Nutrient Availability in the Rhizosphere of Coffee:

Shade-Tree and Fertilization Effects

by

Jake Warner Munroe

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

Department of Geography

University of Toronto

© Copyright by Jake Warner Munroe, 2013

ii

Nutrient Availability in the Rhizosphere of Coffee:

Shade-Tree and Fertilization Effects

Jake Warner Munroe

Master of Science

Department of Geography

University of Toronto

2013

Abstract

Shade tree incorporation is beneficial in coffee cropping systems under sub-optimal conditions.

This study was performed in lowland Costa Rica, at a 12-year-old experimental coffee farm. The

main objective was to compare the effect of a nitrogen fixing shade tree, Erythrina poeppigiana,

on nutrient availability in the rhizosphere of coffee under conventional fertilization.

Accumulation of nutrients (mineral N, available P, and exchangeable base cations) in

rhizosphere relative to bulk soil was greater under shade than full sun. Low nitrate availability in

rhizosphere soil of full sun coffee was explained by root-induced acidification relative to bulk

soil, as abundance of ammonia-oxidizing bacteria (AOB), which mediate nitrification, were

positively correlated with pH. Organic fertilization enhanced AOB abundance and altered soil

bacterial community structure relative to conventional fertilization. This study indicates clear

effects of shade-tree presence on nutrient availability at the micro-scale, management of which is

critical for stability of coffee agroforestry systems.

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Acknowledgements

I am very grateful for the support and guidance of my supervisor, Dr. Marney Isaac,

throughout this process. Your insightful advice and direction combined with an approach that

allowed for individual creativity was really beneficial. I am grateful to Dr. Roberta Fulthorpe for

so enthusiastically agreeing to assist me with the microbial component of my project and, along

with Dr. Nathan Basiliko, for participating as a member of my defense committee.

I am thankful to Gabriela Soto for her practical advice during my fieldwork at CATIE

and to Dr. Elias de Melo. Thank you to Luis Romero, the Farm Manager at CATIE, for

providing important information on management practices at the site. I am also grateful to

Patricia Leandro and Manrique González for generously providing lab space, and to Claudio, for

his endless patience and assistance in the lab despite our language barrier.

I would also like to thank all of the other people who have helped me at some point along

the way. Learning how to conduct independent research requires the support of others at every

turn. For invaluable practical assistance with molecular biology lab techniques, I am incredibly

grateful to Roxana Shen, and to Nicole Rickers, for her help with real-time PCR. Thank you to

all of the others who assisted me, including my lab-mates, volunteers, and staff at UTSC. I am

also grateful to the Ontario Graduate Scholarship (OGS), the Dept. of Geography Graduate

Expansions Fund, and NSERC (Discovery Grant to M. Isaac) for funding.

And last, but certainly not least, thank you to my family and friends for their steady

support and encouragement throughout the past two years.

iv

Table of Contents Abstract ......................................................................................................................................... ii

Acknowledgements ...................................................................................................................... iii

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

List of Figures .............................................................................................................................. vii

Chapter 1: Introduction ............................................................................................................... 1 1.1 Research context ........................................................................................................... 1

1.2 Research background, objectives, and hypotheses ....................................................... 3

Chapter 2: Agroforestry Systems and Nutrient Dynamics in the Rhizosphere ...................... 7

2.1 Multistrata agroforestry systems ................................................................................... 8

2.2 The role of nitrogen fixation in agroforestry ................................................................ 8

2.2.1 N inputs by nitrogen fixing trees .......................................................................... 9

2.2.2 Nutrient cycling by Erythrina poeppigiana ........................................................ 10

2.3 The rhizosphere in agroforestry systems .................................................................... 11

2.4 The rhizosphere ........................................................................................................... 12

2.5 Nutrient availability in the rhizosphere....................................................................... 14

2.5.1 Rhizosphere effects on pH .................................................................................. 15

2.5.2 Mineral N dynamics in the rhizosphere .............................................................. 16

2.6 Ammonia oxidation .................................................................................................... 17

Chapter 3: Costa Rica’s Coffee Sector: Past and Present....................................................... 20

3.1 Introduction ................................................................................................................. 20

3.2 Smallholder coffee producers in Costa Rica ............................................................... 21

3.3 The role of state agricultural research institutions in promoting the modernization of

the coffee sector ............................................................................................................... 22

3.4 The impact of modernization on Costa Rican smallholders ....................................... 25

3.5 Conclusions ................................................................................................................. 26

Chapter 4: Site Description and Methodology ......................................................................... 28 4.1 Site description ........................................................................................................... 28

4.2 Sample selection ......................................................................................................... 31

4.3 Sampling protocol ....................................................................................................... 34

4.4 Soil nutrient analysis ................................................................................................... 34

4.5 Soil microbial analysis ................................................................................................ 35

4.5.1 Denaturing Gradient Gel Electrophoresis ........................................................... 36

4.5.2 Real-time PCR assays ......................................................................................... 36

4.6 Statistical analyses ...................................................................................................... 38

Chapter 5: Results....................................................................................................................... 39

5.1 Bulk soil chemical characteristics ............................................................................... 39

5.2 Rhizosphere effects on nutrient properties ................................................................. 39

v

5.2.1 Rhizosphere effects on nutrient properties within management treatments ....... 42

5.2.2 Magnitude of rhizosphere effect on soil nutrients .............................................. 45

5.3 Relative quantification of bacteria .............................................................................. 45

5.3.1 Relative amoA gene abundance .......................................................................... 45

5.3.2 Correlates of soil chemical and biological parameters ....................................... 48

5.4 Bacterial community structure in bulk soil ................................................................. 48

Chapter 6: Discussion

6.1 Rhizosphere effects on nutrient availability ............................................................... 53

6.1.1 Rhizosphere effects on mineral N availability .................................................... 53

6.1.2 Rhizosphere effects on available P ..................................................................... 55

6.1.3 Rhizosphere effects on exchangeable base cation concentrations ...................... 57

6.2 Management treatment effects on the magnitude of the rhizosphere effect ............... 57

6.2.1 The effect of shade trees ..................................................................................... 57

6.2.1.1 Ammonium ................................................................................................. 58

6.2.1.2 Nitrate ......................................................................................................... 60

6.2.2 The effect of fertility management ..................................................................... 62

6.2.3 Bulk soil properties ............................................................................................. 64

Chapter 7: Conclusions .............................................................................................................. 67

References .................................................................................................................................... 69

Appendix ...................................................................................................................................... 76

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List of Tables

Table 1. Fertilization and pest/weed control protocols at the experimental coffee farm of the

Centro Agronómico Tropical de Investigación y Enseñanza (CATIE) ........................................ 30

Table 2. Soil pH, NO3-, NH4

+, available P, and exchangeable Ca2+, Mg2+, and K+ concentrations

in bulk soil under full sun management with conventional fertilization (FS-C), shade with

conventional fertilization (S-C), and shade with organic fertilization (S-O) at 0-20cm .............. 40

Table 3. Soil chemical and biological properties of rhizosphere and bulk soil of coffee under all

treatments (pooled) at 0-20cm and 20-40cm soil depths. Values are mean ± SE and sample size

refers to number of samples within a soil fraction (rhizosphere or bulk) at a given soil depth .... 41

Table 4. Soil pH and exchangeable base cation concentrations (mean ± SE) in bulk and

rhizosphere soil at 0-20cm (n=9 per management treatment, per soil fraction) and 20-40cm depth

(n=3 per management treatment, per soil fraction) ....................................................................... 44

Table 5. amoA abundance (relative to total bacteria) in rhizosphere and bulk soil fractions across

all three management treatments at 0-20cm. Data are means (n=3 per management treatment, per

soil fraction) ± SE of samples pooled by block before real-time PCR assay (n=3 per block, per

soil fraction). Note, S-C values are used twice in t-tests as the common treatment combination to

comparisons in which i) fertility and ii) shade are held constant ................................................. 47

vii

List of Figures

Figure 1. A conceptual model of nutrient dynamics in a multistrata agroforestry system with a

nitrogen-fixing tree. The NFT fixes atmosphere nitrogen and inputs it primarily via leaf litter-fall

and branch prunings, which decompose and are mineralized at the soil surface. Other nutrients

are cycled from lower soil depths by the tree and deposited in organic form at the litter layer. The

tree modifies light levels, which in the system under study in Costa Rica, has been shown to

enhance the photosynthetic rates of coffee. Inorganic nutrients reach to crop roots via a

combination of mass flow and diffusion, which are driven by transpiration and soil concentration

gradients. Roots affect nutrient availability within the rhizosphere through the release of labile

carbon exudates, as well as H+ ions and enzymes. Carbon-rich exudates drive microbe-mediated

mineralization of native soil organic matter in the root zone, which can result in the release of

mineral N (and other nutrients) via microbial turnover. Diagram at bottom right adapted from

Paterson, 2003 ............................................................................................................................... 13

Figure 2. Map of CATIE experimental coffee farm with delineation of sub-plots sampled as part

of study. Structural pattern of coffee grown in E. poeppigiana shade plots shown, along with

example of sampling within a single subplot ................................................................................ 32

Figure 3. Coffee growing under E. poeppigiana shade (Block 3, Intensive Organic subplot, June

2012). Stump-coppiced tree in centre of picture; full-size Erythrina trees in a row on right side of

picture ........................................................................................................................................... 33

Figure 4. Mean NO3-, NH4

+, and available P concentrations in bulk and rhizosphere soil of coffee

under all three management treatments (FS = full sun; S = shade; C = conventional fertilization;

O = organic fertilization) at (a) 0-20cm depth and (b) 20-40cm depth. Significant differences

between rhizosphere and bulk soils within management treatments are indicated by different

letters (paired t-test, P <0.05). Bars represent ± SE; n=9 per soil fraction for 0-20cm; n=3 per soil

fraction for 20-40cm ..................................................................................................................... 43

Figure 5. Mean percentage rhizosphere effect ([(Rhizosphere - Bulk)/Bulk]*100%) of coffee

grown under FS-C, S-C, and S-O management treatments (FS = full sun; S = shade; C =

conventional fertilization; O = organic fertilization) at 0-20cm depth (n=9 per management

treatment). Significant differences in magnitude of rhizosphere effect between FS-C and S-C are

denoted by different lower case letters (t-test, P <0.05) and by upper case letters between S-C

and S-O (t-test, P <0.05). Bars represent standard error of the mean ........................................... 46

Figure 6. Mean percentage rhizosphere effect ([(Rhizosphere - Bulk)/Bulk]*100%) on amoA

gene abundance relative to total bacteria abundance at 0-20cm (n=3 per treatment; bars are

standard error). Significant difference between conventionally fertilized full sun and shade

treatments denoted by lower case letters; between organic and conventional fertilization by

capital letters (t-test; P <0.05). Asterix denotes a significant rhizosphere effect

(t-test; P <0.05) ............................................................................................................................. 49

Figure 7. Rhizosphere soil NO3- concentration (mg kg-1) in relation to soil pH at 0-20cm soil

depth under FS-C management (n=9) ........................................................................................... 50

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Figure 8. Relative amoA gene abundance as a function of pH in bulk and rhizosphere soil at 0-

20cm as pooled by fertilization treatment (FS-C + S-C; n=11, one outlier removed). Data points

represent block mean values for amoA and pH. Bars represent standard error (n=3) of mean pH

values ............................................................................................................................................ 51

Figure 9. (a) DGGE profiles of 16S ribosomal DNA obtained using universal bacterial primers

from bulk soil (0-20 cm) from all three treatments combinations (FS-C, S-C, S-O). Lanes 2-6

represent samples from FS-C; lanes 7-9 represent samples from S-C; and lanes 10-12 are

samples from S-O. Lanes 1 and 14 are an identical profile from S-O, used as a ladder for

normalization. (b) DGGE-derived dendogram (without lanes 1, 2, 3, or 14), as determined by

unweighted pair group method with arithmetic mean (UPGMA) ................................................ 52

1

Chapter 1

Introduction

1.1 Research context

Coffee is one of the most valuable agricultural exports and it is estimated to employ over

25 million worldwide (Ricketts et al, 2004). Since the 1950s, full-sun coffee cultivation has

emerged as a new mode of production in contrast to the traditional shade-grown model

throughout Central America. In this system, fossil fuel-derived inputs substitute for the functions

of intercropped trees. While higher yields can be achieved under optimal conditions, they come

at the expense of high up-front production costs, loss of biodiversity, and environmental

degradation in fragile upper watersheds (Perfecto et al, 2005; Haggar et al, 2011). This

monoculture production model has not been widely applicable for Costa Rican growers, of which

the vast majority have a small land base and limited capital (Haggar et al, 2011). In response to

this and the opening of markets for “shade-grown” coffee, research efforts have focussed on

improving tree-based coffee production. Essential to such research is an understanding of the

biophysical interactions between shade trees and the associated coffee crop, and how positive

interactions can be maximized through proper management practices.

It is generally acknowledged that the benefits of shade-tree incorporation occur under less

favourable conditions (Beer et al, 1998; DaMatta, 2004). Full sun coffee provides higher yields

when climatic conditions are optimal and there are no severe nutrient or non-nutrient limitations

(Beer et al, 1998; DaMatta, 2004). Beneficial effects of shade trees on coffee yield become

noticeable at low or very high altitudes and under poor edaphic conditions (Beer et al, 1998).

Shade-tree incorporation has also been found to be beneficial when low or moderate levels of

external inputs are used (Haggar et al, 2011). In the case of the leguminous shade trees, this

benefit can be derived from fixed nitrogen, as well as improved nutrient cycling.

2

Arabica coffee, which is the exclusive species grown in Costa Rica, evolved as a tropical

forest understorey shrub in Ethiopia (DaMatta, 2004). Climatic conditions at this latitude and

altitude (1600-2800m) are characterized by a steady, warm (20 ºC) air temperature and well

distributed rainfall for 8 months of the year (DaMatta, 2004). The presence of shade trees can

serve to buffer fluctuations in temperature for coffee in whatever climate it is being cultivated

(Beer et al, 1998). Shaded coffee plants have a longer life expectancy than coffee grown in full

sun, a benefit that has been attributed to reduced plant exhaustion (Beer et al, 1998; DaMatta,

2004). Reduced light levels can exacerbate pest and disease problems if shade is not properly

managed, but prevent strong biennial yield fluctuations common to unshaded coffee (Beer et al,

1998; DaMatta, 2004).

Shade tree incorporation can also serve to improve nutrient availability for associated

coffee plants. In the case of nitrogen-fixing shade trees, significant inputs of nitrogen (N) can be

made available to coffee through litter and pruning deposition, as well as root and nodule

turnover (Beer et al, 1998; Snoeck et al, 2000; Nygren et al, 2012). Higher rates of soil N

mineralization have been found under coffee shaded by Erythrina poeppigiana, a nitrogen-fixing

shade tree, compared to full sun coffee in two separate Costa Rican coffee systems (Beer et al,

1998; Haggar et al, 2011). Cycling of other nutrients, such as phosphorus, potassium,

magnesium, and calcium can be substantial, especially when regular branch pruning is performed

(Beer et al, 1998; Nair et al, 1998).

While the effects of shade tree incorporation have been fairly well described in terms of

aboveground metrics, much is unknown regarding belowground dynamics in coffee agroforestry

systems. As Beer et al (1998) assert, belowground processes in these systems remain a ‘black

box’, of which the underlying biological and chemical mechanisms are poorly understood.

3

Specifically, the belowground mechanisms by which shade-tree incorporation improves coffee

performance under low external inputs have not been fully uncovered. These mechanisms are

difficult to address, as they are highly affected by both aboveground physiological adaptations to

shade as well as plot-level management effects on soil properties. The rhizosphere – the zone of

interaction between live roots and the soil – represents a region that can provide insight as to

differences in nutrient availability between shade and full sun coffee.

1.2 Research background, objectives, and hypotheses

The rhizosphere represents a soil fraction, distinct from bulk soil in its chemical,

physical, and biological properties (Gobran and Clegg, 1996; Phillips and Fahey, 2008; Zhao et

al, 2010), which is rarely considered when determining nutrient status in soils. In addition to root

structure, nutrient acquisition is dependent upon biochemical changes and interactions with

microorganisms in this soil zone (Richardson et al, 2009). Roots release enzymes, H+ ions, and

carbon-rich molecules that can increase nutrient availability through a variety of mechanisms

(Rengel and Marschner, 2005). These plant-mediated activities can in turn be affected by

aboveground environmental conditions (Grayston et al, 1996). Facilitative nutrient effects of

intercropping have been observed within the rhizosphere of herbaceous crop species (Hinsinger

et al, 2009; Isaac et al, 2012); little is known, however, of the effects of shade trees on nutrient

availability in the rhizosphere of coffee. By examining the gradient of available nutrients

between rhizosphere and bulk soil of coffee in monoculture and under shade, I hoped to uncover

how shade tree incorporation affects nutrient acquisition occurring at a micro-scale.

Additionally, I seek to relate differences in the magnitude of rhizosphere-to-bulk

gradients to levels of external inputs. As previously mentioned, shade trees are reportedly

beneficial in systems in which external inputs are low. Interestingly, enhanced rhizosphere

4

accumulation of nutrients has been observed under nutrient-poor edaphic conditions in non-

agroforestry systems (Wang and Zabowski, 1998; Phillips and Fahey, 2008). In order to assess

whether root-induced effects on nutrient availability differ according to soil nutrient status, I

investigated nutrient availability in the rhizosphere of shaded coffee, under intensive (organic)

vs. moderate (conventional) fertilization. Note that throughout this paper, the rhizosphere effect

will refer to the difference between rhizosphere soil and bulk soil, with a positive rhizosphere

effect meaning that a particular nutrient is present in a higher concentration in rhizosphere

relative to bulk soil.

In accordance with the concepts introduced above, I propose the following hypotheses for the

coffee-shade system under study:

1) The rhizosphere effect will be positive for mineral nitrogen, available phosphorus, and

exchangeable base cations across treatments. Coffee root exudation of labile carbon will

stimulate microbial activity and nutrient cycling at the root zone, which will result in

nutrient accumulation in the rhizosphere.

2) The magnitude of the positive rhizosphere effect on nutrients will be greater for

conventionally fertilized coffee grown in association with a N2-fixing shade tree versus in

full sun, due to modifications of coffee plant physiology under shade.

3) The magnitude of the rhizosphere effect will be greater for shade-grown coffee under

conventional fertilization than organic fertilization, as explained by plant carbon

allocation theory, which predicts decreased carbon flow (and therefore exudation) to

roots in fertile soils.

5

To address these hypotheses, I will draw upon a research site in Costa Rica in which

coffee grown in full sun can be compared to coffee grown under the shade of Erythrina

poeppigiana, a nitrogen-fixing shade tree common to coffee agroforestry systems in that country.

At the 12-year-old site, high external input fertilization (henceforth referred to as organic

fertilization) can be compared with moderate levels of fertilization (henceforth referred to as

conventional fertilization). Early research at this site has indicated that the incorporation of E.

poeppigiana has the greatest effect on coffee productivity under low nutrient input conditions

(Haggar et al, 2011). It is believed that under such conditions, the ecological services of the

leguminous shade tree – in terms of N2 fixation and nutrient cycling – become realized to a fuller

extent than when external inputs compensate for them (Haggar et al, 2011).

Previous work at the same site by L. Campbell has demonstrated that under conventional

fertilization, shade tree incorporation results in enhanced photosynthetic rates in coffee relative

to full sun. Campbell (2012) observed significantly higher photosynthetic rates at light saturation

(Amax) under conventionally fertilized coffee grown under shade as compared to monoculture

coffee. Additionally, shaded plants showed a trend towards higher photosynthetic nitrogen use

efficiency and had significantly greater leaf phosphorus (P) content and photosynthetic

phosphorus use efficiency (Campbell, 2012). As no significant correlations were found between

soil nutrients (available P, total N) and coffee leaf parameters at the whole plot level, the author

suggested that leaf trait differences observed under shade were primarily driven by shade effects.

Indeed, shade levels (49-69%) were within the optimal range for a shade-adapted perennial such

as coffee (Campbell, 2012). A positive effect of shade on stomatal conductance, which in turn

was positively correlated with Amax values, points to a possible mechanism underlying the

6

facilitative physiological adaptation. Some observations, however, were not satisfactorily

explained.

In a vector analysis, in which relative biomass, nutrient concentrations and nutrient

content of coffee leaves were compared relative to full-sun conventionally fertilized coffee,

several observations of interest were made. While leaf biomass was universally greater under the

shade of E. poeppigiana and Chloroleucon eurycyclum, another nitrogen-fixing tree intercropped

at the site, N and P content often did not keep pace – a phenomenon known as a dilution effect

(Campbell 2012). Under Erythrina shade and conventional fertilization, however, N leaf

concentration was found to maintain sufficiency, i.e., N uptake kept pace with increased leaf

biomass. Despite this, soil analyses did not present a difference in soil N content between these

plots. Campbell (2012) explained the phenomenon as follows:

“Differences in leaf nutrient response appear to be divided by species, with coffee grown

below Erythrina appearing to be able be better able to match increases in leaf biomass by

increasing leaf nutrient content, presumably via increased nutrient uptake within these

environments.” (italics added for emphasis)

It was with this interesting, yet only partially explained observation in mind that this study was

designed; with the purpose of probing the effects of E. poeppigiana incorporation on nutrient

availability at the root-soil interface of coffee.

Here within, I will describe nutrient dynamics and rhizosphere processes in agroforestry

systems by focussing on coffee agroforestry and drawing on other systems when necessary. I

will then place this thesis within the larger socio-political framework of Costa Rica’s coffee

sector, both past and present. Next, I will provide a detailed methodological approach and

7

present novel results, particularly on the first-time use of molecular techniques to quantify the

abundance of ammonia oxidizing bacteria in a coffee agroforestry system. Finally, I will

interpret my findings within the larger literature on rhizosphere processes and coffee agroforestry

nutrient dynamics.

8

Chapter 2 Agroforestry Systems and Nutrient Dynamics in the Rhizosphere

2.1 Multistrata agroforestry systems

Multistrata agroforestry systems are tree-crop based land use systems with two or more

vegetation layers, which include more than one tree species (Schroth et al, 2001). They range

from highly diverse homegardens to dual-species plantations. Multistrata systems are ubiquitous

throughout the humid and semi-humid tropics and crops commonly grown under the simplified

plantation form, such as coffee and cacao, hold tremendous global economic importance

(Schroth et al, 2001; Isaac et al, 2007; Nygren et al, 2012). The incorporation of a tree over-

storey serves a variety of purposes, which include light and temperature regulation, enhanced

nutrient and water cycling, organic matter accumulation, pest regulation, and, when nitrogen-

fixing trees (NFT) are used, nitrogen input.

2.2 The role of nitrogen fixation in agroforestry

Although natural ecosystems of the humid tropics have relatively open N cycles and high

levels of available nitrogen (Martinelli et al, 1999), export of N in harvest and reduced nutrient

cycling can cause N to be a growth-limiting factor (Kurppa et al, 2010). Application of inorganic

chemical fertilizers can maintain soil fertility levels, but are often inaccessible and unaffordable

for smallholder farmers (Haggar et al, 2011). Additionally, N fertilizers can have low use

efficiency and have detrimental environmental impacts, such as transformation into nitrous

oxides (Nygren et al., 2012). Through enhanced structural and functional diversity, trees within

agroforestry systems can partially restore N cycling in highly simplified cropping systems.

Nitrogen-fixing trees commonly used in agroforestry systems can derive anywhere from 10-92%

of their N from the atmosphere (Nygren et al, 2012); they represent an important source of N

9

input. In Costa Rica, coffee is commonly cultivated under the shade of the regularly pruned NFT

Erythrina poeppigiana.

2.2.1 N inputs by nitrogen fixing trees

Many common NFTs fix sufficient nitrogen to meet current and potentially increasing N

needs of woody perennial crops, including coffee (Nygren et al., 2012). Certain management

practices, such as green pruning, elevate N2 fixation levels and serve to maximize fixation rates.

Of the nitrogen that is fixed, it can make its way to the crop via a number of different pathways,

which include: decomposition and mineralization of donor organic matter (Haggar et al., 1993;

Sierra & Nygren, 2006); release and subsequent uptake of N-rich donor exudates (Paynel et al.,

2001; Jalonen et al, 2009); and transfer by common mycorrhizal networks (He et al., 2009;

Jalonen et al, 2009). For the purposes of this review, I will focus on transfer that occurs via

decomposition and mineralization.

Aboveground nitrogen transfer refers exclusively to decomposition and mineralization of

aboveground biomass of the NFT (e.g. leaf litter and branch prunings). Belowground transfer

refers to any process that occurs solely in the soil, such as nodule and root turnover. Snoeck et al

(2000) found a range of 14.3-42.3% of N transferred to coffee plants by associated shade trees

and woody cover crops at field sites in Burundi. The researchers also demonstrated that

approximately 75% of fixed N was transferred via mineralization of aboveground mulch, while

25% of N transfer occurred belowground. Within a cut-and-carry silvopastoral system, Sierra

and Nygren (2006) found that approximately one third of nitrogen in associated grass N was

derived from Gliricidia sepium, a NFT, despite the removal of its prunings and leaf litter. Kurppa

et al (2010) observed N transfer from Gliricidia sepium and Inga edulis to cacao saplings

without any litter-fall or pruning residue.

10

Pruning of shade trees within multistrata agroforestry systems is performed to limit light

and root competition between tree and crop. As a consequence of branch pruning, acropetal

movement of carbon from roots to stems results in the death of tree root tissue and nodules

(Chesney and Nygren, 2002). Total turnover of Erythrina poeppigiana nodules has been

observed due to twice-yearly complete pruning of branches (Nygren and Ramírez, 1995), as has

a decrease in over 50% root mass (Nygren and Campos, 1995; Muñoz and Beer, 2001). Partial

pruning, in which 1-2 branches are left on the tree, is a traditional practice on Costa Rican coffee

farms (Chesney and Nygren, 2002). Thus, belowground transfer of N represents an important,

yet often overlooked contribution to crop-available N, in addition to nutrients from litter-fall and

prunings.

2.2.2 Nutrient cycling by Erythrina poeppigiana

As Beer et al (1998) assert, the characteristics of nutrient cycling within a particular

agroforestry system depend upon the above and belowground biomass productivity and biomass

decomposition rate of the tree species selected. When pruned 2-3 times annually, Erythrina

poeppigiana can replenish the litter layer with quantities of nutrients, in organic form, equivalent

to those commonly applied to coffee farms through inorganic fertilizers (Beer, 1988). At the

study site of this thesis, bi-annually pruned E. poeppigiana was estimated to produce 6352 kg ha-

1 from litter-fall and 7837 kg ha-1 from prunings in one year (Haggar et al, 2011). Within the

biomass of those prunings was 236 kg ha-1 N, 20.70 kg ha-1 P, and 128 kg ha-1 K (Haggar et al,

2011). According to Beer (1988), the return of nutrients by of E. poeppigiana is estimated to

comprise 90-100% of nutrients stored in the aboveground biomass. He cites a range of 331-461,

22-35, 162-264, 243-328, and 48-76 kg ha-1 year-1 of N, P, K, Ca and Mg inputs, respectively

(dry weight) from litter under various E. poeppigiana-coffee agroforestry systems (Beer, 1988).

11

Given the disproportionately high abundance of coffee fine roots in the top 20 cm of soil under

intercropping with E. poeppigiana (Mora, 2012), significant nutrient acquisition from these

aboveground organic materials is likely substantial.

2.3 The rhizosphere in agroforestry systems

As early as 1977, researchers sought to investigate the dynamics of nutrient acquisition at

the root zone under intercropping. Nair and Rao (1977) observed enhanced microbial activity in

the rhizosphere of coconut intercropped with cacao relative to monoculture coconut. Specifically

they observed higher total bacteria, fungi, phosphorus-solubilizing bacteria, and N2-fixing

bacteria under intercropping. Additionally, there was higher organic carbon in the rhizosphere of

intercropped coconut, which the authors attributed to litter-fall contributions from cacao (Nair

and Rao, 1977). They concluded that intercropping improves microbial activity in the

rhizosphere of coconut and suggested that increased P mobilization, nitrogen fixation, and

release of growth-promoting substances by microorganisms may partially explain increased

coconut yields. Since that study, few (if any) investigations of the effects of intercropping on

rhizosphere properties in agroforestry systems have been performed. Indeed, very little

knowledge has been added to this early finding, despite its pertinence for understanding positive

effects of intercropping within agroforestry systems.

Within multistrata agroforestry systems, light alteration may modify the capacity of

shaded crop to uptake these nutrients. As Grayston et al (1996) note, photosynthetic rates

determine quantity of carbon assimilation, which in turn affect exudation. Thus, the capacity of a

crop under the shade of a NFT to meet its nutritional requirements is impacted by both the

mineralizable organic matter available through litter-fall, prunings, and root turnover, and by

shade effects on crop physiology. As the pool of literature on nutrient availability at the

12

rhizosphere is limited within agroforestry systems, in these next sections I will review the

rhizosphere effect in general and its impact on nutrients in the root zone of various tree species.

2.4 The rhizosphere

Nutrient acquisition is more than simply a function of the movement of soluble nutrients

to the root via mass flow and diffusion. In Figure 1, I illustrate the major influences of

intercropped shade trees within a coffee agroforestry system, as well as the pathways by which

the associated coffee crop acquires nutrients. Rhizosphere processes have long been known to

play an important role in nutrient cycling within both managed and natural systems. The

rhizosphere is generally defined as the region of soil influenced by the presence of plant roots

(Gobran and Clegg, 1996; Turpault et al, 2005; Richardson et al, 2009). This zone is modified by

a variety of root activities, including nutrient uptake, proton release, and exudation of carbon-

rich molecules (Grayston et al, 1996); it is the region at which the plant can exert a level of

control over nutrient availability (Rengel and Marschner, 2005). For example, plants are known

to invoke mechanisms in response to inadequate nutrient availability, including altered root and

exudation of organic compounds and protons (Rengel and Marschner, 2005). The resulting

changes in the rhizosphere drive shifts in microbial abundance and diversity which in turn

influences nutrient availability (Rengel and Marschner, 2005).

13

Figure 1. A conceptual model of nutrient

dynamics in a multistrata agroforestry system

with a nitrogen-fixing tree. The NFT fixes

atmosphere nitrogen and inputs it primarily via

leaf litter-fall and branch prunings, which

decompose and are mineralized at the soil

surface. Other nutrients are cycled from lower

soil depths by the tree and deposited in organic

form at the litter layer. The tree modifies light

levels, which in the system under study in Costa

Rica, has been shown to enhance the

photosynthetic rates of coffee. Inorganic

nutrients reach to crop roots via a combination of

mass flow and diffusion, which are driven by

transpiration and soil concentration gradients.

Roots affect nutrient availability within the

rhizosphere through the release of labile carbon

exudates, as well as H+ ions and enzymes.

Carbon-rich exudates drive microbe-mediated

mineralization of native soil organic matter in

the root zone, which can result in the release of

mineral N (and other nutrients) via microbial

turnover.

Diagram at bottom right adapted from Paterson,

2003.

14

2.5 Nutrient availability in the rhizosphere

A variety of observations have been made with respect to the rhizosphere effect on

nutrient availability in woody perennial plants. In a nutrient-poor, sandy soil, significantly higher

NH4+ concentrations and lower NO3

- concentrations were observed in rhizosphere soil of three

different tree species (Zhao et al, 2010). The authors attributed this phenomenon to enhanced

microbial immobilization and root uptake of NO3- in the rhizosphere. Turpault et al (2005), in

their study of a mature Douglas fir stand, found an accumulation of NH4+ in the rhizosphere from

0-60cm depth, but for NO3- found accumulation only below 20cm depth. A positive rhizosphere

effect on net N mineralization was observed under various tree species (red oak, yellow birch,

sugar maple) at two different experimental sites (Phillips and Fahey, 2008). Interestingly, the

effect was reduced by fertilization in some cases; this occurred to an even greater degree with

regards to phosphatase activity. It was postulated that enhanced carbon allocation belowground

by plants under nutrient limitation may serve to enhance the effect on mineral nutrient

availability in the rhizosphere.

In a Norway spruce stand in Sweden, Yanai et al (2003) found rhizosphere enrichment of

potassium (K), calcium (Ca), and magnesium (Mg), despite a model-based prediction of their

depletion. The authors cite the role of root and microbial-induced organic matter mineralization

and mineral weather as a possible explanation for the discrepancy between the observed results

and the simulation, which only considered uptake rates relative to mass flow of nutrients.

Turpault et al (2005) also observed accumulation of K, Ca, Mg, as did Wang and Zabowski

(1998) in rhizosphere soil solution of unfertilized Douglas fir seedlings at two different sites. No

rhizosphere effect on Ca, Mg, N, or P was observed at the fertilized site in the latter study, which

was attributed to a masking of rhizosphere and bulk differences by the fertilizer (Wang and

15

Zabowski, 1998). In a temporal study of exchangeable cation availability under mature Norway

spruce and beech stands, Collignon et al (2011) found rhizosphere enrichment of base cations

across all four seasons. In the acidic, nutrient-poor site, a positive correlation between carbon

content and % base saturation provided support for the role of rhizosdeposition in enhancing

nutrient availability (Collignon et al, 2011).

As for available phosphorus (P), results vary widely. Zhao et al (2010) found an

enrichment of P in the rhizosphere across all tree species, while Turpault et al (2005) observed a

strong depletion at 20-60cm depth. In the former study, significantly greater levels of acid

phosphatase activity were observed in rhizosphere versus bulk soil; in the latter, the authors

suggested high P uptake and low mobility as explanatory factors. Gobran et al (1998) found

higher rhizosphere P, and both organic and inorganic P in the unfertilized Norway spruce stand

were significantly correlated with the organic matter content in both bulk and rhizosphere soil.

Findings such as these demonstrate the capacity of living roots to alter their physico-chemical

environment so as to enhance the availability of a typically sparingly soluble element such as

phosphorus.

2.5.1 Rhizosphere effects on pH

As with mineral N, P, and base cations, various, sometimes contradictory, findings have

been made regarding the concentration gradient of H+ from rhizosphere to bulk soil. Gobran and

Clegg (1996) observed a decrease in pH from bulk to rhizosphere in the aforementioned Norway

spruce stand, though it was only statistically significant in one of three horizons. Zhao et al

(2010) also found slight acidification of the rhizosphere, though only in one species under study.

In the previously discussed Douglas fir site, Turpault et al (2005) found rhizosphere

16

acidification, but noted that opposing observations existed in others studies of the same site. The

authors proposed that rhizosphere acid-base status fluctuation is a result of temporal shifts in the

interactive influences of CO2 respiration, organic acid exudation, and ion uptake on H+

concentration (Turpault et al, 2005). In the study of Wang and Zabowski (1998), both negative

and positive H+ gradients were observed in different seasons; however, a high NH4+:NO3

-

rhizosphere ratio was consistently associated with acidification, and a low ratio with higher

rhizosphere solution pH. This observation was explained by the dynamic balance between H+

released during NH4+ uptake and OH- or HCO3

- release linked with NO3- uptake (Wang and

Zabowski, 1998).

2.5.2 Mineral N dynamics in the rhizosphere

Nitrogen uptake in the rhizosphere and movement within plant-soil systems is unique to

other nutrients, and as such, deserves brief explanation. Ammonium (NH4+) and nitrate (NO3

-)

represent the major forms of N that are taken up by plants (Jackson et al, 2008). Their

availability is governed by mineralization of organic N to ammonia and its subsequent

nitrification to NO3-, both of which are microbially-mediated processes (Richardson et al, 2009).

Both inorganic forms of nitrogen reach the root surface by a combination of mass flow (i.e.

movement in soil solution driven by transpiration) and diffusion; under low soil N conditions

root distribution and expansion play an important role in N acquisition (Yanai et al, 2003;

Richardson et al, 2009). Uptake of NH4+ results in acidification of the rhizosphere, as protons are

released to balance the charge, and NO3- uptake raises pH due to an influx of protons

(Richardson et al., 2009). Unlike phosphorus, which can be solubilized and made plant-available

directly by root exudates (Chen et al, 2002), the availability of N in natural systems and low-

external-input systems is almost entirely dependent upon microbial activity. In bulk soil,

17

populations of free-living microorganisms make organic sources of N plant-available through

mineralization and nitrification (Chapin III et al, 2002). This process is particularly important in

the rhizosphere, where C-rich exudates can support rapid cycling of organic matter and make N

available in inorganic forms (Jackson et al, 2008; Hinsinger et al, 2009).

Carbon and nitrogen cycles are closely linked, and availability of C, via exudation, root

turnover, and soil organic matter, can drive microbial processes that release soil N for plants to

use (Jackson et al., 2008). The rhizosphere is typically N-limited for microbial growth, in

contrast to C-limitation that is often pervasive in bulk soil (Hinsinger et al., 2009). Plants release

a variety of molecules through their roots; these exudates have been estimated to comprise

anywhere from 5-10% (Jackson et al., 2008) to 40% (Grayston et al, 1996) of total

photosynthetically-fixed C. As a consequence of C-rich root exudation, which represents an

easily usable energy source for microorganisms, rhizosphere microbes decompose native soil

organic matter at an accelerated rate to meet their N requirements (Rengel and Marschner, 2005;

Hinsinger et al., 2009). Inorganic N released from soil organic matter decomposition is believed

to be more easily absorbed by bacteria in the short term; however, plants have been shown to

take up the majority of N in the long term (Jackson et al., 2008). Experimentally, this has been

shown to be due to the microbial loop, a process in which initially-immobilized N is released

over time as microfauna, such as protozoa and nematodes, consume rhizosphere bacteria

(Ingham et al, 1985; Griffith, 1994; Peterson, 2003).

2.6 Ammonia oxidation

Nitrification, the conversion of ammonia to nitrate, is a critically important process

within agriculture systems. It plays a crucial role in governing the transformation of N inputs,

whether they are applied in organic or inorganic form. Ammonia oxidation, in which ammonia is

18

converted to nitrite, is the rate-limiting step of nitrification (Kowalchuk and Stephen, 2001). It is

performed by chemolitho-autotrophic ammonia-oxidizing bacteria (AOB), which have the

unique ability to rely solely on the conversion of ammonia to nitrite for their energy needs

(Kowalchuck and Stephen, 2001). For many years, it was believed that ammonia oxidation was

performed only by bacteria (Jia and Conrad, 2009). Recently, however, the existence of both

anaerobic ammonia-oxidizing bacteria (anammox) and ammonia-oxidizing archaea (AOA) has

been confirmed.

Despite the common observation of greater AOA gene abundance in soils (Leininger

et al., 2006; Chen et al., 2008; Nicol et al., 2008), Jia and Conrad (2009) recently demonstrated

that AOB dominate functionally in situ in an agricultural soil. In other words, nitrate production

was better explained by bacterial rather than archaeal nitrification (Jia and Conrad, 2009). The

authors point out that while AOA do not necessarily use ammonia-oxidation as a sole energy

source, as AOB do, which may account for observed discrepancies between AOA gene

abundance and relative functional importance in soil nitrification (Jia and Conrad, 2009).

Regardless, for the purposes of this thesis, only AOB will be considered.

Ammonia-oxidizing bacteria are encompassed within two monophyletic lineages: the

beta-proteobacteria, which include Nitrosomonas and Nitrospira genera, and the

gammaproteobacteria, which contains the Nitrosococcus genus (Rotthauwe et al, 1997; Junier et

al, 2010). The ecological and physiological characteristics of these bacteria have traditionally

been difficult to understand due to challenges in culturing; this has changed in recent years,

however, with the application of molecular techniques (Okano et al, 2004). Early polymerase

chain reaction (PCR) primers targeted the 16s rRNA gene to identify AOB, though it was soon

discovered that they did not always accurately reflect physiological function (Junier et al, 2010).

19

Functional marker genes that code for essential enzymes involved in ammonia oxidation have

been used with greater efficacy. One of the most commonly used functional markers is amoA, a

gene that encodes the alpha-subunit of ammonia monooxygenase (AMO), a critical enzyme

required for ammonia oxidation (Rotthauwe et al, 1997). Various primer sets have been

developed that target the amoA gene with varying degrees of specificity (Junier et al, 2010).

Several studies have used amoA as a functional biomarker to gain insights as to the

relationships between AOB and mineral N pools within agricultural systems. At two separate

depth categories, Jia and Conrad (2009) observed increases in bacterial copy number for the

amoA gene only in soil samples in which nitrate concentrations increased. A clear, positive effect

of ammonium fertilizer application was observed on amoA abundance, and NO3- concentration

was positively correlated with amoA abundance over nearly all time points (Jia and Conrad,

2009). Okano et al (2004) used real time PCR as well and found amoA gene abundance to be

consistently positively correlated with a decrease in ammonia and rise in nitrate, the by-product

of ammonia oxidation. These results demonstrate the applicability of using the amoA gene in

understanding bacterial-driven transformations within soil environments, and ultimately for

relating root-induced effects to microbial activity in the rhizosphere.

20

Chapter 3 Costa Rica’s Coffee Sector: Past and Present

3.1 Introduction

Coffee has provided livelihoods for rural Costa Ricans for over one hundred and fifty

years. Known as el grano de oro (“the golden bean”), its cultivation has sustained communities

comprised primarily of smallholders. In the 1950s, the state used research, extension, and

economic policies to stimulate widespread planting of new, higher-yielding varieties and the

adoption of fertilizers and agrochemicals. This approach resulted in a drastic increase in

productivity that made Cost Rica the Latin American leader in modern coffee production. While

the benefits of this process were felt unevenly within the coffee economy, the position of

smallholder coffee farmers in Costa Rica has historically been enviable relative to other

countries. With the failure of the managed international coffee market in 1989 and the concurrent

spread of neoliberal, free trade oriented development policy, the position of the small-scale

coffee producer has changed drastically. Most have been forced to reduce costly fertilizer and

agrochemical inputs and reduce upkeep; some have been able to access niche markets for

environmentally friendly and socially just coffee; others, after waiting patiently for years for

prices to rebound, have left the business altogether.

In this chapter, I will provide a brief historical background on the role of the state in the

coffee sector and examine the influence of public agricultural research in Costa Rica’s

development throughout the post-war era. Specifically, I will investigate the potential for public

agricultural research institutions to seek out and extend viable alternatives to small-scale coffee

producers in the wake of the coffee crisis. I will discuss both the obstacles to such action within

the context of globally-dominant neoliberal economic policy. As a social democracy with a

21

history of successful public institutions (Haglund, 2006) and relatively egalitarian distribution of

land and resources, Costa Rica provides a prime example of the tension between social

democracy and neoliberal ideology as it relates to the state’s relationship with petty commodity

producers.

Central to this investigation is reconciling production-oriented agricultural research of the

past sixty years with the complex and nuanced objectives of addressing ecological and socio-

economic sustainability today. Environmental degradation, high input costs, and economic

vulnerability associated with modernized production have necessitated the discovery and

implementation of new research directions, especially to address the needs of small-scale

farmers. A multidisciplinary approach is required that considers the political, economic and

social factors that have contributed to the current position of the Costa Rican coffee farmer. I use

the International Assessment of Agricultural Knowledge, Science, and Technology for

Development (IAASTD) as a framework by which to define sustainable development in the

Costa Rica’s coffee sector. I discuss the role of the Centro Agronómico Tropical de

Investigación y Enseñanza (CATIE), the Costa Rican-based inter-governmental research

institution with whom this thesis research was conducted, to highlight opportunities and

challenges for agricultural research in the contemporary coffee economy.

3.2 Smallholder coffee producers in Costa Rica

Coffee was originally introduced to Costa Rica in 1806 and initial adoption of the crop by

the colony’s primarily peasant population was slow (Seligson, 1980). By the end of the 19th

century, however, Costa Rica was exporting over 20 million tonnes annually (Winson, 1989). By

the early-mid 20th century, significant socio-economic differentiation had occurred within the

22

coffee economy, with the emergence of a distinct set of classes: the processor oligopoly; the

wealthy but non-processor producers; smallholders and; semi-proletarian and fully proletarian

households dependent upon wage labour in haciendas (Gudmundson, 1995).

Of all other major agricultural export activities in Latin America post mid-19th century,

coffee was the most amenable to small-scale cultivation (Gudmundson, 1995). This has been

attributed to the fact that, unlike sugar for example, growing coffee profitably did not necessarily

require large production units, farm sizes, or intensive investment in mechanization

(Gudmundson, 1995). Additionally, labour demand was high only during harvest (typically

November and December), during which time immediate and extended family labour could be

used (Gudmundson, 1995; Sick, 1997). Indeed, in Costa Rica the numerical importance of

smallholders is evident from property registries throughout the 19th century, as well as the Coffee

Census of 1935 (Gudmundson, 1995; Winson, 1989). By the early-mid 1900s, however,

increasing concentration of land ownership and division of smallholdings, as well as out-

migration contributed to the precarious position of the smallholder (Gudmundson, 1995). Despite

the numerical predominance of smallholder coffee farmers, in socio-economic and political

terms they have historically been subordinated by the elite classes (Winson 1989).

3.3 The role of state agricultural research institutions in promoting the modernization of

the coffee sector

In the wake of successful coup in 1948, state intervention became the driving force

behind an economic development model intimately linked with social reform (Winson 1989).

Intervention within the coffee sector was comprehensive, and central to it was technology

transfer and agricultural extension used to modernize coffee production. The government argued

that taxes were needed to finance programmes to stimulate rural development and raise

23

productivity in the agrarian sector. In 1952 legislation was passed that provided government a

percentage of revenues from coffee processors (Winson, 1989). This, among other forms of

taxes, resulted in a more than six-fold increase in government revenue by 1954 as compared to

1938 (Winson, 1989). These funds provided the state with essential resources with which to

intervene economically and to fund agricultural research and extension aimed at modernizing the

coffee sector.

In 1950, coffee yields in Costa Rica were among the lowest in Latin America (Winson,

1989). Cultivation practices were seen as backward and exploitive of soil resources and

production increases were limited by land availability and labour costs (Winson, 1989). For

large, capitalist farms, high labour costs made expansion unprofitable, and small-scale farmers

struggled to sustain their families without supplementary income from wage labour on capitalist

farms (Gudmundson, 1995; Winson, 1989). The approach of the government, newly endowed

with tax-derived resources, was to facilitate increased per-area productivity (Winson, 1989). The

original policy objective was to include all farmers in the process, including those unable to

finance the necessary measures for modernization (Winson, 1989). However, as Winson (1989)

argues, the roots of the inequalities between coffee producers were never fully confronted by the

government.

State-led efforts to modernize the coffee sector were extremely successful in terms of

productivity increases. Costa Rica saw a total production increase of three hundred percent from

1950 to 1973, with an increase in land cultivation of only sixty percent (Winson, 1989). Into the

1980s, Costa Rica had among the highest productivity per hectare in the world (Samper, 2010).

Modernized production was based upon new, higher yielding hybrid varieties, the abandonment

24

or reduction of shade tree intercropping, and intensive use of fertilizers and agro-chemicals

(Perfecto et al, 1996; Winson, 1989). The government subsidized the importation of fertilizers

(Winson, 1989) and established long-term credit programmes through the National Bank that

provided loans for producers to invest in re-planting with new varieties. While such economic

instruments played a critical role in modernization, state agricultural research institutions

established the foundation for change.

During the post-1948 period of modernization in Costa Rica, development of the planting

techniques and technological inputs of intensive coffee cultivation was driven by state

institutions, namely the Coffee Office, the Ministry of Agriculture and Livestock, and the Centre

for Investigations in Coffee (CICAFE) (now ICAFE), which operated research stations in a

variety of different ecological zones (Winson, 1989). These state institutions undertook:

cultivation of new hybrid varieties in order to increase yields, increase disease resistance and

improve structure for mechanized harvesting; fertilizer application experimentation; propagation

of high yielding varieties for distribution; and, assessment of new, intensive planting and pruning

protocols (Winson, 1989). Similar research was performed on a variety of crops throughout Latin

America, as public institutions became the drivers of agricultural modernization during this

period (Kaimowitz, 1993). The goal of increased productivity was paramount – for coffee in

Costa Rica, and in general across Latin America (IAASTD, 2008). [See the entry for IAASTD

under references.] Public extension agents played a key role in the transfer of state-led research

and innovation to producers; they provided the essential link between research and adoption of

new knowledge and technology.

25

3.4 The impact of modernization on Costa Rican smallholders

While small and medium scale coffee farmers have enjoyed relative prosperity within

Costa Rica’s modernized coffee economy Sick (1997; 2008), inequalities have arisen – and been

reinforced – by the agrarian development process in Costa Rica. Flaws in the production model

have become more evident in recent years, with increased economic and ecological vulnerability,

particularly for smallholders.

The shift to reduced-shade, chemical-intensive production has resulted in deforestation,

soil erosion, watershed pollution and loss of biodiversity throughout coffee-growing regions

(Borkhataria et al, 2012; Haggar et al, 2011; Perfecto et al, 1996). Furthermore, removal of shade

trees from production systems hampers important ecosystem functions, which threatens long-

term agroecosystem sustainability and entrenches dependence upon external inputs.

Alternatively, high-diversity shade coffee production systems have been noted to support high

levels of biodiversity (Perfecto et al, 1996). Relative to other Central American countries, Costa

Rica has a relatively high proportion of land under modernized cultivation (Perfecto et al, 1996).

It is the smallholders of Costa Rica, for whom fully “modernized” technology was either not

accessible or appropriate, who have maintained less technologically-intensive production

systems that have helped maintain forest habitat and biodiversity. As Costa Rica has shifted

away from economic dependence on agro-exports and more towards eco-tourism, it could be

argued that this activity has been economically beneficial. Unfortunately, it is also this group that

has struggled the most in recent years to maintain livelihoods in coffee farming (Sick, 2008).

With the collapse of the managed international coffee market in 1989, in addition to

accelerated production in Vietnam and Brazil and stagnant demand in Western markets, the

26

coffee crisis occurred (Petchers and Harris, 2008). Throughout the subsequent years, which have

seen volatile and supressed coffee prices, production costs have risen. Due to pressure from the

International Monetary Fund, Costa Rica devalued the colón in 1990, which resulted in higher

fertilizer and agro-chemical costs for producers (Sick, 1997). Though coffee no longer represents

Costa Rica’s primary agricultural export, as of 2008 it remained the primary crop for over 78,000

small-scale farmers in the country’s highlands (Sick, 2008). Such farmers have been placed in a

precarious position. They are highly vulnerable to large drops in price, especially given the at

least partial dependence of many on purchased fertilizer and agrochemical inputs.

One of the earliest responses of farmers to the coffee crisis was to cut back on fertilizers

and agrochemicals (Sick, 1997). Longer-term approaches have included conversion to low

external input farming systems, gaining certification for already-existent intercropped shade trees

and ecologically-sound management practices, re-incorporation of tree crops, and diversification

with other cash and/or subsistence crops (Samper, 2010). Such trends present opportunities for

the protection of biodiversity, improved watershed health, and reforestation (Perfecto et al,

1996), as well as the potential for ecologically and economically sustainable coffee production

for smallholders.

3.5 Conclusions

For over one hundred and fifty years, Costa Rican coffee smallholders have been in the

tenuous position of participating in the international commodity market. Despite market

fluctuations and domestic power imbalances within the sector, coffee has provided livelihoods

for generations of small-scale farmers. Since the coffee crisis, the viability of those livelihoods

27

has been severely compromised. At this same time, the environmental consequences of

modernized coffee production are coming to light.

In the early years of Costa Rica’s social democracy, with hard-fought political, economic,

and social reform, the state established an active role in enhancing the coffee sector. While the

benefits of state-led modernization were not distributed entirely equally, there is no doubt of the

end result: Costa Rica became one of the most productive per-area coffee nations in the world.

Now that domestic and global economic and environmental conditions have changed, the

challenges facing the small-scale coffee producer are complex, and require a flexible range of

solutions. These solutions are dependent upon a foundation of agricultural knowledge and

technology – generated by public institutions for the public good – that will enable farmers to

adapt in ways that are both ecologically and economically sustainable.

The scientific research within this thesis aims to contribute to such a foundation.

Additionally, it is my hope that this chapter has made evident the importance of partnerships

between Canadian universities and public research institutions in the developing world towards

fostering more sustainable agricultural systems.

28

Chapter 4 Site Description and Methodology

4.1 Site Description

The study was performed at an experimental coffee farm managed by the Centro

Agronómico Tropical de Investigación y Enseñanza (CATIE), located in Turrialba, Costa Rica.

The site is situated in a low altitude (685m above sea level), wet (3,200 mm annual rainfall

annually) coffee zone that lacks a distinct dry season (Haggar et al, 2011). The soil on site is

classified as both Typic Endoaquept and Typic Endoaquult, and is characterized as mixed

alluvial with poor-medium fertility; prior to 2000, it was in sugar cane production (Mora and

Beer, 2012). Coffee (Coffea arabica L. var. Caturra) was planted originally at a density of 8,000

plants per hectare. At the time of sampling (June 2012), coffee plants within the same row were

planted 1 m apart and rows were separated by a distance of 2 m (Figure 1). For those treatment

plots that included E. poeppigiana, trees were spaced every 12 m within a row and 8 m between

rows, which formed a 12 x 8 m repeating rectangular structural pattern. Additionally, a severely

coppiced E. poeppigiana existed in the middle of each 12 x 8 m rectangle (Figure 1). This is a

modification of the original 4 x 6 m tree spacing pattern that was reduced in 2007 in order to

manage shade levels (personal communication with Farm Manager).

Coffee bushes are stump pruned, typically every 3-5 years, based upon their productive

potential for following harvest (Haggar et al, 2011; pers. comm. with Farm Manager). Under all

sub-plot treatments except intensive conventional, pruning of E. poeppigiana is performed

biannually, leaving a minimum of three branches. All pruned material (branches and leaves) is

left to decompose on-site.

29

At this site, the whole plot treatment is shade level, comprised of full sun (coffee

monoculture) and shade of a number of timber and N2-fixing shade trees, intercropped singly and

in combination with one another. Additionally, there are four sub-treatments, which are based on

varying degrees of nutrient inputs and pest management, two of which (medium conventional

and intensive organic) are described in Table 1. Three replicates were established to form a

randomized block design. For the purpose of this study, sampling was performed only from

coffee grown in monoculture (full sun) and coffee grown under the shade of Erythrina

poeppigiana (Walp.) O.F. Cook, a compact N2-fixing shade tree commonly used within Costa

Rican coffee systems. Under the former, samples were collected only from the moderate

conventional sub-plot treatment; under the latter, samples were collected from both moderate

conventional and intensive organic sub-plot treatments.

30

Table 1. Fertilization and pest/weed control protocols at the experimental coffee farm of the

Centro Agronómico Tropical de Investigación y Enseñanza (CATIE)

Management Subplot Treatment

Medium conventional Intensive organic aSoil amendments

bAnnual inputs

Nitrogen (N)

Phosphorus (P)

Potassium (K)

200 kg ha-1 year-1 18–15–6–2

(N, P, K, Mg and B)

22.5 kg ha-1 year-1 NH4NO3

Foliar application: B, Zn

(once a year)

150 kg ha-1

10 kg ha-1

75 kg ha-1

20 tons ha-1 year-1 coffee pulp

7.5 tons ha-1 year-1 chicken manure

200 kg Kmag ha-1 year-1

200 kg phosphoric rock ha-1 year-1

287 kg ha-1

205 kg ha-1

326 kg ha-1

Disease control

Fungicide (2.4g L-1) Atemi or

copper sulfate (CuSO4), once

per year

No fungicide application

Weed control Regular mechanical removal

of weeds with string trimmer.

Herbicide application within

coffee rows (Round-up®

(10ml L-1))

No herbicide application. Mechanical

removal of weeds as required by string

trimmer

aAcquired from Mora and Beer, 2012. bDo not include nutrients recycled by E. poeppigiana or N inputted by nitrogen fixation

31

4.2 Sample selection

Three coffee plants were selected within in each subplot from 3 different trees, for a total

of 9 plants per subplot (Figure 2): 9 under full sun with moderate conventional fertilization,

henceforth referred to as full sun-conventional (FS-C); 9 under E. poeppigiana with moderate

conventional fertilization, henceforth shade-conventional (S-C); and 9 under E. poeppigiana with

intensive organic fertilization, henceforth shade-organic (S-O). Shade trees were selected on the

basis of being a main Erythrina tree (see Figure 2 and 3) of average height and canopy size.

Coffee plants were selected based on the following criteria: minimum of 3 years since last stump

pruning, within 3m of E. poeppigiana trunk (Figure 2), directly under the tree’s canopy, and

deemed to represent average height and health for the subplot. Under FS-C, plants were selected

by using the above criteria and super-imposing the 12 x 8 m repeating pattern of the E.

poeppigiana (Figure 2). As no intensive organic treatment exists for full sun coffee due to

difficultly in establishing and maintaining monoculture coffee organically, it was not included.

Sampling was typically performed between the hours of 8am and 12pm in the month of June,

just prior to pruning of all Erythrina trees.

32

Figure 2. Map of CATIE experimental coffee farm with delineation of sub-plots sampled as part

of study. Structural pattern of coffee grown in E. poeppigiana shade plots shown, along with

example of sampling within a single subplot.

33

Figure 3. Coffee growing under E. poeppigiana shade (Block 3, Intensive Organic subplot, June

2012). Stump-coppiced tree in centre of picture; full-size Erythrina trees in a row on right side of

picture.

34

4.3 Sampling protocol

After surface litter and detritus was cleared, 4 soil cores (8 cm diameter, 20 cm depth;

1000.7 cm3) were taken at 0-20 cm and 20-40 cm (block 2 only) depths at 25 cm from the base

of the each selected coffee plant. They were pooled to give one composite sample per plant, per

depth. From the pooled soil cores, rhizosphere soil was obtained from soil (less than 1 cm in

diameter) that adhered to coffee fine roots (<2 mm) after consistent gentle shaking. This was

performed on all fine roots present from all 4 cores except for very small fragments. Soils were

placed in thin, breathable plastic bags and placed in shade until further subsampling. Bulk

samples were obtained from pooled soil that was mixed thoroughly after rhizosphere soil and

fine root removal, and quartered on-site to a final wet mass of 100-300g. Nine rhizosphere soil, 9

bulk soil, and 9 fine root samples were obtained per shade-fertilization treatment (0-20 cm) and 3

samples each for rhizosphere soil, bulk soil, and fine roots per shade-fertilization treatment (20-

40 cm).

4.4 Soil nutrient analysis

Rhizosphere and bulk soils were placed in open containers and left to air-dry for 2-4

weeks, after which they were ground with a mortar and pestle and sieved to <2 mm. All analysis

was conducted simultaneously on bulk and rhizosphere soils. Air-dried soils were extracted for

orthophosphate with Bray’s 1 (1.5 g: 15 mL), shaken at high speed for 5 minutes, and filtered

through #1 Whatman filter paper. Nitrates and ammonium were extracted using 2M KCl (2.0 g:

20 mL; 1 g: 10 mL for 20-40cm samples due to limited sample mass), shaken for 30 minutes,

and filtered through #1 Whatman filter paper. Quantification was determined colourimetrically,

35

using flow injection analysis (Lachat QuikChem). Soil pH was measured in a 1: 5 soil to water

solution with a pH meter (Mettler Toledo FiveEasy pH meter, Mississauga, Ontario).

Magnesium, calcium, and potassium were extracted simultaneously with ammonium

acetate at pH 7 (2 g: 20 mL; 1 g: 10 mL for 20-40cm samples). All extracts were shaken for 15

minutes, filtered through #1 Whatman filter paper, and quantified against certified elemental

standards using an atomic absorption spectrophotometer (Perkin Elmer AAnalyst 200).

Total N and C were determined using an Elemental Analyzer (Thermo Flash 2000,

Thermo Scientific, MA, USA). Samples were weighed to the thousandth of a milligram,

combusted at 1800 °C, and values were determined against a known standard (ascorbic acid). A

standard reference was placed at intervals of every 15 samples to provide a check for the

accuracy of readings.

4.5 Soil microbial analysis

Subsampling of soils for DNA extraction was performed within 2-6 hours of collection.

For rhizosphere soils, a subsample of approximately 0.5 g was obtained from soil within storage

bag that had fallen off of the roots. This soil was placed in a Ziploc bag and into a freezer (-

20°C) within 30 minutes. For bulk soils, the quartered subsample from the field was spread out

to a depth of 1 inch and 10-12 portions were randomly selected to a total mass of approximately

2g. This soil was placed in a Ziploc bag and into a freezer (-20°C) within 30 minutes.

Total community DNA was extracted using PowerSoil DNA Isolation Kit (MoBio

Laboratories, Carlsbad, CA, USA) within 2-4 weeks of freezing. Instructions were followed

according manufacturer’s protocol, with the exception that isolated DNA was eluted with 200

µL, not 100 µL, in the final step. Prior to the extraction procedure, fine root tissue was removed

from the sample with the use of ethanol-sterilized tweezers.

36

4.5.1 Denaturing Gradient Gel Electrophoresis

Polymerase chain reactions (20 uL) were performed on soil DNA extracts using the

universal bacterial primer set of 341F (GC) and 907R (both at 10 µM). The GC represents the

GC clamp present in the 5’ end of the 341F primer, and has the following sequence: 5’-

CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGG -3’. It is added to prevent

the complete dissociation of the two DNA strands and allows for improved detection of variants

in the sequence (Muyzer & Smalla, 1998). The PCR reactions were carried out in a PTC-100

thermal cycler (MJ Research Inc., St. Bruno, QC, Canada) under the following conditions: initial

denaturing at 95˚C for 5 minutes followed by 35 cycles of: denaturing at 95˚C for 1 min.,

annealing at 56˚C for 1 min. and extension at 72˚C for 1 min.; final extension at 72˚C for 10

minutes. A portion of the product (4 uL) was visualized on a 1% agarose gel to confirm

amplification and the remainder was run in a pre-prepared denaturing gradient gel. The 6%

polyacrylamide gel had a gradient of 40-70% denaturing solution and was run in a DGGE-2001

Tank (C.B.S. Scientific Co, Del Mar, CA, USA) in 0.5 X Tris-acetate-EDTA buffer for 20 hours

at 70V and 58˚C. The gel was stained with 15 uL of 0.5 mg mL-1 of ethidium bromide stain in

300 mL of 0.5X TBE buffer for 30 minutes before being visualized in a UV-light box. Images

were captured using a digital camera, saved, and uploaded to GelCompar II software (Applied

Maths, Austin, TX, USA).

4.5.2 Real-time PCR assays

Real-time quantitative PCR was performed using SYBR green chemistry (Kapa

Biosystems, Woburn, MA, USA). Each assay was conducted on a 96-well plate with 3 replicates

for each standard and sample. DNA was pooled by block for each soil fraction (rhizosphere and

37

bulk) within each management treatment, with an equal quantity of DNA contributed from each

sample (i.e. n=9 for each treatment became n=3). All pooled DNA samples were diluted to 3

ng/µL. Amplification was performed in 20 µL reaction volumes (10.0 µL SYBR Green PCR

Master Mix, 8.2 µL water, 0.4 µL forward primer, 0.4 µL reverse primer, 1.0 µL template DNA).

PCR conditions were 10 min at 95 ºC, followed by 45 cycles of 95 ºC for 30s, 45s at 58 ºC, and

72 ºC for 30s, followed by a dissociation curve stage of 15 s at 95 ºC, 30 s at 60 ºC and 15 s at 95

ºC. The 7300 Real-time PCR system (Applied Biosystems, CA, USA) was used with a threshold

level of Delta Rn = 0.2. Amplicon specificity was confirmed by dissociation curve characteristics

and by performing gel electrophoresis on a 1% agarose gel.

A relative standard curve method was used to perform relative quantification of samples.

The universal bacterial primer pair 341F (no GC clamp) and 907R was used as an endogenous

control for which cycle number at threshold (CT) values of the target gene (amoA) was

normalized against. The primers amoA-1F (5’-GGGGTTTCTACTGGTGGT - 3’) and amoA-2R

(5’- CCCCTCKGSAAAGCCTTCTTC - 3’), which amplify a region of the ammonia oxygenase

gene in ammonia-oxidizing bacteria, were used (Rotthauwe et al, 1997). An environmental soil

sample known to be positive for amoA was diluted and used as a standard. Two-fold dilutions

from 1x to 0.010x (16s) and 1x to 0.050x (amoA) concentrations of amoA-positive control were

used to create 5 and 4-point standard curves, respectively. All sample CT values for both 16s and

amoA amplifications fell within the range of the standard curves.

Triplicate results of real-time PCR CT values were averaged. Standard error of triplicate

CT values was calculated for each sample, and those that had a SE greater than 0.5 were re-

assayed. Relative gene abundance of amoA was determined by comparing average CT value of

the sample against a linear regression of the standard CT as a function of dilution factor. Values

38

for amoA were normalized by dividing each sample’s quantity of template amoA DNA (as

calculated from the standard curve) by the standard curve-derived value of its endogenous

control (16s).

4.6 Statistical analyses

Paired t-tests were used to assess mean difference between rhizosphere and bulk soil for

all nutrients within treatments. Two-sample t-tests were used to assess differences in the

magnitude of rhizosphere effect ([(Rhizosphere-Bulk)/Bulk]*100%) between treatments.

Comparisons were made between two shade levels with fertility held constant (FS-C to S-C) and

between two fertility levels with shade held constant (S-C to S-O). Correlations were performed

between soil chemical parameters and between chemical parameters and amoA abundance, both

within individual soil fractions and with rhizosphere and bulk soil pooled.

Denaturing gradient gel electrophoresis profiles were analyzed by cluster analysis.

Curve-based clustering was performed using the Pearson correlation coefficient and similarities

displayed as a dendrogram. The unweighted pair group with mathematical averages (UPGMA)

method was used to calculate the dendrogram. Analyses were performed using Gel Compar II

software (Applied Maths, Austin, TX, USA).

Normality of residuals was tested using the Shapiro-Wilk test. Data was log-transformed

to correct for non-normality. The Lund's Critical Value was compared with the highest absolute

value of the data set to test for outliers; any outliers found were removed. All statistical analyses

were performed using SAS version 9.2 (SAS Institute Inc. Cary, NC, USA). A type I error rate

was set at 0.05 for all statistical tests.

39

Chapter 5 Results

5.1 Bulk soil chemical characteristics

Soils fertilized conventionally under shade had lower pH, lower available P, and higher

nitrate and exchangeable potassium at 0-20cm (Table 2). Soil in shade-tree plots under organic

management had much higher pH, approximately ten-fold greater available P, and more

exchangeable calcium and magnesium than conventionally-fertilized shade plots at 0-20cm

(Table 2).

5.2 Rhizosphere effects on nutrient properties

In general, soil nutrients were present in greater quantities in rhizosphere soil compared

to bulk soil. Rhizosphere soil of coffee under all management treatments had higher total N (P =

0.005), total C (P = 0.003), NO3- (P <0.0001), NH4

+ (P <0.0001), available P (P <0.0001), Ca2+

(P = 0.0006), Mg2+ (P <0.0001), and K+ (P = 0.005) concentrations than bulk soil under all

management treatments at 0-20cm soil depth (Table 3). There was no significant difference,

however, between pH of rhizosphere and bulk soil at 0-20cm. Deeper in the soil profile, at 20-

40cm soil depth, total N (P = 0.031), NO3- (P = 0.014), NH4

+ (P <0.0001), and exchangeable

Mg2+ (P = 0.006) and K+ (P = 0.04) were significantly greater in the rhizosphere soil fraction

(Table 3). There were no significant differences between rhizosphere and bulk soil at 20-40cm

for exchangeable Ca2+ or available P. Relative amoA abundance did not differ significantly

between rhizosphere and bulk soil at either soil depth.

40

Table 2. Soil pH, NO3-, NH4

+, available P, and exchangeable Ca2+, Mg2+, and K+ concentrations

in bulk soil under full sun management with conventional fertilization (FS-C), shade with

conventional fertilization (S-C), and shade with organic fertilization (S-O) at 0-20cm.

Treatment pH NO3

-

(mg kg-1)

NH4+

(mg kg-1)

PO43-

(mg kg-1)

Ca2+

(cmol+ kg-1)

Mg2+

(cmol+ kg-1)

K+

(cmol+ kg-1)

FS-C 5.12 ± 0.21 0.76 ± 0.10 1.63 ± 0.16 3.82 ± 0.21 0.315 ± 0.034 0.154 ± 0.008 0.077 ± 0.008

S-C 4.88 ± 0.16 1.37 ± 0.22 1.18 ± 0.18 2.57 ± 0.25 0.297 ± 0.041 0.135 ± 0.013 0.270 ± 0.061

T-test * * * *

S-C 4.88 ± 0.16 1.37 ± 0.22 1.18 ± 0.18 2.57 ± 0.25 0.297 ± 0.041 0.135 ± 0.013 0.270 ± 0.061

S-O 7.14 ± 0.04 1.19 ± 0.17 1.22 ± 0.07 23.40 ± 1.94 1.651 ± 0.072 0.393 ± 0.010 0.262 ± 0.044

T-test ** ** ** **

* Denotes significant difference between bulk and rhizosphere soils at P<0.05

** Denotes significant difference between bulk and rhizosphere soils at P<0.01

41

Table 3. Soil chemical and biological properties of rhizosphere and bulk soil of coffee under all

treatments (pooled) at 0-20cm and 20-40cm soil depths. Values are mean ± SE and sample size

refers to number of samples within a soil fraction (rhizosphere or bulk) at a given soil depth.

Parameter Sample

size

0-20cm soil depth Sample

size

20-40cm soil depth

Rhizosphere Bulk Rhizosphere Bulk

% N α5 a0.58 ± 0.07 b0.36 ± 0.04 β6 a0.29 ± 0.04 b0.20 ± 0.01

% C 5 a5.59 ± 0.67 b3.45 ± 0.36 - - -

pH 27 a5.66 ± 0.21 a5.71 ± 0.20 - - -

NO3-

(mg kg-1) 27 a2.29 ± 0.30 b1.11 ± 0.11 9 a4.23 ± 1.20 b0.536 ± 0.087

NH4

+

(mg kg-1) 27 a3.26 ± 0.26 b1.34 ± 0.09 9 a4.91 ± 0.51 b1.21 ± 0.15

PO4

3-

(mg kg-1) 27 a17.76 ± 3.53 b9.93 ± 1.97 9 a2.68 ± 1.09 a3.63 ± 0.79

Ca2+

(cmol+ kg-1) 27 a0.957 ± 0.174 b0.754 ± 0.128 9 a0.577 ± 0.089 a0.577 ± 0.085

Mg2+

(cmol+ kg-1) 27 a0.380 ± 0.039 b0.228 ± 0.024 9 a0.203 ± 0.013 b0.156 ± 0.011

K+

(cmol+ kg-1) 27 *a0.287 ± 0.040 *b0.203 ± 0.030 9 a0.138 ± 0.018 b0.096 ± 0.013

Relative

amoA

abundance

9

a0.482 ± 0.048

a0.425 ± 0.032

3

a0.318 ± 0.027

a0.287 ± 0.052

a Different letters between rhizosphere and bulk soil per depth represent significant difference at

P < 0.05 (Paired t-test) α Includes 2 rhizosphere-bulk paired samples full sun coffee with conventional fertilization, 1

from shaded coffee with conventional fertilization, and 2 from shaded coffee with organic

fertilization β Only includes samples from shade and full sun coffee with conventional fertilization

42

5.2.1 Rhizosphere effects on nutrient properties within management treatments

Concentrations of soil NO3- within each of the three management treatments was

significantly greater (FS-C: P = 0.009; S-C: P = 0.0001; S-O: P = 0.013) in rhizosphere

compared to bulk soil at 0-20cm soil depth (Figure 4a). Soil NH4+ within each of the three

management treatments was also significantly greater (FS-C: P <0.0001; S-C: P = 0.0002; S-O:

P <0.0001) in rhizosphere soil (Figure 4a). Similarly, at 0-20cm there was a significant

accumulation (FS-C: P =0.024; S-C: P = 0.0004; S-O: P <0.0001) of available P in rhizosphere

soil within each management treatment (Figure 4a). At 20-40cm soil depth, a similar trend was

observed under all treatments (Figure 4b), though significant differences for NO3- existed

exclusively for coffee under shade with conventional fertilization (P = 0.005) and in

conventionally fertilized plots (FS-C: P = 0.017; S-C: P = 0.02) for NH4+. Available P in bulk

soil, however, was greater than rhizosphere P, though only significantly so for coffee grown

under full sun with conventional fertilization (P = 0.014) (Figure 4b).

Differences between rhizosphere and bulk soil in pH were not observed at 0-20cm except

under FS-C management, in which rhizosphere soil had a significantly lower (P = 0.0012) pH

(Table 4). Rhizosphere exchangeable magnesium was significantly greater (FS-C: P = 0.0006; S-

C: P <0.0001; S-O: P <0.0001) under all treatments at 0-20cm than bulk soil and under FS-C (P

= 0.044) at 20-40cm (Table 4). Despite consistent indications of enhanced exchangeable

potassium in the rhizosphere across treatments and depth categories, the only significant

accumulation of K+ in the rhizosphere was only observed under FS-C management at 0-20cm (P

= 0.0002) (Table 4).

43

Figure 4. Mean NO3-, NH4

+, and available P concentrations in bulk and rhizosphere soil of coffee

under all three management treatments (FS = full sun; S = shade; C = conventional fertilization;

O = organic fertilization) at (a) 0-20cm depth and (b) 20-40cm depth. Significant differences

between rhizosphere and bulk soils within management treatments are indicated by different

letters (paired t-test, P <0.05). Bars represent ± SE; n=9 per soil fraction for 0-20cm; n=3 per soil

fraction for 20-40cm.

a

aa

b

bb

0

1

2

3

4

5

6

7

FS-C S-C S-O

NO

3-(m

g kg

-1)

a

a

a

a

bb b

0

1

2

3

4

5

6

7

FS-C S-C S-O

NH

4+(m

g kg

-1)

a a

a

bb

b

0

5

10

15

20

25

30

35

40

45

FS-C S-C S-O

Ava

ilab

le P

(m

g kg

-1)

a

a

a

a b a

0

1

2

3

4

5

6

7

FS-C S-C S-O

NO

3-(m

g kg

-1)

ba

a

a

b

b a

0

1

2

3

4

5

6

7

FS-C S-C S-O

NH

4+(m

g kg

-1)

a a

a

ab

a

0

5

10

15

20

25

30

35

40

45

FS-C S-C S-O

Ava

ilab

le P

(m

g kg

-1)

44

Table 4. Soil pH and exchangeable base cation concentrations (mean ± SE) in bulk and

rhizosphere soil at 0-20cm (n=9 per management treatment, per soil fraction) and 20-40cm depth

(n=3 per management treatment, per soil fraction).

Depth Management

treatment Soil fraction pH Ca2+ (cmol+ kg-1) Mg2+ (cmol+ kg-1) K+ (cmol+ kg-1)

0-20 cm FS-C Bulk 5.12 ± 0.07 0.315 ± 0.034 0.154 ± 0.008 0.077 ± 0.008

Rhizosphere 4.98 ± 0.08 0.317 ± 0.058 0.238 ± 0.021 0.131 ± 0.013

Paired t-test * * *

S-C Bulk 4.88 ± 0.05 0.297 ± 0.041 0.135 ± 0.013 0.270 ± 0.060

Rhizosphere 4.85 ± 0.06 0.381 ± 0.041 0.258 ± 0.019 0.377 ± 0.096

Paired t-test *

S-O Bulk 7.14 ± 0.04 1.65 ± 0.07 0.393 ± 0.010 0.262 ± 0.044

Rhizosphere 7.13 ± 0.06 2.17 ± 0.11 0.647 ± 0.020 0.350 ± 0.044

Paired t-test ** **

20-40 cm FS-C Bulk - 0.483 ± 0.069 0.123 ± 0.016 0.098 ± 0.037

Rhizosphere - 0.470 ± 0.086 0.181 ± 0.029 0.108 ± 0.020

Paired t-test *

S-C Bulk - 0.352 ± 0.019 0.168 ± 0.009 0.071 ± 0.008

Rhizosphere - 0.371 ± 0.030 0.201 ± 0.015 0.127 ± 0.015

Paired t-test

S-O Bulk - 0.892 ± 0.043 0.178 ± 0.012 0.114 ± 0.012

Rhizosphere - 0.888 ± 0.108 0.228 ± 0.020 0.175 ± 0.045

Paired t-test

* Denotes significant difference between bulk and rhizosphere soils at P <0.05

** Denotes significant difference between bulk and rhizosphere soils at P <0.01

45

5.2.2 Magnitude of rhizosphere effect on soil nutrients

The mean percentage rhizosphere effect ([(Rhizosphere - Bulk)/Bulk]*100%) was

significantly greater for coffee grown under shade with conventional fertilization (S-C) than

coffee grown in full sun with conventional fertilization for NO3- (P = 0.0135), NH4

+ (P = 0.0324)

and exchangeable magnesium (P = 0.0169) (Figure 5). The magnitude of the rhizosphere effect

was greater under conventionally fertilized shaded coffee than full sun coffee for available P (P

= 0.1121) and exchangeable calcium (P = 0.0553), though not significantly so. There were no

significant differences in mean percentage rhizosphere effect for coffee grown under organically

versus conventionally fertilized shade treatments, though exchangeable magnesium (P = 0.0509)

and available P (P = 0.1501) tended towards accumulation in the rhizosphere under conventional

fertilization (Figure 5).

5.3 Relative quantification of bacteria

5.3.1 Relative amoA gene abundance

Differences in bacterial amoA gene abundance (as normalized to total bacteria

abundance) were detected between soil fractions and between treatments. While the relative

abundance of amoA did not differ with the incorporation of shade under conventional

fertilization, it was significantly greater in bulk soil (P = 0.0327) of organic versus

conventionally-fertilized shade treatments at 0-20cm (Table 5). The only significant difference

between rhizosphere and bulk soil at 0-20cm was found under organic fertilization, in which

rhizosphere amoA abundance (0.609 ± 0.090) was significantly greater (P = 0.0396) than bulk

soil (0.531 ± 0.075).

There were no significant differences between shade and fertilization treatments on the

magnitude of the rhizosphere effect on amoA abundance at 0-20cm. A mean positive effect was

observed in plots with shade (S-C and S-O); due to the high variance under S-C, only S-O had a

46

Figure 5. Mean percentage rhizosphere effect ([(Rhizosphere - Bulk)/Bulk]*100%) of coffee

grown under FS-C, S-C, and S-O management treatments (FS = full sun; S = shade; C =

conventional fertilization; O = organic fertilization) at 0-20cm depth (n=9 per management

treatment). Significant differences in magnitude of rhizosphere effect between FS-C and S-C are

denoted by different lower case letters (t-test, P <0.05) and by upper case letters between S-C

and S-O (t-test, P <0.05). Bars represent standard error of the mean.

-50

0

50

100

150

200

250

300

% R

hiz

osp

her

e Ef

fect

FS-C

S-C

S-O

a

a

a

a

a

a

bA A

bA

A

bA

A

bA

A

bA

A

aA

A

NO3

-

NH4

+ PO4

3- Ca

2+ Mg

2+ K

+

47

Table 5. amoA abundance (relative to total bacteria) in rhizosphere and bulk soil fractions across

all three management treatments at 0-20cm. Data are means (n=3 per management treatment, per

soil fraction) ± SE of samples pooled by block before real-time PCR assay (n=3 per block, per

soil fraction). Note, S-C values are used twice in t-tests as the common treatment combination to

comparisons in which i) fertility and ii) shade are held constant.

Relative abundance of amoA

Management Rhizosphere soil Bulk soil

FS-C 0.368 ± 0.056 aA 0.392 ± 0.017 aA

S-C 0.470 ± 0.088 aA 0.368 ± 0.056 aA

S-C 0.470 ± 0.088 aA 0.368 ± 0.056 aA

S-O 0.609 ± 0.090 aA 0.531 ± 0.075 bB

a – rows are not significantly different with same lower case letter

(paired t-test; P <0.05)

A – columns with same upper case letter are not significantly different

between treatment (t-test; P <0.05)

48

statistically significant positive rhizosphere effect (Figure 6). Soils under coffee grown in full

sun with conventional fertilization (FS-C) did not show a significant mean rhizosphere effect on

amoA abundance at 0-20cm.

5.3.2 Correlates of soil chemical and biological parameters

Exclusively for the 0-20cm soil depth, under conventionally fertilized full sun coffee

rhizosphere soil NO3- was significantly positively correlated (r = 0.828; n = 9; P = 0.006) with

pH (Figure 7). Significant correlations between pH and NO3- were not observed in bulk soil

under conventionally fertilized full sun coffee or in either soil fraction under any other treatment

(see Appendix for correlation coefficient matrices). Relative amoA relative abundance was

positively correlated (r = 0.830; n = 11; P = 0.0016) with soil pH under conventional fertilization

when bulk and rhizosphere soils were analyzed together (Figure 8). Although it was expected to

find a similar trend under organic fertilization (for which pH ranged from 6.8 to 7.3), there was

no significant correlation between amoA abundance and pH for pooled bulk and rhizosphere soil.

5.4 Bacterial community structure in bulk soil

Denaturing gradient gel electrophoresis was performed on bulk soil samples (0-20 cm

depth) from all three management treatment combinations (Figure 9a). Clustering analysis

(independent of band intensity) revealed approximately 85% similarity between DGGE banding

patterns of organically and conventionally managed soils (Figure 9b). Amongst soils managed

with shade and organic fertilization, bacterial banding patterns shared 95% or greater similarity.

There was no distinct clustering by shade level (FS-C vs. S-C) (Figure 9b), and all

conventionally managed soils shared more than 91% similarity in banding patterns.

49

Figure 6. Mean percentage rhizosphere effect ([(Rhizosphere - Bulk)/Bulk]*100%) on amoA

gene abundance relative to total bacteria abundance at 0-20cm (n=3 per treatment; bars are

standard error). Significant difference between conventionally fertilized full sun and shade

treatments denoted by lower case letters; between organic and conventional fertilization by

capital letters (t-test; P <0.05). Asterix denotes a significant rhizosphere effect (t-test; P <0.05).

50

Figure 7. Rhizosphere soil NO3- concentration (mg kg-1) in relation to soil pH at 0-20cm soil

depth under FS-C management (n=9).

0

0.5

1

1.5

2

2.5

4.6 4.7 4.8 4.9 5 5.1 5.2 5.3 5.4 5.5

NO

3-(m

g kg

-1)

pH

r = 0.828

p = 0.006

51

Figure 8. Relative amoA gene abundance as a function of pH in bulk and rhizosphere soil at 0-

20cm as pooled by fertilization treatment (FS-C + S-C; n=11, one outlier removed). Data points

represent block mean values for amoA and pH. Bars represent standard error (n=3) of mean pH

values.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

4.6 4.7 4.8 4.9 5.0 5.1 5.2 5.3 5.4 5.5

Rel

ativ

e am

oA

ab

un

dan

ce

pH

r = 0.830p = 0.002

52

Figure 9. (a) DGGE profiles of

16S ribosomal DNA obtained

using universal bacterial primers

from bulk soil (0-20 cm) from

all three treatments

combinations (FS-C, S-C, S-O).

Lanes 2-6 represent samples

from FS-C; lanes 7-9 represent

samples from S-C; and lanes 10-

12 are samples from S-O. Lanes

1 and 14 are an identical profile

from S-O, used as a ladder for

normalization. (b) DGGE-

derived dendogram (without

lanes 1, 2, 3, or 14), as

determined by unweighted pair

group method with arithmetic

mean (UPGMA).

a

b

53

Chapter 6 Discussion

6.1 Rhizosphere effects on nutrient availability

6.1.1 Rhizosphere effects on mineral N availability

I hypothesized that mineral nitrogen concentrations would be higher in rhizosphere soil

of coffee relative to bulk soil under all shade and nutrient treatments. When pooled, my data

supported this hypothesis for ammonium and nitrates at 0-20cm and 20-40cm soil depth. As

Zhao et al (2010) assert, accumulation or depletion of extractable nutrients in rhizosphere soil is

governed by the balance between rates of extractable nutrient release and uptake by plants and

microorganisms. In my study, accumulation of ammonium in the rhizosphere of coffee indicates

that rates of N mineralization was exceeding ammonium uptake by coffee roots and

immobilization by microorganisms at the time of sampling. Similarly, accumulation of nitrate in

rhizosphere soil suggests that rates of nitrification were out-pacing root and microbial uptake of

nitrates.

There are several possible explanations for these phenomena. Dijkstra et al (2009)

observed a positive relationship between plant-released carbon and gross N mineralization, and

others (Phillips and Fahey, 2006; Zhao et al, 2010) have accounted for enhanced mineralization

rates with rhizodeposition. Although it is a herbaceous species, increased root exudation by

Kentucky bluegrass (Poa pratensis) was found to stimulate microbial activity, which resulted in

higher soil inorganic N (Hamilton and Frank, 2001). Thus, enhanced mineral N concentrations in

the rhizosphere may simply be a function of enhanced mineralization of native soil organic

matter.

54

Accumulated rhizosphere ammonium may also be explained by root-zone feeding of soil

microfauna on bacteria (Ingham, 1985). This phenomenon is known to occur in spatially discrete

regions, including the rhizosphere, and has been estimated to account for approximately 30% (on

average) of total net nitrogen mineralization across various temperate ecosystems (Griffiths,

1994). Herman et al (2006), however, could not explain enhanced rates of gross N mineralization

in rhizosphere soil of slender wild oats through bacterial and protozoa population dynamics.

Given that the populations of bacterial-feeders are controlled by losses of soluble carbon from

roots (Griffiths, 1994), it seems possible that enhanced exudation of coffee under shade could

result in greater bacterial predation and mineral N turnover in the rhizosphere relative to coffee

under full sun in my system. Unfortunately, an investigation of the potential mechanisms of

rhizosphere nitrogen availability was beyond the scope of my study.

The accumulation of nitrate in rhizosphere soils of coffee indicates that, in general,

nitrate in-flow by mass flow and diffusion and its production by nitrification occurred at greater

rates than root uptake or microbial nitrate immobilization. This finding disagrees with Zhao et al

(2010), who, despite measuring enhanced potential net nitrification, found depleted nitrate

concentration in the rhizosphere of three different tree species. They suggest that in N-limited

soils such as theirs, N-limitation in the rhizosphere may result in microbe-mediated N

immobilization (Zhao et al, 2010). Clearly, this was not the case at my site. Additionally, as

drainage was sufficient on site due to the presence of deep trenches, denitrification was not

considered to be a significant factor in N transformation. The trend towards greater relative

ammonia-oxidizing bacteria abundance in rhizosphere soil under shade treatment at 0-20cm,

though only statistically significant under organic fertilization, partially supports the observation

of enhanced NO3- in the rhizosphere.

55

6.1.2 Rhizosphere effects on available P

Accumulation of available P was observed in the rhizosphere of coffee across all

management treatments at 0-20cm soil depth, which supports my hypothesis. There are several

possible explanations for this observation. Under organic fertilization, in which soil pH values

ranged from 6.8 to 7.4, rhizosphere acidification through root H+ release stood as a possible

mechanism by which P availability could have been enhanced in the rhizosphere. At 0-20cm soil

depth under shade with organic fertilization, however, rhizosphere acidification relative to bulk

soil was not observed, nor was a significant correlation between available P and pH in the

rhizosphere. Under conventional fertilization, in which soil pH values ranged from 4.7 to 5.4,

coffee rhizosphere acidification relative to bulk soil was observed under full sun management at

0-20cm soil depth. Despite this, acidification at such a low soil pH is not typically associated

with enhanced P availability, which typically occurs between pH 5.5-7 (Hinsinger et al, 2003).

Additionally, there was no significant correlation under conventionally fertilized soils between

pH and available P. Therefore, I assert that P accumulation in the rhizosphere was not directly

related to pH under either conventional or organic fertilization.

In previous studies, rhizosphere P accumulation was attributed to increased acid

phosphatase activity (Zhao et al, 2010) and organic acid exudation (Gobran and Clegg, 1998),

the latter through formation of stable aluminum complexes. Enhanced phosphatase activity has

been observed in rhizosphere compared to bulk soil across a variety of species, and phosphatase

release is believed to be a general plant response to P deficiency (Richardson et al, 2009).

Additionally, organic anions (which are similar to organic acids), are known to facilitate P

mobilization via desorption and chelation of cations (Richardson et al, 2009). As with mineral N

accumulation, enhanced rhizosphere P may also simply be a function of the priming effect of

56

rhizodeposition on making P plant-available from native soil organic matter (Hinsinger et al,

2009). I did not include measurement of such processes within my study; nevertheless, my

results demonstrate that P availability (at 0-20cm) is determined by more than the balance

between uptake and diffusion.

Deeper in the soil profile at the 20-40cm soil depth, rhizosphere P was not significantly

different on average between bulk and rhizosphere soil fractions when treatments were pooled. It

was, however, significantly depleted in coffee plants under conventionally fertilized shade

management. As Richardson et al (2009) state, orthophosphate diffusion is insufficient to

overcome root-zone gradients in most soils. In this case, it is possible that root release of acid

phosphatase and/or C exudation to stimulate microbial solubilizing and cycling activity did not

occur to the same extent at a lower depth under this particular treatment combination. This

resulted in P mobilization rates that did not keep pace with root uptake in the rhizosphere.

Phosphorus depletion has been observed by others, including Turpault et al (2005) in the

rhizosphere of mature Douglas fir. The difference in rhizosphere soil available P in

conventionally fertilized coffee plants by depth may be explained in terms of resource allocation

patterns within the coffee plant. Given a presumably greater pool of mineral and organic

unavailable P higher in the soil profile, coffee plants may allocate more metabolic resources – in

the form of phosphatase and C exudates to stimulate microbial activity – to phosphorus

acquisition at 0-20cm than 20-40cm. This remains an open question, however, and the spatial

distribution of soil P dynamics an interesting area for further research.

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6.1.3 Rhizosphere effects on exchangeable base cation concentrations

When pooled across management treatments, base cations were significantly accumulated

in rhizosphere soil at both depths (except calcium at 20-40cm). This agrees with my original

hypothesis. Once again, enhanced decomposition of native soil organic matter may partially

explain this phenomenon. Turpault et al (2005), who observed increased exchangeable base

cations in rhizosphere soil, stated that increased organic C due to root exudation results in

increased exchangeable base cation concentrations. Gobran and Clegg (1996) also found

increased base saturation in rhizosphere soil, in a mature Norway spruce stand. They explained

the observation by arguing that increased electrical conductivity reduces organic matter

ionization and decreases aluminum complexation in rhizosphere soil (Gobran and Clegg, 1996),

which can in turn open up space for base cations. Additionally, as Hinsinger et al (2009) state,

rhizosphere accumulation of calcium, magnesium, and sometimes potassium may also occur

simply due to their movement in soil solution via mass flow exceeding plant demand.

6.2 Management treatment effects on the magnitude of the rhizosphere effect

In the above section I discussed general differences in nutrient availability in rhizosphere

and bulk soil, regardless of shade and fertility management practices. In the next section, I

consider how shade tree incorporation and fertilization regime effect the magnitude of

differences between rhizosphere and bulk soil. To do so, I draw upon broader ecological

literature and incorporate my findings on soil biological activity.

6.2.1 The effect of shade trees

The magnitude of the rhizosphere effect was significantly greater under shade coffee than

full sun coffee for all plant-available nutrients and exchangeable base cations except potassium.

58

This finding is consistent with my hypothesis, which was that the difference between rhizosphere

and bulk soil nutrient concentrations would be greater under shade, due to induced modifications

in coffee physiology. There are a number of possible mechanisms by which the incorporation of

N2-fixing E. poeppigiana shade trees in the shade treatments of this study contributed to a greater

positive difference between rhizosphere and bulk soil nutrient properties.

6.2.1.1 Ammonium

The most probably explanation for the difference in rhizosphere effect on ammonium

concentration is underpinned by different photosynthetic capacity observed under shade versus

full sun coffee (Campbell, 2012). As others have noted, the quantity of carbon assimilated by

plants is determined by photosynthetic rates, and as such, photosynthetic capacity should modify

root exudation (Grayston et al, 1996). At the study site, coffee grown under shade was shown to

have enhanced photosynthetic rates in both low and high light conditions as compared to full sun

coffee (Campbell, 2012). Kuzyakov and Cheng (2001) demonstrated the tight coupling of

rhizosphere respiration (i.e. root respiration and rhizomicrobial respiration of exudates and dead

roots) with plant photosynthetic capacity. Reductions in exuded C were observed with reduced

photosynthesis, which in turn led to a subsequent decrease of the rhizosphere priming effect (the

ability of microbes to decompose additional soil organic matter in the root zone) (Kuzyakov and

Cheng, 2001). Although the mechanisms by which photosynthetic capacity is enhanced under

coffee-shade intercropping system are unique and more nuanced, the relationship between

photosynthetic capacity and acceleration of native soil organic matter decomposition in the

rhizosphere is clear.

59

As previously mentioned, Dijkstra et al (2009) have demonstrated that plant available N

is directly linked with root-primed soil C, which itself is a function of the quantity of C exuded

by roots. This relationship only existed, however, when soil inorganic N concentrations were low

(Dijkstra et al, 2009). Under conventional fertility management, coffee at the site under study in

this thesis is fertilized with one-half the optimal inorganic N recommended for optimal

production (Haggar et al, 2011). One could therefore argue that similarly to the low soil N

observed in the study of Dijkstra et al (2009), N availability under conventionally fertilized soils

is growth-limiting. Though it was beyond the scope of this study to estimate C exudation, shaded

coffee may have enhanced ammonium availability in the rhizosphere relative to full sun coffee

due to enhanced rhizodeposition.

Additionally, inputs of organic matter from shade tree prunings and litter-fall may be

responsible for observed differences in rhizosphere effects between shade and full sun coffee.

Decomposable organic C is a soil factor than significantly influences the rhizosphere priming

effect (Pausch et al, 2013). A greater percentage of organic matter in the soil represents a larger

pool of mineralizable N, particularly if it includes additional inputs of N via biological N2-

fixation derived from E. poeppigiana. While measurements at the site from 2004 (Haggar et al,

2011) indicate that shade tree incorporation did not appreciably increase soil organic matter

content at 0-10cm depth relative to full sun plots, much may have changed since then. In a 10-

year-old cacao agroforestry system with E. poeppigiana, Beer et al (1990) observed a 24

ton/hectare increase in soil organic matter reserve over 0-45cm depth over a 10-year period of

shade tree intercropping. In my study, soil was sampled exclusively from coffee plants within 3m

of the N2-fixing shade tree, underneath its canopy. As one would imagine, organic matter

contribution of shade trees through litter-fall is spatially heterogeneous; it is concentrated close

60

to the tree (Rao, 1998). Unfortunately, I did not perform analysis of soil organic matter content;

thus, its effects on the magnitude of the rhizosphere effect on ammonium concentration are

unknown. A recent study on N2-fixation capacity at my study site concluded that these shade

trees are fixing up to 40% of their N from atmospheric sources, though exclusively under the

organic fertilization regime (Campbell et al, 2013). It is presumable that some of this N source,

which is absent under full sun management, is stimulating both soil N dynamics and coffee plant

growth.

6.2.1.2 Nitrate

The magnitude of the rhizosphere effect on nitrate concentration was substantially greater

under conventionally-fertilized shade coffee than full sun coffee. As no other known studies have

been performed on coffee rhizosphere nutrient properties, there is no direct basis for comparison

of this observation. Zhao et al (2010), however, found significantly different magnitudes of

rhizosphere effects on net nitrification rates under mature Siberian elm, Simon poplar, and

Mongolian pine tree species. Despite finding greater net nitrification rates in the rhizosphere

under all three species, nitrates were universally found to be depleted in rhizosphere soil, thus

indicating faster rates of nitrate uptake than nitrification (Zhao et al, 2010). This study was

conducted in monoculture tree stands, however, with no ability to compare the effects of a

secondary species, in my case a shade tree, on rhizosphere properties.

In my study, I found significant correlations between soil chemical and biological

parameters that help explain the observed difference in magnitude of rhizosphere effect on

nitrate concentration between shade treatments. The mean ratio of ammonium to nitrate

concentration in rhizosphere soil of full sun coffee was quite high relative to shaded coffee at 0-

61

20cm soil depth. Within rhizosphere soil of conventionally fertilized, full sun coffee – the only

management treatment in which significant acidification of rhizosphere soil was observed – there

was a significant positive correlation between nitrate concentration and pH. Additionally, the

relative abundance of ammonia-oxidizing bacteria (AOB), as estimated by the relative

abundance of the amoA gene, was positively correlated with pH across bulk and rhizosphere

soils under conventional fertilization.

Taken together, these relationships suggest an association between acidity of rhizosphere

soil of coffee under conventional, full sun management and suppressed nitrification rates.

Alteration of pH is well known by-product of ammonium uptake. Net release of protons occurs

as a result of ammonium uptake and can lead to rhizosphere acidification (Hinsinger et al, 2009;

Richardson et al, 2009). Previous research on Douglas fir trees found that higher ammonium

relative to nitrate in rhizosphere soil resulted in a lower rhizosphere pH (Wang and Zabowski,

1998). Acidity also affects the activity of AOB. In fact, significant batch growth of ammonia

oxidizing bacteria in liquid growth media rarely occurs below pH 7 (Nicol et al, 2008) and rates

of nitrification and ammonia oxidation are significantly depressed in acid soils (de Boer and

Kowalchuk, 2001).

In addition to the effect of ammonium uptake on pH levels, reduced ammonium

availability decreases AOB populations (Okano et al, 2004; Cavagnaro et al, 2008). Thus, the

positive correlation between pH and AOB abundance may be an indirect reflection of

ammonium uptake rates on AOB populations. Indeed, pH alone did not seem to govern AOB

abundance or rhizosphere nitrate concentrations: higher mean AOB abundance was found in the

rhizosphere of conventionally-fertilized shaded coffee, despite its lower mean pH values than in

the rhizosphere of conventionally-fertilized full sun coffee. Additionally, the mean rhizosphere

62

effect on AOB abundance under conventionally-fertilized shaded (positive) and full sun coffee

(negative) accurately reflected differences in the magnitude of the rhizosphere effect on nitrate

concentration. Further, it supports the utility of using AOB population abundance to explain

differences in rhizosphere nitrate concentrations under conventional fertilization. Ultimately, my

data indicates that the relative abundance of AOB, as estimated by real time-PCR analysis of the

ammonia monooxygenase gene, is a useful indicator of nitrification activity under conventional

fertilization at this site.

6.2.2 The effect of fertility management

I hypothesized that the rhizosphere effect on nutrient availability would be more

pronounced under low nutrient conditions. Organically fertilized bulk soils had significantly

higher available P, exchangeable calcium, and exchangeable magnesium at 0-20cm soil depth

than conventionally fertilized bulk soils. Mineral N concentrations, however, did not differ

between organic and conventionally fertilized bulk soils, nor did exchangeable potassium. Thus,

I will focus attention on those nutrients that were deficient in bulk soil under conventional

management relative to organic management.

While there were no significant differences in the magnitude of the rhizosphere effect

between organic and conventionally fertilized shade treatments, there was trend towards a

greater rhizosphere effect on available P and exchangeable magnesium under conventional

fertilization. Due to the fact that the rhizosphere effect is driven by carbon release from roots,

either as a factor stimulating microbial activity (Fontaine et al, 2003) or directly as organic acids

(Richardson et al, 2009; van Schöll et al, 2006), a decrease in its magnitude may be explained by

plant C allocation theory, which predicts decreased C flow to roots in fertile soils (Phillips and

63

Fahey, 2008). van Schöll et al (2006) measured exudation of low molecular weight organic

anions, molecules known to enhance mineral weathering, in response to nutrient deficiencies. In

response to phosphorus deficiency, pine seedling increased overall exudation, while increased

exudation of oxalate was found in response to magnesium deficiency (van Schöll et al, 2006).

Phillips and Fahey (2008) found a decreased rhizosphere effect on phosphatase enzyme activity

in red oak and yellow birch stands fertilized with 58 kg P ha-1 yr-1 relative to unfertilized stands.

The difference in mean rhizosphere effect on available P between conventionally and

organically fertilized treatments also possibly occurred due to higher arbuscular mycorrhizal

fungi (AMF) colonization of conventionally fertilized coffee plants. Coffea arabica is known to

be colonized by AMF (Vaast and Zasoski, 1992). High P fertilization is known to greatly

decrease arbuscular mycorrhizal biomass in mycorrhizal plants (Smith et al, 2011). Lower

available P levels in bulk soil at 0-20cm under conventional fertilization, therefore, may have

stimulated greater mycorrhizal colonization and resulted in increased mycorrhizae-solubilized P

in the rhizosphere. However, without biomass or AMF colonization estimates under the two

fertility treatments, it is difficult to ascertain the role that AMF played in P acquisition at the

rhizosphere.

Overall, there was not sufficient evidence to demonstrate that the magnitude of the

rhizosphere effect was enhanced under conventional fertilization for nutrients that were present

in relatively low concentrations. However, given the trend across all nutrients (particularly

available P and exchangeable magnesium) towards a higher mean rhizosphere effect, the impact

of bulk soil fertility on root-induced changes in nutrient availability is a pertinent area for further

research within coffee agroforestry systems.

64

6.2.3 Bulk soil properties

A significantly higher relative abundance of ammonia-oxidizing bacteria was found

under shade-organic versus shade-conventional management at both soil depths. This finding

may be indicative of a more abundant, steady supply of substrate (ammonium) for ammonia-

oxidation. Okano et al (2004) observed significantly greater AOB populations in an annually

fertilized field relative to an unfertilized control field, despite acquiring measurements 8 months

after fertilizer application. They suggest that ammonia fertilization may have long term, indirect

effects on AOB populations through increasing crop biomass production and subsequent soil

organic matter accumulation (Okano et al, 2004). Average coffee height and biomass (Campbell,

2012) were higher under organic versus conventional fertilization at my site. Along with high

annual inputs of organic materials with organic fertilization, this may have contributed to

significantly elevated soil organic matter levels in bulk soils observed under organic fertilization

(Haggar et al, 2011). Similarly to Okano et al (2004), these conditions in turn may serve to

maintain AOB populations at higher levels than under conventional fertilization.

Such differences in biological soil properties have important implications for the rate at

which organic inputs from shade trees are decomposed and mineralized in plant-available forms.

Although rates of mineralization and nitrification were not measured as part of this study, the

higher abundance of AOB under the organically-fertilized shade treatment indicates that nutrient

cycling may be occurring more rapidly than in conventionally fertilized plots. This could

subsequently elevate the rate at which plant-available nutrients are produced, which has

important implications for coffee nutrient acquisition. Rates of nutrient turnover were not probed

in this single-time-point study, however, and remain an important area of consideration when

comparing conventional to organic fertilization.

65

While I have focused on the differences between rhizosphere and bulk soil in this

research, it is well known that bulk soil properties affect rhizosphere processes. Chemical factors

of bulk soil, such as organic C and mineral N (Pausch et al, 2013), as well as biological factors,

like microbial community structure, can govern the nature of root-induced effects at the

rhizosphere. Previous research has demonstrated that soil properties in some instances can

control microbial community structure to a greater degree than do root-induced effects (Buyer et

al, 2002). As soil microorganisms are the drivers of organic matter decomposition and nutrient

cycling in the soil, management effects on their dynamics has important implications. The effect

of fertility management on bulk soil properties was further borne out by the observation of

distinct differences in bacterial community structure between organic and conventional

treatments at 0-20cm.

Given that DGGE profiles clustered according to fertilization and not shade-tree

presence, it would appear that fertility management is the main driver of bacterial community

structure at 0-20cm soil depth. Modifications of microbial community structure can have

important implications for soil function. For example, Waldrop et al (2000) observed

compositional shifts in a soil microbial community associated with land use change that were

correlated with enzyme activities involved in phosphorus solubilization and lignocellulose

degradation. The alteration in bacterial community structure in response to organic fertilization

therefore may have important effects on soil functioning; a phenomenon that has been hinted at

in my investigation by a greater abundance of ammonia-oxidizing bacteria.

Additionally, it is possible that shade-tree effects on soil bacterial communities exist at

my site, but were just not detected at the soil depth of 0-20cm. The effect of shade tree

incorporation on soil bacterial dynamics would likely only be detected in the top few

66

centimeters, where the impact of litter-fall and tree prunings is greatest. Given that the greatest

fine root density of coffee under Erythrina poeppigiana exists in the top 5-10cm of soil at the

site (Mora, 2011), modification of bacterial community structure and function at depths

shallower than 20cm holds great potential to impact nutrient availability. This is another

promising avenue of inquiry with important implications for linking microbial function to

nutrient effects of shade-tree intercropping in coffee agroforestry systems.

67

Chapter 7 Conclusions

Very little past research has endeavoured to uncover the effects of shade-tree

intercropping within agroforestry systems on nutrient dynamics at the root-soil interface. In this

study, I compared nutrient availability in rhizosphere soil of coffee to bulk soil under the shade

of a N2-fixing tree common to Costa Rican coffee agroforestry systems. In doing so, I

demonstrated that mineral N, available P, and exchangeable base cations are accumulated in the

root zone to a greater degree under shaded coffee than monoculture coffee. This suggests that

bulk soil nutrient status, which at my site was nearly identical under shade and full sun

management, does not always provide an accurate metric of nutrient availability for the crop.

Furthermore, it calls into question to applicability of basing plot-scale management on bulk soil

samples that do not reflect nutrient status in the zone of plant uptake.

Comparisons between shade and full sun management were made under conventionally

fertilized coffee that received only one half of the optimally recommended nutrient inputs.

Previous research at the study site demonstrated substantial aboveground physiological

adaptations of coffee to shade-tree incorporation under this fertilization regime. These adaptions,

which include increased photosynthetic capacity under shade, may have driven the enhanced

rhizosphere effect. Other aboveground properties, however, such as increased leaf nutrient

content, may have been the result of enhanced nutrient availability in the rhizosphere under

shade management. Thus, an enhanced rhizosphere effect may be a result of aboveground, leaf-

level adaptation, and simultaneously an underlying mechanism by which shade-tree

intercropping improves plant nutrient status.

68

My results illustrate that in order to uncover mechanisms behind differences in

rhizosphere nutrient availability, an integrated methodological approach is required. I

quantitatively compared functionally-relevant bacterial populations across shade and fertilization

treatments and between bulk and rhizosphere soil. In doing so, I was able to provide a likely

explanation for reduced nitrate availability in the rhizosphere of conventionally-fertilized full sun

coffee relative to shaded coffee. Additionally, I detected differences in ammonia-oxidizer

populations between organically and conventionally fertilized bulk soils, which indicated

accumulated effects of management on bulk soil processes. Given the central role of soil biology

in rhizosphere nutrient transformations, it is clear that a comprehensive understanding of

rhizosphere dynamics within agroforestry systems, or any plant-soil system, requires linking soil

biological and chemical properties.

Overall, this research challenges the notion that nutrient availability in the root zone is

governed simply by the balance between uptake and replenishment via mass flow and diffusion.

While bulk soil processes play a key role in mediating nutrient supply, rhizosphere accumulation

of inorganic nutrients across management treatments illustrates an important root-induced effect.

The mechanisms underpinning this phenomenon within this system are not definitively known;

aboveground management, however, through intercropping with a N2-fixing tree, clearly plays a

role. A better understanding of the factors that influence the rhizosphere effect on nutrient

availability will enable the design of more sustainable, efficient agroecosystems. This is

especially true in low-input agricultural systems, in which there is greater crop reliance upon

organic and mineral pools for soluble nutrients.

69

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Appendix

Mean coffee plant height under full sun with conventional fertilization (FS-C), shade with

conventional fertilization (S-C) and shade with organic fertilization (S-O; n=9 per treatment).

Management treatment Mean coffee plant height (cm)

FS-C

1.96 ± 0.04 a

S-C 2.05 ± 0.04 aA

S-O 2.19 ± 0.04 B

a – mean values are not significantly different with same lower case letter when fertilization is

held constant (t-test; P <0.05)

A – mean values are not significantly different with same upper case letter when shade is held

constant (t-test; P <0.05)

77

Pearson correlation coefficient (r) values between bulk soil chemical parameters (n=18; pooled

by fertilization treatment (FS-C and S-C)).

NO3-

(mg kg-1)

NH4+

(mg kg-1)

PO43+

(mg kg-1)

Ca2+

(cmol+ kg-1)

Mg2+

(cmol+ kg-1)

K+

(cmol+ kg-1)

pH

NO3-

1 -0.0745 -0.2807 0.05303 0.17508 0.02196 -0.2943

NH4+ 1 0.16163 -0.0995 0.06338 -0.4643 0.08889

PO43+ 1 0.27281 0.36765 -0.5726 0.35357

Ca2+ 1 0.62121 -0.2178 0.50045

Mg2+ 1 -0.569 0.47275

K+ 1 -0.3446

pH 1

Significant effects (at P <0.05) are in bold

78

Pearson correlation coefficient (r) values between rhizosphere soil chemical parameters (n=18;

pooled by fertilization treatment (FS-C and S-C)).

NO3-

(mg kg-1)

NH4

(mg kg-1)

PO43+

(mg kg-1)

Ca2+

(cmol+ kg-1)

Mg2+

(cmol+ kg-1)

K+

(cmol+ kg-1)

pH

NO3-

1 0.55011 0.10882 0.17179 0.42417 0.11161 -0.22282

NH4+ 1 0.49916 -0.12397 0.12819 -0.02109 -0.33176

PO43+ 1 -0.06278 0.09449 -0.33473 -0.27938

Ca2+ 1 0.48012 0.24736 0.67962

Mg2+ 1 -0.04218 0.21697

K+ 1 0.13913

pH 1

Significant effects (at P <0.05) are in bold

79

Pearson correlation coefficient (r) values between bulk soil chemical parameters under shade

with organic fertilization (S-O; n=9).

NO3-

(mg kg-1)

NH4

(mg kg-1)

PO43+

(mg kg-1)

Ca2+

(cmol+ kg-1)

Mg2+

(cmol+ kg-1)

K+

(cmol+ kg-1)

pH

NO3-

1 -0.79274 0.62024 -0.81306 -0.41942 -0.07712 -0.29691

NH4+ 1 -0.64407 0.76023 0.17923 0.29607 0.30358

PO43+ 1 -0.58677 0.26629 -0.05018 -0.62828

Ca2+ 1 0.34838 0.37153 0.35152

Mg2+ 1 0.26420 -0.53372

K+ 1 0.03744

pH 1

Significant effects (at P < 0.05) are in bold

80

Pearson correlation coefficient (r) values between rhizosphere soil chemical parameters under

shaded coffee with organic fertilization (S-O; n=9).

NO3-

(mg kg-1)

NH4

(mg kg-1)

PO43+

(mg kg-1)

Ca2+

(cmol+ kg-1)

Mg2+

(cmol+ kg-1)

K+

(cmol+ kg-1)

pH

NO3-

1 -0.58932 0.62415 -0.74326 -0.45598 -0.08478 -0.36907

NH4+ 1 -0.28171 0.57896 0.41631 0.59330 0.49666

PO43+ 1 -0.80018 -0.17478 -0.02270 -0.29468

Ca2+ 1 0.63220 0.20431 0.47169

Mg2+ 1 0.29146 0.29624

K+ 1 0.31200

pH 1

Significant effects (at P < 0.05) are in bold