caudatum 6.0% 3.6% 8.2% Cersalia afzeli 0.2% 0.2% 0.2% Dialium aubrevillei 0.4% 0.7% 0.1% Diospyros canaliculata 0.1% 0.2% Diospyros soubreana 0.3% 0.5% 0.0% Liana 1.3% 1.1% 1.5% Maesobotria batteri 2.5% 1.0% 3.8% Unknown 0.1% 0.1% 0.1% Xylopia quintasii 0.2% 0.4% Other Frog eggs 0.1% 0.2% Mushrooms 1.1% 1.0% 1.2% Piptadenastrium africanum flowers 0.3% 0.7%

Month Part Pooled Diana 1 Diana 2 Overlap 7 2013 FR 40.0% 43.5% 36.9% 78.4% N=59 scans IN 55.1% 39.8% 61.4% L 5.0% 11.0% 1.7% 8 2013 FR 52.7% 49.1% 56.5% 92.6% N=166 scans IN 39.7% 41.3% 39.4% L 7.6% 10.9% 4.0% 9 2013 FR 43.9% 51.7% 35.5% 83.8% N=179 scans IN 46.2% 39.9% 50.7% L 9.9% 7.2% 12.1% 10 2013 FR 46.3% 52.5% 40.0% 86.9% N=125 scans IN 48.8% 42.3% 55.5% L 4.9% 5.2% 4.5% 11 2013 FR 25.3% 34.8% 18.2% 83.4% N=117 scans IN 74.7% 65.2% 81.8% L 0.0% 0.0% 0.0% 12 2013 FR 36.5% 44.3% 28.1% 82.3% N=102 scans IN 74.7% 53.3% 65.8% L 3.5% 0.9% 6.0% 1 2014 FR 49.2% 48.2% 50.2% 97.5% N=225 scans IN 49.3% 48.9% 49.5% L 0.5% 1.4% 0.3% 2 2014 FR 37.3% 32.2% 42.5% 86.6% N=216 scans IN 59.1% 65.6% 52.2% L 3.6% 2.1% 5.3% 3 2014 FR 14.0% 14.1% 13.9% 98.6% N=136 scans IN 85.3% 85.9% 84.6% L 0.8% 0.0% 1.4% 4 2014 FR 29.8% 31.3% 28.7% 96.3% N=143 scans IN 65.7% 65.5% 67.9% L 4.5% 3.2% 2.1% 10 2014 FR 40.2% - 39.4% N=50 scans IN 58.2% - 57.1% L 1.6% - 1.6% Continued 3. Table 2.3. Monthly contributions of fruit, invertebrates, and leaves to the diets of two Diana monkey groups between July 2013-August 2015, and shared dietary proportions of these two groups.

Table 2.3 continued

Month Part Pooled Diana 1 Diana 2 Overlap 11 2014 FR 48.7% - 48.7% N=77 scans IN 43.0% - 43.0% L 8.3% - 8.3% 1 2015 FR 36.5% 32.6% 39.9% 92.1% N=99 scans IN 63.2% 67.4% 59.5% L 0.3% 0.0% 0.5% 2 2015 FR 45.5% 45.5% - N=132 scans IN 53.1% 53.1% - L 1.4% 1.4% - 3 2015 FR 26.5% 21.9% 30.4% 89.4% N=134 scans IN 72.8% 78.1% 67.5% L 0.8% 0.0% 1.4% 4 2015 FR 49.5% 17.1% 24.9% 81.8% N=152 scans IN 49.1% 81.7% 63.5% L 1.4% 1.2% 10.2% 5 2015 FR 18.0% 12.9% 25.4% 80.7% N=135 scans IN 79.3% 87.1% 67.8% L 2.8% 0.0% 6.8% 6 2015 FR 18.4% 18.6% 17.7% 97.2% N=206 scans IN 76.8% 76.7% 75.3% L 4.8% 3.2% 6.3% 7 2015 FR 17.3% 18.4% 15.8% 83.1% N=153 scans IN 71.1% 77.2% 62.8% L 11.6% 4.5% 20.6% 8 2015 FR 12.8% 12.9% 12.6% 92.5% N=153 scans IN 83.7% 87.1% 80.0% L 3.5% 0.0% 7.0%

Month Species Part Pooled Diana 1 H J Diana 2 H J Overlap 7 2013 0.47 0.68 0.84 0.76 47.5% N= 59 scans Oldfieldia africanum FR 29.0% 52.5% Scottelia chevalieri FR 60.4% 81.8% 43.2% Craterispermum caudatum LM 10.6% 18.2% 4.3% 8 2013 1.53 0.79 1.21 0.55 47.4% N=166 scans Liana FR 5.2% 5.8% 4.6%

Musanga cercopioides FR 3.0% 5.8% Oldfieldia africanum FR 26.7% 41.8% 10.5% Sacoglottis gabonensis FR 47.7% 28.5% 68.3%

Scottelia chevalieri FR 2.5% 5.2%

Uapaca guinensis FR 1.7% 3.5%

Unknown FR 0.6% 1.2% 57 Craterispermum caudatum LM 5.8% 9.0% 2.3%

Dialium aubrevillei LY 4.0% 7.7% Liana LY 2.3% 1.5% 3.2%

Unknown LY 0.6% 1.2% Continued Table 2.4. Monthly contributions of species-specific plant parts to the diets of two Diana monkey groups, monthly diversity (H), and monthly evenness (J) between July 2013-August 2015.

Table 2.4 continued

Liana FR 1.2% 2.2%

Maesobotria batteri FR 0.7% 1.5% Oldfieldia africanum FR 6.4% 10.0% 2.6% Sacoglottis gabonensis FR 69.5% 75.6% 62.8% Craterispermum caudatum LM 10.5% 5.5% 16.0%

Dialium aubrevillei LY 0.8% 1.6% Liana LY 3.8% 6.6% 0.6%

Maesobotria batteri LY 3.0% 6.3%

Mushrooms OT 1.6% 3.4% 10 2013 0.91 0.44 1.06 0.77 65.8% N=125 scans Coelecaryon oxycarpum FR 0.4% 0.8%

58 Dialium aubrevillei FR 0.5% 1.0% Maesobotria batteri FR 6.1% 4.6% 8.2%

Nauclea pobeguini FR 1.8% 3.2%

Pycnanthus angolensis FR 8.8% 20.4% Sacoglottis gabonensis FR 70.6% 77.7% 61.2%

Uapaca esculenta FR 2.2% 3.8%

Craterispermum caudatum LM 4.4% 10.2%

Diospyros soubreana LY 4.4% 7.7%

Liana LY 0.7% 1.3% 11 2013 1.68 0.86 1.31 0.94 51.0% N= 117 scans Dacryodes klaineana FR 8.3% 14.1%

Diospyros sanza-minika FR 6.4% 10.9% Continued

Table 2.4 continued

Landolphia sp. FR 2.5% 4.2%

Pancovia bijuga FR 16.2% 39.3%

Pycnanthus angolensis FR 4.4% 7.4% Sacoglottis gabonensis FR 17.9% 16.7% 19.6% Uapaca esculenta FR 27.5% 40.4% 28.0% Uapaca guinensis FR 16.9% 6.3% 13.1% 12 2013 1.31 0.67 1.94 0.84 56.4% N=102 scans Angelae sp. FR 2.9% 6.9%

Caloncoba brevipes FR 1.6% 3.7% Dacryodes klaineana FR 18.8% 26.0% 9.1% Liana FR 5.1% 7.1% 2.3%

59 Maesobotria batteri FR 1.1% 2.6%

Parinari excelsa FR 2.9% 6.9% Pycnanthus angolensis FR 46.2% 53.3% 36.6%

Spondianthus preussi FR 1.1% 1.9%

Tetracera potateria FR 3.3% 7.8% Uapaca guinensis FR 6.5% 6.5% 6.5% Craterispermum caudatum LM 8.6% 1.9% 17.6%

Mushrooms OT 1.9% 3.2% 1 2014 2.12 0.88 1.47 0.64 60.1% N=225 scans Chrysophylum taiensis FR 6.0% 6.7% 5.3%

Dacryodes klaineana FR 1.3% 2.5% Dialium aubrevillei FR 18.2% 18.6% 17.8%

Diospyros ivoriensis FR 1.3% 2.5% Continued 59

Table 2.4 continued

Diospyros sanza-minika FR 16.1% 15.0% 17.3% Diospyros sanza-minika FR 16.1% 15.0% 17.3% Diospyros soubreana FR 33.6% 17.8% 50.7%

Landolphia sp. FR 0.4% 0.8% Liana FR 3.5% 5.7% 1.1%

Musanga cercopioides FR 5.9% 11.4%

Polyathia olivieri FR 1.6% 3.3% Pycnanthus angolensis FR 9.4% 16.2% 2.0%

Unknown FR 0.4% 0.8%

Craterispermum caudatum LM 0.3% 0.7%

60 Mushrooms OT 2.0% 2.9% 1.1%

2 2014 1.63 0.71 1.62 0.67 49.2% N=216 scans Chrysophylum taiensis FR 0.6% 1.5% Dialium aubrevillei FR 19.3% 34.8% 7.6%

Diospyros ivoriensis FR 3.5% 8.7%

Diospyros manni FR 0.5% 0.9%

Diospyros sanza-minika FR 3.9% 6.9% Diospyros soubreana FR 43.3% 28.1% 54.8%

Landolphia sp. FR 1.1% 2.0%

Liana FR 0.8% 1.4%

Musanga cercopioides FR 2.0% 4.6% Napoleona leonensis FR 1.7% 0.8% 2.5% Parinari excelsa FR 5.7% 5.1% 6.1% Continued

Table 2.4 continued Parkia bicolor FR 3.9% 7.0% 1.5%

Uapaca guinensis FR 1.6% 3.8% Craterispermum caudatum LM 8.9% 6.1% 11.0% 3 2014 0.47 0.67 10.98 0.79 46.0% N=136 scans Dialium aubrevillei FR 54.4% 82.3% 28.3% Diospyros soubreana FR 37.2% 17.7% 55.4%

Musanga cercopioides FR 3.6% 7.0%

Craterispermum caudatum LM 4.8% 9.3% 4 2014 0.42 0.38 0.45 0.32 90.8% N=143 scans Dialium aubrevillei FR 88.7% 88.2% 89.4%

Liana FR 1.4% 2.5%

61 Craterispermum caudatum LM 6.4% 9.2% 2.5%

Liana LY 1.7% 3.9%

Frog eggs OT 1.8% 4.1% 10 2014 1.20 0.67 N=50 scans Maesobotria batteri FR 8.7% 8.7%

Memecylon lateriflorum FR 6.4% 6.4%

Sacoglottis gabonensis FR 64.2% 64.2%

Syzygium rowlandi FR 12.4% 12.4%

Craterispermum caudatum LM 3.7% 3.7%

Mushrooms OT 4.6% 4.6% 11 2014 1.85 0.95 N=117 scans Liana FR 7.2% 7.2%

Memecylon lateriflorum FR 13.1% 13.1%

Continued 61

Table 2.4 Continued Pycnanthus angolensis FR 9.0% 9.0% Sacoglottis gabonensis FR 29.7% 29.7%

Scytopetalum tieghemmi FR 13.8% 13.8%

Syzygium rowlandi FR 12.5% 12.5%

Craterispermum caudatum LM 14.6% 14.6% 1 2015 1.32 0.95 1.30 0.67 38.9% N=99 scans Chrysophylum taiensis FR 12.9% 22.0%

Diospyros ivoriensis FR 10.9% 26.3%

Diospyros manni FR 10.2% 24.6%

Diospyros sanza-minika FR 3.2% 5.4% Diospyros soubreana FR 48.3% 36.8% 56.4%

Landolphia sp. FR 6.3% 12.3% 2.0% 62

Liana FR 3.3% 5.6%

Parinari excelsa FR 4.2% 7.2%

Craterispermum caudatum LM 0.8% 1.4% 2 2015 2.16 0.82 N=132 scans Chrysophylum taiensis FR 6.4% 6.4%

Dacryodes klaineana FR 2.3% 2.2%

Dialium aubrevillei FR 18.0% 18.0%

Diospyros ivoriensis FR 4.8% 4.8%

Diospyros manni FR 0.6% 0.6%

Diospyros soubreana FR 28.6% 28.6%

Landolphia sp. FR 5.1% 5.1%

Liana FR 9.1% 9.1% Continued

Table 2.4 Continued Napoleona leonensis FR 0.5% 0.5% Parinari excelsa FR 5.4% 5.4%

Parkia bicolor FR 13.6% 13.6%

Sacoglottis gabonensis FR 1.6% 1.6%

Sal. awa FR 1.2% 1.2%

Craterispermum caudatum LM 3.1% 3.1% 3 2015 0.62 0.90 1.25 0.64 47.6% N= 134 scans Dialium aubrevillei FR 55.5% 68.5% 47.6%

Diospyros soubreana FR 4.1% 6.7%

Landolphia ap. FR 11.9% 31.5%

Liana FR 0.6% 1.0%

Parinari excelsa FR 22.4% 35.9%

63 Parkia bicolor FR 1.4% 2.2%

Craterispermum caudatum LM 2.8% 4.4%

Mushrooms OT 1.4% 2.2% 4 2015 0.82 0.59 2.09 0.84 48.5% N=152 scans Coelecaryon oxycarpum FR 9.6% 7.6% 10.9% Dialium aubrevillei FR 50.9% 75.4% 35.0%

Diospyros soubreana FR 1.5% 2.5%

Landolphia sp. FR 1.6% 2.7%

Liana FR 1.3% 2.1%

Napoleona leonensis FR 4.5% 7.4%

Uapaca guinensis FR 4.8% 7.9%

Craterispermum caudatum LM 1.6% 2.7% Continued

Table 2.4 Continued

Diospyros canaliculata LY 2.3% 3.7% Liana LY 6.0% 9.9% Maesobotria batteri LY 9.3% 5.9% 11.5%

Mushrooms OT 2.3% 3.7%

Piptadenastrium africanum flowers OT 4.3% 11.0% 5 2015 0.98 0.90 1.51 0.78 32.0% N=135 scans Anthonota fragrans FR 5.4% 8.6% Coelecaryon oxycarpum FR 14.3% 36.1% 1.7%

Maesobotria batteri FR 2.4% 3.7% Sacoglottis gabonensis FR 37.6% 50.3% 30.3%

64 Scytopetalum tieghemmi FR 22.0% 34.8%

Unknown FR 5.0% 13.6%

Craterispermum caudatum LM 12.4% 19.6%

Maesobotria batteri LY 0.9% 1.4% 6 2015 1.68 0.76 1.72 0.83 60.1% N=206 scans Coelecaryon oxycarpum FR 2.2% 4.3%

Liana FR 4.8% 9.9%

Memecylon lateriflorum FR 1.2% 2.5% Sacoglottis gabonensis FR 28.5% 37.7% 19.8% Scytopetalum tieghemmi FR 29.8% 30.0% 29.5%

Uapaca esculenta FR 9.2% 18.1% Craterispermum caudatum LM 3.2% 4.9% 1.6% Liana LY 2.8% 2.4% 3.2% Maesobotria batteri LY 12.7% 4.2% 20.9% Continued 64

Table 2.4 continued

Unknown LY 1.2% 2.5%

Unknown LY 1.2% 2.5% Mushrooms OT 4.2% 5.9% 2.6% 7 2015 1.80 0.87 2.27 0.91 44.2% N=153 scans Canthium tecbe FR 3.0% 6.9% Memecylon lateriflorum FR 5.5% 8.3% 3.4% Musanga cercopioides FR 15.4% 15.5% 15.3%

Oldfieldia africanum FR 16.7% 37.9%

Pachypondathium staudti FR 1.1% 2.0% Sacoglottis gabonensis FR 9.3% 11.8% 7.2%

Uapaca esculenta FR 5.0% 8.9%

65 Xylopia taiensis FR 3.1% 5.6%

Craterispermum caudatum LM 10.4% 18.6% Cersalia afzeli LY 4.4% 5.2% 3.8% Liana LY 5.5% 2.5% 7.9% Maesobotria batteri LY 14.8% 11.9% 17.1%

Xylopia quintasii LY 4.4% 7.9%

Mushrooms OT 1.3% 2.3% 8 2015 0.69 0.50 1.44 0.81 14.6% N=153 scans Canthium tecbe FR 33.3% 80.9% Memecylon lateriflorum FR 29.1% 8.3% 43.7% Musanga cercopioides FR 9.9% 4.1% 14.0%

Oldfielda africanum FR 2.9% 5.0%

Craterispermum caudatum LM 5.6% 9.5%

Maesobotria batteri LY 15.1% 25.6% Mushrooms OT 4.0% 6.6% 2.2% 65

2.5a. Fruit Species 7-13 8-13 9-13 10-13 11-13 12-13 1-14 2-14 3-14 4-14 Anthonota fragrans A C Chrysophylum taiensis A 1.4 1.4 0.4 C 6.0 0.6 Coelocaryon oxicarpum A 0.7 1.1 0.4 C 0.4 Dialium aubrevillei A 0.6 0.6 0.8 1.4 0.6 0.6 C 0.5 18.2 19.3 54.4 88.7 Diospyros manni A 0.2 C 0.5 Diospyros sanza-minika A 0.3 0.3 C 6.4 16.1 3.9 Diosoyros soubreana A 0.6 0.2 C 33.6 43.3 37.2 Memecylon lateriflorum A 0.1 0.2 C Nauclea pobeguini A 0.5 1.0 1.0 0.6 C 1.8 Oldfieldia africanum A 0.4 0.2

66 C 29.0 26.7 6.4

Parinari excelsa A 0.2 C 2.9 5.7 Pycnanthus angolensis A 0.2 0.4 C 8.8 4.4 46.2 9.4 Continued 5. Table 2.5. Mean monthly fruit availability (A) and monthly fruit consumption (C, percent of monthly diet) by the pooled Diana monkey group between July 2013-April 2014 (2.5a), and October 2014-August 2015 (2.5b).

Table 2.5 Continued

Fruit Species 7-13 8-13 9-13 10-13 11-13 12-13 1-14 2-14 3-14 4-14 Sacoglottis gabonensis A 0.7 1.4 0.1 C 47.7 69.5 70.6 17.9 Scytopetalum tieghemmi A 0.3 C 13.8 Spondianthus preussi A C 1.1 Syzygium rowlandii A 0.4 0.8 0.1 C Tetracera potateria A 0.4 1.2 C 3.3 Uapaca guienensis A 0.1 0.1 C 1.7 16.9 6.5 1.6 4.8 67 2.5b Species 10-14 11-14 1-15 2-15 3-15 4-15 5-15 6-15 7-15 8-15 Anthonota fragrans A 0.2 1.0 0.1 C 5.4 Chrysophylum taiensis A C 12.9 6.4 Coelocaryon oxicarpum A 0.4 1.3 1.3 1.1 2.0 0.6 0.8 0.6 C 9.6 14.3 2.2 Dialium aubrevillei A 1.0 0.6 0.1 C 18.0 55.5 50.9 Diospyros manni A C 10.2 0.6 Diospyros sanza-minika A 0.1 C 3.2 Continued

Table 2.5 Continued

Species 10-14 11-14 1-15 2-15 3-15 4-15 5-15 6-15 7-15 8-15 Diosoyros soubreana A C 48.3 28.6 4.1 1.5 Memecylon lateriflorum A 0.6 C 6.4 13.1 1.2 5.5 29.1 Nauclea pobeguini A 0.5 0.4 C Oldfieldia africanum A 0.5 C 16.7 2.9 Parinari excelsa A 0.4 1.0 0.9 0.1 C 4.2 5.4 22.4 Pycnanthus angolensis A C 9.0 Sacoglottis gabonensis A 0.6 0.8 0.3 0.4 0.8 1.0 1.2 C 64.2 29.7 1.5 37.6 28.5 9.3

68 Scytopetalum tieghemmi A 0.4

C 22.0 29.8 Spondianthus preussi A 0.4 C Syzygium rowlandii A 3.0 2.0 C 12.4 12.5 Tetracera potateria A 1.8 3.0 C Uapaca guienensis A 0.3 C

Month Fruit Fruit Consumption Availability Pooled Diana 1 Diana 2 July 2013 0.02 40.0% 43.5% 36.9% August 2013 0.11 52.7% 49.1% 56.5% September 2013 0.20 43.9% 51.7% 35.5% October 2013 0.14 46.3% 52.5% 40.0% November 2013 0.16 25.3% 34.8% 18.2% December 2013 0.18 36.5% 44.3% 28.1% January 2014 0.20 49.2% 48.2% 49.1% February 2014 0.18 37.3% 32.2% 42.5% March 2014 0.10 14.0% 14.1% 13.9% April 2014 0.09 29.8% 31.3% 28.7%

October 2014 0.26 40.2% 39.4% November 2014 0.30 48.7% 48.7%

January 2015 0.13 36.5% 32.6% 39.9% February 2015 0.16 45.5% 45.5% March 2015 0.14 26.5% 21.9% 30.4% April 2015 0.08 49.5% 17.1% 24.9% May 2015 0.15 18.0% 12.9% 25.4% June 2015 0.07 18.4% 18.6% 17.7% July 2015 0.11 17.3% 18.4% 15.8% August 2015 0.12 12.8% 12.9% 12.6% 6. Table 2.6 Monthly fruit availability for all trees on phenology transects, and monthly fruit consumption by Diana 1, Diana 2, and the pooled Diana monkey group data.

Species Overall Diana 1 Diana 2 Anthonota fragrans ρ= -0.11, p= 0.63 ρ= -0.11, p= 0.63 Chrysophylum taiensis ρ= 0.06, p= 0.80 ρ= 0.22, p= 0.32 ρ= 0.15, p= 0.51 Coelycarion oxycarpum ρ= 0.29, p= 0.20 ρ= 0.31, p= 0.18 ρ= 0.46, p= 0.04 Dialium aubrevillei ρ= 0.24, p= 0.29 ρ= 0.27, p= 0.24 ρ= 0.17, p= 0.45 Diospyros manni ρ= 0.49, p= 0.02 ρ= -0.07, p= 0.76 ρ= 0.99, p< 0.01 Diospyros sanza-minika ρ= 0.01, p= 0.98 ρ= -0.15, p= 0.51 ρ= 0.08, p= 0.72 Diospyros soubreana ρ= 0.03, p= 0.91 ρ= 0.09, p= 0.71 ρ= 0.06, p= 0.81 Memecylon lateriflorum ρ= -0.23, p= 0.33 ρ= -0.17, p= 0.47 ρ= -0.20, p= 0.40 Napoleona leonensis ρ= -0.14, p= 0.55 ρ= -0.14, p= 0.55 Oldfieldia africanum ρ= 0.48, p= 0.03 ρ= 0.22, p= 0.34 ρ= 0.54, p= 0.01 Parinari excelsa ρ= 0.56, p= 0.01 ρ= 0.29, p= 0.20 ρ= 0.38, p= 0.09 Parkia bicolor ρ= 0.33, p= 0.14 ρ= 0.42, p= 0.06 ρ= 0.42, p= 0.06 Pycnanthus angolensis ρ= -0.23, p= 0.33 ρ= -0.17, p= 0.47 ρ= -0.20, p= 0.39 Sacoglottis gabonensis ρ= 0.62, p< 0.01 ρ=0 0.46, p= 0.04 ρ= 0.66, p< 0.01 Scytopetalum tieghemmi ρ= 0.35, p= 0.12 ρ= -0.08, p= 0.75 ρ= 0.40, p= 0.07 Syzygium rowlandi ρ= 0.11, p= 0.63 ρ= 0.11, p= 0.63 Tetracera potateria ρ= 0.32, p= 0.16 ρ= 0.32, p= 0.16 Uapaca guiensis ρ= 0.12, p= 0.94 ρ= 0.17, p= 0.47 ρ= -0.20, p= 0.39 7. Table 2.7. Spearman’s rank correlations between mean monthly fruit availability and consumption; bold indicates two-tailed significance at the 0.05 level.

Overall Diana 1 Diana 2 Species N Density %TBA N Density %TBA N Density %TBA Unknown 585 11.8% 10.8% 343 11.9% 11.9% 333 9.9% 8.7% Acioa scabrifolia 1 0.0% 0.0% 1 0.0% 0.0% 0.0% 0.0% Aidia genipaflora 2 0.0% 0.0% 1 0.0% 0.0% 2 0.0% 0.0% Anthonota fragrans 8 0.7% 1.7% 5 1.0% 2.4% 3 0.3% 0.6% Anthonota sassandraensis 7 0.2% 0.2% 4 0.2% 0.3% 6 0.3% 0.3% Bancovia bancoensis 3 0.1% 0.1% 3 0.1% 0.1% Baphia nitida 1 0.0% 0.0% 1 0.0% 0.0% Berlinia grandiflora 21 0.9% 1.3% 16 1.1% 1.8% 12 0.5% 0.5% Beshia bettei 1 0.0% 0.0% 1 0.0% 0.0% 1 0.0% 0.0% Bombax brevicuspes 2 0.2% 0.5% 2 0.3% 0.9% 71

Bussea occidentalis 34 1.0% 1.0% 17 0.8% 0.5% 22 1.2% 1.4% Caloncoba brevicuspes 5 0.1% 0.1% 1 0.1% 0.0% 5 0.1% 0.1% Calpocalyx brevibacteatus 205 3.6% 3.3% 101 2.5% 1.0% 147 4.3% 5.2% Canarium schweinfurthii 1 0.1% 0.4% 1 0.2% 0.7% 1 0.2% 0.7% Carapa procera 3 0.0% 0.0% 2 0.1% 0.0% 2 0.0% 0.0% Chrysophylum taiensis 4 0.2% 0.2% 2 0.2% 0.3% 2 0.1% 0.1% Coelocaryon oxycarpum 6 0.4% 0.5% 6 0.6% 0.9% 3 0.3% 0.5% Cola lateritia 10 0.1% 0.0% 4 0.1% 0.0% 7 0.1% 0.0% Cola nitida 3 0.0% 0.0% 1 0.0% 0.0% 3 0.1% 0.0% Corynanthe pachyceras 55 1.5% 1.4% 43 2.1% 2.0% 17 0.6% 0.6% Continued 8. Table 2.8. Number, relative density, and proportion of total basal area of trees in the entire study area and the home range of Diana 1 and 2.

Table 2.8 Continued Coula edulis 106 2.3% 1.5% 48 1.9% 1.3% 68 2.3% 1.7% Coula gigantea 3 0.0% 0.0% 3 0.1% 0.0% Dacryodes klaineana 15 0.6% 0.8% 12 1.0% 1.3% 5 0.3% 0.6% Dialium aubrevillei 13 0.8% 1.3% 7 0.8% 1.5% 9 0.8% 1.2% Dicapetalum toxicarpum 2 0.0% 0.0% 2 0.0% 0.0% 2 0.0% 0.0% Diospyros canaliculata 194 2.4% 0.7% 128 2.8% 0.9% 113 2.1% 0.7% Diospyros ivoriensis 1 0.0% 0.0% 1 0.0% 0.0% Diospyros manni 573 7.6% 2.6% 336 7.5% 2.5% 334 6.8% 2.7% Diospyros sanza-minika 146 3.7% 2.5% 76 3.4% 2.4% 91 3.4% 2.5% Diospyros soubreana 621 7.1% 1.9% 390 7.6% 2.1% 349 6.2% 1.9%

Drypetas gilgeana 43 0.6% 0.2% 23 0.4% 0.1% 24 0.5% 0.3% 72

Elasticoides 4 0.0% 0.0% 3 0.0% 0.0% 3 0.0% 0.0%

Eleinas guineensis 1 0.1% 0.1% 1 0.1% 0.1% Enantia polycarpa 8 0.1% 0.0% 5 0.1% 0.0% 7 0.1% 0.1% Erythroflorum ivoriensis 6 0.3% 0.3% 5 0.3% 0.4% 4 0.3% 0.5% Ficus sp. 1 0.0% 0.0% 1 0.0% 0.0% 1 0.0% 0.0% Garcinia afzeli 31 0.5% 0.2% 17 0.4% 0.1% 21 0.5% 0.2% Garcinia cola 2 0.0% 0.0% 2 0.0% 0.0% 2 0.0% 0.0% Ge. Pianom 4 0.0% 0.0% 4 0.1% 0.0% 0.0% 0.0% Gilbertiodendron preussi 28 0.7% 0.7% 6 0.2% 0.3% 22 0.9% 0.9% Gilbertiodendron splendiforum 62 1.2% 0.8% 48 1.6% 1.0% 14 0.5% 0.4% Guibourtia ehie 1 0.1% 0.3% 1 0.2% 0.5% Heritia utilis 339 6.4% 5.7% 219 6.4% 5.4% 250 7.1% 6.7% Continued

Table 2.8 Continued Hydea genparfloa 1 0.0% 0.0% 1 0.0% 0.0% Klainodoxa gabonensis 1 0.1% 0.5% 1 0.2% 0.8% Lannea welwitschii 2 0.1% 0.1% 2 0.2% 0.2% Lophira alata 32 1.7% 4.4% 24 1.9% 4.8% 14 1.4% 3.7% Macaranga sp. 4 0.1% 0.0% 4 0.1% 0.0% 3 0.1% 0.0% Maesobotria batteri 39 0.4% 0.1% 15 0.2% 0.0% 28 0.4% 0.1% Massularia acuminata 1 0.0% 0.0% 1 0.0% 0.0% Memecylon guinensis 3 0.0% 0.0% 3 0.0% 0.0% Memecylon lateriflorum 300 4.9% 2.1% 161 4.6% 2.0% 181 4.5% 2.1% Musanga cecropioides 6 0.2% 0.3% 1 0.1% 0.2% 6 0.3% 0.6%

73 Napoleona leonensis 175 1.9% 0.5% 103 1.9% 0.5% 100 1.7% 0.5%

Nauclea diderrichii 1 0.1% 0.5% 1 0.2% 0.8% Nauclea pobeguini 6 0.4% 0.8% 1 0.2% 0.6% 5 0.5% 0.7% Octolobus angustatus 32 0.3% 0.1% 28 0.5% 0.1% 6 0.1% 0.0% Oldfieldia africana 41 1.3% 1.6% 23 1.0% 1.0% 24 1.4% 2.1% Omphalocarpum ahia 3 0.1% 0.1% 3 0.1% 0.1% 2 0.1% 0.1% Ouratea affinis 2 0.0% 0.0% 1 0.0% 0.0% 2 0.0% 0.0% Pancovia bijuga 3 0.1% 0.1% 3 0.2% 0.2% Panda oleosa 26 0.4% 0.2% 9 0.3% 0.2% 20 0.5% 0.3% Parinari aubrevillei 2 0.1% 0.0% 1 0.1% 0.2% 1 0.1% 0.0% Parinari excelsa 3 0.3% 1.0% 2 0.3% 0.9% 1 0.2% 0.9% Parinari glabra 1 0.1% 0.3% 1 0.2% 0.6% Parkia bicolor 7 0.6% 1.5% 4 0.5% 1.0% 4 0.5% 1.7% Continued

Table 2.8 Continued Pentaclethra macrophylla 10 0.3% 0.6% 9 0.5% 0.8% 5 0.5% 0.9% Pentadesma butacerea 2 0.1% 0.2% 1 0.1% 0.3% 2 0.1% 0.3% Piptadeniastrum africanum 6 0.8% 2.7% 2 0.5% 1.4% 5 1.1% 4.2% Polyathia olivieri 70 0.7% 0.2% 36 0.6% 0.2% 49 0.7% 0.2% Popovia sp. 1 0.0% 0.0% 1 0.0% 0.0% Pycnanthus angolensis 14 0.6% 0.9% 10 0.8% 1.4% 11 0.8% 1.5% Rinorea longicuspus 24 0.3% 0.1% 17 0.3% 0.1% 9 0.1% 0.0% Sacoglottis gabonensis 118 7.6% 22.3% 78 8.4% 25.4% 79 7.0% 20.2% Scottelia chevalieri 66 1.6% 2.0% 45 1.6% 0.9% 32 1.4% 2.8% Scytopetalum tieghemmi 234 5.1% 3.6% 130 4.4% 2.9% 149 5.1% 4.1%

Soyauxia floribonda 17 0.2% 0.1% 8 0.2% 0.1% 16 0.3% 0.1% 74

Spondianthus preussi 205 5.6% 5.0% 129 6.0% 5.4% 121 5.2% 5.3% Strephonyma pseudocala 120 1.7% 0.6% 67 1.6% 0.6% 89 2.0% 0.9% Strombosia glaucescens 3 0.0% 0.0% 1 0.0% 0.0% 2 0.0% 0.0% Syzygium rowlandi 8 0.3% 0.3% 4 0.2% 0.1% 8 0.5% 0.6% Tetrapleura tetraptera 2 0.1% 0.3% 2 0.2% 0.5% 2 0.2% 0.5% Trichoscypha arborea 90 1.7% 1.2% 62 1.8% 0.8% 48 1.6% 1.5% Trichoscypha bettei 24 0.2% 0.0% 10 0.2% 0.0% 17 0.2% 0.1% Uapaca esculenta 43 1.5% 3.0% 28 1.4% 2.8% 29 1.8% 4.6% Uapaca guinensis 32 0.7% 0.8% 21 0.7% 1.0% 22 0.9% 1.4% Xylopia aethiopica 9 0.2% 0.2% 34 0.6% 0.1% 8 0.3% 0.3% Xylopia parviflora 54 0.6% 0.2% 13 0.4% 0.2% 32 0.5% 0.2% Xylopia quintasii 39 0.8% 0.4% 64 1.4% 0.6% 35 1.0% 0.6%

Unknown Diana 1 Diana 2 Food Diet Density L Diet Density L Diet Density L Sacoglottis gabonensis F 20.8% 7.5% 0.47 19.7% 8.2% 0.41 21.7% 7.0% 0.51 Dialium aubrevillei F 14.0% 0.8% 0.89 14.9% 0.8% 0.89 10.4% 0.8% 0.86 Diospyros soubreana F 9.9% 7.1% 0.17 7.3% 7.4% -0.01 12.2% 6.2% 0.33 Oldfieldia africanum F 5.0% 1.3% 0.58 6.6% 1.0% 0.73 3.6% 1.2% 0.48 Pycnanthus angolensis F 4.8% 0.6% 0.79 5.9% 0.8% 0.77 3.8% 0.8% 0.65 Scottelia chevalieri F 2.9% 1.6% 0.28 3.5% 1.6% 0.38 2.4% 1.4% 0.25 Scytopetalum tieghemmi F 2.8% 5.1% -0.29 1.4% 4.3% -0.52 4.0% 5.1% -0.12 Maesobotria batteri L 2.5% 0.4% 0.75 1.0% 0.2% 0.63 3.8% 0.4% 0.81 Memecylon lateriflorum F 2.0% 4.9% -0.41 0.7% 4.5% -0.72 3.2% 4.5% -0.17 Musanga cercopioides F 2.0% 0.2% 0.80 2.5% 0.1% 0.90 1.5% 0.3% 0.63 Parinari excelsa F 2.0% 0.3% 0.71 0.6% 0.3% 0.34 3.1% 0.2% 0.86 Diospyros sanza-minika F 1.8% 3.7% -0.34 1.7% 3.3% -0.31 1.9% 3.4% -0.28 Uapaca esculenta F 1.7% 1.5% 0.06 2.2% 1.4% 0.22 1.2% 1.8% -0.19 Uapaca guinensis F 1.7% 0.7% 0.41 1.0% 0.7% 0.21 2.2% 0.9% 0.44

Chrysophylum taiensis F 1.4% 0.2% 0.78 1.1% 0.2% 0.69 1.8% 0.1% 0.90 75

Continued 9. Table 2.9. Food items, their rates of consumption, density, mean DBH, and relative preference (L) for the pooled Diana monkey sample, and both groups. Positive preference values (bold) indicate preferred foods eaten more frequently than their abundance

Table 2.9 Continued Dacryodes klaineana F 1.4% 0.6% 0.38 3.1% 0.9% 0.54 0.5% 0.3% 0.17 Coelecaryon oxycarpum F 1.1% 0.4% 0.51 1.4% 0.6% 0.40 0.9% 0.3% 0.47 Syzygium rowlandi F 0.9% 0.3% 0.51 1.7% 0.5% 0.58 Maesobotria batteri F 0.8% 0.4% 0.39 0.3% 0.2% 0.18 1.2% 0.4% 0.51 Parkia bicolor F 0.7% 0.6% 0.08 1.3% 0.5% 0.49 0.2% 0.6% -0.45 Diospyros manni F 0.6% 7.6% -0.84 1.3% 7.4% -0.70 0.1% 6.9% -0.99 Pancovia bijuga F 0.6% 0.1% 0.65 1.1% 0.2% 0.70 Dialium aubrevillei L 0.4% 0.8% -0.35 0.7% 0.8% -0.08 0.1% 0.8% -0.74 Napoleona leonensis F 0.3% 1.9% -0.70 0.1% 1.8% -0.92 0.6% 1.7% -0.51 Piptadenastrium africanum FL 0.3% 1.1% -0.56 0.7% 0.8% -0.10 Polyathia olivieri F 0.3% 0.7% -0.41 0.5% 0.7% -0.15 Diospyros soubreana L 0.3% 7.1% -0.93 0.5% 7.4% -0.86

76 Xylopia quintasii L 0.2% 2.0% -0.80 0.4% 4.3% -0.83

Anthonota fragrans F 0.2% 0.7% -0.57 0.4% 0.3% 0.13 Diospyros canaliculata L 0.1% 2.4% -0.91 0.2% 2.1% -0.82 Nauclea pobeguini F 0.1% 0.4% -0.60 0.2% 0.2% -0.03 Caloncoba brevipes F 0.1% 0.1% 0.02 0.2% 0.2% 0.12 Spondianthus preussi F 0.1% 5.6% -0.97 0.2% 5.9% -0.95

Species Location Duration Focus Fruit Insects Leaves Other C. d. diana1 Taï, Côte Jul. 2013-Aug. 2015 2 groups 32.8 63.5 3.7 0.5 d’Ivoire (20 months) C. d. diana2 Taï, Jul. 2004-Jul. 2009 4 groups 56.0 37.7 6.3 Côte d’Ivoire (61 months) C. d. diana3 Taï, Jan. 2001-Dec. 2001 1 group 70.9 26.5 2.6 Côte d’Ivoire (12 months) C. d. diana4 Taï, Sept. 2000-Oct. 2001 2 groups 59.0 16.0 16.0 9.0 Côte d’Ivoire (13 months) C. d. diana5 Taï, Oct. 1992-Sept. 1993 2 groups 52.0 37.8 3.5 6.7 Côte d’Ivoire (12 months) C. d. diana6 Tiwai Island, Jul. 1983-Jun. 1984 2 groups 26.5 27.7 12.6 33.2 Sierra Leone (12 months) C. d. diana7 Tiwai Island, Feb. 1988-Apr. 1989 2 groups 23.9 9.9 32.0 34.2 Sierra Leone (15 months) C. roloway8 Bia National Nov. 1976-Jul. 1977 1 group 31.0 25.0 7.0 37.0 Park, Ghana (8 months) Table footnote. 1. Present study. 2. Kane and McGraw, in preparation 3. Eckardt and Zuberbühler, 2004 4. Buzzard 2004, 2006 5. Wachter et al, 1997 6. Oates and Whitesides, 1990. 7. Hill, 1991. 8. Curtin, 2002. Table 2.10. Studies of the Diana monkey (Cercopithecus diana) and Roloway monkeys (C. roloway) diet.

2000-2001 2004-2009 2013-2015 Buzzard, 2004 Kane and McGraw, in This study review Sacoglottis gabonensis 17 Sacoglottis 13 Sacoglottis gabonensis 21 (FR) gabonensis (FR) (FR) Dialium aubrevillei 14 Dialium aubrevillei 10 Dialium aubrevillei 14 (FR) (FR) (FR) Memecylon laterflorum 8 Craterispermum 5 Diospyros soubreana 10 (FR) caudatum (L) (FR) Craterispermum 6 Diospyros soubreana 5 Craterispermum 6 caudatum (L) (FR) caudatum (L) Diospyros soubreana 3 Diospyros manni 4 Oldfieldia africanum 5 (FR) (FR) (FR) Uapaca esculenta (FR) 3 Pycnanthus 3 Pycnanthus angolensis 5 angolensis (FR) (FR) Oldfieldia africanum 3 Oldfieldia africanum 3 Scottelia chevalieri 3 (FR) (FR) (FR) Maesobotria batteri 2 Parinari excelsa (FR) 3 Scytopetalum tieghemmi 3 (FR) (FR) Parkia bicolor (FR) 2 Scytopetalum 2 Maesobotria batteri 3 tieghemmi (FR) (FR) Aphanaotilis leptanta 1 Chrysophylum 2 Memecylon lateriflorum 2 (FR) taiensis (FR) (FR) Table 2.11. Dietary proportions of the top ten plant species contributing to the diet of Diana monkeys at Taï in three different studies.

Foraging Traveling Resting Social 2000-20011 40.6 27.7 24.4 7.3 2004-20092 24.1 43.1 32.2 0.7 2013-20153 53.2 26.6 18.3 2.9 Table footnote. 1. Buzzard, 2004. 2. Kane and McGraw, in revision. 3. Present study. Table 2.12. Activity budgets of Diana monkeys at Taï between 2000-2001, 2004-2009, and 2013-2015

Species Location Groups Dietary comparisons Study Cercopithecus Kakamega, 2 neighboring groups 64-95% monthly overlap in food categories Gathua, 2000 ascanius Kenya 33-69% monthly overlap in species-specific plant parts Cercopithecus Taï, Cote 2 neighboring groups 93% overlap in food categories over 17 months This study diana d’Ivoire 68% overlap in species-specific plant parts

Pairwise comparisons 78-98% monthly overlap in food categories Kane and between 3 neighboring 15-91% monthly overlap in species-specific plant parts McGraw, in groups review 91-98% overlap in food categories over 61 months; 72- 3 neighboring groups, 79% in species-specific plant parts 1 group 2 km away 55-100% seasonal overlap in food categories, 17-96% in species-specific plant parts

90% overlap in food categories over 61 months; 57%

79 2 neighboring groups in species-specific plant parts

2-100% seasonal overlap in food categories, 2-67% in species-specific plant parts

Tiwai, Sierra 87% overlap in consumption of flowers, fruit, seeds, Oates and Leone exudates, leaves, invertebrates, and other material Whitesides, across 16 months 1990

Cercopithecus Kibale, Uganda 2 neighboring groups 45% overlap in plant species over 15 months Rudran, 1978 mitis 23-65% monthly overlap in plant species a, b

4 neighboring groups, 33.5% overlap in top 20 food species among Butysnki, neighboring groups 1990 Chlorocebus Loskop Dam Pairwise comparisons 76-94% overlap in consumption of fruits, leaves, Tournier et aethiops Nature between 6 neighboring flowers, gum, bark, branches, and buds between pairs al. 2014 Reserve, groups of neighboring groups over 4 months South Africa Table 2.13. Intergroup dietary comparisons between guenon groups in the same site.

FIGURES

60% 0.35

50% 0.30

0.25 40% 0.20 30% 0.15

20% Food Availability Food

Proportion of Fruit of Proportion 0.10

10% 0.05

0% 0.00

Overall Group 1 Group 2 Fruit Availability

6. Figure 2.1. Monthly contribution of fruit to the diet of Diana monkeys during this study period, and mean monthly fruit availability over the same period.

7. Figure 2.2. Home range of Diana 1 (in yellow) and Diana 2 (in blue), with overlapping territory in green. The location of the botanical transects and identified and measured trees indicated by colored circles. Blue circles indicate trees in Diana 2’s home range, orange in Diana 1’s, and green in overlapping territory.

8. Figure 2.3. Distribution of 31 species of feeding trees along transects in the home ranges of Diana 1 and 2. Different colored circles indicate different species.

REFERENCES

Altmann JA. 1974. Observational study of behavior: sampling methods. Behaviour 49: 227-267.

Altmann JA. 1980. Baboon Mothers and Infants. Chicago: University of Chicago Press.

Anderson DP. 2001. Tree phenology and distribution, and their relation to chimpanzee social ecology in the Taï National Park, Côte D’Ivoire. PhD dissertation: University of Wisconsin, Madison.

Anderson DP, Nordheim EV, Moermond TC, Gone Bi ZB, and Boesch C. 2005. Factors influencing tree phenology in Taï National Park, Côte d’Ivoire. Biotropica 37(4): 631-640.

Bitty EA, Gonedelé Bi S, Bene Koffi JC, Kouassi PK, McGraw WS. 2015. Cocoa farming and primate extirpation inside Cote d’Ivoire’s protected areas. Tropical Conservation Science 8: 95-113.

Butynski TM. 1990. Comparative ecology of blue monkeys (Cercopithecus mitis) in high- and low-density subpopulations. Ecological Monographs 60: 1-26

Buzzard PJ. 2004. Interspecific competition among Cercopithecus campbelli, C. petaurista, and C. diana at Taï Forest, Côte d’Ivoire. PhD Dissertation: Columbia University.

Buzzard PJ. 2006. Ecological partitioning of Cercopithecus campbelli, C. petaurista, and C. diana in the Taï Forest. International Journal of Primatology 27(2): 529-558.

Buzzard PJ, Eckardt W. 2007. Social systems of the Taï guenons (Cercopithecus spp.). In Zuberbühler K, McGraw S, and Noë R, eds. Monkeys of the Taï Forest: An African Primate Community. Cambridge: Cambridge University Press.

Candiotti A, Coye C, Ouattara K, Petit EJ, Vallet D, Zuberbühler K, Lemasson A. 2015. Female bonds and kinship in forest guenons. International Journal of Primatology 36: 332-352.

Chapman CA, Chapman LJ. 1990. Dietary variability in primate populations. Primates 31: 121-128.

Chapman CA, Chapman LJ, Cords M, Mwangi Gathua J, Gautier-Hion A, Lambert JE, Rode K, Tutin CEG, White LJ. 2002. Variation in the diets of Cercopithecus species: differences within forests, among forests, and between species. In, Glenn ME and

Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. Chicago: University of Chicago Press. 325-350.

Chapman CA, Wrangham R, Chapman LJ. 1994. Indices of habitat-wide fruit abundance in tropical forests. Biotropica 26: 160-171.

Chivers DJ. 1998. Measuring food intake in wild animals: primates. Proceedings of the Nutrition Society 57: 321-332.

Clutton-Brock TH. 1977. Some aspects of intraspecific variation in feeding and ranging behavior in primates. In, Clutton-Brock TH, 1977. Primate Ecology: Studies of feeding and ranging behavior in lemurs, monkeys and apes. New York: Academic press. 539-556.

Cords M. 1986.Interspecific and intraspecific variation in the diet of two forest guenons, Cercopithecus ascanius and C. mitis. The Journal of Animal Ecology 55: 811-827.

Cords M.1987. Mixed-species association of Cercopithecus monkeys in the Kakamega Forest, Kenya. University of California Publications in Zoology 117: 1-109.

Cords M. 2011. The behavior, ecology, and social evolution of cercopithecine monkeys. In, Mitani JC, Call J, Kappeler PM, Palombit RA, Silk JB, eds. The Evolution of Primate Societies. Chicago: University of Chicago Press. 91-112.

DaSilva GL. 1994. Diet of Colobus polykomos on Tiwai Island: selection of food in relation to its seasonal abundance and nutritional quality. International Journal of Primatology 15: 655-680.

Eckardt W, Zuberbühler K. 2004. Cooperations and competition in two forest monkeys. Behavioral Ecology 15: 400-411.

Foerster S, Cords M, Monfort SL. 2011. Social behavior, foraging strategies, and fecal glucocorticoids in female blue monkeys (Cercopithecus mitis): potential fitness benefits of high rank in a forest guenon. American Journal of Primatology 73: 870- 882.

Galat G, Galat-Luong A. 1985. La communaute de primates diurnes de la foret de Tai, Côte d’Ivoire. Terre Vie 40:3-32.

Gathua JM. 2000. Intraspecific variation in foraging patterns of redtail monkeys (Cercopithecus ascanius) in the Kakamega Forest, Kenya. PhD Dissertation: Columbia University.

Gautier-Hion A. 1988. The diet and dietary habits of forest guenons. In, Gautier-Hion A, Bourlière F, and Gautier JP, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. New York: Cambridge University Press. 257-283.

Gonedelé Bi S, Koné I, Bitty EA, Béné Koffi JC, Akpatou B, Zinner D. 2012. Distribution and conservation status of catarrhine primates in Côte d’Ivoire (West Africa). Folia Primatologica 83: 11-23.

Hill CM. 1994. The role of female Diana monkeys, Cercopithecus diana, in territorial defence. Animal Behaviour 47: 425-431.

Holmes RT, Pitelka FA. 1968. Food overlap among coexisting sandpipers on northern Alaskan tundra. Systematics of Zoology 17:305-318.

Isbell LA, Pruetz JD. 1998. Differences between vervets (Cercopithecus aethiops) and Patas monkeys (Erythrocebus patas) in agonistic interactions between adult females. International Journal of Primatology 19: 837-855.

Ivlev VS. 1961. Experimental ecology of the feeding of fishes. New Haven: Yale University Press.

Jaffe KE, Isbell LA. 2011. The guenons: polyspecific associations in socioecological perspective. In, Campbell C, Fuentes A, MacKinnon K, Bearder S, Stumpf R, eds. Primates in Perspective. Oxford: Oxford University Press. 277-300.

Kane EE, Gnepa F. 2016. An infanticide attempt after male takeover in Diana monkeys (Cercopithecus diana diana) in Taï, Côte d’Ivoire. African Primates 11: 37-40.

Klass K, Cords M. 2015. Agonism and dominance in female blue monkeys. American Journal of Primatology 77: 1299-1315.

Lambert JE. 2007. Seasonality, fallback strategies, and natural selection: a chimpanzee and cercopithecoid model for interpreting the evolution of hominin diet. In, Ungar PS, ed. Evolution of the Human Diet: the Known, the Unknown, and the Unknowable. Oxford: Oxford University Press. 324-343.

Lechowicz MJ. 1982. The sampling characteristics of electivity indices. Oecologia 52: 22-30.

McGraw WS. 1998. Comparative locomotion and habitat use of six monkeys in the Taï Forest, Ivory Coast. American Journal of Physical Anthropology 105: 492-510.

McGraw WS, Plavcan JM, Adachi-Kanazawa K. 2002. Adult female Cercopithecus diana employ canine teeth to kill another adult female C. diana. International Journal of Primatology 23: 1301-1308.

McGraw WS, Zuberbühler K. 2007. The Monkeys of the Taï Forest: an introduction. In, McGraw WS, Zuberbühler K, Noë R, eds. Monkeys of the Taï Forest: an African Primate Community. Cambridge: Cambridge University Press. 1-48.

Oates JF, Whitesides GH. 1990. Association between olive colobus (Procolobus verus), Diana guenons (Cercopithecus diana), and other forest monkeys in Sierra Leone. American Journal of Primatology 21:129-146.

Pazol K, Cords M. 2005. Seasonal variation in feeding behavior, competition and female social relationships in a forest dwelling guenon, the blue monkey (Cercopithecus mitis stuhlmanni) in the Kakamega Forest, Kenya. Behavioral Ecology and Sociobiology 58: 566-577.

Refisch J, Koné I. 2005. Impact of commercial hunting on monkey populations in the Taï region, Côte d’Ivoire. Biotropica 37: 136-144.

Rodell MO, Range F, Seppänen JT, Noë R. 2002. Caviar in the rain forest: monkeys as frog-spawn predators in Taï National Park, Ivory Coast. Journal of Tropical Ecology 18: 289-294.

Rowell TE. 1988. The social system of guenons, compared with baboons, macaques, and mangabeys. In, Gautier-Hion A, Bourlière F, and Gautier JP, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. New York: Cambridge University Press. 439-451.

Rudran R. 1978. Socioecology of the Blue monkeys (Cercopithecus mitis stuhlmanni) of the Kibale Forest, Uganda. Smithsonian Contributions to Zoology 249: 148-236.

Sterck EHM, Watts DP, van Schaik CP. 1997. The evolution of female social relationships in nonhuman primates. Behavioral Ecology and Sociobiology 41: 291- 309.

Struhsaker TT. 1997. Ecology of an African Rain Forest. Gainesville, University Press of Florida.

Struhsaker TT. 2010. The Red Colobus Monkeys: Variation in Demography, Behavior, and Ecology of Endangered Species. Oxford: Oxford University Press.

Tutin CEG, Ham RM, White LJT, Harrison MJS. 1997. The primate community of the Lopé Reserve, Gabon: diets, responses to fruit scarcity, and effects on biomass. American Journal of Primatology 42: 1-24.

Tutin CEG. 1999. Fragmented living: behavioural ecology of primates in a forest fragment in the Lopé Reserve, Gabon. Primates 40:249-265.

Wachter B, Schabel M, Noe R. 1997. Diet overlap and polyspecific associations of red colobus and Diana monkeys in the Tai National Park, Ivory Coast. Ethology 103:126.

Wolters S, Zuberbühler K. 2003. Mixed-species associations of Diana and Campbell’s monkeys: the costs and benefits of a forest phenomenon. Behaviour 140: 371-385.

Chapter 3: Food site residence time and social interactions do not reflect dietary preference among wild Diana monkeys

INTRODUCTION

While socioecological models of primate behavior incorporate many factors to explain group dynamics and female behavior, all emphasize that resource distribution and defensibility are significant determinants of social relationships that structure competitive regimes within and between groups [Wrangham, 1980; van Schaik, 1989; Sterck et al.,

1997; Isbell and Young, 2002]. Models generally distinguish between foods with ubiquitous (e.g., mature leaves) or clumped (e.g., ripe fruit) distributions and their relative effects on social interactions. Taxa which feed on ubiquitously distributed foods are not expected to engage in significant inter- or intragroup competition in relation to these food resources because they are of relatively poor nutritional quality and so broadly distributed that there is no way or need to monopolize access. Conversely, primates relying on patchily and discontinuously distributed resources of high nutritional quality are expected to engage in comparatively more competition to access and attempt to monopolize these discrete, high-value food patches [Wrangham, 1980].

As Isbell and Young [2002] note, “patchiness” or “clumpedness” is a difficult characteristic to operationalize, particularly across taxa eating different diets and operating at different scales. For example, what a chimpanzee views as a clump will

88 likely be different from what a tamarin views as a clump. However, Isbell and a number of colleagues have proposed food site “usurpability” as a measurable behavioral consequence of resource distribution [Isbell and Pruetz; 1998, Isbell et al., 1998, Pruetz and Isbell, 2000; Mathy and Isbell, 2001; Chancellor and Isbell, 2009]. Specifically, “a food site is usurpable if it can be taken from a lower-ranking individual” [Isbell and

Pruetz 1998: 839]. A food site’s value and the possibility of taking it from another individual make it worth contesting. Usurpability is time-dependent: the longer an individual forages at a given food site, the greater the risk that someone will contest and potentially usurp that site [Isbell and Young, 2002]. Consequently, the amount of time an individual spends at a food site before moving on is predicted to relate to the characteristics of food items (e.g., distribution, size, value, mechanical properties) and to social pressures (e.g., competition, usurpability, dominance). Foods with longer site residence times, valuable resources, and foods with clumped distributions should be at greater risk of usurpation. The more likely a resource is to be usurped, the more competition it should elicit [Isbell et al., 1998; Chancellor and Isbell, 2009]. Foods which elicit more competition also tend to be ingested at higher rates, and have a higher incidence of cheek pouch caching [Lambert, 2005; Buzzard, 2006]. Most cercopithecines derive the majority of their energy from ripe fruit, supplemented by invertebrates, leaf matter, and other material, so the assumption that ripe fruit is the most valuable food type is a reasonable one [Gautier-Hion, 1988; Cords, 2012]. However, while ripe fruits may be the most valuable resource for most cercopithecines, the relationship between fruit preference and food site residence time remains unclear.

Whether more valuable foods and foods with longer site residence times elicit more competition has only been tested in a few taxa, primarily terrestrial and/or open- habitat primates in wild and captive settings [Papio cynocephalus: Post et al., 1980;

Macaca mulatta: Mathy and Isbell, 2001; Chlorocebus aethiops, Erythrocebus patas:

Isbell et al., 1998; Pruetz and Isbell, 2000; Lemur catta: Gould and Gemmill, 2008].

Because food patches are not just a function of diet and scale, but also habitat, these results may not be applicable to organisms foraging in other environment. A primate moving through a savannah, grassy enclosure, or desert of spiny cactus is foraging in a very different environmental context than a primate moving through a tropical rainforest, regardless of the target food. Aggregated foods (e.g., food patches) may elicit strong competition and lengthy site residence times in particularly sparse or challenging environments because the possible consequences of aggression at a food site may be outweighed by the benefit of increased food intake at that site. On the other hand, in a rich environment with many alternative foods, it may be advantageous to spend less time feeding at valuable food sites where the risk of agonistic encounters are higher.

Seasonality of resource availability adds another layer of complexity: when fruit is readily available, sites may not be worth contesting, whereas in periods of low fruit availability, competition for scarce resouces may increase in frequency or intensity.

In the forest guenons whose socioecology has been studied, the distribution of resources, and social interactions around these resources do not obviously match predictions of classical socioecological theory [Cords, 2000; Pazol and Cords, 2005;

Foerster et al., 2011]. For example, while female blue monkeys (Cercopithecus mitis) do 90 form dominance hierarchies structured by agonistic and affiliative interactions, there were no differences between high- and low-ranked females in their feeding efficiency, feeding time, or number of neighbors while foraging [Cords, 2000]. Even in periods of low fruit availability, agonism in relation to feeding behavior remained rare, with females of all ranks adopting various strategies to avoid conflict including resource switching and foraging with fewer individuals in close proximity [Pazol and Cords, 2005]. The relationship between stress (indicated by fecal glucocorticoid concentrations), rank, and fruit availability was inconclusive, with a rank effect of fecal glucocorticoids only evident in one of the two study groups [Foerster et al., 2011].

To assess how well Diana monkeys fulfill the predictions of socioecological models related to agonism and food value and distribution, I collected data on feeding behavior, site residence time, and social interactions among females in two Diana monkey groups in Cote d’Ivoire’s Taï National Park from 2013-2015. Diana monkeys

(Cercopithecus diana) are forest-dwelling, arboreal primates who consume a diet primarily composed of ripe fruit year-round and supplement their diet with invertebrates and leaves [Kane and McGraw, in review]. I predict that Diana monkeys will have the longest site residence times, highest rates of ingestion, and highest numbers of other individuals within 5m of the focal individual at ripe fruit sites, followed by invertebrate and leaf sites. Considering ripe fruit sites specifically, I predict that Diana monkeys foraging on preferred fruit species will have longer site residence times, higher rates of ingestion, and more individuals within 5m of the focal individual at ripe fruit sites than

Diana monkeys foraging on non-preferred fruit species. I predict that there will be 91 significant differences in the number of females in close proximity to females foraging at fruit sites compared to females foraging at invertebrates or foliage sites, and foraging at preferred fruit sites compared to non-preferred fruit sites. I expect that aggression will occur most frequently at ripe fruit sites. Finally, because food site residence time is expected to be a function of food site value, I assessed seasonal differences in the rate of ingestion, food site residence time, and number of individuals within 5m of the focal individual during different seasons. I expect that all of these will be highest during periods when fruit availability is low, indicating more competition for valuable resources.

METHODS

Study Area and Species

Data were collected in Côte d’Ivoire’s Taï National Park on two groups of habituated Diana monkeys (Cercopithecus diana). Taï National Park is a highly seasonal rainforest, receiveing an average of 1893 mm of rain annually [Anderson et al., 2005]. It is characterized by a long dry season (November-March), a long wet season (April-June), a short dry season (July-August), and a short wet season (September-October) [Anderson et al., 2005]. The two groups, referred to as Diana 1 and Diana 2. Their home ranges are adjacent and contained within the study grid of the Tai Monkey Project. Their home ranges comprised approximately 45 square hectares with approximately 25% overlap

[Chapter 2]. Average group size for Diana monkeys in the Taï Forest is 23.5 individuals, with one adult male, 11-13 adult females, and their offspring [Buzzard and Eckardt,

2007]. Group membership fluctuated over the course of this study and groups were generally smaller than previously reported, with 7-8 adult females in Diana 1, and 8-13 92 adult females in Diana 2. Diana monkeys are female-philopatric, and a male transfer occurred in Diana 1 during the course of this study. Diana monkeys engage in notably more inter- and intra-group aggression than sympatric guenons species, including occasional lethal coalitionary inter-group aggression [McGraw et al., 2002; Buzzard and

Eckardt, 2007].

Data Collection

Data collection occurred from June 2013-April 2014, and May-August 2015.

Groups were sampled on a rotating basis, with each group followed for 4-5 consecutive days every other week. Every morning, the focal group was located in its sleeping tree and followed until it entered a sleeping tree for the night. Thus, observations generally occurred from 07:00-17:00. All data collection protocols were approved by the Ohio

State University IACUC and permit granting bodies in Côte d’Ivoire, and followed the ethical guidelines for noninvasive observational research set out by the International

Primatological Society.

I conducted 5-minute focal follows on individually-identified females to assess feeding behavior, site residence time, and social interactions [Altmann, 1974]. Each female was the focal individual no more than once an hour (e.g., a female who was the focal individual between 8:00 and 8:05 would not be sampled again until at least 9:06).

Because of group spread and low visibility due to Diana monkeys’ extensive use of Taï’s dense canopy, females were opportunistically selected for focal observations. During each focal, I recorded:

1. Rate of ingestion (ROI): The number and species of individual food items

introduced to the mouth per minute.

2. Food site residence time (FSRT): the number of seconds a monkey remained

at a food site before moving. I defined a food site as “any spot at which an

individual stopped to eat food and which was separated [from] other food sites

by hind limb locomotion” [Chancellor and Isbell, 2009: 1450].

3. Neighbors: The number of individuals within 5 meters of the focal individual

and their identification (by name, or age and sex class).

4. Ad libitum notes on all social interactions during the five minute focal,

including aggression (e.g., threaten, chase, display, bite), affiliation (e.g.,

grooming), and nursing. Affiliative behaviors were primarily observed

between adult females and other adults or subadults. Nursing was recorded

separately because nursing infants were not contesting with adult females for

access to food sites and I wanted to determine whether adult females engaged

in different patterns of affiliative behavior with potential competitors at

different foods sites.

5. Ad libitum notes on Diana monkeys’ behavior while feeding, including

notable processing behaviors and foraging style (e.g., unrolled leaves while

searching for invertebrates)

Food Preference

I used Ivlev’s Electivity Index to assess food preference [Strauss, 1979; Loehle and Rittenhouse, 1982; Buzzard, 2004]. This index is calculated as a ratio (I) for a

94 particular plant part, which incorporates the proportion of that food in the diet and the relative abundance of the plant species in the environment (the density):

(퐷푖푒푡푎푟푦 푃푟표푝표푟푡푖표푛 − 퐷푒푛푠푖푡푦) 퐼 = 퐷푖푒푡푎푟푦 푃푟표푝표푟푡푖표푛 + 퐷푒푛푠푖푡푦

I can range from -1 to 1. Preferred foods are eaten more frequently than their abundance in the environment predicts, and have a positive selectivity index, while non-preferred foods are eaten less frequently than their abundance predicts and have a negative selectivity index.

Dietary proportions were derived from scan samples taken every hour by Frederic

Gnépa. To collect these data, F. Gnépa moved through the group and recorded the age, sex-class, and behavior of all visible individuals. When individuals were feeding during the scan sample, he recorded the food type being eaten (e.g., fruit, leaf, insect, and other material), specific attributes of the food (e.g. ripe fruit, young leaf, insect on leaf), and the species being consumed (when fruit or leaves). Individual feeding observations from scan samples were pooled by group, month, and year and divided by the number of days during which sampling occurred, yielding a value of consumption/day which controlled for differences in sampling effort across months.

To determine plant species density, vegetation surveys were carried out between

June 2013 and January 2014 along eleven transects within the home range of these groups. Transects were conducted every 100 m between two trails which run East-West through the study grid. Working with Roman Djobely a local botanist, I measured and identified all trees with a diameter at breast height (DBH) >6.4 cm (i.e., all trees with a circumference at breast height of 20 cm or greater). This is a smaller DBH than is 95 customary because Diana monkeys regularly consume fruit from trees with a DBH <10 cm, including Diospyros soubreana, Diospyros manni, and Maesobotria batteri.

Excluding these trees would have significantly underestimated the number of feeding trees [Buzzard, 2004]. Each tree species’ relative abundance was calculated as the basal area, or the sum of the DBH of all that species’ trees divided by the sum of the DBH of all trees included on transects.

Data Analysis

I used two-tailed univariate ANOVAs to test the relationship between season and

FSRT, ROI, and the number of neighbors for each food type (fruit, invertebrates, and leaves). I also used two-tailed univariate ANOVAs to test relationships between FSRT,

ROI, and number of neighbors, and food type (fruit, invertebrates, leaves). Finally, I used two-tailed univariate ANOVAs to test the relationship between FSRT, ROI, number of neighbors, and fruit species. Fruit species were only included in the latter analysis if they eaten during at least ten focal observations and if their abundance was known (e.g., if they were included on transects). I also used Pearson’s R test to assess correlations between preference (I) and mean FRST, mean ROI, and the mean number of neighbors for these fruit species.

I used chi-square to evaluate the likelihood that the frequencies of nursing, agonism, and affiliation observed during foraging at ripe fruit, invertebrate, leaf, and other food sites were due to random chance. I also used correspondence analysis, which assesses associations between categorical variables, to identify associations between behaviors and food types.

Statistical analyses were conducted using IBM’s SPSS 24.0, with an initial α-level of 0.05 set for all tests. When ANOVAs indicated significant results, I used Bonferroni’s method to make multiple post-hoc comparisons. Normality was visually assessed using q- q plots; FSRT, ROI, and the number of neighbors were approximately normally distributed.

RESULTS

Focal observations

I conducted 1806 5-minute focal observations during which female Diana monkeys foraged on a single food type. Diana monkeys foraged on invertebrates during

67.1% of focals, on ripe fruit during 23.4% of focals, on mature leaves during 3.3% of focals, and on other material such as young leaves, flowers, mushrooms, and exudates, during 6.2% of focals (Table 3.1). Twelve fruit species eaten during at least ten focals were also included on botanical transects; observations of these species accounted for

84.5% of focal observations (Table 3.2).

Fruit availability and foraging behavior

Fruit availability was lowest during the long wet season and short dry season, between approximately April and August (Figure 3.1) [Anderson et al., 2005]. Table 3.3 provides mean FSRT, ROI, and number of neighbors for each food type (fruit, invertebrate, leaves) during the four seasons.

There were significant differences between seasons in mean fruit site residence time (one-way ANOVA: F3, 515=5.13, p=0.001), the mean rate of intake at fruit sites (one- way ANOVA: F3, 523=15.822, p<0.001), and the mean number of neighbors at fruit sites

(one-way ANOVA: F3, 490=4.598, p=0.003). Food site residence times were significantly longer during the long wet season than any other season (short dry: p<0.001; short wet: p<0.001; long dry: p<0.001). The rate of ingestion was significantly higher during the short dry season than any other season (short wet: p=0.002; long dry: p=0.04; long wet: p=0.02). There were significantly more neighbors during the short dry season than the short wet season (p=0.01).

There were significant seasonal differences in mean FSRT at invertebrate sites

(one-way ANOVA: F3, 1200= 26.406, p<0.001), the mean ROI at invertebrate sites (one- way ANOVA: F3, 1198=39.110, p<0.001), and the mean number of neighbors at invertebrate sites (one-way ANOVA: F3, 1143=27.525, p<0.001). Site residence times were significantly longer at invertebrate sites during the long wet season than during any other season (short dry: p<0.001; short wet: p<0.001; long dry: p<0.001), and were significantly longer during the short dry season than during the short wet season

(p<0.001). Rates of ingestion at invertebrate sites were significantly higher during the short wet season than any other season (long dry: p<0.001; long wet: p<0.001; short dry: p=0.02), and significantly higher during the short dry season than during the long dry season (p<0.001) or long wet season (p=0.001). There were significantly more neighbors while focal individuals were foraging at invertebrate sites during the long dry season than during any other season (long wet: p<0.001; short dry: p<0.001; short wet: p<0.001).

There were significant differences between seasons in FSRT at leaf sites (one- way ANOVA: F3, 79= 3.150, p=0.03), but not in the ROI (F3, 79=2.014, p=0.12) or the number of neighbors (F3, 74=0.224, p=0.88). Food site residence times were significantly

98 longer at leaf sites during the long wet season than any other season (short dry: p<0.001; short wet: p<0.001; long dry: p<0.001), and during the short dry season they were significantly longer than during the short wet season (p<0.001).

Food type, fruit preference, and foraging behavior

Invertebrate sites had the longest residence time (108.4 seconds), while ripe fruit sites had the shortest residence times (86.7 seconds) (Table 3.1, Figure 3.2). A two-tailed univariate ANOVA indicated significant differences in food site residence times between food types (F=12.11, df=3, p<0.01); post-hoc analyses indicated a significant difference between invertebrate and ripe fruit site residence time (p<0.01, 95% confidence interval:

[-31.22, -12.48]), but no other significant differences. There were significant differences in food site residence times for the twelve important fruit species (F= 3.64, df= 11, p<

0.01) (Table 3.2, Figure 3.3). Uapaca esculenta had the longest food site residence time, and post-hoc analysis revealed significant differences (p< 0.05) between Uapaca esculenta and eight other fruit species, indicated by asterisks in Figure 3.3. However, there was no correlation between preference and food site residence time in these species

(R= -0.03, p= 0.10). There was no significant relationship between site residence time and the rate of ingestion for the four main food types (Table 3.1, R= -0.47, p= 0.54,

Figure 3.4) or the twelve fruit species I assessed (Table 2, R= -0.03, p=0.94, Figure 3.5).

The number of individuals within 5 meters of a focal individual differed significantly depending on the type of food being consumed (F=37.39, df=3, p<0.01)

(Table 3.1, Figure 3.6). Post-hoc analyses revealed that individuals foraging on ripe fruit had significantly more individuals within 5 meters (1.6) than individuals foraging on

99 invertebrates (0.9 individuals, p<0.01, 95% CI [0.05, 0.08]), mature leaves (1.1 individuals, p=0.01, 95% CI [0.09, 0.88]), and other foods (0.8 individuals, p<0.01, 95%

CI [0.44, 1.06]). There were also significant differences in the number of neighbors depending on which of the twelve fruit species was being eaten (Table 3.2, figure 3.7;

F=1.899, df=11, p=0.04). While post-hoc analyses did not detect significant differences in the number of individuals in proximity to the focal animal between any of these twelve fruit species, this may be because the corrected alpha-level was so low (α=0.0006) (Table

3.2, Figure 3.7). This lack of statistical significance, then, may mask meaningful differences in foraging behavior at these different tree species. For example, individuals feeding on Sacoglottis gabonensis fruit – typically consumed in the large canopy or on the ground – had fewer than one neighbor. Individuals feeding on Chrysophylum taiensis or Diospyros sanza-minika fruit – both smaller trees – had nearly two neighbors in close proximity. There was no significant correlation between preference and the number of individuals within 5 m of the focal individual (R=0.532, p=0.08).

Social behavior and food type

If social behavior was observed during a five-minute focal, I considered that behavior to occur in the context of foraging on a given food item. Social behavior occurred very rarely: there were no social interactions during 89.4% of focals. Nursing was observed during 4.5% of focals, affiliative behavior (playing and grooming) during

4.5% of focals, and aggression during 1.6% (Figure 3.8). Nursing was considered separately from other affiliative behavior because adult females only interacted with infants while nursing, while other affiliative behaviors involved potential competitors for

100 food sites. Using chi-square, I assessed the likelihood that the frequencies of nursing, agonism, and affiliation during observations in which the focal individual foraged on ripe fruit, invertebrate, mature leaf, and other foods was random. There was a significant association between behavior and food type (Figure 3.9, Pearson’s Chi-Square=31.9, df=6, p<0.01). These associations were loosely corroborated by the fact that the monthly rate of aggression exhibited by Diana 1 was significantly negatively correlated with invertebrate consumption (R= -0.258, p=0.004) and significantly positively correlated with monthly fruit consumption (R= 0.251, p=0.005). However, monthly rates of aggression for Diana 2 were significantly negatively correlated with fruit consumption

(R= -0.448, p<0.001) and fruit availability (R= -0.282, p<0.001).

DISCUSSION

There was no clear relationship between relative value of food categories (fruit, invertebrates, leaves, and other material) or species’ preference, and the amount of time

Diana monkeys spent at a given food site. However, food site residence times for all food categories were longest during the long wet season (April-June) and short dry season

(July-August) when fruit availability was lowest [Table 3.3, Figure 3.1, Anderson et al.,

2005]. It may be worthwhile for females to risk contest competition by staying at food sites longer when fruit is scarce because they gain more foraging time. There is mixed evidence supporting this hypothesis from Kenyan populations of Cercopithecus mitis

[Pazol and Cords, 2005; Foerster et al., 2011]. Low-ranking females experience metabolic stress (indicated by elevated fecal glucocorticoid concentrations) during periods of low fruit availability, while higher ranked-females do not [Foerster et al.,

101

2011]. This suggests that individuals experience differential foraging success during periods of low fruit availability, and that rank helps mediate this. However, while food site residence times for female C. mitis are unknown, there is little evidence suggesting that contest competition is the mechanism differentiating females’ foraging success. In fact, rates of agonism remained low across the entire year, regardless of ecological variability [Pazol and Cords, 2005]. Instead, lower-ranking females compensated for low food availability by spending more time feeding and less time resting [Pazol and Cords,

2005]. Furthermore, all females foraged with fewer individuals in close proximity during periods of low fruit availability [Pazol and Cords, 2005]. I was unable to detect dominance rank in my study groups, so it is unclear what role dominance plays in foraging efficiency and food site residence time for female Diana monkeys. However, like blue monkeys, Diana monkeys exhibit very little agonism. Diana monkeys also had more individuals within 5m while foraging for ripe fruit than while foraging for invertebrates. These data suggest that the risk of having a food site usurped does not seem salient for Diana monkeys; longer site residence times when fruit availability is lower is not due to the tradeoff of risk of aggression and increased foraging time.

Differences in search, handling, and processing time provide an alternative explanation for differences in food site residence time between food categories and different fruit species. For example, invertebrate sites may have longer site residence times than fruit sites because of the ways that Diana monkeys find and consume invertebrates. While some invertebrate foraging can be quite active as Diana monkeys climb between different levels of the canopy and opportunistically eat bugs that they

102 catch, some foraging is also deliberate and stationary, as when monkeys sit in the same place and systematically unroll dead leaves. Furthermore, the way that food sites were defined impacts residence times. If an individual found and ate an invertebrate and then sat in the same spot for several minutes before traveling, site residence time would be lengthy even if they did not eat anything else before moving. Anecdotally, this seemed more common at invertebrate sites than at fruit sites.

Although differences in foraging behavior between seasons may suggest a more competitive environment, differences in the numbers of neighbors near the focal animal, rates of ingestion, and site residence time may more accurately reflect food density and handling. For example, Diana monkeys tend to capture invertebrates opportunistically while remaining in the same location before, during, and after consumption as when they systematically unfold dead leaves within arms’ reach and only occasionally catch prey.

Invertebrate sites are not necessarily targeted as such; opportunistic capture of invertebrates while monkeys are otherwise engaged in resting or grooming is also relatively common, and the individual can often capture and eat an invertebrate without changing her position. These largely immobile foraging strategies account for the relatively long residence time characterizing invertebrate food sites. On the other hand, residence times at ripe fruit sites were significantly shorter because focal animals tended to more mobile while foraging for fruit, rapidly depleting fruit sites and moving to new sites within the same tree [McGraw 1996, 1998]. Diana monkey fruit consumption fell into three main categories. (1) small to medium sized fruits, ubiquitously distributed throughout the canopy, with a relatively quick rate of intake and relatively quick food site

103 residence times (e.g., Oldfieldia africanum, Dacryodes klaineana, Diospyros soubreana).

(2) Large fruits with a fairly long handling time, fairly low rate of intake, and fairly long site residence times, often consumed off the ground (e.g., Uapaca esculenta, Sacoglottis gabonensis). (3) Small fruits distributed in clumps ubiquitously throughout the canopy, with a high rate of intake and long site residence time (e.g., Canthium tecbe).

Differences in site residence time, ingestion, and neighbors, therefore, cannot be used to infer competitive pressure Diana monkeys experience while foraging on different food items. While relative value of food items and food availability may play a role,

Diana monkeys’ food site residence time seems to be a function of food handing time and distribution, rather than a reflection of foods’ values. This also seems to be the case for arboreal, forest-dwelling gray-cheeked mangabeys (Lophocebus albigena) who had much longer residence times at bark sites (mean = 106 s) than at invertebrate (56 s) or fruit (62 s) sites [Chancellor and Isbell, 2009]. Foraging at bark food sites was associated with high rates of aggression (9.6% of food sites, compared to 0.3% of food sites), which suggests that for these mangabeys, site residence time may be a strong predictor of competition and the risk of usurpation of food sites [Chancellor and Isbell, 2009].

However, because bark required significant processing before it can be eaten, handling time also plays a significant role in bark sites’ lengthy residence time [Chancellor and

Isbell, 2009].

This distinction is important because most studies of the role food site residence time plays in structuring primate groups’ competitive relationships have focused on terrestrial taxa in open habitats – very different environments from the dense tropical

104 rainforests of Diana monkeys. Research on these taxa emphasizes the relative usurpability of a particular site is important in competition over those resources, but has also shown that resource competition is influenced by food size, food depletion time or handling rates [Papio cynocephalus: Post et al., 1980; Macaca mulatta: Mathy and Isbell,

2001; Chlorocebus aethiops, Erythrocebus patas: Isbell et al., 1998; Pruetz and Isbell,

2000; Lemur catta: Gould and Gemmill, 2008]. Resources eliciting competition tended to be high-value resources such as ripe fruit, and higher-ranked females accrued benefits such as longer bouts of uninterrupted feeding on these resources. In these taxa food site residence time reflected both resource value and the likelihood of competition. In their comparatively rich environment, food sites may be abundant enough that contesting them is unnecessary for Diana monkeys.

Janson [1990] distinguished capuchin monkey foraging strategies based on target food quality: short searches, during which an animal depletes a particular resource so quickly that it cannot be usurped by more dominant individuals, and long searches, during which food sites are vulnerable to usurpation because they cannot be rapidly depleted. Diana monkey foraging is primarily “long search” by Janson’s definition: food site residence times are quite long compared to other monkeys for whom site residence time is known (e.g., gray-cheeked mangabey mean site residence time: 66 s; vervet monkeys: 25 s; patas monkeys: 15 s) [Chancellor and Isbell, 2009]. This is surprising because Diana monkey foraging strategies, and their socioecological consequences, do not match those predicted by Janson for long search foragers [1990]. Even while individuals move between food sites, they often continue to exploit the same resource

105

(i.e., they change position within a tree, but continue to forage on the same fruit species).

This would suggest that the majority of Diana monkey food sites, including high-value resources expected to elicit contest competition, should be vulnerable to usurpation.

However, Diana monkeys’ observed behavior does not match these predictions.

Classification of Diana monkeys as “long searchers” may be a function of the taxa studied to date rather than a reflection of Diana monkeys’ foraging strategies, and as the foraging strategies of more species are examined, Diana monkeys’ food site residence times may fall towards the short search end of the distribution.

Diana monkeys’ food site residence times do not seem to reflect relative resource preference and value, nor do they seem to predict the likelihood of competitive interactions at a given food site. While there were significant differences between food site residence times while Diana monkeys foraged on different food categories and fruit species, these differences neither reflected presumed value nor correlated with species preference. While there was no significant relationship between the rate of consumption and food site residence time, there was a general trend towards longer residence times for foods with lower rates of consumption and vice versa. Individuals had significantly more individuals within 5 meters while they were foraging on ripe fruit than any other food type, likely because individuals are closer together when feeding on resources with clumped distribution. Although aggression was strongly associated with ripe fruit sites, it was quite rare (2.1% of focals). The fact that Diana monkeys had fewer social interactions while foraging on ripe fruit than on any other food type suggests that individuals are relatively tolerant while foraging. However, while Diana monkeys do not

106 seem to be contesting usurpable resources, there may still be subtle differences in females’ access to resources mediated by length of time spent at food sites and rates of ingestion, particularly during periods when fruit is less readily available.

107

TABLES

Proportion Mean food site Mean rate Mean number of residence time of ingestion of individuals Food type observations (seconds) per minute within 5 m Invertebrates 67.1% 108.4 0.8 0.9 N=1202 Ripe fruit 23.4% 86.7 1.8 1.6 N=427 Mature leaves 3.3% 97.7 1.6 1.1 N=61 Other material 6.2% 103.0 2.2 0.8 N=116 14. Table 3.1. Food site residence time, rate of intake, and the number of individuals within 5m of the focal individual while foraging on different food types (N=1806 focals).

Proportion of Food site Rate of Number of Ripe fruit species Preference ripe fruit residence time ingestion/ individuals observations (seconds) min within 5 m Canthium tecbe -0.84 2.8% 60.9 8.6 1.5 N=12 Chrysophylum taiensis 0.78 3.0% 74.3 1.7 1.9 N=13 Dacryodes klaineana 0.38 4.7% 78.8 2.5 1.2 N=20 Dialium aubrevillei 0.89 6.1% 111.3 3.7 2.0 N=26 Diospyros sanza-minika -0.34 4.2% 94.4 1.0 0.6 N=18 Diospyros soubreana 0.14 15.2% 73.0 1.9 1.5 N=65 Oldfieldia africanum 0.57 8.2% 58.5 2.8 2.0 N=35 Parinari excelsa 0.71 4.2% 73.0 1.0 1.3 N=18 Pycnanthus angolensis 0.79 2.3% 56.8 1.3 1.9 N=10 Sacoglottis gabonensis 0.47 27.9% 91.2 0.9 1.6 N=119 Scytopetalum tieghemmi -0.29 3.3% 100.8 1.9 1.5 N=14 Uapaca esculenta 0.06 2.6% 151.0 0.9 1.2 N=11 15. Table 3.2. Preference, dietary proportion, mean site residence time, mean rate of intake, and mean number of individuals within 5m while foraging on twelve species of ripe fruit.

108

Food item Variable Long Wet Short Dry Short Wet Long Dry One-Way ANOVA Season Season Season Season (F-value, p-value) (April-June) (July-August) (September- (December- November) March) Fruit FSRT* 152.18 (± 99.42) 88.18 (±58.43) 83.65 (±61.12) 82.13 (± 54.54) F3, 515=5.13, p=0.001 ROI* 1.35 (± 0.93) 2.36 (± 2.94) 1.47 (± 1.27) 1.81 (±1.35) F3,523=15.82, p<0.001 Neighbors* 1.12 (± 1.35) 1.68 (± 1.45) 1.15 (± 1.20) 1.56 (± 1.30) F3, 490=4.60, p=0.003

Invertebrates FSRT* 141.68 (± 73.64) 110.53 (± 65.80) 83.58 (± 42.26) 108.49 (±62.90) F3,1200=26.41, p<0.001 ROI* 0.71 (± 0.39) 0.90 (± 0.46) 1.01 (± 0.51) 0.68 (± 0.40) F3,1198=39.11, p<0.001 Neighbors* 0.74 (± 0.92) 0.70 (± 0.92) 0.56 (± 0.79) 1.15 (± 1.05) F3,1143=57.53, p<0.001

Leaves 109 FSRT* 128.44 (± 89.90) 104.35 (± 65.96) 69.79 (± 24.46) 77.79 (± 21.87) F3,79=3.15, p=0.03 ROI* 1.44 (± 0.67) 1.89 (± 0.79) 1.75 (± 0.88) 1.39 (± 0.47) F =2.01, p=0.12 3, 79 Neighbors 0.69 (± 0.95) 0.94 (± 01.10) 0.79 (± 1.07) 0.78 (± 0.67) F3,74=0.22, p=0.88

16. Table 3.3. Mean food site residence time, rate of ingestion, and number of individuals within 5m of the focal individual (± standard deviation) during the long wet season (April-June), short dry season (July-August), short wet season (September-November), and the long dry season (December-March). Variables with significant seasonal differences are indicated with an asterisk (*).

109

FIGURES

60% 0.35

50% 0.30

0.25 40% 0.20 30% 0.15

20% Food Availability Food

Proportion of Fruit of Proportion 0.10

10% 0.05

0% 0.00

Group 1 Group 2 Fruit Availability

9. Figure 3.1. Monthly contribution of fruit to the diet of two Diana monkey groups, and mean monthly fruit availability, between July 2013-April 2014, and October 2014- August 2015..

110

Leaves

10. Figure 3.2. Mean food site residence times of invertebrates, ripe fruit, leaves, and other material. Residence time at invertebrate sites was significantly longer than at fruit sites (p<0.01, 95% confidence interval: [-31.22, -12.48]).

111

160

140

120

100

Mean Food Site Residence Time (seconds) Time Site Residence Mean Food 0

Fruit Species

11. Figure 3.3. Mean food site residence time of twelve important fruit species consumed by Diana monkeys. Site esidence time while foraging Uapaca esculenta was significantly longer than while foraging on the eight species under the bracket (p<0.05). Preferred fruit species are indicated by a solid bar while non-preferred fruits are indicated by a dashed bar.

112

2.5

2.0 Other material

1.5 Ripe fruit Leaves

1.0 (per minute)(per

Mean rate of of Mean intake rate 0.5 Invertebrates

0.0 80 85 90 95 100 105 110 Food Site Residence Time

12. Figure 3.4. Mean rate of intake (per minute) vs. mean food site residence time (seconds) for the four main food types.

10 9 8 7 6

3. 5 4 3 2 1 0 0 20 40 60 80 100 120 140 160 Mean Food Site Residence Time

13. Figure 3.5. Mean rate of consumption (per minute) vs. mean food site residence time (seconds) for twelve important fruit species.

113

1.8 1.6 1.4 1.2 1

meters 0.8 0.6 0.4 0.2

Mean Mean number individuals of within 5 0 Ripe fruit Invertebrates MatureLeaves leaves Other material Food Type

14. Figure 3.6. The mean number of individuals within 5 meters of the focal individual while she foraged onripe fruit, invertebrates, leaves, and other material. Individuals foraging on ripe fruit had significantly more individuals within 5 meters than individuals foraging on invertebrates ( p<0.01, 95% CI [0.05, 0.08]), mature leaves (p=0.01, 95% CI [0.09, 0.88]), and other foods (p<0.01, 95% CI [0.44, 1.06]).

114

2.5

2.0

1.5

1.0

0.5

0.0 Mean number of individuals within 5 m 5 within individuals of Mean number

Fruit Species

15. Figure 3.7. The mean number of individuals within 5m of the focal animal while she foraged on twelve important fruit species.

115

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Aggression Affiliation Nursing None

16. Figure 3.8. The proportion of 5-minute focals during which social behaviors, including aggression, affiliation, and nursing, were observed

116

0% Ripe fruit Invertebrates Mature leaves Other Affiliative Nursing Agonistic

17. Figure 3.9. The proportion of focal observations, per food type, in which the focal animal engaged in social behavior.

117

b. 18. Figure 3.10. An adult female Diana monkey carrying Sacoglottis gabonensis fruit in her mouth and hand (a) moves to an isolated spot in the understory to eat the fruit she collected (b). 118

REFERENCES

Altmann JA. 1974. Observational study of behavior: sampling methods. Behaviour 49: 227-267.

Anderson DP, Nordheim EV, Moermond TC, Gone Bi ZB, Boesch C. 2005. Factors influencing tree phenology in Taï National Park, Côte d’Ivoire. Biotropica 37: 631- 640.

Buzzard PJ. 2004. Interspecific competition among Cercopithecus campbelli, C. petaurista, and C. diana at Taï Forest, Côte d’Ivoire. PhD Dissertation: Columbia University.

Buzzard PJ. 2006. Cheek pouch use in relation to interspecific competition and predator risk for three guenon monkeys (Cercopithecus spp.). Primates 47: 336-341.

Buzzard PJ, Eckardt W. 2007. Social systems of the Taï guenons (Cercopithecus spp.). In, Zuberbühler K, McGraw S, Noë R, eds. Monkeys of the Taï Forest: An African Primate Community. Cambridge: Cambridge University Press.

Chancellor RL, Isbell LA. 2009. Food site residence time and female competitive relationships in wild gray-cheeked mangabeys (Lophocebus albigena). Behavioral Ecology and Sociobiology 67: 1447-1458.

Cords M. 2000. Agonistic and affiliative relationships in a blue monkey group. In, Whitehead PF, Jolly CJ, eds. Old World Monkeys. Cambridge: Cambridge University Press. 453-479.

Cords MA. 2012. The behavior, ecology, and social evolution of cercopithecine monkeys. In, Mitani JC, Call J, Kappeler PM, Palombit RA, Silk JB, eds. The Evolution of Primate Societies. Chicago: University of Chicago Press. 91-112.

Foerster S, Cords M, Monfort SL. 2012. Seasonal energetic stress in a tropical forest primate: proximate causes and evolutionary implications. PLoS ONE 7(11): e50108.

Foerster S, Monfort SL. 2010. Fecal glucocorticoids as indicators of metabolic stress in female Sykes’ monkeys (Cercopithecus mitis albogularis). Hormones and Behavior 58: 685-697.

119

Gemmill A, Gould L. 2008. Microhabitat variation and its effects on dietary composition and intragroup feeding interactions between adult female Lemur catta during the dry season at Beza Mahafaly Special Reserve, Southwestern Madagascar. 29: 1511-1533.

Greuter CC, Robbins AM, Abavandimwe D, Vecellio V, Ndagijimana F, Ortmann S, Stoinski TS, Robbins MM. 2016. Causes, mechanisms, and consequences of contest competition among female mountain gorillas in Rwanda. Behavioral Ecology 27: 766-776.

Isbell LA, Pruetz JD. 1998. Differences between vervets (Cercopithecus aethiops) and patas monkeys (Erythrocebus patas) in agonistic interaction between adult females. International Journal of Primatology 19: 837-855.

Isbell LA, Pruetz JD, Young TP. 1998. Movements of vervets (Cercopithecus aethiops) and patas monkeys (Erythrocebus patas) as estimators of food resource size, density, and distribution. Behavioral Ecology and Sociobiology 42: 123-133.

Isbell LA, Young TP. 2002. Ecological models of female social relationships in primates: similarities, disparities, and some directions for future clarify. Behaviour 139: 177- 202.

Janson CH. 1990. Ecological consequences of individual spatial choice in foraging groups of brown capuchin monkeys, Cebus apella. Animal Behavior 40: 922-934.

Lambert JE. 2005. Competition, predation, and the evolutionary significance of the Cercopithecine cheek pouch: the case of Cercopithecus and Lophocebus. American Journal of Physical Anthropology 126: 183-192.

Loehle C, Rittenhouse LR. 1982. An analysis of forage preference indices. Journal of Range Management 35: 316-319.

Marshall AJ, Wrangham RW. 2007. Evolutionary consequences of fallback foods. International Journal of Primatology 28: 1219-1235.

Mathy JW, Isbell LA. 2001. The relative importance of size of food and interfood distance in eliciting aggression in captive Rhesus macaques (Macaca mulatta). Folia Primatologica 72: 268-277.

McGraw WS. 1996. Cercopithecid locomotion, support use, and support availability in the Tai Forest, Ivory Coast. American Journal of Physical Anthropology 100: 507- 522.

120

McGraw WS. 1998. Posture and support use of old world monkeys (Cercopithecidae): the influence of foraging strategies, activity patterns, and the spatial distribution of preferred food items. American Journal of Primatology 46(3): 229-250.

McGraw WS, Plavcan JM, Adachi-Kanazawa. 2002. Adult female Cercopithecus diana employ canine teeth to kill another adult female C. diana. International Journal of Primatology 23:1301-1308.

McGraw WS, Zuberbühler K, Noë R. 2007. Monkeys of the Taï Forest: an African Primate Community. Cambridge: Cambridge University Press. 328 p.

Payne HFP, Lawes MJ, Henzi SP. 2003. Competition and the exchange of grooming among female Samango monkeys (Cercopithecus mitis erythrarchus). Behaviour 140: 453-471.

Pazol K, Cords MA. 2005. Seasonal variation in feeding behavior, competition, and female social relationships in a forest dwelling guenon, the blue monkey (Cercopithecus mitis stuhlmanni) in the Kakamega Forest, Kenya. Behavioral Ecology and Sociobiology 58: 566-577.

Post DG, Hausfater G, McCuskey SA. 1980. Feeding behavior of yellow baboons (Papio cynocephalus): relationship to age, gender, and dominance risk. Folia Primatologica 34: 170-195.

Pruetz JD, Isbell LA. 2000. Correlations of food distribution and patch size with agonistic interactions in female vervets (Chlorocebus aethiops) and patas monkeys (Erythrocebus patas) living in simple habitats. Behavioral Ecology and Sociobiology 49: 38-47.

Refisch J, Koné I. 2005. Impact of commercial hunting on monkey populations in the Taï region, Côte d’Ivoire. Biotropica 37: 136-144.

Sterck EHM, Watts DP, van Schaik CP. 1997. The evolution of female social relationships in nonhuman primates. Behavioral Ecology and Sociobiology 41(5): 291-309.

Strauss RE. 1979. Reliability estimates for Ivlev’s Electivity Index, the forage ratio, and a proposed linear index of food selection. Transactions of the American Fisheries Society 108; 344-352. van Schaik CP. 1989. The ecology of social relationships amongst female primates. In, Standen V, Foley RA, eds. Comparative Socioecology: the Behavioural Ecology of Humans and Other Mammals. Oxford: Blackwell Scientific Publications. 195-218.

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Wrangham RW. 1980. An ecological model of female-bonded primate groups. Behaviour 75: 262–300.

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Chapter 4: Diana monkeys’ fecal glucocorticoid responses to stressful events

INTRODUCTION

Primates live in a complex social and ecological context. Primates must procure, process, and digest enough food to support growth, development, and reproduction

[Chapman et al., 2012]. They must grow, develop, and reproduce [van Schaik and Isler,

2012]. They must avoid being eaten by predators [Fichtel, 2012]. They must coexist, compete, and cooperate with other conspecifics in a potentially complex social system

[Schüilke and Ostner, 2012]. They must cope with challenges from the abiotic environment, and possible anthropogenic effects of disturbance [Cook et al., 2013]. All of these challenges are potential sources of stress which disrupt the body’s homeostatic balance [McEwen and Stellar, 1993; Sapolsky, 2004 Beehner and Bergman, 2017].

In response to stressors – unpredictable, and/or uncontrollable stimuli – the body activates the hypothalamic-pituitary-adrenal axis (HPA axis), stimulating endocrine glands to release a series of hormones readying the body for a “fight or flight” response

[Levine and Ursin, 1991; Nelson, 2012]. The release of glucocorticoids (including cortisol and corticosterone) mobilizes energy in the form of glucose, allowing muscle tissue rapid access to energy at the expense of longer-term functions such as reproduction, growth, and digestion [Sapolsky, 2000]. While the body’s response to activation of the HPA-axis is highly adaptive over the short term, chronically elevated

123 glucocorticoid concentrations can lead to a suite of negative effects including the suppression of reproductive and immune system functions, poor digestion, hypertension, and even neuron death [Sapolsky, 2004]. However, it is important to recognize that glucocorticoids mediate routine metabolic functions; their secretion is also fundamental to the normal maintenance of individuals’ energy balance [Beehner and Berghman,

2017]. Furthermore, stressors are encountered nearly every day; the ability for organisms to respond appropriately enhances survivability. Consequently, the ability for organisms to respond to acute stressors by activating the HPA axis is fundamentally adaptive, allowing individuals to maintain homeostasis and physiological stability even given environmental or psychological challenges [McEwen and Wingfield, 2003; Romero et al., 2009]. In other words, the ability to activate the HPA axis in response to routine environmental challenges such as seasonal shifts in temperature, returning the body to its normal physiological state, enhances individual survival [McEwen and Wingfield, 2003].

The activation of the HPA axis in response to unpredictable events is part of the process of maintaining a normal reactive scope of homeostasis (Figure 4.1) [Romero et al., 2009]. Organisms have measurable stress responses over time, typically with some circadian variation (e.g., glucocorticoid concentrations). The reactive scope model suggests that organisms’ stress response fluctuates annually in response to challenges like seasonal changes in food availability. This fluctuation is defined as predictive homeostasis, or the predictable range of fluctuations in a stress response required to cope with those annual challenges. There are also intermittent fluctuations in response to acute stressors such as predation attempts, agonistic encounters, and so forth. Many of these

124 stress responses fall in the range of reactive homeostasis, in which an elevated stress response returns organisms to their normal homeostatic level of the stress response.

These responses can be considered adaptive: they enhance individual survival in response to acute stressors. However, some stress responses are so extreme that they push organisms out of their reactive homeostasis and into homeostatic overload. It is at this point that a stress response has a detrimental effect on the organism [Sapolsky, 1987;

Romero, 2009].

Evidence collected to date suggests that primates, like many organisms, experience elevations in the concentrations of glucocorticoids in response to acute stressors including aggression and anti-predator defense [Cavigelli, 1999; Pride, 2005;

Engh et al., 2006; Arlet and Isbell, 2009; Wittig et al., 2015]. For example, after an aggressive interaction, wild male chimpanzees experienced increases in urinary cortisol concentrations [Wittig et al., 2015]. Male gray-cheeked mangabeys (Lophocebus albigena) who participated in group defense after an eagle attack had higher cortisol concentrations the day after the eagle attack than they did on other days, and higher cortisol concentrations than males who did not participate in group defense [Arlet and

Isbell, 2009].

There are contexts in which acute stressors such as alarm calls in response to predators do not cause an increase in glucococorticoids. For example, during particular stages of growth and development, diverting resources away from anabolic processes may have significant negative consequences, so glucocorticoid responses to stressors are suppressed during those periods [Wingfield et al., 1998; Dantzer et al., 2016]. For

125 example, during important developmental periods, infant fledglings of some bird species do not respond to their parents’ alarm calls with elevated corticosterone levels because this would divert energy away from growth and development [Wingfield et al., 1998]

Chronically stressed individuals may also have “maxed out” their glucocorticoid response, and they may not respond to acute stressors with increases in fecal glucocorticoid concentrations [Romero et al., 2009]. In addition, females’ reproductive status may complicate interpretations of elevated glucocorticoid concentrations and responses to acute stressors, in part because fetal activation of the HPA axis interferes with the maternal stress response [e.g.,Mastorakos and Ilias, 2003; Engh et al., 2006;

Rodrigues et al., 2015].

Diana monkeys (Cercopithecus diana) in the Taï Forest, Côte d’Ivoire, are preyed upon by eagles (Stephaneaoetus coronatus), leopards (Panthera pardus), and chimpanzees (Pan troglodytes) [Bshary and Noë, 1997; Zuberbühler, 2000; Zuberbühler and Jenny, 2002; McGraw et al., 2006]. Diana monkey groups are territorial, engaging in agonistic encounters with neighboring groups, and even engaging in lethal coalitionary aggression towards stranger females [Hill, 1994; McGraw et al., 2002; Buzzard and

Eckardt, 2007]. Though intergroup encounters are relatively rare, Diana monkey groups have more frequent intergroup encounters than sympatric guenons [Buzzard and Eckardt,

2007]. Given the relative intensity of Diana monkeys’ intergroup encounters compared to closely related taxa, and the risk of predation, this research aims to assess whether female

Diana monkeys respond to acute stressors with elevated glucocorticoid concentrations

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[Bshary and Noë, 1997; Zuberbühler, 2000; Zuberbühler and Jenny, 2002; McGraw et al., 2006].

Fluctuations in glucocorticoid concentrations can be assessed in a number of matrices, including blood, cerebral spinal fluid, saliva, urine, hair, and feces [Behringer and Deschner, 2017]. Diana monkeys’ vulnerable conservation status and arboreal lifestyle make invasive assessment of glucocorticoid concentrations (e.g., darting to extract blood or cerebral spinal fluid) impractical, and collecting saliva, hair, or urine challenging [McGraw, 1998; Oates et al., 2016]. However, fecal samples are relatively easy to collect from wild arboreal primates, enabling a non-invasive, feasible method for assessing fluctuations in fecal metabolites of hormones such as glucocorticoids

[Behringer and Deschner, 2017 Secretion of glucocorticoids is highest in the morning and decreases over the course of the day in some species; this fluctuation may be reflected in fecal glucocorticoid concentrations depending on gut passage time and glucocorticoid metabolism [Felig and Frohman, 2001; Foerster and Monfort, 2010]. Because the excretion and metabolism of hormones can vary dramatically between species, methods to measure hormone concentrations must be validated for the hormone of interest for each study species [Touma and Palme 2005; Behie et al., 2010; Cook, 2012]. This includes a methodological validation, which verifies that the immunoassay used to assess hormone concentrations is precise, sensitive, and accurate, and a physiological/biological validation, which verifies that the hormone of interest is biologically relevant for the research question [Higham, 2017].

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In this study, I provide the first biological and methodological validation of an enzyme immunoassay to assess fecal glucocorticoid concentrations (FGC) in Diana monkeys (Cercopithecus diana), using samples collected from captive Diana monkeys before and after a veterinary exam with sedation to test whether fecal glucocorticoids increase after a stressful experience, and to test whether my assay adequately measures fecal glucocorticoid concentrations. I predict that FGC concentrations will increase after the veterinary exam because anesthesia stimulates the HPA-axis [Toume and Palma,

2005]. I also assess the relationship between the time of day samples were collected (AM or PM) and FGC concentrations. Because studies of FGC concentrations in closely related Cercopithecus mitis populations found elevated values in the morning, I predict that Diana monkeys will also have FGC concentrations that are elevated in the morning

[Foerst and Monfort, 2010]. Lastly, I test the effect of acute stressors on wild Diana monkeys’ FGC concentrations. I predict that Diana monkeys will have significantly elevated FGC concentrations in samples collected after a stressful event compared to samples collected at other periods.

METHODS

Captive Data Collection

Captive data collection focused on three adult male Diana monkeys from the

Tulsa Zoo (n=1) and Jackson Zoo (n=2). While there are significant sex differences in baseline glucocorticoid concentrations, the HPA-axis’s responsiveness to stressors and the metabolites that may be produced by different sexes, using males for this initial validation study still allowed me to verify whether Diana monkeys generally secrete more

128 glucocorticoids in response to stressful situations [Touma and Palme, 2005]. However, because of this, I did not make direct comparisons between FGC concentrations or fluctuations between males and females. Samples were collected from captive males approximately a week before and after a routine veterinary exam. While the gold standard in validation studies is an ACTH challenge, in which animals are injected with known amount of adrenocorticotropic hormone (ACTH) to stimulate glucocorticoid secretion, this invasive procedure is rarely performed on primates and I did not perform one in the process of this study. However, an ACTH challenge performed on captive Sykes’ monkeys (Cercopithecus mitis albogularis) at the Institute of Primate Research in

Nairobi, Kenya verified that an increase in secreted glucocorticoids in the bloodstream lead to a concomitant increase in fecal glucocorticoid metabolites [Foerster and Monfort,

2010]. Given the close phylogenetic relationship between Sykes’ and Diana monkeys, I operate under the assumption that the physiology of the glucocorticoid response is comparable.

In lieu of an ACTH challenge, I collected samples before and after a stressful event to determine whether the stressful event induced elevations in fecal glucocorticoids.

Veterinary exams including capture and housing changes have been shown to cause stress in captive primates; anesthesia also stimulates the adrenocortical system to release corticoids [Wasser et al., 2000; Touma and Palme, 2005; Rodrigues et al., 2015; Wark et al., 2016]. Therefore, veterinary exams served as an acute stressor. Participating individuals were given food marked with different colored glitter that could then be used to individually identify fecal samples even if nobody observed their deposition [Fuller et

129 al., 2011]. Samples were collected every morning for approximately one week before and after the veterinary exam and immediately frozen.

The adult male at the Tulsa Zoo, Kumasi, was 6 years and 5 months old at the time of his veterinary exam and housed with another adult male (Figure 4.2). His exam was conducted in anticipation of a transfer to the Ostrava Zoo in the Czech Republic, and included immobilization for a TB test, and routine physical examination [Patrick

Murphy, Tulsa Zoo veterinarian, pers. comm]. Data collection occurred between

September 10-September 20, 2015, with the exam on September 15. Samples were also collected from Stormy, an adult female at the Tulsa Zoo, but it was discovered that she was pregnant shortly after the veterinary exam. Because pregnancy can have a confounding effect on glucocorticoid responses [Goland et al., 1994; Guesquire et al.,

2008], her samples were removed from this study.

Adult males at the Jackson Zoo were two half-brothers, Hoy, (12 years, 7 months) and Elvis (9 years, 9 months). During data collection, they were separately housed, rotating between two exhibits and sleeping in separate enclosures with visual contact. In addition, they had visual contact with Colobus guereza, Cercopithecus ascanius schmidtii, and Cercopithecus diana in adjacent enclosures. Data collection occurred between January 21, 2016 and January 30, 2016; the veterinary exam was on January 26 and included sedation [Donna Todd, Jackson Zoo veterinarian, pers. comm.]. Data collection at these zoos was approved by the Ohio State IACUC, research bodies at the

Tulsa and Jackson Zoos, and the Diana Monkey Species Survival Plan.

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Wild Data Collection

Data were collected on wild Diana monkey (Cercopithecus diana) females living in two groups in the primary study grid of the Taï Monkey Project in Taï National Park, located approximately 20 km from the nearest village and 25 km from the border with

Liberia. These two groups have been under regular observation since 1991. Individuals are habituated and adult females are individually identified based on features of the tail, nipples, and pelage. During the study period, which spanned from July 2013-Auust 2015, groups consisted of one-male units with 7-13 adult females, 2-5 subadults, and associated juveniles and infants. Diana 2 experienced a male transfer with an associated infanticide and 6 sub-adult females matured to adult females during this period, while one female disappeared from Diana 1.

Fecal samples were opportunistically collected from adult females, labeled by individual, time and date of collection, and stored in a dark bag for no more than 8 hours.

Upon return to the research station, samples were dried in a Coleman stovetop oven for two hours at approximately 100° C and then stored in a dry box with silica gel. Upon return to the United States, samples were stored in a freezer at approximately -20° C until analysis. This method (drying, followed by storage at room temperature and/or freezing) has been shown to successfully stabilize FGC concentrations in bears and elephants

[Hunt and Wasser, 2003], Sifaka lemurs (Propithecus verreauxi) [Brockman et al., 1995;

Brockman and Whitten, 1996], and blue and Sykes monkeys for up to two years [Foerster et al., 2010; Foerster et al., 2011]. I collected 355 fecal samples from 21 adult females between July 2013-March 2014 and May 2015-August 2015.

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I took notes on all occurences of interactions with potential predators and intergroup encounters during regular data collection. I classified events as potential stressors if Diana monkeys produced loud alarm calls and descended from the canopy in response to an eagle or its calls, became quiet and cryptic and ascended into the canopy in the presence of chimpanzees or after hearing chimpanzee vocalizations and buttress drumming, or engaged in a territorial calling bout followed by movement towards or away from a neighboring group or engaging in active aggression between groups [Hill,

1994; Zuberbühler, 2000; McGraw et al., 2002; Shultz et al, 2003]. Based on data from the captive validation study, samples collected after a potential stressor – the day of, or 1-

2 days following – were considered “potentially stressed” samples while samples collected before or at least 3 days after a potential stressor were considered “not stressed.”

Enzyme Immunoassay Protocol

I analyzed glucocorticoid concentrations of fecal samples at the Reproductive

Endocrinology lab of the Smithsonian Conservation Biology Institute in Front Royal, VA with enzyme immunassays (EIAs) following standard lab protocols [Brown et al., 2008].

Immunoassays take advantage of the specificity of immunoreaction and antibodies to detect hormone concentrations in a particular sample by measuring the ratio of labeled antigen (a known amount of tracer steroid) and unlabeled antigen (an unknown hormone concentration in your sample) binding to a limited amount of antibody. Antibodies are produced by immunizing an animal against the hormone of interest (in the case of a specific antibody) or by immunizing a different species against the immunoglobin of the

132 species which produced a primary antibody [Brown et al. 2003]. For example, goat anti- mouse antibodies would be produced by immunizing goats with mouse immunoglobin produced when immunizing mice against a particular hormone.

Extraction Methods

Samples were lyophilized for 120 hours to remove any remaining liquid from samples and obtain dry samples, yielding data on the proportion of hormones per gram dry weight [Wasser et al. 1988]. After lyophilization, samples were crushed and sieved to remove any extraneous material (leaves, seeds, etc.) and homogenize the remaining sample. Hormones were extracted according to the reproductive endocrinology lab’s fecal extraction protocol [Brown et al. 2008]:

I weighed out 0.2 g (+/-0.01) of dry powdered feces from each sample into labeled 16x125 mm glass tubes. To monitor extraction efficiency, I added 100 μL of radiolabeled corticosterone tracer to each tube. I next added 5.0 mL of 90% EtOH/10% deionized water to each tube, which was capped and vortexed using a multi-tube vortex for 30 minutes at 55 RPM. Samples were centrifuged at 2000 RPM for 20 minutes. The extract was poured off into a second set of labeled tubes, and 5.0 mL 90% EtOH/10% deionized water were added to the tubes with fecal pellets. These were individually vortexed for 30 seconds, then centrifuged at 2000 RPM for 15 minutes. The extract was poured off into the tubes containing the first extract and the fecal pellets were discarded.

The tubes with extract were dried down in a fume hood overnight. One mL of MeOH was added to the tubes with now-dried extract. Tubes were sonicated until the sample reconstituted, and then dried down again. I next added 1 mL of EIA dilution buffer to

133 each tube and sonicated until the samples were completely reconstituted. This extract was frozen until assays were run. Following lab protocols, extracts were never thawed more than once.

To measure extraction efficiency, I pipetted 15 μL from each sample into scintillation vials with 3 mL scintillation fluid. They were vortexed, then sat for 1 hour to disperse any air bubbles. This was run through a gamma counter to determine the proportion of radiolabeled steroid tracer extracted. I re-extracted any samples which had

<70% extraction efficiency.

Sample Dilution

Fecal extracts from 20 randomly selected samples were pooled and serially diluted in assay buffer. 50% binding was reached between a 1:8 and 1:16 dilution.

Corticosterone samples were diluted 1:8 in assay buffer. I ran all fecal samples in duplicate, re-assayed samples with binding CVs greater than 10%, and re-diluted and re- assayed samples with binding outside the range of 20-80%.

Assay Protocols

I ran corticosterone assays on goat-anti rabbit IgG plates with all samples in duplicate. Plates were loaded with 50 μL of sample and the following standards and controls, also in duplicate: blank wells with assay buffer, nine standard values from 1000 pg corticosterone/well to 3.9 pg corticosterone/well, and two controls of known concentration. I added 25 μL of Corticosterone Horseradish Peroxidase diluted to

1:45,000 to each well, and 25 μL of Corticosterone Antibody diluted to 1:60,000 to each well, except the two blank wells that contained only assay buffer. After plates incubated

134 on a shaker for 1 hour, I washed them with A2 Wash solution and added 100 μL of Moss

TetraMethylBenzidine (TMB) to each well. After plates incubated at room temperature for 30 minutes, I added 50 μL of 1 N HCL to all wells to stop the immunoassay reactions.

I read plates at 450 nm on a spectrophotometer, and used standards’ readings to create a standard curve to derive sample concentrations.

Statistical Analysis

Peak and baseline concentrations were determined for each individual using an iterative process in which I calculated the mean for each individual, removed all samples greater than the mean plus two standard deviations, and continued this process, recalculating until there were no samples greater than two standard deviations greater than the mean. This mean was considered the baseline concentration; elevated samples were those greater than two standard deviations from the baseline, and peaks were the highest concentration among elevated samples [Brown et al., 1999].

I used Q-Q plots to look for departure from normality. FGC fluctuations were distributed approximately normally. I used linear mixed models (LMM) to compare cortisol concentrations before and after a stressful event. These models are useful because they allow repeated tests on the same individual, using individual identity as the random effect. I ran two LMMs: one that incorporated all samples and identified them as potentially stressed (e.g., collected after a stressful event on the same day, up to two days following) or not, and one that controlled for potential seasonal biases in FGC concentrations by restricting the analysis to potentially stressed samples and samples collected from the same individual 1-2 days before or 3 days after that potential stressor. I

135 report LMM results only when a likelihood ratio test demonstrated that the addition of fixed effects was an improvement over a model based only on the intercept and random effects [Dunteman and Ho, 2006].

RESULTS

Captive samples

Captive males (N=3) had elevated corticosterone concentrations the day immediately following their veterinary exam (Figure 4.3a, b, c). Two males reached their peak FGC concentrations the day immediately after the exam; one male reached his peak

FGC concentration two days after the exam. All three males had returned to baseline concentrations by the third day after the exam. For future analyses, I assume that Diana monkeys will reach peak FGCs by the day after the stressful event, and FGC concentrations return to baseline by the third day after the event. FGC concentrations from samples collected the day of and up to two days after the veterinary exam were significantly higher than FGCs from samples collected throughout the rest of the data collection period (Figure 4.4) (LMM: F27.995, 1=27.995, P<0.001, N=30).

Wild samples

I recorded 52 stressful events during this study period that occurred the day before or the same day as a fecal sample were collected, including eight encounters with chimpanzees, four responses to eagles, and 45 intergroup encounters. I assessed differences between FGCs collected the day of (but after) and the day after one of these stressful events, and FGCs collected on a day in which no stressful events occurred. Fecal glucocorticoid concentrations in “potentially stressed” samples did not differ significantly

136 from FGC concentrations in samples collected on days with no potential stressors (Figure

4.5, LMM: F348, 1=1.494, p=0.22). Samples collected following chimpanzee encounters

(N=26) had a mean FGC concentration of 0.073 µg above baseline (SD: 0.187 µg), samples collected following eagle encounters (N=16) had a mean FGC concentration of

0.056 µg above baseline (SD: 0.100 µg), and samples collected following inter-group encounters (N=116) had a mean FGC concentration of 0.047 µg above baseline (SD:

0.149 µg). Non-stressed samples (N=) had a mean FGC concentration of 0.030 µg above baseline (SD: 0.113 µg).

FGCs from individual samples

I also assessed the impact of a subset of events for which I was able to collect samples from the same individual when they were not stressed, and when they were potentially stressed. This allowed me to examine 36 discrete events (3 in captivity, 33 in the wild) on 18 individuals (3 captive males, 15 wild females) using “potentially stressed” (N=54) and “not stressed” (N=56) fecal samples collected from the same individual 1-2 days before or 3 days after the potential stressor. I found a significant difference in corticosterone concentrations from “potentially stressed” samples and “not stressed” samples (Figure 4.6) (LMM: F1,91.239=13.263, p<0.001). Housing condition had no significant effect on corticosterone concentrations between zoo and wild-housed individuals (EMM: P=0.695).

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DISCUSSION

Fecal glucocorticoids and acute stress

I found that fecal glucocorticoid concentrations in captive males became elevated above baseline within the day of a stressful experience, and returned to approximately baseline levels within 2-4 days of the veterinary exam. When I compared all “non- stressed” samples (i.e., not just samples collected immediately before or several days after a stressful experience), to “stressed” samples, there was no significant difference in heir fecal glucocorticoid concentrations (Figure 4.6). This may be because fluctuations in

FGCs are not only due to stressful events, but can also reflect reproductive status and ecological variables. By comparing stressed and non-stressed samples collected from the same individuals in a short timeframe, I controlled for potentially confounding effects of reproductive status and ecology. In this case I found that FGC concentrations in wild

Diana monkeys were significantly higher the day of or immediately after a stressful experience (intergroup encounter, predator presence), than the day immediately before or two days after a stressful experience (Figure 4.7). This indicates that the secretion and metabolism of glucocorticoids increases in response to acute stressors, including the presence of potential predators and neighboring groups. This finding corroborates research assessing the impact of predation and social stressors on glucocorticoid concentrations in primates, such as includes research showing that male mangabeys’ participation in group defense elevates FGC concentrations compared to males who did not participate [Arlet and Isbell, 2009]; red colobus monkeys at Kanyawara, Uganda had elevated FGC concentrations following chimpanzee predation events [Wasserman et al.,

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2013]; and chimpanzees in the Taï Forest who were participants in aggressive interactions had elevated urinary GC concentrations following those encounters [Wittig et al., 2015].

That primates demonstrate an increase in GC concentrations in response to acute stressors is unsurprising. Elevated GC concentrations enable a “fight or flight” response to an immediate potential threat [Nelson, 2011]. This includes behavioral responses such as improved cognition and vigilance, in addition to a numbing of pain, and inhibited reproductive and digestive processes [Charmandari et al., 2005]. There is a consequent redirection of energy, including glucose and oxygen, to stressed body sites (muscles, etc.) to increase cardiovascular tone, respiratory rates, and metabolic function [Charmandari et al., 2005]. In these cases, elevated glucocorticoids represent reactive homeostasis, enabling a return to predictive homeostasis after an acute stressor.

Guenon endocrinology

Aronsen and colleages [2015] compared urinary cortisol concentrations of redtail monkeys (Cercopithecus ascanius) in a highly disturbed forest and a relatively pristine forest in Kibale National Park, Uganda. They found that, contrary to expectations, individuals at the relatively pristine site had significantly higher urinary cortisol concentrations than individuals at the disturbed site. They attribute this primarily to differences in predation pressure, since chimpanzees and crowned hawk-eagles may have higher densities and higher success rates in pristine forests, while acknowledging the possible effects of social instability, food availability, and the ecological context

[Aronsen et al., 2015]. Foerster and colleages examined fecal glucocorticoid

139 concentrations in Sykes’ monkeys (Cercopithecus mitis albogularis) and blue monkeys

(Cercopithecus mitis stuhlmanni) in two populations in Kenya [Foerster 2009; Foerster and Monfort, 2010; Foerster et al., 2011, 2012]. Though they did not exam the effect of acute stressors, they found evidence that fecal glucocorticoid concentrations in response to metabolic and reproductive variables. Unsurprisingly, environmental stressors such as changing food availability, physiological stressors including pregnancy and lactation, and acute stressors including predation are important contributors to the guenon endocrine response.

Diana monkeys appear to be comparable to the other guenons in their stress responses. Acute stressors such as predation attempts or intergroup encounters can elevate concentrations of fecal glucocorticoids, but these results indicate that season – and, perhaps, seasonal changes in food availability, also contribute to fluctuations in food availability. However, these data compose only the third published data set on endocrine responses in free-ranging arboreal guenons [Pazol, 2001; Pazol et al., 2002; Foerster

2009; Foerster and Monfort, 2010; Foerster et al., 2011, 2012; Aronsen et al., 2015].

Sample sizes in studies of guenon endocrinology thus far are highly variable: Aronsen and colleagues [2015] analyzed 50 urine samples, Foerster and colleagues [2009, 2010,

2011, 2012] analyzed between 1200-1600 fecal samples, and Pazol and colleagues [2002] analyzed just under 1000 samples. The arboreality of many guenons makes collecting fecal and urine samples challenging, while terrestrial guenons tend to be cryptic and wary of observers, which also makes sample collection difficult. Foerster and Pazol both mobilized very large research teams to improve sample collection; Michelle Williams,

140 who studies endocrine responses to intergroup encounters, works with a team of at least 6 research assistants to collect urine samples from guenons at Kibale [Williams, pers. comm.; unpublished data]. Though collecting a sample size adequate for complex analyses is a daunting process, this research shows that field endocrinology enables studies of physiological processes in arboreal, forest-dwelling guenons. Further research on guenon endocrinology, including examining more species, will clarify whether these results are typical.

Methodological Considerations

Enzyme immunoassays conducted in captivity were analytically valid. They demonstrated specificity in that serially diluted fecal extracts from 20 randomly selected samples demonstrated displacement curves parallel to those of corticosterone standards between 20%-80% binding, with slopes that did not significantly differ up to 1:256

(paired-sample t-test: t=0.561, df=11, p=0.59, n=12). Assays were also precise: the mean intra-assay coefficient of variation for this pooled sample was 8.6% (N=16). The inter- assay CV for high and low controls was 9.1% and 8.4%, respectively. The mean inter- assay CV for standard values was 9.9% (N=16). The assay also demonstrated accuracy, with a mean extraction efficiency of 80.6% (SD: 38.4%). There was no significant difference between samples collected during the morning (7:00-11:59) or afternoon

(12:00-18:30) (independent sample t-test: t= -0.442, df=346, p=0.66).

Because I verified the specificity, precision, and accuracy of EIAs in this study species, I am confident of the analytical validity of my results [Toume and Palma, 2005;

Higham, 2016]. That is, these results reflect meaningful changes in FGC concentrations

141 in captive and wild Diana monkeys. In addition, I verified that FGCs increase in response to a stressful event: FGC concentrations of three captive male Diana monkeys peaked at least two standard deviations above baseline levels 1-2 days after a veterinary exam, and returned to baseline levels within 2-4 days of that stressful experience.

There are several important caveats. I did not assess the cross-reactivity of metabolites detected by these EIAs using HPLC or radiometabolism analysis. It is therefore possible that this immunoassay detects the metabolites of adrenal hormones such as testosterone in addition to corticosterone [Ganswindt et al., 2003; Higham, 2016].

This could be particularly problematic for my validation study sample, which focused on males. This will ultimately require further research; however, the assay measured fluctuations as sensitively as possible, and there is no reason to expect an increase in testosterone or other adrenal hormones in response to the veterinary exam. However, given that wild females demonstrated responses to stressful evens that were similar to captive males, I am confident that this assay reflects a biological response to a stressful experience.

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FIGURES

Homeostatic overload Stressor

Reactive Homeostasis Stressor Stressor

Stressor

Stress response Stress Circadian variation Stress response over time Predictive Homeostasis

Time

19. Figure 4.1. The reactive scope model, indicating the normal range of fluctuations in physiological responses to stress (“Predictive Homeostasis”) and the impact of stressors (“Reactive Homeostasis”) [adapted from Romero et al., 2009].

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20. Figure 4.2. Kumasi in his enclosure at the Tulsa Zoo (courtesy of Pat Murphy).

144 a.

Kumasi FGC Validation 0.24

0.19

0.14

0.09

0.04

-0.01

-0.06

Hoy FGC Validation

0.24

0.19

0.14

0.09

0.04

-0.01

-0.06

Continues

21. Figure 4.3. Corticosterone concentrations of Kumasi, Hoy, and Elvis the week before and after their veterinary exams. The date of their veterinary exam is marked with the red arrow; the black line indicates baseline concentrations.

145

Figure 4.3 continued c.

Elvis FGC Validation 0.24

0.19

0.14

0.09

0.04

-0.01

-0.06

146

22. Figure 4.4. Mean fluctuation in FGC concentrations of three captive male Diana monkeys in the days before (N=17), the day of and after (N=6), and at least two days after (N=10) their veterinary exam. Note: Kumasi experienced very little FGC variation in the days before exam.

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23. Figure 4.5. Mean FGC concentrations from fecal samples of 21 wild female Diana monkeys collected on days where there was no stressful event (N=226), and on days when there was a stressful event that day or the previous day (N=156).

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24. Figure 4.6. Mean fluctuation from baseline in FGC concentrations from fecal samples of 3 captive adult males and 15 wild adult females, collected 1-2 days before or 2 days after a stressful event (N=56); and collected the day of or the day after a stressful event (N=54).

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REFERENCES

Arlet ME, Isbell L. 2009. Variation in behavioral and hormonal responses of adult male gray-cheeked mangabeys (Lophocebus albigena) to crowned eagles (Stephanoaetus coronatus) in Kibale National Park, Uganda. Behavioral Ecology and Sociobiology 63: 491-499.

Aronsen G, Beuerlein MM, Watts DP, Bribiescas RG. 2015. Redtail and red colobus monkeys show intersite urinary cortisol concentration variation in Kibale National Park, Uganda. Conservation Physiology 3: 1-10.

Beehner JC, Bergman TJ. 2017. The next step for stress research in primates: to identify relationships between glucocorticoid secretion and fitness. Hormones and Behavior. http://dx.doi.org/10.1016/j.yhbeh.2017.03.003.

Behie AM, Pavelka MSM, Chapman CA. 2010. Sources of variation in fecal cortisol levels in howler monkeys in Belize. American Journal of Primatology 72: 600-606.

Behringer V, Deschner T. 2017. Non-invasive monitoring of physiological markers in primates. Hormones and Behavior. http://dx.doi.org/10.1016/j.yhbeh.2017.02.001.

Brown J, Walker S, Steinman B. 2008. Endocrine Manual for Reproductive Assessment of Domestic and Non-Domestic Species. Front Royal, VA: Smithsonian’s National Zoological Park.

Brown JL, Schmitt DL, Bellem A, Graham LH, Lenhnhardt J. 1999. Hormone secretion in the Asian Elephant (Elephas maximus): characterization of ovulatory and anovulatory luteinizing hormone surges. Biology of Reproduction 61: 1294-1299.

Bshary R, Noë R. 1997b. Red colobus and Diana monkeys provide mutual protection against predators. Animal Behavior 54: 1461-1474.

Cavigelli SA. 1999. Behavioural patterns associated with faecal cortisol levels in free- ranging female ring-tailed lemurs, Lemur catta. Animal Behaviour 57: 935-944.

Chapman CA, Rothman JM, Lambert JE. 2011. Food as a selective force in primates. . In, Mitani JC, Call J, Kappeler PM, Palombit RA, Silk JB, eds. The Evolution of Primate Societies. Chicago: University of Chicago Press. 149-168.

Charmandari E, Tsigos C, Chrousos G. 2005. Endocrinology of the stress response. Annual Review of Physiology 67: 259-284. 150

Cook NJ. 2010. Minimally invasive sampling media and the measurement of corticosteroids as biomarkers of stress in animals. Canadian Journal of Animal Science 92: 227-259.

Cooke SJ, Sack L, Franklin CE, Farrell AP, Beardall J, Wikelski M, Chown SL. 2013. What is conservation physiology? Perspectives on an increasingly integrated and essential science. Conservation Physiology 1: 1-23.

Dantzer B, Westrick SE, van Kesteren F. 2016. Relationships between endocrine traits and life histories in wild animals: insights, problems, and potential pitfalls. Integrative and Comparative Biology 56: 185-197.

Dunteman GH, Ho MHR. 2006. An Introduction to Generalized Linear Models. Thousand Oaks: Sage Publications.

Engh AL, Beehner JC, Berman TJ, Whitten PL, Hoffmeier RR, Seyfarth RM, Cheney DL. 2006. Behavioural and hormonal responses to predation in female chacma baboons (Papio hamadryas ursinus). Proceedings of the Royal Society B 273: 707- 712.

Felig P, Frohman LA. 2001. Endocrinology and Metabolism. New York: McGraw-Hill.

Fichtel C. 2011. Predation. In, Mitani JC, Call J, Kappeler PM, Palombit RA, Silk JB, eds. The Evolution of Primate Societies. Chicago: University of Chicago Press. 169- 194.

Foerster S. 2009. Feeding ecology, social behavior, and physiological responses to stressors in blue and Sykes’ monkeys (Cercopithecus mitis stuhlmanni and C. m. albogularis. PhD Dissertation: Columbia University.

Foerster S, Cords M, Monfort SL. 2012. Seasonal energetic stress in a tropical forest primate: proximate causes and evolutionary implications. PLOS ONE 7: e50108.

Foerster S, Monfort SL. 2010. Fecal glucocorticoids as indicators of metabolic stress in female Sykes’ monkeys (Cercopithecus mitis albogularis). Hormones and Behavior 58: 685-697.

Fuller G, Margulis SW, Santymire R. 2011. The effectiveness of indigestible markers for identifying individual animal feces and their prevalence of use in North American zoos. Zoo Biology 30: 379-398.

151

Ganswindt A, Palme R, Heistermann M, Borragan S, Hodges JK. 2003. Non-invasive assessment of adrenocortical function in the male African elephant (Loxodonta africana) and its relation to musth. General Comparative Endocrinology 134: 156- 166.

Goland RS, Josak S, Conwell I. 1994. Placental corticotropin-releasing hormone and the hypercortisolism of pregnancy. American Journal of Obstetrics and Gynecology 171: 1287-1291.

Guesquire LR, Khan M, Shek L, Wango TL, Wango EO, Alberts SA, Altmann J. 2008. Coping with a challenging environment: effects of seasonal variability and reproductive status on glucocorticoid concentrations of female baboons (Papio cynocephalus). Hormones and Behavior 54: 410-416.

Higham JP. 2016. Field endocrinology of nonhuman primates: past, present, and future. Hormones and Behavior 84: 145-155.

Higham JP, Vitale AB, Mas Rivera A, Ayala JE, Maestripieri D. 2010. Measuring salivary analytes from free-ranging monkeys. Physiology and Behavior 101: 601-607.

Hill CM. 1994. The role of female Diana monkeys, Cercopithecus diana, in territorial defence. Animal Behaviour 47: 425-431.

Levine S, Ursin H. 1991. What is stress? In, Brown MR, Koob GF, Rivier C, eds. Stress: Neurobiology and Neuroendocrinology. New York: Marcel Dekker, Inc. 3-21.

Mason JW. 1968. A review of psychoendocrine research on the pituitary-adrenal cortical system. Psychosomatic Medicine 30: s576-s607.

Mastorakos G, Ilias I. 2003. Maternal and fetal hypothalamic-pituitary-adrenal axes during pregnancy and postpartum. Annals of the New York Academy of Sciences 997: 136-149.

McEwen BS, Stellar E. 1993. Stress and the individual: mechanisms leading to disease. Archives of Internal Medicine 153: 2093-2101.

McEwen BS, Wingfield JC. 2003. The concept of allostasis in biology and biomedicine. Hormones and Behavior 43: 2-15.

McGraw WS. 1998. Comparative locomotion and habitat use of six monkeys in the Taï Forest, Ivory Coast. American Journal of Physical Anthropology 105: 493-510.

McGraw WS, Cooke C, Shultz S. 2006. Primate remains from African crowned eagle (Stephanoaetus coronatus) nests in Ivory Coast’s Tai Forest: implications for primate predation and early hominid taphonomy in South Africa. American Journal of Physical Anthropology 131: 151-166. 152

McGraw WS, Plavcan JM, Adachi-Kanazawa K. 2002. Adult female Cercopithecus diana employ canine teeth to kill another adult female C. diana. International Journal of Primatology 23: 1301-1308.

McGraw WS, Zuberbühler K. 2007. The monkeys of the Taï forest: an introduction. In, McGraw WS, Zuberbühler K, Noë R, eds. The Monkeys of the Taï Forest: an African Primate Community. Cambridge: Cambridge University Press. 1-48. Nelson RJ. 2011. An Introduction to Behavioral Endocrinology. Sunderland: Sinauer Associates.

Oates JF, Gippoliti S, Groves CP. 2016. Cercopithecus diana. The IUCN Red List of Threatened Species e.T4245A92376689.

Pazol KA. 2001. Social, ecological, and endocrine influences on female relationships in blue monkeys (Cercopithecus mitis stuhlmanni). PhD Dissertation: University of Pennsylvania.

Pazol KA, Carlson AA, Ziegler TE. 2002. Female reproductive endocrinology in wild blue monkeys: a preliminary assessment and discussion of potential adaptive functions. In, Glenn ME, Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. Chicago: University of Chicago Press. 217-232.

Pride RE. 2005. Optimal group size and seasonal stress in ring-tailed lemurs (Lemur catta). Behavioral Ecology 16: 550-560.

Rodrigues MA, Wittwer D, Kitchen DM. 2015. Measuring stress responses in female Geoffroy’s spider monkeys: validation and influence of reproductive state. American Journal of Primatology 77: 925-935.

Romero LM, Dickens MJ, Cry NE. 2009. The Reactive Scope Model – a new model integrating homeostasis, allostasis, and stress. Hormones and behavior: 55: 375-389.

Sapolsky RM. 1987. Stress, social status, and reproductive physiology in free-living baboons. In, D. Crews, Ed. Psychobiology of Reproductive Behavior: An Evolutionary Perspective. 291-322.

Sapolsky RM. 2000. Stress hormones: good and bad. Neurobiology of Disease 7: 540- 542.

Sapolsky RM. 2004. Social status and health in humans and other animals. Annual Review of Anthropology 33: 393-418.

Sapolsky RM, Romero LM, Munck AU. 2000. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocrine Reviews 21: 55-89. 153 van Schaik CP, Isler K. 2011. Life-history evolution. In, Mitani JC, Call J, Kappeler PM, Palombit RA, Silk JB, eds. The Evolution of Primate Societies. Chicago: University of Chicago Press. 220-244.

Schülje O, Ostner J. 2011. Ecological and social influences on sociality. In, Mitani JC, Call J, Kappeler PM, Palombit RA, Silk JB, eds. The Evolution of Primate Societies. Chicago: University of Chicago Press. 195-219.

Shultz S, Faurie C, Noë R. 2003. Behavioural responses of Diana monkeys to male long- distance calls: changes in ranging, association patterns and activity. Behavioural Ecology and Sociobiology 53: 238-245.

Touma C, Palme R. 2005. Masuring fecal glucocorticoid metabolites in mammals and birds: the importance of validation. Annals of the New York Academy of Sciences 1046: 54-74.

Wark JD, Amendolagine L, Lukas KE, Kuhar CW, Dennis PM, Snowdon CT, Schoffner T, Schook MW. 2016. Fecal glucocorticoid metabolite responses to management stressors and social change in four species of callitrichine monokeys. Primates 57: 267-277. Wasser SK. Hunt KE, Brown JL, Cooper K, Crockett CM, Bechert U, Millspaugh JJ, Larson S, Monfort SL. 2000. A generalized fecal glucocorticoid assay for use in a diverse array of nondomestic mammalian and avian species. General and Comparative Endocrinology 120: 260-275.

Wasser SK, Risler L, Steiner RA. 1988. Excreted steroids in primate feces of the menstrual cycle and pregnancy. Biology of Reproduction 39: 862-872.

Wasserman M, Chapman C, Milton K, Goldberg T, Ziegler T. 2013. Physiological and behavioral effects of capture darting on red colobus monkeys (Procolobus rufomitratus) with a comparison to chimpanzee (Pan troglodytes) predation. International Journal of Primatology 34: 1020-1031.

Wingfield JC, Maney DL, Breuner CW, Jacobs JD, Lynn S, Ramenofsky M, Richardson RD. 1998. Ecological bases of hormone-behavior interactions: the “emergency life history stage.” American Zoologist 38: 191-206.

Wittig RM, Crockford C, Weltring A, Deschner T, Zuberbühler K. 2015. Single aggressive interactions increase urinary glucocorticoid levels in wild male chimpanzees. PlOSOne 10: e0118695.

Zuberbühler K. 2000. Causal knowledge of predators’ behaviour in wild Diana monkeys. Animal Behaviour 59: 209-220.

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Zuberbühler K, Jenny D. 2002. Leopard predation and primate evolution. Journal of Human Evolution 43: 873-886.

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Chapter 5: Reproductive endocrinology and ecology in wild female Diana monkeys: a preliminary analysis

INTRODUCTION

Wrangham’s sociecological model of female bonded primates is framed upon the fact that primates of different sexes have different relationships with local ecology

[Wrangham, 1980]. Males’ reproductive success is determined primarily by their access to reproductively active females [Trivers, 1972]. On the other hand, female primates have a significant energetic investment in the survival of their offspring, through gestation, lactation, and extended support throughout their juvenile period and even into adulthood

[Trivers, 1972; van Noordwijk, 2011]. Females’ diets and environmental context are the primary limits on their reproductive success, which is contingent on their ability to either build up energetic stores to support pregnancy and lactation or consume enough food during particularly energetically taxing periods of their reproductive cycle [Drent and

Daan, 1980; Stearns, 1992].

An understanding of environmental effects on female reproductive success and fitness outcomes in wild primates requires an understanding of reproductive biology.

From an applied perspective, an examination of reproductive function is also fundamental to ensuring effective conservation and management of wild and captive populations

[Wildt and Wemmer, 1999; Wikelski and Cooke, 2006]. Given the impending primate extinction crisis, examining the reproductive physiology of primates with a vulnerable 156 conservation status is particularly important, as is examining the link between the environment and reproduction [Estrada et al., 2017]. Research on reproductive physiology of female primates in degraded habitats has demonstrated the importance of ecological and behavioral flexibility for the maintenance of reproductive functions

[Milich et al., 2014]. For example, female red colobus (Procolobus rufomitratus) in logged areas of Kibale National Park expand their dietary breadth, maintaining a comparable population density with red colobus in pristine habitats where females have a narrower dietary breadth [Milich et al., 2014].

Diana monkeys, like many guenons, have a vulnerable conservation status

[Ukizintambara and Thébaud, 2002; Oates et al., 2016]. Because Diana monkeys have a diet which is seasonally variable and fruit-rich, their reproduction may also be closely linked to environmental quality and food availability [Buzzard, 2006; Kane and McGraw, in review; Chapter 2]. Much of what we know about guenons’ reproductive biology, and particularly their reproductive endocrinology, comes from captive populations. However, evidence compiled from research on wild populations suggests that the guenons are seasonal breeders, timing energetically-expensive periods of late pregnancy and lactation for periods when fruit availability peaks [Butynski, 1988]. Although many old world monkeys show external signs of estrus such as menstruation or sexual swellings, guenons do not [Hrdy and Whitten, 1987; Sommer et al. 1992]. Consequently, the best way to determine reproductive status in female guenons is to assess hormonal correlates of reproductive cycling and pregnancy such as estradiol or progesterone.

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Wasser and colleagues [1988)] established that, by analyzing concentrations of progesterone in blood, one could detect and differentiate between different phases of captive female macaques’ (Macaca nemestrina) menstrual cycles. They showed that progesterone concentrations in blood were closely correlated with progesterone metabolites in fecal samples (fP), and that ovulation could also be reliably detected through analyses of fP [Wasser et al., 1988]. They additionally carried out a cross- sectional study of wild baboons (Papio cynocephalus), finding again that fecal hormone levels were strongly correlated with blood hormone levels and that fP concentrations differentiated between females at different stages of cycling and pregnancy. Blue monkeys (Cercopithecus mitis stuhlmanni) are the only forest guenons whose reproductive endocrinology has been examined to date. In blue monkeys, ovulation and conception were indicated by peaks in fecal estrogen (fE) followed by rising concentations of both fP and fE [Pazol 2001; Pazol et al. 2002]. Because females secrete and metabolize glucocorticoids differently at different stages of the reproductive cycle, an examination of reproductive endocrinology should also examine the relationship between glucocorticoid concentrations and reproductive hormones [Mastorakos and Ilias, 2003].

In this chapter, I examine Diana monkey reproductive strategies by analyzing the timing of reproductive activity, and reproductive endocrinology. Fecal progesterone metabolites are analyzed because they have a greater magnitude of variation and tend to be easier to interpret than fE concentrations, particularly with relatively infrequent sampling, [Brockman et al. 1995; Hodges and Heistermann 2011]. Although Diana monkeys are relatively well-known from an ecological perspective, their reproductive

158 strategies have never been studied [Butynski, 1988]. Therefore, I discuss preliminary observations of Diana monkeys’ reproductive strategies. I also validate the use of fP to assess reproductive status in Diana monkeys, report fP and FGC concentrations of wild females at different stages of reproduction, and examine the relationship between feeding ecology and reproductive cycling. I predict that progesterone concentrations will be highest in pregnant females, intermediate in cycling females, and lowest in lactating females. I further predict that, because fP increases across pregnancy, and fGC concentrations at late stages of pregnancy are elevated as the fetal HPA-axis is activated, fP and FGC concentrations are correlated [Mastorakas and Ilias, 2003]. Finally, I predict that Diana monkeys, like other guenons, are seasonal breeders, with late pregnancy, birth, and lactation timed near peaks in fruit availability.

METHODS

Data Collection

Liberia. These two groups have been under regular observation since 1991. Individuals are habituated and adult females are individually identified based on features of the tail, nipples, and pelage. Fecal samples were all collected from known individuals, typically during focal follows. During the study period, which spanned from July 2013-Auust

2015, groups consisted of one-male units with 7-13 adult females, 2-5 subadults, and associated juveniles and infants. Diana 2 experienced a male transfer with an associated

159 infanticide and 6 sub-adult females matured to adult females during this period, while one female disappeared from Diana 1.

During data collection, I took ad libitum, all-occurence notes on the context of observed copulations, births, infanticide, and observations of lactation [Altmann, 1974].

Because guenons have a mean pregnancy length of 5.5 months; females were considered pregnant during the 6 months before they were observed with a neonate [Butynski, 1988].

Data on weaning in guenons is lacking; however, females were considered to be in an energetically expensive lactation stage for the 6 months following birth when infants and young juveniles spent significant time clinging to the adult females’ ventrum or extended periods of time nursing [Foerster, 2010]. I considered adult females infrequently observed nursing larger juveniles to be in a later stage of lactation, and adult females never observed nursing were assumed to be cycling.

Fecal samples were opportunistically collected from adult females, labeled by individual, time, and date of collection, and stored in a dark bag for no more than 8 hours.

Enzyme Immunoassay Protocol

Samples were extracted and FGC concentrations were assayed using the protocol described in detail in Chapter 4 [Brown et al., 2008]. To determine the proper dilution for progesterone assays, I pooled fecal extracts from 20 randomly selected samples, serially

160 diluted them, and tested for the proportion of binding when running an enzyme immunoassay for progesterone. 50% binding was reached between 1:128 and 1:256; progesterone samples were diluted 1:250 in assay buffer. I ran all samples in duplicate, re-assayed samples with % binding CVs greater than 10%, and re-diluted and re-assayed samples with binding outside the range of 20-80%.

Assay Protocol: Progesterone

Progesterone assays were run following the established protocol of the reproductive endocrinology laboratory at the Smithsonian Conservation Biology Institute, on goat-anti mouse IgG plates with all samples in duplicate [Brown et al., 2008]. Plates were loaded with 50 μL of sample and the following standards and controls, also in duplicate: blank wells with assay buffer, 9 standard values from 200 pg progesterone/well

– 0.78 pg progesterone/well, and two controls of known concentration. Twenty five μL of

Progesterone Horseradish Peroxidase (Pg-HRP) diluted to 1:100,000 was added to each well, and 25 μL of progesterone antibody (1:50,000 dilution) was added to each well except two blank wells containing only assay buffer. Plates were then covered and incubated on a shaker at 500 RPM for two hours. After two hours, they were washed with

A2 Wash solution, and 100 μL TMB (tetramethylbenzidine) was added to all wells. After incubating at room temperature for 30 minutes. Fifty μL of 1 N HCL was added to all wells to stop the immunoassay reactions. The plate was read at 450 nm on a spectrophotometer. Readings from the standards of known concentration were used to create a standard curve from which hormone concentrations were calculated for the samples.

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Statistical Methods

I used Q-Q plots to look for departure from normality. Both fP and FGC concentrations were distributed approximately normally, so I used linear mixed models

(LMM) to compare the fixed effects of progesterone and corticosterone concentrations at different reproductive stages. These models are useful because they allow repeated tests on the same individual, using individual as a random effect. I report LMM results only when a likelihood ratio test demonstrated that the addition of fixed effects was an improvement over a model based only on the intercept and random effects [Dunteman and Ho, 2006]. I also used non-parametric Kruskal-Wallis and Mann-Whitney U tests to assess intra-individual differences in fP and FGC concentrations across reproductive states. All tests were two-tailed, unless otherwise noted, with α-levels set at 0.05.

Bonferroni’s correction was used for multiple comparisons.

RESULTS

Between July 2013-August 2015, I collected 347 fecal samples from 20 females that were analyzed for fP concentrations (Pregnant: N=9; early lactation: N=14; late

162 lactation: N=252; cycling: N=80). Copulations (N=11) were observed only between

March and May, and births (N=4) occurred between October and December. Three of the four infants survived through December 2016; the fourth infant disappeared the day after its birth [Kane and Gnepa, 2016].

Reproductive Endocrinology

I collected 9 fecal samples from pregnant females, 14 fecal samples from females at the early stages of lactation, 252 fecal samples from females in the late stages of lactation, and 80 fecal samples from cycling females. FP concentrations were significantly, positively correlated with FGC concentrations (Pearson’s correlation coefficient: r=0.214, p<0.001), and fP concentrations had a significant effect on fGC concentrations (LMM: F1, 336.0 = 17.48, p<0.01) (Figure 5.1). Reproductive state also had a significant effect on fP concentrations (LMM: F3, 84.7 =3.387, p=0.02) (Figure 5.2, Table

5.1). Pregnant females had significantly higher fP concentrations (0.257, SE: 0.12) than females at the early stages of lactation (-0.062, SE=0.10) (p=0.022). A Kruskal-Wallis analysis showed that FGC concentrations at different reproductive stages differed significantly (Kruskal-Wallis: p=0.028) (Table 5.1, Figure 5.2). Post-hoc analyses showed that females in the late stages of lactation had FGC concentrations that were significantly higher than cycling (p=0.02) and pregnant females (p=0.05), and that females in the early stages of lactation had FGC concentrations that were significantly higher than pregnant females (p=0.03). However, low sample sizes during pregnancy and early lactation, make reaching broad conclusions from these data challenging.

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It was possible to collect samples at different reproductive stages for four females

(Table 5.2, Figure 5.3, Figure 5.4). Benja gave birth in December of 2014. I collected samples during her pregnancy (N=1), early lactation (N= 5; December 2013-March

2014), and late lactation (N= 11, May-August 2015). Benja’s fP concentrations differed significantly across these reproductive stages (Kruskal-Wallis: p=0.04), with the highest fP concentrations during late lactation. She displayed no significant difference in FGC concentrations across reproductive stages (Kruskal-Wallis: p=0.32). Kalje gave birth in

October of 2013. I collected fecal samples during her pregnancy (N= 4, July-October

2013), during early lactation (N= 9, November 2013-March 2014), and late lactation (N=

15, May-August 2015). Kalje’s fP concentrations also differed significantly across three reproductive stages (Kruskal-Wallis: p=0.02), with fP concentrations comparable during pregnancy and late lactation, and lowest during early lactation. There were no significant differences in corticosterone across reproductive stages (Kruskal-Wallis: p=0.12).

I collected samples from Leah as a nulliparous, cycling young adult during my first field season (N=4, July 2013-March 2014). She gave birth in October of 2014, and was in late lactation during the second field season (N=7, May-August 2015). There were no significant differences in Leah’s fP concentration between late lactation and cycling

(Mann-Whitney U: p=0.79); however, FGC concentrations were significantly higher during late lactation (Mann-Whitney U: p=0.04). Melo gave birth in October of 2013, but her infant disappeared the day after birth [Kane and Gnepa, 2016]. I collected samples during her pregnancy (N=4, July 2013-October 2013), and after her infant’s disappearance when she resumed cycling (N= 16, October 2013-August 2016). She had

164 significantly higher fP concentrations while she was pregnant than when she was cycling

(Mann-Whitney U: p=0.03); however there was no significant difference in FGC concentrations during these two reproductive stages (Mann-Whitney U: p=0.10).

DISCUSSION

Diana Monkeys’ Reproductive Strategies

These observations suggest that Diana monkeys, like most guenon species, are seasonal breeders [Butynski, 1988]. Copulations occurred only between March, April, and May. This is consistent with research on other forest guenons, whose mating seasonality seems to be exogenously cued by rainfall and perhaps photoperiodicity

[Butynski, 1988]. Some East African guenon species experience male influxes during the mating season, most notably among blue monkeys (Cercopithecus mitis: Tsingalia and

Rowell, 1984; Cords et al., 1986, Henzi and Lawes, 1988; Cords, 2000; Cords, 2002;

Macleod et al., 2002; Pazol, 2003), red-tailed monkeys (Cercopithecus ascanius: Cords,

1984; Jones and Bush, 1988; Struhsaker, 1988), and patas monkeys (Erythrocebus patas:

Chism and Rowell, 1986; Hardin and Olson, 1986; Ohsawa et al., 1993; Chism and

Rogers, 1997). In these species, extra-group males take advantage of the resident male’s inability to monopolize estrous females, and will occasionally replace the resident male

[Enstam and Isbell, 2007]. Though I did not collect behavioral data April-May 2014 or

March-April 2015, I observed no male influxes during March 2014 or May 2015, and these have not been reported in previous work on the Taï Diana monkeys. Therefore, I find no evidence that male influxes play an important role in Diana monkey reproduction

[Galat and Galat-Luong, 1979; Buzzard, 2002].

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Considering aggregated data on fruit availability and consumption, Diana monkeys in the Taï Forest seem to be “classically timed” seasonal breeders, with births occurring shortly before a peak in fruit availability [van Schaik and van Noordwijk, 1985;

Anderson et al., 2005; Kane and McGraw, in review; Chapter 2]. Diana monkeys mate between March and May, when fruit availability is generally quite low; fruit availability increases and peaks between November and February, and Diana monkeys give birth and engage in energetically expensive late pregnancy and early lactation between October-

March during a peak in fruit availability (Figure 5.6) [Anderson et al., 2005; van

Noordwijk, 2011; Polansky and Boesch, 2013; Kane and McGraw in review, 2017]. This is generally consistent with research on other guenons in the Upper Guinean Forest of

West Africa: Campbell’s monkeys (Cercopithecus campbelli) in southeastern Côte d’Ivoire were observed giving birth between August and January, with births primarily occurring between November and January [Bourlière et al., 1970; Galat-Luong and Galat,

1979]. Diana monkeys in Tiwai, Sierra Leone and Roloway monkeys (Cercopithecus roloway; until recently C. diana roloway) in Bia, Ghana, have birth seasons that peak between November and February [Enstam and Isbell, 2007; Oates, 2011; Koné et al.,

2017].

A useful way to conceptualize this is to place Diana monkeys and other guenons along a continuum, between females who rely on available energetic capital (e.g., fat stores) and females who rely on energetic income (e.g., diet) to support their reproductive output [Drent and Daan, 1980; Stearn, 1989]. A species with an entirely capital-breeding strategy, such as hooded seals (Cystophora cristata) relies only on its built-up fat to

166 support pregnancy and lactation [Iverson et al., 1995]. On the other hand, a species with an entirely income-breeding strategy maintains no energy stores and relies entirely on its diet to supply the energy for reproduction [Stearns, 1989]. Tokophyra lemnarum stein, ciliate protozoa that feed on Paramecium, exemplify this strategy: they bud off one offspring per Paramecium ingested [Kent, 1981]. While the strategies of these organisms are extreme, aspects of their reproductive strategies are recognizeable among the primates, and the capital-income breeding spectrum remains a useful heuristic for understanding primate reproduction [Brockman and van Schaik, 2005]. For example, orangutans are classic capital breeders who do not conceive until they have adequate energy stores, and have lengthy inter-birth inverals [Knott, 2001]. Ring-tailed lemurs, on the other hand, can be considered income breeders because they conceive at the same annually regardless of their energy status and rely heavily on food intake to support the energetic demands of pregnancy and lactation [Brockman and van Schaik, 2005].

Diana monkeys, who nurse their offspring at least intermittently for between a year and two years, cannot sustain this energetic output purely on their fat reserves, nor is there a 1:1 energetic input and output that enables reproduction and lactation. Available data suggest that the reproductive strategy of Diana monkeys, and guenons more generally, lies towards the income breeding end of the spectrum (Table 5.3) [Brockman and van Schaik, 2005; van Noordwijk, 2011]. While detailed data on fat storage and maternal condition of wild guenons are lacking, as are data on prenatal mortality [e.g.,

Roberts et al., 2012], guenons mate and give birth during distinct seasons relative to fruit availability, have consistent inter-birth intervals from year to year, and relatively high

167 infant mortality [Butynski, 1988; Cheney et al., 1988; Nakagawa et al., 2003; Jaffe and

Isbell, 2011; Isbell et al., 2009; Cords and Chowdhury, 2010; Oates, 2011; Kane and

Gnepa, 2016]. Female guenons tend to conceive on their first ovulation after amenorrhea

[Rowell and Dixson, 1975; Rowell, 1977; Andelman et al., 1985; Pazol, 2001]. On the more capital end of the spectrum, captive female Diana monkeys may relax breeding seasonality. A female Diana monkeys at the Tulsa Zoo gave birth in May 2015 and a female at Chicago’s Lincoln Park Zoo gave birth in January 2015 [Pers. comm., Patrick

Murphy]. This suggests that females may ovulate in response to maternal condition rather than an external trigger such as photoperiod [van Noordwijk, 2011]. More detailed data on guenon reproductive endocrinology will help clarify the Cercopithecini reproductive strategy.

Diana Monkey Reproductive Endocrinology

Enzyme immunoassays were analytically valid for fecal progesterone concentrations. They demonstrated specificity in that serially diluted fecal extracts from

20 randomly selected samples demonstrated displacement curves parallel to those of progesterone standards between 20-80% binding, with slopes that did not significantly differ (paired-sample t-test: t=1.439, df=13, p=0.174, n=20). Assays were precise: the mean intra-assay coefficient of variation for this pooled sample was 8.4% (N=18). The inter-assay CVs for high and low controls were 7.2% and 7.3%, respectively, and the inter-assay CVs for standards was 9.3% (N=18). The assays were also accurate, with a mean extraction efficiency of 80.0% (SD: 12.5%). I did not conduct a separate

168 physiological analysis of fP, but did assess differences in fP concentrations between females at different reproductive stages.

These data on Diana monkey reproductive endocrinology are highly preliminary, limited in their explanatory power by low sample sizes during pregnancy and early lactation, and relatively low sampling frequency for most monkeys. However, these data demonstrate that fecal progesterone concentrations are significantly higher in pregnant females than in females at the early stages of lactation (Figure 5.1, 5.3). Fecal progesterone concentrations do not differ significantly between females who were at the late stages of lactation (i.e., intermittently nursing an infant or juvenile at least 6 months old) and females who were cycling (i.e., nulliparous adult females, adult females whose infant disappeared, females with weaned offspring). These relationships were consistent in intra-individual comparisons across different reproductive stages: females had consistently higher fP concentrations while pregnant than during the early stages of lactation. These data are comparable to data on reproductive endocrinology of blue monkeys (Cercopithecus mitis), whose fP concentrations rose across the pregnancy, though in this species fecal estradiol metabolites were better indicators of ovulation and conception [Pazol, 2001; Pazol et al., 2002].

During pregnancy, interactions between the maternal and fetal hypothalamic- pituitary-adrenal (HPA) axis acts to increase secretion of ACTH and thus circulating cortisol concentration [Mastorakos and Ilias, 2003]. However, during this study pregnant females tended to have lower FGCs than lactating or cycling females, though this trend was non-significant (Figure 5.2, 5.4). This is likely due at least in part to very low sample

169 sizes during pregnancy compared to lactating and cycling females. Considering intra- individual variation in different reproductive states, Leah had higher FGC concentrations during late lactation than cycling (Figure 5.4, Table 5.2). This corroborates data from species such as baboons and macaques, where lactating females have elevated FGC concentrations compared to cycling females [Weingrill et al., 2004; Beehner et al., 2005;

Engh et al., 2006]. This is hypothesized to be the result of increased female vigilance and received aggression in response to risks to infants from infanticide and kidnapping [Silk,

1980; Cheney et al., 2004]. We have observed two infanticides in three years of research on Diana monkeys, which suggests that infanticide may be a salient threat to very young

Diana monkeys [Kane and Gnepa, 2016; TMP unpublished data]. However, it is not clear that this would be a concern for mothers of older infants and juveniles towards the end of lactation. Foerster and colleagues [2012] found no effect of reproductive stage on FGC concentrations in blue monkeys (C. mitis stuhlmanni). They hypothesize that the expected increase in FGCs in late pregnancy may have been masked because females give birth when fruit availability is highest, relieving metabolic stress [Foerster et al.,

2012]. In other words, in blue monkeys, environmental stressors may be more important determinants of glucocorticoid concentrations, masking the physiological effects of pregnancy on glucocorticoid secretions. This hypothesis also may help explain the unexpected relationship betweeen Diana monkeys’ fGC concentrations at different reproductive states; however, more data at different reproductive stages are required.

This preliminary work provides only the second dataset on reproductive endocrinology of wild forest guenons (genus Cercopithecus) [Pazol, 2001; Pazol et al.,

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2002]. Future work will require a more intensive sampling regime, perhaps with a larger field team. In this study, Frederic Gnepa and I opportunistically collected fecal samples during the course of regular data collection, which included scan and focal sampling.

Work on the reproductive endocrinology of blue monkeys (Cercopithecus mitis), by contrast, is based on 1603 fecal samples collected from 37 females over 3 years as part of a focused effort by a relatively large team [Pazol, 2001; Pazol et al., 2002]. Advantages of that study included a high defecation frequency (mean inter-defecation interval of less than two hours), monkeys who spent much of the day low in the canopy or in open habitat, and between 3 and 11 field assistants with groups at a given time [Pazol, 2001].

Although Diana monkey strata use is less amenable to this sort of research, increasing the number of observers will certainly improve sample sizes.

Consequently, future work with more intensive sampling may allow stronger inferences regarding the relationship between female reproductive state and endocrinology. In particular, it would be helpful to test the relationship between progesterone and estradiol concentrations in Diana monkeys, and determine whether estradiol indicates ovulation and conception in Diana monkeys as it does in blue monkeys

[Pazol, 2001; Pazol et al. 2002]. An important step in understanding female reproductive strategies is to determine whether conception occurs during the first ovulation after amenorrhea ceases [van Noordwijk, 2011]. Assessing the energetic status of Diana monkeys in relation to reproductive state and cycling would also help clarify whether maternal condition, abiotic factors, or a combination thereof cues ovulation.

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Preliminary data collection to address these questions is ongoing at the Tulsa Zoo, where zookeepers have been collecting fecal samples from Stormy, an adult female

Diana monkey, 5 times a week since September 2015. Stormy gave birth on May 13,

2016; since that date keepers have also been collecting samples from her infant. I plan to assess corticosterone, progesterone, and estradiol concentrations in Stormy’s fecal samples across this period, capturing the endocrinology her of estrus cycle, pregnancy, parturition, and early and late lactation. I also hope to assess metabolites of oxytocin and prolactin to assess the effect of lactation on these hormones. Finally, I would like to assess the impact of weaning on Stormy and her infant with endocrine and stable isotope analyses [Reitsema, 2012; Bădescu et al., 2017]. I plan to expand this captive study to incorporate Diana monkeys at the Lincoln Park Zoo and other European facilities, and eventually apply these methods to wild Diana monkeys.

Because Diana monkeys do not display external signals of ovulation, non- invasive analyses of reproductive hormones are required to assess Diana monkey reproduction. This study provides a preliminary methodological and biological validation for the use of fecal metabolites of progesterone to detect pregnant and lactating females.

In addition, this study shows that Diana monkeys, like most guenons, have a reproductive strategy that is generally towards the “income breeder” side of the spectrum [van

Noordwijk, 2011]. Diana monkeys have focused mating seasons, which consistently occur during periods of low fruit availability, and focused birth seasons that are consistently timed as fruit availability is increasing. This research, then, supports the

172 notion that fruit consumption, productivity, and access to fruiting trees can have a significant effect on the reproductive success of female Diana monkeys.

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TABLES

Reproductive fP concentration 95% FGC 95% Stage ± SE confidence concentration ± confidence interval SE interval Pregnant 0.30 ± 0.11 0.09 – 0.51 -0.04 ± 0.04 -0.12 – 0.05 Early lactation -0.92 ± 0.09 -0.27 – 0.08 0.08 ± 0.04 0.01 – 0.15 Late lactation 0.09 ± 0.03 0.04 – 0.14 0.05 ± 0.01 0.03 – 0.07 Cycling 0.35 ± 0.04 -0.43 – 0.11 0.02 ± 0.02 -0.01 – 0.05 17. Table 5.1. Mean concentrations of fecal progesterone and fecal glucocorticoids (μg/g fecal dry weight; difference from baseline) when females are pregnant, in early stages of lactation, late stages of lactation, and cycling.

Individual Pregnant Early Late Cycling Lactation Lactation

Benja N=1 N=5 N=11 fP -0.023 -0.173 0.081 P=0.04 FGC -0.063 0.084 0.053 P=0.32

Kalje N=4 N=9 N=15 fP 0.252 -0.001 0.221 P=0.02 FGC -0.011 0.057 0.096 P=0.12

Leah N=4 N=7 fP -0.026 0.045 P=0.79 FGC 0.205 -0.040 P=0.04

Melo N=4 N=16 fP 0.354 -0.089 P=0.03 FGC -0.006 0.077 P=0.10 18. Table 5.2. Intra-individual comparisons of mean fecal progesterone and fecal corticosterone concentrations (μg/g fecal dry weight; difference from baseline) during different reproductive stages

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Income Capital Guenons Diana and Roloway monkeys Breeders Breeders Seasonal mating Variable, non- Income Income and birth seasonal mating Tightly spaced mating and birth Mating peaks between March- periods and birth seasons for most species in which April [this study] periods this has been studied [Butynski, Tightly spaced birth season 1988; Jaffe and Isbell, 2011] between October-December [this study]; December- February [Oates, 2011]; November-January [Jaffe and Isbell, 2011] Mating and birth No seasonality in Unknown Capital seasonality after mating and birth Female Diana monkeys gave translocation after birth in January at the translocation Lincoln Park Zoo [LPZ news], gave birth in May at the Tulsa Zoo [Pers. communication, Pat Murphy] Few ovarian Variable number Income Unknown cycles before of ovarian Females tend to conceive on their conception cycles before first ovulation following conception amenorrhea in Cercopithecus mitis [Pazol, 2001]; Erythrocebus patas [Pazol, 2001]; Miopithecus talapoin [Rowell and Dixson, 1975; Rowell, 1977], Chlorocebus aethiops [Andelman et al., 1985] Little to no fat Fat reserves Unknown Unknown accumulation accumulate during during pregnancy pregnancy

Low prenatal High prenatal Unknown Unknown mortality mortality Low variation in High variation in Income Unknown interannual birth interannual birth Guenon species tend to have inter- Preliminary data suggest that rates and inter- rates and inter- birth intervals from 1-2 years that Diana monkeys have a two- birth intervals birth intervals are consistent within species at year inter-birth interval particular sites [Jaffe and Isbell, 2011] High variation in Low variation in Income Income infant mortality infant mortality Variable infant mortality in Probable infanticide accounted rates rates Cercopithecus mitis [Cords and for at least two infant deaths Chowdhury, 2010], Chlorocebus during this study period aethiops [Cheney et al., 1988; [Kane and Gnepa, 2016; Taï Isbell et al., 2009], Erythrocebus Monkey Project, unpublished patas [Nakagawa et al., 2003] data] 19. Table 5.3 Income vs. Capital Breeders: Diana monkeys’ place on the continuum [Adapted from Brockman and van Schaik, 2005 and van Noordwijk, 2011]

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FIGURES

2.5

2.0

1.5

1.0

0.5

0.0 (µg/g fecal dry weight) dry (µg/g fecal

-0.5 Progesteronee baseline fluctuation from Progesteronee -1.0 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 Corticosterone fluctuation from baseline (µg/g fecal dry weight)

25. Figure 5.1. The relationship between progesterone concentrations (fluctuation from baseline) and corticosterone concentrations (fluctuations from baseline) in 347 samples collected from wild female Diana monkeys.

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Meanfluctuation Progesteroneof fecal from baseline

26. Figure 5.2. Mean fluctuation from baseline of fecal progesterone (fP) concentrations when females were pregnant (N=9), in early lactation (N=14), in late stages of lactation (N=252), and cycling (N=80).

177

frombaseline

corticosterone Meanfluctuation of fecal

27. Figure 5.3. Mean fluctuation of fecal corticosterone concentrations from baseline when females were pregnant (N=9), in early lactation (N=14), in late stages of lactation (N=252), and cycling (N=80).

178

(µg/g fecal dry weight) (µg/g dry fecal Mean fP Fluctuation baseline from of

28. Figure 5.4. Intra-individual comparisons of fecal progesterone (fP) concentrations across the reproductive cycle for four females with samples collected during at least two reproductive stages.

179

from baseline from

(µg/g fecal dry weight) (µg/g dry fecal Meanf Fluctuation of

29. Figure 5.5. Intra-individual comparisons of fecal glucocorticoid (fGC) concentrations across the reproductive cycle for four females with samples collected during at least two reproductive stages.

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60.0% 0.35

50.0% 0.30

0.25 40.0% 0.20 30.0%

0.15 FoodAvailability

Proportion of Fruit 20.0% 0.10

10.0% 0.05

0.0% 0.00

Overall Fruit Consumption Fruit Availability

30. Figure 5.6. Monthly fruit consumption (green line), fruit availability (purple line), and timing of births (blue stars) in the two Diana monkey groups.

181

REFERENCES

Altmann JA. 1974. Observational study of behavior: sampling methods. Behaviour 49: 227-267.

Andelman SJ, Else JG, Hearn JP, Hodges JK. 1985. The non-invasive monitoring of reproductive events in wild Vervet monkeys (Cercopithecus aethiops) using urinary prgnanediol-3α-glucuronide and its correlation with behavioural observations. Journal of Zoology 205: 467-477.

Anderson DP, Nordheim EV, Moermond TC, Gone Bi ZB, and Boesch C. 2005. Factors influencing tree phenology in Taï National Park, Côte d’Ivoire. Biotropica 37: 631- 640.

Bădescu I, Katzenberg MA, Watts DP, Sellen DW. 2016. A novel fecal stable isotope approach to determine the timing of age-related feeding transitions in wild infant chimpanzees. American Journal of Physical Anthropology 16: 285-299.

Beehner JC, Bergman TJ, Cheney DL, Seyfarth RM, Whitten PL. 2005. The effect of new alpha males on female stress in free-ranging baboons. Animal Behaviour 69: 1211-1221.

Bourlière F, Hunkeler C, Bertrand M. 1970. Ecology and behaviour of Lowe’s guenon (Cercopithecus campbelli lowei) in the Ivory Coast. In, Napier JR, Napier PH, eds. Old World Monkeys: Evolution, Systematics, and Behaviour. New York: Academic Press. 297-350.

Brockman DK, van Schaik CP. 2005. Seasonality and reproductive function. In, Brockman DK, van Schaik CP, eds. Seasonality in Primates: Studies of Living and Extinct Human and Non-Human Primates. New York: Cambridge University Press. 269-305.

Brockman DK, Whitten PL, Russell E, Richard AF, Izard MK. 1995. Application of fecal steroid techniques to the reproductive endocrinology of female Verreaux’s Sifaka (Propithecus verreauxi). American Journal of Primatology 36: 313-325.

Brown J, Walker S, Steinman B. 2008. Endocrine Manual for Reproductive Assessment of Domestic and Non-Domestic Species. Front Royal, VA: Smithsonian’s National Zoological Park.

182

Butynski TM. 1988. Guenon birth seasons and correlates with rainfall and food. In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. New York: Cambridge University Press. 284-322.

Buzzard PJ, Eckardt W. 2007. The social systems of the guenons. In, McGraw WS, Zuberbühler K, Noë R, eds. Monkeys of the Taï Forest: An African Primate Community. Cambridge: Cambridge University Press. 51-71. Cheney DL, Seyfarth RM, Andelman SJ, Lee PC. 1988. Reproductive success in vervet monkeys. In, Clutton-Brock, TH, ed. Reproductive Success. Chicago: Chicago University Pres. 384-402. Cheney DL, Seyfarth RM, Fischer J, Beehner J, Bergman T, Johnson SE, Kitchen DM, Palombit RA, Rendall D, Silk JB. 2004. Factors affecting reproduction and mortality among baboons in the Okavango Delta, Botswana. International Journal of Primatology 25: 401-428. Chism JB, Rogers W. 1997. Male competition, mating success, and female choice in a seasonally breeding primate (Erythrocebus patas). Ethology 103: 109-126.

Chism JB, Rowell TE. 1986. Mating and residence patterns of male patas monkeys. Ethology 72: 31-39.

Cords M. 1984. Mating patterns and social structure in redtail monkeys (Cercopithecus ascanius). Zeitschrift für Tierpsychologie 64: 313-339. Cords M. 2000. The number of males in guenon groups. In, Kappeler P, ed. Primate Males. Cambridge: Cambridge University Press. 84-96.

Cords M. 2002. When are there influxes in blue monkey groups? In, Glenn ME, Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. New York: Kluwer Academic/Plenum Publishers. 189-201.

Cords M, Chowdhury S. 2010. Life history of Cercopithecus mitis stuhlmanni in the Kakamega Forest, Kenya. International Journal of Primatology 31: 433-455. Cords M, Mitchell BJ, Tsingalia HM, Rowell TE. 1986. Promiscuous mating among blue monkeys in the Kakamega Forest, Kenya. Ethology 72: 214-226.

Drent, RH and Daan, S. 1980. The Prudent Parent: Energetic adjustments in avian breeding. In, Klomp H, Woldendrop JW, eds. The Integrated Study of Bird Populations. New York: North Holland, pp. 225-252.

Dunteman GH, Ho MHR. 2006. An Introduction to Generalized Linear Models. Thousand Oaks: Sage Publications.

183

Engh AL, Beehner JC, Bergman TJ, Whitten PL, Hoffmeier RR, Seyfarth RM, Cheney DL. 2006. Female hierarchy instability, male immigration, and infanticide increase glucocorticoid levels in female chacma baboons. Animal Behaviour 71: 1227-1237.

Enstam KL, Isbell LA. 2007. The guenons (genus Cercopithecus) and their allies: behavioral ecology of polyspecific associations. In, Campbell CJ, Fuentes A, MacKinnon KC, Panger M, Bearder SK, eds. Primates in Perspective. 252-274.

Estrada A, Garber PA, Rylands AB, Roos C, Fernandez-Duque E, di Fiore A, Nekaris KA, Nijman V, Heymann EW, Lambert JE, Rovero F, Barelli C, Setchell JM, Gillespie TR, Mittermeier RA, Arregoitia LV, de Guinea M, Gouveia S, Dobrovolski R, Shanee S, Shanee N, Boyle SA, Fuentes A, MacKinnon KC, Amato KR, Meyer ALS, Wich S, Sussman RW, Pan R, Kone I, Li B. 2017. Impending extinction crisis of the world’s primates: why primates matter. Science Advances 3: e1600946.

Foerster S, Cords M, Monfort SL. 2012. Seasonal energetic stress in a tropical forest primate: proximate causes and evolutionary implications. PLOS ONE 7: e50108.

Galat-Luong A, Galat G. 1979. Consèquences comportementales de perturbations sociales repetés sur une troupe de mones de Lowe Cercopithecus campbelli lowei de Côte d’Ivoire. Tere Vie 33: 49-58.

Harding RSO, Olson DK. 1986. Patterns of mating among male patas monkeys (Erythrocebus patas) in Kenya. American Journal of Primatology 11: 343-358.

Henzi SP, Lawes, M. 1988. Strategic responses of male samango monkeys (Cercopithecus mitis) to a decline in the number of receptive females. International Journal of Primatology 9: 479-495.

Hodges JK, Heistermann M. 2011. Field endocrinology: monitoring hormonal changes in free-ranging primates. In, Setchell J, Curtis D, eds. Field and Laboratory Methods in Primatology. Cambridge: Cambridge University Press. 282-294.

Hrdy SB, Whitten PL. 1986. Patterning of sexual activity. In, Smutts BB, Cheney DL, Sefarth R, Wrangham RW, Struhsaker TT, eds. Primate Societies. Chicago: Chicago University Press. 370-384.

Isbell LA, Young TP, Jaffe KE, Carlson AA, Chancellor RL. 2009. Demography and life histories of sympatric patas monkeys, Erythrocebus patas, and vervets, Cercopithecus aethiops, in Laikipia, Kenya. International Journal of Primatology 30: 103-124.

Iverson SJ, Oftedal OT, Bowen WD, Boness DJ, Sampugna J. 1995. Prenatal and postnatal transfer of fatty acids from mother to pup in the hooded seal. Journal of Comparative Physiology B. 165: 1-12.

184

Jones WT, Bush BB. 1988. Movement and reproductive behavior of solitary male redtail guenons (Cercopithecus ascanius). American Journal of Primatology 14: 203-222.

Kane EE, Gnepa F. 2016. An infanticide attempt after male takeover in Diana monkeys (Cercopithecus diana diana) in Taï, Côte d’Ivoire. African Primates 11: 37-40.

Kent EB. 1981. Life history responses to resource variation in a sessile predator, the ciliate protozoan Tokophyra lemnarum stein. Ecology 62: 296-302.

Knott CD. 2001. Female reproductive ecology of the apes. In, Ellison PT, ed. Reproductive Ecology and Human Evolution. New York: Aldine de Gruyter. 429- 463.

Koné I, Gonedelé Bi S, Osei D, Wiafe E, Dempsey A, McGraw WS, Oates JF. 2017. Cercopithecus Roloway. IUCN 2017, IUCN Red List of Threatened Species. Macleod MC, Ross C, Lawes MJ. 2002. Costs and benefits of alternative mating strategies in Samango monkey males. In, Glenn ME, Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. New York: Kluwer Academic/Plenum Publishers. 203-216.

Mastorakos G, Ilias I. 2003. Maternal and fetal hypothalamic-pituitary-adrenal axes during pregnancy and postpartum. Annals of the New York Academy of Sciences 997: 136-149.

Milich KM, Stumpf RM, Chambers JM, Chapman CA. 2014. Female red colobus monkeys maintain their densities through flexible feeding strategies in logged forests in Kibale National Park, Uganda. American Journal of Physical Anthropology 154: 52-60.

Nakagawa N, Ohsawa H, Muroyama Y. 2003. Life-history parameters of a wild group of West African patas monkeys (Erythrocebus patas patas). Primates 44: 281-290. van Noordwijk MA. 2011. From maternal investment to lifetime maternal care. In, Mitani JC, Call J, Kappeler PM, Palombit RA, Silk JB, eds. The Evolution of Primate Societies. Chicago: Chicago University Press. 321-342.

Oates JF. 2011. Cercopithecus diana (Linnaeus, 1758) Diana and roloway monkeys. In Primates of West Africa. Bogotá: Panamericana Formas e Impresos. 251-264.

Oates JF, Gippoliti S, Groves CP. 2016. Cercopithecus diana. The IUCN Red List of Threatened Species 2016: e.T425A92376689. 185

Ohsawa H, Inoue M, Takenaka O. 1993. Mating strategy and reproductive success of male patas monkeys (Erythrocebus patas). Primates 34: 533-544.

Pazol KA. 2001. Social, ecological, and endocrine influences on female relationships in blue monkeys (Cercopithecus mitis stuhlmanni). PhD Dissertation: University of Pennsylvania.

Pazol KA. 2003. Mating in the Kakamega Forest blue monkeys (Cercopithecus mitis): does female sexual behavior function to manipulate paternity assessment? Behaviour 140: 473-499.

Polansky L, Boesch C. 2013. Long-term changes in fruit phenology in a West African lowland tropical rain forest are not explained by rainfall. Biotropica 45: 434-440.

Reitsema LJ. 2012. Introducing fecal stable isotope analysis in primate weaning studies. American Journal of Primatology 74: 926-939.

Roberts EK, Lu A, Bergman TJ, Beehner JC. 2012. A Bruce effect in wild Geladas. Science. 335: 1222-1225.

Rowell, TE, and Dixon AF. 1975. Changes in the social organization during the breeding season of wild talapoin monkeys. Journal of Reproduction and Fertility 43: 419-434.

Rowell TE. 1977. Reproductive cycles of the talapoin monkey (Miopithecus talapoin). Folia Primatology 28: 188-202. van Schaik CP, van Noordwijk M. 1985. Interannual variability in fruit abundance and the reproductive seasonality in Sumatran Long-tailed macaques (Macaca fascicularis). Journal of Zoology 206: 533-549.

Silk JB. 1980. Kidnapping and female competition among captive bonnet macaques. Primates 21: 100-110.

Sommer V, Srivastava A, Borries C. 1992. Cycles, sexuality, and conception in free- ranging langurs (Presbytis entellus). American Journal of Primatology 10: 293-317.

Stavisky R, Russell E, Stallings J, Smith EO, Worthman C, Whitten PL. 1995. Fecal steroid analysis of ovarian cycles in free-ranging baboons. American Journal of Primatology 36: 285-297.

Stearns, S.C. 1989. Trade-offs in life-history evolution. Functional Ecology 3: 259-268. 186

Struhsaker TT. 1988. Male tenure, male influxes, and reproductive success in redtail monkeys (Cercopithecus ascanius). In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. New York: Cambridge University Press. 340-363.

Trivers RL. 1972. Parental investment and sexual selection. In, Campbell B, ed. Sexual Selection and the Descent of Man 1871-1971. Chicago: Aldine Press. 139-179. Tsinalia HM, Rowell TE. 1984. The behaviour of adult male blue monkeys. Ethology 64: 253-268. Ukizintambara T, Thébaud C. 2002. Assessing extinction risk in Cercopithecus monkeys. In, Glenn ME, Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. Chicago: University of Chicago Press. 393-410. Wasser SK, Risler L, Steiner RA. 1988. Excreted steroids in primate feces over the menstrual cycle and pregnancy. Biology of Reproduction 39: 862-872.

Weingrill T, Gray D, Barrett L, Henzi SP. 2004. Fecal cortisol levels in free-ranging female chacma baboons: relationship to dominance, reproductive state, and environmental factors. Hormones and Behavior 45: 259-269.

Wikelski M, Cooke SJ. 2006. Conservation physiology. Trends in Ecology and Evolution 21: 38-46.

Wildt DE, Wemmer C. 1999. Sex and wildlife: the role of reproductive science in conservation. Biodiversity and Conservation 8: 965-976.

Wrangham RW. 1980. An ecological model of female-bonded primate groups. Behaviour 75: 262-300.

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Chapter 6: Assessing the relationship between stress, ecology, and female behavior

INTRODUCTION

Diana monkeys, like most guenons, are seasonal breeders who time energetically expensive periods of reproduction during periods of high fruit availability [Butynski,

1988; Chapter 5]. This reproductive seasonality is typically explained as a response to energetic burdens placed on females during these energetically-demanding periods of the reproductive cycle [van Schaik and van Noordwijk, 1985; van Noordwijk, 2011]. For capital breeders, easy access to fruit in certain seasons allows females to store excess energy for late pregnancy and lactation [Brockman et al., 2005]. Income breeders rely on access to energy-rich food during their late pregnancy and lactation to support these energy expenditures [Brockman et al., 2005]. Observed reproductive seasonality, then, indicates that food availability is a limiting factor for females’ reproductive success, and that their energy requirements can only be satisfied at certain times of year. The Tai

Forest is a seasonal environment with predictable fluctuations in food availability

[Anderson et al., 2005; Polansky and Boesch, 2013]. Diana monkey diets differ from month to month; though these fluctuations are not directly correlated with fruit availability, consumption of most fruit species are at least loosely correlated with phenological productivity [Chapter 2].

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Non-invasive assessment of the energy status of wild primates is challenging. The most sensitive method for assessing energy balance requires the collection and analysis of ketones and metabolites of insulin in urine [Emery Thompson and Knott, 2008].

Successfully collecting uncontaminated urine from arboreal guenons [e.g., no cross- contamination from feces, ideally pipetted directly from leaves] can be prohibitive, so researchers have adopted other non-invasive proxies for health and energetic status using fecal analyses [Michelle Williams, pers. comm.]. Periods of extreme metabolic stress can be detected through fecal isotope analysis, but for this to be possible organisms must be in extremely poor energetic condition, such that their body metabolizes itself and isotopically enriches its own tissues [e.g., Cherel et al., 2005]. However, fluctuations in fecal and urinary glucocorticoid metabolites, however, have been used as proxies for metabolic status in several primate species [e.g., Pride, 2005; Foerster and Monfort,

2010; Foerster et al., 2011, 2012].

The mobilization of glucose is an important function of normal day-to-day metabolic function; glucocorticoids are an important part of this physiological process in addition to their role modulating the response to acute stressors via activation of the hypothalamic-pituitary-adrenal axis [Sapolsky et al., 2000; Beehner and Bergman, 2017].

Consequently, assessing glucocorticoid concentrations – or the concentration of fecal glucocorticoid metabolites (FGCs) – can help track both the prevalence of acute stressors, social stress, and metabolic stress. For example, FGC concentrations of female blue monkeys (C. m. stuhlmanni) increased as time spent feeding, time spent feeding on non- preferred foods, and availability of non-preferred foods increased [Foerster and Monfort,

189 et al., 2012]. Increased time spent feeding on preferred foods (invertebrates, fruits, and young leaves) decreased these monkeys’ FGC concentrations, though fruit availability had no effect on FGC concentrations. Provisioned blue monkeys (C. m. albogularis) experienced increased FGC concentrations when preferred foods were less available, and decreased FGC concentrations as preferred foods were more readily available – even in light of high rates of agonism and provisioning [Foerster and Monfort, 2010]. This underscores the complex role of glucocorticoids in moderating both physiological responses to the environment and psychosocial variables, as well as the challenges of interpreting fluctuations in glucocorticoids [Beehner and Bergman, 2017].

Here, I examine the effects of several of these variables – diet and food availability, reproductive status, and social interactions – on fecal glucocorticoid concentrations in wild female Diana monkeys (Figure 6.1). I expect that a subset of variables will be correlated with elevated fecal FGC concentrations, a subset will be correlated with lower FGC concentrations, and a few will have no correlation. Increased feeding effort is associated with a rank-related effect of elevated FGCs in female blue monkeys (C. mitis albogularis) [Foerster and Monfort, 2010]. Though I did not evaluate rank in this population, I expect Diana monkeys will also have an inverse relationship between FGC concentrations and feeding effort. Here, I use fruit availability as a proxy for feeding effort, assuming that Diana monkeys will have a harder time consuming a fruit-rich diet when fruit is less available. I expect Diana monkeys will have higher FGCs in months when fruit availability is low, and lower FGCs in months when fruit is readily available. I expect Diana monkeys will have lower FGCs in months where they eat more

190 fruit, since fruit provides a ready source of energy, and higher FGCs in months where they eat more invertebrates and less fruit. Because leaves make up a relatively small proportion of Diana monkey diets, I expect no correlation between leaf consumption, leaf availability, and FGCs.

In examining the relationship between FGCs and reproductive status, I predict that females in the energetically-demanding stages of pregnancy and lactation will have higher FGC concentrations than cycling females. Because fecal progesterone concentrations tend to increase during pregnancy, I also predict that FGC concentrations will be correlated with fP concentrations. Finally, I test the hypothesis that Diana monkeys’ FGC concentrations are reflective of group-level psychological stress. In blue monkeys (C. mitis stuhlmanni), rates of agonism had no effect on FGC concentrations, but the group which engaged in more grooming had lower FGC concentrations overall

[Foerster et al., 2011]. Though Diana monkeys engage in these behaviors rarely, I expect that months with more prosocial behavior will have lower FGC concentrations, and months with higher rates of agonism will have higher FGC concentrations.

METHODS

Behavioral and Ecological Methods

Data were collected on wild female Diana monkeys (Cercopithecus diana) between May 2013-August 2015. Females lived in two groups in the primary study grid of the Taï Monkey Project in Taï National Park. Individuals were individually identifiable based on features of the tail, nipples, and pelage, as well as vocalizations.

Data on diet and activity were generated from scan samples conducted every 60 minutes

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[Altmann, 1974]. Each scan lasted up to 15 minutes due to visibility constraints. During scan sampling, Frederic Gnépa and I walked below the group, recording individual identity, age- and sex-class, and behavior of all visible juveniles, subadults, and adults.

Behaviors included foraging, resting, locomotion, nursing, aggression (threats, fights, vocalizing), and affiliation (grooming, social play). If individuals were foraging, we recorded food type (fruit, leaves, invertebrate, other) and species. To assess forest productivity in home ranges, field assistants conducted phenological surveys every two weeks along an established fruit trail that cut through group home ranges, incorporating

289 trees in 58 species [Chapman et al., 1994]. Trees were assessed for fruiting, leaf flushing, and flowering on a 0-3 scale (0=0-25% full; 1=25-50% full; 2=50-75% full;

3=75-100% full) [Buzzard, 2004]. The score reflects how much of a tree’s maximum

(100%) production of fruit, flower, or leaves was present on the day of the survey. For each species, I calculated a mean monthly score for fruiting and leaf flushing, which I summed each month to generate a value for monthly fruit and leaf availability. Because mature leaf productivity did not vary monthly, I tested the relationship between FGCs , leaf consumption, and young leaf availability.

Hormone Analyses

Fecal samples were opportunistically collected from identified adult females during daily follows, including the 9 adult females in Diana 1 and 12 adult females in

Diana 2. Fecal samples were immediately collected upon defecation and placed in a sealed Ziplock bag. They were labeled by individual, time, and date of collection, homogenized by hand in a Ziplock bag and then stored in a dark bag for no more than 8

192 hours. Samples were then dried in a Coleman stovetop oven for two hours at approximately 100° C and stored in a dry box with silica gel [Foerster and Monfort,

2010]. This method, adapted from Brockman and colleagues [1995; 1996], yielded no storage-related effects in Cercopithecus mitis samples for at least two years, an advantage over ethanol preservation [Hunt and Wasser, 2003; Foerster, 2009]. Samples were then analyzed for concentrations of fecal metabolites of glucocorticoids and progesterone at the Reproductive Endocrinology lab at the Smithsonian Conservation Biology Institute, using enzyme immunoassay protocols following standard lab protocols discussed in detail in Chapters 4 and 5 [Brown et al., 2008].

Statistical Methods

Monthly differences in diet, food availability, rates of social behavior, and fecal glucocorticoid concentrations were assessed using one-way ANOVAs, with Bonferroni’s correction used when making multiple post-hoc comparisons. Relationships between

FGC concentrations and monthly values for fruit availability, fruit consumption, invertebrate consumption, leaf consumption, young leaf availability, rates of affiliation, and rates of aggression, were assessed with Pearson’s R (the entire data set) and

Spearman’s ρ (individual females, due to sample size constraints). FGC concentrations during different reproductive stages were assessed using Kruskal-Wallis test because data were non-normally distributed across the reproductive stages. Finally, I used a univariate linear model to examine the effects of fruit availability and consumption, leaf availability and consumption, invertebrate consumption, aggression, and affiliation on FGC

193 concentrations. All samples were analyzed using SPSS 24.0. Tests were two-tailed and α- levels were set at 0.05.

I analyzed fecal glucocorticoid concentrations in three ways: I pooled all samples for analysis, I analyzed data by groups, and I analyzed individual females’ data. This allowed me to identify large-scale trends in addition to more specific relationships modulated by group or individual-level specificities. To identify possible effects of sample storage time on FGC concentrations, I also examined data across the entire study period, and divided by the field season in which data were collected (July 2013-March

2014; May-August 2015) [Hunt and Wasser, 2003; Lynch et al., 2003]. Though samples were collected at different times, they were analyzed between February and March of

2016. Fecal glucocorticoid concentrations are reported here as relative fluctuations from baseline, µg/g dry fecal weight [Brown et al., 1999]. I excluded two samples that were outliers for corticosterone concentrations (Kalje, 17 Jun 2015, FGC concentration =

0.7996 µg/g dry fecal weight; Candi, 13 August 2015, FGC concentration =0.8657 µg/g dry fecal weight). I used Q-Q plots to visually assess normality of the data sets. FGC concentrations were distributed approximately normally considering all samples; individual samples had a non-normal distribution.

RESULTS

Diana Monkey Feeding Ecology and Food Availability

Data from 2,589 scan samples collected between July 2013 and August 2015 show that the overall Diana monkey diet was 63.5% invertebrates, 32.8% fruit, 3.7% leaves, and 0.5% other material. The pooled Diana monkey diet varied significantly by

194 month in consumption of invertebrates (F(19, 1269)= 4.948, p<0.001) and fruit (F(19,

756)=4.039, p<0.001). There were no significant monthly differences in leaf consumption (F(18, 129)=1.163, p=0.304) (Figure 6.2).

Though there were no significant monthly differences in fruit availability

(F(12,247)=0.373, p=0.972), fruit availability tended to be lower between June and

August (Figure 6.3). There were also no significant monthly differences in the availability of young leaves (F=0.938, p=0.509) (Figure 6.3). The lack of statistical significance here may obscure biological significance. Fruit was readily available year- round, however because Diana monkey diets were not perfectly even, low availability of fruits that were very important to Diana monkey diets could have an impact on foraging behavior and metabolic stress even if other fruit was available. Additionally, because I only sampled 5 trees per species, the productivity of trees on our phenology may not have been representative of the species’ productivity throughout group home ranges.

Social Behavior

There were significant differences in the monthly rates of prosocial, affiliative behavior, including grooming and playing (F(12, 1434)=3.204, p<0.001). A post-hoc comparison using Bonferroni’s correction showed that Diana monkeys engaged in significantly more affiliative behavior during January 2014 than during October 2013, or

June, July, and August 2015 (Figure 6.4). However, there were no significant monthly differences in the rate of aggressive behavior (F(12, 14234)=0.971, p=0.475) (Figure

6.4).

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Fecal Glucocorticoid Concentrations

There were significant differences in Diana monkeys’ mean monthly fecal glucocorticoid concentrations (F(12, 349)=2.216, p=0.01) (Figure 6.5). Posthoc analyses with Bonferroni’s correlation showed that Diana monkeys had significantly higher FGC concentrations during August 2015 than September 2013 but found no other significant differences between months. There were no other significant differences in monthly

FGCs after adjusting the p-value for post-hoc analyses; however, January 2014 and

August 2015 were the months with highest FGC concentrations, with May, June, and July

2015 experiencing elevated FGC concentrations as well. FGCs were lowest during July

2013 and March 2014; however, these were also the months with the smallest sample sizes (N=3 and 8, respectively) and it is possible that a larger sample size would have shown a greater fluctuation from baseline. Samples collected between July 2013-March

2014 had mean fGC concentrations that were significantly lower than samples collected between May-August 2015 (independent samples t-test, t=-2.65, df=345, p=0.008). There were no differences between groups’ mean fecal glucocorticoid concentrations during these periods (Table 6.1, figure 6.6) (2014: independent samples t-tet, t=0.90, df=155, p=0.42. 2015: independent samples t-test: t=-0.52, df=189, p=0.60). Individual females’ fluctuations in fecal glucocorticoid concentrations are pictured in figure 6.7.

Diet, Food Availability, and Fecal Glucocorticoids

I found little evidence supporting the hypothesis that low fruit availability is correlated with elevated FGC concentrations (Table 6.2, Figure 6.8, Figure 6.9).

Individual females’ fluctuations in fecal glucocorticoid concentrations are pictured in

196 figure 6.7; these data were correlated with group data on ecology, diet, and sociality to derive table 6.3. Fruit availability was significantly positively correlated with FGCs for just one of 19 females (Emi), and significantly negatively correlated with FGCs for two of 19 females (Kemi and Pensette) (Figure 6.7, Table 6.3). My results provide limited support for the hypothesis that fruit consumption has an inverse relationship with FGC concentrations. Fruit consumption was weakly, negatively correlated with FGC concentrations, such that Diana monkeys had slightly lower FGC concentrations in months when they are more fruit (Table 6.2, Figure 6.10, Figure 6.11). However, this correlation was driven by data from Diana 2; FGC concentrations for Diana 1 as an entire group were not significantly correlated with monthly fruit consumption. Fruit consumption was significantly negatively correlated with FGC concentrations for 5 of 19 females – four from Diana 2, one from Diana 1 (Agnes, Emi, Fiona, Odji, Pensette;

Figure 6.7, Table 6.3).

Invertebrate consumption was weakly, positively correlated with FGC concentrations such that Diana monkeys have slightly elevated FGC concentrations in months when they eat more invertebrates (Table 6.2, Figure 6.12, Figure 6.13). This relationship is also likely driven by data from Diana 2 as Diana 1 exhibits no significant correlation between invertebrate consumption and FGC concentrations. Invertebrate consumption was significantly positively correlated with FGC concentrations of two females (Agnes, Emi), and significantly negatively correlated with FGC concentrations of two females (Benja, Melo; Figure 6.7, Table 6.3).

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As predicted, I found little evidence suggesting that leaf consumption (Figure

6.14, Figure 6.15) or the availability of young leaves (Figure 6.16, Figure 6.17) were correlated with FGC concentrations (Table 6.2). Leaf consumption was weakly negatively correlated with FGCs of Diana 2 between July 2013-March 2014, but there were no other significant correlations. Leaf consumption was significantly, positively correlated with FGCs of one adult female (Sarah). Young leaf availability was significantly negatively correlated with FGC concentrationss of three individuals (Candi,

Fiona, Sarah), and significantly positively corrected with FGC concentrations of one individual (Figure 6.7, Table 6.3).

Social Behavior and Fecal Glucocorticoids

I found limited support for the hypothesis that higher rates of affiliation decrease

FGC concentrations. Between July 2013-March 2014, Diana 2 had a significant negative correlation between monthly FGC concentrations and monthly rates of affiliation (Table

6.2, Figure 6.18, Figure 6.19). Five females had significant negative correlations between

FGCs and monthly rates of affiliation (Agnes, Cheri, Leah, Melo, Pensette, Figure 6.7,

Table 6.3). I also found limited support for the hypothesis that higher rates of aggression elevate FGC concentrations. Between July 2013-March 2014, Diana 1 had a significant positive correlation between monthly FGC concentrations and monthly rates of aggression (Table 6.2, Figure 6.20, Figure 6.21). Two females exhibited significant negative correlations between FGC concentrations and the monthly rate of aggression

(Agnes, Emi); one female exhibited a significant positive correlation between FGC concentrations and monthly rates of aggression (Candi).

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Reproductive Status and Fecal Glucocorticoids

Reproductive status had a significant effect on fecal glucocorticoid concentrations

(Figure 6.22) (Kruskal-Wallis: p=0.028). Post-hoc analyses showed that females in the late stages of lactation had FGC concentrations that were significantly higher than cycling females (p=0.02) or pregnant females (p=0.05).

Generally, regardless of reproductive status, fGC concentrations were highest between May and August, which may be due to low fruit availability during this period

[Chapter 2]. Data on FGC concentrations for pregnant females were only available from

August-October. Pregnant females had FGC concentrations that were significantly higher in September than August (Figure 6.23.a) (Kruskal-Wallis test: p=0.03). Monthly FGC concentrations did not differ for females in the early stages of lactation, although females in early lactation in January had notably high FGC concentrations (Figure 6.23.b)

(Kruskal-Wallis test: p=0.202). There were significant monthly differences in FGC concentrations for females in the late stages of lactation, with particularly high FGC concentrations between May and August, and again in January (Figure 6.23.c). This may be because of relatively low fruit availabllity between May and August. Females had

FGC concentrations that were significantly higher in May than September (p=0.036) and

March (p=0.041), significantly higher in June than September (p=0.015), November

(p=0.028), December (p=0.036), and March (p=0.031); significantly higher in July than in September (p=0.004), November (p= 0.008), December (p=0.013), February (p=0.017) and March (p=0.015); and significantly higher in August than September (p=0.016),

November (p=0.028), December (p=0.036), and March (p=0.031). Monthly FGC

199 concentrations did not differ significantly by month for cycling females (Figure 6.19.d)

(Kruskal-Wallis test: p=0.22).

Table 6.4 presents the relationship between dietary variables and FGC concentrations of females at different reproductive stages. Pregnant females had significantly higher FGC concentrations in months where they consumed more fruit, and significantly lower FGC concentrations in months with higher availability of young leaves. Females at early stages of lactation had significantly higher FGC concentrations in months when fruit was more readily available and they ate fewer invertebrates.

Females at later stages of lactation had significantly lower FGC concentrations in months when fruit and leaves were more readily available, and they ate more fruit and fewer invertebrates. Cycling females had significantly higher FGC concentrations in months when they ate more invertebrates.

Modeling FGCs, Ecology, Reproduction, and Social Stress

I used a univariate linear model to test the effects of monthly fruit availability, monthly fruit consumption, monthly availability of young leaves, monthly leaf consumption, invertebrate consumption, reproductive status, monthly rate of aggression, and monthly rate of affiliation on FGC concentrations. Considering the entire data set, none of these variables had a significant effect on FGC concentrations; the rate of aggression had a significant effect on FGC concentrations of Diana 1 (F1, 109=6.40, p=

0.01) and reproductive state had a significant effect on FGC concentrations of Diana 2

(F2, 203= 4.21, p= 0.02) (Table 6.5).

DISCUSSION

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Despite demonstrated differences in group dietary composition, groups did not differ significantly in their mean FGC concentrations. FGC concentrations were weakly correlated with a range of variables, including dietary variables, behavioral variables, and reproductive variables. The weak correlations and non-significance of most of these variables in a model are likely in part because of the way I measured the variables I chose: because of small sample sizes for individuals’ behaviors, I correlated individual

FGC concentrations with groups’ monthly rates of behavior/diet. Individual behavioral differences – for example, dietary disparities, personality differences related to proximity and time spent grooming or aggression – were subsumed into group data, which removes some of their explanatory power. I do not have an adequate sample size to examine inter- individual differences. However, individual trends can still be instructive. Variations in most females’ FGC concentrations were not correlated with ecological or behavioral variables, suggesting that fluctuations in diet, food availability, affiliation, and aggression, are not explanatory. This corroborates the findings of my univariate model, which showed that few variables had significant explanatory power in terms of fecal glucocorticoid concentrations.

Small sample sizes during pregnancy and early lactation make it difficult to draw strong conclusions about the relationship between reproductive status and fecal glucocorticoids. However, one intriguing result suggests that FGC concentrations are significantly correlated with fruit availability during pregnancy, such that pregnant females have higher FGCs at periods when fruit availability is highest. In blue monkeys

(Cercopithecus mitis), there was no independent effect of reproductive status on FGC

201 concentrations, suggesting that the effects of fetal activation of the HPA-axis during late pregnancy was overwhelmed by environmental stress [Mastorakos and Ilias, 2003;

Foerster and Monfort, 2010]. During this study, pregnant females had significantly lower

FGC concentrations than females at other reproductive stages (Figure 6.17); a puzzling result because of that fetal activation of the HPA-axis. However, the relationship between fruit availability and FGC elevation may not be causal; it may be that Diana monkeys experience elevated FGC concentrations at the end of their pregnancies (relative to the beginning of their pregnancies, a period for which I have no samples), which are timed for periods of increased fruit availability. Elevated FGC concentrations during lactation may reflect both the energetic stress of lactation, and the social stress of caring for infants and young juveniles at risk of infanticide and predation [e.g., Weingrill et al., 2004;

Beehner et al., 2005; Engh et al., 2006; Kane and Gnepa, 2016].

Diana Monkeys and the Reactive Scope of the Stress Response

Despite these caveats, I argue that my findings reflect the fact that Diana monkeys in the Taï Forest do not experience significant stress or the negative consequences of chronically elevated stress. Elevated FGCs are expected in response to normal strains of day-to-day life: competition within and between groups, reproduction, changes in food availability reflective of a seasonal environment, metabolic processes [Beehner and

Bergman, 2017]. Considering vertebrates broadly, most organisms experience no net decrease in fitness from stress responses because the activation of the HPA axis is an adaptive response that enables mobilization and metabolism of glucose (among other things) in response to strains enacted on a regular basis [Wingfield, 2013; Beehner and

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Bergman, 2017]. In fact, “Organisms should exhibit extensive variation in GCs that correspond to circadian variation, circannual variation, and different developmental and reproductive stages” [Beehner and Bergman, 2017: 4].

This has been conceptualized as a “reactive scope” model of the stress response

(Figure 6.24) [Romero et al., 2009]. Seasonal and circadian variation in GC secretion is normal, and the range of these secretions should be relatively predictable from year to year in the process of maintaining “predictive homeostasis” [Romero et al., 2009]. The range of GC concentrations individuals secrete in response to stressors such as reproductive events (e.g., pregnancy, lactation) or predation attempts should also be relatively predicable (“Reactive homeostasis”). Importantly, the range of reactive homeostasis falls within the normal reactive scope of a healthy organism, as reactive homeostasis is an adaptive response that allows organisms to cope with “normal” strains of life. Perturbations that push organisms outside of their range of reactive homeostasis are pathological, and when they are chronic, they can eventually lead to a suite of diseases and syndromes [Selye 1936, 1971; Sapolsky, 2004].

My findings suggest that Diana monkeys do not experience chronic or pathological levels of stress as diets vary in response to fluctuating food availability – even when females are under greater metabolic stress during energetically-expensive periods of reproduction, or under greater amounts of social stress. In fact, I argue that none of these stressors push Diana monkeys outside of their range of “predictive homeostasis.” Furthermore, none of the acute stressors I observed – intergroup encounters, predator responses – are unusual or aberrant considering the life of wild

203 primates. Even predation attempts may not incur a stress response beyond an organism’s normal reactive scope [Romero et al., 2009]. Successfully evading predation enhances fitness; mobilizing a stress response quickly and effectively to escape a predator is adaptive. Because of this, I suspect that all the fecal samples I collected, and the range of

FGC concentrations they exhibit, fall well within the normative “reactive scope” of Diana monkey stress responses [Romero et al., 2009]. The exception to this was the male transfer/infanticide attempt/chimpanzee predation attempt I observed on October 15,

2013, which was almost certainly an aberrant event that may have briefly perturbed

Diana monkeys beyond their reactive scope [Kane and Gnepa, 2016]. Unfortunately fecal samples were very difficult to collect the day of and immediately following that event because the group was unusually high in the canopy.

This has potentially significant conservation implications. If Diana monkeys in the Taï Forest are indeed well within their reactive scope for homeostasis, analysis of flucutations in other Diana monkey populations’ fecal glucocorticoid concentrations could identify populations that are unhealthily stressed. Because fecal samples offer a variety of relevant data, such as parasite loads and evidence of extreme metabolic stress, collection and analysis of primate feces offer many complementary lines of evidence to understanding population health and conservation status [Cherel et al., 2005; Gillespie,

2006]. These data could inform conservation and management strategies, such as targeted planting of important fruit trees or mitigating poaching. Incorporating conservation physiology into future research, especially on populations of Diana monkeys and other endangered primates facing a changing and contested environment could help direct

204 resources to areas where they may have the greatest impact on preserving primate populations [Cooke et al., 2013]. In particular, because this is a non-invasive strategy for monitoring population health, it could be widely applied even in already-endangered populations.

An important next step before using this research to inform conservation strategy is to examine glucocorticoid concentrations themselves rather than their fluctuations.

While it is true that Diana monkey FGC concenstrations did not vary dramatically, it is possible that concentrations were elevated to begin with. In other words, Diana monkeys in the Taï Forest may be coping with very high fecal glucocorticoid concentrations by having constantly elevated FGCs that do not vary very much. This would indicate that populations in the relatively pristine and abundant Taï National Park are already pushed to their limit in terms of maintaining a normal reactive scope for coping with annual stressors, and perhaps explain why Diana monkeys are so rare outside of primary forest

[Oates et al., 2016]. However, these findings complement recent work reframing elevated glucocorticoid concentrations by considering fluctuations of fecal glucocorticoids in the context of the normal scope of individuals’ responses to regularly-experienced stressors – circadian, intra-annual, acute. Recognizing the adaptive potential of glucocorticoids, and their role maintaining homeostasis, opens the way for a new set of research questions that treat fluctuations in glucocorticoids as more than simply indicative of a pathological and detrimental state [Romero et al., 2009; Beehner and Bergman, 2017].

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TABLES

Entire study period: Dataset 1: Dataset 2: July 2013-August 2015 July 2013-March May 2015-August 2015 2014 Overall 0.033 μg/g dry feces 0.016 μg/g dry feces 0.047 μg/g dry feces (SD: 0.112) (SD: 0.092) (SD: 0.125) Diana 1 0.036 μg/g dry feces 0.024 μg/g dry feces 0.044 μg/g dry feces (SD: 0.101) (SD: 0.117) (SD: 0.087) Diana 2 0.032 μg/g dry feces 0.011 μg/g dry feces 0.049 μg/g dry feces (SD: 0.118) (SD: 0.077) (SD: 0.143) 20. Table 6.1. Mean FGC concentrations of both groups and the entire sample across the entire study period, between July 2013-March 2014, and between May-August 2015.

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Correlation between FGCs and: Entire study period July 2013-March 2014 May 2015-August 2015 Fruit availability All R= -0.05, p= 0.31 R= 0.13, p= 0.10 R= 0.03, p= 0.72 D1 R= 0.04, p= 0.66 R= -0.25, p= 0.07 R= 0.06, p= 0.96 D2 R= -0.06, p= 0.38 R= 0.08, p= 0.45 R= 0.05, p= 0.62 Fruit consumption All R= -0.12, p= 0.03 R= 0.10, p= 0.22 R= -0.6, p= 0.41 D1 R= -0.09, p= 0.32 R= 0.24, p=0.09 R= -0.11, p= 0.37 D2 R= -0.13, p= 0.05 R= 0.02, p= 0.87 R= -0.04, p= 0.68

Leaf Consumption All R= -0.06, p= 0.26 R= -0.14, p= 0.07 R= -0.10, p= 0.16 D1 R= -0.08, p= 0.40 R= -0.03, p= 0.83 R= -0.12, p= 0.32 D2 R= -0.04, p= 0.58 R= -0.20, p= 0.04 R= -0.11, p= 0.21

Young leaf availability All R= -0.07, p= 0.17 R= -0.10, p= 0.21 R= 0.07, p=0.35 D1 R= -0.15, p= 0.10 R= -0.25, p= - 0.07 R= 0.03, p= 0.79 D2 R= -0.02, p= 0.78 R= 0.04, p= 0.70 R= 0.09, p= 0.32

Invertebrate consumption All R= 0.14, p= 0.01 R= -0.06, p= 0.47 R= 0.12, p= 0.09 D1 R= 0.08, p= 0.37 R= -0.22, p= 0.12 R= 0.11, p= 0.37 D2 R= 0.16, p= 0.01 R= 0.05, p= 0.62 R= 0.14, p= 0.14

Affiliation All R= 0.01, p= 0.91 R= -0.25, p= 0.002 R= -0.08, p= 0.59 D1 R= 0.02, p= 0.80 R= 0.17, p= 0.24 R=-0.04, p= 0.75 D2 R= -0.06, p= 0.34 R= -0.24, p= 0.01 R= -0.12, p= 0.21 Aggression All R= -0.05, p= 0.36 R= -0.3, p= 0.74 R= -0.08, p= 0.25 D1 R= 0.07, p= 0.45 R= 0.28, p= 0.04 R= -0.05, p= 0.68 D2 R= 0.02, p= 0.76 R= 0.00, p= 0.97 R= -0.11, p= 0.26 Sample size All N= 348 N= 157 N= 191 D1 N= 123 N= 52 N= 71 D2 N= 225 N= 105 N= 120 21. Table 6.2. Pearson’s correlation coefficients (R) between fecal glucocorticoid concentrations and monthly fruit availability, fruit consumption, leaf consumption, leaf availability invertebrate consumption, rates of affiliation, rates of aggression across the entire study period, from July 2013-March 2014, and from May 2015-August 2015, pooling and separating group data.

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Monthly Monthly proportion of: Monthly Monthly fruit leaf rate of: Female availability Fruit Inverts Leaves availability Affilation Agonism Agnes ρ= 0.50 ρ = -0.81 ρ= 0.86 ρ= -0.50 ρ= 0.50 ρ= -0.86 ρ= -0.86 N=8 p= 0.21 p= 0.02 p= 0.01 p= 0.21 p= 0.21 p= 0.01 p= 0.01 D2 Benja ρ= 0.16 ρ= 0.29 ρ= -0.29 ρ= 0.15 ρ= -0.45 ρ= -0.02 ρ= 0.11 N=17 p= 0.53 p= 0.26 p=0.03 p= 0.56 p= 0.07 p=0.95 p= 0.68 D2 Candi ρ= -0.15 ρ= -0.35 ρ= 0.28 ρ= 0.10 ρ= -0.54 ρ= -0.23 ρ= 0.56 N=21 p= 0.52 p= 0.27 p= 0.23 p= 0.67 p= 0.01 p= 0.31 p= 0.01 D1 Cheri ρ= -0.16 ρ= -0.15 ρ= 0.06 ρ= 0.26 ρ= 0.11 ρ= -0.45 ρ= -0.27 N=28 p= 0.41 p= 0.44 p= 0.75 p= 0.17 p= 0.58 p= 0.02 p= 0.17 D2 Emi ρ= 0.68 ρ= -0.68 ρ= 0.70 ρ= -0.16 ρ= 0.73 ρ= -0.49 ρ= -0.70 N=10 p= 0.03 p=0.03 p= 0.03 p= 0.66 p= 0.02 p= 0.15 p= 0.03 D2 Eva ρ= 0.18 ρ= -0.17 ρ= 0.12 ρ= -0.09 ρ= -0.12 ρ= -0.04 ρ= 0.07 N=25 p= 0.39 p= 0.41 p= 0.56 p= 0.66 p= 0.56 p= 0.84 p= 0.75 D2 Fiona ρ= 0.27 ρ= -0.44 ρ= 0.40 ρ= 0.27 ρ= -0.56 ρ= 0.02 ρ= 0.01 N=21 p= 0.23 p= 0.05 p= 0.08 p= 0.24 p= 0.01 p= 0.94 p= 0.97 D2 Ilka ρ= 0.09 ρ= -0.21 ρ= 0.15 ρ= 0.03 ρ= -0.09 ρ= 0.22 ρ= 0.15 N=22 p= 0.70 p= 0.34 p= 0.52 p= 0.89 p= 0.68 p= 0.34 p= 0.50 D2 Julie ρ= 0.46 ρ= -0.46 ρ= 0.46 ρ= -0.27 ρ= 0.58 ρ= -0.17 ρ= 0.27 N=8 p= 0.26 p= 0.26 p= 0.26 p= 0.51 p= 0.13 p= 0.69 p= 0.41 D1 Kalje ρ= -0.11 ρ= -0.34 ρ= 0.32 ρ= -0.12 ρ= -0.12 ρ= -0.04 ρ= 0.05 N=28 p= 0.59 p= 0.07 p= 0.10 p= 0.37 p= 0.55 p= 0.86 p= 0.82 D1 Kemi ρ= -0.65 ρ= -0.41 ρ= 0.34 ρ= 0.35 ρ= -0.10 ρ= -0.48 ρ= -0.13 N=11 p= 0.03 p= 0.21 p= 0.31 p= 0.29 p= 0.76 p= 0.13 p= 0.71 D1 Leah ρ= -0.46 ρ= -0.50 ρ= 0.48 ρ= 0.53 ρ= -0.25 ρ= -0.58 ρ= -0.05 N=12 p= 0.13 p= 0.10 p= 0.12 p= 0.08 p= 0.44 p= 0.05 p= 0.88 D2 Melo ρ= -0.21 ρ= -0.16 ρ= -0.56 ρ= -0.13 ρ= -0.04 ρ= -0.55 ρ= -0.32 N=21 p= 0.37 p= 0.48 p= 0.01 p= 0.57 p= 0.85 p= 0.01 p= 0.16 D2 Nina ρ= -0.38 ρ= -0.18 ρ= 0.29 ρ= -0.33 ρ= 0.43 ρ= 0.17 ρ= -0.08 N=14 p= 0.18 p= 0.55 p= 0.31 p= 0.24 p= 0.13 p= 0.57 p= 0.77 D2 Table 6.3 Continues 22. Table 6.3. Spearman’s correlation coefficients (ρ) of the fecal glucocorticoid concentrations of 19 adult females, and monthly fruit availability, fruit consumption, invertebrate consumption, leaf consumption, leaf availability, rates of affiliation, and rates of agonism.

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Table 6.3 Continued.

Nora ρ= -0.25 ρ= -0.20 ρ= 0.18 ρ= 0.14 ρ= -0.42 ρ= -0.30 ρ= 0.06 N=33 p= 0.15 p= 0.26 p= 0.32 p= 0.42 p= 0.81 p= 0.09 p= 0.74 D2 Odji ρ= -0.33 ρ= -0.76 ρ= 0.76 ρ= -0.26 ρ= 0.30 ρ= -0.47 ρ= 0.29 N=7 p= 0.47 p= 0.05 p= 0.06 p= 0.58 p= 0.52 p= 0.28 p= 0.53 D1 Pensette ρ= -0.61 ρ= -0.81 ρ= 0.49 ρ= 0.51 ρ= -0.59 ρ= -0.65 ρ= 0.04 N=12 p= 0.03 p= 0.03 p= 0.10 p= 0.09 p= 0.10 p= 0.02 p= 0.91 D2 Sarah ρ= 0.17 ρ= -0.16 ρ= -0.09 ρ= 0.33 ρ= -0.37 ρ= -0.12 ρ= 0.15 N=37 p= 0.32 p= 0.36 p= 0.59 p= 0.05 p= 0.02 p= 0.47 p= 0.38 D2 Sonia ρ= 0.23 ρ= 0.18 ρ= 0.50 ρ= -0.44 ρ= 0.36 ρ= -0.50 ρ= -0.50 N=11 p= 0.49 p= 0.59 p= 0.12 p= 0.18 p= 0.28 p= 0.12 p= 0.12 D2

Female Reproductive Status: Correlation Pregnant Early Lactation Late Lactation Cycling between FGCs and: Fruit ρ= 0.82, p=0.007 ρ= 0.44, p= 0.12 ρ= -0.15, p=0.02 ρ= 0.03, p= 0.83 availability

Fruit ρ= -0.38, p= 0.32 ρ= 0.56, p= 0.04 ρ= -0.22, p<0.001 ρ= -0.17, p= 0.15 consumption

Invertebrate ρ= 0.21, p= 0.60 ρ= -0.61, p= 0.02 ρ= 0.17, p= 0.007 ρ= 0.39, p= 0.001 consumption

Leaf ρ= 0.38, p= 0.32 ρ= 0.31, p= 0.28 ρ= 0.06, p= 0.30 ρ= -0.16, p= 0.20 consumption

Young leaf ρ= -0.86, p= 0.003 ρ= -0.28, p= 0.34 ρ= -0.15, p= 0.02 ρ= 0.15, p= 0.22 availability

Sample size N=9 N=14 N=258 N=69

23. Table 6.4. Spearman’s correlation coefficients (ρ) between females’ fecal glucocorticoid concentrations during different reproductive stages and monthly fruit availability, fruit consumption, invertebrate consumption, leaf consumption, and leaf availability.

209

Independent Overall Diana 1 Diana 2 Variable Individual ID F3, 320 = 1.62, p= 0.19 F5, 109=1.04, p= 0.40 F12, 203= 1.59, p= 0.10 (random effect) Reproductive state F19, 320= 0.93, p= 0.55 F2, 109=0.84, p= 0.43 F2, 203= 4.21, p= 0.02 (fixed effect) Fruit F1, 320= 0.95, p= 0.33 F1, 109=2.47, p= 0.12 F1, 203= 0.30, p= 0.58 availability Fruit F1, 320= 1.25, p= 0.26 F1, 109=2.51, p= 0.12 F1, 203= 0.02, p= 0.88 consumption Invertebrate F1, 320= 0.01, p= 0.91 F1, 109=2.19, p= 0.14 F1, 203= 0.09, p= 0.77 consumption Leaf F1, 320= 1.25, p= 0.27 F1, 109=0.01, p= 0.94 F1, 203= 0.03, p= 0.88 consumption Leaf F1, 320= 0.03, p= 0.87 F1, 109=0.30 p= 0.58 F1, 203= 0.20, p= 0.66 availability Rate of F1, 320= 0.01, p= 0.92 F1, 109=6.40, p= 0.01 F1, 203= 0.04, p= 0.84 aggression Rate of F1, 320= 0.01, p= 0.97 F1, 109=0.26, p= 0.61 F1, 203= 0.12, p= 0.73 affiliation 24. Table 6.5. Factors in a univariate general linear model testing the main effects of ecological and behavioral variables on FGC concentrations for the pooled data set, Diana 1, and Diana 2.

210

FIGURES

31. Figure 6.1. Predicted relationships between independent variables and Diana monkeys’ fecal glucocorticoid concentrations.

211

90%

80%

70%

60%

50%

40%

30%

20%

10%

Fruit Invertebrates Leaves Other

32. Figure 6.2. The relative contributions of fruit, invertebrates, leaves, and other material to the overall Diana monkey diet from July 2013-March 2013, and May 2015-August 2015.

212

0.35

0.30

0.25

0.20

0.15

0.10

0.05 Mean Monthly Score Phenological Mean Monthly

0.00 7 8 9 10 11 12 1 2 3 5 6 7 8 2013 2013 2013 2013 2013 2013 2014 2014 2014 2015 2015 2015 2015 Young Leaf Availability Fruit Availability

33. Figure 6.3. Mean monthly availability of fruit and leaves in the home ranges of two Diana monkey groups between July 2013-March 2014, and May-August 2015

213

1% Monthly Rtae Behavior of Monthly

0% 7 8 9 10 11 12 1 2 3 5 6 7 8 2013 2013 2013 2013 2013 2013 2014 2014 2014 2015 2015 2015 2015 Affiliation Aggression

34. Figure 6.4. Monthly rates of affiliation and aggression exhibited by Diana monkeysbetween July 2013-March 2014, and May-August, 2015

214

N= 3 25 26 17 21 17 20 20 8 32 64 55 42

35. Figure 6.5. Diana monkeys’ mean monthly fluctuation from their baseline fecal glucocorticoid concentrations. August 2015 differed significantly from September 2013 (p=0.042, 95%CI [0.002-0.221].

215

36. Figure 6.6. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) of Diana groups 1 and 2, during the first (July 2013-March 2014) and second (May-August 2015) field seasons.

216

Benja Aug. 2013--March 2014 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 -0.05Jun-13 Aug-13 Oct-13 Nov-13 Jan-14 Mar-14 Apr-14 -0.10 -0.15

Benja May-August 2015 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 May-15 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 Aug-15 -0.05 -0.10

Figure 6.7 continues

37. Figure 6.7 Scatterplots of fecal glucocorticoid concentrations for adult females with at least 8 fecal samples collected during this study period. This includes 6 females in Diana 1 (a-f) and Y females in Diana 2 (g-s).

217

Figure 6.7 Continued b.

Candi Aug. 2013-Mar. 2014 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 Aug-13 Oct-13 Nov-13 Jan-14 Mar-14 Apr-14 -0.05 -0.10

Candi May-Aug. 2015 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 Apr-15 May-15 Jun-15 Jun-15 Jul-15 Aug-15 Aug-15 -0.05 -0.10

Figure 6.7 continues

218

Figure 6.7 continues c.

Julie May-Aug. 2015 0.20

0.15

0.10

0.05

0.00 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 Aug-15 -0.05

-0.10

-0.15

Kemi Aug. 2013-Mar. 2014 0.02

0.01

0.00 Sep-13 Oct-13 Nov-13 Nov-13 Dec-13 Jan-14 Jan-14 Feb-14 Mar-14 Mar-14 -0.01

-0.02

-0.03

-0.04

Figure 6.7 continues

219

Figure 6.7 continued e.

Kalje Aug. 2013-Mar. 2014 0.7000

0.6000

0.5000

0.4000

0.3000

0.2000

0.1000

0.0000 Jun-13 Aug-13 Oct-13 Nov-13 Jan-14 Mar-14 Apr-14 -0.1000

Kalje May-Aug. 2015 0.30

0.25

0.20

0.15

0.10

0.05

0.00 May-15 May-15 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 Aug-15 -0.05

Figure 6.7 continues

220

Figure 6.7 continued f.

Nora Aug. 2013-Mar. 2014 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 -0.05Aug-13 Oct-13 Nov-13 Jan-14 Mar-14 Apr-14 -0.10

Nora May-Aug. 2015 0.16 0.14 0.12 0.10 0.08 0.06 0.04 0.02 0.00 -0.02May-15 May-15 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 Aug-15 -0.04 -0.06

Figure 6.7 continues

221

Figure 6.7 continued g.

Agnes May-Aug. 2015 0.40

0.30

0.20

0.10

0.00 May-15 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 Aug-15 -0.10

-0.20

-0.30

Emi May-Aug. 2015 0.20

0.15

0.10

0.05

0.00 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 Aug-15 -0.05

-0.10

-0.15

Figure 6.7 continues

222

Figure 6.7 continued i.

Cheri Jul. 2013-Mar. 2014 0.10 0.08 0.06 0.04 0.02 0.00 Jun-13 Aug-13 Oct-13 Nov-13 Jan-14 Mar-14 Apr-14 -0.02 -0.04 -0.06 -0.08

Cheri May-Aug. 2015 0.60

0.50

0.40

0.30

0.20

0.10

0.00 May-15 Jun-15 Jun-15 Jul-15 Aug-15 Aug-15 -0.10

Figure 6.7 continues

223

Figure 6.7 continued j.

Eva Jul. 2013-Mar. 2014 0.50

0.40

0.30

0.20

0.10

0.00 Jun-13 Aug-13 Oct-13 Nov-13 Jan-14 Mar-14 -0.10

Eva May-Aug. 2015 0.20

0.15

0.10

0.05

0.00 May-15 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 Aug-15 -0.05

-0.10

Figure 6.7 continues

224

Figure 6.7 continued k.

Fiona Jul. 2013-Mar. 2014 0.12

0.10

0.08

0.06

0.04

0.02

0.00 Jun-13 Aug-13 Oct-13 Nov-13 Jan-14 Mar-14 -0.02

-0.04

Fiona May-Aug. 2015 0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 Aug-15 -0.05

Figure 6.7 continues

225

Figure 6.7 continued l.

Ilka Jul. 2013-Mar. 2014 0.15

0.10

0.05

0.00 Jun-13 Aug-13 Oct-13 Nov-13 Jan-14 Mar-14 Apr-14

-0.05

-0.10

Ilka May-Aug. 2015 0.30

0.25

0.20

0.15

0.10

0.05

0.00 May-15 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 -0.05

Figure 6.7 continues

226

Figure 6.7 continued m.

Leah May-Aug. 2015 0.70

0.60

0.50

0.40

0.30

0.20

0.10

0.00 May-15 May-15 May-15 Jun-15 Jun-15 Jun-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 -0.10

Sonia May-Aug. 2015 0.30 0.25 0.20 0.15 0.10 0.05 0.00 -0.05May-15 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 Aug-15 -0.10 -0.15 -0.20

Figure 6.7 continues

227

Figure 6.7 continued o.

Melo Jul. 2013-Mar. 2014 0.01

0.01

0.00 Jun-13 Aug-13 Oct-13 Nov-13 Jan-14 Mar-14 Apr-14 -0.01

-0.01

-0.02

-0.03

Melo May-Aug. 2015 0.60

0.50

0.40

0.30

0.20

0.10

0.00 May-15 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 Aug-15 -0.10

Figure 6.7 ontinues

228

Figure 6.7 continued p.

Nina Jul. 2013-Mar. 2014 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 -0.05Jun-13 Aug-13 Oct-13 Nov-13 Jan-14 Mar-14 Apr-14 -0.10

Nina May-Aug. 2015 0.12

0.10

0.08

0.06

0.04

0.02

0.00 Apr-15 May-15 May-15 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 -0.02

-0.04

Figure 6.7 continues

229

Figure 6.7 continued q.

Pensette Aug. 2013-Mar. 2014 0.00 Aug-13 Sep-13 Sep-13 Oct-13 Nov-13 Nov-13 Dec-13 Jan-14 Jan-14 Feb-14 -0.01

-0.02

-0.03

-0.04

-0.05

-0.06

Pensette May-Aug. 2015 0.10

0.08

0.06

0.04

0.02

0.00 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 Aug-15 -0.02

Figure 6.7 continues

230

Figure 6.7 continued r.

Sarah Jul. 2013-Mar. 2014 0.45 0.40 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 -0.05May-13 Jun-13 Aug-13 Oct-13 Nov-13 Jan-14 Mar-14 -0.10

Sarah May-Aug. 2015 0.25

0.20

0.15

0.10

0.05

0.00 May-15 May-15 Jun-15 Jun-15 Jun-15 Jul-15 Jul-15 Jul-15 Aug-15 Aug-15 -0.05

231

Fecal sample N= 5 2 7 10 8 10 7 3

Figure 6.8 Continues 38. Figure 6.8. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly fruit availability of Diana 1 from August 2013-March 2014 and May-August 2015.

232

Figure 6.8 Continued

233

Figure 6.9 Continues

39. Figure 6.9. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly fruit availability of Diana 2 between July 2013-March 2014, and May 2015-August 2015.

234

Figure 6.9 Continued

235

Fecal sample N= 5 2 7 10 8 10 7 3

Figure 6.10 Continues

40. Figure 6.10. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly fruit consumption of Diana 1 from August 2013-March 2014 and May-August 2015.

236

Figure 6.10 Continued

237

Figure 6.11 Continues 41. Figure 6.11. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly fruit consumption of Diana 2 from July 2013-March 2014, and May-August 2015.

238

Figure 6.11 Continued.

239

Fecal sample N= 5 2 7 10 8 10 7 3

Figure 6.12 Continues 42. Figure 6.12. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly invertebrate consumption of Diana 1 from August 2013-March 2014 and May-August 2015.

240

Figure 6.12 Continued

Fecal sample N= 10 30 18 15

241

Fecal sample N= 3 20 24 10 11 9 10 13 5

Figure 6.13 Continues 43. Figure 6.13. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly invertebrate consumption of Diana 2 from July 2013-March 2014 and May-August 2015.

242

Figure 6.13 Continued

243

Fecal sample N= 5 2 7 10 8 10 7 3

Figure 6.14 Continues 44. Figure 6.14. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly leaf consumption of Diana 1 from August 2013-March 2014 and May-August 2015.

244

Figure 6.14 Continued

Fecal sample N= 10 30 18 15

245

Fecal sample N= 3 20 24 10 11 9 10 13 5

Figure 6.15 Continues 45. Figure 6.15. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly leaf consumption of Diana 2 from July 2013-March 2014 and May-August 2015.

246

Figure 6.15 Continued

Fecal sample N= 22 34 37 27

247

Fecal sample N= 5 2 7 10 8 10 7 3

Figure 6.16 Continues 46. Figure 6.16. Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly young leaf availability of Diana 1 from August 2013-March 2014 and May-August 2015.

248

Figure 6.16 Continued

Fecal sample N= 10 30 18 15

249

Fecal sample N= 3 20 24 10 11 9 10 13 5

Figure 6.17 Continues 47. Figure 6.17 Mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly leaf availability of Diana 2 from July 2013-March 2014 and May- August 2015.

250

Figure 6.17 Continued

251

Fecal sample N= 5 2 7 10 8 10 7 3

Figure 6.18 Continues 48. Figure 6.18. Diana 1’s mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly rate of affiliation from August 2013-March 2014 and May- August 2015.

252

Figure 6.18 Continued

Fecal sample N= 10 30 18 15

253

Fecal sample N= 3 20 24 10 11 9 10 13 5

Figure 6.19 Continues 49. Figure 6.19. Diana 2’s mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly rate of affiliation from August 2013-March 2014 and May- August 2015.

254

Figure 6.19 Continued

255

Fecal sample N= 5 2 7 10 8 10 7 3

Figure 6.20 Continues 50. Figure 6.20. Diana 1’s mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly rate of aggression from August 2013-March 2014 and May- August 2015.

256

Figure 6.20 Continued

Fecal sample N= 10 30 18 15

257

Fecal sample N= 3 20 24 10 11 9 10 13 5

Figure 6.21 Continues 51. Figure 6.21. Diana 2’s mean FGC concentrations (μg/g fecal dry weight; difference from baseline) and monthly rate of aggression from August 2013-March 2014 and May- August 2015.

258

Figure 6.21 Continued

259

52. Figure 6.22. Mean fecal glucocorticoid concentrations during different reproductive stages.

260 a.

Figure 6.23 Continues 53. Figure 6.23. Mean monthly FGC concentrations during (a) pregnancy, (b) early lactation, (c) late lactation, and (d) cycling.

261

Figure 6.23 Continued b.

Figure 6.23 Continues

262

Figure 6.23 Continued c.

Figure 6.23 Continues

263

Figure 6.23 Continued d.

264

Figure 18. Homeostatic overload Infanticide attempt

Reactive Homeostasis Chimpanzee Low fruit present Intergroup availability

encounter

Pregnancy

Circadian variation

Fecal Glucocorticoids Fecal FGC concentrations Predictive Homeostasis

Time

54. Figure 6.24. The reactive scope model of the Diana monkey stress response, indicating the normal range of fluctuations in physiological responses to stress (“Predictive Homeostasis”) and the impact of stressors such as the presence of predators, reproductive status, fluctuations in food availability, and intergroup encounters (Adapted from Romero et al., 2009).

265

REFERENCES

Altmann JA. 1974. Observational study of behavior: sampling methods. Behaviour 49: 227-267.

Anderson DP. 2001. Tree phenology and distribution, and their relation to chimpanzee social ecology in the Taï National Park, Côte D’Ivoire. PhD Dissertation: University of Wisconsin, Madison.

Anderson DP, Nordheim EV, Moermond TC, Gone Bi ZB, and Boesch C. 2005. Factors influencing tree phenology in Taï National Park, Côte d’Ivoire. Biotropica 37(4): 631-640.

Beehner JC, Bergman TJ, Cheney DL, Seyfarth RM, Whitten PL. 2005. The effect of new alpha males on female stress in free-ranging baboons. Animal Behaviour 69: 1211-1221.

Brockman DK, Whitten PL. 1996. Reproduction in free-ranging Propithecus verreauxi: estrus and the relationship between multiple partner matings and fertizilation. American Journal of Physical Anthropology 100: 47-69.

Brown J, Walker S, Steinman B. 2008. Endocrine Manual for Reproductive Assessment of Domestic and Non-Domestic Species. Front Royal, VA: Smithsonian’s National Zoological Park.

Bshary R, Noë R. 1997a. Anti-predation behavior of red colobus monkeys in the presence of chimpanzees. Behavioral Ecology and Sociobiology 41: 321-333. Butynski TM. 1988. Guenon birth seasons and correlates with rainfall and food. In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. New York: Cambridge University Press. 284-322.

266

Buzzard PJ. 2004. Interspecific competition among Cercopithecus campbelli, C. petaurista, and C. diana at Taï Forest, Côte d’Ivoire. PhD Dissertation: Columbia University. Buzzard PJ. 2006. Ecological partitioning of Cercopithecus campbelli, C. petaurista, and C. diana in the Taï Forest. International Journal of Primatology 27: 529-558. Buzzard PJ. 2010. Polyspecific associations of Cercopithecus campbelli and C. petaurista with C. diana: what are the costs and benefits? Primates 51: 307-314. Buzzard PJ, Eckardt W. 2007. The social systems of the guenons. In, McGraw WS, Zuberbühler K, Noë R, eds. Monkeys of the Taï Forest: An African Primate Community. Cambridge: Cambridge University Press. 51-71. Chapman CA, Wrangham RW, Chapman LJ. 1994. Indices of habitat-wide fruit abundance in tropical forests. Biotropica 26: 160-171. Cherel Y, Hobson KA, Bailleul F, Groscolas R. 2005. Nutrition, physiology, and stable isotopes: new information from fasting and molting penguins. Ecology 86: 2881- 2888.

Emery Thompson M, Knott CD. 2008. Urinary C-peptide of insulin as a non-invasive marker of energy balance in wild orangutans. Hormones and Behavior 53: 526-535.

Eckardt W, Zuberbühler K. 2004. Cooperation and competition in two forest monkeys. Behavioral Ecology 15: 400-411. Engh AL, Beehner JC, Bergman TJ, Whitten PL, Hoffmeier RR, Seyfarth RM, Cheney DL. 2006. Female hierarchy instability, male immigration, and infanticide increase glucocorticoid levels in female chacma baboons. Animal Behaviour 71: 1227-1237.

Foerster S, Cords M, Monfort SL. 2012. Seasonal energetic stress in a tropical forest primate: proximate causes and evolutionary implications. PLoS ONE 7(11): e50108.

267

Foerster S, Monfort SL. 2010. Fecal glucocorticoids as indicators of metabolic stress in female Sykes’ monkeys (Cercopithecus mitis albogularis). Hormones and Behavior 58: 685-697.

Gillespie TR. 2006. Noninvasive assessment of gastrointestinal parasite infections in free-ranging primates. International Journal of Primatology 27: 1129-1143.

Hill CM. 1994. The role of female Diana monkeys, Cercopithecus diana, in territorial defence. Animal Behaviour 47: 425-431. Hunt KE, Wasser SK. 2003. Effects of long-term preservation methods on fecal glucocorticoid concentrations of grizzly bear and African elephant. Physiological and Biochemical Zoology 76: 918-928.

Kane EE, Gnepa F. 2016. An infanticide attempt after male takeover in Diana monkeys (Cercopithecus diana diana) in Taï, Côte d’Ivoire. African Primates 11: 37-40.

Mastorakos G, Ilias I. 2003. Maternal and fetal hypothalamic-pituitary-adrenal axes during pregnancy and postpartum. Annals of the New York Academy of Sciences 997: 136-149.

McGraw WS, Zuberbuhler K. 2008. Socioecology, predation, and cognition in a community of West African monkeys. Evolutionary Anthropology 17: 254-266.

Noë R, Bshary R. 1997. The formation of red colobus-Diana monkey associations under predation pressure from chimpanzees. Proceedings of the Royal Society of Biological Sciences 264: 253-259. van Noordwijk MA. 2011. From maternal investment to lifetime maternal care. In, Mitani JC, Call J, Kappeler PM, Palombit RA, Silk JB, eds. The Evolution of Primate Societies. Chicago: Chicago University Press. 321-342.

Oates JF, Gippoliti S, Groves CP. 2016. Cercopithecus diana. The IUCN Red List of Threatened Species 2016: e.T425A92376689. Polansky L, Boesch C. 2013. Long-term changes in fruit phenology in a West African lowland tropical rain forest are not explained by rainfall. Biotropica 45: 434-440.

Pride RE. 2005. Optimal group size and seasonal stress in ring-tailed lemurs (Lemur catta). Behavioral Ecology 16: 550-560.

Romero LM, Dickens MJ, Cry NE. 2009. The Reactive Scope Model – a new model integrating homeostasis, allostasis, and stress. Hormones and behavior: 55: 375-389.

268

Sapolsky RM, Romero LM, Munck AU. 2000. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocrine Reviews 21: 55-89.

Sapolsky RM. 2004. Social status and health in humans and other animals. Annual Review of Anthropology 33: 393-418. van Schaik CP, van Noordwijk M. 1985. Interannual variability in fruit abundance and the reproductive seasonality in Sumatran Long-tailed macaques (Macaca fascicularis). Journal of Zoology 206: 533-549.

Selye H. 1936. A syndrome produced by diverse nocuous agents. Nature. July 4, 1936. 32.

Selye H. 1973. The evolution of the stress concept: the originator of the concept traces its development from the discovery in 1936 of the alarm reaction to modern therapeutic applications of syntoxic and catatoxic hormones. American Scientist 61: 692-699.

Wingfield JC. 2013. The comparative biology of environmental stress: behavioural endocrinology and variation in ability to cope with novel, changing environments. Animal Behaviour 85: 1127-1133.

Wolters S, Zuberbühler K. 2003. Mixed-species associations of Diana and Campbell’s monkeys: the costs and benefits of a forest phenomenon. Behaviour 140: 371-385.

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Chapter 7: Diana monkey socioecology, reproduction, and stress: a synthesis

CONCLUSIONS

It is not surprising that Diana monkeys in the Taï Forest experience only relatively minimal stress over the course of a typical year. Taï has relatively high tree species diversity and productivity compared to other African forests such as, Kakamega,

Kenya or Kibale, Uganda [Anderson, 2001]. Though the dietary data in this dissertation differ from previously reported diets in relative proportions of fruit, invertebrates, and leaves, available evidence supports the hypothesis that Diana monkeys in the Taï Forest eat a diet which incorporates a significant amount of ripe fruit, in addition to large amounts of invertebrates and, to a lesser degree, foliage [Buzzard, 2006; Kane and

McGraw, in preparation; Chapter 2]

Diana monkeys form the core of the polyspecific associations that typify the Taï

Forest’s monkey community, with other species initiating and maintaining associations

[Bshary and Noë, 1997; Noë and Bshary, 1997; Wolters and Zuberbühler, 2003; Eckardt and Zuberbühler, 2004; Buzzard, 2006, 2010; McGraw and Zuberbühler, 2008]. Diana monkeys consistently dominate the other guenons in these associations, expanding their use of forest strata and incorporating more fruit in their diet when in association with these taxa [Wolters and Zuberbühler, 2003; Buzzard, 2006; Kane and McGraw, in review]. They do not compete with other taxa for access to ripe fruit; they dominate other 270 taxa and supplant them from valuable resources [Wolters and Zuberbühler, 2003;

Buzzard, 2006; Kane and McGraw, in review].

Diana monkeys minimize intra-group competition over access to resources by preferentially eating fruit from trees that are large enough to support many individuals foraging in close proximity without engaging in contest competition [Chapter 2]. Fruit from these large trees are supplemented by invertebrates and fruit from less preferred, but smaller and more ubiquitously distributed, trees [Chapter 2]. Because of this, competition over access to usurpable foods does not play a significant role structuring intra-group social dynamics for female Diana monkeys [Chapter 3]. Females forage in close proximity while eating valuable ripe fruit; though aggression was more strongly associated with foraging for fruit than for other food types, the rate of aggression is incredibly low and I could not detect a dominance hierarchy based on aggressive or competitive encounters.

Diana monkeys timed energetically expensive periods of reproduction – late pregnancy, early lactation – during periods when fruit consumption was highest, and fruit was readily available [Chapter 5]. This preliminary research strongly suggests that food availability and fruit consumption has a significant effect on Diana monkeys’ reproductive timing, and that their reproductive strategy may involve maximizing access to these valuable resources during energetically expensive time periods. Non-invasive endocrine analyses help clarify aspects of Diana monkeys’ reproductive cycling and experience metabolic and social stress that observational research alone cannot detect

[Chapter 4, Chapter 5]. Furthermore, Diana monkeys experience elevated FGC

271 concentrations in response to acute stressors, such as responses to predators or intergroup encounters [Chapter 4].

Diana monkeys seem to be particularly well-buffered against metabolic stress.

They do not experience chronic or pathological levels of stress as diets vary in response to fluctuating food availability – even when females are under greater metabolic stress during energetically-expensive periods of reproduction, or under greater amounts of social stress. This contrasts with work on blue monkeys (Cercopithecus mitis stuhlmanni, C. m. allbogularis) in the Kakamega Forest and Gede Ruins in Kenya

[Foerster and Monfort, 2010; Foerster et al., 2012], which found that fluctuations in food availability – particularly of important fruit species – were significant drivers of fluctuations in fecal glucocorticoids. However, both of these forests are significantly more disturbed habitats than the Taï Forest, and variability in food availability may have been more dramatic. Because the Taï Forest is a more diverse and productive habitat than

Kakaemega or Gede, it may be easier for Diana monkeys to buffer themselves against periods of low fruit availability [Anderson, 2001; Chapter 2, Kane and McGraw, in review].

Diana Monkeys and Sociecological Models.

In my dissertation, I have examined the way that female Diana monkeys interact with the environment and each other, starting from a series of expectations underpinning socioecological models derived from research on a “typical cercopithecine” [Wrangham,

1980; Strier, 1994]. I reaffirm the finding that, in many ways, Diana monkeys are exemplars of predictions of socioecological models. They live in female-bonded groups

272

[Candiotti et al., 2015]. They consume diets focusing on resources that are patchily distributed throughout their homerange [Buzzard, 2006; Chapter 2]. They engage in encounters between and within groups that are more frequent than sympatric guenons

[Gautier-Hion, 1988; Buzzard and Eckardt, 2007]. However, as McGraw and

Zuberbühler [2008: 264] note, while the models provide “valuable templates for testing hypotheses,” variation from the predictions of these models are expected.

Diana monkeys differ from, or complicate, the predictions of the sociological model in several important ways. It is difficult to characterize resources, and their interactions with those resources, based on spatial distribution alone. For example, Diana monkeys eat large amounts of fruit from Oldfieldia africanum, a tree which is relatively rare in the Taï Forest. These trees could be considered clumped or patchy resources, but fruits are distributed relatively uniformly throughout their canopy. When Diana monkeys are moving through their home ranges, Oldfieldia africanum are patchily distributed and it may be worth engaging in intergroup competition to defend individual trees. However, while Diana monkeys are actively feeding in their canopy, their relative ubiquity makes contest competition unnecessary. Considering resource distribution at multiple scales can help tease apart the relationship between ecology and sociality. Isbell and colleagues’ concept of “usurpability” helps clarify the relationship between food patches and competition in some taxa, but it does not explain this in Diana monkeys [Isbell et al.,

1999; Chancellor and Isbell, 2009]. The amount of time Diana monkeys spend foraging in one place seems to be a function of handling time, including time to search for and

273 manually and orally process resources, rather than a function of a resource’s perceived value.

In species that are not the “typical cercopithecines,” such as the guenons, behavioral observations may also fall outside the expectations of socioecological models.

As Rowell [1988: 443] noted:

“At a most cursory level of inspection, the social behavior of papionines and guenons seems different. Baboons, macaques, and even mangabeys are rowdy animals, seemingly continuously squabbling among themselves and then making conspicuous gestures of appeasement or reconciliation. Thus baboons will lipsmack, present, embrace, or mount one another after a fight. In contrast, guenons seem discreet. Fighting is relatively rare, and affiliative behavior is also subtle and infrequent.”

The intragroup discretion of the guenons makes examining social dynamics between females challenging [but see Candiotti et al., 2015]. However, non-invasive methods for analyzing the consequences of these dynamics can provide additional clarity, as evidenced by research showing intragroup disparities between female blue monkeys during periods of resource scarcity [Foerster et al., 2012]. While my data did not uncover similar disparities, this may be a consequence of comparatively small sample sizes – or it may reflect the fact that Diana monkeys enjoy a relatively privileged primate existence.

Diana monkeys’ dominance in the primate community at Taï may enable all females, even lower-ranking ones, to buffer themselves against periods of low fruit availability.

Examination of intra- and inter-group dynamics among the other sympatric guenons, extending the work of Paul Buzzard [2006, 2010] on niche differentiation among C. diana, C. campbelli, and C. petaurista with endocrine analyses that allow comparisons of physiological and stress will help contextualize these results. 274

This research focused on Diana monkeys in isolation. Like most research from a socioecological perspective, it examines one species in great detail while ignoring other potential competitors for the same resources. This is a sensible perspective considering that Diana monkey actively attack and kill strange female Diana monkeys, yet they tolerate the presence of Campbell’s monkeys, lesser spot-nosed guenons, and putty-nosed guenons despite extensive dietary overlap [McGraw et al., 2002; Eckardt and

Zuberbühler, 2003; Wolters and Zuberbühler, 2004; Buzzard, 2010]. However, these interspecific dynamics complicate the simple predictions of socioecological models.

Perhaps because many “typical cercopithecines” live in environments with relatively sympatric primate competitors, the socioecological consequences have been underexamined; however, in a complex rainforest environment these merit attention

[Rowell, 1988]. As primatologists work to develop generalizable, synthetic models of primate sociality and ecology, it seems these primate communities are an under-utilized resource [e.g., Thierry, 2008; Jaffe and Isbell, 2011].

Even forty years after their development, socioecological models can provide a useful starting point for the generation of hypotheses about primate behavioral ecology.

Particularly as longitudinal research on poorly-known primates, including the guenons, some New World monkey taxa, and lemurs, expands our knowledge of the diversity of primate socioecological strategies, these models have a place in primatological research.

Given that much of primate evolution occurred as frugivorous primates were interacting in arboreal forest environments, examining extant arboreal frugivores’ sociality, ecology,

275 and health in light of resource distribution can help reconstruct the evolutionary pressures experienced by early primates and old world monkeys [Kay et al., 1980; Rose, 2006].

In this dissertation, I have argued that socioecological models provide a useful starting point for primatological research on primate taxa which are still poorly understood. Diana monkeys complicate classic sociecological models because, although they eat high-value, discontinuously distributed resources, feeding competition does not seem to drive their social behavior and there is little evidence that they experience negative consequences to periods of low food availability. To refine and further develop socioecological models of primate behavior, we must broaden our understanding of primate diets and sociality by testing aspects of these models in a wider variety of taxa – particularly among arboreal old world monkeys – and examine both behavioral and physiological responses to resource distribution.

276

REFERENCES

Anderson DP. 2001. Tree phenology and distribution, and their relation to chimpanzee social ecology in the Taï National Park, Côte D’Ivoire. PhD dissertation: University of Wisconsin, Madison.

Bshary R, Noë R. 1997. Anti-predation behavior of red colobus monkeys in the presence of chimpanzees. Behavioral Ecology and Sociobiology 41: 321-333. Buzzard PJ. 2006. Ecological partitioning of Cercopithecus campbelli, C. petaurista, and C. diana in the Taï Forest. International Journal of Primatology 27: 529-558. Buzzard PJ. 2010. Polyspecific associations of Cercopithecus campbelli and C. petaurista with C. diana: what are the costs and benefits? Primates 51: 307-314. Buzzard PJ, Eckardt W. 2007. The social systems of the guenons. In, McGraw WS, Zuberbühler K, Noë R, eds. Monkeys of the Taï Forest: An African Primate Community. Cambridge: Cambridge University Press. 51-71. Candiotti A, Coye C, Ouattara K, Petit EJ, Vallet D, Zuberbühler K, Lemasson A. 2015. Female bonds and kinship in forest guenons. International Journal of Primatology 36: 332-352. Chancellor RL, Isbell LA. 2009. Food site residence time and female competitive relationships in wild gray-cheeked mangabeys (Lophocebus albigena). Behavioral Ecology and Sociobiology 67: 1447-1458.

Eckardt W, Zuberbühler K. 2004. Cooperation and competition in two forest monkeys. Behavioral Ecology 15: 400-411. Foerster S, Cords M, Monfort SL. 2012. Seasonal energetic stress in a tropical forest primate: proximate causes and evolutionary implications. PLoS ONE 7(11): e50108.

Foerster S, Monfort SL. 2010. Fecal glucocorticoids as indicators of metabolic stress in female Sykes’ monkeys (Cercopithecus mitis albogularis). Hormones and Behavior 58: 685-697.

Gautier-Hion A. 1988. The diet and dietary habits of forest guenons. In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. Isbell LA, Pruetz JD, Young TP. 1998. Movements of vervets (Cercopithecus aethiops) and patas monkeys (Erythrocebus patas) as estimators of food resource size, density, and distribution. Behavioral Ecology and Sociobiology 42: 123-133.

277

Kay RF, Simons EL. 1980. The ecology of Oligocene African anthropoidea. International Journal of Primatology 1: 21-37.

McGraw WS, Zuberbuhler K. 2008. Socioecology, predation, and cognition in a community of West African monkeys. Evolutionary Anthropology 17: 254-266.

Noë R, Bshary R. 1997. The formation of red colobus-Diana monkey associations under predation pressure from chimpanzees. Proceedings of the Royal Society of Biological Sciences 264: 253-259.

McGraw WS, Plavcan JM, Adachi-Kanazawa KA. 2002. Adult female Cercopithecus diana employ canine teeth to kill another adult female C. diana. International Journal of Primatology 23: 1301-1308. Rose KD. 2006. Archonta: bats, dermopterans, primates, and tree shrews. The Beginning of the Age of Mammals. Baltimore: Johns Hopkins University Press. 156-197. Rowell TE. 1988. The social system of guenons, compared with baboons, macaques, and mangabeys. In, Gautier-Hion A, Bourlière F, and Gautier JP, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. New York: Cambridge University Press. 439-451.

Strier K. 1994. The myth of the typical primate. Yearbook of Physical Anthropology 37: 233-271.

Thierry B. 2008. Primate socioecology, the lost dream of ecological determinism. Evolutionary Anthropology 17: 93-96. Wolters S, Zuberbühler K. 2003. Mixed-species associations of Diana and Campbell’s monkeys: the costs and benefits of a forest phenomenon. Behaviour 140: 371-385.

Wrangham RW. 1980. An ecological model of female-bonded primate groups. Behaviour 75: 262-300.

278

References

Altmann JA. 1974. Observational study of behavior: sampling methods. Behaviour 49: 227-267.

Altmann JA. 1980. Baboon Mothers and Infants. Chicago: University of Chicago Press.

Andelman SJ, Else JG, Hearn JP, Hodges JK. 1985. The non-invasive monitoring of reproductive events in wild Vervet monkeys (Cercopithecus aethiops) using urinary pregnanediol-3α-glucuronide and its correlation with behavioural observations. Journal of Zoology 205: 467-477.

Anderson DP. 2001. Tree phenology and distribution, and their relation to chimpanzee social ecology in the Taï National Park, Côte D’Ivoire. PhD Dissertation: University of Wisconsin, Madison.

Anderson DP, Nordheim EV, Moermond TC, Gone Bi ZB, and Boesch C. 2005. Factors influencing tree phenology in Taï National Park, Côte d’Ivoire. Biotropica 37: 631- 640.

Arnold K, Zuberbühler K. 2008. Meaningful call combinations in a non-human primate. Current Biology 18: R202-R203. Aronsen G, Beuerlein MM, Watts DP, Bribiescas RG. 2015. Redtail and red colobus monkeys show intersite urinary cortisol concentration variation in Kibale National Park, Uganda. Conservation Physiology 3: 1-10.

Beehner JC, Bergman TJ, Cheney DL, Seyfarth RM, Whitten PL. 2005. The effect of new alpha males on female stress in free-ranging baboons. Animal Behaviour 69: 1211-1221.

Behie AM, Pavelka MSM, Chapman CA. 2010. Sources of variation in fecal cortisol levels in howler monkeys in Belize. American Journal of Primatology 72: 600-606.

Behringer V, Deschner T. 2017. Non-invasive monitoring of physiological markers in primates. Hormones and Behavior. http://dx.doi.org/10.1016/j.yhbeh.2017.02.001.

Bi GS, Koné I, Bitty AE, Koffie JCB, Akpatou B, Zinner D. 2012. Distribution and conservation status of catarrhine primates in Côte d’Ivoire (West Africa). Folia Primatologica 83: 11-23. Bitty EA, Gonedelé Bi S, Bene Koffi JC, Kouassi PK, McGraw WS. 2015. Cocoa farming and primate extirpation inside Cote d’Ivoire’s protected areas. Tropical Conservation Science 8: 95-113.

Bitty EA, McGraw WS. 2007. Locomotion and habitat use of Stamplfii’s putty-nosed monkey (Cercopithecus nictitans stampflii) in the Taï National Park, Ivory Coast. American Journal of Physical Anthropology 134: 383-391. Bloch JI, Boyer DM. 2002. Grasping primate origins. Science 298: 1606-1610. Booth AH. 1956. The Cercopithecidae of the Gold and Ivory Coast: geographic and systematic observations. Annals and Magazine of Natural History, 9th Series 9: 476- 480. Booth AH. 1958. The zoogeography of West African primates: a review. Bulletin de l’Institut Français d’Afrique Noire 20: 587-622. Bourlière F, Hunkeler C, Bertrand M. 1970. Ecology and behaviour of Lowe’s guenon (Cercopithecus campbelli lowei) in the Ivory Coast. In, Napier JR, Napier PH, eds. Old World Monkeys: Evolution, Systematics, and Behaviour. New York: Academic Press. 297-350.

Brockman DK, van Schaik CP. 2005. Seasonality and reproductive function. In, Brockman DK, van Schaik CP, eds. Seasonality in Primates: studies of living and extinct human and non-human primates. New York: Cambridge University Press. 269-305.

280

Brown J, Walker S, Steinman B. 2008. Endocrine Manual for Reproductive Assessment of Domestic and Non-Domestic Species. Front Royal, VA: Smithsonian’s National Zoological Park.

Butynski TM. 1990. Comparative ecology of blue monkeys (Cercopithecus mitis) in high- and low-density subpopulations. Ecological Monographs 60: 1-26. Butynski TM. 2002. The guenons: an overview of diversity and taxonomy. In, Glenn ME, Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. Chicago: University of Chicago Press. 3-13. Buxton AP. 1952. Observations on the diurnal behaviour of the redtail monkey (Cercopithecus ascanius schmidti Matschie) in a small forest in Uganda. Journal of Animal Ecology 21: 25-58. Buzzard PJ. 2004. Interspecific competition among Cercopithecus campbelli, C. petaurista, and C. diana at Taï Forest, Côte d’Ivoire. PhD Dissertation: Columbia University. Buzzard PJ. 2006a. Ecological partitioning of Cercopithecus campbelli, C. petaurista, and C. diana in the Taï Forest. International Journal of Primatology 27: 529-558.

281

Buzzard PJ. 2006b. Ranging patterns in relation to seasonality and frugivory among Cercopithecus campbelli, C. petaurista, and C. diana in the Taï Forest. International Journal of Primatology 27: 559-573. Buzzard PJ. 2010. Polyspecific associations of Cercopithecus campbelli and C. petaurista with C. diana: what are the costs and benefits? Primates 51: 307-314. Buzzard PJ, Eckardt W. 2007. The social systems of the guenons. In, McGraw WS, Zuberbühler K, Noë R, eds. Monkeys of the Taï Forest: An African Primate Community. Cambridge: Cambridge University Press. 51-71. Candiotti A, Coye C, Ouattara K, Petit EJ, Vallet D, Zuberbühler K, Lemasson A. 2015. Female bonds and kinship in forest guenons. International Journal of Primatology 36: 332-352. Cavigelli SA. 1999. Behavioural patterns associated with faecal cortisol levels in free- ranging female ring-tailed lemurs, Lemur catta. Animal Behaviour 57: 935-944.

Chancellor RL, Isbell LA. 2009. Food site residence time and female competitive relationships in wild gray-cheeked mangabeys (Lophocebus albigena). Behavioral Ecology and Sociobiology 67: 1447-1458.

Chapman CA, Chapman LJ. 1990. Dietary variability in primate populations. Primates 31: 121-128.

Chapman CA, Chapman LJ, Cords M, Gathua JM, Gautier-Hion A, Lambert JE, Rode K, Tutin CEG, White LJT. 2002. Variation in the diets of Cercopithecus species: differences within forests, among forests, and across species. In, Glenn ME, Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. Chicago: University of Chicago Press. 325-350. Chapman CA, Wrangham RW, Chapman LJ. 1994. Indices of habitat-wide fruit abundance in tropical forests. Biotropica 26: 160-171. Chapman CA, Rothman JM, Lambert JE. 2011. Food as a selective force in primates. . In, Mitani JC, Call J, Kappeler PM, Palombit RA, Silk JB, eds. The Evolution of Primate Societies. Chicago: University of Chicago Press. 149-168.

Chapman CA, Struhsaker TT, Lambert JE. 2005. Thirty years of research in Kibale National Park, Uganda, reveals a complex picture for conservation. International Journal of Primatology 26: 539-555. Charmandari E, Tsigos C, Chrousos G. 2005. Endocrinology of the stress response. Annual Review of Physiology 67: 259-284.

282

Cheney DL, Seyfarth RM, Andelman SJ, Lee PC. 1988. Reproductive success in vervet monkeys. In, Clutton-Brock, TH, ed. Reproductive Success. Chicago: Chicago University Pres. 384-402. Cheney DL, Seyfarth RM, Fischer J, Beehner J, Bergman T, Johnson SE, Kitchen DM, Palombit RA, Rendall D, Silk JB. 2004. Factors affecting reproduction and mortality among baboons in the Okavango Delta, Botswana. International Journal of Primatology 25: 401-428. Cherel Y, Hobson KA, Bailleul F, Groscolas R. 2005. Nutrition, physiology, and stable isotopes: new information from fasting and molting penguins. Ecology 86: 2881- 2888.

Chivers DJ. 1998. Measuring food intake in wild animals: primates. Proceedings of the Nutrition Society 57: 321-332.

Chism JB, Rogers W. 1997. Male competition, mating success, and female choice in a seasonally breeding primate (Erythrocebus patas). Ethology 103: 109-126.

Chism JB, Rowell TE. 1986. Mating and residence patterns of male patas monkeys. Ethology 72: 31-39.

Clutton-Brock TH, Harvey PH. 1977. Primate ecology and social organization. Journal of Zoology 183: 1-39.

Clutton-Brock T, Janson C. 2012. Primate socioecology at the crossroads: past, present, and future. Evolutionary Anthropology 21: 136-150. Cook NJ. 2010. Minimally invasive sampling media and the measurement of corticosteroids as biomarkers of stress in animals. Canadian Journal of Animal Science 92: 227-259.

Cords M. 1984. Mating patterns and social structure in redtail monkeys (Cercopithecus ascanius). Zeitschrift für Tierpsychologie 64: 313-339. Cords M. 1986. Interspecific and intraspecific variation in diet of two forest guenons, Cercopithecus ascanius and C. mitis. Journal of Animal Ecology 55: 811-827. 283

Cords M. 1987. Mixed species association of Cercopithecus monkeys in the Kakamega Forest, Kenya. University of California Publications in Zoology 117: 1-109. Cords M. 2000. Agonistic and affiliative relationships in a blue monkey group. In, Whitehead PF, Jolly CJ, eds. Old World Monkeys. Cambridge: Cambridge University Press. 453-479.

Coye C, Zuberbühler K, Lemasson A. 2016. Morphological structured vocalizations in female Diana monkeys. Animal Behaviour 115: 97-105. Crook JH, Gartlan JS. 1966. Evolution of primate societies. Nature 210: 1200-1203. Dantzer B, Westrick SE, van Kesteren F. 2016. Relationships between endocrine traits and life histories in wild animals: insights, problems, and potential pitfalls. Integrative and Comparative Biology 56: 185-197.

DaSilva GL. 1994. Diet of Colobus polykomos on Tiwai Island: selection of food in relation to its seasonal abundance and nutritional quality. International Journal of Primatology 15: 655-680.

DeVore I. 1965. Primate Behavior: Field Studies of Monkeys and Apes. New York: Holt, Rinehart, and Winston. Drent, RH and Daan, S. 1980. The Prudent Parent: Energetic adjustments in avian breeding. In, Klomp H, Woldendrop JW, eds. The Integrated Study of Bird Populations. New York: North Holland, pp. 225-252.

Dunteman GH, Ho MHR. 2006. An Introduction to Generalized Linear Models. Thousand Oaks: Sage Publications. 284

Eckardt W, Zuberbühler K. 2004. Cooperation and competition in two forest monkeys. Behavioral Ecology 15: 400-411. Eisenberg JF, Muckenhirn NA, Rudran R. 1972. The relationship between ecology and social structure in primates. Science 176: 873-874. Emery Thompson M, Knott CD. 2008. Urinary C-peptide of insulin as a non-invasive marker of energy balance in wild orangutans. Hormones and Behavior 53: 526-535.

Felig P, Frohman LA. 2001. Endocrinology and Metabolism. New York: McGraw-Hill.

Fichtel C. 2011. Predation. In, Mitani JC, Call J, Kappeler PM, Palombit RA, Silk JB, eds. The Evolution of Primate Societies. Chicago: University of Chicago Press. 169- 194.

Foerster SF, Cords M, Monfort SL. 2012. Seasonal energetic stress in a tropical forest primate: proximate causes and evolutionary implications. PLoS ONE 7: e50108. Foerster S, Monfort SL. 2010. Fecal glucocorticoids as indicators of metabolic stress in female Sykes’ monkeys (Cercopithecus mitis albogularis). Hormones and Behavior 58: 685-697. 285

Galat-Luong A, Galat G. 1979. Consèquences comportementales de perturbations sociales repetés sur une troupe de mones de Lowe Cercopithecus campbelli lowei de Côte d’Ivoire. Tere Vie 33: 49-58.

Galat G, Galat-Luong A. 1985. La communauté de primates diurnes de la forêt de Taï, Côte d’Ivoire. La Terre et la Vie 40: 3-32. Ganswindt A, Palme R, Heistermann M, Borragan S, Hodges JK. 2003. Non-invasive assessment of adrenocortical function in the male African elephant (Loxodonta africana) and its relation to musth. General Comparative Endocrinology 134: 156- 166.

Gathua JM. 2000. Intraspecific variation in foraging patterns of redtail monkeys (Cercopithecus ascanius) in the Kakamega Forest, Kenya. PhD Dissertation: Columbia University.

Gautier JP, Gautier-Hion A. 1969. Les associations polyspecifiques chez les cercopithecidae du Gabon. La Terre et La Vie 2: 164-201. Gautier-Hion A. 1975. Dimorphisme sexuel et organization sociale chez les cercopithecines forestiers Africains. Mammalia 39: 365-374. Gautier-Hion A. 1980. Seasonal variations of diet related to species and sex in a community of Cercopithecus monkeys. Journal of Animal Ecology 49: 237-269. Gautier-Hion A. 1988. The diet and dietary habits of forest guenons. In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J. 1988a. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J. 1988b. General introduction: why study African guenons? In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. 1-3. Gautier-Hion A, Gautier JP, Quris R. 1981. Forest structure and fruit availability as complementary factors influencing habitat use by a troop of monkeys (Cercopithecus cephus). La Terre et La Vie 35: 511-536.

286

Gautier-Hion A, Quris R, Gautier JP. 1983. Monospecific vs. polyspecific life: a comparative study of foraging and antipredatory tactics in a community of Cercopithecus monkeys. Behavioral Ecology and Sociobiology 12: 325-335. Gemmill A, Gould L. 2008. Microhabitat variation and its effects on dietary composition and intragroup feeding interactions between adult female Lemur catta during the dry season at Beza Mahafaly Special Reserve, Southwestern Madagascar. 29: 1511-1533.

Gillespie TR. 2006. Noninvasive assessment of gastrointestinal parasite infections in free-ranging primates. International Journal of Primatology 27: 1129-1143.

Glenn ME, Cords M. 2002. The Guenons: Diversity and Adaptation in African Monkeys. Chicago: University of Chicago Press. Goland RS, Josak S, Conwell I. 1994. Placental corticotropin-releasing hormone and the hypercortisolism of pregnancy. American Journal of Obstetrics and Gynecology 171: 1287-1291.

Haddow AJ. 1952. Field and laboratory studies on an African monkey, Cercopithecus ascanius schmidti Matschie. Proceedings of the Zoological Society of London 122: 297-394. Hall KRL, Devore I. 1965. Baboon Social Behavior. In, Devore I, ed. Primate Behavior: Field Studies of Monkeys and Apes. New York: Holt, Rinehart and Winston. 53-110. Harding RSO, Olson DK. 1986. Patterns of mating among male patas monkeys (Erythrocebus patas) in Kenya. American Journal of Primatology 11: 343-358.

Henzi SP, Lawes, M. 1988. Strategic responses of male samango monkeys (Cercopithecus mitis) to a decline in the number of receptive females. International Journal of Primatology 9: 479-495.

Higham JP. 2016. Field endocrinology of nonhuman primates: past, present, and future. Hormones and Behavior 84: 145-155.

287

Higham JP, Vitale AB, Mas Rivera A, Ayala JE, Maestripieri D. 2010. Measuring salivary analytes from free-ranging monkeys. Physiology and Behavior 101: 601-607.

Hill CM. 1994. The role of female Diana monkeys, Cercopithecus diana, in territorial defence. Animal Behaviour 47: 425-431. Hodges JK, Heistermann M. 2011. Field endocrinology: monitoring hormonal changes in free-ranging primates. In, Setchell J, Curtis D, eds. Field and Laboratory Methods in Primatology. Cambridge: Cambridge University Press. 282-294.

Holenweg AK, Noë R, Schabel M. 1996. Waser’s gas model applied to associations between red colobus and Diana monkeys in the Taï National Park, Ivory Coast. Folia Primatologica 67: 125-136. Holmes RT, Pitelka FA. 1968. Food overlap among coexisting sandpipers on northern Alaskan tundra. Systematics of Zoology 17:305-318.

Hunt KE, Wasser SK. 2003. Effects of long-term preservation methods on fecal glucocorticoid concentrations of grizzly bear and African elephant. Physiological and Biochemical Zoology 76: 918-928. Hrdy SB, Whitten PL. 1986. Patterning of sexual activity. In, Smutts BB, Cheney DL, Sefarth R, Wrangham RW, Struhsaker TT, eds. Primate Societies. Chicago: Chicago University Press. 370-384.

Isbell LA. 1991. Contest and scramble competition: patterns of female aggression and ranging behavior among primates. Behavioral Ecology 2: 143-155. Isbell LA, Pruetz JD. 1998. Differences between vervets (Cercopithecus aethiops) and Patas monkeys (Erythrocebus patas) in agonistic interactions between adult females. International Journal of Primatology 19: 837-855.

Isbell LA, Young TP. 2002. Ecological models of female social relationships in primates: similarities, disparities, and some directions for future clarity. Behaviour 139: 177- 202. Isbell LA, Young TP, Jaffe KE, Carlson AA, Chancellor RL. 2009. Demography and life histories of sympatric patas monkeys, Erythrocebus patas, and vervets, Cercopithecus aethiops, in Laikipia, Kenya. International Journal of Primatology 30: 103-124.

288

Iverson SJ, Oftedal OT, Bowen WD, Boness DJ, Sampugna J. 1995. Prenatal and postnatal transfer of fatty acids from mother to pup in the hooded seal. Journal of Comparative Physiology B. 165: 1-12.

Ivlev VS. 1961. Experimental ecology of the feeding of fishes. New Haven: Yale University Press.

Janson CH. 1990. Ecological consequences of individual spatial choice in foraging groups of brown capuchin monkeys, Cebus paella. Animal Behavior 40: 922-934.

Jones WT, Bush BB. 1988. Movement and reproductive behavior of solitary male redtail guenons (Cercopithecus ascanius). American Journal of Primatology 14: 203-222.

Kane EE, Gnepa F. 2016. An infanticide attempt after male takeover in Diana monkeys (Cercopithecus diana diana) in Taï, Côte d’Ivoire. African Primates 11: 37-40.

Kay RF, Simons EL. 1980. The ecology of Oligocene African anthropoidea. International Journal of Primatology 1: 21-37.

Kent EB. 1981. Life history responses to resource variation in a sessile predator, the ciliate protozoan Tokophyra lemnarum stein. Ecology 62(2): 296-302.

Klass K, Cords M. 2015. Agonism and dominance in female blue monkeys. American Journal of Primatology 77: 1299-1315.

Knott CD. 2001. Female reproductive ecology of the apes. In, Ellison PT, ed. Reproductive Ecology and Human Evolution. New York: Aldine de Gruyter. 429- 463.

Koenig A, Borries C. 2009. The lost dream of ecological determinism: time to say goodbye? ... Or a White Queen’s proposal? Evolutionary Anthropology 18: 166-174. Koné I, Gonedelé Bi S, Osei D, Wiafe E, Dempsey A, McGraw WS, Oates JF. 2017. Cercopithecus roloway. IUCN 2017, IUCN Red List of Threatened Species. Koné I, Refisch J. 2007. Can monkey behavior be used as an indicator for poaching pressure? A case study of the Diana guenon (Cercopithecus diana) and the western red colobus (Procolobus badius) in the Taï National Park. In, McGraw WS, Zuberbühler K, Noë R, eds. The Monkeys of the Taï Forest: an African Primate Community. Cambridge: Cambridge University Press. 257-289.

289

Korstjens AH, Sterck EHM, Noë R. 2002. How adaptive or phylogenetically inert is primate social behavior? A test with two sympatric colobines. Behaviour 139: 203- 225. Lambert JE. 1999. Seed handing in chimpanzees (Pan troglodytes) and redtail monkeys (Cercopithecus ascanius): implications for understanding hominoid and cercopithecine fruit-processing strategies and seed dispersal. American Journal of Physical Anthropology 109: 365-386. Lambert JE. 2005. Competition, predation, and the evolutionary significance of the Cercopithecine cheek pouch: the case of Cercopithecus and Lophocebus. American Journal of Physical Anthropology 126: 183-192.

Lechowicz MJ. 1982. The sampling characteristics of electivity indices. Oecologia 52: 22-30.

Levine S, Ursin H. 1991. What is stress? In, Brown MR, Koob GF, Rivier C (eds). Stress: Neurobiology and Neuroendocrinology. New York: Marcel Dekker, Inc. 3-21.

Loehle C, Rittenhouse LR. 1982. An analysis of forage preference indices. Journal of Range Management 35(3): 316-319.

Macleod MC, Ross C, Lawes MJ. 2002. Costs and benefits of alternative mating strategies in Samango monkey males. In, Glenn ME, Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. New York: Kluwer Academic/Plenum Publishers. 203-216.

Marler P. 1973. A comparison of vocalizations of red-tailed monkeys and blue monkeys, Cercopithecus ascanius and C. mitis, in Uganda. Zeitschrift für Tierpsychologie 33: 223-247. Marshall AJ, Wrangham RW. 2007. Evolutionary consequences of fallback foods. International Journal of Primatology 28: 1219-1235.

Mason JW. 1968. A review of psychoendocrine research on the pituitary-adrenal cortical system. Psychosomatic Medicine 30: s576-s607.

Mastorakos G, Ilias I. 2003. Maternal and fetal hypothalamic-pituitary-adrenal axes during pregnancy and postpartum. Annals of the New York Academy of Sciences 997: 136-149.

290

Mathy JW, Isbell LA. 2001. The relative importance of size of food and interfood distance in eliciting aggression in captive Rhesus macaques (Macaca mulatta). Folia Primatologica 72: 268-277.

McEwen BS, Stellar E. 1993. Stress and the individual: mechanisms leading to disease. Archives of Internal Medicine 153: 2093-2101.

McEwen BS, Wingfield JC. 2003. The concept of allostasis in biology and biomedicine. Hormones and Behavior 43: 2-15.

McGraw WS. 1996. Cercopithecid locomotion, support use, and support availability in the Taï Forest, Ivory Coast. American Journal of Physical Anthropology 100: 507- 522. McGraw WS. 1998. Comparative locomotion and habitat use of six monkeys in the Taï Forest, Ivory Coast. American Journal of Physical Anthropology 105: 493-510. McGraw WS. 2007. Vulnerability and conservation of the Taï monkey fauna. In, McGraw WS, Zuberbühler K, Noë R, eds. The Monkeys of the Taï Forest: an African Primate Community. Cambridge: Cambridge University Press. 290-316. McGraw WS, Bshary R. 2002. Association of terrestrial mangabeys (Cercocebus atys) with arboreal monkeys: experimental evidence for the effects of reduced ground predator pressuer on habitat use. International Journal of Primatology 23: 311-325. McGraw WS, Cooke C, Shultz S. 2006. Primate remains from African crowned eagle (Stephanoaetus coronatus) nests in Ivory Coast’s Tai Forest: implications for primate predation and early hominid taphonomy in South Africa. American Journal of Physical Anthropology 131: 151-166.

McGraw WS, Plavcan JM, Adachi-Kanazawa KA. 2002. Adult female Cercopithecus diana employ canine teeth to kill another adult female C. diana. International Journal of Primatology 23: 1301-1308. McGraw WS, Zuberbühler K. 2007. The monkeys of the Taï forest: an introduction. In, McGraw WS, Zuberbühler K, Noë R, eds. The Monkeys of the Taï Forest: an African Primate Community. Cambridge: Cambridge University Press. 1-48. McGraw WS, Zuberbühler K, Noë R. 2007. Monkeys of the Taï Forest: an African Primate Community. Cambridge: Cambridge University Press. 328 p.

291

Nakagawa N, Ohsawa H, Muroyama Y. 2003. Life-history parameters of a wild group of West African patas monkeys (Erythrocebus patas patas). Primates 44: 281-290.

Nelson RJ. 2011. An Introduction to Behavioral Endocrinology. Sunderland: Sinauer Associates.

Oates JF. 1988. The distribution of Cercopithecus monkeys in West African forests. In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. 79-103.

Oates JF. 2011. Cercopithecus diana (Linnaeus, 1758) Diana and roloway monkeys. In Primates of West Africa. Bogotá: Panamericana Formas e Impresos. 251-264.

Oates JF, Gippoliti S, Groves CP. 2016. Cercopithecus diana. The IUCN Red List of Threatened Species 2016: e.T425A92376689. Oates JF, Whitesides GH. 1990. Associations between olive colobus (Procolobus verus), Diana guenons (Cercopithecus diana), and other forest monkeys in Sierra Leone. American Journal of Primatology 21: 129-146. Oates JF, Whitesides GH, Davies AG, Waterman PG, Green SM, Dasilva GL, Mole S. 1990. Determinants of variation in tropical forest primate biomass: new evidence from West Africa. Ecology 71: 328-343.

Ohsawa H, Inoue M, Takenaka O. 1993. Mating strategy and reproductive success of male patas monkeys (Erythrocebus patas). Primates 34: 533-544.

Ouattara K, Lemasson A, Zuberbühler K. 2009. Anti-predator strategies of free-ranging Campbell’s monkeys. Behaviour 146: 1687-1708. Payne HFP, Lawes MJ, Henzi SP. 2003. Competition and the exchange of grooming among female Samango monkeys (Cercopithecus mitis erythrarchus). Behaviour 140: 453-471.

292

Pazol KA. 2001. Social, ecological, and endocrine influences on female relationships in blue monkeys (Cercopithecus mitis stuhlmanni). PhD Dissertation: University of Pennsylvania.

Pazol KA. 2003. Mating in the Kakamega Forest blue monkeys (Cercopithecus mitis): does female sexual behavior function to manipulate paternity assessment? Behaviour 140: 473-499.

Pazol K, Cords M. 2005. Seasonal variation in feeding behavior, competition, and female social relationships in a forest dwelling guenon, the blue monkey (Cercopithecus mitis stuhlmanni), in the Kakamega Forest, Kenya. Behavioral Ecology and Sociobiology 58: 566-577. Polansky L, Boesch C. 2013. Long-term changes in fruit phenology in a West African lowland tropical rain forest are not explained by rainfall. Biotropica 45: 434-440.

Post DG, Hausfater G, McCuskey SA. 1980. Feeding behavior of yellow baboons (Papio cynocephalus): relationship to age, gender, and dominance risk. Folia Primatologica 34: 170-195.

Pride RE. 2005. Optimal group size and seasonal stress in ring-tailed lemurs (Lemur catta). Behavioral Ecology 16: 550-560.

Refisch J, Koné I. 2005. Impact of commercial hunting on monkey populations in the Taï region, Côte d’Ivoire. Biotropica 37: 136-144.

Reitsema LJ. 2012. Introducing fecal stable isotope analysis in primate weaning studies. American Journal of Primatology 74: 926-939.

Roberts EK, Lu A, Bergman TJ, Beehner JC. 2012. A Bruce effect in wild Geladas. Science. 335: 1222-1225.

Rodell MO, Range F, Seppänen JT, Noë R. 2002. Caviar in the rain forest: monkeys as frog-spawn predators in Taï National Park, Ivory Coast. Journal of Tropical Ecology 18: 289-294.

293

Romero LM, Dickens MJ, Cry NE. 2009. The Reactive Scope Model – a new model integrating homeostasis, allostasis, and stress. Hormones and behavior: 55: 375-389.

Rose KD. 2006. Archonta: bats, dermopterans, primates, and tree shrews. The Beginning of the Age of Mammals. Baltimore: Johns Hopkins University Press. 156-197. Rowell TE. 1977. Reproductive cycles of the talapoin monkey (Miopithecus talapoin). Folia Primatology 28: 188-202.

Rowell TE. 1988a. Beyond the one-male group. Behaviour 104: 189-201. Rowell TE. 1988b. The social system of guenons, compared with baboons, macaques, and mangabeys. In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. 439-451. Rowell TE. 1993. Reification of social systems. Evolutionary Anthropology 2: 135-137. Rowell TE, Dixon AF. 1975. Changes in the social organization during the breeding season of wild talapoin monkeys. Journal of Reproduction and Fertility 43: 419-434.

Rudran R. 1978. Socioecology of the blue monkeys (Cercopithecus mitis stuhlmanni) of the Kibale Forest, Uganda. Smithsonian Contributions to Zoology 249: 1-88. Sapolsky RM. 1987. Stress, social status, and reproductive physiology in free-living baboons. In, D. Crews, Ed. Psychobiology of Reproductive Behavior: An Evolutionary Perspective. 291-322.

Sapolsky RM. 2000. Stress hormones: good and bad. Neurobiology of Disease 7: 540- 542.

Sapolsky RM. 2004. Social status and health in humans and other animals. Annual Review of Anthropology 33: 393-418.

Sapolsky RM, Romero LM, Munck AU. 2000. How do glucocorticoids influence stress responses? Integrating permissive, suppressive, stimulatory, and preparative actions. Endocrine Reviews 21: 55-89.

Van Schaik CP. 1983. Why are diurnal primates living in groups? Behaviour 87: 120- 144.

294

Van Schaik CP. 1989. The ecology of social relationships amongst female primates. In, Standen V, Foley RA, eds. Comparative Socioecology: The Behavioural Ecology of Humans and Other Mammals. Oxford: Blackwell Scientific Publications. 195-218. van Schaik CP, van Noordwijk M. 1985. Interannual variability in fruit abundance and the reproductive seasonality in Sumatran Long-tailed macaques (Macaca fascicularis). Journal of Zoology 206: 533-549. van Schaik CP, Isler K. 2011. Life-history evolution. In, Mitani JC, Call J, Kappeler PM, Palombit RA, Silk JB, eds. The Evolution of Primate Societies. Chicago: University of Chicago Press. 220-244.

Selye H. 1936. A syndrome produced by diverse nocuous agents. Nature. July 4, 1936. 32.

Silk JB. 1980. Kidnapping and female competition among captive bonnet macaques. Primates 21: 100-110.

Sommer V, Srivastava A, Borries C. 1992. Cycles, sexuality, and conception in free- ranging langurs (Presbytis entellus). American Journal of Primatology 10: 293-317.

Stavisky R, Russell E, Stallings J, Smith EO, Worthman C, Whitten PL. 1995. Fecal steroid analysis of ovarian cycles in free-ranging baboons. American Journal of Primatology 36: 285-297.

Stearns, S.C. 1989. Trade-offs in life-history evolution. Functional Ecology 3: 259-268.

Stephan C, Zuberbühler K. 2008. Predation increases acoustic complexity in primate alarm calls. Biology Letters 4: 641-644. Stephan C, Zuberbühler K. 2016. Social familiarity affects Diana monkey (Cercopithecus diana diana) alarm call responses in habitat-specific ways. Royal Society Open Science 3: 150639.

295

Sterck EHM, Watts DP, van Schaik CP. 1997. The evolution of female social relationships in nonhuman primates. Behavioral Ecology and Sociobiology 41: 291- 309. Strauss RE. 1979. Reliability estimates for Ivlev’s Electivity Index, the forage ratio, and a proposed linear index of food selection. Transactions of the American Fisheries Society 108; 344-352.

Strier K. 1994. The myth of the typical primate. Yearbook of Physical Anthropology 37: 233-271. Struhsaker TT. 1969. Correlates of ecology and social organization among African cercopithecines. Folia Primatologica 11: 80-118. Struhsaker TT. 1977. Infanticide and social organization in the redtail monkeys (Cercopithecus ascanius schmidti) in the Kibale Forest, Uganda. Ethology 45: 75-84. Struhsaker TT. 1988. Male tenure, multi-male influxes, and reproductive success in redtail monkeys (Cercopithecus ascanius). In, Gautier-Hion A, Bourlière F, Gautier JP, Kingdon J, eds. A Primate Radiation: Evolutionary Biology of the African Guenons. Cambridge: Cambridge University Press. 340-363. Struhsaker TT. 1997. Ecology of an African Rain Forest. Gainesville, University Press of Florida.

Struhsaker TT. 2010. The Red Colobus Monkeys: Variation in demography, behavior, and ecology of endangered species. Oxford: Oxford University Press.

Thierry B. 1997. Adaptation and self-organization in primate societies. Diogenes 180: 39- 71. Thierry B. 2008. Primate socioecology, the lost dream of ecological determinism. Evolutionary Anthropology 17: 93-96. Touma C, Palme R. 2005. Masuring fecal glucocorticoid metabolites in mammals and birds: the importance of validation. Annals of the New York Academy of Sciences 1046: 54-74.

Trivers RL. 1972. Parental investment and sexual selection. In, Campbell B, ed. Sexual Selection and the Descent of Man 1871-1971. Chicago: Aldine Press. 139-179. Tsinalia HM, Rowell TE. 1984. The behaviour of adult male blue monkeys. Ethology 64: 253-268. Tutin CEG, Ham RM, White LJT, Harrison MJS. 1997. The primate community of the Lopé Reserve, Gabon: diets, responses to fruit scarcity, and effects on biomass. American Journal of Primatology 42: 1-24. 296

Tutin CEG. 1999. Fragmented living: behavioural ecology of primates in a forest fragment in the Lopé Reserve, Gabon. Primates 40:249-265.

Ukizintambara T, Thébaud C. 2002. Assessing extinction risk in Cercopithecus monkeys. In, Glenn ME, Cords M, eds. The Guenons: Diversity and Adaptation in African Monkeys. Chicago: University of Chicago Press. 393-410. Wachter B, Schabel M, Noë R. 1997. Diet overlap and polyspecific associations of red colobus and Diana monkeys in the Taï National Park, Ivory Coast. Ethology 103: 514-526. Wark JD, Amendolagine L, Lukas KE, Kuhar CW, Dennis PM, Snowdon CT, Schoffner T, Schook MW. 2016. Fecal glucocorticoid metabolite responses to management stressors and social change in four species of callitrichine monokeys. Primates 57: 267-277. Wasser SK. Hunt KE, Brown JL, Cooper K, Crockett CM, Bechert U, Millspaugh JJ, Larson S, Monfort SL. 2000. A generalized fecal glucocorticoid assay for use in a diverse array of nondomestic mammalian and avian species. General and Comparative Endocrinology 120: 260-275. Wasser SK, Risler L, Steiner RA. 1988. Excreted steroids in primate feces of the menstrual cycle and pregnancy. Biology of Reproduction 39: 862-872.

Whitesides GH. 1989. Interspecific associations of Diana monkeys, Cercopithecus diana, in Sierra Leone, West Africa: biological significance or chance? Animal Behavior 37: 760-776. Wikelski M, Cooke SJ. 2006. Conservation physiology. Trends in Ecology and Evolution 21: 38-46.

Wildt DE, Wemmer C. 1999. Sex and wildlife: the role of reproductive science in conservation. Biodiversity and Conservation 8: 965-976.

Wingfield JC. 2013. The comparative biology of environmental stress: behavioural endocrinology and variation in ability to cope with novel, changing environments. Animal Behaviour 85: 1127-1133. 297

Wittig RM, Crockford C, Weltring A, Deschner T, Zuberbühler K. 2015. Single aggressive interactions increase urinary glucocorticoid levels in wild male chimpanzees. PlOSOne 10: e0118695.

Wolters S, Zuberbühler K. 2003. Mixed-species associations of Diana and Campbell’s monkeys: the costs and benefits of a forest phenomenon. Behaviour 140: 371-385. Wrangham RW. 1980. An ecological model of female-bonded primate groups. Behaviour 75: 262-300. Zuberbühler K. 2000a. Causal knowledge of predators’ behavior in wild Diana monkeys. Animal Behaviour 59: 209-220. Zuberbühler K. 2000b. Interspecies semantic communication in two forest primates. Proceedings of the Royal Society of London B: Biological Sicences 267: 713-718. Zuberbühler K, Jenny D. 2002. Leopard predation and primate evolution. Journal of Human Evolution 43: 873-886.

Zuberbühler K, Jenny D, Bshary R. 1999. The predator deterrence function of primate alarm calls. Ethology 105: 477-490. Zuberbühler K, Noë R, Seyfarth RM. 1997. Diana monkey long-distance calls: messages for conspecifics and predators. Animal Behaviour 53: 589-604.

298