Why Get Along? Dietary and Molecular Influences on Cooperation in an Ant-Plant Symbiosis

by

Kyle Matthew Turner

A thesis submitted in conformity with the requirements for the degree of Masters of Science

Graduate Department of Ecology and Evolutionary Biology University of Toronto

© Copyright Kyle Matthew Turner, 2013

 

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Why Get Along? Dietary and Molecular Influences on

Cooperation in an Ant-Plant Symbiosis Kyle Matthew Turner

Masters of Science

Graduate Department of Ecology and Evolutionary Biology

University of Toronto

2013

ABSTRACT

In mutualisms, individuals exchange goods and services for net benefit. However, many

sources of variation in these interactions remain unexplored. To examine why plant-

dwelling ants protect their host plants by killing herbivores, I shifted the macronutrient

balance of their background diets. Providing ants with supplemental protein caused them

to invest less in patrolling and defence activities, likely because the availability of low-

cost protein made hunting for herbivores relatively less profitable. In contrast,

supplemental sugar caused an increase in ant activity, possibly because carbohydrates

serve as ‘fuel’ for patrolling. To examine a second source of variation in this interaction,

I treated ants with an activator of PKG, a protein encoded by foraging, a gene with

behavioural functions in other taxa. PKG activation caused ants to become more

aggressive towards herbivores, causing their host plants to experience less herbivory.

This suggests that an ortholog of foraging may influence cooperation in this system.

 

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ACKNOWLEDGEMENTS

This is a thesis about cooperation, and it could not have been produced without the help

of many others. First, I want to thank Megan Frederickson, my supervisor and mentor.

Megan is a truly great mind, and has consistently supported me, pushed me, and

encouraged me to take risks I never would have taken alone. I also want to acknowledge

the contributions of John Stinchcombe, James Thomson, and Marla Sokolowski, who

served on my supervisory committee; they were sometimes tough and intimidating, but

always fair and insightful. Thank you also to Marc Johnson and Helen Rodd for agreeing

to sit on my exam committee. And thank you to Ben Gilbert for always giving in to my

pestering for advice on statistics.

There are many people who directly helped me out with my experiments, and I want to

extend my deepest thanks to them. Thank you to Antonio Coral for invaluable help in the

field – I don’t think I would have found half my plants without his keen eye. I want to

give the most sincere thanks to the undergraduate students who helped me out: to Jackie

Awad, Shannon Meadley Dunphy, Margaret Thompson, and Kriti Saxena, thank you for

helping me and thank you even more for putting up with me. Thanks also to Stephanie

Fox, Erik Dean, and Gnanushan Krishna – though the work that they helped with did not

make it into this thesis, their help greatly enriched my graduate experience.

The Department of Ecology and Evolutionary Biology is intellectually strong, and I want

to thank the faculty for fostering that environment. I would also like to thank the

 

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administrative, maintenance, and janitorial staff – I fear that their contribution to our

work often goes unrecognized.

I also have to give my deepest thanks to the members of my lab and the other students in

the department. You have served as assistants, sounding boards, debate partners, and

above all, friends. Thank you to Kirsten Prior, Lina Arcila Hernández, Adam

Cembrowski, Rebecca Batstone, Eric Youngerman, and Jackie Day for making my time

in the Frederickson Lab wonderful. Thank you also to Jane Ogilvie, Ali Parker, Eddie

Ho, Emily Austen, Susana Wadgymar, Sandy Watts, Alex De Serrano, Jordan Pleet,

Natalie Jones, Kelly Carscadden, and Rachel Germain for the innumerable ways that you

have supported and helped me. And I am very grateful to the Pierce Lab at Harvard for

taking me in and becoming my fast friends.

And thank you finally to my family. I would not be where I am now had my parents not

provided me with a warm, supportive environment, and always encouraged curiosity and

exploration. Their support has never wavered, and their gestures of help made all the

difference in the tougher times of these projects. To everyone, I will forever appreciate

your help… and your cooperation.

 

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TABLE OF CONTENTS

ABSTRACT ...................................................................................................................... ii

ACKNOWLEDGEMENTS ............................................................................................ iii

LIST OF FIGURES........................................................................................................ vii

LIST OF APPENDICES ..................................................................................................ix

GENERAL INTRODUCTION ........................................................................................1

CHAPTER ONE - Satiation and Cooperation: Diet Affects Protective Behaviour in

a Plant-Dwelling Ant .........................................................................................................6

Abstract............................................................................................................................6

Introduction .....................................................................................................................6

Methods .........................................................................................................................10

Study System .............................................................................................................10

Experiment.................................................................................................................11

i) Ant Activity........................................................................................................11

ii) Ant Aggression .................................................................................................12

Statistical Analysis ....................................................................................................13

Results ...........................................................................................................................15

i) Ant activity.........................................................................................................15

ii) Ant Aggression .................................................................................................17

Discussion......................................................................................................................18

References .....................................................................................................................23

 

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Figures ...........................................................................................................................30

CHAPTER TWO - Activation of Protein Kinase G (PKG) makes plant-protecting

ants better mutualist........................................................................................................37

Abstract..........................................................................................................................37

Introduction ...................................................................................................................37

Methods .........................................................................................................................41

Study System .............................................................................................................41

Experiment.................................................................................................................42

Ant Aggression Assays..............................................................................................42

Herbivory and Plant Traits ........................................................................................43

Statistical Analysis ....................................................................................................44

Results ...........................................................................................................................45

Discussion......................................................................................................................46

References .....................................................................................................................51

Figures ...........................................................................................................................61

CONCLUDING REMARKS ..........................................................................................67

WORKS CITED ..............................................................................................................71

APPENDIX ......................................................................................................................87

 

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LIST OF FIGURES

Figure 1.1. Mean (± SE) number of workers on (a) old leaves and (b) young leaves in

the four diet treatments…………………………………………………..……....30

Figure 1.2. Mean (± SE) numbers of workers found in the domatium attached to the

young leaves..……………………………...…………………………………….32

Figure 1.3. Mean (± SE) aggression score (average attacks on grasshoppers across each

minute for five minutes) measured four weeks after treatment..…..………….....33

Figure 1.4. Area of damaged tissue on the focal set of young leaves vs aggression score

(average attacks on grasshoppers across each minute for five minutes), with least-

squares regression line..……………………………………………………….....34

Figure 1.5. Mean (± SE) area of damaged tissue on the focal set of young leaves in

plants in part ii, by treatment..…………………….……………………………..35

Supplementary Figure 1.1. Activity of workers on young leaves at final vs initial

counts, in the sugar, mixed, control, and protein treatments……………...……..36

Figure 2.1. Schematic of the experimental set-up on a C. nodosa branch..…….…….....59

Figure 2.2. Mean (± SE) number of attacks on grasshoppers per minute in the control

and PKG activator treatments.……………………….………………………......60

Figure 2.3. Aggression score (attacks on grasshoppers averaged over five minutes)

before and after treatment, in control (a) and PKG activator-treated (b) colonies,

with least-squares regression lines. ……………………………………………..61

 

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Figure 2.4. Mean (± SE) area of herbivore damage in the control and PKG activator

treatments. …………………………………………………………………….....63

Supplementary Figure 2.1. Damaged leaf area vs leaf size (the width of the largest leaf

in the whorl) in the control and activator treatments. …………………………...64

 

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LIST OF APPENDICES

APPENDIX A – Pilot study: The effect of PKG on cooperation may vary across

systems…………………………………………………………………………84

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GENERAL INTRODUCTION

Cooperative interactions can facilitate radical shifts in a species’ ecology, opening new

dietary niches, creating enemy-free space, and allowing colonization of new habitats

(Redecker et al. 2000, Janson 2008, Corradi & Bonfante 2012). In these mutualistic

interactions, species provide partners with goods or services, and in exchange acquire

resources that would be impossible or too costly to produce alone (Bronstein 1994a,

Bronstein et al. 2006). By definition, both partners obtain a net benefit. These

interactions can lead to coevolution, as interacting species evolve traits to attract and

retain partners, and to maximize the net gain from their interactions. This process can

drive diversification and the evolution of specialized morphologies and behaviours

(Powell 1992, Weiblen & Bush 2002, Ramírez et al 2011). As with other forms of

evolution, however, coevolution in cooperative interactions requires variation for

selection to act upon (Thompson 1988).

The outcomes of mutualistic interactions do frequently vary over space and time (e.g.

Thompson & Cunningham 2002, Rudgers & Strauss 2004). The net benefit of mutualism

can, for instance, depend on age or size class, partner density, or the abundance of third

parties like competitors or predators (Thompson 1988, Bronstein 1994b, Frederickson et

al. 2012a). Outcomes can also fluctuate with variability in the resources required for

cooperative phenotypes (e.g. Folgarait & Davidson 1995, Pringle et al. 2011), or with the

availability of alternative sources of the resource gained from the interaction (Kiers et al.

2006, Ness et al. 2009, Kiers et al. 2011). Genetic variation in cooperative phenotypes

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can also have a substantial impact on the outcome of cooperation, for both partners

(Brock et al. 2011, Friesen 2011, Vantaux et al. 2011, Soares et al. 2012). But though all

these sources of variation will affect the fitness of interacting partners, they will not have

equivalent effects on coevolution. For cooperative traits to evolve, there must be a

genetic component to phenotypic variation (Thompson 1988). Strong environmental

variation in the outcomes of mutualism, in contrast, could slow coevolution, as strong

selection is only experienced in some contexts (Bronstein 1994b).

Many authors writing on mutualism are particularly concerned with how mutualisms

remain stable in the face of the apparent threat of cheating, that is, the potential for a

partner to reap the benefits of the interaction without paying the cost (e.g. Ferriere et al.

2002, Kiers et al. 2006, Heath & Tiffin 2009, Jandér & Herre 2011, Oono et al. 2011).

There are several potential mechanisms that stabilize mutualism by selecting for

cooperation (Sachs et al. 2004, Weyl et al. 2010, Archetti et al. 2011), including

preferential association with high-quality partners (‘partner choice’), derived traits

reducing the fitness of low-quality partners (‘host sanctions’), and links between the

fitness of both partners (‘partner fidelity feedback’). Though there is disagreement about

the relative importance of these alternative mechanisms, all require that variation in

partner quality have a genetic basis.

In this thesis, I explored some of the potential sources of variation in myrmecophytism, a

specialized ant-plant defensive interaction. In this interaction, plants produce hollow

structures (‘domatia’) in stems, thorns, or leaf pouches as nesting sites for ants (Heil &

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McKey 2003). Ant colonies that live on these plants also derive food from their host

plants, either directly through food bodies (Janzen 1966, Folgarait & Davidson 1995,

Solano et al. 2005), or indirectly through scale insects, which feed on plants and secrete

honeydew for ants (Fonseca 1993, Pringle et al. 2011, Frederickson et al. 2012a). More

than 100 plant genera contain examples of myrmecophytism (Heil & McKey 2003), and

myrmecophytic plants are a conspicuous part of many tropical communities.

My work primarily focused on the interaction between the treelet Cordia nodosa

(Boraginaceae) and its ant partner, Allomerus octoarticulatus (Formicidae: Myrmicinae).

While both species associate with multiple partners (Yu & Pierce 1998, Frederickson

2009), A. octoarticulatus is the most common defender of C. nodosa at my field site in

southeastern Peru. A single, monogynous colony inhabits one C. nodosa tree, raising

brood (eggs, larvae, and pupae) and tending scale insects (Hemiptera: Sternorrhyncha:

Coccoidea) within the domatia (Frederickson et al. 2012a). The protective activities of

these ants reduce folivory (Yu & Pierce 1998, Frederickson 2005, Frederickson et al.

2012a) and promote plant growth (Frederickson & Gordon 2009, Frederickson et al.

2012a). Ants benefit from their protective behaviour because plant growth increases

available nesting space, reducing colony mortality and increasing reproduction (Yu &

Pierce 1998, Frederickson 2006, Frederickson & Gordon 2009, Frederickson et al.

2012a). The net benefit for plants, however, is dependent on the presence of herbivores:

when they are excluded, plants incur a net cost of hosting ants (Frederickson et al.

2012a).

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In my first chapter, I explore whether this interaction might also be sensitive to variation

in the availability of resources in the environment. Foraging A. octoarticulatus workers

completely restrict their activity to the plant surfaces (Yu & Pierce 1998, Frederickson &

Gordon 2009), obtaining food from cellular food bodies produced on the young tissues of

C. nodosa (Solano et al. 2005), honeydew excreted by scale insects, and the invertebrates

that land on their host plant (Yu & Pierce 1998, Frederickson et al. 2012a). Herbivores

appear to be an important source of food for the ants, as they construct elaborate carton

galleries on stems to trap their prey (Dejean et al. 2005, Ruiz-González et al. 2011).

Since ants’ protective behaviour is based in food acquisition, it may be affected by

optimal foraging (Charnov 1976). Particularly, ants have been found to reject food items

when they are less profitable than the expected gain rate from alternative sources in the

environment (Kay 2002); the availability of alternative protein sources may therefore

reduce ants’ investment in hunting and killing insect herbivores. Conversely, additional

carbohydrate sources might increase defensive behaviour, either by acting as fuel for

high-tempo activity (Davidson 1997, Grover et al. 2007, Pringle et al. 2011, González-

Teuber et al. 2012), or, as a macronutrient complementary to nitrogen, increasing ant

‘hunger’ for protein (Dussutour & Simpson 2009, Cook & Behmer 2010, Cook et al.

2012). Chapter One describes field studies exploring these possibilities.

In Chapter Two, I explore a second source of variation in ant defence: behavioural

genetics. Recent study has revealed genes linked to learning, mating, dominance, and a

number of other ecologically-relevant behaviours (Fitzpatrick & Sokolowski, Fitzpatrick

et al. 2005). One of these genes, foraging, has been linked to food-seeking behaviours

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and activity levels across taxa (Osborne et al. 1997, Ben-Shahar et al. 2002, Tobback et

al. 2008), including in ants (Lucas & Sokolowski 2009, Ingram et al. 2011). Since plant

protection in A. octoarticulatus represents both foraging and nest defence, I predicted

that the activity of PKG, the enzyme encoded by foraging, would influence the level of

protection ants provide. Chapter Two describes a field study in which I

pharmacologically activated PKG to test this prediction. As the effects of foraging

orthologs are known to vary across systems, I also tested for an influence of PKG in

another system, the interaction between Acacia drepanolobium and two of its partner ant

species, Crematogaster nigriceps and Crematogaster mimosae. Though this work was

hindered by high ant mortality in the greenhouse population studied, the results,

described in Appendix A, have implications for our understanding of the genetic basis of

cooperation.

The relationship between ants and myrmecophytic plants is a highly specialized

interaction. Understanding how the ants’ cooperative behaviour might be sensitive to diet

and the activity of PKG helps us understand why they continue to cooperate, and how

plants might maximize their benefit from the interaction. But many cooperative

interactions involve the exchange of food, and all mutualisms involving animals will be

influenced by behaviour. Learning more about how cooperation is influenced by diet and

genetics thus extends our understanding of how a diverse array of mutualistic interactions

might function and coevolve.

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CHAPTER ONE

Satiation and cooperation: diet affects protective behaviour in a plant-dwelling ant

Abstract

In mutualisms, organisms get goods or services by cooperating with a partner. However,

the value of these rewards can vary with the availability of alternative sources. Here, we

use the cooperative interaction between Allomerus octoarticulatus ants and the Cordia

nodosa trees they inhabit and protect to test whether changing the food available to the

animal partner might change its level of cooperation. When we supplemented the diets of

A. octoarticulatus colonies with protein, ants patrolled less, recruited to wounds less

readily, and became less aggressive towards herbivores placed on the plant. Thus, with

alternative, less-costly sources of protein, colonies invested less in hunting herbivores

and protecting their hosts. Under sugar supplementation, in contrast, a subset of colonies

increased the intensity of patrolling activity on young tissues of the plants. This supports

the hypothesis that excess carbohydrates fuel high-tempo activity in ants. Though ants

benefit indirectly from protective behaviour through the growth of their host plants, the

direct role of food rewards is also important for understanding cooperation in this system.

Introduction

Mutualisms are phylogenetically and functionally diverse, but are unified by an exchange

of goods and services benefiting both partners (Bronstein 1994, Bronstein et al. 2006).

Nearly universally, food is used as a reward for animal partners in plant-animal

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mutualisms. Animals receive food in exchange for dispersal of plant gametes

(pollination, Bronstein et al. 2006) or offspring (frugivory, Herrera 1984; ant seed-

dispersal, Gammans et al. 2005), parasite removal (cleaner fish, Soares et al. 2012), or

other protection against natural enemies (hemipteran-tending by ants, Way 1963). In

many cases, the partner itself is eaten (e.g. leafcutter ant-fungal interactions, Quinlan &

Cherrett 1978). However, food in mutualism can serve a more complicated role than

simply as currency.

One interaction involving food exchange is myrmecophytism. Found in more than 100

plant genera (Heil & McKey 2003), myrmecophytic plants produce hollow or hollowable

structures (‘domatia’) for ants. ‘Plant-ants’ nest in the domatia and protect their host

plants from herbivores, pathogens, or competitors (Trager et al. 2010). Many plant

species produce food bodies or extrafloral nectar for ants (e.g., Müllerian and pearl

bodies in Cecropia spp., Folgarait & Davidson 1995; Beltian bodies and EFN in Central

American Acacia spp., Janzen 1966; food bodies in Cordia nodosa, Solano et al. 2005).

After water, lipids often form the major component of these food bodies, followed by

protein and soluble carbohydrates like sugars (Heil et al. 1998, Fischer et al. 2002, Heil

et al. 2004). Ants may also acquire plant-derived food via the honeydew-producing scale

insects they often tend (Fonseca 1993, Pringle et al. 2011). In plants that are facultatively

visited by ants, nectar composition is known to affect the attraction of partners (Heil

2011), but the optimal composition of food rewards in myrmecophytes is less clear.

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Food plays a dual role in this interaction. First, as many plant-ant species restrict their

foraging to the plant, plant-derived food sustains the colony. More food may increase

colony size, possibly providing the plant with a larger defensive force to reduce

herbivory (Heil et al. 2001, Pringle et al. 2011). But food could more directly affect

defensive behaviour. Excess carbohydrates, for instance, might fuel active, ‘high tempo’

foraging and patrolling activity (Davidson 1997). Moderately high levels of sucrose were

associated with high activity and aggression in an ecologically dominant ground-nesting

ant (Grover et al. 2007), and a high-sucrose diet increased anti-herbivore aggression in

lab colonies of the plant-ant Azteca pittieri (Pringle et al. 2011). Thus, plant-derived food

sustains ants, but its composition may also specifically influence ants’ ability to sustain

high-energy defensive behaviours.

Food may have a particularly strong impact in systems where defending ants are

predatory. Some plant-ants just repel threatening herbivores (e.g. Madden & Young

1992, Fonseca 1993) or remove them from plant surfaces (e.g. Letourneau 1983), but

many kill and eat them (e.g. Dejean et al. 2005, 2010). Thus, background diet may

additionally affect ants’ defensive behaviour by changing the relative value of herbivores

as a food source. As outlined by Kay (2002), ants can make foraging decisions based on

optimal foraging, foraging on food sources until their marginal gain drops below the

expected gain from other sources in the environment. The ants’ decisions to attack prey

items should therefore be dependent on the availability of more profitable alternative

sources of the nutrients commonly present in insect prey (Charnov et al. 1976).

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Alternative sources of protein may thus affect ants’ investment in hunting insect prey, but

this may also be affected by carbohydrate availability. Because of behavioural and

physiological demands, ant species have characteristic carbon:nitrogen ‘target ratios’ in

their diets (Davidson 2005, Ness et al. 2009). Prolonged exposure to diets with

suboptimal ratios can be physiologically costly (Grover et al. 2007, Dussutour &

Simpson 2009, Cook et al. 2009), so ants have evolved strategies to deal with unbalanced

food, including hoarding (Cook et al. 2009), selective extraction (Dussutour & Simpson

2009), and preferential collection of foods with ratios that counter standing imbalances

(Kay 2004, Cook & Behmer 2010, Cook et al. 2012). Davidson (2005) suggested that the

latter mechanism explained ant defence of plants, hypothesizing that nitrogen-deprived

ants were more likely to aggressively attack protein-rich herbivores. Ness et al. (2009)

demonstrated such an effect in the myrmecophilous cactus Ferocactus wislizeni, which is

facultatively visited by ants: supplementation with sugary syrup increased ant

aggressiveness and preference for proteinaceous baits, while supplementation with meat

had the opposite effect. Ferocactus wislizeni’s nectar is too carbohydrate-biased to meet

ants’ nutritional needs, and Ness et al. (2009) argued that compensating for this

imbalance drives ants to aggressively hunt herbivores.

In Ness et al.’s (2009) study, ants only facultatively visited the cacti, and received

primarily direct food benefits from killing herbivores. However, in obligate ant-plant

interactions, ants additionally receive indirect benefits from anti-herbivore defence.

Protection promotes plant growth (e.g. Frederickson & Gordon 2009, Frederickson et al.

2012a), which increases nesting space and thus ant colony size (Fonseca et al. 1993,

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Pringle et al. 2011, Handa et al. 2013), and, in turn, ant reproduction (Yu & Pierce 1998,

Frederickson & Gordon 2009). Because of these indirect benefits, obligate plant-ants

may have evolved defensive behaviours that are less sensitive to environmental variation.

In this study, we use the interaction between the tropical plant Cordia nodosa and its

symbiotic Allomerus octoarticulatus ants to explore how food affects plant defence in an

obligate ant-plant interaction.

Methods

Study System

Studies were conducted at the Los Amigos Research Centre (12°34’S, 70°05’W;

elevation ~270 m), in the Peruvian Amazon. The myrmecophyte Cordia nodosa Lam.

(Boraginaceae) is common at the field site. Each node on C. nodosa is directly associated

with a whorl of four leaves, as well as two additional leaves on the internode below.

Almost all of these nodes are swollen into hollow domatia, which serve as nesting sites

for plant-ants. Plants also produce cellular food bodies on all young tissues (Solano et al.

2005), though the nutritional contents of these food bodies is unknown. At our study site,

C. nodosa is most often inhabited by Allomerus octoarticulatus Wheeler (Formicidae:

Myrmicinae). Single monogynous colonies of this ant aggressively defend host plants,

reducing herbivory and promoting plant growth (Frederickson 2005, Frederickson &

Gordon 2009, Frederickson et al. 2012a). Allomerus octoarticulatus workers kill and eat

herbivores (Yu & Pierce 1998), constructing complex galleries on stems in order to trap

and capture prey (Dejean et al. 2005, Ruiz-González et al. 2011).

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Experiments

i) Ant Activity

In late June and early July 2011, we selected 40 individual C. nodosa with at least one

incompletely expanded whorl of young leaves, as both herbivory and ant defence are

concentrated on young leaves (Edwards et al. 2006). If the young leaves were originally

too high off the ground, we used cord to secure the branch in a position low enough to

observe.

To measure ant activity, we counted the total number of ants on the upper and lower

surfaces of the whorl of young leaves, as well as a comparable set of fully-expanded old

leaves at least two internodes away. To test how ants would respond to herbivory cues,

we randomly selected one of the three largest young leaves and used clean forceps to

make a 1 cm incision, 1 cm from the midvein and halfway down the length of the leaf.

Then, we counted the number of ants that recruited to the wound over five minutes.

We measured eight plants per day and randomly assigned two plants each to one of four

treatments: control, sugar, protein, and mixed. After counts, we affixed a 1.5 mL micro-

centrifuge tube to each plant, one node below the young domatium. This tube contained 1

mL of a treatment solution. In the “sugar” treatment, this tube contained a 0.15 g/mL

sucrose solution in distilled water. In the “protein” treatment, the tube contained a 0.17

g/mL solution of whey protein powder, equivalent to 0.15 g/mL of protein. The “mixed”

treatment solution contained 0.075 g/mL of sucrose and 0.085 g/mL of whey protein, and

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the control tubes contained only distilled water. Solutions were replaced weekly, and we

saw ants feeding on all the treatment solutions.

The experiment ended after four weeks. We repeated ant counts and wounding trials,

making a fresh incision on the same leaf. At this time, we also counted the number of

domatia on each plant, and measured the stem diameter at ground level, to see whether

plant size (as a proxy for colony size) might also affect ant behaviour. For 24 plants (6

per treatment), we counted the number of larvae, pupae, and workers in the domatium

attached to the young leaves.

ii) Ant Aggression

To test whether diet would directly affect attacks on herbivores, we conducted a similar

experiment in July 2011, using 36 plants from the same population, again each with

young leaves. Before the experiment, we measured the plants’ stem diameter at ground

level and height, and counted domatia. If necessary, we used cord to secure the branch

bearing young leaves in a lower position at least 24 hours before observations.

We tested the response of ants to herbivores. We tethered a eumastacid grasshopper to a

pin pushed through the largest of the four leaves attached to the domatium below the

whorl of expanding, young leaves. These grasshoppers, which are frequently found on C.

nodosa plants and consume their leaves, were collected the day before trials. In our trials,

the grasshoppers rarely attempted to feed, but moved about on the leaf until attacked by

ants. Each minute for ten minutes following placement, we counted the number of ants

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that were attacking (biting, stinging, or climbing on) the grasshopper. As attacks

generally plateaued after five minutes, we averaged the final five counts to generate an

aggression score.

We measured six plants per day, and assigned two to each of three treatments: sugar,

protein, and control. As in the previous study, 1 mL of treatment solution (0.20 g/mL

sucrose, 0.20 g/mL whey protein, or distilled water) was provided in a 1.5 mL micro-

centrifuge tube attached on the stem below the leaves on which grasshoppers were tested.

We replaced the food tubes weekly, and ran the experiment over the course of a month.

We conducted grasshopper trials before the experiment, and after two and four weeks.

We also photographed leaves before treatment and again after four weeks. We used

ImageJ (v. 1.43u, 2012 National Institutes of Health) to analyze the leaf photographs, and

measured accumulated herbivory as the difference in damage between the before and

after measures.

Statistical Analysis

In i), we analyzed the final counts of ants on young leaves, on old leaves, and recruiting

to wounds in models including treatment and the corresponding initial ant count as a

covariate, to control for natural variation in ant activity. For ant activity on old leaves and

recruitment to wounds, the treatment by covariate interactions were non-significant and

thus excluded (Engqvist 2005). For ant activity on young leaves, this interaction was

significant, and thus the data did not meet the ANCOVA assumption of homogeneity of

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regression slopes. When this assumption is violated, the main treatment effect depends

on the covariate value. Following Hendrix et al. (1982), we repeated the analysis, re-

centering the covariate to find the region in which treatment groups significantly

differed. Plant size measures (number of domatia and stem diameter) and date of

measurement were also tested for inclusion in the models but did not improve model fit.

We tested for treatment effects on counts of larvae, pupae, and workers in domatia in

similar models. Since initial counts would have required us to open (and destroy)

domatia, the initial number of active workers on the young leaves was instead included in

the model as a covariate. We also regressed final ant activity on young leaves against the

number of workers in domatia to see if this might explain treatment effects.

In ii), aggression scores were similarly analyzed in models including treatment and initial

aggression as a covariate, with the non-significant covariate by treatment interaction

excluded. Plant height was also included after a separate study (see Chapter 2) suggested

a strong influence on ant aggression, likely because plant size and colony size are

correlated (Frederickson & Gordon 2009, Frederickson et al. 2012a).

All of these data were highly over-dispersed, and so were modeled using generalized

linear models with a negative binomial error distribution, in R v 2.15.2. In each case, we

used the Vuong test (Vuong 1989) to confirm that the negative binomial distribution

improved fit over a comparable Poisson model. This test also indicated an excess of

zeroes in the data from ii), and so a zero-inflated negative binomial model was used.

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Effects of model terms were tested using Wald X2 tests. Multiple comparisons were

conducted using Tukey-corrected Wald Z-tests.

We measured herbivory as the difference in damaged area between initial and final

photographs. Three plants (two in the carbohydrate treatment, one in the control) were

excluded as entire leaves were lost, which can be caused by relatively small areas of

damage (e.g. on the basal portion of the midvein). Area of herbivore damage was log-

transformed to improve normality and was tested for treatment effects using GLMs with

a Gaussian error distribution. Additionally, we tested for an association between ant

aggression and herbivory using least-squares regression, as well as quantile regression, a

technique that tests for how predictor variables affect the median and other quantiles of a

response, rather than the mean (Cade & Noon 2003).

Results

i) Ant activity

Protein treatment lowered final ant activity on old leaves. Diet treatment had a significant

effect on the number of ants patrolling the surfaces of old leaves (X2=14.12, df=3,

p=0.0027, Fig. 1.1a). Final patroller counts were also higher in plants that had had high

initial counts (X2=25.51, df=1, p<0.0001), but plants in the protein treatment had lower

final counts than in the control (multiple comparison: Wald Z=-3.06, Tukey p=0.012) or

sugar treatments (Wald Z=-3.54, Tukey p=0.0023). Eight of ten plants treated with

protein had no active patrollers on older leaves at the end of the experiment.

16  

 

Diet treatment also affected final ant activity on most young leaves (Fig. 1.1b). On young

leaves, initial ant densities strongly influenced final measures (X2=6.14, df=1, p=0.013).

On the average leaf, treatment had a significant effect on patroller activity (X2=11.36,

df=3, p=0.0099), but the significant interaction between treatment and the initial activity

covariate (X2=15.72, df=3, p=0.0013) meant that the effect of treatment depended on the

value of this covariate. Re-analyzing the data centered at several covariate values showed

that treatment significantly (p<0.05) affected final ant counts on plants that had initial

counts up to 38 ants, which included 65% of plants (supplementary Fig. 1.1). In this

range, the sugar and mixed treatments had higher final ant counts than the control and

protein treatments, with significant contrasts (Tukey p<0.05) from the minimum to

median covariate values. Thus the presence of sugar led to higher ant activity on most

plants.

Protein supplementation resulted in fewer workers recruiting to wounds. Colonies that

recruited more initially also recruited more after treatment (X2=20.95, df=1, p<0.0001),

and recruitment was also affected by treatment (X2=20.10, df=3, p=0.0002). None of the

ten colonies in the nitrogen treatment showed any recruitment to the wound at the end of

the experiment, whereas workers did recruit on some plants in each of the other

treatments (mean workers ± SE: control, 3.1 ± 2.5; sugar, 1.9 ± 1.6; mixed, 3.0 ± 2.1;

protein, 0 ± 0).

Diet treatment also affected the number of workers inside the domatium attached to the

young leaves. After controlling for initial variation between ant colonies, worker counts

17  

 

within domatia were affected by treatment (X2=8.01, df=3, p=0.046; Fig. 1.2).

Specifically, domatia in the protein treatment had fewer workers than those in the sugar

treatment (Wald Z=-3.06, Tukey p=0.021). The treatment effects on the activity of

workers on leaves (Fig. 1.1b) were not explained by these differences in workers in the

domatia, as the regression of activity against domatium worker counts was not significant

(X2=1.86, df=1, p=0.17). Treatment did not affect the number of larvae (X2=0.52, df=3,

p=0.91) or pupae (X2=0.82, df=3, p=0.84) in the domatium.

ii) Ant Aggression

In ii), protein also reduced ants’ attacks towards herbivores. Treatment significantly

affected the attack score after a month (X2=8.56, df=2, p=0.014; Fig. 1.3), and ants

attacked grasshoppers less in the protein than control treatment (Wald Z=-2.92, Tukey

p=0.0092). Plant height (X2=2.63, df=1, p=0.11) did not predict final aggression to

herbivores, though ants that were more aggressive initially were also more aggressive in

final measures (X2=4.15, df=1, p=0.042). After only two weeks of treatment, initial

aggression significantly predicted aggression score (X2=6.90, df=1, p=0.0086), and

neither treatment (X2=2.22, df=2, p=0.33) nor plant height (X2=0.62, df=1, p=0.43) had

an effect.

Leaves with more aggressive ants tended to suffer less damage (X2=3.71, df=1, p=0.054;

Fig. 1.4), though the effect of treatment was not significant (X2=0.57, df=2, p=0.75; Fig.

1.5). Quantile regression showed that while the least-damaged plants had no or low

damage regardless of ant aggression levels (5th percentile of damage: t=0.00, p=1; 10th

18  

 

percentile: t=0.00, p=1; 25th percentile: t=-0.20, p=0.84), the maximum level of damage

suffered was much higher when plants had less aggressive ants (90th percentile: t=-4.39,

p=0.00012; 95th percentile: t=-3.88, p=0.00051). Thus, plants with less aggressive ants

had greater variation in damage.

Discussion

Allomerus octoarticulatus ants invest less in hunting herbivores and defending their host

plants when provided with alternative sources of protein. On both young and old leaves,

ants were less active in the protein treatment. Additionally, protein supplementation

completely eliminated recruitment to wounds and reduced ants’ attacks towards

grasshoppers. Allomerus octoarticulatus ants receive indirect benefits from protection of

their host trees: ants promote host growth, which benefits the ants through larger colony

sizes, reduced colony mortality, and increased reproduction (Yu & Pierce 1998,

Frederickson 2006, Frederickson & Gordon 2009, Frederickson et al. 2012a). But here,

we have shown that in large part, ants cooperate to accrue the direct benefits of food

acquisition. Though the net benefit of hunting insect herbivores is likely positive

(Frederickson et al. 2012a), constructing carton traps and subduing large prey are also

likely quite costly (Ruiz-González et al. 2011). Thus, when ants could obtain protein

from an alternative source without incurring these costs, they reduced investment in

hunting less-profitable insect prey, consistent with predictions of optimal foraging

(Charnov 1976, Kay 2002).

19  

 

Sugar supplementation typically increased ant activity on young leaves. Ants recognize

carbohydrates and protein as distinct resources, and high abundance of one should not

increase rejection of the other (Kay 2002). Instead, supplemental sugar appeared to fuel

high activity, as some authors have proposed (Davidson 1997, Pringle et al. 2011).

However, colonies did not increase recruitment to wounds or attacks on herbivores, and

so our results do not provide strong support for the hypothesis that carbohydrates fuel

predation by increasing the need for protein (Ness et al. 2009). However, plants could

still benefit from increased ant activity alone, if they remove pathogens from plants

(Letourneau 1998) or if herbivores are deterred by ant pheromones (Offenberg et al.

2004).

Compared with protein, the effects of carbohydate supplementation on ant behaviour

seem more variable (Petry et al. 2012). While several studies have reported positive

effects of carbohydrate supplementation on worker activity and aggression (Grover et al.

2007, Gonzalez-Teuber et al. 2012; aggression but not activity, Pringle et al. 2011),

others have suggested that increased activity may sometimes simply reflect increased

colony size (Kay et al. 2010). Some studies have even shown negative effects of

carbohydrates on activity levels (Cook et al. 2009, Grover et al. 2007, at high

carbohydrate levels), with knock-on effects on mutualists (Petry et al. 2012). We found

that the effects of sugar depended on initial activity levels: while sucrose boosted ant

activity in colonies with low to average initial activity, it did not affect colonies with very

high initial activity. These unaffected colonies may have simply had dietary treatment

effects diluted by higher worker numbers. Thus, the effect of carbohydrate addition is

20  

 

variable, but for the majority of colonies in our study, sugar supplementation led to

higher patroller activity.

Diet treatment may additionally have effects on colony demographics, as protein-treated

colonies had lower numbers of workers in their domatia compared with sugar-treated

colonies, after controlling for variation in initial densities. As we examined only the

single domatium associated with the young leaves and not the whole colony, it is

possible that protein supplementation causes ants to recruit in lower numbers to the

growing branch, as fewer workers are needed to collect the easily-accessible dissolved

protein. However, it is also possible that augmented protein caused higher worker

mortality, as increased mortality with excess dietary nitrogen has been reported in several

ant species (Dussutour & Simpson 2009, Cook et al. 2009, Kay et al. 2012). Mortality in

nitrogen-biased diets is likely associated with higher levels of the N-rich waste product

uric acid (Kay et al. 2012), as well as reduced worker lipid content (Cook et al. 2009).

Cook et al. (2009) argued that poor worker condition might have explained the reduced

foraging intensity they observed in their nitrogen-biased treatment. A similar effect may

have been at play in our study, as changes in worker numbers alone did not explain the

treatment’s effects on patroller activity.

In our study, colonies with more aggressive ants suffered lower herbivory. In the same

system, domatia containing more worker ants also had reduced herbivory on the

associated leaves (Frederickson et al. 2012b). Thus, by reducing aggression and the

density of workers in domatia, excess protein available to ants is likely harmful for

21  

 

plants. Though we were unable to detect a direct effect of diet treatment on leaf damage,

these effects were likely swamped by high variability in herbivory over the short time

scale of this study. On a whole plant level, persistent changes in diet would almost

certainly have effects on herbivory, and in turn, plant growth and fitness (Yu & Pierce

1998, Frederickson et al. 2012b).

Because protein depressed ant protection, while sugar increased ant activity, our results

agree with the suggestion that plants would benefit from producing high-carbohydrate,

low-nitrogen food (Davidson 2005, Ness et al. 2009). This may explain why extrafloral

nectar available to ants tends to be highly carbohydrate-biased (Ness et al. 2009), and

why hemipterans, which siphon carbohydrate-rich plant sap to ants, are ‘permitted’ by

the vast majority of ant-plants (Pringle et al. 2011). In this light, it is interesting that the

food bodies produced by many myrmecophytic plants are reasonably high in protein (e.g.

Heil et al. 1998, Fischer et al. 2002, Heil et al. 2004). In many of these cases, however,

ants are highly or exclusively dependent on plant-produced food for nourishment. Thus

plants must more closely match the nutritional requirements of their ants in order to

sustain defending colonies. This may also explain why lipids are often common in food

bodies (e.g. Heil et al. 1998, Fischer et al. 2002), even though ants may also hunt insects

as a source of this macronutrient (Thompson 1973). To better understand how ant-plants

balance keeping ant colonies healthy and keeping them aggressive, future work should

focus on plants like Cordia nodosa, whose ants are not so completely reliant on food

bodies or nectar.

22  

 

Though plant-ants like Allomerus octoarticulatus gain indirect fitness benefits by

protecting their host trees (Yu & Pierce 1998, Frederickson 2006, Frederickson &

Gordon 2009, Frederickson et al. 2012a), we have shown that food acquisition is a

significant proximate reason why ants protect host plants. When provided with a highly

profitable alternative source of protein, ants invested less in hunting prey, reducing their

activity, recruitment to wounds, and aggression towards herbivores. In contrast,

supplemental sugar appeared to fuel increased ant activity. Diet also affected the density

of workers in domatia, either by changing worker allocation within colonies, or by

affecting mortality. Thus, even in an obligate ant-plant system, cooperation can vary

depending on the availability of different resources.

Acknowledgements

We thank Antonio Coral, Shannon Meadley-Dunphy, and Jackie Awad for field

assistance; Jon Sanders, Lina Arcila Hernández, and Adam Cembrowski for assistance

with experimental design; the Amazon Conservation Association and the staff at Los

Amigos for support; and members of the Frederickson, Gilbert, Agrawal, and Thomson

Labs for comments on this manuscript. We thank MINAG-DGFFS for permits to do

research in Peru (RD No. 299-2011-AG-DGFFS-DGEFFS and RD No. 278-2012-AG-

DGFFS-DGEFFS). We thank funding from an NSERC Discovery Grant, a Connaught

New Researcher Award, and the University of Toronto to MEF, and from a Sigma Xi

Grant-in-Aid-of-Research to KMT.

23  

 

References

Bronstein, J. L. (1994). Our current understanding of mutualism. The Quarterly Review

of Biology, 69(1), 31–51.

Bronstein, J. L., Alarcón, R., & Geber, M. (2006). The evolution of plant-insect

mutualisms. The New Phytologist, 172(3), 412–28. doi:10.1111/j.1469-

8137.2006.01864.x

Cade, B. S., & Noon, B. R. (2003). A gentle introduction to quantile regression for

ecologists. Frontiers in Ecology and the Environment, 1(8), 412–420.

Charnov, E. L. (1976). Optimal foraging: Attack strategy of a mantid. The American

Naturalist, 110(971), 141–151.

Cook, S. C., & Behmer, S. T. (2010). Macronutrient regulation in the tropical terrestrial

ant Ectatomma ruidum (Formicidae): A field study in Costa Rica. Biotropica,

42(March 2009), 135–139.

Cook, S. C., Eubanks, M. D., Gold, R. E., & Behmer, S. T. (2009). Colony-level

macronutrient regulation in ants: Mechanisms, hoarding and associated costs.

Animal Behaviour, 79(2), 429–437. doi:10.1016/j.anbehav.2009.11.022

Cook, S. C., Wynalda, R. A., Gold, R. E., & Behmer, S. T. (2012). Macronutrient

regulation in the Rasberry crazy ant (Nylanderia sp. nr. pubens). Insectes Sociaux,

59(1), 93–100. doi:10.1007/s00040-011-0193-7

Davidson, D. W. (1997). The role of resource imbalances in the evolutionary ecology of

tropical arboreal ants. Biological Journal of the Linnean Society, 61(2), 153–181.

doi:10.1006/bijl.1996.0128

24  

 

Davidson, D. W. (2005). Ecological stoichiometry of ants in a New World rain forest.

Oecologia, 142(2), 221–31. doi:10.1007/s00442-004-1722-0

Dejean, A., Leroy, C., Corbara, B., Roux, O., Céréghino, R., Orivel, J., & Boulay, R.

(2010). Arboreal ants use the “Velcro(R) principle” to capture very large prey. PLoS

One, 5(6), e11331. doi:10.1371/journal.pone.0011331

Dejean, A., Solano, P. J., Ayroles, J., Corbara, B., & Orivel, J. (2005). Arboreal ants

build traps to capture prey. Nature, 434(April), 5174.

Dussutour, A., & Simpson, S. J. (2009). Communal nutrition in ants. Current Biology,

19(9), 740–4. doi:10.1016/j.cub.2009.03.015

Edwards, D. P., Hassall, M., Sutherland, W. J., & Yu, D. W. (2006). Selection for

protection in ant ant-plant mutualism: Host sanctions, host modularity, and the

principal-agent game. Proceedings of the Royal Society B, 273(1586), 595–602.

doi:10.1098/rspb.2005.3273

Engqvist, L. (2005). The mistreatment of covariate interaction terms in linear model

analyses of behavioural and evolutionary ecology studies. Animal Behaviour, 70(4),

967–971. doi:10.1016/j.anbehav.2005.01.016

Fischer, R. C., Richter, A., Wanek, W., & Mayer, V. (2002). Plants feed ants: food

bodies of myrmecophytic Piper and their significance for the interaction with

Pheidole bicornis ants. Oecologia, 133(2), 186–192.

Folgarait, P. J., & Davidson, D. W. (1995). Myrmecophytic Cecropia: Antiherbivore

defenses under different nutrient treatments. Oecologia, 104, 189–206.

Fonseca, C. R. (1993). Nesting space limits colony size of the plant-ant Pseudomyrmex

concolor. Oikos, 67(3), 473–482.

25  

 

Frederickson, M. E. (2005). Ant species confer different partner benefits on two

neotropical myrmecophytes. Oecologia, 143(3), 387–95. doi:10.1007/s00442-004-

1817-7

Frederickson, M. E. (2006). The reproductive phenology of an Amazonian ant species

reflects the seasonal availability of its nest sites. Oecologia, 149, 418–427.

doi:10.1007/s00442-006-0460-x

Frederickson, M. E., & Gordon, D. M. (2009). The intertwined population biology of two

Amazonian myrmecophytes and their symbiotic ants. Ecology, 90(6), 1595–607.

Frederickson, M. E., Ravenscraft, A., Arcila Hernández, L. M., Booth, G., Astudillo, V.,

& Miller, G. A. (2012). What happens when ants fail at plant defence? Cordia

nodosa dynamically adjusts its investment in both direct and indirect resistance

traits in response to herbivore damage. Journal of Ecology, 101(2), 400–409.

doi:10.1111/1365-2745.12034

Frederickson, M. E., Ravenscraft, A., Miller, G. A., Arcila Hernández, L. M., Booth, G.,

& Pierce, N. E. (2012). The direct and ecological costs of an ant-plant symbiosis.

The American Naturalist, 179(6), 768–78. doi:10.1086/665654

Gammans, N., Bullock, J. M., & Schönrogge, K. (2005). Ant benefits in a seed dispersal

mutualism. Oecologia, 146(1), 43–9. doi:10.1007/s00442-005-0154-9

González-Teuber, M., Silva Bueno, J. C., Heil, M., & Boland, W. (2012). Increased host

investment in extrafloral nectar (EFN) improves the efficiency of a mutualistic

defensive service. PLoS one, 7(10), e46598. doi:10.1371/journal.pone.0046598

Grover, C. D., Kay, A. D., Monson, J. A., Marsh, T. C., & Holway, D. A. (2007).

Linking nutrition and behavioural dominance: Carbohydrate scarcity limits

26  

 

aggression and activity in Argentine ants. Proceedings of the Royal Society B,

274(1628), 2951–7. doi:10.1098/rspb.2007.1065

Handa, C., Okubo, T., Yoneyama, A., Nakamura, M., Sakaguchi, M., Takahashi, N.,

Okamoto, M., et al. (2013). Change in biomass of symbiotic ants throughout the

ontogeny of a myrmecophyte, Macaranga beccariana (Euphorbiaceae). Journal of

Plant Research, 126(1), 73–9. doi:10.1007/s10265-012-0500-z

Heil, M, Fiala, B., & Kaiser, W. (1998). Chemical contents of Macaranga food bodies:

adaptations to their role in ant attraction and nutrition. Functional Ecology, 12(1),

117–122.

Heil, Martin. (2011). Nectar: Generation, regulation and ecological functions. Trends in

Plant Science, 16(4), 191–200. doi:10.1016/j.tplants.2011.01.003

Heil, Martin, Baumann, B., Kruger, R., & Linsenmair, K. E. (2004). Main nutrient

compounds in food bodies of Mexican Acacia ant-plants. Chemoecology, 14(1), 45–

52. doi:10.1007/s00049-003-0257-x

Heil, Martin, Hilpert, A., Fiala, B., & Linsenmair, K. E. (2001). Nutrient availability and

indirect (biotic) defence in a Malaysian ant-plant. Oecologia, 126(3), 404–408.

doi:10.1007/s004420000534

Heil, Martin, & McKey, D. (2003). Protective ant-plant interactions as model systems in

ecological and evolutionary research. Annual Review of Ecology, Evolution, and

Systematics, 34(1), 425–553. doi:10.1146/annurev.ecolsys.34.011802.132410

Hendrix, L. J., Carter, M. W., & Scott, D. T. (1982). Covariance analyses with

heterogeneity of slopes in fixed models. Biometrics, 38(3), 641–50.

27  

 

Herrera, C. M. (1984). A study of avian frugivores, bird-dispersed plants, and their

interaction in Mediterranean scrublands. Ecological Monographs, 54(1), 1–23.

Janzen, D. H. (1966). Coevolution of mutualism between ants and acacias in Central

America. Evolution, 20(3), 249–275.

Kay, A. D. (2002). Applying optimal foraging theory to assess nutrient availability ratios

for ants. Ecology, 83(7), 1935–1944.

Kay, A. D. (2004). The relative availabilities of complementary resources affect the

feeding preferences of ant colonies. Behavioral Ecology, 15(1), 63–70.

doi:10.1093/beheco/arg106

Kay, A. D., Shik, J. Z., Van Alst, A., Miller, K. A., & Kaspari, M. (2012). Diet

composition does not affect ant colony tempo. Functional Ecology, 26(2), 317–323.

doi:10.1111/j.1365-2435.2011.01944.x

Kay, A. D., Zumbusch, T., Heinen, J. L., Marsh, T. C., & Holway, D. A. (2010).

Nutrition and interference competition have interactive effects on the behavior and

performance of Argentine ants. Ecology, 91(1), 57–64.

Letourneau, D K. (1983). Passive aggression: An alternative hypothesis for the Piper-

Pheidole association. Oecologia, 60, 122–126.

Letourneau, Deborah K. (1998). Ants, stem-borers, and fungal pathogens: Experimental

tests of a fitness advantage in Piper ant-plants. Ecology, 79(2), 593–603.

Madden, D., & Young, T. P. (1992). Symbiotic ants as an alternative defense against

giraffe herbivory in spinescent Acacia drepanolobium. Oecologia, 91, 235–238.

Ness, J. H., Morris, W. F., & Bronstein, J. L. (2009). For ant-protected plants, the best

defense is a hungry offense. Ecology, 90(10), 2823–31.

28  

 

Offenberg, J., Nielsen, M. G., MacIntosh, D. J., Havanon, S., & Aksornkoae, S. (2004).

Evidence that insect herbivores are deterred by ant pheromones. Proceedings of the

Royal Society of London B, 271 Suppl, S433–5. doi:10.1098/rsbl.2004.0210

Petry, W. K., Perry, K. I., & Mooney, K. a. (2012). Influence of macronutrient imbalance

on native ant foraging and interspecific interactions in the field. Ecological

Entomology, 37(3), 175–183. doi:10.1111/j.1365-2311.2012.01349.x

Pringle, E. G., Dirzo, R., & Gordon, D. M. (2011). Indirect benefits of symbiotic

coccoids for an ant-defended myrmecophytic tree. Ecology, 92(1), 37–46.

Quinlan, R. J., & Cherrett, J. M. (1978). Aspects of the symbiosis of the leaf-cutting ant

Acromyrmex octospinosus (Reich) and its food fungus. Ecological Entomology, 3,

221–230.

Ruiz-González, M. X., Malé, P.-J. G., Leroy, C., Dejean, A., Gryta, H., Jargeat, P.,

Quilichini, A., et al. (2011). Specific, non-nutritional association between an

ascomycete fungus and Allomerus plant-ants. Biology Letters, 7(3), 475–9.

doi:10.1098/rsbl.2010.0920

Soares, M. C., Bshary, R., Mendonça, R., Grutter, A. S., & Oliveira, R. F. (2012).

Arginine vasotocin regulation of interspecific cooperative behaviour in a cleaner

fish. PLoS One, 7(7), e39583. doi:10.1371/journal.pone.0039583

Solano, P.-J., Belin-Depoux, M., & Dejean, A. (2005). Formation and structure of food

bodies in Cordia nodosa (Boraginaceae). Comptes Rendus Biologies, 328(7), 642–7.

doi:10.1016/j.crvi.2005.05.004

29  

 

Thompson, S. N. (1973). A review and comparative characterization of the fatty acid

compositions of seven insect orders. Comparative Biochemistry and Physiology,

45B, 467–482.

Trager, M. D., Bhotika, S., Hostetler, J. a, Andrade, G. V, Rodriguez-Cabal, M. a,

McKeon, C. S., Osenberg, C. W., et al. (2010). Benefits for plants in ant-plant

protective mutualisms: A meta-analysis. PLoS one, 5(12), e14308.

doi:10.1371/journal.pone.0014308

Vuong, Q. H. (1989). Likelihood Ratio Tests for model selection and non-nested

hypotheses. Econometrica, 57(2), 307–333.

Way, M. J. (1963). Mutualism between ants and honeydew-producing homoptera.

Annual Review of Entomology, 8, 307–344.

Yu, D. W., & Pierce, N. E. (1998). A castration parasite of an ant-plant mutualism.

Proceedings of the Royal Society B, 265, 375–382.

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Figures

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Figure 1.1. Number of workers on (a) old leaves and (b) young leaves in the four

treatments. Counts are presented as least-squares means (± SE) to correct for significant

effects of the covariate. In (a), groups sharing letters are not significantly different

according Tukey multiple comparisons. Multiple comparisons for (b) varied according to

the value of initial worker densities (see text).

32  

 

Figure 1.2. Mean (± SE) numbers of workers found in the domatium attached to the

young leaves. Groups sharing letters are not significantly different according Tukey

multiple comparisons.

33  

 

Figure 1.3. Mean (± SE) aggression score (average attacks on grasshoppers across each

minute for five minutes) measured four weeks after treatment. Groups sharing letters are

not significantly different according Tukey multiple comparisons.

34  

 

Figure 1.4. Area of damaged tissue on the focal set of young leaves vs aggression score

(average attacks on grasshoppers across each minute for five minutes), with least-

squares regression line. Each point represents a plant.

35  

 

Figure 1.5. Mean (± SE) area of damaged tissue on the focal set of young leaves in

plants in part ii, by treatment.

36  

 

Supplementary Figure 1.1. Activity of workers on young leaves at final vs initial counts,

in the sugar (black circles), mixed (white circles), control (black triangles) and protein

(white triangles) treatments. Diet treatment had a significant effect on final worker

counts on plants with initial worker counts less than 38 (grey line). Each point represents

a plant.

37  

 

CHAPTER TWO

Activation of protein kinase G (PKG) makes plant-protecting ants better mutualists

Abstract

Almost nothing is known about the molecular basis of cooperation in plant-animal

mutualisms. In the Peruvian Amazon, we used a pharmacological manipulation to

examine the interaction between a plant-dwelling ant species (Allomerus octoarticulatus)

and the host plants it protects against herbivores (Cordia nodosa). We tested for an effect

of protein kinase G (PKG), an enzyme encoded by the gene foraging, as this enzyme has

been linked to relevant behaviours in other taxa. When we added the PKG activator 8-Br-

cGMP to the ants’ diet, ants behaved more aggressively towards herbivores, resulting in

less herbivore damage to their host plants. Our finding strongly suggests that foraging

mediates this ant-plant interaction.

Introduction

Almost all organisms are involved in cooperative interactions within or between species

(Bronstein 1994, Wilson & Hölldobler 2005, Bronstein et al. 2006, Clutton-Brock 2009).

These interactions have driven major ecological and evolutionary transitions (Redecker

et al. 2000, Bronstein et al. 2006, Janson 2008, Ramírez et al 2011, Corradi & Bonfante

2012), but the molecular basis for cooperation in most systems is unknown. Within

species, recent work has identified the genetic elements behind higher levels of social

organization (e.g. Ross et al. 2003, Ott et al. 2011, Wang et al. 2013). In mutualisms

38  

 

between species, the existence of inter-clone (Brock et al. 2011, Vantaux et al. 2011) and

inter-population (Rudgers & Gardener 2004) variation in cooperative phenotypes

suggests a genetic basis for these traits, but the actual molecular basis for mutualism

remains almost completely unknown, especially outside plant-microbe mutualisms.

Understanding molecular mechanisms lends insight into mutualism evolution. For

instance, in three clades of a tropical plant family, Zhang et al. (2012) demonstrated that

shifts in the community of pollinators led to convergent changes in floral signaling genes,

suggesting a common genetic predisposition towards certain signal changes. In legumes

and rhizobia, identifying nodule production genes and examining them for signatures of

selection has increased our understanding of the adaptive history of these mutualisms

(Oldroyd & Long 2003, Ané et al 2004, De Mita et al. 2007). Associating variation in

cooperation with allelic variation can also advance our understanding of mutualism

stability. If less cooperative partners are “cheaters” (or “defectors”), then they should

benefit from uncooperative behaviour, and less cooperative alleles should show signs of

recent positive selection. If less cooperative partners are simply “defective” (sensu

Friesen 2012), and not cooperating is maladaptive, then we should detect purifying

selection on the locus of interest, in response to partner feedbacks (or other proposed

mechanisms that maintain cooperation; Sachs et al. 2004, Weyl et al. 2010, Archetti et al.

2011). However, in most systems such analyses are impossible because we do not know

which genes affect mutualist quality.

39  

 

In animals, cooperation depends largely on behaviour, making it possible to leverage our

growing understanding of behavioural genetics to study the molecular underpinnings of

animal cooperation (e.g. in social insects, Ben-Shahar et al. 2002, Lucas & Sokolowski

2009, Ingram et al. 2011). Recent work has identified a number of genes involved in

feeding, learning, mating, social interactions, and other behaviours (Fitzpatrick &

Sokolowski 2004, Fitzpatrick et al. 2005). Despite the ecological relevance of these

traits, the impacts of these genes on the wider environment (their “extended phenotypes”;

Dawkins 1982) have rarely been explored, though Weber et al. (2013) recently

demonstrated the extended phenotype of loci involved in deer mouse nest construction.

The potential to detect extended phenotypic effects is particularly high in intimate

interspecific interactions, such as symbioses. Hoover et al. (2011) showed that a viral

gene induces climbing behaviour in its host, thereby increasing transmission of the

parasite to new hosts. In plant-animal mutualisms, animal phenotypes extend to the

performance and fitness of their plant partners, and feedback through this process drives

coevolution. Yet the genes underlying extended phenotypes in plant-animal mutualisms

are completely unknown.

One taxonomically and ecologically abundant example of plant-animal cooperation is

myrmecophytism, a protective mutualism between ants and plants (Heil & McKey 2003,

Bronstein et al. 2006, Trager et al. 2010). Myrmecophytic plants produce hollow housing

structures and often food rewards for ants (Janzen 1966, Folgarait & Davidson 1995,

Solano et al. 2005). ‘Plant-ants’ living in these housing structures (‘domatia’) patrol plant

structures and often deter herbivores, pathogens, and encroaching plant competitors

40  

 

(Trager et al. 2010). Ants collect plant-derived food and often kill and eat insect

herbivores, and therefore they forage, defend their nest, and protect host plants through

the same activities (e.g. Yu & Pierce 1998, Dejean et al. 2005, 2010). The gene foraging

influences movement and feeding in several taxa (Fitzpatrick & Sokolowski 2004), and

so we predicted that an ortholog of foraging might be involved in this interaction. This

gene encodes one form of cGMP-dependent protein kinase (PKG), and was originally

identified as influencing movement during feeding in Drosophila melanogaster (Osborne

et al. 1997). Allelic differences also affect response to sucrose (Belay et al. 2007) and

resilience to starvation in these flies (Donlea et al. 2012). Throughout social

Hymenoptera, foraging workers have shown different PKG activity or foraging gene

expression than nursing workers (Ben-Shahar et al. 2002, Ingram et al. 2005, Tobback et

al. 2008, Kodaira et al. 2009, Ingram et al. 2011, Tobback et al. 2011), and in the ant

Pheidole pallidula, PKG mediated a trade-off between foraging and nest-defence

behaviour (Lucas & Sokolowski 2009). Experimentally, providing organisms with 8-

bromoguanosine 3’,5’-cyclic monophosphate (8-Br-cGMP) increased PKG activity and

caused them to express the same behavioural phenotypes associated with high expression

of the gene (Ben-Shahar et al. 2002, Lucas & Sokolowski 2009). These manipulations,

however, occurred in a laboratory setting, and only measured the effects on the single

species of interest.

Here, we examined whether PKG might influence cooperation between the tropical ant

Allomerus octoarticulatus and its Cordia nodosa host trees, as ants’ foraging and nest

defence behaviour form the basis of plant protection. Working with colonies inhabiting

41  

 

trees in the field, we fed the ants the PKG activator 8-Br-cGMP and measured the effects

of this treatment on ant aggression towards herbivores, and plant performance. Thus, we

asked: Does PKG influence workers’ attacks on herbivores? And do these effects extend

to affect the amount of herbivory plants experience?

Methods

Study System

We studied the ant-plant Cordia nodosa Lam. (Boraginaceae) and its most common ant

associate, Allomerus octoarticulatus Wheeler (Formicidae: Myrmicinae), at the Los

Amigos Research Center (12°34’S, 70°05’W; elevation ~270 m) in the Peruvian

Amazon. This site is mostly primary tropical rain forest, with a mix of floodplain and

terra firme habitats. A single A. octoarticulatus colony lives in one individual C. nodosa

tree. Workers patrol leaves, especially young leaves, and aggressively defend their plant

against herbivores (Frederickson et al. 2012a), which promotes plant growth

(Frederickson 2005, Frederickson & Gordon 2009). Cordia nodosa trees produce hollow

stem swellings (domatia, see Fig. 2.1) whether or not ants are present. There is one

domatium per internode, and each domatium is associated with a whorl of four leaves;

two additional leaves are on the stem below (Fig. 2.1). Inside the domatia, ants rear their

young (eggs, larvae, and pupae, collectively called brood) and also tend scale insects

(Hemiptera: Sternorrhyncha: Coccoidea) and eat the honeydew these scale insects

produce (Frederickson et al. 2012a). The ants also eat many of the insect herbivores they

attack, as well as the miniscule food bodies that grow on C. nodosa’s young leaves (Yu

& Pierce 1998, Frederickson et al. 2012a).

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Experiment

In January 2012, we selected 40 individuals of Cordia nodosa occupied by Allomerus

octoarticulatus that had young (i.e., incompletely expanded) leaves, as both herbivory

and ant defence are concentrated on young leaves (Edwards et al. 2006). If young leaves

were initially too far off the ground to observe with ease, we used cord to secure the

branch in a lower position, at least 24 hours before observations. On each of the first four

days of the experiment, we measured initial ant aggression and standing herbivory (see

below) on ten plants and then randomly assigned them to two treatments (control or PKG

activator) after stratifying by estimated herbivore damage. In both treatments, we

attached a 2-mL micro-centrifuge tube containing a sugar solution to the stem below the

leaves where we measured aggression (Fig. 2.1). In the activator treatment, this tube

contained a 2.5 mM 8-Br-cGMP solution with 20% w/v sucrose. The control treatment

was 20% w/v sucrose only. We replaced the food tubes 7 and 13 days after initial

measurements, and then measured ant aggression and herbivory again on the 14th day.

We regularly observed ants in both treatments feeding on the solutions in the tubes.

Ant Attacks

We measured ant attacks towards common herbivores of C. nodosa, grasshoppers in the

family Eumasticidae (cf. Paramastax spp.). These grasshoppers are commonly found on

C. nodosa and other ant-associated plants, and did consume C. nodosa leaves in

preliminary trials. Because Lucas and Sokolowski (2009) showed that PKG can affect

ant aggression towards conspecific ants from other colonies, we also measured ant

43  

 

aggression towards virgin queens from a different A. octoarticulatus colony (hereafter,

alates), which ants may recognize as conspecific intruders, and not herbivores. We

collected alates (from source colonies which were not among the 40 in our experiment)

and grasshoppers (from Cordia nodosa and other ant-plants) one to three days before use.

We tethered each insect to a leaf by tying the insect to a pin with thread and pushing the

pin through the leaf (about 2 cm from the domatium entrance, see Fig. 2.1). Expanding

young leaves are very fragile, so we tethered insects to leaves associated with the

domatium below the young leaves (Fig. 2.1). We measured ant aggression towards one

grasshopper and one alate per tree, presenting the two insects in random order. Every

minute for five minutes, we counted the number of ants stinging, biting, or walking on

the insect, and then removed the insect. We waited five minutes between trials, and then

attached the other insect to the opposite leaf (Fig. 2.1) and again measured how many

ants responded. We generated an aggression score for each insect by averaging the five

counts. We used the same protocol to measure ant aggression to herbivores and alates

both before and after the two-week experiment.

Herbivory and Plant Traits

At the beginning of the experiment, we also counted the number of domatia on the plant,

measured height to the highest point, and measured stem diameter at ground level. We

also measured the width and length (excluding the petiole) of the four young leaves

attached to the domatium. Before and after the experiment, we photographed damaged

leaves against a transparent grid (for scale). We analyzed the photographs in ASSESS (v.

1.0, 2002 American Phytopathological Society), a program that allows the user to

44  

 

measure total leaf area and damage by selecting green, brown, or missing areas (see Prior

& Hellman 2010).

Statistical Analysis

We used generalized linear models with a negative binomial error distribution (in R v.

2.15.2) to analyze ant aggression scores for grasshoppers and alates, with treatment as a

main effect and initial aggression as a covariate. Because colony size may affect the

number of ants responding to a tethered insect and is correlated with plant size

(Frederickson & Gordon 2009, Frederickson et al. 2012a), we also included plant height

as a covariate; plant height predicted aggression more strongly than our other measures

of plant size (stem diameter and domatium counts). Finally, we included the date of the

behavioral assays as a random factor, to account for possible effects of variation in

weather. Interactions between the treatment and covariates were non-significant and were

excluded from the model (Engqvist 2005).

Herbivore damage was log-transformed to improve normality, and analyzed using

generalized linear models with a Gaussian error distribution. We excluded one control

plant and two treatment plants whose focal leaves were all missing, as many factors can

cause plants to shed leaves. Herbivory peaked on mid-sized leaves (supplementary Fig.

2.1), and so our analyses of herbivory included treatment and a quadratic leaf size

covariate (the linear term was not significant and was excluded). The treatment by

covariate interaction was significant, so the data did not meet the assumption of

homogeneity of regression slopes. Because this assumption was violated, the main effect

45  

 

of treatment depended on the value of the covariate; following White (2003), we used the

Johnson-Neyman procedure to isolate the range of leaf sizes where herbivory differed

between treatments. We also ran separate quadratic regressions to confirm that treatment

changed the relationship between leaf size and herbivory.

Results

PKG activation changed how many ants attacked herbivores. Activator treatment

significantly increased ant aggression towards grasshoppers (X2=6.07, df=1, p=0.014;

Fig. 2.2). Colonies on larger plants were also more aggressive (X2=7.46, df=1,

p=0.0063), and colonies that were initially more aggressive remained more aggressive in

final measures (X2=7.91, df=1, p=0.0049). Analyzing the treatments separately, the final

aggression of ants in the control was correlated with their initial aggression (X2=7.68,

df=1, p=0.0056; Fig. 2.3a), but PKG activator treatment broke down this relationship

(X2=0.75, df=1, p=0.39; Fig. 2.3b). Ants’ attacks towards conspecific alates were not

affected by treatment, plant size, or initial aggression (results not shown).

Leaves received less damage in the PKG activator than in the control treatment (Fig.

2.4). For average-sized leaves, damage was significantly higher on control than PKG

activator treated plants (X2=9.72, df=1, p=0.0077), but since the treatment by leaf size

interaction was significant (X2=5.12, df=1, p=0.024), the treatment effect depended on

leaf size. The damage in the control plants was significantly higher (p<0.05) for leaves in

whorls in which the largest leaf was greater than 1.5 and more than 6.5 cm wide

(supplementary Fig. 2.1), which represents over half of the leaves measured. Separate

46  

 

quadratic regressions on the two treatments confirmed that leaf damage peaked on mid-

sized leaves in the control (X2=6.66, df=1, p=0.0099), but remained low on leaves of all

sizes in the PKG activator treatment (X2=0.19, df=1, p=0.67; supplementary Fig. 2.1).

Thus, PKG activator treatment reduced herbivory on mid-sized leaves.

Discussion

When we fed A. octoarticulatus ants with the PKG activator, patrolling workers became

more aggressive towards herbivores. This effect extended to impact the ants’ host plants,

protecting them from damage during a developmental window when they may be most

vulnerable to folivory. We have thus shown for the first time that the behavioural effects

of PKG activation are detectable in a field setting. Though we did not directly assay

enzyme activity or gene expression, in flies (e.g. Dawson-Scully et al. 2010) and other

Hymenoptera (Ben-Shahar et al. 2002, Lucas & Sokolowski 2009), applying the PKG

activator has increased PKG activity and elicited the same behaviours normally

associated with high foraging gene. This suggests that the defensive behaviour we

measured here was similarly influenced by an ortholog of that gene. If so, then foraging’s

extended phenotype acts through ant aggression to impact plant performance in this

system.

Ant aggression also displayed substantial natural variation. Colonies on larger plants

were more aggressive; since plant and colony size are correlated in this system

(Frederickson & Gordon 2009, Frederickson et al. 2012a), this likely reflects an effect of

colony size on protection, which has been previously demonstrated (Heil et al. 2001,

47  

 

Pringle et al. 2011). However, even after accounting for this effect, initially aggressive

colonies remained highly aggressive at the end of the experiment, particularly in the

control treatment. This may reflect other variation in the demographics of ant colonies

(e.g. number of brood or alates) or in background dietary state (see Chapter One), but

could also indicate persistent variation in the expression of foraging or other genes

affecting behaviour. Further study of the genetic architecture of these behavioural

phenotypes will illuminate precisely which genes these might be and their sensitivity to

environmental context, but the fact that PKG activation broke the association between

initial and final aggression suggests an overriding role for a foraging ortholog.

Even with substantial variation in aggression, we detected effects of PKG activation on

leaf damage. This effect was restricted to mid-sized leaves, as very small and large leaves

had low herbivory in both treatments. Grangier et al. (2008) similarly found that the

presence of Allomerus decemarticulatus ants affected herbivory only on mid-sized leaves

of their Hirtella physophora host plants; as in our study, very small and very large leaves

suffered negligible herbivory regardless of ants’ presence. Large, expanded leaves were

likely effectively protected by chemical and structural defences (e.g. toughness; Coley

1983, Kursar & Coley 1992, Frederickson, unpublished data). Very small leaves, in

contrast, were likely protected by high trichome density (Grangier et al. 2008) or by

biotic defence – food bodies are produced primarily on young leaves in C. nodosa

(Solano et al. 2005), and ant densities tend to be highest on these leaves in C. nodosa

(Edwards et al. 2006), as in many myrmecophytes (e.g. Gaume et al. 1997, Linsenmair et

al. 2001, Debout et al. 2005). As they grow, leaves may commonly experience a period

48  

 

of vulnerability as biotic defences fall off, before abiotic defences reach full

effectiveness. However, treatment with the PKG activator reduced this vulnerability,

extending the defensive activity of ants to protect mid-sized leaves (supplementary Fig.

2.1). Though in the present study the activator’s effect was restricted to this size class, by

definition all leaves will pass through it while expanding. A longer study would likely

detect a broader effect of PKG activation on herbivory.

Such a long-term study would likely also show effects of PKG activity on the fitness of

both partners. Over the two weeks of our study, plants lost an average of 15 and 6 cm2 of

leaf tissue in the control and activator treatments, respectively, corresponding to

approximately 4.3% and 1.6% of leaf area. In the same population, Frederickson et al.

(2012b) showed that comparable differences in folivory had substantial effects on plant

height and domatium production. As larger plants produce more fruit (Yu & Pierce

1998), and house colonies with reduced mortality and increased reproduction

(Frederickson & Gordon 2009), increased PKG activity and expression should be

beneficial for both partners.

However, the high pleiotropy of foraging may suggest potential costs of higher activity

of expression. foraging orthologs are known to influence the allocation of workers to

different tasks in social insects (Ben-Shahar et al. 2002, Ingram et al. 2005, Lucas &

Sokolowski 2009, Tobback et al. 2008, Ingram et al. 2011), so increasing allocation to

protection may be costly to ants through reduced allocation to other tasks like nursing.

foraging may also affect other behavioural or physiological traits. In D. melanogaster

49  

 

fruit flies, for instance, alternative alleles are associated with differences in sleep,

courtship, habituation, learning, and memory formation, as well as resistance to sleep

deprivation, starvation, anoxia, and high temperatures (Belay et al. 2007, Mery et al.

2007, Dawson-Scully et al. 2010, Chen et al. 2011, Burns et al. 2012, Donlea et al. 2012,

Eddison et al. 2012). Expression differences also influence sleep, habituation, and

movement in C. elegans (L’Etoile et al. 2002, Fujiwara et al. 2002, Raizen et al. 2008),

as well as more physiological traits like body size, fat storage, and longevity (Raizen et

al. 2006). Thus, while high PKG activity has short-term benefits for plants, the long-term

effects on ants may be more complex.

Regardless, if foraging is important to ant-plant cooperation, it suggests several avenues

for future research. For instance, the pleiotropic effects of foraging described above (e.g.

costs to fat storage, longevity; Raizen et al. 2006) suggest hypotheses for tradeoffs and

costs that plant-defending ants might experience. If foraging plays a role in this

interaction, it also suggests mechanisms by which host plants might manipulate ant

behaviour to their benefit. PKG is activated by cGMP, which is also a known signaling

molecule in plants (Isner et al. 2012) – our results suggest that plants could benefit if it is

possible to provide cGMP to ants through food bodies, or even through phloem sap via

scale insects. PKG activity is also responsive to starvation (Lucas & Sokolowski 2009,

Sokolowski 2010), and so our results may suggest a molecular reason why

myrmecophytic plants often feed ants (e.g. Folgarait & Davidson 1995, Solano et al.

2005): it may allow plants to keep ants’ PKG activity at optimal levels. How PKG

50  

 

mediates cooperation in this and other systems merits further exploration, but our results

suggest some immediate directions.

The molecular basis for cooperation between plants and animals is largely unexplored,

precluding the kind of evolutionary genetic studies that have illuminated the adaptive

history of other mutualisms (e.g. De Mita et al. 2007). Here, we show that PKG, an

enzyme with diverse behavioural effects across taxa, also affects the protection that ants

provide to their host plants. Future work is needed to confirm a role for the foraging gene

in this interaction, but our study suggests that it does influence ants’ cooperative

behaviour, and that its phenotype extends to affect the performance of their plant

partners.

Acknowledgments

We thank Antonio Coral and Adam Cembrowski for field assistance; the Amazon

Conservation Association and the staff at Los Amigos for support; and members of the

Frederickson, Gilbert, Agrawal, and Thomson labs at the University of Toronto for

comments on this manuscript. We thank MINAG-DGFFS for permits to do research in

Peru (RD No. 299-2011-AG-DGFFS-DGEFFS and RD No. 278-2012-AG-DGFFS-

DGEFFS). We thank funding from an NSERC Discovery Grant, a Connaught

New Researcher Award, and the University of Toronto to MEF, and from a Sigma Xi

Grant-in-Aid-of-Research to KMT.

51  

 

References

Ané, J.-M., Kiss, G. B., Riely, B. K., Penmetsa, R. V., Oldroyd, G. E. D., Ayax, C.,

Lévy, J., et al. (2004). Medicago truncatula DMI1 required for bacterial and fungal

symbioses in legumes. Science, 303, 1364–1367.

Archetti, M., Scheuring, I., Hoffman, M., Frederickson, M. E., Pierce, N. E., & Yu, D.

W. (2011). Economic game theory for mutualism and cooperation. Ecology Letters,

14(12), 1300–12. doi:10.1111/j.1461-0248.2011.01697.x

Belay, A. T., Scheiner, R., So, A. K., Douglas, S. J., Chakaborty-Chatterjee, M., Levine,

J. D., & Sokolowski, M. B. (2007). The foraging gene of Drosophila melanogaster:

Spatial-expression analysis and sucrose responsiveness. The Journal of

Comparative Neurology, 582(December 2006), 570–582. doi:10.1002/cne

Ben-Shahar, Y. (2005). The foraging gene, behavioral plasticity, and honeybee division

of labor. Journal of Comparative Physiology A, 191(11), 987–94.

doi:10.1007/s00359-005-0025-1

Ben-Shahar, Y., Robichon, A., Sokolowski, M. B., & Robinson, G. E. (2002). Influence

of gene action across different time scales on behavior. Science, 296(5568), 741–4.

doi:10.1126/science.1069911

Brock, D. a, Douglas, T. E., Queller, D. C., & Strassmann, J. E. (2011). Primitive

agriculture in a social amoeba. Nature, 469(7330), 393–6. doi:10.1038/nature09668

Bronstein, J. L. (1994). Our current understanding of mutualism. The Quarterly Review

of Biology, 69(1), 31–51.

52  

 

Bronstein, J. L., Alarcón, R., & Geber, M. (2006). The evolution of plant-insect

mutualisms. The New Phytologist, 172(3), 412–28. doi:10.1111/j.1469-

8137.2006.01864.x

Burns, J. G., Svetec, N., Rowe, L., Mery, F., Dolan, M. J., Boyce, W. T., & Sokolowski,

M. B. (2012). Gene-environment interplay in Drosophila melanogaster: Chronic

food deprivation in early life affects adult exploratory and fitness traits. Proceedings

of the National Academy of Sciences of the United States of America, 109, 17239–

44. doi:10.1073/pnas.1121265109

Chen, A., Kramer, E. F., Purpura, L., Krill, J. L., Zars, T., & Dawson-Scully, K. (2011).

The influence of natural variation at the foraging gene on thermotolerance in adult

Drosophila in a narrow temperature range. Journal of Comparative Physiology A,

197(12), 1113–8. doi:10.1007/s00359-011-0672-3

Clutton-Brock, T. (2009). Cooperation between non-kin in animal societies. Nature,

462(7269), 51–7. doi:10.1038/nature08366

Coley, P. D. (1983). Herbivory and defensive characteristics of tree species in a lowland

tropical forest. Ecological Monographs, 53(2), 209–234.

Corradi, N., & Bonfante, P. (2012). The arbuscular mycorrhizal symbiosis: Origin and

evolution of a beneficial plant infection. PLoS Pathogens, 8(4), e1002600.

doi:10.1371/journal.ppat.1002600

Dawkins, R. (1982). The Extended Phenotype. Oxford: Oxford University Press.

Dawson-Scully, K., Bukvic, D., Chakaborty-Chatterjee, M., Ferreira, R., Milton, S. L., &

Sokolowski, M. B. (2010). Controlling anoxic tolerance in adult Drosophila via the

53  

 

cGMP-PKG pathway. The Journal of Experimental Biology, 213, 2410–2416.

doi:10.1242/jeb.041319

De Mita, S., Ronfort, J., McKhann, H. I., Poncet, C., El Malki, R., & Bataillon, T.

(2007). Investigation of the demographic and selective forces shaping the nucleotide

diversity of genes involved in nod factor signaling in Medicago truncatula.

Genetics, 177(4), 2123–33. doi:10.1534/genetics.107.076943

Debout, G., Schatz, B., & McKey, D. (2005). Behavioural traits mediating effects of two

plant-ants on their specific myrmecophyte host. Insectes Sociaux, 52(3), 205–211.

doi:10.1007/s00040-004-0795-4

Dejean, A., Leroy, C., Corbara, B., Roux, O., Céréghino, R., Orivel, J., & Boulay, R.

(2010). Arboreal ants use the “Velcro(R) principle” to capture very large prey. PLoS

One, 5(6), e11331. doi:10.1371/journal.pone.0011331

Dejean, A., Solano, P. J., Ayroles, J., Corbara, B., & Orivel, J. (2005). Arboreal ants

build traps to capture prey. Nature, 434(April), 5174.

Donlea, J., Leahy, A., Thimgan, M. S., Suzuki, Y., Hughson, B. N., Sokolowski, M. B.,

& Shaw, P. J. (2012). Foraging alters resilience/vulnerability to sleep disruption and

starvation in Drosophila. Proceedings of the National Academy of Sciences of the

United States of America, 109(7), 2613–26188. doi:10.1073/pnas.1112623109

Eddison, M., Belay, A. T., Sokolowski, M. B., & Heberlein, U. (2012). A genetic screen

for olfactory habituation mutations in Drosophila: analysis of novel foraging alleles

and an underlying neural circuit. PLoS One, 7(12), e51684.

doi:10.1371/journal.pone.0051684

54  

 

Edwards, D. P., Hassall, M., Sutherland, W. J., & Yu, D. W. (2006). Selection for

protection in ant ant-plant mutualism: Host sanctions, host modularity, and the

principal-agent game. Proceedings of the Royal Society B, 273(1586), 595–602.

doi:10.1098/rspb.2005.3273

Engqvist, L. (2005). The mistreatment of covariate interaction terms in linear model

analyses of behavioural and evolutionary ecology studies. Animal Behaviour, 70(4),

967–971. doi:10.1016/j.anbehav.2005.01.016

Fitzpatrick, M. J., Ben-Shahar, Y., Smid, H. M., Vet, L. E. M., Robinson, G. E., &

Sokolowski, M. B. (2005). Candidate genes for behavioural ecology. Trends in

Ecology & Evolution, 20(2), 96–104. doi:10.1016/j.tree.2004.11.017

Fitzpatrick, M. J., & Sokolowski, M. B. (2004). In search of food: Exploring the

evolutionary link between cGMP-dependent Protein Kinase (PKG) and behaviour.

Integrative and Comparative Biology, 36, 28–36.

Folgarait, P. J., & Davidson, D. W. (1995). Myrmecophytic Cecropia: Antiherbivore

defenses under different nutrient treatments. Oecologia, 104, 189–206.

Frederickson, M. E. (2005). Ant species confer different partner benefits on two

neotropical myrmecophytes. Oecologia, 143(3), 387–95. doi:10.1007/s00442-004-

1817-7

Frederickson, M. E., & Gordon, D. M. (2009). The intertwined population biology of two

Amazonian myrmecophytes and their symbiotic ants. Ecology, 90(6), 1595–607.

Frederickson, M. E., Ravenscraft, A., Arcila Hernández, L. M., Booth, G., Astudillo, V.,

& Miller, G. A. (2012). What happens when ants fail at plant defence? Cordia

nodosa dynamically adjusts its investment in both direct and indirect resistance

55  

 

traits in response to herbivore damage. Journal of Ecology, 101(2), 400–409.

doi:10.1111/1365-2745.12034

Frederickson, M. E., Ravenscraft, A., Miller, G. a, Arcila Hernández, L. M., Booth, G.,

& Pierce, N. E. (2012). The direct and ecological costs of an ant-plant symbiosis.

The American Naturalist, 179(6), 768–78. doi:10.1086/665654

Friesen, M. L. (2012). Widespread fitness alignment in the legume-rhizobium symbiosis.

The New Phytologist, 194, 1096–1111. doi:10.1111/j.1469-8137.2012.04099.x

Fujiwara, M., Sengupta, P., & McIntire, S. L. (2002). Regulation of body size and

behavioral state of C. elegans by sensory perception and the EGL-4 cGMP-

dependent protein kinase. Neuron, 36(6), 1091–1102.

Gaume, L., Mckey, D., & Anstett, M.-C. (1997). Benefits conferred by “timid” ants:

Active anti-herbivore protection of the rainforest tree Leonardoxa africana by the

minute ant Petalomyrmex phylax. Oecologia, 112(2), 209–216.

Grangier, J., Dejean, A., Malé, P.-J. G., & Orivel, J. (2008). Indirect defense in a highly

specific ant-plant mutualism. Die Naturwissenschaften, 95(10), 909–16.

doi:10.1007/s00114-008-0398-4

Heil, M., Hilpert, A., Fiala, B., & Linsenmair, K. E. (2001). Nutrient availability and

indirect (biotic) defence in a Malaysian ant-plant. Oecologia, 126(3), 404–408.

doi:10.1007/s004420000534

Heil, M., & McKey, D. (2003). Protective ant-plant interactions as model systems in

ecological and evolutionary research. Annual Review of Ecology, Evolution, and

Systematics, 34(1), 425–553. doi:10.1146/annurev.ecolsys.34.011802.132410

56  

 

Hoover, K., Grove, M., Gardner, M., Hughes, D. P., McNeil, J., & Slavicek, J. (2011). A

gene for an extended phenotype. Science, 333(6048), 1401.

doi:10.1126/science.1209199

Ingram, K. K., Kleeman, L., & Peteru, S. (2011). Differential regulation of the foraging

gene associated with task behaviors in harvester ants. BMC Ecology, 11(1), 19.

doi:10.1186/1472-6785-11-19

Ingram, K. K., Oefner, P., & Gordon, D. M. (2005). Task-specific expression of the

foraging gene in harvester ants. Molecular Ecology, 14(3), 813–8.

doi:10.1111/j.1365-294X.2005.02450.x

Isner, J. C., Nühse, T., & Maathuis, F. J. M. (2012). The cyclic nucleotide cGMP is

involved in plant hormone signalling and alters phosphorylation of Arabidopsis

thaliana root proteins. Journal of experimental botany, 63(8), 3199–205.

doi:10.1093/jxb/ers045

Janson, E. M., Stireman, J. O., Singer, M. S., & Abbot, P. (2008). Phytophagous insect-

microbe mutualisms and adaptive evolutionary diversification. Evolution, 62(5),

997–1012. doi:10.1111/j.1558-5646.2008.00348.x

Janzen, D. H. (1966). Coevolution of mutualism between ants and acacias in Central

America. Evolution, 20(3), 249–275.

Kodaira, Y., Ohtsuki, H., Yokoyama, J., & Kawata, M. (2009). Size-dependent foraging

gene expression and behavioral caste differentiation in Bombus ignitus. BMC

Research Notes, 2, 184. doi:10.1186/1756-0500-2-184

Kursar, T. A., & Coley, P. D. (1992). Delayed greening in tropical leaves: An

antiherbivore defense? Biotropica, 24(2), 256–262.

57  

 

L’Etoile, N. D., Coburn, C. M., Eastham, J., Kistler, A., Gallegos, G., & Bargmann, C. I.

(2002). The cyclic GMP-dependent protein kinase EGL-4 regulates olfactory

adaptation in C. elegans. Neuron, 36(6), 1079–1089.

Linsenmair, K. E., Heil, M., Kaiser, W. M., Fiala, B., Koch, T., & Boland, W. (2001).

Adaptations to biotic and abiotic stress: Macaranga-ant plants optimize investment

in biotic defence. Journal of Experimental Botany, 52(363), 2057–65.

Lucas, C., & Sokolowski, M. B. (2009). Molecular basis for changes in behavioral state

in ant social behaviors. Proceedings of the National Academy of Sciences of the

United States of America, 106(15), 6351–6. doi:10.1073/pnas.0809463106

Mery, F., Belay, A. T., So, A. K.-C., Sokolowski, M. B., & Kawecki, T. J. (2007).

Natural polymorphism affecting learning and memory in Drosophila. Proceedings

of the National Academy of Sciences of the United States of America, 104(32),

13051–13055. doi:10.1073/pnas.0702923104

Oldroyd, G. E. D., & Long, S. R. (2003). Identification and characterization of

Nodulation-Signaling Pathway 2, a gene of Medicago truncatula involved in Nod

factor signaling. Plant Physiology, 131(March), 1027–1032.

doi:10.1104/pp.102.010710.ence

Osborne, K. A., Robichon, A., Burgess, E., Butland, S., Shaw, R. A., Coulthard, A.,

Pereira, H. S., et al. (1997). Natural behavior polymorphism due to a cGMP-

dependent protein kinase of Drosophila. Science, 277(5327), 834–836.

doi:10.1126/science.277.5327.834

Ott, S. R., Verlinden, H., Rogers, S. M., Brighton, C. H., Quah, P. S., Vleugels, R. K.,

Verdonck, R., et al. (2011). Critical role for protein kinase A in the acquisition of

58  

 

gregarious behavior in the desert locust. Proceedings of the National Academy of

Sciences of the United States of America, 109(7), E381–7.

doi:10.1073/pnas.1114990109

Pringle, E. G., Dirzo, R., & Gordon, D. M. (2011). Indirect benefits of symbiotic

coccoids for an ant-defended myrmecophytic tree. Ecology, 92(1), 37–46.

Prior, K. M., & Hellmann, J. J. (2010). Impact of an invasive oak gall wasp on a native

butterfly: A test of plant-mediated competition. Ecology, 91(11), 3284–3293.

Raizen, D. M., Cullison, K. M., Pack, A. I., & Sundaram, M. V. (2006). A novel gain-of-

function mutant of the cyclic GMP-dependent protein kinase egl-4 affects multiple

physiological processes in Caenorhabditis elegans. Genetics, 173(1), 177–187.

doi:10.1534/genetics.106.057380

Raizen, D. M., Zimmerman, J. E., Maycock, M. H., Ta, U. D., You, Y., Sundaram, M. V,

& Pack, A. I. (2008). Lethargus is a Caenorhabditis elegans sleep-like state. Nature,

451(7178), 569–572. doi:10.1038/nature06535

Ramírez, S. R., Eltz, T., Fujiwara, M. K., Gerlach, G., Goldman-Huertas, B., Tsutsui, N.

D., & Pierce, N. E. (2011). Asynchronous diversification in a specialized plant-

pollinator mutualism. Science, 333(6050), 1742–6. doi:10.1126/science.1209175

Redecker, D., Kodner, R., & Graham, L. E. (2000). Glomalean fungi from the

Ordovician. Science, 289(5486), 1920–1921. doi:10.1126/science.289.5486.1920

Ross, K. G., Krieger, M. J. B., & Shoemaker, D. D. (2003). Alternative genetic

foundations for a key social polymorphism in fire ants. Genetics, 165(4), 1853–67.

Rudgers, J. A., & Gardener, M. C. (2004). Extrafloral nectar as a resource mediating

multispecies interactions. Ecology, 85(6), 1495–1502.

59  

 

Sachs, J. L., Mueller, U. G., Wilcox, T. P., & Bull, J. J. (2004). The evolution of

cooperation. The Quarterly Review of Biology, 79(2), 135–160.

Sokolowski, M. B. (2010). Social interactions in “simple” model systems. Neuron, 65(6),

780–94. doi:10.1016/j.neuron.2010.03.00

Solano, P.-J., Belin-Depoux, M., & Dejean, A. (2005). Formation and structure of food

bodies in Cordia nodosa (Boraginaceae). Comptes Rendus Biologies, 328(7), 642–7.

doi:10.1016/j.crvi.2005.05.004

Tobback, J., Heylen, K., Gobin, B., Wenseleers, T., Billen, J., Arckens, L., &

Huybrechts, R. (2008). Cloning and expression of PKG, a candidate foraging

regulating gene in Vespula vulgaris. Animal Biology, 58(4), 341–351.

doi:10.1163/157075608X383665

Tobback, J., Mommaerts, V., Vandersmissen, H. P., Smagghe, G., & Huybrechts, R.

(2011). Age- and task-dependent foraging gene expression in the bumblebee

Bombus terrestris. Archives of Insect Biochemistry and Physiology, 76(1), 30–42.

doi:10.1002/arch.20401

Trager, M. D., Bhotika, S., Hostetler, J. a, Andrade, G. V, Rodriguez-Cabal, M. a,

McKeon, C. S., Osenberg, C. W., et al. (2010). Benefits for plants in ant-plant

protective mutualisms: A meta-analysis. PLoS one, 5(12), e14308.

doi:10.1371/journal.pone.0014308

Vantaux, A., Van den Ende, W., Billen, J., & Wenseleers, T. (2011). Large interclone

differences in melezitose secretion in the facultatively ant-tended black bean aphid

Aphis fabae. Journal of Insect Physiology, 57(12), 1614–1621.

doi:10.1016/j.jinsphys.2011.08.014

60  

 

Wang, J., Wurm, Y., Nipitwattanaphon, M., Riba-Grognuz, O., Huang, Y.-C.,

Shoemaker, D., & Keller, L. (2013). A Y-like social chromosome causes alternative

colony organization in fire ants. Nature, 493(7434), 664–668.

doi:10.1038/nature11832

Weber, J. N., Peterson, B. K., & Hoekstra, H. E. (2013). Discrete genetic modules are

responsible for complex burrow evolution in Peromyscus mice. Nature, 493(7432),

402–5. doi:10.1038/nature11816

Weyl, E. G., Frederickson, M. E., Yu, D. W., & Pierce, N. E. (2010). Economic contract

theory tests models of mutualism. Proceedings of the National Academy of Sciences

of the United States of America, 107, 15712–15716. doi:10.1073/pnas.1005294107/-

/DCSupplemental.www.pnas.org/cgi/doi/10.1073/pnas.1005294107

White, C. R. (2003). Allometric analysis beyond heterogeneous regression slopes: Use of

the Johnson-Neyman technique in comparative biology. Physiological and

Biochemical Zoology, 76(1), 135–40. doi:10.1086/367939

Wilson, E. O., & Hölldobler, B. (2005). Eusociality: Origin and consequences.

Proceedings of the National Academy of Sciences of the United States of America,

102(38), 13367–13371.

Yu, D. W., & Pierce, N. E. (1998). A castration parasite of an ant-plant mutualism.

Proceedings of the Royal Society B, 265, 375–382.

Zhang, W., Kramer, E. M., & Davis, C. C. (2012). Similar genetic mechanisms underlie

the parallel evolution of floral phenotypes. PLoS One, 7(4), e36033.

doi:10.1371/journal.pone.0036033

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Figures

Figure 2.1. Schematic of the experimental set-up on a C. nodosa branch. Domatia (dark

grey) occur at nodes, and are each associated with a whorl of four leaves, as well as two

leaves on the branch below. Herbivory was measured on young leaves (light grey). We

placed alates and grasshoppers at the base of leaves (*). The treatment food tube was

attached to the stem at the point indicated by X.

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Figure 2.2. Mean (± SE) number of attacks on grasshoppers per minute in the control

and PKG activator treatments.

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Figure 2.3. Aggression score (attacks on grasshoppers averaged over five minutes)

before and after treatment, in control (a) and PKG activator-treated (b) colonies, with

least-squares regression lines. Each point represents a plant.

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Figure 2.4. Mean (± SE) area of herbivore damage in the control and PKG activator

treatments.

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Supplementary Figure 2.1. Damaged leaf area vs leaf size (the width of the largest leaf

in the whorl) in the control (black) and activator (white) treatments. The difference

between treatments was significant on mid-sized leaves (the region bounded by grey

lines). Each point represents a plant.

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CONCLUDING REMARKS

Cooperative interactions are abundant, diverse, and implicated in many of the major

innovations in the evolutionary history of life (Bronstein 1994a, Bronstein et al. 2006).

Understanding how these interactions function and how their outcomes vary is important

for understanding the coevolutionary relationships between interacting partners.

Organisms cooperate when the benefits of doing so outweigh the cost, but on a proximate

scale, what drives cooperation? In this thesis, I have explored how organisms’

cooperative behaviours can vary, even when their partners’ contributions to the

interaction remain fixed. Using a specialized, symbiotic interaction between ants and

plants, I showed how cooperative behaviours change with the availability of different

resources. I also showed how a key enzyme linked to behaviour might influence

cooperation.

Colonies of Allomerus octoarticulatus protect their Cordia nodosa hosts by patrolling

plant tissues and killing herbivores that attempt to feed on the plant (Yu & Pierce 1998,

Frederickson 2005, Frederickson et al. 2012a). In Chapter One, I changed the

background diet of A. octoarticulatus colonies to examine whether this might disrupt

defensive behaviour. Provided with low-cost sources of proteinaceous food, colonies

invested less in hunting and attacking herbivores. This is likely an optimal strategy for

ants: hunting also provides the colony with protein, but is probably quite costly (e.g.

Ruiz-González et al. 2011). In nature, ants could gain access to protein through fungal

spores, pollen, or feces that land on their host plants; though the nutrient inputs from

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such sources would seem to be low, the ant Tetraponera penzigi is reported to subsist

entirely on these types of materials gleaned from the surfaces of its host plant, Acacia

drepanolobium (Palmer et al. 2008). My results suggest that fluxes in the availability of

such sources may generate variation in the level of protection ants provide to their host

plants. The abundance of non-herbivorous insects that land on the plant could also affect

the interaction through diet, because ants would obtain protein from these insects, but

killing them would not benefit the plant. Variation in any exogenous food sources could

generate variation in plant fitness. Future study should explore how the components of

ants’ diets vary over time and space, and how the system may have evolved to buffer this

variation.

In Chapter Two, I explored how ant protection might also be influenced by PKG, an

enzyme encoded by the gene foraging. After I fed ants with a PKG activator, they

became more aggressive towards herbivores, and, in turn, their host plants benefited from

reduced herbivory. Further studies, currently underway, will examine whether natural

variation in foraging expression is similarly associated with variation in ants’ behaviour

and their efficacy as an anti-herbivore defence. My results suggest a number of avenues

to further explore this and other cooperative interactions. First, on a practical level, my

study demonstrates the utility of the PKG activator in manipulating behaviour in

ecologically meaningful ways. Many studies test the benefits of ant defence by removing

colonies from plants or by associating plant performance with natural variation in colony

size (Trager et al. 2010); the PKG activator makes it possible to manipulate behaviour

without immediately changing ant numbers. Second, if an ortholog of foraging is

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conclusively shown to influence cooperative behaviour in ants, it will permit the kind of

evolutionary genetic studies that have illuminated the adaptive history of other

partnerships, like that between legumes and rhizobia (e.g. De Mita et al. 2007).

Both chapters of my thesis suggest ways in which plants could manipulate their resident

ant colonies to maximize protection. Myrmecophytic plants frequently produce food for

their resident ants (e.g. Janzen 1966, Folgarait & Davison 1995, Solano et al. 2005), and

the results of Chapter One suggest that plants will obtain the highest levels of defence by

keeping protein levels in this food relatively low. They may instead benefit from

producing high levels of sugars or other carbohydrates, as I found this to promote ant

activity in some colonies. Diet may also influence the interaction through effects on

PKG, as PKG activity changes in response to food deprivation in both flies (Sokolowski

2010) and ants (Lucas & Sokolowski 2009). PKG activity may be particularly responsive

to certain macronutrients, and so plants may have evolved a nutrient balance in their food

that optimally affects PKG activity and ant behaviour. Further, the activator that I used in

my experiment is 8-Br-cGMP, a non-hydrolysable, membrane-permeable form of cGMP,

the cyclic nucleotide that naturally activates PKG. The fact that cGMP also serves as a

signaling molecule in plants (Isner et al. 2012) suggest the tantalizing additional

possibility that plants could directly manipulate PKG activity if some similarly non-

hydrolysable form of the molecule is present in the food plants produce for ants. Thus,

both diet and behavioural genetics may interact to drive cooperation between plants and

their ant bodyguards.

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Overall, I have highlighted two major potential sources of variation in cooperation

among species. As many mutualisms involve an exchange of food, and all involve the

exchange of resources or services, it is important to be cognizant of how the background

availability of those resources might change the value of rewards on offer, even when the

actual level of reward provided appears to be fixed. Additionally, there is an enormous

gulf of knowledge yet unexplored in terms of how genes like foraging might influence

cooperation. The work I have presented shows that it is important to consider both diet

and genes involved in behaviour to fully understand cooperation between ants and plants,

and among other species involved in mutualism.

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WORKS CITED

Ané, J.-M., Kiss, G. B., Riely, B. K., Penmetsa, R. V., Oldroyd, G. E. D., Ayax, C.,

Lévy, J., et al. (2004). Medicago truncatula DMI1 required for bacterial and fungal

symbioses in legumes. Science, 303, 1364–1367.

Archetti, M., Scheuring, I., Hoffman, M., Frederickson, M. E., Pierce, N. E., & Yu, D.

W. (2011). Economic game theory for mutualism and cooperation. Ecology Letters,

14(12), 1300–12. doi:10.1111/j.1461-0248.2011.01697.x

Belay, A. T., Scheiner, R., So, A. K., Douglas, S. J., Chakaborty-Chatterjee, M., Levine,

J. D., & Sokolowski, M. B. (2007). The foraging gene of Drosophila melanogaster:

Spatial-expression analysis and sucrose responsiveness. The Journal of

Comparative Neurology, 582(December 2006), 570–582. doi:10.1002/cne

Ben-Shahar, Y. (2005). The foraging gene, behavioral plasticity, and honeybee division

of labor. Journal of Comparative Physiology A, 191(11), 987–94.

doi:10.1007/s00359-005-0025-1

Ben-Shahar, Y., Robichon, A., Sokolowski, M. B., & Robinson, G. E. (2002). Influence

of gene action across different time scales on behavior. Science, 296(5568), 741–4.

doi:10.1126/science.1069911

Brock, D. a, Douglas, T. E., Queller, D. C., & Strassmann, J. E. (2011). Primitive

agriculture in a social amoeba. Nature, 469(7330), 393–6. doi:10.1038/nature09668

Bronstein, J. L. (1994a). Our current understanding of mutualism. The Quarterly Review

of Biology, 69(1), 31–51.

72  

 

Bronstein, J. L. (1994b). Conditional outcomes in mutualistic interactions. Trends in

Ecology & Evolution, 9(6), 214–217.

Bronstein, J. L., Alarcón, R., & Geber, M. (2006). The evolution of plant-insect

mutualisms. The New Phytologist, 172(3), 412–28. doi:10.1111/j.1469-

8137.2006.01864.x

Burns, J. G., Svetec, N., Rowe, L., Mery, F., Dolan, M. J., Boyce, W. T., & Sokolowski,

M. B. (2012). Gene-environment interplay in Drosophila melanogaster: Chronic

food deprivation in early life affects adult exploratory and fitness traits. Proceedings

of the National Academy of Sciences of the United States of America, 109, 17239–

44. doi:10.1073/pnas.1121265109

Cade, B. S., & Noon, B. R. (2003). A gentle introduction to quantile regression for

ecologists. Frontiers in Ecology and the Environment, 1(8), 412–420.

Charnov, E. L. (1976). Optimal foraging: Attack strategy of a mantid. The American

Naturalist, 110(971), 141–151.

Chen, A., Kramer, E. F., Purpura, L., Krill, J. L., Zars, T., & Dawson-Scully, K. (2011).

The influence of natural variation at the foraging gene on thermotolerance in adult

Drosophila in a narrow temperature range. Journal of Comparative Physiology A,

197(12), 1113–8. doi:10.1007/s00359-011-0672-3

Clutton-Brock, T. (2009). Cooperation between non-kin in animal societies. Nature,

462(7269), 51–7. doi:10.1038/nature08366

Coley, P. D. (1983). Herbivory and defensive characteristics of tree species in a lowland

tropical forest. Ecological Monographs, 53(2), 209–234.

73  

 

Cook, S. C., & Behmer, S. T. (2010). Macronutrient regulation in the tropical terrestrial

ant Ectatomma ruidum (Formicidae): A field study in Costa Rica. Biotropica, 42,

135–139.

Cook, S. C., Eubanks, M. D., Gold, R. E., & Behmer, S. T. (2009). Colony-level

macronutrient regulation in ants: mechanisms, hoarding and associated costs.

Animal Behaviour, 79(2), 429–437. doi:10.1016/j.anbehav.2009.11.022

Cook, S. C., Wynalda, R. A., Gold, R. E., & Behmer, S. T. (2012). Macronutrient

regulation in the Rasberry crazy ant (Nylanderia sp. nr. pubens). Insectes Sociaux,

59(1), 93–100. doi:10.1007/s00040-011-0193-7

Corradi, N., & Bonfante, P. (2012). The arbuscular mycorrhizal symbiosis: Origin and

evolution of a beneficial plant infection. PLoS Pathogens, 8(4), e1002600.

doi:10.1371/journal.ppat.1002600

Davidson, D. W. (1997). The role of resource imbalances in the evolutionary ecology of

tropical arboreal ants. Biological Journal of the Linnean Society, 61(2), 153–181.

doi:10.1006/bijl.1996.0128

Davidson, D. W. (2005). Ecological stoichiometry of ants in a New World rain forest.

Oecologia, 142(2), 221–31. doi:10.1007/s00442-004-1722-0

Dawkins, R. (1982). The Extended Phenotype. Oxford: Oxford University Press.

Dawson-Scully, K., Bukvic, D., Chakaborty-Chatterjee, M., Ferreira, R., Milton, S. L., &

Sokolowski, M. B. (2010). Controlling anoxic tolerance in adult Drosophila via the

cGMP-PKG pathway. The Journal of Experimental Biology, 213, 2410–2416.

doi:10.1242/jeb.041319

74  

 

De Mita, S., Ronfort, J., McKhann, H. I., Poncet, C., El Malki, R., & Bataillon, T.

(2007). Investigation of the demographic and selective forces shaping the nucleotide

diversity of genes involved in Nod factor signaling in Medicago truncatula.

Genetics, 177(4), 2123–33. doi:10.1534/genetics.107.076943

Debout, G., Schatz, B., & McKey, D. (2005). Behavioural traits mediating effects of two

plant-ants on their specific myrmecophyte host. Insectes Sociaux, 52(3), 205–211.

doi:10.1007/s00040-004-0795-4

Dejean, A., Leroy, C., Corbara, B., Roux, O., Céréghino, R., Orivel, J., & Boulay, R.

(2010). Arboreal ants use the “Velcro(R) principle” to capture very large prey. PLoS

One, 5(6), e11331. doi:10.1371/journal.pone.0011331

Dejean, A., Solano, P. J., Ayroles, J., Corbara, B., & Orivel, J. (2005). Arboreal ants

build traps to capture prey. Nature, 434, 5174.

Donlea, J., Leahy, A., Thimgan, M. S., Suzuki, Y., Hughson, B. N., Sokolowski, M. B.,

& Shaw, P. J. (2012). Foraging alters resilience/vulnerability to sleep disruption and

starvation in Drosophila. Proceedings of the National Academy of Sciences of the

United States of America, 109(7), 2613–26188. doi:10.1073/pnas.1112623109

Dussutour, A., & Simpson, S. J. (2009). Communal nutrition in ants. Current Biology,

19(9), 740–4. doi:10.1016/j.cub.2009.03.015

Eddison, M., Belay, A. T., Sokolowski, M. B., & Heberlein, U. (2012). A genetic screen

for olfactory habituation mutations in Drosophila: analysis of novel foraging alleles

and an underlying neural circuit. PLoS One, 7(12), e51684.

doi:10.1371/journal.pone.0051684

75  

 

Edwards, D. P., Hassall, M., Sutherland, W. J., & Yu, D. W. (2006). Selection for

protection in ant ant-plant mutualism: Host sanctions, host modularity, and the

principal-agent game. Proceedings of the Royal Society B, 273(1586), 595–602.

doi:10.1098/rspb.2005.3273

Engqvist, L. (2005). The mistreatment of covariate interaction terms in linear model

analyses of behavioural and evolutionary ecology studies. Animal Behaviour, 70(4),

967–971. doi:10.1016/j.anbehav.2005.01.016

Ferriere, R., Bronstein, J. L., Rinaldi, S., Law, R., & Gauduchon, M. (2002). Cheating

and the evolutionary stability of mutualisms. Proceedings of the Royal Society B,

269(1493), 773–80. doi:10.1098/rspb.2001.1900

Fischer, R. C., Richter, A., Wanek, W., & Mayer, V. (2002). Plants feed ants: food

bodies of myrmecophytic Piper and their significance for the interaction with

Pheidole bicornis ants. Oecologia, 133(2), 186–192.

Fitzpatrick, M. J., Ben-Shahar, Y., Smid, H. M., Vet, L. E. M., Robinson, G. E., &

Sokolowski, M. B. (2005). Candidate genes for behavioural ecology. Trends in

Ecology & Evolution, 20(2), 96–104. doi:10.1016/j.tree.2004.11.017

Fitzpatrick, M. J., & Sokolowski, M. B. (2004). In search of food: Exploring the

evolutionary link between cGMP-dependent Protein Kinase (PKG) and behaviour.

Integrative and Comparative Biology, 36, 28–36.

Folgarait, P. J., & Davidson, D. W. (1995). Myrmecophytic Cecropia: Antiherbivore

defenses under different nutrient treatments. Oecologia, 104, 189–206.

Fonseca, C. R. (1993). Nesting space limits colony size of the plant-ant Pseudomyrmex

concolor. Oikos, 67(3), 473–482.

76  

 

Frederickson, M. E. (2005). Ant species confer different partner benefits on two

neotropical myrmecophytes. Oecologia, 143(3), 387–95. doi:10.1007/s00442-004-

1817-7

Frederickson, M. E. (2006). The reproductive phenology of an Amazonian ant species

reflects the seasonal availability of its nest sites. Oecologia, 149, 418–427.

doi:10.1007/s00442-006-0460-x

Frederickson, M. E., & Gordon, D. M. (2009). The intertwined population biology of two

Amazonian myrmecophytes and their symbiotic ants. Ecology, 90(6), 1595–607.

Frederickson, M. E., Ravenscraft, A., Arcila Hernández, L. M., Booth, G., Astudillo, V.,

& Miller, G. A. (2012). What happens when ants fail at plant defence? Cordia

nodosa dynamically adjusts its investment in both direct and indirect resistance

traits in response to herbivore damage. Journal of Ecology, 101(2), 400–409.

doi:10.1111/1365-2745.12034

Frederickson, M. E., Ravenscraft, A., Miller, G. a, Arcila Hernández, L. M., Booth, G.,

& Pierce, N. E. (2012). The direct and ecological costs of an ant-plant symbiosis.

The American Naturalist, 179(6), 768–78. doi:10.1086/665654

Friesen, M. L. (2012). Widespread fitness alignment in the legume-rhizobium symbiosis.

The New Phytologist, 194, 1096–1111. doi:10.1111/j.1469-8137.2012.04099.x

Fujiwara, M., Sengupta, P., & McIntire, S. L. (2002). Regulation of body size and

behavioral state of C. elegans by sensory perception and the EGL-4 cGMP-

dependent protein kinase. Neuron, 36(6), 1091–1102.

Gammans, N., Bullock, J. M., & Schönrogge, K. (2005). Ant benefits in a seed dispersal

mutualism. Oecologia, 146(1), 43–9. doi:10.1007/s00442-005-0154-9

77  

 

Gaume, L., Mckey, D., & Anstett, M.-C. (1997). Benefits conferred by “timid” ants:

Active anti-herbivore protection of the rainforest tree Leonardoxa africana by the

minute ant Petalomyrmex phylax. Oecologia, 112(2), 209–216.

González-Teuber, M., Silva Bueno, J. C., Heil, M., & Boland, W. (2012). Increased host

investment in extrafloral nectar (EFN) improves the efficiency of a mutualistic

defensive service. PLoS One, 7(10), e46598. doi:10.1371/journal.pone.0046598

Grangier, J., Dejean, A., Malé, P.-J. G., & Orivel, J. (2008). Indirect defense in a highly

specific ant-plant mutualism. Die Naturwissenschaften, 95(10), 909–16.

doi:10.1007/s00114-008-0398-4

Grover, C. D., Kay, A. D., Monson, J. A., Marsh, T. C., & Holway, D. A. (2007).

Linking nutrition and behavioural dominance: Carbohydrate scarcity limits

aggression and activity in Argentine ants. Proceedings of the Royal Society B,

274(1628), 2951–7. doi:10.1098/rspb.2007.1065

Handa, C., Okubo, T., Yoneyama, A., Nakamura, M., Sakaguchi, M., Takahashi, N.,

Okamoto, M., et al. (2013). Change in biomass of symbiotic ants throughout the

ontogeny of a myrmecophyte, Macaranga beccariana (Euphorbiaceae). Journal of

Plant Research, 126(1), 73–9. doi:10.1007/s10265-012-0500-z

Heath, K. D., & Tiffin, P. (2009). Stabilizing mechanisms in a legume-rhizobium

mutualism. Evolution, 63(3), 652–62. doi:10.1111/j.1558-5646.2008.00582.x

Heil, M, Fiala, B., & Kaiser, W. (1998). Chemical contents of Macaranga food bodies:

adaptations to their role in ant attraction and nutrition. Functional Ecology, 12(1),

117–122.

78  

 

Heil, Martin. (2011). Nectar: Generation, regulation and ecological functions. Trends in

Plant Science, 16(4), 191–200. doi:10.1016/j.tplants.2011.01.003

Heil, Martin, Baumann, B., Kruger, R., & Linsenmair, K. E. (2004). Main nutrient

compounds in food bodies of Mexican Acacia ant-plants. Chemoecology, 14(1), 45–

52. doi:10.1007/s00049-003-0257-x

Heil, Martin, Hilpert, A., Fiala, B., & Linsenmair, K. E. (2001). Nutrient availability and

indirect (biotic) defence in a Malaysian ant-plant. Oecologia, 126(3), 404–408.

doi:10.1007/s004420000534

Heil, Martin, & McKey, D. (2003). Protective ant-plant interactions as model systems in

ecological and evolutionary research. Annual Review of Ecology, Evolution, and

Systematics, 34(1), 425–553. doi:10.1146/annurev.ecolsys.34.011802.132410

Hendrix, L. J., Carter, M. W., & Scott, D. T. (1982). Covariance analyses with

heterogeneity of slopes in fixed models. Biometrics, 38(3), 641–50. Retrieved from

Herrera, C. M. (1984). A study of avian frugivores, bird-dispersed plants, and their

interaction in Mediterranean scrublands. Ecological Monographs, 54(1), 1–23.

Hoover, K., Grove, M., Gardner, M., Hughes, D. P., McNeil, J., & Slavicek, J. (2011). A

gene for an extended phenotype. Science, 333(6048), 1401.

doi:10.1126/science.1209199

Ingram, K. K., Kleeman, L., & Peteru, S. (2011). Differential regulation of the foraging

gene associated with task behaviors in harvester ants. BMC Ecology, 11(1), 19.

doi:10.1186/1472-6785-11-19

79  

 

Ingram, K. K., Oefner, P., & Gordon, D. M. (2005). Task-specific expression of the

foraging gene in harvester ants. Molecular Ecology, 14(3), 813–8.

doi:10.1111/j.1365-294X.2005.02450.x

Isner, J. C., Nühse, T., & Maathuis, F. J. M. (2012). The cyclic nucleotide cGMP is

involved in plant hormone signalling and alters phosphorylation of Arabidopsis

thaliana root proteins. Journal of Experimental Botany, 63(8), 3199–205.

doi:10.1093/jxb/ers045

Jandér, K. C., & Herre, E. A. (2010). Host sanctions and pollinator cheating in the fig

tree-fig wasp mutualism. Proceedings of the Royal Society B, 277(1687), 1481–8.

doi:10.1098/rspb.2009.2157

Janson, E. M., Stireman, J. O., Singer, M. S., & Abbot, P. (2008). Phytophagous insect-

microbe mutualisms and adaptive evolutionary diversification. Evolution, 62(5),

997–1012. doi:10.1111/j.1558-5646.2008.00348.x

Janzen, D. H. (1966). Coevolution of mutualism between ants and acacias in Central

America. Evolution, 20(3), 249–275.

Kay, A. D. (2002). Applying optimal foraging theory to assess nutrient availability ratios

for ants. Ecology, 83(7), 1935–1944.

Kay, A. D. (2004). The relative availabilities of complementary resources affect the

feeding preferences of ant colonies. Behavioral Ecology, 15(1), 63–70.

doi:10.1093/beheco/arg106

Kay, A. D., Shik, J. Z., Van Alst, A., Miller, K. A., & Kaspari, M. (2012). Diet

composition does not affect ant colony tempo. Functional Ecology, 26(2), 317–323.

doi:10.1111/j.1365-2435.2011.01944.x

80  

 

Kay, A. D., Zumbusch, T., Heinen, J. L., Marsh, T. C., & Holway, D. A. (2010).

Nutrition and interference competition have interactive effects on the behavior and

performance of Argentine ants. Ecology, 91(1), 57–64.

Kiers, E. T., Duhamel, M., Beesetty, Y., Mensah, J. a, Franken, O., Verbruggen, E.,

Fellbaum, C. R., et al. (2011). Reciprocal rewards stabilize cooperation in the

mycorrhizal symbiosis. Science, 333(6044), 880–2. doi:10.1126/science.1208473

Kiers, E. T., Rousseau, R. A., & Denison, R. F. (2006). Measured sanctions: Legume

hosts detect quantitative variation in rhizobium cooperation and punish accordingly.

Evolutionary Ecology, 8, 1077–1086.

Kodaira, Y., Ohtsuki, H., Yokoyama, J., & Kawata, M. (2009). Size-dependent foraging

gene expression and behavioral caste differentiation in Bombus ignitus. BMC

Research Notes, 2, 184. doi:10.1186/1756-0500-2-184

Kursar, T. A., & Coley, P. D. (1992). Delayed greening in tropical leaves: An

antiherbivore defense? Biotropica, 24(2), 256–262.

L’Etoile, N. D., Coburn, C. M., Eastham, J., Kistler, A., Gallegos, G., & Bargmann, C. I.

(2002). The cyclic GMP-dependent protein kinase EGL-4 regulates olfactory

adaptation in C. elegans. Neuron, 36(6), 1079–1089.

Letourneau, D K. (1983). Passive aggression: An alternative hypothesis for the Piper-

Pheidole association. Oecologia, 60, 122–126.

Letourneau, Deborah K. (1998). Ants, stem-borers, and fungal pathogens: Experimental

tests of a fitness advantage in Piper ant-plants. Ecology, 79(2), 593–603.

81  

 

Linsenmair, K. E., Heil, M., Kaiser, W. M., Fiala, B., Koch, T., & Boland, W. (2001).

Adaptations to biotic and abiotic stress: Macaranga-ant plants optimize investment

in biotic defence. Journal of Experimental Botany, 52(363), 2057–65.

Lucas, C., & Sokolowski, M. B. (2009). Molecular basis for changes in behavioral state

in ant social behaviors. Proceedings of the National Academy of Sciences of the

United States of America, 106(15), 6351–6. doi:10.1073/pnas.0809463106

Madden, D., & Young, T. P. (1992). Symbiotic ants as an alternative defense against

giraffe herbivory in spinescent Acacia drepanolobium. Oecologia, 91, 235–238.

Mery, F., Belay, A. T., So, A. K.-C., Sokolowski, M. B., & Kawecki, T. J. (2007).

Natural polymorphism affecting learning and memory in Drosophila. Proceedings

of the National Academy of Sciences of the United States of America, 104(32),

13051–13055. doi:10.1073/pnas.0702923104

Ness, J. H., Morris, W. F., & Bronstein, J. L. (2009). For ant-protected plants, the best

defense is a hungry offense. Ecology, 90(10), 2823–31.

Offenberg, J., Nielsen, M. G., MacIntosh, D. J., Havanon, S., & Aksornkoae, S. (2004).

Evidence that insect herbivores are deterred by ant pheromones. Proceedings of the

Royal Society of London B, 271 Suppl, S433–5. doi:10.1098/rsbl.2004.0210

Oldroyd, G. E. D., & Long, S. R. (2003). Identification and characterization of

Nodulation-Signaling Pathway 2, a gene of Medicago truncatula involved in Nod

factor signaling. Plant Physiology, 131, 1027–1032.

doi:10.1104/pp.102.010710.ence

Oono, R., Anderson, C. G., & Denison, R. F. (2011). Failure to fix nitrogen by non-

reproductive symbiotic rhizobia triggers host sanctions that reduce fitness of their

82  

 

reproductive clonemates. Proceedings of the Royal Society B, 278(1718), 2698–703.

doi:10.1098/rspb.2010.2193

Osborne, K. A., Robichon, A., Burgess, E., Butland, S., Shaw, R. A., Coulthard, A.,

Pereira, H. S., et al. (1997). Natural behavior polymorphism due to a cGMP-

dependent protein kinase of Drosophila. Science, 277(5327), 834–836.

doi:10.1126/science.277.5327.834

Ott, S. R., Verlinden, H., Rogers, S. M., Brighton, C. H., Quah, P. S., Vleugels, R. K.,

Verdonck, R., et al. (2011). Critical role for protein kinase A in the acquisition of

gregarious behavior in the desert locust. Proceedings of the National Academy of

Sciences of the United States of America, 109(7), E381–7.

doi:10.1073/pnas.1114990109

Palmer, T. M., Stanton, M. L., Young, T. P., Goheen, J. R., Pringle, R. M., & Karban, R.

(2008). Breakdown of an ant-plant mutualism follows the loss of large herbivores

from an African savanna. Science, 319(5860), 192–5. doi:10.1126/science.1151579

Petry, W. K., Perry, K. I., & Mooney, K. a. (2012). Influence of macronutrient imbalance

on native ant foraging and interspecific interactions in the field. Ecological

Entomology, 37(3), 175–183. doi:10.1111/j.1365-2311.2012.01349.x

Powell, J. A. (1992). Interrelationships of yuccas and yucca moths. Trends in Ecology &

Evolution, 7(1), 10–5. doi:10.1016/0169-5347(92)90191-D

Pringle, E. G., Dirzo, R., & Gordon, D. M. (2011). Indirect benefits of symbiotic

coccoids for an ant-defended myrmecophytic tree. Ecology, 92(1), 37–46.

Prior, K. M., & Hellmann, J. J. (2010). Impact of an invasive oak gall wasp on a native

butterfly: A test of plant-mediated competition. Ecology, 91(11), 3284–3293.

83  

 

Quinlan, R. J., & Cherrett, J. M. (1978). Aspects of the symbiosis of the leaf-cutting ant

Acromyrmex octospinosus (Reich) and its food fungus. Ecological Entomology, 3,

221–230.

Raizen, D. M., Cullison, K. M., Pack, A. I., & Sundaram, M. V. (2006). A novel gain-of-

function mutant of the cyclic GMP-dependent protein kinase egl-4 affects multiple

physiological processes in Caenorhabditis elegans. Genetics, 173(1), 177–187.

doi:10.1534/genetics.106.057380

Raizen, D. M., Zimmerman, J. E., Maycock, M. H., Ta, U. D., You, Y., Sundaram, M. V,

& Pack, A. I. (2008). Lethargus is a Caenorhabditis elegans sleep-like state. Nature,

451(7178), 569–572. doi:10.1038/nature06535

Ramírez, S. R., Eltz, T., Fujiwara, M. K., Gerlach, G., Goldman-Huertas, B., Tsutsui, N.

D., & Pierce, N. E. (2011). Asynchronous diversification in a specialized plant-

pollinator mutualism. Science, 333(6050), 1742–6. doi:10.1126/science.1209175

Redecker, D., Kodner, R., & Graham, L. E. (2000). Glomalean fungi from the

Ordovician. Science, 289(5486), 1920–1921. doi:10.1126/science.289.5486.1920

Ross, K. G., Krieger, M. J. B., & Shoemaker, D. D. (2003). Alternative genetic

foundations for a key social polymorphism in fire ants. Genetics, 165(4), 1853–67.

Rudgers, J. A., & Gardener, M. C. (2004). Extrafloral nectar as a resource mediating

multispecies interactions. Ecology, 85(6), 1495–1502.

Rudgers, J. A., & Strauss, S. Y. (2004). A selection mosaic in the facultative mutualism

between ants and wild cotton. Proceedings of the Royal Society B, 271(1556),

2481–8. doi:10.1098/rspb.2004.2900

84  

 

Ruiz-González, M. X., Malé, P.-J. G., Leroy, C., Dejean, A., Gryta, H., Jargeat, P.,

Quilichini, A., et al. (2011). Specific, non-nutritional association between an

ascomycete fungus and Allomerus plant-ants. Biology Letters, 7(3), 475–9.

doi:10.1098/rsbl.2010.0920

Sachs, J. L., Mueller, U. G., Wilcox, T. P., & Bull, J. J. (2004). The evolution of

cooperation. The Quarterly Review of Biology, 79(2), 135–160.

Soares, M. C., Bshary, R., Mendonça, R., Grutter, A. S., & Oliveira, R. F. (2012).

Arginine vasotocin regulation of interspecific cooperative behaviour in a cleaner

fish. PLoS One, 7(7), e39583. doi:10.1371/journal.pone.0039583

Sokolowski, M. B. (2010). Social interactions in “simple” model systems. Neuron, 65(6),

780–94. doi:10.1016/j.neuron.2010.03.007

Solano, P.-J., Belin-Depoux, M., & Dejean, A. (2005). Formation and structure of food

bodies in Cordia nodosa (Boraginaceae). Comptes Rendus Biologies, 328(7), 642–7.

doi:10.1016/j.crvi.2005.05.004

Thompson, S. N. (1973). A review and comparative characterization of the fatty acid

compositions of seven insect orders. Comparative Biochemistry and Physiology,

45B, 467–482.

Thompson, J. N. (1988). Variation in interspecific interactions. Annual Review of

Ecology and Systematics, 19, 65–87.

Thompson, J. N., & Cunningham, B. M. (2002). Geographic structure and dynamics of

coevolutionary selection. Nature, 417(6890), 735–8. doi:10.1038/nature00810

Tobback, J., Heylen, K., Gobin, B., Wenseleers, T., Billen, J., Arckens, L., &

Huybrechts, R. (2008). Cloning and expression of PKG, a candidate foraging

85  

 

regulating gene in Vespula vulgaris. Animal Biology, 58(4), 341–351.

doi:10.1163/157075608X383665

Tobback, J., Mommaerts, V., Vandersmissen, H. P., Smagghe, G., & Huybrechts, R.

(2011). Age- and task-dependent foraging gene expression in the bumblebee

Bombus terrestris. Archives of Insect Biochemistry and Physiology, 76(1), 30–42.

doi:10.1002/arch.20401

Trager, M. D., Bhotika, S., Hostetler, J. a, Andrade, G. V, Rodriguez-Cabal, M. a,

McKeon, C. S., Osenberg, C. W., et al. (2010). Benefits for plants in ant-plant

protective mutualisms: A meta-analysis. PLoS one, 5(12), e14308.

doi:10.1371/journal.pone.0014308

Vantaux, A., Van den Ende, W., Billen, J., & Wenseleers, T. (2011). Large interclone

differences in melezitose secretion in the facultatively ant-tended black bean aphid

Aphis fabae. Journal of Insect Physiology, 57(12), 1614–1621.

doi:10.1016/j.jinsphys.2011.08.014

Vuong, Q. H. (1989). Likelihood Ratio Tests for model selection and non-nested

hypotheses. Econometrica, 57(2), 307–333.

Wang, J., Wurm, Y., Nipitwattanaphon, M., Riba-Grognuz, O., Huang, Y.-C.,

Shoemaker, D., & Keller, L. (2013). A Y-like social chromosome causes alternative

colony organization in fire ants. Nature, 493(7434), 664–668.

doi:10.1038/nature11832

Way, M. J. (1963). Mutualism between ants and honeydew-producing homoptera.

Annual Review of Entomology, 8, 307–344.

86  

 

Weber, J. N., Peterson, B. K., & Hoekstra, H. E. (2013). Discrete genetic modules are

responsible for complex burrow evolution in Peromyscus mice. Nature, 493(7432),

402–5. doi:10.1038/nature11816

Weiblen, G. D., & Bush, G. L. (2002). Speciation in fig pollinators and parasites.

Molecular Ecology, 11(8), 1573–8.

Weyl, E. G., Frederickson, M. E., Yu, D. W., & Pierce, N. E. (2010). Economic contract

theory tests models of mutualism. Proceedings of the National Academy of Sciences

of the United States of America, 107, 15712–15716. doi:10.1073/pnas.1005294107/-

/DCSupplemental.www.pnas.org/cgi/doi/10.1073/pnas.1005294107

White, C. R. (2003). Allometric analysis beyond heterogeneous regression slopes: Use of

the Johnson-Neyman technique in comparative biology. Physiological and

Biochemical Zoology, 76(1), 135–40. doi:10.1086/367939

Wilson, E. O., & Hölldobler, B. (2005). Eusociality: Origin and consequences.

Proceedings of the National Academy of Sciences of the United States of America,

102(38), 13367–13371.

Yu, D. W., & Pierce, N. E. (1998). A castration parasite of an ant-plant mutualism.

Proceedings of the Royal Society B, 265, 375–382.

Zhang, W., Kramer, E. M., & Davis, C. C. (2012). Similar genetic mechanisms underlie

the parallel evolution of floral phenotypes. PLoS One, 7(4), e36033.

doi:10.1371/journal.pone.0036033

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APPENDIX A

Pilot study: The effect of PKG on cooperation may vary across systems

Abstract

Mutualisms are abundant in nature, yet we know very little about the molecular basis of

cooperative behaviours. In Chapter Two, we provided evidence that PKG, an enzyme

encoded by the gene foraging, influences protective behaviour in a plant-dwelling ant.

Here, we tested whether similar effects could be found in other cooperative interactions

by feeding an activator of PKG to two species of Crematogaster ants living on Acacia

drepanolobium plants. In one of the two species, C. nigriceps, PKG activation caused

ants to be somewhat less responsive when the plant was disturbed, and to recruit less

readily to protein baits. In the other species, C. mimosae, activator treatment had no

effect on any behaviour measured. We suggest that some inconsistencies between species

may be due to differences in genetic architecture, though others may be due to

differences in context or in the behaviour studied.

Introduction

Many species participate in mutually beneficial interactions with other species, and such

interactions are implicated in major ecological and evolutionary shifts throughout the

history of life (Bronstein 1994, Redecker et al. 2000, Bronstein et al. 2006, Janson 2008,

Ramírez et al 2011). Understanding the molecular basis for these interactions makes it

possible to examine their adaptive history by screening genes involved in the interaction

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for signatures of selection (e.g. De Mita et al. 2007). Identifying the genes involved in

convergent coevolutionary shifts (e.g. Zhang et al. 2012) also deepens our understanding

of what genetic or genomic conditions allow those shifts to occur. However, knowledge

of the molecular underpinnings of cooperation between plants and animals remains

limited.

Plant-animal interactions, including pollination, seed dispersal, third-party defence,

inevitably involve basic behaviours like movement, foraging, and learning. Recent work

in behavioural genetics has identified a number of genes influencing these behaviours

(Fitzpatrick & Sokolowski 2004, Fitzpatrick et al. 2005), generating a list of candidate

genes that may influence cooperative interactions. The foraging gene, for instance,

influences food-related behaviours and activity levels across taxa (Osborne et al. 1997,

Ben-Shahar et al. 2002, Fitzpatrick & Sokolowski 2004, Tobback et al. 2008). In social

Hymenoptera, the shift from nursing work to foraging has been linked with changes in

both the expression of foraging orthologs, and with the activity of foraging’s product, the

enzyme protein kinase G (PKG; Ben-Shahar et al. 2002, Ingram et al. 2005, Tobback et

al. 2008, Ingram et al. 2011). Lucas and Sokolowski (2009) also demonstrated that PKG

influences nest defence in the ant Pheidole pallidula. Since PKG influences food

collection and aggression, among other traits, it likely plays a role in a variety of species

interactions.

In Chapter Two, we examined the potential effects of PKG on a symbiotic interaction

between ants and plants, myrmecophytism. In this interaction, plants produce hollow

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housing structures and food for ants, and ants in exchange patrol plant surfaces and deter

herbivores (Heil & McKey 2003, Bronstein et al. 2006). In our experiment, we provided

plant-dwelling Allomerus octoarticulatus ants with a PKG activator (8-Br-cGMP), which

caused the ants to become more aggressive towards herbivores. Their Cordia nodosa

host plants, in turn, benefited from reduced herbivory. However, PKG may not affect

other myrmecophytic interactions in the same way, as the effects of foraging orthologs

are known to vary across taxa. In D. melanogaster larvae, for instance, high movement

while feeding is associated with a high-expression allele of the gene; in constrast, high

movement during feeding is associated with low PKG levels in C. elegans nematodes

(Fitzpatrick & Sokolowski 2004). Even within ants, associations vary: while foraging

workers in Pogonomyrmex occidentalis harvester ants have elevated foraging expression

(Ingram et al. 2011), in Pheidole pallidula, high expression is associated with reduced

foraging (Lucas & Sokolowski 2009). Thus, we wanted to explore how the effects of

PKG on cooperative behaviour, as described in Chapter Two, might also vary among

taxa.

To examine this possibility, we performed a study on two of the ant partners of

myrmecophytic Acacia drepanolobium. This small tree dominates certain soil types in

East Africa (Young et al. 1997), and is protected from herbivory by both spines and

active colonies of ants that inhabit swollen thorns and feed on extrafloral nectar (Hocking

1970). Unlike in Cordia nodosa, where insect herbivores cause the majority of damage

(Dejean et al. 2004), damage by large vertebrates has the strongest influence on growth

in A. drepanolobium (Stanton & Palmer 2011). In this study, we focused on two of the

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four primary associates of A. drepanolobium, Crematogaster mimosae and C. nigriceps.

Crematogaster mimosae is more responsive to herbivores (Stanton & Palmer 2011),

recruits more actively to protein baits (Palmer 2003), and is often successful in territorial

conflicts over C. nigriceps (Palmer et al. 2000). Crematogaster nigriceps is a poorer

competitor, and a less active defender (Palmer et al. 2000). It also crops axillary buds on

its host trees, directing growth away from competitor colonies (Stanton et al. 1999). In

this study, we explored whether PKG activation might influence cooperation between

these ants and their host trees, and whether the effect was consistent between the two ant

species.

Methods

Study System

We took advantage of a greenhouse population of A. drepanolobium at Harvard

University. Seeds were collected in Laikipia, Kenya (0°17’ N, 37°52’ E, ~1800 m

elevation) in March, 2011, and grown in the greenhouse. Colonies of Crematogaster

nigriceps and C. mimosae were collected from the same population in March, 2012, and

maintained in containers with their clipped domatia and water tubes in an environmental

chamber. Between April and early October, 2012, a single colony was introduced to each

tree. For this experiment, we used 16 colonies of C. mimosae, and 20 of C. nigriceps.

Experiment

The experiment was conducted in October, 2012. On the first day of the experiment, we

counted the number of swollen thorns on the plants, and then measured each colony of

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both species for ant activity, swarming, and recruitment to baits (see below). Then, we

assigned each colony randomly to one of two treatments, PKG activator or control, after

stratifying by the number of ants on the plant. In both treatments, we attached a 1 mL

centrifuge halfway up the plant. In the PKG activator treatment, this contained 0.4 mL of

a 3.5 mM 8-Br-cGMP in distilled water, with 10% w/v sucrose added as a feeding

stimulus. In the control, this tube contained only 0.4 mL of 10% sucrose in distilled

water. These feeding tubes were replaced on the third and fourth days of the experiment,

and we repeated the activity, swarming, and recruitment measures on the third and fifth

days, after which we ended the experiment.

Ant Activity and Swarming

To measure ant activity, we counted the total number of worker ants visible on the plant

(i.e. outside the swollen thorns). To examine allocation to foraging vs allocation to plant

defence, we also counted the subset of ants that were feeding at extrafloral nectaries, and

that were crawling on leaves.

After these counts, we subjected trees to a disturbance simulating vertebrate herbivory.

We vigorously shook each plant across a ~10° arc for 10 seconds, then counted the

number of ants swarming on the plant every 30 seconds for five minutes. Similar trials

have successfully elicited ant responses in A. drepanolobium previously (e.g. Madden &

Young 1992). Ant responses rapidly diminished after 30 seconds, so we only analyzed

counts at that time point.

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Recruitment

After activity and swarming measures, we affixed three bait tubes halfway up the plant,

to measure the recruitment of ants to different food sources. One tube contained ~0.15

mL of pure clover honey, and the second contained ~0.15 cm3 of tuna meat. Since C.

nigriceps destroys axillary buds (Stanton et al. 1999), the third tube contained a single

axillary bud cushion collected from one of four source plants not used in the experiment.

At 10, 20, and 30 minutes following the attachment of the tubes, we counted the number

of worker ants found in the interior of each.

Statistical Analyses

We used generalized linear models with negative binomial errors in R (v. 2.15.2) to

analyze all data. We first tested all response variables with species, treatment, and their

interaction as predictors. As we were interested in how each species responded to

treatment, we additionally ran each model for the two species separately. Swarming

responses were highly variable between colonies, and so the models for swarming also

included pre-treatment (first day) swarming counts as a covariate, as well as the number

of swollen thorns on the plant, as a proxy for potential colony size. Covariate interactions

were not significant, and we excluded them from the model (Engqvist 2005).

Results

Species Differences

Crematogaster mimosae colonies recruited more to some food baits than C. nigriceps,

but we generally failed to detect differences between the two species (Table I). On the

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third day of the experiment, C. mimosae recruited more than C. nigriceps to honey baits,

but the difference was only significant 20 minutes after placement. Crematogaster

mimosae also recruited more to tuna baits on the fifth day, but the difference was only

significant at the 10- and 30-minute time points. No other responses significantly

differed between species (Table I), though swarming and recruitment to tuna showed

marginal species by treatment interactions, so we tested for treatment effects in each

species separately.

Ant Activity and Swarming

For C. nigriceps, PKG activator treatment somewhat decreased swarming in response to

a disturbance. On the final day of the experiment, Crematogaster nigriceps colonies in

the PKG activator treatment had marginally fewer ants swarming (X2=2.83, df=1,

p=0.092; Fig. 1). Colonies that had strong responses before treatment had similarly

strong responses after treatment (X2=20.42, df=1, p<0.0001), and colonies on plants with

more swollen thorns were also marginally more responsive (X2=3.70, df=1, p=0.054).

The effect of PKG activator treatment was not present on the third day of the experiment

(results not shown), and treatment did not affect the total activity of ants or their

allocation to nectaries or leaves (Table II).

Crematogaster mimosae colonies were completely unaffected by treatment. On the third

day of the experiment, swarming counts were significantly predicted by the same

measure before treatment (X2=23.03, df=1, p<0.0001), and plants with more swollen

thorns had marginally more responsive ants (X2=2.84, df=1, p=0.092), but treatment had

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no effect (X2=2.21, df=1, p=0.14; Fig. 2). On the fifth day, colonies that had been more

responsive before treatment were still more responsive (X2=22.09, df=1, p<0.0001), but

there was no effect of swollen thorn numbers (X2=1.36, df=1, p=0.24) or treatment

(X2=1.06, df=1, p=0.30). Ant activity was also unaffected by treatment (Table II)

Recruitment

The PKG activator also depressed the response of C. nigriceps to the tuna bait (Fig. 2).

On the fifth day, immediate recruitment (10 minutes after the bait was placed) was

significantly lower in the PKG activator treatment, though the treatment difference

attenuated over time, and was only marginally significant after twenty and thirty minutes

(Table II). Again, this difference was not present on the third day of treatment. There

were also no effects of treatment on recruitment to honey or axillary buds. Treatment had

no effect on the recruitment of C. mimosae to any bait type (Table II).

Discussion

The effect of the PKG activator on ants’ protective behaviour was limited. The activator

treatment did depress recruitment to protein baits in Crematogaster nigriceps, which is

consistent with Lucas & Sokolowski’s (2009) finding that activator treatment made

Pheidole pallidula ants less inclined to collect mealworms. However, activator treatment

also appeared to depress the response of C. nigriceps to shaking of the tree. This result is

inconsistent with the findings reported in Chapter Two, where we found that PKG

activation made Allomerus octoarticulatus workers more aggressive towards herbivores

that threatened their host plants. Treatment did not affect the total number of ants active

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on the plants, nor their allocation to nectaries or leaves. It also did not affect their

recruitment to honey or axillary buds. In C. mimosae, no measures were affected by

treatment.

There are a number of potential explanations for the inconsistencies between this study

and that described in Chapter Two, and between the two species studied here. First, it is

highly likely that the genetic architecture underlying the traits of interest varies across

taxa. The effect of foraging orthologs on food-related behaviour varies between

Drosophila melanogaster and C. elegans (Fitzpatrick & Sokolowski 2004), as well as

within Hymenoptera (Ben-Shahar et al 2002, Tobback et al. 2008, Kodaira et al. 2009,

Tobback et al. 2011) and within ants in particular (Ingram et al. 2005, Lucas &

Sokolowski 2005, Ingram et al. 2011). The effect of foraging orthologs on plant-defence

behaviours could be similarly variable. Though strong variation in gene regulation seems

unlikely to explain differences between two species within the same genus, differences

may have arisen due to demographic differences: C. mimosae has higher worker densities

per thorn (Palmer 2004), and this could dilute any perturbations to their behaviour. Thus

species could simply differ in the way PKG activity is regulated or affected by treatment.

Differences in results between this study and the one described in Chapter Two could

also indicate that the behaviours measured are in fact not comparable. In Chapter Two,

we measured how many ants attacked grasshoppers, as invertebrate herbivores are the

major defoliators of Cordia nodosa (Dejean et al. 2004); in this study, we measured

swarming after trees were disturbed, since this behaviour deters vertebrate herbivores

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(Madden & Young 1992), which are more important to Acacia (Stanton & Palmer 2011).

Though these behaviours are both, broadly, ‘anti-herbivore behaviours’, we would not

necessarily expect them to have the same genetic basis. This may also explain

inconsistencies among previous studies. For instance, though Lucas and Sokolowski

(2009) and Ingram et al. (2011) found opposing associations between foraging

expression and food-collection behaviour, this comparison was between seed-collecting

and predatory ants, respectively. Seed-carrying and prey-hunting behaviours may have

distinct evolutionary origins, and so we would not expect the genetic basis to be

identical, even though they are both generally foraging behaviours.

Finally, it is likely that much of the failure to detect consistent treatment effects can be

attributed to issues with the study. The study was conducted across a short time scale

(five days, as compared with two weeks in Chapter Two), and suffered from low sample

sizes, reducing statistical power. Indeed, though the differences between the two

Crematogaster species are well established (e.g. Palmer et al. 2000, Stanton & Palmer

2011), we failed even to detect consistent differences between them, though the

differences we did detect (some evidence of higher recruitment to food by C. mimosae)

are consistent with expectations (Palmer 2003). While the greenhouse setting was

intended to minimize variation in environmental conditions, the setting was highly

unnatural. Colonies were removed from their original host trees and re-introduced to new

ones, sometimes after several months. Further, ants patrolling the trees encountered

herbivores and competitors they would not face in a natural setting, including mealybugs,

spider mites, and Cardiocondyla obscurior ants. These factors introduced substantial

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variation into their responses, and obscured treatment effects that may have been present.

The unnatural context also makes it difficult to conclude that the limited effects detected

would be similar in a natural setting.

However, the limited results do suggest that it would be worthwhile to repeat a similar

study with a larger number of plants in a natural setting. Additionally, this study still may

indicate that the influence of genes on ecological interactions can vary substantially

between taxa. However, it also demonstrates that it is important to measure consistent,

comparable behaviours across species in order to draw any firm conclusions about how

gene effects change between systems. And finally, it demonstrates that the effects of

genes on species interactions may be quite subtle, and easily swamped by other sources

of variation, or affected by differences in context. It remains clear that there is much left

to be explored in terms of how genes may influence cooperation between species.

Acknowledgments

We thank the Pierce Lab at Harvard for collection of the plant population, and for access

to lab space and equipment. We thank Chris Baker, Julianne Pelaez, Jignasha Rana, and

Kadeem Gilbert for maintaining colonies and for assistance with the experiment.

Research was supported by a John Templeton Grant to Naomi Pierce, and KMT was

supported by an NSERC Michael Smith Foreign Study Supplement.

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References

Ben-Shahar, Y., Robichon, A., Sokolowski, M. B., & Robinson, G. E. (2002). Influence

of gene action across different time scales on behavior. Science, 296(5568), 741–4.

doi:10.1126/science.1069911

Bronstein, J. L. (1994). Our current understanding of mutualism. The Quarterly Review

of Biology, 69(1), 31–51.

Bronstein, J. L., Alarcón, R., & Geber, M. (2006). The evolution of plant-insect

mutualisms. The New Phytologist, 172(3), 412–28. doi:10.1111/j.1469-

8137.2006.01864.x

De Mita, S., Ronfort, J., McKhann, H. I., Poncet, C., El Malki, R., & Bataillon, T.

(2007). Investigation of the demographic and selective forces shaping the nucleotide

diversity of genes involved in Nod factor signaling in Medicago truncatula.

Genetics, 177(4), 2123–33. doi:10.1534/genetics.107.076943

Dejean, A., Quilichini, A., Delabie, J. H. C., Orivel, J., Corbara, B., & Gibernau, M.

(2004). Influence of its associated ant species on the life history of the

myrmecophyte Cordia nodosa in French Guiana. Journal of Tropical Ecology,

20(6), 701–704. doi:10.1017/S026646740400183X

Engqvist, L. (2005). The mistreatment of covariate interaction terms in linear model

analyses of behavioural and evolutionary ecology studies. Animal Behaviour, 70(4),

967–971. doi:10.1016/j.anbehav.2005.01.016

99  

 

Fitzpatrick, M. J., Ben-Shahar, Y., Smid, H. M., Vet, L. E. M., Robinson, G. E., &

Sokolowski, M. B. (2005). Candidate genes for behavioural ecology. Trends in

Ecology & Evolution, 20(2), 96–104. doi:10.1016/j.tree.2004.11.017

Fitzpatrick, M. J., & Sokolowski, M. B. (2004). In search of food: Exploring the

evolutionary link between cGMP-dependent Protein Kinase (PKG) and behaviour.

Integrative and Comparative Biology, 36, 28–36.

Heil, M., & McKey, D. (2003). Protective ant-plant interactions as model systems in

ecological and evolutionary research. Annual Review of Ecology, Evolution, and

Systematics, 34(1), 425–553. doi:10.1146/annurev.ecolsys.34.011802.132410

Hocking, B. (1970). Insect associations with the swollen thorn acacias. Transactions of

the Royal Entomological Society of London, 122(7), 211–255.

Ingram, K. K., Kleeman, L., & Peteru, S. (2011). Differential regulation of the foraging

gene associated with task behaviors in harvester ants. BMC Ecology, 11(1), 19.

doi:10.1186/1472-6785-11-19

Ingram, K. K., Oefner, P., & Gordon, D. M. (2005). Task-specific expression of the

foraging gene in harvester ants. Molecular Ecology, 14(3), 813–8.

doi:10.1111/j.1365-294X.2005.02450.x

Janson, E. M., Stireman, J. O., Singer, M. S., & Abbot, P. (2008). Phytophagous insect-

microbe mutualisms and adaptive evolutionary diversification. Evolution, 62(5),

997–1012. doi:10.1111/j.1558-5646.2008.00348.x

Kodaira, Y., Ohtsuki, H., Yokoyama, J., & Kawata, M. (2009). Size-dependent foraging

gene expression and behavioral caste differentiation in Bombus ignitus. BMC

Research Notes, 2, 184. doi:10.1186/1756-0500-2-184

100  

 

Lucas, C., & Sokolowski, M. B. (2009). Molecular basis for changes in behavioral state

in ant social behaviors. Proceedings of the National Academy of Sciences of the

United States of America, 106(15), 6351–6. doi:10.1073/pnas.0809463106

Madden, D., & Young, T. P. (1992). Symbiotic ants as an alternative defense against

giraffe herbivory in spinescent Acacia drepanolobium. Oecologia, 91, 235–238.

Osborne, K. A., Robichon, A., Burgess, E., Butland, S., Shaw, R. A., Coulthard, A.,

Pereira, H. S., et al. (1997). Natural behavior polymorphism due to a cGMP-

dependent protein kinase of Drosophila. Science, 277(5327), 834–836.

doi:10.1126/science.277.5327.834

Palmer, T. M. (2003). Spatial habitat heterogeneity influences competition and

coexistence in an African acacia ant guild. Ecology, 84(11), 2843–2855.

Palmer, T. M. (2004). Wars of attrition: Colony size determines competitive outcomes in

a guild of African acacia ants. Animal Behaviour, 68(5), 993–1004.

doi:10.1016/j.anbehav.2004.02.005

Palmer, T. M., Young, T. P., Stanton, M. L., & Wenk, E. (2000). Short-term dynamics of

an acacia ant community in Laikipia, Kenya. Oecologia, 123(3), 425–435.

doi:10.1007/s004420051030

Ramírez, S. R., Eltz, T., Fujiwara, M. K., Gerlach, G., Goldman-Huertas, B., Tsutsui, N.

D., & Pierce, N. E. (2011). Asynchronous diversification in a specialized plant-

pollinator mutualism. Science, 333(6050), 1742–6. doi:10.1126/science.1209175

Redecker, D., Kodner, R., & Graham, L. E. (2000). Glomalean fungi from the

Ordovician. Science, 289(5486), 1920–1921. doi:10.1126/science.289.5486.1920

101  

 

Stanton, M. L., & Palmer, T. M. (2011). The high cost of mutualism: Effects of four

species of East African ant symbionts on their myrmecophyte host tree. Ecology,

92(5), 1073–82.

Stanton, M. L., Palmer, T. M., Young, T. P., Evans, A., & Turner, M. L. (1999).

Sterilization and canopy modification of a swollen thorn acacia tree by a plant-ant.

Nature, 401, 578–581.

Tobback, J., Heylen, K., Gobin, B., Wenseleers, T., Billen, J., Arckens, L., &

Huybrechts, R. (2008). Cloning and expression of PKG, a candidate foraging

regulating gene in Vespula vulgaris. Animal Biology, 58(4), 341–351.

doi:10.1163/157075608X383665

Tobback, J., Mommaerts, V., Vandersmissen, H. P., Smagghe, G., & Huybrechts, R.

(2011). Age- and task-dependent foraging gene expression in the bumblebee

Bombus terrestris. Archives of Insect Biochemistry and Physiology, 76(1), 30–42.

doi:10.1002/arch.20401

Young, T. P., Stubblefield, C. H., & Isbell, L. A. (1997). Ants on swollen-thorn acacias:

Species coexistence in a simple system. Oecologia, 109, 98–107.

Zhang, W., Kramer, E. M., & Davis, C. C. (2012). Similar genetic mechanisms underlie

the parallel evolution of floral phenotypes. PLoS One, 7(4), e36033.

doi:10.1371/journal.pone.0036033

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Tables

Table I. Results (X2, p-value) for tests of differences between Crematogaster mimosae

and C. nigriceps, and between the PKG activator treatment and the control. Response

variables are ant activity counts, swarming counts, and recruitment, on the third and fifth

days of the experiment. For recruitment tests, results are shown for counts of ants 10, 20,

and 30 minutes after placement of the bait. Marginally significant differences are

highlighted in italics, and significant differences are highlighted in bold. In all cases,

there is one degree of freedom.

  predictor  response   species   treatment   species  x  

treatment  total  ant  activity                day  three   1.52,  0.22   0.74,  0.39   0.18,  0.67          day  five   1.17,  0.28   0.52,  0.47   0.04,  0.85          ants  on  leaves                day  three   1.14,  0.29   0.61,  0.43   0.03,  0.85          day  five   0.31,  0.58   0.06,  0.80   0.12,  0.73          ants  at  nectaries                day  three   0.02,  0.89   0.05,  0.82   0.02,  0.90          day  five   0.17,  0.68   0.18,  0.67   0.01,  0.92          swarming                  day  three   0.00,  0.99   2.27,  0.13   3.54,  0.06            day  five   0.08,  0.78   0.94,  0.33   2.63,  0.10          recruitment  to  tuna                  day  three:                        10  minutes   2.14,  0.14   0.01,  0.92   0.01,  0.93                  20  minutes   1.22,  0.27   0.00,  0.98   0.32,  0.57                  30  minutes   1.72,  0.19   0.00,  0.97   0.77,  0.38          day  five:                        10  minutes   5.55,  0.02   0.05,  0.83   1.78,  0.18                  20  minutes   2.09,  0.15   0.03,  0.86   0.87,  0.35                  30  minutes   4.34,  0.04   0.06,  0.81   2.88,  0.09  

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Table I continued

  predictor  response   species   treatment   species  x  

treatment  recruitment  to  sugar                day  three:                        10  minutes   2.24,  0.13   0.12,  0.73   0.79,  0.37                  20  minutes   5.11,  0.02   0.03,  0.87   1.60,  0.21                  30  minutes   1.88,  0.17   0.04,  0.85   0.90,  0.34          day  five:                        10  minutes   0.22,  0.64   1.58,  0.21   0.70,  0.40                  20  minutes   0.06,  0.80   2.89,  0.09   1.27,  0.26                  30  minutes                recruitment  to  buds                day  three:                        10  minutes   0.66,  0.42   0.08,  0.78   0.04,  0.85                  20  minutes   0.99,  0.32   0.46,  0.50   0.62,  0.43                  30  minutes   0.43,  0.51   0.50,  0.48   0.69,  0.41          day  five:                        10  minutes   0.16,  0.69   0.01,  0.93   0.27,  0.61                  20  minutes   0.00,  0.96   0.00,  1.00   0.02,  0.90                  30  minutes   0.06,  0.80   0.45,  0.50   0.03,  0.87  

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Table II. Results for tests of effects of PKG activator treatment (vs. control) in

Crematogaster nigriceps and C. mimosae, on the third and fith days of treatment. For

recruitment tests, results are shown for counts of ants 10, 20, and 30 minutes after

placement of the bait. On the fifth day, no C. nigriceps workers recruited to sugar.

Marginally significant differences are highlighted in italics; the significant difference is

highlighted in bold. In all cases, there is one degree of freedom.

  C.  nigriceps   C.  mimosae  response   X2   p   X2   p  recruitment  to  tuna                  day  three:                          10  minutes   0.060   0.81   0.0082   0.93                  20  minutes   0.71   0.40   0.00064   0.98                  30  minutes   1.41   0.24   0.0019   0.97          day  five:                          10  minutes   4.53   0.033   0.033   0.86                  20  minutes   2.64   0.10   0.87   0.35                  30  minutes   3.46   0.063   0.47   0.49            recruitment  to  sugar                  day  three:                          10  minutes   1.39   0.24   0.11   0.74                  20  minutes   0.18   0.67   0.032   0.86                  30  minutes   1.11   0.29   0.034   0.85          day  five:                          10  minutes   -­‐   -­‐   1.17   0.28                  20  minutes   -­‐   -­‐   2.03   0.15                  30  minutes   -­‐   -­‐   1.45   0.23            recruitment  to  buds                  day  three:                          10  minutes   0.00   1   0.070   0.79                  20  minutes   0.18   0.67   0.45   0.50                  30  minutes   0.24   0.63   0.43   0.51          day  five:                          10  minutes   0.62   0.43   0.067   0.80                  20  minutes   0.05   0.83   0.00   1                  30  minutes   0.25   0.61   0.48   0.49  

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Table II continued

  C.  nigriceps   C.  mimosae  response   X2   p   X2   p  total  ant  activity                  day  three   0.12   0.73   0.71   0.40          day  five   0.33   0.56   0.42   0.52            ants  on  leaves                  day  three   0.34   0.56   0.72   0.39          day  five   0.55   0.46   0.078   0.78            ants  at  nectaries                  day  three   0.22   0.64   0.042   0.84          day  five   0.14   0.71   0.13   0.72  

106  

 

Figures

Figure 1. Mean (±SE) number of C. nigriceps ants swarming on plants in the control and

PKG activator treatment 30 seconds after a simulated vertebrate disturbance, after four

days of treatment.

107  

 

Figure 2. Mean (±SE) number of C. mimosae ants swarming on plants in the control and

PKG activator treatment 30 seconds after a simulated vertebrate disturbance.

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Figure 3. Mean (±SE) number of C. nigriceps ants, four days after treatment, in tuna

baits in the control (black) and PKG activator (white) treatment 10, 20, and 30 minutes

after bait placement. The treatment difference is significant (p = 0.033) at 10 minutes,

and marginally significant at 20 (p=0.10) and 30 (0.063) minutes.