A Thesis

entitled

Influence of Soil-Quality on Coffee-Plant Quality and a Complex Tropical Insect Food

Web

by

David J. Gonthier

Submitted to the Graduate Faculty as partial fulfillment of the requirements for the

Master of Science in Biology (Ecology track)

Dr. Stacy Philpott, Committee Chair

Dr. Scott Heckathorn, Committee Member

Dr. Ivette Perfecto, Committee Member

Dr. Patricia Komuniecki, Dean College of Graduate Studies

The University of Toledo

May 2010

Copyright 2010, David J. Gonthier

This document is copyrighted material. Under copyright law, no parts of this document may be reproduced without the expressed permission of the author.

An Abstract of

Influence of Soil-Quality on Coffee-Plant Quality and a Complex Tropical Insect Food

Web

by

David J. Gonthier

Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Master of Science in Biology (Ecology track)

The University of Toledo May 2010

Tropical systems are complex, species diverse, and are often regulated by top-down forces (higher trophic levels control lower trophic levels). In many ecosystems insects, especially herbivores and their mutualists, may be strongly affected by plant quality and other bottom-up controls (nutrient availability, plant genetic variation, ect.). Yet few have asked how plant quality (nutritional and defensive plant traits) can contribute to the population regulation and the complexity of these systems. In this thesis, I investigate the importance of soil-quality to both the elemental and secondary metabolite content in coffee and ask how changes to plant quality can influence hemipteran herbivores, their ant-mutualists, predators, and insect communities in a tropical coffee agroecosystem.

First, I investigated the relationship between nitrogen fertilization and coffee growth, carbon and nitrogen balance, and the production of caffeine, one of coffee’s most abundant secondary metabolites. Second, I determined how elemental nutrients and caffeine content correlated with the distribution of the phloem-feeding herbivore, Coccus viridis, in the proximity of Azteca instabilis ant nests, a keystone mutualist with C.

iii viridis. Third, I examined whether changes in soil-quality alter coffee-plant quality (N and caffeine), and how soil-quality and the presence of ant-mutualists regulate population size of C. viridis, the abundance of ant partners, the abundance of natural enemies, and the insect community as a whole. The laboratory experiment suggested N fertilization resulted in greater leaf N and phloem caffeine exudation. However, root, stem, leaf, and total caffeine did not differ with fertilization treatment. In the field, I found a positive association between leaf N and the density of C. viridis. Stepwise multiple regression revealed that A. instabilis ant activity and leaf N explained 45 % in the variation in C. viridis abundance. Caffeine concentration in coffee leaves and phloem exudates had no relationship with C. viridis density. Finally, in the field experiment, high-soil-quality resulted in higher plant growth rate, greater leaf N, and greater phloem caffeine. High- soil-quality plants had 45% greater C. viridis population sizes than plants in the low- quality treatment. Additionally ant-exclusion also increased scale population size by

34% relative to control plants. However, greater C. viridis density did not result in greater recruitment of A. instabilis. Overall, there were 40% more arthropods on high-soil-quality treatment plants relative to low and 20% more arthropods on ant-excluded plants than control. However, this result was driven by changes in the abundance of ants and hemipterans. Additional experimentation revealed Pheidole sp. ants increased recruitment by more than three times to C. viridis on high-soil-quality plants relative to low. Thus, soil-quality, plant growth rate, and percent N appear to be important in the distribution and population size of C. viridis and for recruitment of Pheidole ant-mutualists.

However, other factors likely more strongly affect A. instabilis tending of C. viridis.

Further, caffeine may not be an important regulator of C. viridis in field settings. Overall,

iv soil-quality had important impacts at the community level through changes in abundance of the dominant arthropod group (ant-hemipteran mutualism) on coffee seedlings. This study contributes to the under-represented literature describing the effects of bottom-up forces in tropical systems by 1) showing how host-plant quality can affect the density and growth of a herbivore in coffee agroecosystems and 2) comparing the indirect effect of soil-quality on the recruitment of multiple ant species to hemipteran mutualists.

v

Acknowledgments

Many people played important roles in the production of this thesis. S. Philpott, contributed to all aspects of research. G. Dominguez helped with the majority of field work. J. Witter & A. Spongberg provided equipment and laboratory work for analysis of caffeine. J. Frantz and the USDA provided elemental analysis. C. Murnen, L. Moorhead,

G. Pardee, R. Friedrich helped in lab and field work. S. Heckathorn and I. Perfecto contributed greatly to the preparation of this thesis. J. Vandermeer and K. Ennis aided in field work and project design. The Colegio de la Frontera Sur was gracious in allowing the use of their laboratories and A. De la Mora, E. Ruiz Suarez, R. Bello, G. M.

Gonzalez, M. Sokolov, and Ibarra‐Núñez aided in logistics, equipment, and storing of samples. The Peter’s family allowed work on their coffee plantation. This research was supported by University of Toledo Travel Grant, Grant in aid of Research- Sigma xi,

Grant in aid of research- Society of Integrated and Comparative biology, start up funds to

Stacy Philpott, and NSF # DEB-0349388 to I. Perfecto and J. Vandermeer.

vi

Table of Contents

Abstract...... iii

Acknowledgments...... v

Table of Contents...... Vvii

List of Tables...... x

List of Figures...... xii

1 Chapter 1: Introduction and background...... 1

1.1 Introduction...... 1

1.2 Study System...... 5

1.3 Research Objectives...... 7

2 Chapter 2: Effect of nitrogen availability on plant growth, leaf nutrient

concentrations, and the production of caffeine in coffee ...... 9

2.1 Materials & Methods...... 9

2.1.1 Experimental Setup...... 9

2.1.2 Plant Growth Measurements & Water Status...... 10

2.1.3 Plant Caffeine Concentration & Content...... 11

vii 2.1.4 Plant Nitrogen & Carbon...... 12

2.1.5 Statistical Analysis ...... …………………...... 13

2.2 Results...... ………………………………………...... 13

2.2.1 Plant growth and water status…………………………………...…13

2.2.2 Leaf carbon & nitrogen balance………………………………...….14

2.2.3 Effect of Nitrogen availability on caffeine production……….……15

2.3 Discussion……………………………………………………….…..…...16

3 Chapter 3: Influence of plant quality on the distribution of a keystone ant-

hemipteran mutualism in a coffee agroecosystem……………...….…………25

3.1 Materials & Methods……………………………………..……….……..25

3.2 Results…………...... …………………………………………………..28

3.3 Discussion…………………..……………………………………………29

4 Chapter 4: Impact of soil-quality on plant quality and a coffee insect

community….………………………………………………………………...…34

4.1 Material & Methods…………..………………………………………….34

4.1.1 Field methods………………………………………..……………..34

4.1.2 Data Analysis……………………………………………..………..38

4.1.3 Pheidole sp. recruitment to scale insects ………………………….40

4.1.4 Effect of ant-exclusion on Azya orbigera larval

foraging...……...…………..…………………………………….....41

4.2 Results……………………………..……………………………………..40

viii 4.2.1 Effect of soil-quality treatment on scales, aphids, and ant-

mutualist……………………………...…………………………..40

4.2.2 Effect of soil and ant treatments on C. viridis predators, parasitoids,

and pathogens.…….…………………………………….....……..41

4.2.3 Insect community……………….…………………………...……..42

4.2.4 Plant growth and quality……………………..…………………….42

4.2.5 Plant and food web variables correlated with green scales….……..43

4.2.6 Effect of soil-quality on Pheidole sp. recruitment to C. viridis……44

4.2.7 Effect of ant-exclusion on Azya orbigera larval foraging……...….44

4.3 Discussion..….………………………………….………………………..45

4.3.1 Effect of treatments on green scale growth………………………..45

4.3.2 Effect of treatments on ant attendance of green scales…………….47

4.3.3 Effect of treatments on predators, parasitoids, and pathogens……..48

4.3.4 Community level effects of treatments……………………...……..49

4.3.5 Effect of soil-quality treatment on coffee seedling growth and

quality...... 50

4.3.6 Pheidole recruitment to scales on across soil-quality treatments….51

4.3.7 Conclusions…………………...……………………………..….….52

5 Conclusions……………………………………………………………………...67

5.1 The effect of nitrogen availability and soil-quality on coffee-plant

quality……………………………………………………………………67

ix 5.2 Effect of soil-quality and plant quality on green scale

growth……...... …67

5.3 Effect of soil-quality on species interactions……...………………….….68

5.4 Effect of soil-quality on arthropod community………...... …………..….69

5.5 Future directions…………………………………………………………69

5.6 Conclusions..……………………………….………….…………..……..71

References…………………………………………………………………..……….…..72

x

List of Tables

2-1 Effect of nitrogen treatment on growth rate, change in leaf number, and change in

stem diameter……………………………………………………………….……19

2-2 Coffee seedling biomass and water status across three nitrogen treatments…….20

2-3 Effect of nitrogen fertilization on carbon, nitrogen, and carbon: nitrogen ratio....21

2-4 Effect of nitrogen fertilization treatment on dry mass caffeine concentration and

content…………………………………...………………………………...……..22

3-1 Field and plant quality characteristics for coffee plants with high- or low-density

concentrations of Coccus viridis scale insects adjacent to trees with Azteca

instabilis ant nests………………………………………………………………..31

4-1 Characteristics of the three soil-quality treatments………………………………54

xi 4-2 Effect of soil-quality and ant-exclusion treatment on arthropods………………..55

4-3 Effect of soil-quality and ant-exclusion treatments on common arthropods…….57

4-4 Effect of soil-quality and exclusion treatments on predators, parasitoids, and

pathogens of Coccus viridis…………………………………………………….58

4-5 Effect of soil-quality and ant-exclusion treatment on coffee insect

community…………………………………………….…………………….…..60

4-6 Effect of soil-quality on coffee leaf area, growth rate, elemental nutrients, and leaf

and phloem caffeine………………………………………………………….…61

4-7 Correlation table with green scales vs. independent variables………………….62

xii

List of Figures

1-1 Diagram of species interactions across trophic levels. The effect of nutrient

availability on coffee host nitrogen and caffeine level (a)……………..………….8

2-1 Mean phloem caffeine exuded from leaf petioles (µl L-1) across nitrogen

fertilization treatments………………………………………………..………….23

4-1 The effect of soil-quality and ant-exclusion treatments on mean number of total

scales averaged across the five sampling events………………...……………….64

4-2 The effect of soil-quality treatment on the number of Pheidole sp. workers per

coffee seedlings with Coccus viridis…………….……..……………………..….65

4-3 The effect of soil-quality treatment on the number of Pheidole sp. per scale insect

on coffee seedlings with Coccus viridis……………………..……………….….65

xiii 4-4 The effect of ant-exclusion treatment on scale removal by Azya orbigera

larvae………………………………………………………………..…………...66

xiv

Chapter 1

Introduction and Background

1.1 Introduction

Ecologists have long debated how different biotic and abiotic factors control populations and provide structure to ecological communities (Hairston et al. 1960,

Murdoch 1966, Hunter & Price 1992). In the past, debate has centered on determining which force is solely responsible for patterns observed within a given community.

However today, many move to understand how multiple biotic and abiotic factors may combine or interact to structure communities (Hunter & Price 1992). Many systems are still described as being primarily structured by top-down or bottom-up controls, and few comparative studies have been conducted. Tropical humid systems, as an example, are greatly complex, species diverse systems that are often cited as regulated by top-down effects. Specifically, tropical insect communities are often controlled by predation from birds, bats, and lizards (e.g. Spiller & Schoener 1990, Dial & Roughgarden 1995,

Williams-Guillen et al. 2009, Mooney et al., in press). But insects, especially herbivores and their mutualists may be strongly affected by plant quality (Awmack & Leather 2002,

Mooney & Agrawal 2008). Despite the pervasive importance of both predation and plant

1 traits for structuring tropical insect communities, few have examined the absolute or relative importance of plant quality or resource availability or the combined effects of top-down and bottom-up forces in structuring tropical communities (but see Dyer et al.

2004, Gruner 2004).

Variation in plant nutritional and defensive traits (i.e. plant quality) may affect the distribution and population dynamics of herbivores (Underwood 1999, Underwood &

Rausher 2000, Awmack & Leather 2002, Underwood 2004). Plant chemical defenses

(e.g. alkaloids) can reduce hemipteran growth rates (Levin 1976, Sipura 2002 Agrawal

2004) and alter the spatial distribution of hemipterans (Vrieling et al. 1991). Hemipteran population growth may also be limited by low amino acid content in phloem saps of host- plants (Ponder et al. 2000). Further, hemipteran growth and density generally increase when host-plants receive nitrogen fertilizer (McClure 1980, Breton & Addicott 1992,

Kainulainen et al. 1996, Straw & Green 2001, Awmack & Leather 2002, Stadler et al.

2002, Morales & Beal 2006) or when host-plant genotypes express high phloem nitrogen

(Wimp & Whitham 2001, Mooney & Agrawal 2008, Johnson 2008). However, nutrient availability can simultaneously alter both nutritional quality and secondary defenses important to herbivore growth (Herms & Mattson 1992, Bryant et al. 1983, Hamilton et al. 2001, Lerdau & Coley 2002, Nitao et al. 2002). For example, the production of carbon-based condensed tannins and phenolic glycosides in quaking aspen (Populus tremuloides) declined with nitrogen fertilization (Bryant et al. 1987). On the other hand, secondary metabolites can increase as plant nutrition increases. In yaupon holly (Ilex vomitoria), production of the nitrogen-based metabolite caffeine increased with higher nitrogen availability (Palumbo et al. 2007).

2 Variation in host-plant quality may also have strong effects on ant-hemipteran mutualisms. In an ant-hemipteran mutualism, the hemipteran (sap-sucking herbivores) offers ants a honeydew reward in return for protection from predators or through (Stadler

& Dixon 2008). Variation in host-plant quality may directly affect hemipteran fitness through diet or may indirectly mediate their fitness by altering tending behavior of their ant-mutualists (Cushman 1991). Higher host-plant quality may lead to increases in hemipteran density, greater honeydew rewards, and thus more ant attendance (Cushman

1991, Strauss 1987, Baylis & Pierce 1992, Billick et al. 2005). For instance, fertilization of Artemisia sp., an herbaceous weed, increased the density of aphids and membracids and led to subsequent increases in ant attendance (Strauss 1987). However, honeydew rewards offered to ants are byproducts of hemipteran feeding on the phloem or xylem saps, thus plant quality may control honeydew quality. Indeed, increased quality of honeydew can result in increased ant attendance (Cushman 1991, Völkl et al. 1999,

Fischer et al. 2001, Yao & Akimoto 2002). Genetic variation in milkweed hosts led to an increase of ant attendance on plants with more aphids, and increased ant recruitment per aphid on plants of high quality genotypes (Mooney & Agrawal 2008).

Alteration of ant-hemipteran mutualisms may affect both hemipteran survival and other insect members of the food web. In cases where predation pressure on hemipterans is intense, feeding on high quality host-plants may lead to greater hemipteran survival through increased ant protection (Cushman 1991). Indeed, in sub-tropical Australia,

Jalmenus evagoras (honeydew-excreting Lepidopteran larvae) feeding on fertilized

Acacia hosts were better- attended by ants and had greater survivorship than those feeding on un-fertilized Acacias (Baylis & Pierce 1991). In other instances, hemipterans

3 feeding on high-quality plants with increased ant attendance did not have greater survivorship (Wimp & Whitham 2001, Morales & Beal 2006, Mooney & Agrawal 2008).

The presence of hemipteran-tending ants can influence the abundance, diversity,

(Wimp & Whitman 2001, Kaplan & Eubanks 2005) and community composition (Floren et al. 2002) of insects present in a community. However, host-plant quality could also impact abundance (Strauss 1987) and composition, but few (but see Dyer et al. 2004,

Gruner 2004) have considered if host-plant quality and ant-hemipteran mutualisms simultaneously influence the structure of insect communities, especially in complex systems.

The indirect effect of host-plant quality can also alter other interactions at higher trophic levels, such as predation, parasitism, and pathogenesis. For example, fitness and survival of parasitoid wasps may vary when they parasitize herbivores feeding on different quality host plants (Ode 2006). Gut parasites of honeybees are often reduced by the nectar alkaloids their host honeybee consumes (Manson et al. 2010). Some effects of the entomopathogenic fungus, Verticillium lecanii, on its aphid hosts are mediated through the cereal host species consumed by aphids (Hsiao & Khachatourians 1997).

Few have used tropical systems to examine the impacts of plant quality on insect communities because of their inherent complexity. However, coffee agroecosystems are considered model systems for the study of tropical ecology because they contain complex food webs that are less heterogeneous at local levels (Greenberg et al. 2008). Species interactions, such as mutualism and predation, appear to structure the local distributions of organisms within coffee agroecosystems (Perfecto et al. 2004, Vandermeer & Perfecto

2006, Vandermeer et al. 2008, Vandermeer et al. in press). At the same time, coffee

4 agroecosystems provide an ideal arena to ask how bottom-up forces structure tropical insect communities because coffee systems vary along resource axes, such as nutrient and light availability with changes in agricultural management. Additionally, coffee plants vary substantially in concentrations of secondary metabolites, like caffeine and chlorogenic acid, compounds with known biological consequences for insect communities (Nathanson 1984, Ikonen et al. 2001, Magalhães et al. 2008). Thus, coffee- plant quality may vary in many ways, thereby affecting insect communities via several pathways. Further, in coffee agroecosystems, ant-hemipteran mutualisms play important roles in structuring the insect community (Vandermeer & Perfecto 2006, Vandermeer et al. in press) and predation pressure on hemipterans is strong (Uno in review, b). In sum, coffee systems offer a model system for examining contributions of both bottom-up and top-down forces in structuring insect communities.

1.2 Study System

Here, I use coffee agroecosystems as a model system to ask how soil-quality affects host-plant quality, and how changes in host-plant quality can alter the distribution and strength of a keystone ant-mutualism that is dominant in this ecosystem. In coffee plantations in southern Mexico, the coffee green scale (Coccus viridis Green [Hemiptera:

Coccidae]) feeds on the phloem of coffee (Coffea arabica L.). This scale insect forms associations with many ant species, but reaches highest densities with a dominant arboreal ant, Azteca instabilis F. Smith (Hymenoptera: Formicidae). Generally, as distance increases away from A. instabilis nest trees, the density of green scales on coffee bushes declines. An assembly of natural enemies, including predators, parasites, and

5 pathogens, attack green scales in the coffee agroecosystem. These predators quickly remove un-tended scales (~90% in fewer than 40 days) (Uno in review a, b), confirming the obligatory nature of the mutualism (ability of Azteca to defend) and the severity of predation. Two parasitoid wasps (Encyrtidae) have been reared from green scales.

However, the adults and larvae of Azya orbigera Mulsant (Coleoptera: Coccinellidae) are the major predators in shade coffee plantations (Uno in reviewa, Liere & Perfecto 2008).

Additionally, C. viridis is attacked by an entomopathogenic white halo fungus,

Lecanicillium lecanii (Vandermeer et al. 2009).

Coffee also produces caffeine that may affect the insect community on coffee. The secondary metabolite caffeine, a methylxanthine, contains four nitrogen atoms in its chemical structure (Filho & Mazzafera 2000) and caffeine production varies with limitation of essential minerals (Mazzafera 1999). Caffeine is present in the leaf tissues and xylem of coffee (Mazzafera & Gonçalves 1999), and although contrary to past research (discussed in Mazzafera & Gonçalves 1999), our preliminary findings suggest caffeine can be found within the phloem. The effect of caffeine on herbivores appears to be variable; specialist species appear unaffected, but caffeine may protect coffee from generalists (Nathanson 1984, Hewavitharanage et al. 1999, Filho & Mazzafera 2000,

2003, Hollingsworth et al. 2002, Magalhães et al. 2008). A recent study found a negative correlation between the concentration of coffee leaf caffeine and green-scale population size (Fernandes 2007). Additionally, increasing fertilization of host plants with both N and K positively increased green-scale populations, suggesting both the nutrition and defense of coffee are important to green scale fitness (Fernandes 2007).

I investigated how variation in coffee host quality defined by nutritional and

6 defense traits, affects green scale herbivores, an ant-hemipteran mutualism, and the coffee insect community in a coffee agroecosystem. First, I investigated how total nitrogen [N] and caffeine content varies with nutrient availability provided to coffee plants. Second, in a coffee plantation I examined how the density of the ant-scale mutualism correlates with coffee host quality (N and caffeine). Third, in the field, I examined whether changes in soil-quality alter coffee-plant quality (N and caffeine), and whether plant quality regulates growth of scales or indirectly affects the protection by ant partners and predation rate of scales by beetles.

1.3 Research Objectives

The specific objectives of this research were to:

1) Explore the relationship between soil nitrogen availability and the nitrogen and

caffeine levels in coffee leaves (Fig. 1-1a).

2) Investigate the relationship between coffee green scale survival, growth, and

distribution in relation to coffee host quality (N and caffeine) (Fig. 1-1b).

3) Examine the indirect effects of coffee host quality (N and caffeine) on ant recruitment

of green scales (Fig. 1-1c).

4) Determine the indirect effect of coffee host quality (N and caffeine) on the predation

of green scales (Fig. 1-1d).

7

Figure 1-1. Diagram of species interactions across trophic levels. The effect of nutrient availability on coffee host nitrogen and caffeine level (a). The effect of host quality (N and caffeine) on green scale survival, growth, and distribution (b). The indirect effects of coffee host quality (N and caffeine) on ant attendance of scales (c). The indirect effect of coffee host quality (N and caffeine) on the predation of scales (d).

8

Chapter 2

Effect of nitrogen availability on plant growth, leaf nutrient concentrations, and the production of caffeine in coffee

To better understand how nutrient availability can influence the nutritional and defensive characters of coffee I conducted a nitrogen fertilization experiment with coffee seedlings and determined N effects on in plant growth rates, concentrations of leaf nutrients, and leaf and phloem caffeine.

2.1 Materials & Methods

2.1.1 Experimental Setup

To examine the influence of nitrogen availability on coffee plant growth, root, stem, leaf, and phloem caffeine concentrations, and leaf nitrogen, I conducted a growth chamber experiment. I obtained coffee seedlings (Coffea arabica L.) of approximately equal size (6-10 leaves) from Hirt’s Garden (Medina, OH). In February 2009, I repotted individual seedlings in 8 x 8-cm pots containing a 4:1 sand-to-soil mixture (Miracle-gro

9 Moisture control potting mix). Then, seedlings were transferred to a growth chamber

(CONVIRON PGR15) at the University of Toledo (UT). I set growth chamber conditions to mimic those of the understory of a high shaded coffee plantation; 104 µmol (photons) m-2 s-1 light (Araujo et al. 2008) on a 12:12 light-to-dark cycle, 60-90% relative humidity

(RH), and a temperature of 20-30 °C. In late February of 2009, I began applying three distinct nutrient treatments to coffee seedlings. In the low nutrient treatment (N = 25), I provided plants with 40 ml of half-strength Hoagland’s solution (Hoagland & Arnon

1950), without nitrogen and the respective elemental adjustments weekly (0.5 KH2PO4, 1

MgSO4, 1 Fe-EDTA, 0.9 MnCl2, 0.15 CuCl2, 0.15 ZnCl2, 0.45 H3BO3, 0.1 MoNa2O4, 2.5

K2SO4 mL/L, and 0.375 CaSO4 g/L) each week for the first 6 weeks. For the medium nutrient treatment (N = 25), I provided plants with 40 ml of the same half-strength

-1 Hoagland’s solution, but with an additional 0.5 mmol L NO3NH4. For the high nutrient treatment (N = 25), I provided 40 ml of the half strength Hoagland’s solution with 3

-1 mmol L NO3NH4. After 6 weeks, I transplanted seedlings to larger pots (13 width x 13 length x 15 cm deep) filled with sand. For the remainder of the experiment, I provided plants with 100 ml of respective treatment solutions twice a week for a total of 10 weeks

(February to May 2009) before destructive sampling occurred.

2.1.2 Plant Growth Measurements & Water Status

To quantify plant growth, I measured several plant traits at the onset of the experiment and every two weeks thereafter to compare differences across treatments.

Plant growth traits measured included stem diameter (approximately 1 cm above the cotyledon), number of leaves, leaf length, and leaf width. I used leaf measurements to

10 calculate total leaf area using the following empirically derived formula (elliptical area = length/2 × width/2 × π). To compare growth across treatments, I calculated the growth rate as final divided by initial total leaf area. I also compared the accumulation of number of leaves and stem diameter by subtracting initial from final for total number of leaves and stem diameter, respectively. After 10 weeks, I destructively sampled plants and measured total wet root, stem, and leaf weight (g). I then immediately placed plants on dry ice before oven drying plant tissues at 60 °C for 48 h and reweighing tissues for dry weights. To calculate percent water content, I subtracted dry weights from wet weight and divided by wet weight. To prepare plant samples for chemical analyses, I ground dried leaf, stem, and root samples for each seedling with a mortar and pestle in liquid N.

2.1.3 Plant Caffeine Concentration & Content

On the same date plants were harvested, I collected phloem samples from three leaves of six plants per treatment following methods from King and Zeevaart (1974).

Each of the leaves were 2nd newly expanding leaves approximately 0.1 - 0.4 g in fresh weight. I placed leaf petioles in 5 ml of 20 mmol Ethylenediaminetetraacetate (EDTA) for 6 hours in total darkness. The EDTA solution increases the efficiency of phloem exudation. Next, I analyzed 100 µl aliquots of phloem samples for caffeine concentration with Liquid Chromatography Tandem Mass Spectrometry (LC-ESI-MS/MS; Varian Inc.,

Walnut Creek, CA). Before analysis, I diluted samples to the working linear range of the instrument with methanol. MS/MS precursor and ion transitions monitored for caffeine were 195 to 138 and 195 to 110. Because leaf tissues also were submerged in the aqueous

EDTA solution it was important to determine how much caffeine may have been

11 extracted off of leaf surfaces. Therefore I created control leaf samples by inverting a leaf

(N = 3) into the vial so that only the leaf tip was submerged within the solution and its petiole pointing up out of the vial. These control samples were compared to sample phloem exudates samples with a two-sample t-test to ensure that caffeine was indeed a product of phloem exudation and not surface extraction. To compare caffeine phloem exudation across treatments, I calculated mean of the phloem samples (per plant) minus the mean of control samples.

To quantify the impacts of soil nitrogen availability on total caffeine content, I analyzed caffeine concentrations in seedling roots, stems, and leaves and calculated total seedling caffeine content. To prepare tissues for caffeine analysis, I extracted caffeine from leaf tissues by shaking 0.1 g of ground leaf tissue in 7.5 ml of methanol for 4 h.

Next, I passed 1.5 ml of sample through a 13 mm (0.45 µm pores) syringe filter and diluted liquid aliquots to the working linear range of the instrument. To control for

13 instrumental error, I added an internal standard ( C3-caffeine) with precursor and ion transitions monitored at 198.1 to 140.0. Samples were analyzed with LC-ESI-MS/MS. I ran plant samples in triplicate, unless plant material was insufficient, in which case I ran samples in duplicate or singles and reported averages or single values for each plant where necessary. To calculate caffeine content, I multiplied the caffeine concentration in a given plant tissue by the total dry biomass.

2.1.4 Plant Nitrogen & Carbon

To examine how N availability affected, nitrogen, carbon, and the carbon to nitrogen ratio (C:N) of leaf tissues, I analyzed dry leaf tissues for total N and C using a

12 C-H-N combustion analyzer (Perkin Elmer model 2400). I ran each plant sampled in triplicate (N = 3 per treatment). All instrumental measurements were conducted at UT and Application Technology Research Unit at the USDA in Toledo, OH.

2.1.5 Statistical Analysis

I examined the effect of nitrogen treatment on several plant response variables. I examined differences in plant growth variables (i.e. leaf growth rate, leaf accumulation, stem diameter, root, stem and leaf dry biomass, and root to shoot ratio) with one-way analysis of variance (ANOVA) and used Tukey’s post hoc tests to distinguish differences between treatments. I natural-log transformed stem diameter and root dry biomass values to meet the assumptions of normality. I compared percent water content of roots, stems, and leaves with a non-parametric Kruskal-Wallis test because these variables did not meet the assumptions of normality. I examined the impact of nitrogen treatment on plant quality traits (i.e. leaf N, C, and C:N, caffeine concentration and content in leaf, stem and root dry tissues, phloem caffeine exudates, and total caffeine content) with one-way

ANVOA and Tukey’s post hoc tests. To determine if different plant tissues contained different concentrations or contents of caffeine, I ran separate one-way ANOVAs comparing caffeine concentration and content across root, stem, and leaf tissues. All caffeine variables were natural log transformed to meet the assumptions of normality. I ran all statistical tests with SPSS 16.0.

2.2 Results

13 2.2.1 Plant growth and water status

Nitrogen fertilization increased growth rate for two of three response variables

(Table 2-1). Plants growth in high-N plants was 20% higher than low (P = 0.037), but did not differ from the intermediate-N plants (P = 0.259). Plant growth for the intermediate and low treatments did not differ (P = 0.607). High-N treatment plants also accumulated

50% more leaves than low (P < 0.001) and 25% more leaves than intermediate treatment plants (P = 0.006). Leaf accumulation did not differ for intermediate and low treatments

(P = 0.103). Change in stem diameter did not differ with treatment (Table 2-1).

Nitrogen treatment significantly affected biomass production (Table 2-2). Dry leaf biomass was 40% greater in high-N plants than low (P = 0.002), but did not differ in intermediate N plants (P = 0.067). There was no difference between dry leaf biomass in low and intermediate-N plants (P = 0.403). Additionally, root to shoot ratio was 24% lower in high compared to low N plants (P = 0.002), but did not differ from intermediate

N plants (P = 0.102). Intermediate-N plants did not differ from low in the root to shoot ratio (P = 0.287). Root, stem, and total biomass did not differ with N treatment (Table 2).

The percent water content differed with N treatment. Ranked means differed by treatment for both stem and leaf percent water contents, but root water content did not differ (Table 2-2).

2.2.2 Leaf carbon & nitrogen balance

Nitrogen fertilization affected the content of carbon and nitrogen in leaf dry biomass. The percent nitrogen of dry leaf biomass was 33% greater in high- relative to low-N plants (P = 0.008), but was not different from intermediate-N plants (P = 0.063).

14 Percent N in dry leaf tissues did not differ for low- and intermediate-N plants (P =

0.248). The C: N ratio was also influenced by the amount of N fertilization. The C: N ratio was 25% lower under high-N fertilization relative to low N (P = 0.009), but not the intermediate-N treatment (P = 0.072). Low- and intermediate-N treatments did not differ in their C: N ratio (P = 0.248). Nitrogen fertilization did not affect the percent carbon in dry leaf tissues (Table 2-3).

2.2.3 Effect of Nitrogen availability on caffeine production

Nitrogen treatment had varying effects on caffeine content across plant tissues

(Table 2-4). There was 3.5 times more caffeine in phloem samples (1.54 ± 0.16) than in leaf surface control samples (0.44 ± 0.11) (t = -3.855, df = 58, P < 0.001). Additionally, caffeine was greater 20 times more concentrated in leaf relative to root (P < 0.001) tissues and 19 times more concentrated than in stem (P < 0.001) tissues, but root and stem caffeine concentrations were not different from one another (P = 1). Further, high-N treatment plants had 2.5 times more caffeine in phloem exudates than in low- (P = 0.003) and 88% more than in intermediate-N plants (P = 0.024) (F2, 15 = 8.972, P = 0.004, Fig.

2-1). Yet, there was no difference between low- and intermediate-N treatments (P =

0.642). Unlike phloem exudates, there was no difference in leaf, stem, or root caffeine concentration or leaf, stem, root, or total caffeine content (Table 2-4). Similarly, caffeine content was 18 times greater in the leaf than root (P < 0.001) tissues and 27 times greater than stem (P < 0.001) tissues, but root and stem caffeine content were not different from one another (P = 0.999). However, there was no difference in caffeine concentration and content across N treatments for root, stem, or leaf tissues or for total caffeine content

15 (Table 2-4).

2.3 Discussion

Nitrogen treatment impacted a number of coffee seedling characteristics, including growth and leaf nutrients. Growth rate calculated as total leaf area and accumulation of leaves suggest N treatment impacted growth of coffee seedlings under these growth chamber conditions. Indeed, others have demonstrated coffee growth increases with N fertilization (de Matta et al. 1999). There was also a higher percent N in coffee leaf tissues of plants of the high-N treatment, suggesting growth of plants in the low-N treatment may have been limited by N availability. The percent water content of stem and leaf tissues of coffee seedlings also increased with N fertilization, however differences were small and probably biologically insignificant.

Caffeine content varied greatly across plant tissues, but caffeine in plant tissues did not vary with N treatment. Caffeine concentration was higher in leaf tissue relative to root and stem tissues. Caffeine content followed the same trend as concentration; higher content in leaves than in roots or stems. Zheng et al. (2004) reported similar differences and concentrations of caffeine across tissues of coffee seedlings, where leaf caffeine was greater than root and stem. However they did not compare caffeine content (Zheng et al.

2004). Caffeine concentration or content did not vary across N treatment, suggesting limitation in N or surplus N did not alter the ability of coffee seedlings to produce caffeine. These results contrast with caffeine production in yaupon holly (Ilex vomitoria), where production increased with higher nitrogen availability (Palumbo et al. 2007). A

16 plausible explanation for the difference in the two plants may be that in coffee, caffeine production is likely strongly regulated by genetic factors (e.g. genotype) rather than environment (i.e. nitrogen availability). For example, Coffea canephora (Robusta coffee), a close relative of C. arabica, has high narrow-sense heritability. In other words, the additive genetic variance in phenotype for caffeine content is passed from parental to offspring generations in coffee seeds (Montagnon et al. 1998), and therefore environmental variation may play little role in the caffeine phenotype expressed by coffee. If variability in C. arabica caffeine production is similar to C. canephora, large variation in caffeine in plant tissues would not be expected. Other coffee secondary metabolites, such as, trigonelline and chlorogenic acid, show intermediate levels of narrow-sense heritability and therefore may show more plasticity across nutrient availability (Montagnon et al. 1998).

One perplexing observation was that caffeine phloem exudates increased with increasing nitrogen availability, even though caffeine concentration did not change in leaves, stems, or roots. This result could be due to caffeine extracted off of leaf surfaces into EDTA solutions. However, this is unlikely because leaf surface controls were three times less concentrated than sample phloem exudates and if this were indeed the case, I would predict phloem exudates would follow the same pattern as leaf caffeine.

Alternatively, other unknown mechanism might be responsible for phloem caffeine exudation, and indeed further research is pending.

Although coffee seedlings had greater total leaf area under the high-N treatment, caffeine content did not differ among nitrogen treatments. This suggests that coffee seedlings with higher nitrogen availability should be a higher quality resource for

17 herbivores that consume whole plant root, stem, or leaf tissues. However, phloem caffeine increased with nitrogen availability. If phloem-feeding insects are sensitive to caffeine alkaloids, fertilized plants may be of lower quality from the insect perspective.

Yet, caffeine concentrations found in the phloem exudates appear very dilute (~1-3 µl L-

1). Unfortunately, the true caffeine concentration within the phloem is unknown because the volume extracted from each leaf sample was diluted in 5 ml of EDTA solution. Also, phloem-feeding insects often consume substantial quantities of phloem to obtain the appropriate amount of amino acids (Herms & Mattson 1992) and even dilute levels of caffeine in the phloem may have impacts as excessive quantities are consumed.

In conclusion, coffee percent N and plant growth increased with N fertilization, suggesting nutritional traits to herbivores should increase with N fertilization. However, the N-based alkaloid caffeine did not increase in root, stem, or leaf tissues with N fertilization, thus negative effects of this alkaloid on chewing-herbivores may remain constant across N fertilization. In contrast, caffeine phloem exudates increased with N fertilization suggesting that at high-N fertilization there may be a trade off between the effect of positive % N and the influences of negative alkaloid content.

18 Table 2-1. Effect of nitrogen treatment on plant growth rate, measured as change in leaf area, leaf number, and stem diameter (mean ± std. error).

Nitrogen treatment* One-way ANOVA

Low Intermediate High df F P

Growth rate† 2.43 ± 0.13a 2.62 ± 0.17a 2.96 ± 0.13b 2, 64 3.23 0.046

Change in leaf number†† 5.04 ± 0.36a 6.04 ± 0.27a,b 7.62 ± 0.4b 2, 64 13.79 <0.001

Change in stem diameter (mm) ‡ 0.22 ± 0.07a 0.3 ± 0.07a 0.17 ± 0.04a 2, 54 2.07 0.136

†Growth rate was calculated from the final divided by initial total leaf area.

††Change in leaf number was calculated as final minus initial leaf number.

‡Change in stem diameter was calculated as final minus initial stem diameter.

* Common letters denote non-significant differences between treatment means, as indicated by Tukey’s HSD.

19 Table 2-2. Coffee seedling biomass and water status across three nitrogen treatment (mean ± std. error)*.

Nitrogen Treatment One-way ANOVA

Variables Low Intermediate High df F P

Dry weights (g)

Roots 0.45 ± 0.02a 0.47 ± 0.05a 0.44 ± 0.03a 2, 67 0.16 0.854

Stems 0.29 ± 0.02a 0.30 ± 0.02a 0.29 ± 0.01a 2, 67 0.26 0.776

Leaves 0.41 ± 0.03a 0.47 ± 0.03a,b 0.57 ± 0.03b 2, 67 6.6 0.002

Root: shoot 0.67 ± 0.03a 0.6 ± 0.04a,b 0.50 ± 0.02a 2, 67 6.61 0.002

Total biomass 1.14 ± 0.06a 1.23 ± 0.08a 1.3 ± 0.08a 2, 67 1.16 0.319

Kruskal-Wallis Test

Water content (%) df H P

Roots 86 ± 0.3 86 ± 0.7 87 ± 0.4 2, 67 0.57 0.75

Stems 64 ± 0.7 61 ± 0.3 67 ± 0.7 2, 67 12.88 0.002

Leaves 78 ± 0.4 78 ± 0.6 79 ± 0.2 2, 67 6.33 0.042

*Common letters denote non-significant differences across means, indicated by Tukey's HSD.

20 Table 2-3. Effect of nitrogen fertilization on carbon, nitrogen, and carbon: nitrogen ratio

(mean ± std. error).

Nitrogen treatment* One-way ANOVA

Variables Low Intermediate High df F P

Carbon 43.18 ± 0.06a 43.53 ± 0.12a 42.96 ± 0.3a 2, 7 2.27 0.185

Nitrogen 2.76 ± 0.08a 3.11 ± 0.21a,b 3.69 ± 0.09b 2, 7 11.15 0.01

C:N 15.69 ± 0.47a 14.1 ± 0.92a,b 11.66 ± 0.3b 2, 7 10.59 0.011

*Common letters denote non-significant differences across means, indicated by Tukey's HSD.

21 Table 2-4. Effect of nitrogen fertilization treatment on tissue caffeine concentration and content (mean ± std. error).

Nitrogen treatment One-way ANOVA

Variables Low Intermediate High df F P

Caffeine concentration in dry biomass (mg g-1)

Root 0.19 ± 0.06 0.22 ± 0.01 0.19 ± 0.06 2, 9 0.321 0.733

Stem 0.17 ± 0.08 0.24 ± 0.12 0.15 ± 0.02 2, 9 1.35 0.34

Leaf‡ 12.7 ± 3.26 12.43 ± 0.55 13.46 ± 0.07 2, 17 0.111 0.896

Comparison across different plant tissues 2, 33 369.6 <0.001

Caffeine content (mg)†

Root 0.08 ± 0.03 0.08 ± 0.01 0.06 ± 0.02 2, 9 0.492 0.627

Stem 0.1 ± 0.06 0.14 ± 0.08 0.06 ± 0.02 2, 9 0.118 0.89

Leaf‡ 8.78 ± 1.99 7.49 ± 1.28 10.44 ± 1.17 2, 17 0.13 0.882

Total 7.24 ± 1.75 7.71 ± 1.33 7.75 ± 1.8 2, 9 0.029 0.971

Comparison across different plant tissues 2, 33 75.57 <0.001

‡ Leaf caffeine concentration and content was significantly greater than root or stem. Root and stem did not differ. † Calculated as dry mass multiplied by concentration.

22

3.0 b

)* 2.5 ­1

2.0 a a 1.5

1.0

Phloem caffeine (ul L 0.5

0.0 Low Intermediate High Nitrogen fertilization treatment

Figure 2-1. Mean phloem caffeine exuded from leaf petioles (µl L-1) across nitrogen fertilization treatments. Common letters denote non-significant means, as indicated by

Tukey’s HDS for that particular time period.

23

Chapter 3

Influence of plant quality on the distribution of a keystone ant- hemipteran mutualism in a coffee agroecosystem

To explore the importance of coffee host-plant quality to the green coffee scale and its ant-mutualist, Azteca instabilis, I investigated how the density of green scales and A. instabilis varied with host-plant quality at local levels.

3.1 Materials & Methods

To determine if plant quality plays a role in green scale insect abundance on coffee bushes near to A. instabilis nest sites, I conducted a field survey at Finca Irlanda an organic coffee plantation in the Soconusco region of Chiapas, Mexico. In early June

2009, I located trees with A. instabilis nests within a mapped 45-hectare plot and surveyed the surrounding coffee bushes for green scales. I then paired coffee trees of similar size and distance to A. instabilis nests, but differing substantially in abundance of green scales (high vs. low scale density). Each pair of coffee bushes was in close proximity to one another to reduce the effects of microclimate. In July, I counted the number of scale insects on three randomly selected branches per coffee plant to confirm

24 the differences between high- and low-scale density plants. I included both healthy scales and scales infested with Lecanicillium lecanii (white halo fungus). To account for any differences in scale density resulting from increased attendance by A. instabilis, I counted the number of ants crossing a point on the main stem of the coffee tree (~1.5 m above ground) at eye level for one minute. To control for the effect of A. instabilis, I measured the distance to the tree with the A. instabilis nest for all coffee bushes. To estimate relative size differences in coffee plants, I counted the number of branches on each plant.

To determine differences in coffee-plant quality, I compared a number of plant characteristics including caffeine content of phloem and leaves and nutritional content of leaves. I collected phloem exudates from 2-3 coffee leaves per plant using a method modified from King & Zeevart (1974). Following 1 h of darkness in the evening, I cut the petiole of one newly expanding leaf (~2-4 cm in width) with a razor and submerged the tip in a vial of 5 ml of 20 mmol EDTA. Next I wrapped parafilm tightly around the opening of the vial to prevent the leaf from falling to deep into the EDTA solution and to prevent the solution from splashing out of the vial. I kept petioles in the EDTA solution and in darkness for 8 h before removing the leaf.

To examine caffeine content of leaves, I collected leaf tissue samples from four or more pairs of the newest and second newest expanding leaves from multiple branches

(~15-25 leaves). Access to a drying oven was limited at the study site, so I immediately placed leaf tissues on ice in the field, before freezing -5°C overnight. Plant tissues were dried at (40-45°C) for 48 h at ECOSUR (El Colegio de la Frontera Sur) in Tapachula 24 h after sampling. Leaf samples were stored at -5°C, until transported on ice to the

25 University of Toledo where they were kept at -20°C until analysis. Prior to leaf analysis, I ground leaf tissue with liquid nitrogen with a mortar and pestle.

Specifically for leaf caffeine analysis, I followed the methods of Witter et al. (in prep) to maximize extraction efficiency. First, I extracted caffeine from 0.1 g of dry leaf tissue in 20 ml of methanol by ultra-sonicating for 4 h at 65°C. Then, I passed extracts through filter paper and diluted liquid aliquots with methanol to the working range of the

13 instrument and spiked samples with an internal standard ( C3-caffeine) to control for instrumental error, before analysis using LC-ESI-MS/MS. I ran each homogenized plant sample in triplicate.

To determine leaf nutritional characteristics, I analyzed coffee leaf tissues for elemental nutrients. First, I digested 0.15 g of leaf tissue in a microwave digester

(MARS; CEM Corp, Matthews, NC) using a modified EPA method (EPA method 3051 with additional peroxide step). To determine nutrient concentration for P, K, S, Ca, Mg,

B, Cu, Fe, Zn, and Mn, I used inductively coupled plasma optical emission spectroscopy

(ICP-OES; Model IRIS Intrepid II, Thermo Corp., Waltham, MA). Next, I analyzed total

N and C using a C-H-N combustion analyzer (Perkin Elmer model 2400). I conducted all instrumental measurement at UT and Application Technology Research Unit at the

USDA in Toledo, OH.

To determine which coffee plant characteristics were important to the distribution of green scales, I compared the characteristics of high- and low-scale-density coffee plant pairs with paired t-tests. To meet the assumptions of normality, distance to ant nest, mean scales per branch, ant activity, magnesium, boron, manganese, zinc, and phloem caffeine were natural log transformed (value + 1/3 of lowest non-zero measured value, as in

26 Tukey 1977). Next, I preformed a stepwise multiple-linear regression across all plants to determine which variables were most important to scale density. I tested for multicollinearity between independent variables with collinearity diagnostics. In the stepwise regression model I used an entry probability of F equal to 0.2 and a removal probability of F equal to 0.25. All statistical tests were completed with SPSS 16.0.

3.2 Results

High-scale-density coffee plants had 12 times more scale insects than low-scale density plants, confirming the selected plants did differ in scale insect density (Table 3-

1). The distance to the nearest tree with an A. instabilis nest did not differ between high- and low-scale-density coffee plants. However, A. instabilis activity was three times greater on high-scale density plants relative to low-density plants. There were 20 percent more branches on high-scale density plants relative to low-density plants, but this difference in plant size was not significant (Table 3-1).

Some, but not all, plant quality measures differed for the paired coffee plants.

Percent nitrogen was eight percent greater and percent calcium was 15 percent higher in high-scale density plants relative to low-scale density plants. However, high- and low- scale density plants did not differ in caffeine content of phloem exudates or leaf tissues and there were no differences for any other nutritional elements (i.e., C, P, Ca, Mg, S, B,

Cu, Fe, Mn, and Zn) (Table 3-1). Variation in A. instabilis activity and percent nitrogen in host plants explained 45% of the variation in scale density across all coffee bushes (F2,

2 28 = 59.271, P < 0 .001, R = 0.452), after branch number, carbon, calcium, manganese, and zinc were removed from the step-wise multi-regression model.

27

3.3 Discussion

Coffee characters differed between paired high- and low-scale-density coffee plants (Table 3-1). The results from the survey of paired coffee plants suggest, that plant quality may influence the abundance of the A. instabilis - green scale mutualism at a local level. Particularly, the percent nitrogen of leaf tissues was greater on high-density scale plants relative to low-density scale plants and correlated with green-scale abundance.

Other characters, such as distance to A. instabilis nest or the number of branches were not important in predicting scale abundance at this local scale. Other elements, such as calcium, manganese, or carbon tended to or significantly differed between high- and low- scale pairs, but did not correlate with green-scale abundance across all plants.

Surprisingly, no significant correlation was found between plant characteristics and A. instabilis activity, suggesting that effects of host plants on A. instabilis are either un- important or are mediated by changes in scale abundance or quality.

There was no correlation between caffeine and green scale growth suggesting the variation in caffeine content present in this study did not affect green scales. This is somewhat surprising because green scales contain caffeine in their tissue or digestive tracts (D. Gonthier, unpublished data) and negative correlation between green scale density and caffeine leaf content have been established in the greenhouse (Fernandes

2007). One explanation could be that caffeine only weakly affects scale growth and under field conditions other factors are more important in controlling scales, for example natural enemies or plant N. It also should be noted that the origin of green scales is

28 thought to coincide with coffee in Ethiopia or Brazil (Gill et al. 1977, Zimmerman 1948, in Bach 1991), and therefore green scales may have evolved resistance to caffeine.

Although clumped patterns of ant-hemipteran mutualists are commonly reported across a broad latitudinal gradient (Laine & Niemelä 1980, Karhu & Neuvonen 1998,

Wimp et al. 2001), few have considered how host-plant quality can be incorporated into that pattern. Local clumping of the ant-scale mutualism is generally considered a strong top-down pattern that also may determine the distribution of other insects in the food web

(e.g. parasitoids, predators) (Vandermeer et al., in press). Yet my results suggest, at close proximity to nests (~2 m), when host plants are equal distance to ant nests, plant quality may limit the abundance of hemipterans. At least one other study has questioned the relationship between host-plant quality and distance to ant nest (Karhu & Neuvonen

1998); authors show percent N in leaf tissues is greatest at close distances (1 m) to the nest relative to plants further away (>4 m). However, they did not discuss this result in relation to hemipteran distribution (Karhu & Neuvonen 1998). In another system aphids feeding on Populus fremontii in the Western United States, are highly clumped around ant nests and their abundance declines with distance from the nest (Wimp et al. 2001).

However, near to ant nests (< 1 m), there is much higher variance in numbers of aphids than further from ant nests (6 or 16 m) where aphid populations are consistently low

(Wimp et al. 2001). This variance may possibly be due to differences in plant quality at ant nest sites, as was found here.

The ecological consequences of the presence of ants on plants cannot be understated (Rosumek et al. 2009, Floren et al. 2002). A recent meta-analysis suggests that the presence of ants on plants generally results in a positive benefit to host plants

29 (Chamberlain & Holland 2009). In some cases, the presence of ants on Betula trees near ant mounds can protect trees from defoliation during severe herbivore outbreaks, essentially making ‘green islands’ (Laine & Niemelä 1980). In our system, previous research shows higher abundance of green scales result in higher A. instabilis abundance, which limits seed predation by the coffee berry borer, the most devastating pest of coffee

(Perfecto & Vandermeer 2006). Further, A. instabilis can reduce some herbivore and predator groups on coffee (Philpott et al. 2008) and coffee shade trees (Philpott et al.

2004, Gonthier et al. 2010). Yet, it remains to be experimentally demonstrated that changes in A. instabilis abundance caused indirectly by host-plant quality may result in ecological consequences for the coffee insect community.

30 Table 3-1. Field and plant quality characteristics for coffee plants with high- or low- density concentrations of Coccus viridis scale insects adjacent to trees with Azteca instabilis ant nests (mean ± std. error).

Coffee plant characteristic Low-Scales† High-Scales t†† df Sig.

Distance to ant nest site (m) 2.12 ± 0.3 1.99 ± 0.26 -0.949 17 0.356

Number of coffee branches 75 ± 9 91 ± 10 2.029 15 0.061

Mean no. scales per branch 13 ± 8 164 ± 25 9.426 18 <0.001

No. of A. instabilis 3 ± 2 11 ± 2 5.311 18 <0.001

Carbon (%)††† 46.97 ± 0.13 46.61 ± 0.16 -1.961 18 0.066

Nitrogen (%) 2.62 ± 0.07 2.84 ± 0.06 2.192 18 0.042

Phosphorous (%) 0.17 ± 0.01 0.18 ± 0.01 0.873 16 0.396

Potassium (%) 1.65 ± 0.1 1.78 ± 0.11 1.278 16 0.219

Calcium (%) 0.83 ± 0.06 0.96 ± 0.05 2.643 16 0.018

Magnesium (%) 0.38 ± 0.03 0.37 ± 0.02 -0.249 16 0.807

Sulfur (%) 0.2 ± 0.01 0.2 ± 0.01 0.181 16 0.859

Boron (mg kg-1) 78 ± 5 76.33 ± 5.84 -0.567 16 0.579

Copper (mg kg-1) 11 ± 1 12.18 ± 0.68 1.73 16 0.103

Iron (mg kg-1) 140 ± 16 150 ± 13 0.419 15 0.681

Manganese (mg kg-1) 103 ± 17 67 ± 8 -2.041 16 0.058

Zinc (mg kg-1) 20 ± 3 20 ± 3 -0.099 16 0.922

Phloem caffeine (ug L-1) 2.12 ± 0.3 0.38 ± 0.09 0.933 18 0.363

Leaf caffeine (mg g-1) 8.63 ± 0.72 8.83 ± 0.85 0.244 18 0.81

†Numbers show mean ± SE.

31 ††Statistical results are for two-tailed paired t-tests. †††Elemental results are for leaf tissue analyses.

32

Chapter 4

Impact of soil-quality on plant quality and a coffee insect community

To investigate how soil-quality may influence coffee-plant quality, green-scale population growth, an ant-scale mutualism, abundance of scale predators, and the insect community, I conducted a field experiment with coffee seedlings grown in three soil treatments and monitored effects on several response variables.

4.1 Materials & Methods

4.1.1 Field methods

I obtained 8-month old coffee (Coffea arabica var. Catuai, Catimor, Bourbon) seedlings (with approximately 16 leaves) from the Finca Irlanda plant nursery in

February 2009 and subjected them to different soil treatments. To manipulate soil- quality, I repotted seedlings in pots (11.5 cm diameter by 15 cm height) with one of three different soil-quality treatments: 1) a low-quality treatment with a 3:1 mixture of sand and soil, 2) an intermediate-quality treatment with a 1:2:1 mixture of sand, soil, and organic compost, and 3) a high-quality treatment with a 1:3 mixture of soil and organic

33 compost. I obtained soil from the study site and sand from riverbanks near the study site.

I used organic compost from the Finca Irlanda composting facility. The compost is a mixture of coffee parchment, chicken manure, and calcium carbonate subjected to worm vermiculture. For each soil-quality treatment, I ran soil analyses (N = 3) to test soil- quality at UNACH (Universidad Autonoma de Chiapas) in Huehuetan Chiapas, Mexico.

The mixtures differed in some nutrients (Table 4-1), confirming differing quality of the mixtures. The high-quality mixture had greater nitrogen (%), potassium (%) and organic matter (%) content than the intermediate- and low-quality mixtures. The intermediate- quality mixture had higher organic matter (%) and higher phosphorus (ml L-1) than the low-quality mixture, but did not differ in potassium (ml L-1). The treatment mixtures also likely differed in other characteristics such as bulk density, water-holding capacity, and micro-nutrient content, but these differences were not quantified. Additionally, on a weekly basis after the first two months of growth, the high-treatment received 100 ml and the intermediate-treatment received 50 ml of organic compost ‘tea’ produced by Finca

Irlanda and used in their regular plant fertilization activities. The compost ‘tea’ is organic compost stewed in a tub of water for several days. Rainfall occurred almost daily saturating the soil of potted seedlings, therefore watering was unnecessary.

After plants had grown in the three soil-quality mixtures for approximately two months, I infested plants with scale insects. I transferred green scales onto experimental plants by putting plants in direct contact with other heavily infested coffee seedlings.

Adult scales are sessile, but nymphs (crawlers) are mobile and readily colonize new plant tissues (Fredrick 1943). I then allowed scale populations to establish on seedlings before thinning populations to ~30 individuals with cotton Q-tips prior to field experiments.

34 I then placed plants in the field to examine the indirect impact of the soil-quality mixtures on the insect community. I first selected 19 sites, each with an independent A. instabilis nest on an Inga micheliana tree. I placed six coffee seedlings, two of each soil- quality mixture, in random order 1 m from the base of the tree. I then excluded ants from half of the plants (one per soil treatment) by painting a ring of Tanglefoot (Grand Rapids,

MI), a sticky residue that prevents ants and other crawling insects from passing, around the stem ~3 cm above ground level. To control for any effects of Tanglefoot on plants, I then painted a half circle of Tanglefoot on all control plants. During weekly surveys I re- applied Tanglefoot and removed any encroaching vegetation. To quicken A. instabilis discovery of scale insects on experimental plants, I tied strings and built paths with natural sticks to connect A. instabilis foraging trails to the control plants and also placed

30-60 A. instabilis workers on each control plant.

One week after the experiment set-up, and for the following four weeks, I measured a number of response variables to examine the influences of soil-quality treatment and ant access on scale insect populations, activity of tending ants, scale predators, parasitoids, pathogens, and the insect community as a whole. First, I counted the number of adult and nymph scale insects. Adults have a characteristic U-shaped marking that nymphs lack (Fredrick 1943). I did not count crawlers because they are difficult to count with the naked eye. I counted the number of A. instabilis and other ants on experimental plants (either tending scales or not). I counted adults and larvae of A. orbigera scale predators. Additionally, on the last three sample dates, I counted the number of parasitized scales and number infected by L. lecanii. I also recorded abundance of arachnids and other insect orders (except Diptera which moved to quickly

35 to be accurately assessed). Another abundant ant-tended hemipteran (Toxoptera sp.

[Aphidae]) was frequently encountered in surveys, and I individually assessed abundance of this species. All measurements were taken between 6:30 AM and 1:30 PM under similar weather conditions. I visited sites in a different order during each survey week.

To determine the influence of soil-quality treatment on plant traits I examined plant growth rates, phloem and leaf caffeine concentrations, and leaf nutrients. I compared plant growth rates by examining total leaf area at the onset of the experiment and at the completion. Initially, I measured the length and width of each leaf, and estimated leaf area with the equation for an ellipse (area = length/2 × width/2 × π). On subsequent sample dates, I measured only width, and used the following regression (y =

1.8399x + 0.5438) to estimate length and calculate leaf area. In both cases, individual leaf areas were summed to give total leaf area per seedling. To determine growth rate, I divided initial by final leaf area. At the completion of the experiment, I collected phloem exudates from 2-3 coffee leaves per plant using a method modified from King & Zeevart

(1974). Following 1 h of darkness in the evening, I cut the petiole of each leaf with a razor and submerged the tip in a vial of 5 ml of 20 mmol EDTA. I kept the petiole of the leaf submerged for 8 h in complete darkness. I also collected leaf surface control leaves from each soil-quality treatment (N = 3). Mean sample phloem caffeine was calculated as in Chapter 1 (mean of individual plant minus mean control).

To examine leaf caffeine and elemental nutrition, I cut young (1st and 2nd newly expanding leaves) and old (all other leaves) leaves and as in Chapter 2, and immediately placed leaves on ice, and stored them at -5°C overnight before being drying (40-45°C) for at 72 h and stored them at -5°C. For elemental and leaf caffeine analyses, I used mature

36 (e.g. full size) leaves ground in liquid nitrogen because younger leaves were too few to conduct all analyses. As in Chapter 3, elemental analysis was conducted with ICP-OES and C-H-N analyzer and caffeine analysis was conducted with LTC MS/MS.

4.1.2 Data Analysis

I examined differences in common arthropod species (scale insects, A. instabilis, A. orbigera larvae, Toxoptera sp., other ants), less common arthropod groups (spiders,

Hemiptera excluding C. viridis and Toxoptera sp., Coleoptera) and total arthropods on seedlings differing in soil-quality treatment and ant-exclusion treatment. For common arthropod species, I calculated mean values across all sample dates. Because, adult and nymph scales followed similar trends, the two size classes were grouped in total scales.

For uncommon arthropods and total arthropods, I summed all individuals across sample dates because abundance of the less common arthropods was low on a given sample date.

When examining for impacts of soil-quality and ant presence on other insect orders, I excluded groups that rarely occurred on seedlings (< 25 occurrences). For total arthropods, I analyzed data in two different ways. First, I examined differences in total arthropod abundance (including all arthropods observed). Second, I examined differences in total arthropod abundance specifically excluding ants and ant-mutualists from the calculation. In addition to examining raw values, I also examined differences in mean abundance of ant mutualists, predators, parasitoids and pathogens on a per-scale-insect basis. This allowed me to determine if any differences in patterns of abundance were due to scale density or the effect of treatment.

I compared the abundance of arthropod orders (e.g. Hemiptera, Coleoptera,

37 spiders) with a GLM multivariate analysis of variance with soil-quality treatment and ant treatment as main factors and site as a blocking factor. Higher order interactions are not possible when each treatment combination is only represented by a single replicate within each block, therefore I did not include the interactions between main factors and the blocking factor in the model. I followed the significant MANOVA model with individual

ANOVAs to determine treatment effects on individual arthropod groups. I natural log transformed (+ 1/3 of the lowest measured value; Tukey 1977) values for Hemiptera,

Coleoptera, and spiders to meet conditions of normality. I did not include ants, scales, aphids, or Azya orbigera in the MANOVA because 1) the ant-exclusion treatment was enforced to impact ant abundance and 2) abundance of ant-tended hemipterans and their primary predator is affected by ant presence. Instead, for these groups, I compared means across treatments with a GLM ANOVA with soil-quality and ant treatments as fixed factors and blocked by A. instabilis nest site as a random factor. I natural log transformed all variables (value + 1/3 of lowest non-zero measured value; Tukey 1977) to meet assumptions of normality.

To determine the effect of soil-quality treatment on plant traits, I compared plant growth (total leaf area, number of leaves, leaf area growth rate), elemental nutrition (N,

P, K, ect.), and caffeine secondary metabolites (phloem and leaf) using one-way ANOVA with a Tukey’s post hoc test. To meet the assumptions of normality, I transformed (value

+ 1/3 of lowest non-zero measured value; Tukey 1977) total leaf area, zinc, and phloem caffeine with a natural log transformation and number of leaves and total leaf area were square root transformed to meet the conditions of normality.

To further elaborate relationships between green scales, the arthropod food web,

38 and plant characteristics, I performed Pearson’s correlations. To meet the assumptions of normality, I used transformed data as described above. All tests were conducted with

SPSS 16.0.

4.1.3 Pheidole sp. recruitment to scale insects

Upon completion of the field experiment, I moved all experimental plants to the

Finca Irlanda plant nursery to measure leaf area and destructively sample tissues. Upon noticing ants tending scale insects on the experimental seedlings, I opportunistically investigated the effect of soil-quality treatment on recruitment of a second ant species,

Pheidole sp. In the absence of A. instabilis, Pheidole sp. is most numerically dominant scale-tending ant species in the nursery (Pers. obsv.). This Pheidole sp. is a ground- nesting unidentified ant species and appears to be less aggressive than A. instabilis; often the disturbance of counting Pheidole on seedlings will cause them to retreat down the coffee seedling towards the ground.

To examine differences in numbers of Pheidole sp. workers tending scale insects,

I placed experimental seedlings in two areas of the nursery (separated by 30 m) on 24 and

25 of June 2009. First, I removed Tanglefoot from all plants. In each area, I placed seedlings in two or more rows approximately 0.25 m apart and with treatments evenly interspersed. Then on two dates (27 June and 1 July), I counted the number of Pheidole sp. workers on each plant and calculated mean values per plant across the two sample dates. I examined mean numbers of Pheidole sp. and numbers of Pheidole workers per scale insect on plants differing in soil-quality treatment with a one-way ANOVA. I

39 natural log transformed numbers (value + 1/3 of lowest non-zero measured value) to meet assumptions of normality.

4.1.4 Effect of ant-exclusion on Azya orbigera larval foraging

To determine if A. orbigera larvae were potentially excluded from seedlings by

Tanglefoot barriers, I preformed a laboratory study. I collected coffee seedlings with ~10-

20 adult scale insects. Then, I placed two seedlings with known number of scales in insect arenas (61 x 61 x 61 cm, Bug Dorm3, Bioquip, Rancho Dominguez, CA) and on one seedling painted Tanglefoot in a ring around the stem ~3 cm above the soil as in the field experiment. I then placed two 3rd instar A. orbigera larvae at the base of each plant, and allowed the coccinellids to forage for 24 hours before noting the location of the beetles and counting the number of remaining scale insects. I replicated the experiment 9 times with new seedlings and larvae, and then compared the number of scales removed with a paired t-test (SPSS 16.0).

4.2 Results

4.2.1 Effect of soil-quality treatment on scales, aphids, and ant-mutualists

There was a significant effect of soil treatment on total number of green scales

(Fig. 4-1, F2,90 = 4.19, P = 0.018). High-quality treatment plants had 45% more total scales than low-quality treatment plants (P = 0.013), but intermediate plants did not differ

40 from high- (P = 0.303) or low-quality plants (P = 0.341). There were 34% more scales on ant-excluded plants relative to controls (F2, 90 =11.17, P = 0.001), but there was no interaction between soil and ant factors (F2, 90 = 1.17, P = 0.315).

Exclusion treatments were successful at excluding both A. instabilis and other species of ants (Brachymyrmex sp. 1, Brachymyrmex sp. 2, Pheidole protensa, Pheidole sp., Xenomyrmex sp., Pseudomyrmex ejectus, Procryptocerus scabriusculus, Cephalotes atratus, Wasmania sp.). However, neither abundance of A. instabilis nor of other ant species differed across soil-quality treatment. Further there was no interaction between soil and ant factors. Numbers of A. instabilis per scale insect did not differ with soil treatment or ant presence and there was no interaction between ant-exclusion and soil- quality treatment (Table 4-2, 4-3).

Like scale insects, the number of Toxoptera sp. per plant was affected by ant treatment. There were more than two and a half times more aphids on ant-excluded plants than control plants, but aphid abundance did not differ with soil treatment. There was no interaction between factors (Table 4-2, 4-3).

4.2.2 Effect of soil and ant treatments on C. viridis predators, parasitoids, and pathogens

Ant treatment had a significant impact on the abundance of predators, parasitoids, and pathogens of green scales. On ant-excluded plants there were four-fold more A. orbigera larvae, seven times more parasitized scales, and 50% more scales infected with

L. lecanii. On a per- scale-insect basis, the effect of ant-exclusion diminished for A.

41 orbigera larvae and scales infected with L. lecanii, however, number of parasitized scales per scale insect remained higher on ant-excluded plants relative to controls (Table 4-2, 4-

4). There was no effect of soil-quality treatment on A. orbigera larvae, parasitized scales, or scales infected with L. lecanii and no interaction between factors.

4.2.3 Insect community

Both soil-quality and ant presence affected certain arthropods. Abundance of all arthropods was 40% greater on high- (P = 0.006) relative to low-soil-quality plants, but arthropod abundance on intermediate treatment plants did not different from high (P =

0.442) or low treatment plants (P = 0.127). There were also 20% more arthropods on ant- excluded plants relative to controls, but there was no interaction between terms. When ants and ant-mutualists were withdrawn from total arthropods for analysis, the effect of soil-quality diminished, however there were 45% more arthropods (excluding ant- hemipteran mutualists) on ant-excluded plants relative to controls (Table 4-2, 4-5).

Spiders were twice as abundant on ant-excluded plants relative to controls, but did not differ across soil-quality treatments and there was no interaction between factors.

Hemiptera (excluding ant-tended species) and Coleoptera abundance did not differ across treatments (Table 4-2, 4-5).

4.2.4 Plant growth and quality

Soil-quality treatments impacted coffee seedling growth rate and size. Coffee seedling growth rate differed across soil-quality treatment (F2, 87 = 40.537, P <0.001).

Plants in the high-quality treatment grew 2.4 times more rapidly than those in the low-

42 treatment (P < 0.001) and 30% more rapidly than intermediate- plants (P = 0.005).

Additionally, plants in the intermediate-treatment grew 70% had a faster rate of growth than plants in the low-treatment (P < 0.001). The final total leaf area (F2, 111 = 32.1, P

<0.001) and the total number of leaves (F2, 111 = 19.9, P < 0.001) were greater in high and intermediate treatments relative to low, although they did not differ from one another.

Soil-quality also affected leaf nutrient concentrations. Nitrogen (F2, 62 = 2.066, P

< 0.001) and copper (F2, 21 = 9.866, P < 0.001) concentrations tended to be higher in the higher-quality treatment. Boron (F2, 21 = 7.682, P = 0.003) and manganese (F2, 21 =

14.004, P < 0.001) declined in the higher-quality treatments. Magnesium (F2, 21 = 12.136,

P < 0.001) and calcium (F2, 21 = 4.573, P = 0.022) concentrations peaked at the intermediate-treatment. Potassium concentrations dipped on plants grown in the intermediate-quality treatment (F2, 21 = 3.658, P = 0.043). Carbon, phosphorus, sulfur, iron, and zinc concentrations did not differ between treatments (Table 4-6).

Leaf caffeine concentrations did not differ with soil-quality (F2, 20 = 5.399, P =

0.559). However, as in Chapter 1, caffeine phloem exudates increased with increases in soil-quality (F2, 41 = 5.575, P = 0.007). There was twice the amount of caffeine in exudates from plants grown in high- relative to low-quality treatments (P = 0.007), but plants grown in high- and intermediate-quality treatments did not differ (P = 0.739).

Caffeine was also twice as abundant in phloem exudates from the intermediate treatment relative to the low (P = 0.046, Table 4-6).

4.2.5 Plant and food web variables correlated with green scales

43 There were several Plant growth and nutritional characteristics, as well as, one arthropod group that correlated with green-scale abundance. The strongest correlations were found with plant growth rate, total leaf area, and total number of leaves. Leaf zinc was the only plant nutrient significantly correlated, although nitrogen was marginally correlated. The number of parasitized scales was also correlated with the number of green scales per plant (Table 4-7).

4.2.6 Effect of soil-quality on Pheidole sp. recruitment to C. viridis

Numbers of Pheidole sp. workers tending C. viridis were strongly affected by soil treatment (Fig. 4-2, F2, 108 = 6.708, P = 0.002). The number of Pheidole workers per plant was three times greater on high-quality plants relative to low (P = 0.001), but neither high- (P = 0.077) or low- quality plants (P = 0.301) differed from intermediate plants.

There was no difference between Pheidole recruitment with block (F1, 108 = 0.089, P =

0.767). Additionally, the numbers of Pheidole sp. workers per scale insect differed with soil treatment (Fig. 4-3, F2, 108 = 17.232, P = 0.026). On high treatment plants there were more than three times as many Pheidole sp. workers per scale insect relative to low treatment plants (P = 0.046). Numbers of workers per scale insect on intermediate plants did not differ from high- (P = 0.064) or low-quality (P = 0.987) plants. There was no significant difference between numbers of Pheidole sp. workers per scale in the two sites

(F1, 108 = 1.321, P = 0.591).

4.2.7 Effect of ant-exclusion on Azya orbigera larval foraging

44 Tanglefoot affected predatory impacts of A. orbigera larvae on C. viridis in laboratory experiments. The mean number of scales removed by A. orbigera larvae was

25 times greater on control plants relative to no-ant plants (Fig. 4-4, t = 5.936, df = 8, P <

0.001). Indeed, A. orbigera larvae were never observed to cross Tanglefoot barriers (Pers. obsv.).

4.3 Discussion

4.3.1 Effect of treatments on green scale growth

There were larger green-scale populations on the high-soil-quality plants relative to the low, suggesting host-plant quality does affect green scales. Green scale growth rate appeared comparable to other studies (Hanks & Sadof 1990, Fernandes 2007). Growth of phloem feeding insects is generally limited by amino acid content in the phloem (Ponder et al. 2000, Awmack & Leather 2002), which could be expected to correlate with total N of plant tissues. In a greenhouse experiment, Fernandes (2007) showed fertilization of host plants with N and/or K resulted in increased green-scale population growth. Levels of both leaf N and K were the highest in the high-soil-quality treatment were scale population size was the greatest, however plant growth rate was most strongly correlated with scale population size. Other factors important to plant growth are therefore also indirectly important to scale population size.

Unlike in Fernandes (2007) caffeine concentration was not negatively correlated with scale population size, in fact we found no correlation at the leaf and phloem level,

45 suggesting caffeine has little effect on green scale growth. It also could be that in the field other forces might be more important to scale growth, like predation and pathogenesis.

Alternatively, because phloem caffeine exudates were greater on intermediate and high- soil-quality plants relative to low, it is possible that positive effects of higher leaf quality masked the negative effects of caffeine. In quaking aspen, for example, production of condensed tannins (a defense compound) and percent N co-vary with fertilization, and bioassays revealed that both factors affect herbivore growth (Bryant et al. 1987). Other secondary compounds, not measured here, might also hinder green scale growth.

Chlorogenic acid, for instance, is also negatively correlated with scale growth (Fernandes

2007). Further, variation in caffeine content across coffee genetic cultivars could reveal a caffeine effect on green scale growth.

Scales were more abundant on seedlings without ants than on plants that were accessible to ants. This may be contrary to what might be expected given the nature of typical ant-hemipteran mutualism. Indeed, other studies have found increases in green scale-insect density in the presence of ants relative to ant-exclusion on Pluchea indica

(Indian Fleebane) (Bach 1991) coffee in Hawaii (Reimer et al. 1993), and in the study system (Uno unpublished a, b). Yet at least one other study at the study site (Philpott et al. 2008) encountered higher scale insect densities on plants from which ants were excluded. One reason for this increase may be elimination of hemipteran predators on plants from which ants have been excluded. For example, ant-exclusion treatments lowered abundance of predatory earwigs leading to increases in aphid densities (Mueller et al. 1988, Piñol et al. 2009). A. orbigera larvae (scale predators) were also excluded by ant-exclusion treatments (Fig. 4-4) and in the presence of ants are protected from A.

46 instabilis ants by waxy extensions (Liere et al. 2008). Therefore this predator exclusion may explain the scale abundance differences across treatments, however it is important to note that A. orbigera larvae were more abundant on ant-excluded plants contradicting this logic. Another hypothesis is that A. instabilis ants may prey on scale insects occasionally as in other ant-hemipteran mutualisms (Offenberg 2001) and therefore ant presence may result in a decrease in scales at some densities or during some periods. Offenberg (2001) demonstrated the ant Lasius niger would increase predation on ant-tended hemipterans when other sugar resources are available. It may be likely that both ant consumption and predator exclusion are occurring simultaneously.

4.3.2 Effect of treatments on ant attendance of green scales

Recruitment of the arboreal nesting ant, A. instabilis, to scale insects did not vary with soil-quality treatments in the field. There may be several reasons why A. instabilis recruitment did not change: 1) Seedlings had low scale density relative to the number of green scales on adjacent coffee plants and helmet scales in the Inga micheliana canopies, therefore the experimental introduction of seedlings laden with scales was not enough to attract sufficient numbers of A. instabilis to coffee seedlings. The presence of scales in nest tree canopies has been shown to limit the number of scales on coffee bushes

(Livingston et al. 2008) and in other systems manipulating the abundance of hemipterans on adjacent experimental plants limited ant attendance to hemipterans on those experimental plants (Cushman & Whitham 1991). Although this may be an influence here, it is important to note that A. instabilis did recruit to all but three seedlings and recruitment was strong enough to have important ecological impacts on spider abundance

47 and parasitization of scale insects. Further, experimentation will always be confounded by the presence of other honeydew producing hemipterans, and results should been considered in relative terms. It also should be noted that at the onset of the experiment, I placed seedlings with high scale densities (>300) at the base of A. instabilis nests and ant recruitment still appeared quite low. Alternatively, A. instabilis may not have had sufficient time to change recruitment patterns across the one-month study. Azteca instabilis may not begin to forage for new scale resources until their current resources have been diminished, which may take the entire wet season.

Other ants were present at some sites and as a group did not respond to changes in soil-quality. First, it is possible and even likely that not all ants observed tend scale insects. Second, other species of scale-tending ants such as Pheidole sp. and

Brachymyrmex spp. may have been limited by competitive interactions with A. instabilis.

Past studies have strongly shown A. instabilis presence limits the abundance of other ant species (Philpott et al. 2004).

4.3.3 Effect of treatments on predators, parasitoids, and pathogens

The number of A. orbigera larvae, parasitized scales, and scales attacked by L. lecanii did not differ across soil-quality treatment at the per plant and per scale insect level (Table 4-2), suggesting attack was not indirectly modified by soil-quality treatment.

All three of the natural enemy groups increased on ant-excluded plants relative to control plants (Table 4-2), but only the parasitized scales increased when density of scales was accounted for confirming that A. instabilis presence reduces parasitism of scales (Uno in review a, b). As in Jackson & Zemenick (in review) field studies reveal that percentage of

48 scales infected by the L. lecanii does not differ across ant-excluded and control plants.

Although scale infection by L. lecanii did not differ across soil-quality treatment, it is interesting that effects of other entomopathogenic fungi are mediated by the host plant species in other systems (Hsiao & Khachatourians 1997). Green scales can be found on many host plants and across coffee varieties, perhaps differences in plant secondary metabolites across species or variety may mediate the infection rate of L. lecanii. It is also worth noting that impacts of ants on A. orbigera larvae tended to differ across soil treatments (P = 0.078), suggesting A. orbigera larvae or adult oviposition may respond differently to plant quality depending on ant presence or absence. In some systems host plants respond to herbivore damage by producing volatile chemicals that attract natural enemies and under low nitrogen conditions some plants respond by increasing production volatile attractants (Schmelz et al. 2003, but see Lou & Baldwin 2004). However, little research has investigated the production of volatile compounds in coffee (but see

Mazzafera & Robinson 2000) or their production in response to phloem feeding insects.

4.3.4 Community level effects of treatments

A number of arthropod groups were affected by ant-exclusion treatment. The number of ant-tended Toxoptera sp. increased on ant-exclusion plants, and as for green scales, A. instabilis may have preyed on aphids, or aphid predators may have been excluded by ant-exclusion treatment. Further, aphid numbers tended to increase with higher soil-quality and further experimentation, controlling for initial aphid population size could reveal a stronger effect of treatment. There were fewer spiders on control plants than ant-excluded plants. Previous studies in the coffee agroecosystems have

49 demonstrated that A. instabilis limit spider nymphs, but abundance of adults increases with A. instabilis (Vandermeer et al. 2001). This increase in adults was not significant when the family Linyphiidae was excluded, suggesting taxonomic resolution is important when spiders are considered (Vandermeer et al. 2001). Neither Hemiptera nor Coleoptera were affected by ant or soil treatments. Overall, arthropod abundance (not including ants or their hemipteran mutualists) was reduced in the presence of A. instabilis relative to ant-exclusion plants. This is not surprising considering the aggressive behavior of this ant species, however other studies have found limited effects of A. instabilis on arthropod communities with changes in two orders on Inga micheliana shade trees (Philpott et al.

2004) and for Lepidoptera on coffee plants (Philpott et al. 2008). Differences in methodologies between studies may account for different results. I observed plants five times to quantify arthropod abundance; other studies used leaf collection and D-vac sampling. Additionally, the use of seedlings rather than mature plants may result in an effect of ontogeny due to differences in plant architecture, general size, or quality that may influence the corresponding arthropod community (Boege & Marquis 2005).

4.3.5 Effect of soil-quality treatment on coffee seedling growth and quality

Higher soil-quality treatments were effective at increasing total leaf area, the number of leaves, and plant growth relative to the low treatment. However, all growth rates were low (< 1), suggesting that the total plant leaf area did not actually increase during the study period (although plants did accumulate leaves). The estimation of leaf length used may have underestimated leaf area, but there is a biological explanation as well. This trend can be explained by the presence of the coffee leaf spot fungus, Mycena

50 citricolor, which attacks old, larger leaves and causes premature leaf drop (Rao & Tewari

1987). The fungus attacked all plants, but leaf drop appeared reduced in high-soil-quality treatments resulting in greater leaf area for those plants. High-quality soil plants may have better resisted fungal attacks due to higher concentrations of some elemental nutrients (e.g. N, Cu), secondary plant compounds, or perhaps higher growth rates helped avoid attack by constantly producing new leaf tissues. Also, low-soil-quality treatment plants had greater leaf concentrations of manganese and boron than high treatment plants

(Table 4-6). Boron levels in all treatments at least doubled levels reported in one plant nutrition study of coffee (Martinez et al. 2003). However boron levels in the present study were almost six times less than the levels (400 mg kg-1) needed to cause metabolic stress or reduce growth reported in other plants (Papadakis et al. 2004). Additionally, there was significant decline in manganese levels (334-100 mg kg-1) from low to high- soil-quality treatments, however this variation was both in the range reported in the literature (Martinez et al. 2003) and far from the levels (800-1200 mg kg-1) reported to reduce plant growth (González et al. 1998). Therefore the variation in these elements may not be biologically significant to plant growth.

Caffeine content varied across soil-quality treatments in some plant measurements. Leaf caffeine content did not increase with soil-quality treatment, however, caffeine phloem exudates were greater in intermediate and high-soil-quality treatment relative to low.

4.3.6 Pheidole recruitment to scales on across soil-quality treatments

51 In contrast to A. instabilis, Pheidole sp. recruitment to scale insects responded rapidly to the changes in soil-quality treatment. Several other studies have demonstrated increased ant recruitment to honeydew producing insects on host plants of greater quality.

For example, lycaenid larvae in the USA (Billick et al. 2005) and sub-tropical Australia

(Baylis & Pierce 1991), aphids on milkweed (Mooney & Agrawal 2008), cottonwood

(Wimp & Whitham 2001), and on evening primrose (Johnston 2008), and leafhoppers on goldenrod (Morales & Beal 2006) in North America experienced greater ant tending activity on high-quality plants. The increased recruitment of on average 3 Pheidole workers per scale from high to low-soil-quality plants, could lead to greater protection of scales from scale predators. However, it is unknown to what extent Pheidole defends scale insects and therefore further experimentation is needed to investigate this question.

4.3.7 Conclusions

Green scale growth increased on host plants of high-soil-quality. Scale abundance was also higher on ant-excluded plants and further experimentation suggests that

Tanglefoot exclusions also limit A. orbigera larvae from preying on larvae. Azteca instabilis attendance of scale insects did not change across soil-quality treatment. Natural enemies of scale insects were more abundant on ant-excluded plants relative to control, but this response was likely due to increased scale density on ant-excluded plants.

Overall, arthropods were more abundant on high-soil-quality plants, however, that increase was mainly due to scale and aphid abundance. Additionally, ant-exclusion had a significant impact on the abundance of arthropods even without accounting for changes in ant, scale, and aphid abundance suggesting ants have a strong impact on the abundance

52 of other arthropods. Thus in this system, it appears that both bottom-up effects of nutrients and top down effects of predators may mediate scale insect populations and insect communities.

53 Table 4-1. Characteristics of the three soil-quality treatments (mean ± std. error)*.

Soil-quality treatment

Soil-quality Treatment Low Intermediate High df F P

N (%) 0.17 ± .01a 0.21 ± .02a 0.34 ± .03b 2, 7 15.78 0.004

P (ml/L) 16 ± 2a 68 ± 17b 29 + 1a,b 2, 7 7.68 0.022

K (ml/L) 49 ± 3a 88 ± 1a 189 ± 19b 2, 7 41.22 <0.001

Organic matter (%) 4.6 ± .1a 5.3 ± .1b 10.7 ± .1c 2, 7 1418.9 <0.001

*Common letters denote means are not significantly different (P = 0.05) from one another, as determined by Tukey's HSD.

54

Table 4-2. Effect of soil-quality and ant-exclusion treatment on abundance of arthropods (mean ± std. error).

Low-soil-quality Intermediate-soil-quality High-soil-quality

Control No ant Control No ant Control No ant

Total scales 35 ± 5 56 ± 5 55 ± 10 67 ± 13 57 ± 7 75 ± 8

A. instabilis 3.2 ± 0.6 0.1 ± 0.1 3.6 ± 0.8 0.5 ± 0.2 4.8 ± 1.1 0.6 ± 0.2

A. instabilis (per scale) 0.12 ± 0.03 0 ± 0 0.09 ± 0.02 0.01 ± 0 0.13 ± 0.04 0.01 ± 0

Other ants 5.5 ± 4.5 0.8 ± 0.5 5.6 ± 3.8 0.2 ± 0.1 7.7 ± 5.7 2.9 ± 2.1

Toxoptera sp. 0 ± 0 2 ± 1 5 ± 4 8 ± 5 0 ± 0 6 ± 2

A. orbigera larvae 0.04 ± 0.03 0.48 ± 0.19 0.09 ± 0.03 0.41 ± 0.16 0.11 ± 0.05 0.14 ± 0.08

A. orbigera (per scale) 0 ± 0 0.01 ± 0 0.01 ± 0 0.01 ± 0 0.01 ± 0.01 0 ± 0

Parasitoids 0.11 ± 0.1 0.33 ± 0.1 0.07 ± 0 0.75 ± 0.3 0.04 ± 0 0.54 ± 0.2

Parasitoids (per scale) 0 ± 0.01 0.01 ± 0 0 ± 0 0.02 ± 0.01 0 ± 0 0.01 ± 0

Lecanicillium lecanii 6 ± 2 10 ± 2 8 ± 4 17 ± 7 10 ± 3 10 ± 2

L. lecanii (per scale) 0.45 ± 0.3 0.28 ± 0.09 0.28 ± 0.13 0.56 ± 0.26 0.23 ± 0.08 0.18 ± 0.05

Hemiptera 0.9 ± 0.3 0.7 ± 0.2 0.6 ± 0.2 0.8 ± 0.2 0.9 ± 0.3 1.5 ± 0.3

55 Coleoptera 0.8 ± 0.4 0.3 ± 0.1 1.4 ± 0.8 0.7 ± 0.3 1.3 ± 0.7 0.4 ± 0.1

Spiders 0.5 ± 0.2 1 ± 0.3 0.5 ± 0.2 1.5 ± 0.3 0.7 ± 0.2 1.1 ± 0.4

Total arthropods 47 ± 7 64 ± 6 74 ± 11 82 ± 15 74 ± 10 89 ± 8

Arthropods (without mutualists) 2.8 ± 0.6 5.3 ± 1.1 3.8 ± 1 6 ± 1.4 4.2 ± 0.9 4.5 ± 0.8

56 Table 4-3. Effect of soil-quality and ant-exclusion treatments on common arthropods.

df F P

A. instabilis

Soil-quality 2, 90 1.767 0.177

Ant 1, 90 116 <0.001

Soil × Ant 2, 90 0.128 0.88

Site 18, 90 1.984 0.018

A. instabilis (per scale)

Soil-quality 2, 90 0.464 0.631

Ant 1, 90 57.05 <0.001

Soil × Ant 2, 90 0.534 0.588

Site 18, 90 2.716 0.001

Other ants

Soil-quality 2, 90 0.148 0.863

Ant 1, 90 14.66 <0.001

Soil × Ant 2, 90 0.556 0.576

Site 18, 90 3.472 <0.001

Toxoptera sp.

Soil-quality 2, 90 2.737 0.07

Ant 1, 90 6.534 0.012

Soil × Ant 2, 90 0.819 0.444

Site 18, 90 2.021 0.016

57 Table 4-4. Effect of soil-quality and exclusion treatments on predators, parasitoids, and pathogens of Coccus viridis

No. of individuals No. of individuals per scale

insect

df F P df F P

Azya orbigera larvae

Soil-quality 2, 90 2.22 0.114 2, 90 2.44 0.093

Ant 1, 90 7.43 0.008 1, 90 3.10 0.082

Soil × Ant 2, 90 2.63 0.078 2, 90 2.27 0.109

Site 18, 90 2.73 <0.001 18, 90 2.28 0.006

Parasitized scales

Soil-quality 2, 90 0.42 0.656 2, 90 0.36 0.698

Ant 1, 90 21.67 <0.001 1, 90 18.53 <0.001

Soil × Ant 2, 90 0.48 0.618 2, 90 0.42 0.656

Site 18, 90 2.77 <0.001 18, 90 2.76 <0.001

Lecanicillium lecanii

58 Soil-quality 2, 90 0.33 0.721 2, 90 0.28 0.756

Ant 1, 90 5.80 0.018 1, 90 1.81 0.182

Soil × Ant 2, 90 0.95 0.392 2, 90 0.76 0.47

Site 18, 90 3.38 <0.001 18, 90 4.19 <0.001

59 Table 4-5. Effect of soil-quality and ant-exclusion treatment on coffee arthropod community.

Soil-quality Ant Soil-quality x Ant Site

df F P df F P df F P df F P

Total Arthropods 2, 90 5.177 0.007 1, 90 4.725 0.032 2, 90 2.826 0.253 18, 90 1.397 0.001

Arthropods (no ants or mutualists) 2, 90 0.275 0.76 1, 90 8.411 0.005 2, 90 0.482 0.619 18, 90 3.45 <0.001

54,

MANOVA 6, 178 1.187 0.315 3, 88 3.053 0.033 6, 178 1.412 0.212 270 2.152 <0.001

Hemiptera 2, 90 1.677 0.193 1, 90 2.139 0.147 2, 90 1.267 0.287 18, 90 1.476 0.118

Coleoptera 2, 90 1.2 0.306 1, 90 1.482 0.227 2, 90 1.516 0.225 18, 90 4.199 <0.001

Spiders 2, 90 0.203 0.817 1, 90 6.06 0.016 2, 90 0.784 0.46 18, 90 1.566 0.086

60 Table 4-6. Effect of soil-quality on coffee leaf area, growth rate, elemental nutrients, and leaf and phloem caffeine.

Soil-quality treatment

Plant characteristic Low Intermediate High

Final leaf count 27 ± 1a 42 ± 2b 40 ± 2b

Final total leaf area 186 ± 11a 312 ± 17b 315 ± 12b

Growth rate (final/initial TLA) 0.37 ± 0.02a 0.63 ± 0.04b 0.86 ± 0.06c

Carbon (%) 45 ± 0.24 45 ± 0.21 45 ± 0.18

Nitrogen (%) 2 ± 0.05a 2.5 ± 0.06b 2.6 ± 0.06b

Phosphorus (%) 0.2 ± 0.03 0.2 ± 0.01 0.2 ± 0.03

Potassium (%) 2.4 ± 0.12a,b 2.2 ± 0.07a 2.6 ± 0.05b

Calcium (%) 1 ± 0.04a 1.2 ± 0.08b 1 ± 0.03a,b

Magnesium (%) 0.2 ± 0.01a 0.3 ± 0.02b 0.3 ± 0.01a

Sulfur (%) 0.2 ± 0.01 0.2 ± 0.01 0.2 ± 0.01

Boron (mg kg-1) 86 ± 4a 83 ± 4a 67 ± 2b

Copper (mg kg-1) 5 ± 1a 10 ± 1b 12 ± 1b

Iron (mg kg-1) 246 ± 30 267 ± 36 276 ± 34

Manganese (mg kg-1) 334 ± 34a 229 ± 28b 125 ± 21c

Zinc (mg kg-1) 13 ± 0.4 13 ± 0.6 14 ± 1.3

Phloem caffeine (ug L-1) 0.1 ± 0.04a 0.2 ± 0.04b 0.21 ± 0.03b

Leaf caffeine (mg g-1) 5 ± 0.89 5 ± 0.74 6 ± 0.9

61 Table 4-7. Correlation table with green-scale abundance vs. independent variables.

Independent Variables N r P

A. instabilis 114 -0.042 0.654

A. orbigera larvae 114 0.009 0.926

L. lecanii 114 -0.129 0.17

Parasitoids 114 0.188 0.045

Other ants 114 -0.126 0.182

Leaf area growth rate 111 0.249 0.008

Final total leaf area 111 0.226 0.017

Final number of leaves 111 0.19 0.046

C 65 -0.133 0.291

N 65 0.231 0.064

P 24 0.136 0.525

K 24 0.133 0.534

Ca 24 0.085 0.693

Mg 24 0.078 0.717

S 24 0.093 0.667

B 24 -0.184 0.39

Cu 24 0.111 0.604

Fe 24 0.215 0.314

Mn 24 -0.21 0.324

Zn 24 0.426 0.038

Phloem caffeine 44 -0.112 0.469

62 Leaf caffeine 23 0.226 0.3

63

80

60

40 Control 20 No ant Total green scales 0 Low Intermediate High

Soil quality treatment

Figure 4-1. The effect of soil-quality and ant-exclusion treatments on mean (± std. error) number of total scales averaged across the five sampling events.

64

40

30

20 Pheidole

No. 10

0 Low Intermediate High Soil quality treatment

Figure 4-2. The effect of soil-quality treatment on the mean (± std. error) number of

Pheidole sp. workers per coffee seedlings with Coccus viridis.

3

2 per scale insect per 1 Pheidole

No. 0 Low Intermediate High Soil quality treatment

Figure 4-3. The effect of soil-quality treatment on the mean (± std. error) number of

Pheidole sp. per scale insect on coffee seedlings with Coccus viridis.

65

12

9

6

3 Scales removed Scales removed

0 Control Exclusion

Figure 4-4. The effect of ant-exclusion treatment on mean (± std. error) scale removal by

Azya orbigera larvae.

66

Chapter 5

Conclusions

5.1 The effect of nitrogen availability and soil-quality on coffee-plant quality

In Chapter 2, I demonstrated that nitrogen fertilization increased N in plant tissues and in Chapter 4, I showed that high-soil-quality resulted in higher N. Together these results suggest that greater N availability will result in a greater foliar N in coffee plants, which should translate to higher diet quality for insect herbivores (Awmack & Leather

2002). At the same time, caffeine content in leaf tissues, as well as, root and stem were unaffected by soil or nitrogen fertilization. However, both in Chapter 2 and 4, my results suggest that caffeine phloem exudation increases under increased nitrogen fertilization and soil-quality. The mechanism behind this increase is unknown. Regardless, this data suggest that if caffeine indeed affects phloem-feeding insects then it might have greater impacts at greater N availability or soil-quality. The relative importance of caffeine or N within the phloem would then be important to herbivore growth. It should be noted that N was not measured in the phloem, but at the leaf level, which may be a crude estimate of phloem amino acids, the form of N important to hemipteran herbivores (Ponder et al.

2000).

5.2 Effect of soil-quality and plant quality on green-scale growth

67 The results from both the field survey in Chapter 3 and the field experiment in

Chapter 4 suggest that plant nutrition and growth rate are more important to scale growth than caffeine. In Chapter 3, coffee green scale density on coffee plants was found to be related to the percent N within plant tissues, but not phloem or leaf caffeine (Table 3-1).

Additionally, in Chapter 4, higher soil-quality led to higher leaf N, higher phloem caffeine, and higher green-scale populations. Together, these data suggest that under field conditions green scales are more responsive to N than to caffeine content. However, it should be noted that plant N was only marginally correlated with green-scale population size. Further, other plant characters showed higher correlations, for example plant growth rate was most highly correlated with green-scale population size (Chapter 4). Therefore, other characters that limit plant growth might also be important to scale growth, for instance light availability.

5.3 Effect of soil-quality on species interactions

The results of this study suggest that soil-quality can influence the interactions between the Pheidole sp. ants and green scales, but not A. instabilis and green scales.

This is perhaps the first time two ant species have been compared in terms of recruitment to scale insects across varying soil-quality. Pheidole sp. ants showed increased recruitment to green scale at a rate of about 3 times more workers per scale insect. The importance of this change in recruitment is unknown because little is known about the nature of the Pheidole – green scale association. Only a handful of studies have investigated the effect of fertilization or plant quality on ant recruitment to hemipterans, and only one study has found marginal support that increased recruitment (caused by

68 plant quality) leads to higher hemipteran fitness (Baylis & Pierce 1991). It is unknown why A. instabilis did not alter recruitment to scales on high-soil-quality plants. It may be a result of low abundance of green scales on coffee seedlings or the short duration of this study.

I found little evidence that soil-quality mediated the interactions between green scales and predators, parasitoids, or pathogens. The abundance of A. orbigera larval predators, parasitized scale insects, or scale insects infested with white halo fungus, did not differ across soil-quality treatments. The presence or absence of A. instabilis ants appeared much more important to the natural enemies of green scales.

5.4 Effect of soil-quality on arthropod community

When all arthropods were taken into consideration, soil-quality treatment had strong impacts on arthropod total abundance. However, these impacts were strongly due to the effect of soil-quality treatment on ant-tended hemipterans and ants. When, ant- hemipteran mutualists were excluded the effect of soil-quality diminished. However, both measurements of total arthropods (with and without ant-hemipteran mutualism) showed more arthropods on ant-excluded plants relative to ant-free plants, suggesting A. instabilis could limit the abundance of the arthropod community on coffee. Although other studies have found A. instabilis to limit some arthropod groups (Vandermeer et al. 2001, Philpott et al. 2004, Philpott et al. 2008), this study is the first to demonstrate that A. instabilis may impact the entire arthropod community.

5.5 Future directions

69 Plant ontogeny can mediate the effects of plant quality and predation in some cases (Boege & Marquis 2006), therefore manipulation of host-plant quality at the adult coffee plant stage, rather than at the seedling stage, could reveal different effects of plant quality on the insect community. For example, recruitment of A. instabilis may be altered at larger scale population densities and the influence of host-plant quality or soil-quality may be observed at that level. Additionally, long-term soil-quality manipulations could also reveal the importance of host-plant quality to the population dynamics of the green scale in this complex community. Few have modeled how plant quality can alter the spatial dynamics of herbivores and predators, let alone in a complex system.

Manipulating other abiotic and biotic factors that can be important to the insect community is also warranted. For example, strong effects of host plant genotype or variety have been demonstrated in many systems. In the coffee agroecosystem, coffee characters vary across cultivars and interspecific hybrids with C. canephora and the importance of this variation to scale growth and the insect community could provide novel findings in complex tropical ecosystems. Investigating what other coffee secondary metabolites might be important to herbivores is also justified. Chlorogenic acid, for example is negatively correlated with scale insect growth (Fernandes 2007) and important in other plant-herbivore systems (Ikonen et al. 2001). Additionally, coffee agroecosystems range across a shade intensification gradient and understanding how variation in light availability across levels of shade effects the quality of host plants to herbivores could provide interesting results.

Finally, scrutinizing the effect of host plant nutrition and chemistry could reveal far-reaching effects of host plants in the complex coffee agroecosystem. Indirect effects

70 of host plant on predators, parasitoids, and pathogens may be observed under laboratory conditions and at higher trophic levels. For example, A. orbigera larvae contain caffeine in their tissues or digestive traits (D. Gonthier unpublished data), spiders rarely consume larvae, and caffeine is toxic to spiders (Noever et al. 1995), but does caffeine provide larvae resistance from spider predation? Questions such as these could provide novel influences of host plants at the fourth trophic level of this community.

5.6 Conclusions

N availability and soil-quality influenced plant N and phloem caffeine exudation in coffee seedlings. The coffee green scale density was correlated with host plant leaf N across natural variation in coffee host plants in the field. Additionally, green-scale populations were greater on coffee seedlings with higher soil-quality, relative to low-soil- quality plants. Soil-quality influenced the recruitment of Pheidole ants to green scales, however A. instabilis recruitment was not altered. Effects of soil-quality were observed across total arthropods, but this was due mostly to the effect on ant-hemipteran mutualisms. These results suggest soil-quality and host-plant quality can have important impacts on a tropical arthropod community dominated by species interactions. Further, this research will add to the under-represented literature describing bottom-up effects in top-down systems.

71

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