© 2016 Adriana Corrales Osorio

© 2016 Adriana Corrales Osorio

ECTOMYCORRHIZAL ASSOCIATIONS IN TROPICAL MONTANE FOREST: INSIGHTS INTO THEIR INFLUENCE ON NUTRIENT CYCLING AND FUNCTIONAL RESPONSES

TO SOIL FERTILITY

BY

ADRIANA CORRALES OSORIO

DISSERTATION

Submitted to fulfillment of the requirements for the degree of Doctor of Philosophy in Plant Biology

in the Graduate College of the University of Illinois at Urbana-Champaign, 2016

Urbana, Illinois

Doctoral Committee:

Professor James W. Dalling, Chair and Director of Research Professor Ken N. Paige Assistant Professor Katy Heath Associate Professor Anthony Yannarell Assistant Professor Scott Mangan

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Abstract

In Panamanian montane forest, the ectomycorrhizal tree Oreomunnea mexicana forms

monodominant stands where it accounts for up to 70% of individuals. Monodominance is

unexpected in tropical forest because the accumulation of host-specific pathogens is thought to

limit the local abundance of individual species. Although rare, monodominant forests have now

been recognized in all major tropical regions and include a wide diversity of tree taxa. Notably,

many monodominant species associate with a particular type of mutualist: ectomycorrhizal (EM)

fungi. Ectomycorrhizal associations are rare in tropical forests where most species associate with

arbuscular mycorrhizal fungi.

Oreomunnea associates with a diverse community of ectomycorrhizal fungi. In a survey

of Oreomunnea root tips using sanger sequencing, I identified 115 EM fungal taxa from 234 EM

Oreomunnea root tips collected from four sites across a soil fertility gradient. There was a high

compositional turnover in the EM fungal communities associated with Oreomunnea with a

significant effect of soil fertility on EM fungal compositional variation. In addition, analysis of

the phylogenetic beta diversity for Russula, the most abundant and diverse EM genus in the

community, revealed that Russula species show greater than expected phylogenetic dissimilarity

among taxa occupying sites with contrasting fertility.

Current theory on how monodominance is maintained has focused on alterations to plant-

microbial interactions. I tested three potential mechanisms by which EM fungi may potentially

allow a host tree species to achieve monodominance: (1) by conferring resistance to soil-borne

pathogens that are responsible for negative plant-soil feedback experienced by competing

species, (2) by connecting juveniles to adults through ectomycorrhizal networks that transfer

water, nutrients or carbon, and (3) by altering ecosystem nutrient economies, thereby reducing

the availability of limiting resources to competing species. After testing these three hypotheses I

found no evidence for positive feedback on Oreomunnea abundance caused by either pathogen

resistance or the formation of mycorrhizal networks. Instead, the presence of EM fungi was

associated with a reduction in inorganic nitrogen availability tightening the nitrogen cycle,

making it difficult for other, non-EM tree species to compete.

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Ectomycorrhizal fungi have been shown to respond differently to N addition depending

on their functional traits. I studied EM fungal communities associated with Oreomunnea in

control plots and plots that had received a nitrogen addition treatment for nine years, I found a

significant difference in the species composition of the EM fungal community between plot

treatments, and differences in the abundance of some genera. Members of the EM fungal genera

Laccaria and Lactarius, showed an increase in their relative abundance with N addition while

members of the genus Cortinarius showed a strong reduction in relative abundance. Increased N

availability in tropical ecosystems could result in a reduction in EM fungal taxa specialized in

organic N and P absorption (e.g., Cortinarius) along with a decrease in EM colonization of host

plants potentially having implications in soil C storage, and ecosystem N cycling ultimately

affecting forest productivity and diversity.

The isotopic composition of EM fruiting bodies has been shown to be a useful tool for

understanding the functional role of EM fungi in ecosystems. After analyzing the δ15N and δ13C

of Russula fruiting bodies, and its correlation with Oreomunnea host abundance and soil

inorganic N availability, I found that the isotopic composition of the Russula community reflects

increased host demand for ectomycorrhizal fungal nitrogen supply with a reduction in soil

inorganic nitrogen availability. These results are consistent with an increase in N sequestration

by EM fungi in sites with higher host abundance. Given the high correlation of host abundance,

N availability, and N transfer from EM fungi to the host (reflected in fruiting body δ15N) in our

system here I provide further evidence that the formation of Oreomunnea dominated forest is

facilitated by its associated EM fungi.

In conclusion I found that EM fungi are highly diverse in tropical montane forest and that

they can facilitate the formation of monodominant forest of EM associated tree species by

altering the N cycle. Also, I predicted increase in N availability due to atmospheric N deposition,

could potentially alter the interaction between EM fungi and their host plant potentially leading

to biotic and abiotic changes in the ecosystem.

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To my parents, Julia Osorio and Fernando Corrales,

Thank you for your great support and inconditional love.

and

To Dr. Esperanza Franco-Molano, the person that motivated me to explore the world of mycology

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Acknowledgments

I would especially like to thank Dr. Jim Dalling for acting as my adviser, and for his

committed guidance and assistance during the research and preparation of my thesis. I would

also like to thank all the members of my committee for providing helpful suggestions and

comments during the development of this project. I would like to thank my collaborators Scott

Mangan, Ben Turner, Betsy Arnold, Astrid Ferrer, Clark Ovrebo, and Leho Tedersoo for all their

guidance in their topic of expertise and their useful comments to my thesis.

I would like to thank to the many people that have contributed their help to make this

project possible. I would like to thank my fellow lab mates Katie Heineman, Cecilia Prada,

Jennifer Jones, Camilo Zalamea, and Carolina Sarmiento for their help their help during the

development of the project. For their assistance with molecular lab work I would like to thank

Dr. Katy Heath and her lab personnel for hosting the DNA lab work, also Kayla Arendt, Jana

U’Ren, Pat Burke, and Sten Anslan. Also would like to thank Mike Masters, Dayana Agudo,

Aleksandra Bielnicka, and Iulianna Taritsa for help with resin bag and isotopic analysis and

Carmen Velasquez, Carlos Espinosa, Marggie Rodriguez, Pedro Caballero, Freddy Miranda, Jan

Miranda and Evidelio Garcia for their help with fieldwork and logistic support in Panama.

Finally I would like to thank Aaron DiMartino and Shawn Brown for their useful comments on

the early versions of several chapters.

There were also many institutions that made this project possible thanks to their generous

funding. That includes COLCIENCIAS (497-2009 Programa de Formación doctoral “Francisco

José de Caldas”), Smithsonian Tropical Research Institute Short-Term Fellowship and Pre-

doctoral fellowships, NSF Dissertation Improvement Grant (Award Id: 1501483), Tinker

Summer Research Fellowship, Francis M. and Harlie M. Clark Research support grant, Robert L.

Gilbertson Mycological Herbarium Grant (University of Arizona), and Dissertation Improvement

Grant from the Graduate College at University of Illinois.

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TABLE OF CONTENTS CHAPTER 1: INTRODUCTION .............................................................................................................. 1 CHAPTER 2: VARIATION IN ECTOMYCORRHIZAL FUNGAL COMMUNITIES ASSOCIATED WITH OREOMUNNEA MEXICANA (JUGLANDACEAE) IN A NEOTROPICAL MONTANE FOREST ................................................................................................................................. 5 CHAPTER 3: AN ECTOMYCORRHIZAL NITROGEN ECONOMY FACILITATES MONODOMINANCE IN A NEOTROPICAL FOREST ..................................................................... 53 CHAPTER 4: NITROGEN ADDITION ALTERS ECTOMYCORRHIZAL FUNGAL COMMUNITIES AND SOIL ENZYME ACTIVITIES IN A TROPICAL MONTANE FOREST . 85 CHAPTER 5: VARIATION IN STABLE ISOTOPES OF RUSSULA SPECIES ASSOCIATED WITH OREOMUNNEA MEXICANA IN A TROPICAL MONTANE FOREST ............................. 119 CHAPTER 6: CONCLUSIONS ............................................................................................................. 146

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Chapter 1: Introduction

Mycorrhizal associations – which are mutually beneficial associations between plants and

fungi-- play a critical role in nutrient acquisition and, therefore, the growth and survival of

plants. There are several kinds of mycorrhizas that occur across vascular plants, however two

types predominate: Arbuscular mycorrhizas (AM), that are most frequent associations in

neotropical ecosystems, and Ectomycorrhizas (EM), which dominate in boreal and many

temperate ecosystems (Smith & Read 2008). However, in contrast to this general pattern, some

tropical forests support EM tree species that reach high abundance and host a considerable

diversity of EM fungi (Peay et al. 2010, Smith et al. 2011).

A defining feature of tropical forests is the presence of a high biodiversity, where

hundreds of tree species occur in areas of a few hectares or less. While most attention from

ecologists has been directed toward understanding how these species coexist, less attention has

been given to the exception to this pattern, known as ‘monodominance’. Monodominant forests

arise when a single tree species accounts for the majority of individuals in a stand. Although an

infrequent occurrence, monodominant forests have now been recognized in all major tropical

regions and include a wide diversity of tree taxa. Monodominance is unexpected in tropical

forest because the accumulation of host-specific pathogens is thought to limit the local

abundance of individual species (Klironomos 2002, Bell et al. 2006, Mangan et al. 2010).

Current theory on how monodominance is maintained has therefore focused on alterations to

plant-microbial interactions. Notably, many monodominant species associate with

ectomycorrhizal fungi.

For my doctoral dissertation, I characterized the general structure of the ectomycorrhizal

(EM) fungal community in stands of the EM tree Oreomunnea mexicana (Juglandaceae) at

Fortuna Forest Reserve in western Panama. Oreomunnea is distributed from Mexico to Panama

at 900–2600 m.a.s.l., becoming dominant in some locations where it accounts for up to 70% of

individuals. Oreomunnea forms EM associations in contrast to almost all co-occurring species at

Fortuna. For my second chapter I described the EM fungal community associated with

Oreomunnea populations. Sequencing of fungal nrITS DNA revealed 115 EM fungi taxa

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(including 36 Russula) from 234 EM Oreomunnea root tips collected from four sites across a soil

fertility gradient. Soil fertility did not have an effect on overall EM fungal species richness,

however high compositional turnover was observed among sites located < 6 km apart, with a

significant effect of soil fertility on EM fungal compositional variation. Analysis of the

phylogenetic diversity of the Russula sequences also revealed greater than expected phylogenetic

dissimilarity among taxa occupying sites with contrasting fertility, suggesting that environmental

filtering is important in structuring EM fungal communities. This study was published in the

journal Mycorrhiza and is coauthored by Drs. Astrid Ferrer, Elizabeth Arnold, Benjamin Turner,

and James Dalling.

For my third chapter, I tested three hypotheses to explain how EM fungi allow a host tree

species to achieve local dominance: (1) by conferring resistance to soil-borne pathogens that are

responsible for negative plant-soil feedback, (2) by enabling transfer of water, nutrients or

carbon through ectomycorrhizal networks, and (3) by reducing the availability of nitrogen (N) to

competing species due to the capacity of EM fungi to access organic N sources via extracellular

enzymes. I tested for plant soil-feedback using a greenhouse experiment in which growth of

seedlings of five species was measured after addition of conspecific or heterospecific soil

inocula. I also tested for EM network effects in the field using nylon mesh to exclude hyphal

connections. I found no evidence for positive plant-soil feedback or that EM networks confer a

competitive advantage to Oreomunnea seedlings. However, I found ~3-fold higher nitrate and

ammonium concentrations outside than inside Oreomunnea-dominated forest. Additionally, I

found lower bulk soil stable δ15N in Oreomunnea-dominated forest compared with adjacent AM

mixed forest. Nitrification and denitrification processes strongly discriminate against 15N,

leaving behind 15N-enriched N in the soil. Therefore soils with low inorganic N and low

mineralization rates, show reduced δ15N of the soil N pool. This indicates a tighter N cycle in

Oreomunnea-dominated forest due to depletion of N from the soil organic matter pool by EM

fungi. This study was published in the journal Ecology Letters and was coauthored by Drs. Scott

Mangan, Benjamin Turner, and James Dalling.

For my fourth chapter I studied the changes in EM fungal community composition after

long-term N fertilization along with changes in the soil in enzymatic activity associated with

carbon (C) and nitrogen (N) mineralization. In N-limited temperate forests, long-term increases

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in N availability can reduce the species richness and alter the community composition of EM

fungi. It has been proposed that differences in the sensitivity to N addition among EM fungi is

associated with fungal strategies of growth and colonization, and nutrient acquisition strategies

that can vary considerably among taxa. Consistent with this, my results revealed that nine years

of N fertilization are enough to significantly change the species composition of the EM fungal

community associated with Oreomunnea and affect the abundance of some genera. Members of

the EM fungal genera Laccaria and Lactarius, showed an increase in their relative abundance

with N fertilization while members of the EM fungal genus Cortinarius showed a strong

reduction in relative abundance. Consistent with this pattern, the genera Laccaria and Lactarius

have previously been reported to increase in abundance in response to high N availability and to

uptake labile N forms, while Cortinarius has been reported as showing a consistent negative

association with N availability and to be capable of absorbing organic N in temperate forest

(Lilleskov et al. 2011). I also found lower phosphatase activity in the soil in N addition plots

potentially linked with a reduction in the abundance of EM fungi, and reflected in lower EM

colonization of Oreomunnea roots. This study will be submitted to the journal Soil Biology and

Biogeochemistry.

For my fifth chapter I studied the variation in the isotopic composition of Russula species

found in a gradient of soil inorganic N availability and host abundance. The genus Russula is an

important component of the EM community at our study site and accounts for almost half of the

EM fungal species. I found that the Russula community average δ15N was positively correlated

with the abundance of the host species Oreomunnea mexicana while δ13C was negatively

associated with host abundance. I also found that the abundance of Oreomunnea was negatively

correlated with soil inorganic N availability as expected based on results from chapter two. This

δ15N enrichment and δ13C depletion of Russula fruiting bodies with increase in host abundance

and decrease in inorganic N availability is evidence of a higher transfer rate of N from Russula to

their host plant and higher transfer of C from the host plant to Russula due to a higher

Oreomunnea N demand. As proposed in chapter 2, low soil inorganic N availability conditions

under Oreomunnea dominated forest are created by competition between EM fungi and the

community of free living saprotrophs (Averill et al. 2014), suggesting that EM fungi create soil

conditions that increase Oreomunnea dependency on EM fungal N. These findings are in line

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with the results from the second chapter of this dissertation supporting that EM fungi associated

with Oreomunnea can cause a reduction in soil inorganic N availability facilitating the

maintenance of Oreomunnea monodominant forest. Here I provide additional evidence that this

reduction in N availability could be caused by an increase in N sequestration by EM fungi in

sites with higher host abundance due to higher C transfers from Oreomunnea to its associated

EM fungi in sites with lower fertility.

In the final chapter I summarize the main results from each of the above-mentioned

chapters and give an overview of the mechanisms facilitating the monodominance of

Oreomunnea mexicana at Fortuna Forest Reserve. I also discuss the implications of high

abundance of EM fungi in tropical montane forest for soil carbon sequestration and N cycling.

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Chapter 2: Variation in ectomycorrhizal fungal communities associated with Oreomunnea mexicana (Juglandaceae) in a Neotropical montane forest1

Introduction

Nutrient uptake and transfer via mycorrhizal associations strongly influences the growth

and survival of most plant species in nearly all of earth’s most species-rich and threatened

terrestrial biomes (Bonfante and Genre 2010; Smith and Read 2008). In tropical forests, trees

predominantly form associations with arbuscular mycorrhizal (AM) fungi (Glomeromycota)

(Béreau and Garbaye 1994, Janos 1983, McGuire 2008, Onguene and Kuyper 2001, St John

1980, St John and Uhl 1983). However, forests dominated by tree species that associate with

ectomycorrhizal (EM) fungi, especially Basidiomycota, have been recognized in all major

tropical regions (Becker 1983, Connell and Lowman 1989, Hart et al. 1989, Henkel 2003).

Ectomycorrhizal plants in lowland tropical forests belong mostly to the Dipterocarpaceae and

Fabaceae (primarily a narrow group of Caesalpinioideae), whereas Fagales (including members

of the Juglandaceae, Betulaceae and Fagaceae) frequently occur in montane sites (Itoh 1995,

Conway and Alexander 1992, Hart et al. 1989, Henkel 2003, Morris et al. 2008). In some cases

these EM species grow in ‘monodominant’ forests, wherein a single tree species accounts for

more than 50% of canopy trees in a stand (Connell and Lowman 1989). Why these

monodominant forests persist in otherwise diverse plant communities is not fully understood

(Peh et al. 2011).

Mast fruiting, low rates of disturbance, high tolerance of shade by seedlings, slow litter

decomposition, and escape from herbivory have been proposed as mechanisms to explain

tropical monodominance (reviewed by Peh et al. 2011). Strikingly, a common feature of many

monodominant tree species in tropical forests is the formation of EM associations (Connell and

Lowman 1989, Malloch et al. 1980, Henkel 2003). In temperate forests, natural isotope

1 This chapter appeared in its entirety in the Journal Mycorrhiza and is referred to later in this dissertation as “Corrales et al. 2016a”. Corrales, A.; Arnold A.E.; Ferrer, A; Turner, BL; and Dalling J.W. 2016. Variation in ectomycorrhizal fungal communities associated with Oreomunnea mexicana (Juglandaceae) in a Neotropical montane forest. Mycorrhiza 26:1–17. This article is reprinted with the permission of the publisher and is available from http://link.springer.com/article/10.1007/s00572-015-0641-8 and using DOI: 10.1007/s00572-015-0641-8

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abundance and radio-isotopic labeling experiments have shown that some EM tree species can

develop EM networks, where hyphal connections transfer water, carbon, and nutrients from adult

to juvenile plants (Booth and Hoeksema 2010, Simard et al. 1997, Plamboeck et al. 2007, see

Simard et al. 2012 for review). In tropical forests, direct evidence of resource transfer among

individuals is currently lacking, but decreased survival and growth of seedlings when isolated

from neighboring plants is consistent with EM network effects (McGuire 2007, Onguene and

Kuyper 2002).

Ectomycorrhizal networks may increase survival of conspecific seedlings in a spatially

structured fashion, disproportionately increasing their abundance near adult trees (Henkel 2003,

McGuire 2007, Onguene and Kuyper 2002, Booth and Hoeksema 2010, Teste et al. 2009) in a

manner consistent with positive plant–soil feedbacks (reviewed by Bever et al. 2012). In turn, the

presence and strength of plant–soil feedback depends on the functional traits and taxonomic

composition of the EM fungal community (e.g., Dickie et al. 2002, O’Brien et al. 2010, Kennedy

et al. 2012). Determinants of EM fungal community composition remain poorly understood in

tropical forests. For example, there is conflicting evidence regarding host specificity in tropical

EM fungal communities (e.g., for evidence of host preference, see Morris et al. 2009, Tedersoo

et al. 2008, and Tedersoo et al. 2010a, for evidence of low host specificity, see Diédhiou et al.

2010, Smith et al. 2011, 2013, and Tedersoo et al. 2011). Similarly the influence of soil type on

EM fungal community composition remains unresolved, in part because EM fungal communities

associated with the same host species have not been studied across a range of soil conditions.

Here we examine EM fungal communities associated with Oreomunnea mexicana

(Standl.) J.-F. Leroy, a widely distributed neotropical tree in the walnut family (Juglandaceae),

and one of the few examples of a monodominant EM species in the Neotropics. In montane

forests in western Panama, Oreomunnea forms locally monodominant stands within otherwise

highly species-rich forest comprised mostly of taxa that form AM associations (Andersen et al.

2010). In this region, Oreomunnea forms dominant stands on several distinct soil types that are

distributed over a scale of only a few kilometers. These soils are derived from contrasting parent

materials and occur in areas that differ in the seasonality and quantity of annual rainfall

(Andersen et al. 2010), making this system unique for the study of EM fungal ecology.

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Preliminary field surveys of fungal fruiting bodies indicated that diverse communities of EM

fungi associate with Oreomunnea in these stands (A. Corrales et al. unpublished data).

In this first characterization of the EM fungal community associated with Oreomunnea,

we used data generated from root tips of seedlings, saplings, and adult trees across this landscape

to test four predictions. First, we predicted that infection frequency of EM fungi would be lower

in more fertile soils, consistent with the general view that benefits of EM fungi depend on soil

conditions (Treseder 2004). Second, we predicted that the diversity, composition, and

phylogenetic diversity of EM fungi would vary with soil fertility. Third, we expected to see (a)

commonalities in EM fungal communities shared across seedling, sapling, and adult life stages

of Oreomunnea, and that (b) community similarity among developmental stages would be

particularly strong in the lowest fertility soils, where selection for EM networks or particularly

beneficial symbionts would likely be strongest. Fourth, we expected lower phylogenetic diversity

of EM fungi in high-fertility sites, reflecting lower colonization rates and consequently lower

community diversity.

Methods

The study focused on stands of Oreomunnea mexicana (Juglandaceae; hereafter,

Oreomunnea) in three watersheds in a primary lower montane forest (1000–1400 m.a.s.l.) in the

Fortuna Forest Reserve in western Panama (Figure 2.1; hereafter, Fortuna; 8°45 N, 82°15 W).

Oreomunnea is a mid-elevational canopy tree distributed from southern Mexico to western

Panama at 900–2600 m.a.s.l. (Stone 1972). It produces ca. 100 mg, wind-dispersed fruits, which

can generate high-density seedling patches in the understory (Table 2.1). Oreomunnea is locally

dominant at some of our study sites, accounting for up to 70% of individuals and stand basal area

at the Honda watershed (A. Corrales unpublished data). Dominance by Oreomunnea is not

directly related to particular functional traits such as leaf chemistry (i.e., nitrogen (N) and

phosphorus (P)) and wood density, which are close to community averages for the area (K.

Heineman unpublished data). However, Oreomunnea forms EM associations (as previously

reported from Mexican populations; Quist et al. 1999), in contrast to almost all co-occurring tree

species at Fortuna. Other EM tree species that are present in the study area (i.e., Quercus

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insignis, Q. cf lancifolia, and Coccoloba spp.) occur at low densities (typically <10 individuals

>10 cm DBH per ha) and are present within and outside of Oreomunnea-dominated stands.

Climate records indicate that the mean annual temperature for Fortuna ranges from 19 to

22˚C (Cavelier 1996). Annual rainfall averages ca. 5800 mm at our sites in Hornito and Alto

Frio, and 9000 mm at our sites in Honda A and Honda B, although all were drier during our

study (Table 2.1; Figure 2.1). Hornito and Alto Frio typically have 1–2 months per year with

<100 mm of precipitation; in contrast, no months with <100 mm of rainfall have been recorded

over the seven-year period for which records are available at Honda A and Honda B (Andersen

et al. 2012, J. Dalling unpublished data).

In addition to differences in rainfall, these sites differ markedly in soil characteristics,

with contrasting pH, N, P and base cation availability (Table 2.1). These distinctive soil traits are

related to underlying geology: low-fertility Ultisols at Honda A and Honda B are derived from

rhyolite, whereas high fertility soils at Hornito (Ultisol) and Alto Frio (Inceptisol) are derived

from dacite and andesite (Andersen et al. 2012, B. Turner unpublished data). Sites differing in

soil fertility are ca. 6 km apart, with 200 m separating the two low fertility sites (Honda A and B)

and 1 km separating the two high fertility sites (Hornito and Alto Frio). A third soil type of

intermediate fertility derived from andesite separates the high and low fertility sites in this study,

and does not support populations of Oreomunnea (Andersen et al. 2010). Characteristics of our

study sites are shown in Table 2.1, and methods for distinguishing potential effects of spatial

proximity, fertility, and rainfall on community structure of EM fungi are described below.

Sampling of ectomycorrhizas

Root tips of Oreomunnea were collected at all sites between January and July 2012

(Table 2.2). At Honda A, Honda B, and Hornito, samples were collected from a total of 44

individuals per site: four adults per site (mean DBH = 50 cm) located > 50 m apart; five

seedlings (5 – 20 cm height) within 20 m of each adult; and five saplings (40 – 100 cm height)

within 20 m of each adult. The area where the trees were sampled was approximately 4500 ±

3500 m2 per site. Adults and juveniles of Oreomunnea were less common at Alto Frio, such that

17 individuals were sampled there (four adults, nine seedlings, and four saplings).

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Five lateral roots were excavated 2–3 m from the trunk of each adult tree until fine roots that

were clearly connected to the tree were found. From each adult we collected up to 50 cm of total

root length representing multiple root branches. All roots obtained from adult trees were included

in field collections even if EM fungal infection was not visible macroscopically. The entire root

system of each focal seedling and sapling was collected.

Roots were stored in plastic bags and refrigerated within 2 h of collection. Each sample

was carefully cleaned with tap water, cut into 1 cm pieces, and observed with a dissecting

stereoscope. Three 1 cm pieces with EM structures were collected haphazardly from each sample

and preserved in 95% alcohol at 4˚C for DNA extraction. Infection frequency was calculated for

each sample as the number of root tips among 10 haphazardly chosen 1 cm fragments with

presence of an EM mantle observed under a dissecting microscope.

Molecular analysis

Molecular analyses followed Peay et al. (2011) with slight modifications. Genomic DNA

was extracted from EM root tips and the internal transcribed spacers and 5.8S rDNA of fungal

associates was amplified directly using the REDExtract–N–Amp plant PCR kit (following the

manufacturer’s instructions; Sigma-Aldrich) with primers ITS1F and ITS4 or ITS4B. PCR

conditions consisted of 95˚C for 1 min, and then 35 cycles of 95˚C for 30 sec, 52˚C for 30 sec,

and 72˚C for 45 sec, with a final extension time at 72˚C for 10 min. PCR amplicons were

visualized on 1.5% agarose gel stained with ethidium bromide or SYBR Green. Positive products

were cleaned using ExoSap–IT (Affymetrix; Santa Clara, CA, USA: 1.5 uL Exosap, 7.5 uL PCR

product) and sequenced bidirectionally using the Applied Biosystems BigDye Terminator v3.1

cycle sequencing kit and the original PCR primers on an Applied Biosystems 3730xl DNA

Analyzer (Foster City, CA, USA) at the University of Arizona Genetics Core (UAGC).

Sequences were assembled and quality scores were assigned using phred and phrap (Ewing and

Green 1998; Ewing et al. 1998) with orchestration by Mesquite v. 1.06

(http://mesquiteproject.org), and then manually verified and edited in Sequencher 5.1 (Gene

Codes Corporation, MI, USA) following U’Ren et al. (2012). Sequences were assigned to

operational taxonomic units (OTUs) using a 97% sequence similarity cutoff (see Smith et al.

2007a, Hughes et al. 2009) with Sequencher 5.1 (see Arnold et al. 2007, U’Ren et al. 2009).

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Statistical analyses

Two-way ANOVA was used to assess the effect of developmental stage (seedling,

sapling and adult) and site (Honda A, Honda B, Hornito and Alto Frio) on infection frequency.

An alternative model was also assessed where sites were grouped into high fertility/low rainfall

sites (Hornito and Alto Frio) and low fertility/high rainfall sites (Honda A and B). Species

accumulation curves were used to compare OTU richness among developmental stages and sites.

Total species richness was estimated using the bootstrap estimator (Smith and van Belle 1984;

U’Ren et al. 2012). Singleton OTUs were excluded to provide a robust data set to compare the

diversity of EM fungal communities among sites and host developmental stages.

To explore broader patterns of EM fungal diversity we compiled records from EM fungal

inventories of temperate and tropical forests, including studies reviewed by Tedersoo et al.

(2012) and three more recent studies Diédhiou et al. (2014), Smith et al. (2013), and Kennedy et

al. (2012). We calculated diversity for data presented in each study using Fisher’s alpha, which is

robust to differences in sample size and compared temperate vs. tropical forests using a one-way

ANOVA.

Differences in EM fungal community composition among sites and developmental stages

were visualized by Nonmetric Multidimensional Scaling (NMDS). Only nonsingleton OTUs

were used in these analyses, allowing us to evaluate the distributions of the more common

species while reducing the potential for rare species, whose occurrence in the dataset may be

influenced by undersampling, to influence inferences about composition. Nonetheless, results

with and without singletons were very similar (results not shown). NMDS analyses were based

on Bray-Curtis dissimilarity matrices using abundance and presence-absence data. Significance

of visualized differences was determined using permutational analyses of dissimilarity

(ADONIS) using 200 permutations and a Euclidean distance matrix (Oksanen et al. 2008).

Because location, soil fertility, and rainfall patterns were correlated in this study, we used

a statistical approach to explore the interplay of these factors with regard to observed community

structure. A Mantel test based on 999 permutations first was used to examine the relationship of

species community composition to geographic distance among sites. However, geographic

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proximity also reflected environmental similarity (Figure 2.1, Table 2.1). Therefore, a principal

component analysis (PCA) was used to reduce 14 environmental variables (see Table 2.1) to two

axes (describing 62.56% and 15.30% respectively of the total variance). Environmental variables

included in the PCA were site-specific annual rainfall from May 2012–April 2013, and soil

characteristics: bulk density (g cm-3), total C, inorganic N, and P (mg cm-3), NaOH–EDTA

inorganic P (µg cm-3), NaOH–EDTA organic P (µg cm-3), resin P (µg cm-3), NH4 (µg cm-3), NO3

(µg cm-3), K2SO4 extractable organic C (µg cm-3), and base cations Al, Ca, and K (cmol L-1). The

first two of the resulting PCA axes were used in a NMDS analysis, with correlation coefficients

between the PCA axes and the NMDS axes identifying differences between sites with

contrasting fertility and rainfall patterns (Ter Braak 1995). All statistical analyses were carried

out using the package vegan 2.0-6 in R 2.15.1 (R Development Core Team 2011).

Taxonomic placement

Taxonomic placement of OTUs was estimated by comparisons via BLAST with

GenBank (blastn; Altschul et al., 1990) and the UNITE database (Kõljalg et al. 2013). The

databases gave matching results with high confidence at the genus level for 92% of sequences

(Table 2.5). The remaining 8% of sequences showed <50% query length and were left as

undetermined (19 sequences representing 12 OTUs). Sequences that matched named sequences

at 91%–97% identity in GenBank and UNITE were identified only to genus. Genus names were

only assigned to OTUs when all sequences within the OTU returned the same genus name after

BLAST/UNITE searches. For Russula, species-level taxonomic placement of OTUs also was

informed by phylogenetic inference including GenBank sequence data from vouchered and

identified specimens (see below).

Phylogenetic analysis of Russula species

Preliminary collections of fruiting bodies in the study area indicated that Russula was

common in the EM fungal community associated with Oreomunnea. Given that this genus is an

important component of many EM fungal communities in the tropics (Peay et al. 2010; Smith et

al. 2011; Tedersoo et al. 2011) and appears to shift in community composition with changes in

soil N availability (Avis 2003, Avis et al. 2008, Lilleskov et al. 2002), it was chosen to test

12

hypotheses concerning phylogenetic diversity. To augment data on Russula distribution obtained

from root tips, Russula fruiting bodies were collected every two weeks throughout the study

period from January 2012 to July 2012 along four 50 m × 4 m transects in each site. Transects

were established in Oreomunnea stands at the same sites from which root tips were sampled,

averaging 150 m (± 110 m) linear distance from root tip sampling points. Macromorphology of

fresh Russula fruiting bodies was recorded in the field, and a sample of tissue was preserved for

DNA extraction. Sequences from fruiting bodies were obtained as described above. Vouchers of

fruiting bodies are deposited at the University of Arizona Robert L. Gilbertson Mycological

Herbarium (MYCO-ARIZ).

To evaluate the structure of Russula communities as a function of Oreomunnea

developmental stage and soil fertility/rainfall level, we inferred phylogenetic relationships of the

genus using 109 sequences representing root tips and fruiting bodies collected in this study

(Table 2.6), and 32 sequences downloaded from GenBank. Sequences were selected from

GenBank only if they were obtained from vouchered and identified specimens, and if there was a

>90% BLAST match with one or more sequences from the study site. This approach permitted

us to select high-quality, fully identified sequences from GenBank to estimate taxonomic

placement of Oreomunnea-associated species. Four sequences from voucher specimens of

Stereum hirsutum (Willd.) Pers. (AY854063), Amylostereum laevigatum (Fr.) Boidin

(AY781246), Gloeocystidiellum porosum (Berk. & M.A. Curtis) Donk (AY048881), and

Bondarzewia montana (Quél.) Singer (DQ200923) were used for the outgroup following Miller

and Buyck (2002) and Buyck et al. (2008).

Sequences were aligned using MUSCLE (Edgar 2004). The resulting alignment was

edited using Gblocks 0.91b (Castresana 2002) to exclude positions that were poorly or

ambiguously aligned. The final data set consisted of 639 characters and 144 terminal taxa. The

tree was inferred using maximum likelihood analysis using the GTR+I+Gamma model of

evolution in GARLI 2.0 (Zwickl 2006). Support was assessed using 1000 bootstrap replicates.

The resulting phylogenetic tree was used as input for two subsequent analyses. First, we

calculated Faith’s phylogenetic diversity index (PD) using the package Picante 1.5-2 in R

(Kembel et al. 2010) to compare the phylogenetic diversity of Russula within each

13

fertility/rainfall environment (i.e., alpha diversity). Faith’s PD, defined as the sum of the branch

lengths connecting all taxa within a local community (Faith 1992), was calculated based on

random subsets of 19 OTUs (the smallest number of Russula OTUs recovered per site).

Second, UniFrac permutation analysis (Lozupone et al. 2006, 2010) was used to

determine whether the phylogenetic structure of communities differed in a manner consistent

with environmental filtering. For comparisons among communities associated with different

sites, soil fertility/rainfall conditions, or developmental stages of Oreomunnea, the lengths of

branches in the phylogeny that were unique to each community were calculated and compared to

50 permutations in which assignment of taxa to communities was randomized. If the

environment or developmental stage selects for fungi that share phylogenetically-conserved

traits, then we would expect communities from similar environments or stages to share more

branch length (i.e., be more closely related) than the random expectation (Lozupone et al. 2006).

Results

Ectomycorrhizal fungi were common in roots of Oreomunnea at all developmental stages

and sites at Fortuna, Panama. Seedlings, saplings, and adults of Oreomunnea did not differ

significantly in infection frequency (i.e., the percentage of root tips with visible EM infection)

(F2,160 = 2.69, P = 0.07), although a trend suggested somewhat lower incidence in seedlings

(Figure 2.2).

Infection frequency by EM fungi differed significantly among sites (F3,159 = 2.88, P =

0.04), reflecting a significantly higher infection frequency at Alto Frio than Honda B (Tukey

HSD P = 0.043). Consistent with the differences among sites, we observed significant

differences in infection frequency when the sites were grouped by soil fertility/rainfall (P =

0.0195; Figure 2.2). There was no evidence that variation in infection frequency reflected a

meaningful interaction of site and developmental stage (F6,151 = 0.16, P = 0.98).

Richness and diversity of EM fungi

In total, 473 mycorrhizal root tips were collected from adult trees, saplings, and

seedlings. Sequences obtained from 234 root tips (49.3%; Table 2.2) yielded 115 OTUs (Figure

14

2.3). Overall EM fungal diversity was high (Shannon-Wiener Index: H’ = 4.56; Simpson’s

Index: 1-D = 0.99, Fisher’s alpha = 89.5; Table 2.4; see also Figure 2.3).

Diversity of EM fungi was similar among developmental stages of Oreomunnea (Table

2.3, Figure 2.4). In contrast to our prediction, EM fungal diversity was similar among sites, with

no apparent relationship to soil fertility/rainfall (Table 2.3, Figure 2.4).

Community composition of EM fungi

Although the community of EM fungi was highly diverse, accumulation curves were

asymptotic once singletons were removed (Figure 2.4). Consistent with our prediction, we found

that communities of EM fungi did not differ as a function of Oreomunnea developmental stage

(F2,30 = 1.09, P = 0.34). Only one species (Laccaria sp. 4) was found in all sites. Six OTUs

occurred in at least three sites (Table 2.5). Overall community composition was most similar

between Honda A and Honda B, which shared 16 OTUs.

ADONIS revealed significant differences in EM fungal community composition among

sites (F3,29 = 1.81, R2 = 0.17, P = 0.005). NMDS suggested differences in the EM fungal

community as a function of soil fertility/rainfall: the low fertility/high rainfall sites (Honda A and

B) grouped separately from the high fertility/low rainfall sites (Hornito and Alto Frio) (Figure

2.5). However, the Mantel test also revealed a significant, positive correlation between

geographic proximity and community similarity (R = 0.61, P = 0.001). Because geographic

proximity is positively associated with environmental similarity in our study, the relative

importance of spatial and environmental factors is difficult to interpret. We therefore examined

the importance of environmental factors alone by evaluating correlations of PCA axes with

NMDS. Only the first PCA axis (PC1), was significantly correlated with the first two axes of the

NMDS (R2 = 0.69, P = 0.001; Figure 2.5). PC1 accounted for 62.5% of the variation in

environmental variables, and was negatively associated with soil fertility and positively

associated with annual rainfall. Correlation of the PCA axis with the NMDS suggests

environmental filtering driven by rainfall and/or soil fertility influences EM fungal community

composition in addition to geographic proximity.

15

Taxonomic placement of EM fungi

Overall 99% of sequenced root tips were colonized by EM fungi belonging to 13 lineages

sensu Tedersoo et al. (2010): /amanita, /byssocorticium, /boletus, /clavulina, /laccaria,

/cortinarius, /elaphomyces, /cantharellus, /coltricia, /inocybe, /russula-lactarius, /sebacina,

/tomentella-thelephora, and /tricholoma. The most OTU-rich lineages were /russula-lactarius (36

OTUs from 97 root tips), /tomentella-thelephora (25 OTUs from 39 root tips), /cortinarius (14

OTUs from 27 root tips), /boletus (10 OTUs from 12 root tips), and /laccaria (5 OTUs from 17

root tips). Three root tips were colonized by members of the Strophariaceae, Marasmiaceae, and

a genus of Atheliaceae considered to be saprotrophic; these were excluded from further analysis.

Russula, Tomentella, and Laccaria were present in all sites. Laccaria was especially

abundant in the high fertility/low rainfall sites (Table 2.5). Cortinarius was not observed in Alto

Frio and was rarely observed in Hornito (high fertility/low rainfall sites), but was abundant in

Honda A and B, making up 16% and 26% respectively of the total number of sequenced root

tips. Boletus and Clavulina were found only in low fertility/high rainfall sites (Honda A, Honda

B), but were not common.

The four most abundant OTUs represented Russula (16% of sequences). These included

one unidentified species (Russula sp. 2), Russula cyanoxantha (Russula sp. 3), Russula puellaris,

and Russula cf. pectinata (see Table 2.5 for information about OTU and taxonomic distributions

across sites). Russula spp. were found in association with roots of adults, saplings, and seedlings

(Figure 2.6).

Phylogenetic diversity of Russula

The most commonly found clades in our surveys included representatives from roots as

well as fruiting bodies (Figure 2.7). In some clades, BLAST matches were consistent with

estimated taxonomy based on phylogenetic analysis, but in other cases taxonomic placement at

the species level differed between the two approaches. For example, one of the more common

morphotypes is related to R. cyanoxantha, since sequences from this study form a clade with

identified vouchers from Hibbet (GQ452059) and Smith et al. 2007b (DQ974758).

16

Phylogenetic diversity of Russula did not differ as a function of fertility/rainfall (PDhigh

fertility/low rainfall = 2.15, PDlow fertility/high rainfall = 3.53, t = -0.9521, df = 2, P = 0.506) (Table 2.3). We

found no significant structure in the Russula phylogeny as a function of Oreomunnea

developmental stage (Figure 2.7), either when comparing adults and seedlings (UniFrac analysis,

P = 0.29) or seedlings and saplings (P = 0.73). However, consistent with our prediction, the

phylogenetic composition of Russula communities differed significantly among sites (P < 0.001)

and when sites were grouped according to fertility/rainfall (P < 0.001). Significant differences

were observed between Alto Frio and Honda A (P < 0.001), Alto Frio and Honda B (P < 0.001),

and Honda B and Hornito (P = 0.01 – 0.05), but not between sites with similar fertility/rainfall.

Discussion

This is the first detailed inventory of EM fungi associated with the widely distributed

neotropical tree Oreomunnea mexicana, and one of the few analyses of EM fungal community

diversity in a tropical montane forest. Ectomycorrhizal tree species that have been studied in

detail in the neotropics include Dicymbe corymbosa (Fabaceae), Pakaraimaea dipterocarpacea

(Dipterocarpaceae), Quercus crassifolia and Q. laurina (Fagaceae), and Coccoloba spp. (Henkel

2003, Miller et al. 2000, Morris et al. 2009, Smith et al. 2011, Smith et al. 2013, Tedersoo et al.

2010a). Our study adds new data for a representative of the Juglandaceae in an area of high plant

species richness, and dramatic local-scale differences in soil types and rainfall patterns.

Our results reveal that species diversity of EM fungi associated with Oreomunnea is high

despite the small spatial scale at which this study was carried out. In conjunction with other

inventories, our data suggest that tropical forest EM fungal communities can be as species-rich

as those found in temperate forests (i.e., Diédhiou et al. 2014, Henkel et al. 2012, Smith et al.

2011). A comparison of EM fungal diversity in root tips using Fisher's alpha showed no

significant difference between temperate forests (mean Fisher’s alpha = 46.87, SD = 55.23) and

tropical forests studied thus far (mean Fisher’s alpha = 47.06, SD = 52.65; F1,46 = 0, P = 0.992).

When comparisons were restricted only to angiosperms, the results still did not differ

significantly (temperate forests, mean Fisher’s alpha = 62.02, SD = 80.97; P = 0.618).

17

All of the major EM fungal clades sensu Tedersoo et al. (2010b) encountered in this

study have been reported previously in both temperate and tropical EM fungi inventories

(Tedersoo et al. 2011, Phosri et al. 2012, Smith et al. 2011, Peay et al. 2010, Diédhiou et al.

2014). Members of the /russula-lactarius, /cortinarius, and /tomentella-thelephora lineages were

particularly abundant, accounting for 72% of OTUs. An overall dominance by Russula has been

found in other EM fungal inventories in tropical forests (Tedersoo et al. 2011, Henkel et al. 2012,

Phosri et al. 2012, Smith et al. 2011, Peay et al. 2010, Diédhiou et al. 2014), suggesting that this

is an important taxonomic group to focus on in future biogeographic and systematics-based

studies.

Consistent with the few previous studies of EM fungal communities in tropical forests,

we observed strong community dissimilarity of EM fungi across sites. For example, in

Fabaceae-dominated forest in Guyana, Smith et al. (2011) found significant differences in EM

fungal species composition among 19 sites with an average inter–site distance of 689 m. Peay et

al. (2010) found significant clustering in community composition in sites with similar soil types

in dipterocarp-dominated forest in Lambir Hills National Park, Sarawak (Malaysia). Our results

suggest that variation in EM fungal communities at small spatial scales also may be a feature in

montane tropical forests, expanding the scope for local turnover to greatly enhance alpha and

beta diversity at small spatial scales.

Geographic distance and environmental similarity are confounded in our study area, as

the distance between sites within the same soil/rainfall characteristics was small (0.2–1 km)

compared to the distance between sites with different characteristics (6 km). However, our

analyses suggest an important role of environmental factors, here defined as soil fertility and

rainfall patterns, in potentially filtering community structure.

At present, our sampling is not sufficient to define the relative importance of soil fertility

vs. rainfall patterns in shaping EM fungal communities in Oreomunnea. In general, high rainfall

sites tend to have low nutrient availability due to increased leaching (Austin and Vitousek 1998);

however, variation in fertility in our sites is determined by differences in underlying geology.

Variation in fungal community composition may also in part be driven by dispersal limitation,

which also could underlie a significant Mantel correlation between geographic distance and

18

community dissimilarity. In spite of our inability to identify the exact environmental variables

that drive EM fungal beta diversity, our study suggests that abiotic factors can drive high levels

of species turnover in EM fungal communities that associate with the same host species.

Turnover in the EM fungal community as a whole was echoed by turnover in OTU

assemblages among sites in key fungal genera. For example, even when singletons were

removed, 14 of 21 Russula OTUs found at the high fertility/low rainfall sites were not found in

either of the low fertility/high rainfall sites. UniFrac results also showed significant differences

in the phylogenetic relatedness of Russula communities across sites consistent with

environmental filtering: Russula communities associated with the two high fertility/low rainfall

sites were less closely related with the ones found in low fertility/high rainfall sites than expected

by chance.

Temperate Russula, particularly from the subsection Foetentineae, tend to inhabit more

fertile habitats with relatively higher N availability (Avis 2003, Avis et al. 2012), and have been

reported to increase in abundance in response to N fertilization in permanent plots (N addition of

5.4 or 17 g N m−2 yr−1 in oak savanna, Avis et al. 2003). Several authors have also noted that EM

fungi associated with N-rich habitats may form less beneficial or parasitic relationships with

their hosts (Johnson et al. 1997, Egger and Hibbett 2004, Avis 2012). It is possible that less

beneficial EM fungi reduce the competitive advantage of Oreomunnea relative to co-occurring

tree species in the more fertile sites studied here (Table 2.1).

In contrast, all of the 14 species of Cortinarius observed here were found infecting root

tips at the low fertility/high rainfall sites. Cortinarius can extract N from organic sources under

conditions of low N availability (Taylor et al. 2000, Lilleskov et al. 2002, Avis et al. 2003). More

research on functional traits may help us understand the influence of fertility and rainfall on

fungal community composition, and its effect on associated plant communities.

We found that diversity and composition of EM fungal communities did not differ among

developmental stages of Oreomunnea. Strikingly, some of the most abundant Russula OTUs

were found in all stages, and UniFrac analyses revealed the similarity of Russula communities in

both adults and seedlings, and seedlings and saplings. A similar result was found in seedlings

19

and adults of EM tree species in Guinean tropical rain forest, where the OTUs infecting several

developmental stages were the most abundant in the EM fungal community (Diédhiou et al.

2010).

Russula as a candidate for ectomycorrhizal network effects in Oreomunnea

Indirect evidence consistent with the existence of EM networks in tropical forest comes

from experiments showing that hyphal exclusion increases the mortality and decreases the

growth rate of EM seedlings (McGuire 2007, Onguene and Kuyper 2002). However, no study

has yielded direct evidence of resource transfer (i.e., nutrients or water) to seedlings, nor

identified the EM fungal potentially involved in such transfer in tropical forest. Analyses of EM

fungal composition is important, as EM networks effects are unlikely to strongly impact

recruitment of host trees unless common EM fungal taxa infect both seedlings and adults. At

Fortuna, network effects on Oreomunnea might be more likely to occur at the low fertility/high

rainfall sites of Honda A and B, where seedling densities are exceptionally high, and seedling

mortality rates are low below crowns (Table 2.1). In our surveys, OTUs representing Russula

cyanoxantha, Russula sp3, Russula puellaris, and Russula cf. pectinata accounted for 24% of

sequences in the low fertility/high rainfall sites. Further studies should target whether resource

transfer to seedlings occurs via members of this group.

Although inventories of fruiting bodies and root tips of EM fungi have been made in oak-

dominated Central American montane forests (Halling and Mueller 2005, Mueller et al. 2006,

Morris et al. 2009), this is one of the first below-ground surveys of EM fungi in a tropical

montane forest and provides insight into the diversity of EM fungal species associated with

Oreomunnea across sites varying in fertility and in the amount and seasonality of rainfall. The

rationale for this project was to provide information for future experiments that will explicitly

test for the existence of mycorrhizal networks and their effects on Oreomunnea seedling

performance. This information will be useful to uncover the factors driving plant–soil feedback

and EM host tree dominance in tropical montane forests.

20

Figures and Tables

Figure 2.1. Upper panel, location of Fortuna Forest Reserve, Panama. Lower panel, sampling

sites at Fortuna: circles represent low fertility/high rainfall sites (Honda A and B) and triangles

represent high fertility/low rainfall sites (Hornito and Alto Frio). Reproduced with modifications

from Andersen et al. (2010)

!!

Honda&B Honda&A

Hornito

Alto&Frio

!!

!!

!!

!!

21

Figure 2.2. Infection frequency (i.e., percent of root tips visibly infected by ectomycorrhizal

fungi) in roots of Oreomunnea mexicana (A) adults, saplings and seedlings in (B) four study

sites in Fortuna, Panama. Error bars indicate the 95% confidence interval around the mean.

Honda A (HA) and Honda B (HB) are low fertility/high rainfall sites; Alto Frio (AF) and Hornito

(HO) are high fertility/low rainfall sites. Sample sizes (n) indicate the number of root tips

sequenced

0

10

20

30

40

50

60

Age

% in

fect

ion

Adults Saplings Seedlings

n=60 n=49 n=54

A

0

10

20

30

40

50

60

Site

% in

fect

ion

HA HB HO AF

n=44 n=45 n=44 n=30

B

22

Figure 2.3. Species (OTU) accumulation curves of EM fungi colonizing root tips of

Oreomunnea mexicana at Fortuna. OTUs were based on 97% sequence similarity. The analysis

includes all sequences obtained in the present study. The grey solid line indicates observed OTU

richness; dotted grey lines represent the 95% confidence interval around observed richness; the

black solid line indicates the bootstrap estimate of total species richness; the dashed black line

indicates the accumulation curve for nonsingleton OTUs.

0 50 100 150 200

050

100

150

Number of root tips

Num

ber o

f OTU

s

BootstrapObserved richness95 %CINonsingleton

23

Figure 2.4. Ectomycorrhizal species accumulation curves and 95% confidence intervals based

on nonsingleton OTUs derived from 97% sequence similarity. Upper panel: Accumulation

curves per site for Honda A, and Honda B, Hornito, Alto Frio. Lower panel: Accumulation

curves for three developmental stages: seedlings 5–20 cm in height, saplings 40–100 cm in

height, and adults.

0 10 20 30 40 50 60

010

2030

4050

Honda A

Number of root tips

Num

ber o

f OTU

S

0 10 20 30 40 50 60

010

2030

4050

Honda B

Number of root tips

Num

ber o

f OTU

S

0 10 20 30 40 50 60

010

2030

4050

Hornito

Number of root tips

Num

ber o

f OTU

S

0 10 20 30 40

010

2030

4050

Alto Frio

Number of root tips

Num

ber o

f OTU

S

0 20 40 60 80

010

2030

4050

60

Adults

Number of root tips

Num

ber o

f OTU

S

0 20 40 60 80

010

2030

4050

60

Saplings

Number of root tips

Num

ber o

f OTU

S

0 10 20 30 40 50

010

2030

4050

60

Seedlings

Number of root tips

Num

ber o

f OTU

S

24

Figure 2.5. Nonmetric multidimensional scaling (NMDS) plot showing differences in the EM

fungal community composition among sites that differ in fertility and rainfall (high fertility/low

rainfall: triangles, low fertility/high rainfall: circles). The first PCA axis of environmental

variables (PC1) was significantly correlated with compositional variation (R2 = 0.69, P = 0.00;

see text for further explanation). Stress = 0.116

-0.4 -0.2 0.0 0.2 0.4

-0.4

-0.2

0.0

0.2

0.4

NMDS1

NMDS2

HAHBHoAF

PC1H L

25

Figure 2.6. (A) Relative abundance of OTUs based on 97% sequence similarity. Columns in

black show OTUs infecting adults, saplings, and seedlings. (B) Relative abundance of fungal

genera

0

1

2

3

4

5

6 1 6 11

16

21

26

31

36

41

46

51

56

61

66

71

76

81

86

91

96

101

106

111

116

Abu

ndan

ce (%

)

EM fungal taxa (OTUs)

A

44.1

14.5 13.4 7.5 4.3 2.7 2.2 1.6 1.6 1.6 1.1 1.1 1.1 0.5 0.5 0.5 0.5 0.5 0.5

0

10

20

30

40

50

Abu

ndan

ce (%

)

EM genus

B

26

Fig. 2.7 Results of maximum likelihood analysis of Russula obtained from mycorrhizal root tips (by direct PCR) and fruiting bodies in Oreomunnea mexicana-dominated stands at Fortuna, Panama (bold font), and exemplar taxa chosen as described in the text. Thickened branches indicate ≥ 70% bootstrap support. Strains from root tips are annotated to indicate the life stage (seedling, sapling, adult), site (low fertility/high rainfall in blue font: HA, Honda A; HB, Honda B; high fertility/low rainfall in green font: HO, Hornito; AF, Alto Frio), name and accession number for the closest match to the sequence in GenBank, and sequencing code. Sequences from fruit bodies are annotated to indicate site (those listed previously; collections also were made at ZA, Zarceadero; see supplementary material), name and accession number for the closest match to the sequence in GenBank, and sequencing code.

Root•Adult•HB•KM594970-AC408/Russula cf. pectinata HQ604835Russula pectinatoides EU819493

Russula illota DQ422024 Root•Seedling•AF•KM594875-AC150/Russula illota HQ677769

Root•Seedling•AF•KM594873-AC148/Russula illota HQ677769Root•Seedling•AF•KM594874-AC149/Russula illota HQ677769

Fruiting body•ZA•KM594814-AC545/Russula cf. pectinata HQ604835

Russula pectinatoides EU598185Russula amoenolens GU222264

Fruiting body•HA•KM594828-AC572/Russula cf. pectinata HQ604835

Fruiting body•AF•KM594802-AC497/Russula illota HQ677769Fruiting body•AF•KM594804-AC507/Russula foetens FJ845427

Fruiting body•ZA•KM594794-AC334/Russula cf. foetens DQ422023Russula foetens FJ845427

Root•Seedling•HO•KM595042-AC262/Russula cf. pectinata HQ604835

Root•Adult•HO•KM594922-AC277/Russula cf. pectinata HQ604835

Root•Adult•HO•KM594926-AC282/Russula cf. pectinata HQ604835

Root•Seedling•HA•KM594896-AC210/Russula cf. pectinata HQ604835

Root•Adult•HA•KM594893-AC195/Russula cf. pectinata HQ604835

Root•Adult•HB•KM594907-AC237/Russula cf. pectinata HQ604835

Fruiting body•HO•KM594818-AC588/Russula eccentrica EU598163

Fruiting body•AF•KM594803-AC501/Russula eccentrica EU598163Fruiting body•AF•KM594807-AC518/Russula eccentrica EU598163

Root•Adult•AF•KM594890-AC190/Russula eccentrica EU598163Root•Adult•HO•KM594944-AC350/Russula eccentrica EU598163

Root•Adult•AF•KM594963-AC394/Russula eccentrica EU598163

Root•Sapling•HO•KM594933-AC302/Russula nigricans JQ711972Root•Seedling•AF•KM594871-AC145/Russula nigricans EU597075Fruiting body•AF•KM594808-AC520/Russula nigricans EU597075

Fruiting body•AF•KM594806-AC517/Russula subnigricans AB291748

Uncultured Russula JN168741

Uncultured Russula JN168752

Root•Adult•HB•KM594908-AC239/Russula compacta GU229820Fruiting body•ZA•KM594790-AC317/Russula sp. DQ778002

Russula cyanoxantha DQ974758

Fruiting body•HB•KM594786-AC270/Russula cf. cyanoxantha EU598166

Fruiting body•HA•KM594809-AC521/Russula sp. DQ777996



Fruiting body•HB•KM594787-AC271/Russula cf. cyanoxantha EU598166Fruiting body•HB•KM594799-AC431/Russula sp. DQ777996

Fruiting body•HA•KM594817-AC584/Russula cf. cyanoxantha EU598166


Root•Seedling•HB•KM595010-AC573/Russula sp. DQ777996





Root•Sapling•HA•KM594986-AC47B/Russula cf. cyanoxantha EU598166

Root•Sapling•HO•KM594931-AC296/Russula sp. DQ777996

Russula cyanoxantha GQ452059



Fruiting body•HB•KM594811-AC523/Russula sp. DQ777996

Root•Adult•HB•KM594978-AC450/Russula sp. DQ777996Root•Sapling•HB•KM594977-AC445/Russula sp. DQ777996

Fruting body•HO•KM594820-AC591/Russula cf. cyanoxantha EU598166

Root•Sapling•HO•KM594957-AC381/Russula crustosa EU598153Russula nitida EU598164

Root•Sapling•HB•KM594914-AC249/Russula sp. AF350057Root•Seedling•HA•KM594949-AC36/Russula crassotunicata DQ384580Root•Sapling•HA•KM594903-AC223/Russula crassotunicata DQ384580

Fruiting body•HO•KM594830-C581/Russula sp. DQ777996Russula variata EU819436

Root•Seedling•HO•KM594948-AC359/Russula sp. DQ777989

Root•Adult•HO•KM594881-AC158/Russula crenulata HQ604846Root•Seedling•HA•KM594991-AC494/Russula crenulata HQ604846

Root•Adult•HA•KM595054-C562/Russula crenulata HQ604846

Russula viscida FJ627039

Russula bicolor FJ845435

Root•Adult•HA•KM594998-AC537/Russula puellaris HQ604852

Root•Seedling•HB•KM594935-AC310/Russula puellaris HQ604852Root•Sapling•HB•KM594915-AC250/Russula puellaris HQ604852

Root•Sapling•HB•KM594918-AC257/Russula puellaris HQ604852

Root•Adult•HB•KM595051-AC442/Russula puellaris HQ604852Root•Adult•HA•KM595034-AC205/Russula puellaris HQ604852

Root•Adult•HB•KM595036-AC229/Russula puellaris HM189938

Fruiting body•HB•KM595014-AC72/Russula puellaris HQ604852Root•Sapling•HA•KM594904-AC225/Russula puellaris HQ604852

Root•Adult•HA•KM594992-AC495/Russula puellaris HM189941

Russula puellaris HQ604852

Russula fragilis JF899569Russula gracilis FJ845431

Russula odorata JQ888198

Fruiting body•AF•KM594821-AC603/Russula gracilis FJ845431Fruiting body•AF•KM594810-AC522/Russula puellaris HQ604852

Fruiting body•HO•KM594824-AC430/Russula sp. AY456357Fruting body•HO•KM594827-AC531/Russula sp. AY456357

Root•Sapling•HA•KM594901-AC221/Russula odorata JQ711877Root•Seedling•HB•KM594910-AC241/Russula odorata JQ711900

Russula puellaris HM189935

Fruiting body•ZA•KM594792-AC329/Russula sp. JF834367

Russula risigallina DQ422022Root•Sapling•HA•KM594898-AC215/Russula lutea HQ604848

Root•Adult•HA•KM594990-AC491/Russula cf. flavisiccans EU598156Fruiting body•HO•KM594816-AC580/Russula cf. flavisiccans EU598156

Russula xerampelina JF899571Russula paludosa GU373486

Fruiting body•HB•KM594785-AC269/Russula cf. favrei EF530934Fruiting body•HB•KM594800-AC434/Russula cf. favrei EF530934

Fruiting body•HO•KM594831-AC587/Russula sp. EU569264

Root•Adult•AF•KM595032-AC189/Russula rubellipes EU598175Root•Adult•HO•KM595043-AC288/Russula rubellipes EU598175Root•Sapling•HO•KM594946-AC357/Russula sp. EU598161

Fruiting body•AF•KM594825-AC503/Russula rubellipes 598175

Root•Seedling•HO•KM594887-AC173/Russula sp. EU598161Root•Sapling•HB•KM594976-AC441/Russula sp. EU598161

Fruiting body•HB•KM594788-AC272/Russula sp. EU598159

Root•Adult•HA•KM594993-AC504/Russula sp. EU598159

Root•Seedling•HA•KM594956-AC38/Russula sp. EU598159

Fruiting body•HB•KM594795-AC336/Russula sp. EU598159

Fruiting body•HA•KM594796-AC369/Russula sp. EU598159

Root•Seedling•HB•KM594975-AC427/Russula sp. EU598159Root•Sapling•HA•KM594902-AC222/Russula sp. EU598159

Fruiting body•HB•KM594813-AC528/Russula sp. EU598159Russula compacta EU598157

Root•Sapling•HB• KM595037-AC233/Russula solaris JN944007Root•Sapling•HA•594983-AC457/Russula occidentalis AY228349

Root•Sapling•HO•AC612/Russula sp. GU220376Fruiting body•ZA•KM594791-AC318/Russula sp. HQ604851Fruiting body•ZA•KM594793-AC331/Russula sp. HQ604851

Russula lepidicolor AY061687

Fruiting body•ZA•KM594783-AC132/Russula sp. EU569264Fruiting body•ZA•KM594789-AC305/Russula sp. EU569264

Root•Adult•AF•KM595025-AC100/Russula xerampelina HM240542

Root•Adult•AF•KM594837-AC624/Russula decolorans FJ845432

Russula subtilis GQ166871Fruiting body•HB•KM594822-AC52/Russula corallina JN944006

Russula subtilis EU598178Root•Adult•HA•KM594895-AC204/Russula olivacea AF418634

Root•Adult•HO•KM594942-AC345/Russula decolorans DQ367913

Russula integra HM189840

Root•Adult•AF•KM594833-AC615/Russula tenuiceps DQ974756Russula velenovskyi HM189951

Russula decolorans FJ845432

Fruiting body•ZA•KM594823-AC335/Russula sp. GU234030Fruiting body•AF•KM594826-AC511/Russula sp. GU234030

Russula xerampelina HM240542Russula sphagnophila AY061719

Russula firmula DQ422017

Stereum hirsutum AY854063Amylostereum laevigatum AY781246

Bondarzewia montana DQ200923Gloeocystidiellum porosum AY048881

Article title: Variation in ectomycorrhizal fungal communities associated with Oreomunnea mexicana (Juglandaceae) in tropical montane forests. Journal Mycorrhiza.Adriana Corrales1,4, A. Elizabeth Arnold2, Astrid Ferrer1, Benjamin L. Turner3, James W. Dalling1,3. 1) Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana-Champaign, IL 61801 USA. 2) School of Plant Sciences, University of Arizona, Tucson, AZ 85721 USA. 3) Smithsonian Tropical Research Institute, Apartado Postal 0843–03092, Republic of Panama.4) Corresponding author: Adriana Corrales- [email protected]

27

Table 2.1. Characteristics of the study sites at Fortuna Forest Reserve, Panama. Honda A and Honda B are low

fertility/high rainfall sites, and Hornito and Alto Frio are high fertility/low rainfall sites. Soil data are expressed in

volume basis due to large variation in bulk density among plots.

Site Honda A Honda B Hornito Alto Frio

Elevation (m) 1175 1266 1404 1176

Annual rainfall 2013 (mm) 6055 6440 1990 1895

Soil variables

Geology Rhyolite Rhyolite Dacite Andesite

NaOH–EDTA inorg. P (µg cm-3) 17.9 15.1 24.3 27.7

NaOH–EDTA org. P (µg cm-3) 73.4 60.8 122.7 248.8

NH4 (µg cm-3) 2.2 1.8 1.8 3.8

NO3 (µg cm-3) 1.2 0.4 1.2 2.6

K2SO4 extract. org. C (µg cm-3) 152.2 92.0 95.3 92.8

pH in water 4.63 3.63 5.76 5.62

Total N (mg cm-3) 2.92 2.39 2.87 4.72

Total C (mg cm-3) 43.9 40.9 35.0 51.1

Total P (µg cm-3) 180.6 127.7 280.2 503.0

Resin P (µg cm-3) 0.2 1.9 2.2 1.4

Bulk density (g cm-3) 0.11 0.13 0.39 1.00

Al (cmol L-1) 1.1 1.3 0.5 0.0

Ca (cmol L-1) 0.0493 0.1046 4.9381 8.4702

K (cmol L-1) 0.0241 0.0248 0.1834 0.1225

Light variables

Canopy openness (%) 6.66 7.90 8.70 9.32

Vegetation variables

Community basal area >10 cm

(m2/ha) 45.6 46.5 52.9 40.7

No. Oreomunnea seedlings/m2 9.9 7.8 0.7 0.2

28

Table 2.1 (continued)

Site Honda A Honda B Hornito Alto Frio

Annual seedling mortality rate

(%) 0.31 0.17 0.19 0.5

Oreomunnea adults /0.1 ha 31 79 71 42

Oreomunnea basal area >10 cm

(m2/0.1ha) 1.59 2.48 2.58 1.80

29

Table 2.2. Number of ectomycorrhizal root tips sequenced, root tips collected, individuals

sampled, and OTUs observed for each site in Fortuna, and each developmental stage of

Oreomunnea.

Site Honda A Honda B Hornito Alto Frio Total

Root tips sequenced / total root tips collected (individuals sampled)

Adults 22/48 (4) 17/33 (4) 30/57 (4) 25/49 (4) 94/187 (16)

Saplings 30/52 (20) 35/67 (20) 19/54 (19) 4/10 (5) 88/183 (64)

Seedlings 12/25 (20) 15/34 (20) 14/30 (20) 11/14 (9) 52/103 (69)

Number of OTUs

Adults 17 13 23 15 55

Saplings 26 25 18 4 59

Seedlings 11 13 12 7 39

30

Table 2.3. Diversity of the EM fungal community for each site and for all developmental stages of

Oreomunnea. Simpson and Shannon indexes are based on 99 randomizations and restricted to 24

samples per site and 42 samples per developmental stage (consistent with the minimum number of

samples recovered per site or stage; see Table 2.2). Faith’s phylogenetic diversity index (PD) was

calculated based on sampling 19 Russula OTUs per site.

Index Honda A Honda B Hornito Alto Frio Seedlings Saplings Adults

Simpson 0.94 0.94 0.95 0.94 0.97 0.97 0.97

Shannon 3.07 3.07 3.09 2.57 3.67 3.64 3.61

Fisher’s alpha 73.3 33.9 64.7 28.5 79.4 78.3 55.5

PD 0.87 0.99 1.33 0.98

31

Table 2.4 Comparison of the results of this study with other studies of ectomycorrhizal species in tropical and

temperate biomes (adapted from Tedersoo et al. 2012). Columns indicate latitude in degrees (Lat), longitude in

degrees (Lon), elevation in meters (Elev), dominant host lineage (Host), Mean Annual Precipitation in mm (MAP),

diversity (Fisher’s alpha), number of samples analyzed (N) and number of ectomycorrhizal species found in study

site (OTUs based on 97% sequence similarity).

Reference Country Lat Lon Elev Host MAP Fisher’s

alpha N

No.

Species

Corrales et al.

(this study) Panama 9˚02’91"N 82˚32’46” W 1000 Juglandaceae 4000 89.5 234 115

Diédhiou et al.

2014

Southern

Guinea

8˚51’ and

7˚60’ N

9˚31’ and

8˚49’ W

500–

1752 Fabaceae

2500-

3000 182.1 332 189

Diédhiou et al.

2010 Guinea 8°50' 60" N 9° 31' 01" W 600 Fabaceae 3000 16.9 370 53

Morris et al.

2009 Mexico 18˚36’ N 99˚36’ W

2450–

2550 Fagaceae

1200-

1500 27.1 8000 154

Phosri et al.

2012 Thailand

16° 51' 14”

N 100° 31' 4” E 160 Dipterocarpaceae 1250 38.3 194 69

Peay et al.

2010 Malaysia 4°19' 59" N

113°49' 59"

E 140 Dipterocarpaceae 3000 37.7 589 106

Smith et al.

2011 Guyana 5°16' 1.2"N

59° 50' 24"

W 710 Fabaceae 3866 34.5 1020 118

Tedersoo et al.

2007

The

Seychell

es

4° 41' 17" S 55° 29' 6" E 480 Dipterocarpaceae 3500 4.3 135 15

Tedersoo et al.

2010a Ecuador 0° 41' S 76° 24' 0" W 232 Caryophyllales 3081 20.4 105 37

Smith et al.

2013 Guyana 5˚26’21” N 60˚04’43” 800

Dipterocarpaceae

and Fabaceae

2000 –

>2400

mm

19.8 255 52

Temperate studies

Avis et al. 2003

USA 45°25′ N 93°10′ W 450 Quercus/ Corylus 790 20.7 648 72

Avis et al.

2008 USA

41˚ 37’51”

N 87˚05’13” W 206 Quercus 945 129.5 1333 314

32



alpha N

No.

Species

Bahram et al.

2011 Estonia 58˚17’ N 27˚19’ E 35 Populus 620 312.55 122 103

Bahram et al.

2012 Iran 36°27 N 51°06’ E

100–

2700 Several spp

237-

552 141.34 1755 367

Bergemann

and

Garbelotto

2006

USA 40˚00’30”N 123˚57’00”

W 580 Lithocarpus 1125 59.28 382 119

Courty et al.

2008 France 48˚75’N 6˚35’E 250 Quercus 744 48.3 180 75

Dickie et al.

2010

New

Zealand 43˚9’12”S 171˚43’48”E 1000

Pinus and

Nothofagus 1447 61.98 354 118

Douglas et al.

2005

(Lodgepole

pine site)

USA 44˚27’21”N 110˚29’34”

W 2430 Pinus contorta 510 13.43 5570 81

Douglas et al.

2005 (Mixed

conifer site)

USA 44˚27’21”N 110˚29’34”

W 2430 Several spp 510 4.93 5933 35

Gao and Yang

2010 China 27°50′N 99°24′ E 4300 Kobresia spp 2000 48.11 150 70

Ishida et al.

2007 Japan

35°56′−

35°57′ N

138°48′−138

°49′ E

1350–

1500 Several spp 1596 66.25 1396 205

Izzo et al.

2005 USA 36°58′N 119°2′W 2100 Several spp 1250 27.05 1105 101

Jones et al.

2008 Canada

50° 18' 43

N

125° 28' 29

W 37–160 Several spp 2240 31.48 138 53

Kennedy et al.

2003 USA 37°54′ Ν 122°37′ W 600 Several spp 1250 16.5 442 56

33



alpha N

No.

Species

Kennedy et al.

2012 USA 42°10′52N 122°43′85W 1082 Arbutus/Pinaceae 611 51.85 537 126

Kjøller and

Clemmensen

2009

Sweden 57° 56' 13° 47' 132–300 Pinaceae 582-

818 30.72 969 107

Krpata et al.

2008 Austria 46°33’ N 13°42’ E 578 Populus tremula 1297 7.28 12020 54

Lang et al.

2011

German

y

51°05’20”

N 10°31′24′′E 350 Several spp 670 14.83 94893 130

Lian et al.

2006 Japan 39°56′ N, 141°14′ E 360–380 Pinus densiflora 1145 5.67 5499 39

Mühlmann

and Peintner

2008a, 2008b;

Mühlmann et

al. 2008

Austria 46°50′ N 11°01′ E 2280–

2450 Several spp 6.86 10000 50

Nara 2006 Japan 35° 19'N 138° 11'E 1450–

1600 Several spp 4854

4.99 6698 36

Palmer et al.

2008 USA 43° 57'N 91° 2'W 275 Several spp 820

17.13 233 46

Parrent and

Vilgalys 2007 USA 35° 57'N 79° 7'W 130 Pinus taeda 1140 33.55 1787 134

Pena et al.

2010

German

y 47°59 ︎ N 8°45 ︎ E 800 Fagus sylvatica 776 31.03

At least

515 89

Richard et al.

2005 France 42°20′ N 8°49′ E Several spp 750 77.73 393 140

Richard et al.

2011 France

43° 44′ 29′′

N 3° 35′ 45′′ E 270 Quercus ilex 908 38.11 1147 131

Roy et al.

2013 France

41° 59'–

45° 46'N

0° 38'–9°

17'E Alnus spp 284 21.34 1178 86

34



alpha N

No.

Species

Ryberg et al.

2009 Sweden 68°21’N 18°30’E

1010–

1040

Dryas

octopetala, Salix

reticulata

850 27.08 389 74

Ryberg et al.

2010 Sweden 68°20’N 18°30’E 980 Several spp 847 13.50 154 34

Smith et al.

2004 USA 43.5°N 118.5°W

1600–

1700

Pinus ponderosa,

Cercocarpus

ledifolius

173 66.44 480 140

Smith et al.

2005 USA 45.4°N 117.3°W

1300–

1600 Several spp 642 92.25 543 178

Smith et al.

2007b, 2009;

Morris et al.

2008

USA 39°17′ N 121°17′ W 400–

600 Several spp 710 30.65 11590 182

Taniguchi et

al. 2007 Japan 35°32′N 134°13′E Several spp 1083 11.79 284 38

Tedersoo et al.

2003 Estonia 58°17′N 27°19′E 36 Several spp 620 43.22 85 47

Tedersoo et al.

2006 Estonia 58°27’ N 22°00’ N 8 Several spp 550 98.15 468 172

Toljander et

al. 2006 Sweden 64°39′ N 18°30′ E 235 Several spp 570 12.50 2442 66

Twieg et al.

2007 Canada

50°22'-

50°58'

118°32'–

119°23'

500–

1200

Pseudotsuga

menziesii, Betula

papyrifera

663 30.31 938 105

Walker et al.

2005 USA

35°02′29′′

N 83°27′16′′ W

Quercus rubra,

Q. prinus 1800 32.72 291 75

35

Table 2.5 Ectomycorrhizal fungi found in roots of Oreomunnea mexicana and their distribution among develpmental stages and sites in the Fortuna Forest Reserve, Panama. OTUs were assigned to species if all the sequences in the OTU had a percentage of match ≥97% with vouchered sequences in GenBank, to genus if >90%-97%, and to family if ≤90%. Identification of Russula was augmented by phylogenetic analysis. The most abundant OTUs are shown in bold. Developmental stage abbreviations: A: Adult, Sa: Sapling, Se: Seedling; site abbreviations: AF, Alto Frio; HA, Honda A; HB, Honda B; HO, Hornito.

OTU BLAST ID Family Developmental

stages Sites GenBank accession numbers Abundance A Sa Se

AF

HA

HB HO

Russula sp1 Russulaceae 1 x 1 KM594827 Russula puellaris Russulaceae 13 x x x 6 7 KM595056,

KM595014, KM595034, KM594904, KM595036, KM594915, KM594917, KM594918, KM594935, KM594998, KM595051, KM594992, KM595060

Laccaria sp1 Hydnangiaceae 5 x x 3 2 KM594869, KM594870, KM594962, KM594835, KM594856

Byssocorticium atrovirens

Atheliaceae 4 x 3 1 KM594883, KM594839, KM594841, KM594843

Cortinarius sp1 Cortinariaceae 4 x x 4 KM594909, KM595012, KM594834, KM594845

Cortinarius sp2 Cortinariaceae 1 x 1 KM594851 Thelephoraceae sp9 Thelephoraceae 4 x x x 1 3 KM594953,

KM595004, KM594853, KM594857

Russula sp2 (cyanoxantha)

Russulaceae 7 x x x 1 5 1 KM594986, KM594931, KM594977, KM594978, KM595010, KM595061, KM594854

36




AF

HA

HB HO

Russula sp3 Russulaceae 12 x x x 8 1 3 KM594858, KM594867, KM594872, KM594891, KM594967, KM594969, KM595008, KM595058, KM595059, KM595063, KM595064, KM595065

Clavulina sp1 Clavulinaceae 4 x x x 1 3 KM594984, KM594987, KM594861, KM594862

Russula nigricans Russulaceae 1 x 1 KM594871 Hydnum sp1 Hydnaceae 3 x 3 KM594876,

KM594877, KM594880

Tomentella sp1 Thelephoraceae 4 x x x 3 1 KM594884, KM594900, KM595006, KM594988

Russula sp5 Russulaceae 5 x x x 1 1 3 KM594887, KM595032, KM595043, KM594946, KM594976

Laccaria sp2 Hydnangiaceae 2 x x 1 1 KM594892, KM595048

Russula cf. pectinata Russulaceae 8 x x 2 1 5 KM594893, KM594896, KM594907, KM595041, KM595042, KM594922, KM594926, KM594927

Boletaceae sp Boletaceae 4 x 3 1 KM594960, KM594899, KM594937, KM595001

Russula crassotunicata Russulaceae 2 x x 2 KM594949, KM594903

37




AF

HA

HB HO

Boletus cf. innixus Boletaceae 3 x 3 KM594906, KM594913, KM594919

Russula sp6 Russulaceae 4 x x x 3 1 KM594956,

KM594902, KM594975, KM594993

Fungal sp. JK-02M 2 x x 2 KM594924, KM594932

Boletus sp Boletaceae 1 x 1 KM594940 Russula eccentrica Russulaceae 3 x 2 1 KM594890,

KM594944, KM594963

Tomentella bryophila Thelephoraceae 3 x 2 1 KM594952, KM594965, KM594885

Cortinarius sp3 Cortinariaceae 4 x x x 1 3 KM595015, KM595039, KM595053, KM594971

Cortinarius obtusus Cortinariaceae 6 x x 2 4 KM595013, KM595023, KM595024, KM594972, KM594996, KM594838

Cortinarius herpeticus Cortinariaceae 1 x 1 KM594989 Laccaria sp3 Hydnangiaceae 3 x 1 2 KM594912,

KM595040, KM594982

Laccaria sp4 Hydnangiaceae 6 x x 1 1 2 2 KM595030, KM594925, KM595045, KM594997, KM595049, KM594848

Russula sp8 Russulaceae 4 x x 1 3 KM595005, KM595057, KM594865, KM594995

Cortinarius sp4 Cortinariaceae 3 x x 1 2 KM595022, KM594938, KM595007

Russula sp9 Russulaceae 2 x x 2 KM595025, KM595029

Boletus sp1 Boletaceae 1 x 1 KM595033

38




AF

HA

HB HO

Lactarius leonardii Russulaceae 2 x 2 KM594941, KM594847

Chalciporus aff. rubinellus

Boletaceae 1 x 1 KM594868

Phylloporus centroamericanus

Boletaceae 2 x x 1 1 KM594879, KM594911

Russula crenulata Russulaceae 3 x x 2 1 KM594881, KM595054, KM594991

Thelephoraceae sp. Thelephoraceae 3 x x x 1 2 KM594860, KM594936, KM594974

Tomentella sp. Thelephoraceae 2 x 1 1 KM595011, KM594939

Russula decolorans Russulaceae 2 x 2 KM594942, KM594943

Laccaria sp5 Hydnangiaceae 2 x 2 KM594950, KM594954

Octaviania asterosperma Boletaceae 2 x 2 KM594955, KM594958

Lactarius sp1 Russulaceae 4 x x 1 3 KM595028, KM595038, KM594934, KM595003

Elaphomyces sp. Elaphomycetaceae

2 x x 2 KM595018, KM595020

Amanita sp. Amanitaceae 1 x 1 KM595044 Cortinarius sp5 Cortinariaceae 1 x 1 KM594849 Leccinum sp. Boletaceae 1 x 1 KM594894 Russula illota Russulaceae 3 x 3 KM594873,

KM594874, KM594875

Russula odorata Russulaceae 2 x x 1 1 KM594901, KM594910

Russula sp10 Russulaceae 1 x 1 KM594908 Russula sp11 Russulaceae 1 x 1 KM594970 Russula cf. flavisiccans Russulaceae 1 x 1 KM594990 Cortinarius sp6 Cortinariaceae 1 x 1 KM594850 Tomentella sp2 Thelephoraceae 2 x x 2 KM594920,

KM594929 Russula sp13 Russulaceae 2 x 1 1 KM595037,

KM594983 Tomentella sp3 Thelephoraceae 2 x 2 KM594866,

KM594968 Thelephoraceae sp2 Thelephoraceae 2 x x 1 1 KM594928,

KM595009

39




AF

HA

HB HO

Lactarius cf. gerardii Russulaceae 1 x 1 KM594852 Sebacinaceae sp. Sebacinaceae 1 x 1 KM594864 Thelephoraceae sp3 Thelephoraceae 1 x 1 KM594973 Leratiomyces ceres Strophariaceae 1 x 1 KM594985 Inocybe sp1 Inocybaceae 1 x 1 KM595016 Rhodocollybia turpis Marasmiaceae 1 x 1 KM595017 Elaphomyces sp1 Elaphomycetace

ae 1 x 1 KM595019

Sebacina sp1 Sebacinaceae 1 x 1 KM595021 Tylopilus pseudoscaber Boletaceae 1 x 1 KM594859 Leptosporomyces galzinii Atheliaceae 1 x 1 KM595026 Russula variata Russulaceae 1 x 1 KM595027 Coltricia sp Hymenochaetac

eae 1 x 1 KM594863

Tomentella sp4 Thelephoraceae 1 x 1 KM595031 Amanita virosa Amanitaceae 1 x 1 KM594878 Tomentella sp5 Thelephoraceae 1 x 1 KM594882 Boletaceae sp Boletaceae 1 x 1 KM594886 Hydnum repandum Hydnaceae 1 x 1 KM594888 Elaphomyces sp2 Elaphomycetace

ae 1 x 1 KM594889

Russula olivacea Russulaceae 1 x 1 KM594895 Coltriciella dependens Hymenochaetac

eae 1 x 1 KM594897

Tomentella sp6 Thelephoraceae 1 x 1 KM595035 Russula lutea Russulaceae 1 x 1 KM594898 Cortinarius junghuhnii Cortinariaceae 1 x 1 KM594905 Russula sp16 Russulaceae 1 x 1 KM594914 Thelephoraceae sp4 Thelephoraceae 1 x 1 KM594916 Thelephoraceae sp5 Thelephoraceae 1 x 1 KM594921 Coltriciella dependens Hymenochaetac

eae 1 x 1 KM594923

Inocybe cicatricata Inocybaceae 1 x 1 KM594930 Lactarius sp2 Russulaceae 1 x 1 KM595046 Russula sp17 Russulaceae 1 x 1 KM594933 Tricholoma sulphureum Tricholomatacea

e 1 x 1 KM594945

Thelephoraceae sp6 Thelephoraceae 1 x 1 KM595047 Sebacina sp2 Sebacinaceae 1 x 1 KM594947 Russula sp20 Russulaceae 1 x 1 KM594948 Thelephoraceae sp7 Thelephoraceae 1 x 1 KM594951 Russula crustosa Russulaceae 1 x 1 KM594957 Russula sp21 Russulaceae 1 x 1 KM594959 Tomentella sp7 Thelephoraceae 1 x 1 KM594961 Cortinarius junghuhnii Cortinariaceae 1 x 1 KM594964 Cortinarius laetus Cortinariaceae 1 x 1 KM594966 Tomentella sp8 Thelephoraceae 1 x 1 KM594999

40




AF

HA

HB HO

Thelephoraceae sp8 Thelephoraceae 1 x 1 KM595000 Clavulina sp2 Clavulinaceae 1 x 1 KM595002 Cortinarius sp9 Cortinariaceae 1 x 1 KM595050 Cortinarius sp Cortinariaceae 1 x 1 KM595052 Byssocorticium sp Atheliaceae 1 x 1 KM594979 Tomentella sp9 Thelephoraceae 1 x 1 KM594980 Inocybe tubarioides Inocybaceae 1 x 1 KM594981 Cortinarius sp10 Cortinariaceae 1 x 1 KM594994 Russula sp26 Russulaceae 1 x 1 KM595055 Russula sp27 Russulaceae 1 x 1 KM594833 Tomentella sp10 Thelephoraceae 1 x 1 KM594836 Russula sp28 Russulaceae 1 x 1 KM594837 Tomentella sp11 Thelephoraceae 1 x 1 KM594840 Tomentella ramosissima Thelephoraceae 1 x 1 KM594842 Tomentella sp12 Thelephoraceae 1 x 1 KM594844 Tomentella sp13 Thelephoraceae 1 x 1 KM594846 Clavulina sp3 Clavulinaceae 1 x 1 KM594855

41

Table 2.6 Distribution of Russula from Oreomunnea root tips in Fortuna Forest Reserve, Panama. Columns indicate the GenBank number for sequences generated in this study; sequence code; tentative ID; sites, developmental stages, and fertility levels of origin; whether the sequence was obtained from a root tip (RT) or fruiting body (FB) in Oreomunnea stands; and the top BLAST match. Sequences referenced here were used in phylogenetic reconstruction for measures of phylogenetic diversity and UniFrac analyses. Site abreviations HA: Honda A, HB: Honda B, HO: Hornito, AF: Alto Frio, ZA: Zarceadero (not included for root tip collections). Developmental stage abbreviations: A: Adult, Sa: Sapling, Se: Seedling.

GenBank accession

#

Sequence Code OTU BLAST ID Site Fertility Developmental

stages Tissue Best match in BLAST

KM594949 AC36 Russula crassotunicata HA Low Se RT Russula crassotunicata KM594956 AC38 Russula sp6 HA Low Se RT Russula sp.

KM594986 AC47B Russula sp3 (cyanoxantha) HA Low Sa RT Russula cf. cyanoxantha

KM594822 AC52 Russula sp29 HB Low FB Russula corallina KM595014 AC72 Russula sp2 HA Low A RT Russula puellaris KM595025 AC100 Russula sp4 AF High A RT Russula xerampelina KM594783 AC132 Russula sp23 ZA FB Russula sp. KM594871 AC145 Russula nigricans AF High Se RT Russula nigricans KM594873 AC148 Russula illota AF High Se RT Russula illota KM594874 AC149 Russula illota AF High Se RT Russula illota KM594875 AC150 Russula illota AF High Se RT Russula illota KM594881 AC158 Russula crenulata HO High A RT Russula crenulata KM594887 AC173 Russula sp5 HO High Se RT Russula sp. KM595032 AC189 Russula sp5 AF High A RT Russula rubellipes KM594890 AC190 Russula sp7 AF High A RT Russula eccentrica KM594893 AC195 Russula cf. pectinata HA Low A RT Russula cf. pectinata

KM594784 AC198 Russula sp3 (cyanoxantha) HA Low FB Russula cf. cyanoxantha

KM594895 AC204 Russula olivacea HA Low A RT Russula olivacea KM595034 AC205 Russula sp2 HA Low A RT Russula puellaris KM594896 AC210 Russula cf. pectinata HA Low Se RT Russula cf. pectinata KM594898 AC215 Russula sp16 HA Low Sa RT Russula lutea KM594901 AC221 Russula sp11 HA Low Sa RT Russula odorata KM594902 AC222 Russula sp6 HA Low Sa RT Russula sp. KM594903 AC223 Russula crassotunicata HA Low Sa RT Russula crassotunicata KM594904 AC225 Russula sp2 HA Low Sa RT Russula puellaris KM595036 AC229 Russula sp2 HB Low A RT Russula puellaris KM595037 AC233 Russula sp14 HB Low Sa RT Russula solaris KM594907 AC237 Russula cf. pectinata HB Low A RT Russula cf. pectinata KM594908 AC239 Russula sp12 HB Low A RT Russula compacta KM594910 AC241 Russula sp11 HB Low Se RT Russula odorata KM594914 AC249 Russula sp17 HB Low Sa RT Russula sp. KM594915 AC250 Russula sp2 HB Low Sa RT Russula puellaris KM594918 AC257 Russula sp2 HB Low Sa RT Russula puellaris KM595042 AC262 Russula cf. pectinata HO High Se RT Russula cf. pectinata KM594785 AC269 Russula sp26 HB Low FB Russula cf. favrei

KM594786 AC270 Russula sp3 (cyanoxantha) HB Low FB Russula cf. cyanoxantha

42


GenBank accession

#



KM594787 AC271 Russula sp3 HB Low FB Russula cf. cyanoxantha KM594788 AC272 Russula sp6 HB Low FB Russula sp. KM594922 AC277 Russula cf. pectinata HO High A RT Russula cf. pectinata KM594926 AC282 Russula cf. pectinata HO High A RT Russula cf. pectinata KM595043 AC288 Russula sp5 HO High A RT Russula rubellipes voucher

KM594931 AC296 Russula sp3 (cyanoxantha) HO High Sa RT Russula sp.

KM594933 AC302 Russula sp18 HO High Sa RT Russula nigricans isolate KM594789 AC305 Russula sp23 ZA FB Russula sp. KM594935 AC310 Russula sp2 HB Low Se RT Russula puellaris voucher KM594790 AC317 Russula sp12 ZA FB Russula sp. KM594791 AC318 Russula sp24 ZA FB Russula sp. KM594792 AC329 Russula sp30 ZA FB Russula sp. KM594793 AC331 Russula sp24 ZA FB Russula sp. KM594794 AC334 Russula sp31 ZA FB Russula cf. foetens KM594823 AC335 Russula sp28 ZA FB Russula sp. KM594795 AC336 Russula sp6 HB Low FB Russula sp. KM594942 AC345 Russula sp10 HO High A RT Russula decolorans isolate KM594944 AC350 Russula sp7 HO High A RT Russula eccentrica voucher KM594946 AC357 Russula sp5 HO High Sa RT Russula sp. KM594948 AC359 Russula sp19 HO High Se RT Russula sp. KM594796 AC369 Russula sp6 HA Low FB Russula sp. KM594957 AC381 Russula crustosa HO High Sa RT Russula crustosa voucher KM594963 AC394 Russula sp7 AF High A RT Russula eccentrica voucher


KM594970 AC408 Russula sp13 HB Low A RT Russula cf. pectinata


KM594975 AC427 Russula sp6 HB Low Se RT Russula sp. KM594824 AC430 Russula sp27 HO High FB Russula sp.

KM594799 AC431 Russula sp3 (cyanoxantha) HB Low FB Russula sp.

KM594800 AC434 Russula sp26 HB Low FB Russula cf. favrei KM594976 AC441 Russula sp5 HB Low Sa RT Russula sp.

KM594977 AC445 Russula sp3 (cyanoxantha) HB Low Sa RT Russula sp.


KM594978 AC450 Russula sp3 (cyanoxantha) HB Low A RT Russula sp.

KM595051 AC442 Russula sp2 HB Low A RT Russula puellaris voucher KM594983 AC457 Russula sp14 HA Low Sa RT Russula occidentalis KM594990 AC491 Russula cf. flavisiccans HA Low A RT Russula cf. flavisiccans KM594991 AC494 Russula crenulata HA Low Se RT Russula crenulata KM594992 AC495 Russula sp2 HA Low A RT Russula puellaris voucher

43


GenBank accession

#



KM594802 AC497 Russula sp25 AF High FB Russula illota KM594803 AC501 Russula sp7 AF High FB Russula eccentrica voucher KM594825 AC503 Russula sp5 AF High FB Russula rubellipes voucher KM594993 AC504 Russula sp6 HA Low A RT Russula sp. KM594804 AC507 Russula sp33 AF High FB Russula foetens voucher KM594826 AC511 Russula sp28 AF High FB Russula sp.

KM594805 AC516 Russula sp3 (cyanoxantha) HA Low FB Russula sp.

KM594806 AC517 Russula sp34 AF High FB Russula subnigricans KM594807 AC518 Russula sp7 AF High FB Russula eccentrica voucher KM594808 AC520 Russula nigricans AF High FB Russula nigricans


KM594810 AC522 Russula sp27 HO High FB Russula puellaris voucher

KM594811 AC523 Russula sp3 (cyanoxantha) HB Low FB Russula sp.


KM594813 AC528 Russula sp6 HB Low FB Russula sp. KM594827 AC531 Russula sp1 HO High FB Russula sp. KM594998 AC537 Russula sp2 HA Low A RT Russula puellaris voucher KM594814 AC545 Russula sp13 ZA FB Russula cf. pectinata KM595054 AC562 Russula crenulata HA Low A RT Russula crenulata KM594828 AC572 Russula cf. pectinata HA Low FB Russula cf. pectinata

KM595010 AC573 Russula sp3 (cyanoxantha) HB Low Se RT Russula sp.



KM594830 AC581 Russula sp35 HO High FB Russula sp. KM594816 AC580 Russula cf. flavisiccans HO High FB Russula cf. flavisiccans


KM594818 AC588 Russula sp36 HO High FB Russula eccentrica voucher


KM594820 AC591 Russula sp3 (cyanoxantha) HO High FB Russula cf. cyanoxantha

KM594831 AC587 Russula sp23 HO High FB Russula sp. KM594821 AC603 Russula sp37 AF High FB Russula gracilis voucher KM595055 AC612 Russula sp20 HO High Sa RT Russula sp. KM594833 AC615 Russula sp21 AF High A RT Russula tenuiceps voucher KM594837 AC624 Russula sp22 AF High A RT Russula decolorans voucher

44

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Chapter 3: An ectomycorrhizal nitrogen economy facilitates monodominance in a neotropical forest2

Introduction

Tropical forests are renowned for high local species richness, often exceeding 100 tree

species ha-1 (Wright 2002). Nonetheless, exceptions to the general pattern of high-diversity and

low relative abundance exist throughout the tropics. These 'monodominant' communities, in

which a single tree species accounts for > 60% of basal area (Hart et al. 1989), include Dicymbe

corymbosa forests in Guyana, Gilbertiodendron dewevrei forests in central Africa, and some

dipterocarp forests in Southeast Asia (e.g., Dryobalanops aromatica¸ Shorea curtisii). Several

potential mechanisms that promote monodominance in tropical forest have been proposed, but a

general explanation remains elusive (Peh et al. 2011a).

Mechanisms to explain monodominance have focused either on the disturbance regime of

the forest, with low disturbance rates favoring competitive exclusion (Connell & Lowman 1989;

Hart et al. 1989), or on intrinsic traits of the species that confer a competitive advantage,

including low palatability to herbivores, slow rates of leaf litter decomposition, high seedling

shade-tolerance, and large seed size (Hart et al. 1989, Torti et al. 2001). However, a feature of

many monodominant species, both temperate and tropical, is that they form associations with

ectomycorrhizal (EM) fungi (Connell and Lowman 1989). Only 6% of neotropical tree species

are estimated to form associations with EM fungi, while 94% associate with arbuscular

mycorrhizal (AM) fungi (Table 3.1). In contrast, of the 22 tree species reported as

monodominant by Peh et al. (2011a), ten (45%) are EM and twelve (55%) are AM. As a

consequence, mechanisms have been sought that could account for how EM-associated plants

achieve monodominance at sites with similar soil conditions and disturbance regimes as those

2 This chapter appeared in its entirety in the Journal Ecology Letters and is referred to later in this dissertation as “Corrales et al. 2016b”. Corrales, A.; Mangan, S.A.; Turner, B.L.; and Dalling, J.W. 2016. An ectomycorrhizal nitrogen economy explains monodominance in a neotropical forest. Ecology Letters 19: 383–392. This article is reprinted with the permission of the publisher and is available from http://onlinelibrary.wiley.com/doi/10.1111/ele.12570/abstract and using DOI: 10.1111/ele.12570.

54

that support diverse communities of AM-associated trees (Connell and Lowman 1989, Dickie et

al. 2014).

Two mechanisms have been proposed for the EM facilitation of local monodominance.

First, EM networks consisting of hyphal connections linking plants could facilitate the transfer of

water, carbon (C), and nutrients from adults to seedlings (Simard et al. 2012). Ectomycorrhizal

networks are predicted to increase juvenile survival, disproportionately increasing their

abundance near adult trees (Teste et al. 2009, Simard et al. 2012). Consistent with this

hypothesis, seedlings of the monodominant species Paraberlinia bifoliolata in Cameroon, and

Dicymbe corymbosa in Guyana grew more slowly and died more frequently when isolated from

potential EM networks using exclosures (Onguene and Kuyper 2002, McGuire 2007). However,

these studies provided no direct evidence that EM networks transfer nutrients or photosynthate.

Moreover, neither study included a non-mycorrhizal plant species to assess exclosure effects

unrelated to mycorrhizal associations.

Second, recent reviews hypothesize that monodominance may arise through microbially

mediated positive plant-soil feedbacks (McGuire 2014). Plant-soil feedbacks (PSF) mediated by

EM fungi could lead to monodominance in two ways. First, the build-up of beneficial EM fungi

around adult host trees might favor the growth and survival of conspecific seedlings relative to

those of neighboring non-ectomycorrhizal seedlings. This positive plant-soil feedback is

expected to promote the dominance of EM plant species (Bever et al. 1997). Second, EM fungi

could weaken the strength of negative PSF produced by species-specific pathogens and increase

the survivorship rates of EM seedlings around conspecific adult trees (Bever 2003). Plant species

that exhibit weak negative feedbacks often dominate the community (Klironomos 2002, Mangan

et al. 2010), yet no experimental study has examined the strength of PSF in tropical EM tree

species.

In addition to network effects and altered plant-soil feedback, EM fungi might also

facilitate monodominance by altering N cycling, with detrimental effects on competing AM plant

species. Recent research has highlighted mycorrhizal association as an important functional trait

influencing species interactions and ecosystem processes (Phillips et al. 2013, Averill et al.

2014). Here we propose that EM associations facilitate monodominance via the "Microbial

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competition for N hypothesis" (referred to as the “organic nutrient-use hypothesis” in Dickie et

al. 2014). Ectomycorrhizal fungi have the enzymatic capability to access organic N directly from

soil organic matter, including the litter layer (Hobbie and Högberg 2012), implying that they

compete directly with saprotrophs for N (Orwin et al. 2011, Hobbie and Högberg 2012, Averill

et al. 2014). This enhanced competition is expected to reduce litter decomposition and N

mineralization rates in the presence of EM fungi compared to AM fungi (Connell and Lowman

1989, McGuire et al. 2010, Phillips et al. 2013). Slower decomposition rate and reduced N

availability could, in turn, favor EM plants when competing with AM plants (Orwin et al. 2011,

Phillips et al. 2013). Consistent with this hypothesis, lower concentrations of total N, ammonium

and nitrate have been reported below stands of monodominant forest relative to nearby mixed

forest (Torti et al. 2001, Read 2006, Brookshire and Thomas 2013, Dickie et al. 2014).

Here we evaluated these three potential mechanisms mediating monodominance in a

lower-montane tropical forest in Panama. We used a combination of field and growing house

experiments to test for mycorrhizal networks, plant-soil feedback, and changes in the N cycle in

forest dominated by Oreomunnea mexicana (Juglandaceae), a widely distributed EM tree species

that forms monodominant forest. We predicted that if dominance is promoted by mycorrhizal

networks, then disruption of hyphal networks would negatively affect Oreomunnea seedling

growth and survival and alter leaf tissue and leaf sugar C isotope ratios. In contrast, if dominance

is mediated by plant-soil feedback then we predicted that Oreomunnea seedling growth would

either be increased in the presence of soil inoculum from beneath Oreomunnea trees relative to

inoculum from competing species (positive PSF), or that the strength of negative PSF in the

presence of conspecific inoculum would be weaker for Oreomunnea than for competitors.

Finally, if dominance is mediated via the “Microbial competition for N hypothesis”, then we

predicted that mineral N supply would be reduced inside Oreomunnea-dominated forest, and that

bulk soil stable δ15N isotope ratio –an integrated measure of the N cycle– would be smaller

inside than outside Oreomunnea-dominated forest, indicating a tighter N cycle due to depletion

of N from the soil organic matter pool by EM fungi.

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Methods

Study site

The study was located in a primary lower montane forest (1000–1400 m a.s.l.) in the

Fortuna Forest Reserve in western Panama (hereafter Fortuna; 8°45 N, 82°15 W). Mean annual

temperature ranges from 19 to 22˚C, and annual rainfall from 5800 to 9000 mm (Andersen et al.

2012). Tree communities at Fortuna are diverse, containing between 61 and 153 species ha-1 ( >

10 cm DBH), with high compositional turnover reflecting variation in both rainfall and soils.

Oreomunnea mexicana is a canopy tree distributed between Mexico and Panama at elevations

from 900 to 2600 m. The distribution of Oreomunnea at Fortuna is patchy, with populations

occurring on both high and low fertility soils (Corrales et al. 2016a). On low fertility rhyolite-

derived soils, mixed forest is interspersed within Oreomunnea-dominated forest, where it

accounts for up to 70% of individuals and basal area (Andersen et al. 2010, Corrales et al.

2016a). Dominance by Oreomunnea appears unrelated to particular plant functional traits

previously associated with monodominance: foliar N, phosphorus (P), and C:N ratios are close to

community averages for the site (Adamek 2009) and seeds are small (approximately 100 mg).

However, Oreomunnea forms EM associations (Corrales et al. 2016a) in contrast to almost all

co-occurring tree species at Fortuna. Other EM tree species found at low abundance at the study

area are Quercus insignis, Q. cf. lancifolia, and Coccoloba spp.

Experimental assessment of EM network effects

We established a hyphal exclusion experiment to test whether Oreomunnea seedlings

benefit from EM hyphal connections to neighboring plants. Roupala montana (Proteaceae), a

non-mycorrhizal tree species that co-occurs with Oreomunnea, was used to assess the non-

mycorrhizal treatment effects of exclosures on seedling growth. Oreomunnea and Roupala

seedlings were planted in mesh exclosures inside and outside a ~25 ha Oreomunnea-dominated

forest. Individual seedlings were transplanted 2 m from each of 20 randomly selected

Oreomunnea trees (blocks) inside the Oreomunnea forest and 10 similar-sized heterospecific

trees 30 m outside the edge of the forest. Nearest-neighbour focal trees inside the Oreomunnea-

dominated forest were on average 40 m apart; trees outside were on average 45 m apart.

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Treatments consisted of: 1) fungal hyphal exclosures with 0.5 µm mesh to prevent

seedlings from connecting to EM networks; 2) root exclosures with 35 µm mesh to exclude roots

of neighboring plants, but allow hyphae access to the transplanted seedling (this treatment was

used to assess the effect of reduced root competition in the analysis of EM network effects); 3)

transplants without an exclosure, to assess the effect of soil disturbance on seedling growth (the

seedlings and surrounding soil was removed and replaced in a similar way to treatments 1 and 2);

4) control: A naturally occurring Oreomunnea seedling of similar size growing next to the other

treatments, but left untouched for comparison (inside Oreomunnea forest only). A total of 202

seedlings were established, 112 Oreomunnea (30 replicates × 3 exclosure treatments, and 22

control seedlings) and 90 Roupala (30 replicates × 3 exclosure treatments, no control). Mesh

exclosures were assembled following Nottingham et al. (2010) from 16 cm diameter, 20 cm deep

PVC piping, perforated along the sides and covered on the bottom and sides with the nylon mesh

corresponding to each treatment (Plastok, Birkenhead, UK).

Seedlings were transplanted from a nearby forest into the exclosure treatments between

August and October of 2013 and grown for 297 to 345 days. Previous studies that have reported

effects of EM networks on seedling mortality and RGR grew plants for between 5 and 12 months

(Onguene and Kuyper 2002, McGuire 2007). We therefore expected that 10 to 11 months would

be sufficient time to detect differences in our experiment. Seedlings were harvested and the

relative growth rate (RGR, mg g-1day-1) was calculated as the natural log of final dry mass minus

the natural log of initial dry mass divided by the number of days in the experiment. To estimate

initial seedling biomass 20 and 15 seedlings of Oreomunnea and Roupala from outside of the

experiment were harvested, and height, leaf number, and leaf area measured to develop biomass

models (Table 3.2). In a subset of the surviving Oreomunnea seedlings growing inside (n = 32)

and outside (n = 8) a sample of root tissue was saved to evaluate EM colonization by clearing in

10% KOH and staining with trypan blue. Colonization of 10 randomly chosen 2.0-cm root

sections per seedling was assessed using the grid-line intersect method (McGonigle et al. 1990).

Fresh leaf tissue was frozen immediately in liquid N for isotopic analysis. In tropical trees with

long leaf life spans, foliar isotope ratios can reflect nutrient uptake over months or years, and

may mask any signal of fungal C dependency (Hynson et al. 2012). We therefore analyzed leaf

soluble sugars, which represent recently acquired C. Sugars were extracted using ion exchange

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resins for sugar purification following Hynson et al. (2012). In addition, leaf tissue from a subset

of the surviving Oreomunnea seedlings growing inside (n =16) and outside (n = 12)

Oreomunnea-dominated forest was analyzed for C and N concentrations and stable isotope ratios

(δ13C and δ15N) by continuous flow isotope ratio mass spectrometry using an elemental analyzer

(Costech 4010) coupled to a Delta-V Advantage isotope ratio mass spectrometer (Thermo Fisher

Scientific, Bremen, Germany). Run precision for δ13C and δ15N was typically < 0.2‰.

Plant-soil feedback experiment

To determine whether Oreomunnea shows positive or negative PSF compared with co-

occurring species, seedlings of five tree species were grown in a fully factorial greenhouse

experiment. The species included were two EM plant taxa, Oreomunnea mexicana

(Juglandaceae) and Quercus insignis (Fagaceae), and three AM species, Guarea pterorhachis

(Meliaceae), Cupania seemannii (Sapindaceae), and Nectandra purpurea (Lauraceae). Species

were chosen based on seed availability and contrasting abundance in permanent 1-ha forest plots.

Species relative abundance of individuals with a diameter at breast height (DBH) >10 cm ranged

from 0.3% for Quercus to 7.7% for Oreomunnea.

Seedlings were grown in different soil treatments: each species was grown either in their

own soil inoculum ("conspecific" soil treatment), where pots received an inoculum of live soil

from underneath conspecifics representing 6% of the total soil volume (120 cm3), or in pots

inoculated with live soil from one of each of the other four species separately ("heterospecific"

soil treatment). Seven seedlings of each species were grown in each of the "heterospecific"

treatments and 10 were grown in the "conspecific" treatment. To control for differences in

abiotic conditions associated with the live soil, two additional replicates of each treatment were

established in which the inoculum was sterilized (Figure 3.7). A total of 240 sampling units were

used for the full experiment ("heterospecific" treatments = 5 species × 4 inoculum types × 7

replicates = 140 seedlings; "conspecific" treatments = 5 species × 10 replicates = 50 seedlings;

sterilized inoculum controls = 10 replicates × 5 species = 50 seedlings).

Between June and October 2013, seeds of the five species were collected from the forest

floor, surface sterilized with 1% NaClO and grown in sterile sand for 2 months prior to the start

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of the experiment. Oreomunnea seeds were also soaked in 1% HCl for 1 hour prior to planting to

break dormancy. Each species was grown in a 2-L pot (14 cm × 11 cm × 13 cm depth) filled with

steam-pasteurized soil collected from three relatively nutrient-rich sites in the Fortuna Reserve.

Seedlings were planted during November and December 2013 and grown under 18% full sun in

a growing house at Fortuna Forest Reserve. Inoculum was collected from underneath five adult

individuals of each species (about 500 g of soil per tree) and inoculum from each tree used

separately to keep track of individual inoculum sources. Nectandra seedlings were grown for 3

months, while the remaining species were grown for 5 to 6 months depending on growth rate.

Plants were watered once or twice per week and did not receive additional nutrients.

At harvest a subsample of root tissue was saved to evaluate EM colonization using the

same method described above. The roots of all plants were washed and all plant parts were dried

at 70°C for 48 h and weighed to quantify total biomass. To calculate leaf area, photographs of all

fresh leaves of each plant were analyzed using ImageJ (Schneider et al. 2012). For individual

plants, the RGR was calculated as above. Leaf Area Ratio (LAR) was calculated by dividing

total leaf area by total biomass. To estimate the initial seedling biomass 14 to 20 seedlings per

species were harvested, and height, number of leaves, and leaf area measured to develop biomass

models (Table 3.2).

Nutrient availability and uptake inside and outside Oreomunnea-dominated forest

To determine whether Oreomunnea forest influences N cycling in a way that is consistent

with the “Microbial competition for N hypothesis”, we compared resin-extractable nitrate,

ammonium and phosphate inside and outside the same Oreomunnea-dominated forest used for

the EM exclosure experiment. Twenty resin bags containing 5 g of mixed-bed anion and cation

exchange resins (Dowex Marathon Mr-3) sealed inside 220 µm polyester mesh were buried 2 cm

beneath the soil surface 0.5-1 m from 10 trees inside and 10 trees outside the Oreomunnea forest.

Bags were buried during August 2014 at the same locations where mesh cores were installed.

After incubation in situ for 18 days the resin bags were collected, rinsed with deionized water to

remove adhering soil, extracted with 75 mL of 0.5 M HCl, and then nitrate (+nitrite),

ammonium, and phosphate were determined by automated colorimetry on a Lachat QuikChem

8500 (Hach Ltd., Loveland, CO, USA). In addition, soils collected inside (n =10) and outside (n

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= 8) Oreomunnea forest were analyzed for C and N isotope ratios and total concentrations as

described above using a Flash HT analyzer (Thermo Scientific, Waltham, MA, USA).

Finally, we examined whether there was a relationship between tree abundance and soil

properties. Abundance was calculated for the two EM tree species (Oreomunnea mexicana and

Quercus insignis) and the four most abundant AM tree species (Ardisia sp., Dendropanax

arboreus, Cassipourea guianensis, and Eschweilera panamensis) as the sum of individuals >5

cm DBH in 20 × 20-m sub-plots located in two permanent 1-ha forest plots at the study site (n

=18 sub-plots; plots = Honda A and Honda B in Andersen et al. 2010). Soils data specific to

each sub-plot were collected in 2008 to 10 cm depth, and included soil ammonium (µg N g-1 soil

dry mass), nitrate (µg N g-1), total N (%), total C (%), total P (µg P g-1), and litter mass (g m-2)

(Table 3.3).

Statistical analysis

For the mesh exclosure study, a two-way ANOVA was used to compare seedling RGR,

isotopic data, and EM colonization among treatments inside and outside Oreomunnea forest,

with location (inside versus outside) and mesh treatment (0.5 µm, 35 µm, transplant, and control)

as fixed effects and replicates (trees) as a random effect. The mortality rates of seedlings were

compared using contingency tables and a Chi-square test of independence. Resin extractable

nitrate, ammonium and phosphate were not normally distributed, and were compared between

locations (inside versus outside) using a Wilcoxon test.

We used ANCOVA to analyze the effects of inoculum source and plant species (and their

interaction) on plant growth using the SAS procedure PROC MIXED. Estimated initial biomass

was included as a covariate. Within this model, we used a priori contrasts to isolate the

inoculum source × species interaction of each possible pair of species (Bever et al. 1997) to

determine the strength and direction of plant-soil feedback. In the case where seedlings

performed better in conspecific inoculum relative to that of heterospecifics, the interaction

coefficient (i.e. pairwise feedback) would be positive. Average feedback strength of a given

species was then determined by averaging all pair-wise interaction terms that involved that

species (Bever et al. 1997). The relationship between tree species abundance and strength of

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average feedback was examined using linear regression. The relative abundance of each species

was calculated for trees >10 cm DBH in permanent plots established where the species inoculum

was collected (Oreomunnea mexicana = Honda A, Cupania seemannii and Nectandra purpurea

= Pinola, Quercus insignis and Guarea pterorhachis = Hornito) (J.W. Dalling personal

communication).

Soil extractable C, N and δ15N were compared inside and outside the Oreomunnea forest

using one-way ANOVA. The relationship between the number of trees or basal area in sub-plots

and soil variables in permanent plots was analyzed using a simple linear regression after (log+1)

transformation of the independent variable (individuals and basal area).

Results

EM network effects

From an initial total of 202 seedlings established in the experiment (112 Oreomunnea and

90 Roupala), 173 survived until the end of the experiment: 86 Oreomunnea and 87 Roupala. Of

the 86 surviving Oreomunnea seedlings, 70 seedlings grew inside and 16 outside Oreomunnea

forest. There were no significant effects of hyphal and root exclosure treatments on growth rate

of Oreomunnea seedlings, with the exception of faster growth in the root exclosure treatment

(0.35 µm mesh) compared to the control (undisturbed) treatment (F3,78 = 2.67, P = 0.05) when

including seedlings both inside and outside Oreomunnea forest (Figure 3.1A). Therefore,

excluding hyphae (0.5 µm mesh) did not reduce seedling growth as predicted. Roupala did not

show significant differences among treatments (F2,78 = 0.39, P = 0.68; Figure 3.1B).

Oreomunnea mortality was significantly lower inside (9%) versus outside Oreomunnea

forest (34%; n = 112, X2 = 19.8, df = 1, P < 0.001), but there was no significant difference in its

growth rate (F1,78 = 1.05, P = 0.31; Figure 3.1C). Roupala grew significantly faster outside

Oreomunnea forest (F1,78 = 6.02, P = 0.02; Figure 3.1D), but mortality rate did not differ (2%

inside and outside; n = 90, X2 = 0.13, df = 1, P = 0.71).

Overall, there was no significant difference in EM colonization of Oreomunnea seedlings

among treatments (F3,34 = 0.81, P = 0.50). However, the percentage of EM colonization of

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Oreomunnea seedlings was significantly higher inside than outside Oreomunnea forest (F1,38 =

13.71, P < 0.001; Figure 3.2), and there was a significant site × treatment interaction (F1,34 =

9.46, P = 0.004) driven by significantly lower EM colonization (F1,2 = 38.06, P = 0.03) among

the few surviving seedlings analyzed from the 0.5 µm mesh treatment outside Oreomunnea

forest.

There were no significant differences among treatments for seedlings growing inside the

Oreomunnea forest for δ13C of the extracted leaf sugars (F3,28 = 1.97, P = 0.14), or for δ13C (F3,12

= 1.02, P = 0.7, Figure 3.1E) or δ15N (F3,12 = 0.46, P = 0.98, Figure 3.1F) of leaf bulk tissue.

Oreomunnea seedlings growing inside Oreomunnea forest did not differ in foliar δ13C

(F1,23=1.15, P = 0.35, Table 3.4). However, seedlings growing inside Oreomunnea forest were

significantly depleted in foliar 15N compared with seedlings growing outside (F = 17.33, P <

0.001, Table 3.4) and had significantly greater foliar N concentration (F1,23 = 6.55, P = 0.02,

Table 3.4).

Plant-soil feedback experiment

Monodominance could arise if beneficial EM fungi are restricted to forest dominated by

Oreomunnea and provide a competitive growth advantage to Oreomunnea seedlings. If so, we

predicted that Oreomunnea would show positive PSF or weaker negative PSF effects relative to

co-occurring species. However, Oreomunnea showed the strongest negative PSF among species

in the experiment (Figure 3.3, Table 3.5), and the strength of negative PSF was significantly

positively correlated with species relative abundance (Figure 3.3).

Differences in seedling and soil nutrient status inside and outside Oreomunnea forest

There was significantly lower resin extractable ammonium (Wilcoxon test W = 19, P =

0.021) and nitrate (W = 9, P = 0.002) inside compared to outside the Oreomunnea forest (Table

3.4), but there was no difference in resin-extractable phosphate across the same sites (W = 38, P

= 0.31, Table 3.4). There were also significantly higher concentrations of total C (P < 0.001)

and total N (P = 0.001, Table 3.4), and a higher C:N ratio (P < 0.001; Table 3.4) in soils inside

compared to outside Oreomunnea forest. Soils inside Oreomunnea forest were significantly

depleted in 15N (P < 0.001; Table 3.4).

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The number of Oreomunnea individuals > 5 cm DBH in 20 × 20-m sub-plots in two 1-ha

plots was significantly negatively associated with the concentration of nitrate (R2 = 0.48, P <

0.001), and P (R2 = 0.21, P < 0.001) measured in the center of each subplot, but was not

significantly correlated with ammonium (R2 = 0.06, P = 0.15), total N (P = 0.79), total C (P =

0.65), or litter mass (P = 0.44, Figure 3.4). Results were similar when the regression analysis was

repeated using Oreomunnea basal area (Figure 3.5). Quercus insignis abundance was not

significantly correlated with any soil nutrients (Figure 3.6). However, all the most abundant AM

species were negatively associated with either ammonium or nitrate concentrations in the soil

(Table 3.6). Ardisia sp., Cassipourea guianensis, and Eschweilera panamensis were also

significantly positively correlated with the number of individuals or basal area of Oreomunnea

mexicana (Table 3.6).

Discussion

Here we provide the first simultaneous test of two prominent hypotheses to account for

monodominance in tropical forests. Our results suggest that neither the absence of negative PSF

nor the formation of EM networks can account for monodominance in our study system. Instead,

we provide evidence that Oreomunnea dominated forest is associated with lower availability of

soil ammonium and nitrate than nearby forest where Oreomunnea is infrequent or absent. This

reduced nutrient availability, presumably driven by depletion of readily mineralizable N from

soil organic matter by EM fungi, could confer Oreomunnea seedlings a competitive advantage

over AM or non-mycorrhizal species.

Plant-soil feedback and EM associations

Several authors have proposed that positive PSF experienced by EM plants underlie

monodominance in tropical forests (McGuire 2007, 2014). However, all of these studies identify

EM networks as the mechanism generating positive PSF. Here we differentiate microbially-

mediated PSF sensu Bever et al. (1997) from positive distance-dependent effects of EM

networks. To our knowledge, only two studies of microbially-mediated PSF have included EM

tree species, and in general negative feedbacks dominate over positive feedbacks (McCarthy-

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Neumann and Ibañez 2012, Liu et al. 2012). In our study, Oreomunnea showed the strongest

negative PSF among the species tested, despite its high local abundance. This result contrasts

with findings from lowland tropical forest and temperate grasslands, where more abundant

species show weaker negative PSF (Klironomos 2002, Mangan et al. 2010). This is the first PSF

experiment ever done including montane tree species and more research in this topic is needed to

conclude if this is a widespread phenomenon or just a peculiarity of our system. The reduced

RGR of Oreomunnea when grown in its own inoculum indicates that the negative effect of

Oreomunnea species-specific pathogens is stronger than any potential positive effects that might

arise from more beneficial inoculum sources.

Mycorrhizal network effects

Previous experiments that have tested for the presence of EM networks in tropical

monodominant forests reported higher growth and survival for seedlings in contact with the roots

of conspecifics and EM mycelium relative to those isolated in mesh exclosures (Onguene and

Kuyper 2002, McGuire 2007). In contrast, our results show no evidence of C or N transfer from

adults to seedlings through EM networks based on either changes in seedling growth or survival

in response to hyphal exclosure treatments. The only difference in growth rate among treatments

was higher RGR in seedlings grown in 35-µm mesh exclosures compared with control seedlings,

which was probably due to release from belowground competition with roots of other plants.

However, the fact that we used already established (and EM-infected seedlings in the

experiment) could have reduced the likelihood Oreomunnea seedlings joined existing EM

networks.

The leaves of plants connected to EM networks have an isotopic composition that is

distinct from fully photosynthetic plants (Selosse and Roy 2009, Hynson et al. 2012). If plants

receive sugars via EM networks then we would expect that leaf tissue, and in particular leaf

soluble sugars, would be enriched in 13C (Selosse and Roy 2009, Hynson et al. 2012). Here we

found no differences in the isotopic composition of leaf tissue among exclosure treatments,

further suggesting that no EM networks were formed in this system.

65

Instead, this study shows that seedlings growing inside Oreomunnea-dominated forest

had higher EM colonization, lower foliar 15N, and higher foliar N concentration. Previous studies

have found a correlation between δ15N in plants and the degree of EM fungal colonization

(Hobbie and Colpaert 2003). The presence of EM colonization alters host plant δ15N by

transferring 15N depleted compounds to the plant while sequestering 15N-enriched compounds in

fungal tissue (Hobbie and Colpaert 2003). In the case of Oreomunnea seedlings growing inside

Oreomunnea forest, the lower 15N of their leaves could have been partially due to lower 15N in

the soil. However, a decrease in foliar 15N has been observed in EM plants experiencing

increased N limitation (McLauchlan et al. 2010, Craine et al. 2015), associated with a higher

dependency on EM fungi (Craine et al. 2015). These results suggest that the patchiness of

Oreomunnea populations in part reflects reduced mycorrhizal infection outside Oreomunnea

forest. The lack of appropriate or compatible EM inoculum outside Oreomunnea patches could

have strongly reduced survivorship rates due to a reduced capacity of seedlings to compete for N

with larger AM trees (Nara et al. 2006).

Microbial competition for N as a mechanism facilitating monodominance in tropical forest

A reduction in the decomposition rate of litter, and an increase in organic matter

accumulation has been frequently noted under EM dominated forest (Torti et al. 2001, Orwin et

al. 2011, Phillips et al. 2013, Averill et al. 2014). The mechanisms underlying this effect are not

fully understood, although it has been proposed that direct competition for N between EM fungi

and the community of free-living decomposers could reduce litter decomposition rates (Read and

Perez-Moreno 2003, Orwin et al. 2011). Competition for nutrients is proposed to result in the

accumulation of organic matter depleted in N under EM dominated forest, resulting in a

reduction in nutrient availability for AM or non-mycorrhizal plant species, as well as microbial

heterotrophs, that rely to a greater extent on inorganic N sources (Phillips et al. 2013).

Ectomycorrhizal plants growing in soils with low available N may have a competitive advantage

over AM plants because EM fungi are able to acquire N directly from organic matter when

supplied with sugar from their host plant (Phillips et al. 2013, Lindahl and Tunlid 2015).

Lower N availability could reduce plant diversity (Dickie et al. 2014) and ultimately

drive monodominance in tropical forests (Figure 3.8). The differences in soil 15N in our system

66

along with the higher total C, reflects N limitation and an accumulation of soil organic matter

with a higher C : N ratio. We propose that N depletion from the soil organic matter by EM fungi

increases N limitation. This results in a tightened N cycle, and is consistent with low rates of

nitrification, denitrification and gaseous N losses from the soil organic layer of our study site

reported over two years of measurements (Koehler et al. 2009, Corre et al. 2010). Nitrification

and denitrification strongly discriminate against 15N, enriching the soil in 15N (Houlton et al.

2006). Therefore, soils with low resin extractable inorganic N, and presumably therefore low

mineralization rates, show reduced δ15N of the soil available N pool (Martinelli et al. 1999). This

is supported by the finding that the abundance of Oreomunnea, as well as the most abundant AM

tree species, was negatively correlated with inorganic N concentration in the soil in permanent

plots.

Several studies have found results consistent with our findings of lower availability of

inorganic N inside than outside monodominant forest (Read et al. 1995, 2006, Torti et al. 2001,

Brookshire and Thomas 2013). Further, studies that failed to find differences in soil nutrients did

not measure plant available ammonium or nitrate in the soil (i.e. Hart et al. 1989, Conway and

Alexander 1992, Henkel 2003, Peh et al. 2011b).

Finally, differences in N mineralization between EM and AM dominated forests may be a

consequence of intrinsic differences in litter quality between EM and AM associated plants.

However, using a global database of leaf functional traits, Koele et al. (2012) found no

relationship between leaf traits and mycorrhizal type after correcting by phylogenetic placement.

At Fortuna, Oreomunnea is close to the community average for leaf traits associated with

decomposition (foliar C : N, Adamek 2009) and δ15N (Mayor et al. 2014).

We conclude that changes in N availability due to the ability of EM fungi to acquire N

directly from organic matter is the likely mechanism underlying Oreomunnea monodominance

in our study system. This positive density-dependent mechanism creates patterns consistent with

previous evidence in EM tree species. Furthermore, the reduction in N availability may explain

the occurrence of other monodominant forests, including Dicymbe corymbosa in Guyana,

Gilbertiodendron dewevrei in central Africa, and dipterocarp species in Southeast Asia.

67

Figures and Tables

Figure 3.1 Relative growth rate (RGR) of Oreomunnea (A) and Roupala (B) seedlings among treatments; RGR of

Oreomunnea (C) and Roupala (D) seedlings inside and outside Oreomunnea forest; Oreomunnea seedling δ13C (E)

and δ15N (F) of leaf bulk tissue among treatments inside Oreomunnea-dominated forest. Exclosure treatment

abbreviations: 0.5 µm (0.5), 35 µm (35), transplant (trans), and control. Error bars in the bar plots represent the

standard error of the mean. The boxplots were created using the median and the 25th and 75th percentiles and the

95% confidence interval of the median was used for the error bars.

0.0000

0.0025

0.0050

0.0075

0.0100

0.5

35control

trans

-35.0

-34.5

-34.0

-33.5

-33.0

0.5

35control

trans

p=0.70%

δ13C%%

-3-2-101

0.5

35control

trans

Treatment

δ15N%%

p=0.98%

0.000

0.002

0.004

0.006

inout

0.000

0.002

0.004

0.006

0.5

35control

trans

Treatment

0.000

0.002

0.004

0.006

0.008

inout

Inisd

e vs

Out

side

p=0.05*%

p=0.68%

p=0.31%

p=0.02*%

RGR%(mg%g61%d61)%%

A%C%

B%D%

E% F%

*%

*%

68

Figure 3.2 (a) Differences in the percentage of EM colonization of Oreomunnea seedlings

between sites inside Oreomunnea-dominated forest and 30 m outside in mixed AM dominated

forest and, (b) across exclosure treatments including seedling from both inside and outside

Oreomunnea forest.

P=0.00714 **

0

25

50

75

100

Inside OutsideInside vs Outside

EM

% c

olon

izat

ion

P=0.729

0

25

50

75

100

0.5 35 control transTreatment

EM

% c

olon

izat

ion

P=#0.007#**# P=0.729#A# B#

69

Figure 3.3 A. Strength of negative plant-soil feedback effects on relative growth rate in 240

seedlings of five tree species differing in abundance in permanent forest plots. AM species are

Guarea pterorhachis (GUAPTE), Cupania seemannii (CUPSEE), and Nectandra purpurea

(NECPUR). EM species are Oreomunnea mexicana (OREMEX) and Quercus aff insignis

(QUEINS). Bars indicate standard errors of the mean. (* P < 0.05, ** P < 0.01). B. Regression

model for the strength of plant-soil feedback vs species abundance individuals > 10 cm DBH in

five 1 ha permanent plots.

-0.004 -0.003 -0.002 -0.001 0.000

0.000

0.005

0.010

0.015

0.020

0.025

Strength of feedbackR

elat

ive

abun

danc

e of

tree

s >1

0 cm

DBH

OREMEX

GUAPTE CUPSEE

QUEINS

NECPUR

Str

en

gth

of fe

ed

ba

ck

-0.005

-0.003

-0.001

CUPSEE GUAPTE NECPUR OREMEX QUEINS

**

*A" B"

R2= 0.79, p= 0.029

70

Figure 3.4 Regression models for Oreomunnea basal area in m2 in 20 × 20 sub-plots and (a)

nitrate (mg N kg-1), (b) ammonium, (c) total N (%), and (d) total P (mg P kg-1) measurements in

the same sub-plots.

0.0 0.2 0.4 0.6 0.8 1.0

02

46

810

1214

log(BA_ore + 1)

Nitrate

0.0 0.2 0.4 0.6 0.8 1.0

05

1015

2025

3035

log(BA_ore + 1)

Ammonium

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Log(Oreomunnea BA +1)

N

0.0 0.2 0.4 0.6 0.8 1.0

0500

1000

1500

Log(Oreomunnea BA +1)

P

Nitrate'(m

g'N'kg,1 )'

Ammon

ium'(m

g'N'kg,1 )'

Total'N

'(%)'

Total'P'(m

g'P'kg

,1)'

A" B"

C" D"

R2'='0.43,'P"<0.001***' R2'=',0.05,'P"='0.66'

R2'='0.04,'P"='0.22' R2'='0.002,'P"='0.32'

71

Figure 3.5 Regression models for the number of Oreomunnea individuals > 5 cm DBH in 20 ×

20 sub-plots of two 1 ha permanent plots and ammonium (mg N kg-1), nitrate (mg N kg-1), total

N (%), and total P (mg P kg-1) measured in the same sub-plots.

0 1 2 3 4

02

46

810

12

log(indiv_ore + 1)

Nitrate

0 1 2 3 4

05

1015

2025

3035

log(indiv_ore + 1)Ammonium

A" B"

0 1 2 3 4

0.0

1.0

2.0

3.0

Log(Oreomunnea abundance + 1)

N

0 1 2 3 4

0500

1000

1500

Log(Oreomunnea abundance + 1)

P

D"C"

R2=0.48,)p=<0.001***) R2=0.06,)p=0.16)

R2=.0.06,)p=0.98) R2=0.30,)p=0.01)*)

Nitrate)(m

g)N)Kg.1 ))

Total)N

)(%))

Ammon

ium)(m

g)N)Kg.1 ))

Total)P)(m

g)N)Kg.1 ))

72

Figure 3.6 Regression models for Quercus aff. insignis basal area in 20 × 20 sub-plots and (a)

nitrate (mg N kg-1), (b) ammonium, (c) total N (%), and (d) total P (mg P kg-1) measurements in

the same sub-plots.

0.0 0.2 0.4 0.6 0.8 1.0

02

46

810

1214

log(BA_Q + 1)

Nitrate

0.0 0.2 0.4 0.6 0.8 1.0

05

1015

2025

3035

log(BA_Q + 1)Ammonium

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Log(Quercus BA + 1)

N

0.0 0.2 0.4 0.6 0.8 1.0

0500

1000

1500

Log(Quercus BA + 1)

P

Nitrate'(m

g'N'kg,1 )'

Ammon

ium'(m

g'N'kg,1 )'

Total'N

'(%)'

Total'P'(m

g'P'kg

,1)'

A" B"

C" D"

R2'=',0.06,'P"='0.79' R2'='0.04,'P"='0.21'

R2'='0.03,'P"='0.23' R2'='0.004,'P"='0.32'

73

Figure 3.7 A) Comparison of the Relative growth rate (RGR), and B) Mycorrhizal colonization of seedlings grown on sterile vs live inoculum. We grew 10 replicates of each species in sterile substrate using the same bulk soil and sterile inoculum of all the species (2 replicates of each species inoculum, to give a total of 10 replicates per species x 5 species = 50 pots with sterile inoculum). Seedlings grown in sterile inoculum had a significantly lower RGR compared with seedlings grown with a live inoculum independent of the inoculum sources (Figure 3.4A). This evidence suggests that the benefits of mycorrhizal associations on seedlings’ RGR were stronger than the negative effects caused by pathogens present in the soil. However, as shown in the paper, the effect of the species-specific pathogens found in the conspecific inocula had a stronger negative effect on Oreomunnea seedlings than pathogens found in heterospecific inocula.

We started the experiment with sterile seedlings grown in sterile sand from sterile seeds. At the end of the experiment roots of a subset of fourteen seedlings per species, four grown in sterile control and ten grown in live inoculum (two plants per species per inoculum source), was preserved in 96 % ethanol for quantification of mycorrhizal colonization. Seedlings grown in sterile control had very low or no colonization while seedlings grown in live inoculum had high colonization rates (Figure 3.4B). Notably, none of the Oreomunnea seedlings in sterile inoculum showed signs EM colonization at the end of the experiment, while seedlings in the live inoculum were highly colonized.

0

10

20

30

40

CUPSEE GUAPTE OREMEX QUINSSpecies

Myc

orrh

izal

col

oniz

atio

n (%

)

Inoculum

Live

Sterile

0.004

0.008

0.012

0.016

CUPSEE GUAPTE NECPUR OREMEX QUERCUSSpecies

Mea

n R

GR Inoculum

Live

Sterile

A" B"

74

Figure 3.8 Feedback loop to explain monodominance of Oreomunnea mexicana based on the

‘microbial competition for nitrogen hypothesis’. Abbreviations: Ectomycorrhizal (EM).

Hypothesis*for*EM*mediated*monodominance*

High%abundance%of%Oreomunnea)

High%abundance%of%EM%fungi%

EM%fungi%compete%with%saprophy8c%fungi%for%nitrogen%slowing%down%li:er%decomposi8on%

rates%

Low%decomposi8on%rates%produce%a%reduc8on%in%the%availability%of%inorganic%nitrogen%in%the%soil%

Increase%survivorship%and%growth%rate%of%

Oreomunnea%seedlings%

75

Table 3.1 List of mycorrhizal status inventories in neotropical areas used to calculate the average

percentage of EM vs AM trees in neotropical forest.

Reference Site Total spp %EM %AM

McGuire et al. 2008 Guyana 142 2.1 96.4 Béreau et al. 1997 French Guyana 75 5.3 94.7 Kottke et al. 2008 Ecuador 115 2.6 97.4 Thomazini 1974 Brasil 60 7 93 St. John 1980 Brasil 83 3 97 St. John and Uhl 1983 Venezuela 22 14 86 Moyersoen 1993 Venezuela 42 12 89 Lodge 1987 Puerto Rico 48 6 96 SD

39.61 4.4 4.3

Mean 73.38 6.4 93.6 Béreau M., Gazel M., & Garbaye, J. 1997. Les symbioses mycorhizienne des arbres de la foret tropicale humide de Guyane francaise. Canadian Journal of Botany 75:711–716. Kottke, I., Beck, A., Haug, I., Setaro, S., Jeske, V., Suárez, J.P. et al. 2008. Mycorrhizal state and new and special features of mycorrhizae of trees, ericads, orchids, ferns, and liverworts. In: Gradients in a Tropical Mountain Ecosystem of Ecuador (eds. Beck, E., Bendix, J., Kottke, I. & Makeschin, F.). Ecological Studies 198. Springer-Verlag Berlin Heidelberg. Lodge D.J. Resurvey of mycorrhizal associations in the El Verde rainforest, Puerto Rico. In: Sylvia D.M., Hung L.L., Graham J.H. (eds.) Mycorrhiza in the next decade practical applications and research priorities. Ins. Food Agric Sci, Univ of Florida Gainsville, p 127. McGuire KL, Henkel TW, Granzow de la Cerda I., Villa G., Edmund F., Andrew C. 2008. Dual mycorrhizal colonization of forest-dominating tropical trees and the mycorrhizal status of non-dominant tree and liana species. Mycorrhiza DOI 10.1007/s00572-008-0170-9. Moyersoen B. 1993. Ectomicorrizas y micorrizas vesiculo-arbusculares en Caatinga Amazonica del Sur de Venezuela. Scientia Guianae 3:1–82. St. John TV. 1980 A survey of mycorrhizal infection in an Amazonian rain forest. Acta Amazonica 10:527–533.; St. John T.V. & Uhl C. 1983. Mycorrhizae in the rain forest at San Carlos de Rio Negro, Venezuela. Acta Científica Venezolana 34: 233:237 Thomazini L.I. 1974. Mycorrhiza in plants of the ‘Cerrado’. Plant and Soil 41(3): 707-711.

76

Table 3.2 Biomass models used for the estimation of initial seedling biomass in the calculation

of RGR. LA = leaf area, D = diameter, H = height.

Species Intercept Total

LA

D H No.

leaves

F P R2

CUPSEE 69.709 9.729 17.98 < 0.001 0.4592

GUAPTE -63.67 10.69 47.32 43.25 < 0.001 0.816

NECPUR 71.29 67.79 -146.82 16.48 0.0004 0.7043

OREMEX 8.052 12.845 -15.367 8.547 0.003 0.4561

QUEINS 0.1645 0.2023 6.009 0.036 0.3337

ROUMON -1232 394.4 149.6 11.67 0.002 0.6213

77

Table 3.3 Soil variables values by sub-plot from two 1-ha permanent plots (Honda A = HA, and

Honda B = HB).

Plot Quadrant NO3

mg N kg-1

NH4

mg N kg-1

N

%

C

%

P

mg P kg-1

Litter

g m-2

Microbial N

mg N kg-1

Microbial C

mg C kg-1

HA 1 11.46 1.48 1.02 13.95 920.07 4.86 223.07 973.67

HA 2 0.07 1.55 0.99 19.80 542.51 3.71 158.60 816.37

HA 3 6.34 18.35 1.68 25.86 1056.23 2.50 151.41 821.22

HA 4 1.95 13.23 0.94 13.99 566.36 0.74 83.13 466.16

HA 5 10.44 3.49 1.55 23.41 781.59 1.57 161.69 1065.02

HA 6 0.92 13.87 0.61 11.54 358.77 2.59 111.63 631.15

HA 7 3.51 13.02 0.94 15.01 605.50 1.36 154.60 800.48

HA 8 4.12 3.84 0.65 9.79 410.94 4.47 137.04 725.38

HA 9 1.27 4.99 1.63 16.88 639.37 2.94 231.97 1081.67

HB 1 7.24 28.13 1.57 21.81 683.77 9.08 188.13 932.95

HB 2 8.44 20.02 1.28 16.34 1462.32 5.73 240.35 1010.29

HB 3 0.10 29.21 2.27 41.21 878.10 3.19 305.52 1605.51

HB 4 0.24 5.14 1.81 36.31 727.97 3.60 264.01 1407.24

HB 5 0.37 4.49 1.00 15.48 668.22 3.83 107.67 685.00

HB 6 -‐0.15 7.05 2.12 49.62 681.61 5.26 170.45 903.47

HB 7 2.66 2.78 0.79 13.72 596.03 9.57 72.60 232.18

HB 8 0.97 8.97 2.60 42.23 855.45 3.83 323.13 1490.16

HB 9 0.13 4.10 0.75 12.56 443.99 8.98 133.44 720.59

78

Table 3.4 Mean C : N, total C, total N, δ13C and δ15N of soils and seedlings, and soil ammonium,

nitrate, and phosphate (lg bag-1) measured using an 18- day resin bag incubation at sites either

inside Oreomunnea-dominated forest, or 30 m outside in mixed AM dominated forest.

Variable Locatio

n Soil n F p Seedlings n F p

C:N Inside 19.30 23.68

Outside 15.75 17 26.77 < 0.001 24.94 23 0.45 0.51

%C Inside 28.19 46.22

Outside 12.63 17 21.37 < 0.001 41.44 23 23.10 < 0.001

% N Inside 1.46 1.98

Outside 0.80 17 15.9 0.001 1.70 23 17.33 < 0.001

δ13C Inside -28.01 -33.84

Outside -28.55 17 8.65 < 0.01 -33.38 23 1.15 0.35

δ15N Inside 0.57 -1.18

Outside 2.84 17 26.31 < 0.001 0.87 23 6.55 0.02

Ammonium Inside 4.46

Outside 10.67 19 W=19 0.02

Nitrate Inside 4.33

Outside 12.4 19 W=9 <0.01

Phosphate Inside 0.28

Outside 0.33 19 W=38 0.31

79

Table 3.5 Average plant-soil feedback per species and pairwise feedback between species

included in the experiment. Species abbreviations are Guarea pterorhachis (Guapte), Cupania

seemannii (Cupsee), and Nectandra purpurea (Necpur). EM species are Oreomunnea mexicana

(Oremex) and Quercus aff. insignis (Queins).

Parameter Estimate

feedback

Standard

Error t-value P

Cupsee average -0.00138 0.00140 -0.99 0.3244

Guapte average -0.00284 0.00140 -2.03 0.0444

Necpur average -0.00089 0.00140 -0.64 0.5233

Oremex average -0.00381 0.00145 -2.62 0.0095

Queins average -0.00135 0.00141 -0.96 0.3402

Cupsee & Guapte -0.00111 0.00110 -1.01 0.3129

Cupsee & Necpur -0.00037 0.00110 -0.34 0.7367

Cupsee & Oremex -0.00174 0.00111 -1.57 0.1178

Cupsee & Queins 0.00046 0.00110 0.42 0.6746

Guapte & Necpur -0.00177 0.00110 -1.61 0.1089

Guapte & Oremex -0.00232 0.00114 -2.04 0.0429

Guapte & Queins -0.00050 0.00110 -0.44 0.657

Necpur & Oremex -0.00027 0.00111 -0.24 0.8109

Necpur & Queins 0.00062 0.00110 0.56 0.5755

Oremex & Queins -0.00329 0.00117 -2.81 0.0056

80

Table 3.6 Coefficient of correlation of two EM tree species (Oreomunnea mexicana and

Quercus aff. insignis) and the four most abundant AM tree species with the ammonium and

nitrate concentrations in the soil and with the number of individuals and basal area of

Oreomunnea in 20 × 20 sub-plots. The stars represent the significance of the correlation based on

its p-value = *** < 0.0001, ** < 0.001, * < 0.05.

Species NO3 (R2) NH4 (R2) Individuals

Oreomunnea

Basal area

Oreomunnea

Oreomunnea mexicana

No. of individuals (indv/ 20×20 sub-plot) 0.48 *** 0.06 - -

Basal area (m2/ sub-plot) 0.43 *** -0.05 - -

Quercus aff. insignis

No. of individuals (indv/ 20×20 sub-plot) 0.09 -0.06 -0.06 -0.06

Basal area (m2/ sub-plot) -0.06 0.04 -0.06 0.021

Ardisia sp.

No. of individuals (indv/ 20×20 sub-plot) 0.33** 0.21 * 0.58 *** 0.32 *

Basal area (m2/ sub-plot) 0.18 * 0.07 0.56 *** 0.31 **

Dendropanax arboreus

No. of individuals (indv/ 20×20 sub-plot) -0.06 0.09 0.03 -0.03

Basal area (m2/ sub-plot) -0.05 0.23 * -0.01 0.008

Cassipourea guianensis

No. of individuals (indv/ 20×20 sub-plot) -0.06 0.22 * 0.18 * 0.011

Basal area (m2/ sub-plot) -0.05 0.26 * 0.11 -0.01

Eschweilera panamensis

No. of individuals (indv/ 20×20 sub-plot) -0.02 0.20 * 0.22 * 0.18 *

Basal area (m2/ sub-plot) 0.04 0.08 0.24 * 0.11

81

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Chapter 4: Nitrogen addition alters ectomycorrhizal fungal communities and soil enzyme

activities in a tropical montane forest

Introduction

Anthropogenic nitrogen (N) deposition has increased over the last century (Matson et al.,

1999), extending across unmanaged ecosystems, with measureable impacts on tissue N

concentration in tropical forest (Hietz et al. 2011). Nitrogen deposition causes soil acidification,

reduces plant productivity, and changes plant species composition, soil C storage, and N cycling

(Hasselquist and Högberg 2014, BassiriRad, 2015). Nitrogen deposition is predicted to continue

to rise globally in the next decade with impacts expected on tropical and sub-tropical biodiversity

hotspots (Allen et al. 2011, Phoenix et al. 2012, Liu et al. 2013, Vet et al. 2014, BassiriRad

2015).

Communities dominated by ectomycorrhizal (EM) associated tree species are expected to

be particularly sensitive to increases in N availability. This is because EM fungi specialize in N

absorption from soil (Read 1991) and are particularly sensitive to increases in N availability

since host trees strongly reduce C allocation to their root symbionts under excess N conditions

(Treseder 2004, Högberg et al. 2010 Hasselquist and Högberg 2014). In N-limited temperate

forest it has been shown that long-term increases in inorganic N availability can also reduce the

species richness of EM fungi and alter EM fungal community structure and composition

(Arnebrant and Sördeström 1992, Peter et al. 2001, Lilleskov et al. 2002, Avis 2003, Pardo et al.

2011). However, effects of N addition on EM species composition may depend on the functional

traits of component EM fungal taxa (see Lilleskov et al. 2011 for review). It has been proposed

that these differences in sensitivity to N addition are associated with fungal exploration type and

enzymatic activity. Fungal exploration types are strategies of growth and colonization of the soil

environment that can vary considerably among taxa (Hobbie and Agerer 2010). Sensitive or

"nitrophobic" species usually have high enzymatic capabilities for organic N uptake, a process

that incurs a higher carbon cost to their hosts (Lilleskov et al. 2002). In contrast, "nitrophilic"

species are usually limited to the uptake of labile nitrogen forms, and incur a lower carbon cost

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to their hosts (Lilleskov et al. 2002). With increased N availability, nitrophobic EM species may

respond by reduced production of sporocarps (Arnolds 1991, Lilleskov et al. 2011), mycelia

growth rate (Wallander and Nylund 1992), and colonization of root tips (Treseder and Allen

2000, Peter et al. 2001), while nitrophilic species tend to increase in abundance.

Changes in the composition and functional trait composition of EM fungi associated with

increases in inorganic N availability are expected to have an impact on ecosystem processes

including soil C storage, N cycling, and plant community productivity (Treseder et al. 2012,

Treseder and Lennon 2015). Ectomycorrhizal associations play an important role in soil nutrient

dynamics due to their capacity to compete for organic nitrogen with the decomposer microbial

community (Phillips et al. 2013, Averill et al. 2014). Further, because different ectomycorrhizal

lineages vary in their capacity to uptake different N or P sources they differentially affect

ecosystem level processes (Koide et al. 2014). Changes in EM fungal community composition

could therefore result in changes in enzyme activity, with long-term consequences for N, P and C

cycling in the soil. In addition, changes in the EM community composition may influence the

competitive ability of EM associated plants, since nitrophilic EM fungal species may be less

beneficial or even parasitic on their host plants (Avis 2003, Avis 2012).

Montane forests in Central America are often dominated by tree species that form EM

associations. For example, montane cloud forests in Mexico and Costa Rica are often dominated

by several species of Quercus spp. (Halling 2001, Morris et al. 2008). Similarly, montane forest

in western Panama support EM fungal communities associated with Oreomunnea mexicana that

differ according to soil fertility (Corrales et al. 2016a). Thus, there is a critical need to

understand the response of EM associations to N addition in this region, if we are to predict the

response of this ecosystem to global change (Dalling et al. 2015). Here we take advantage of a

nine-year N addition experiment at a site with low background N availability to explore the

effect of N on soil enzyme activity and on the composition of the EM fungal community

associated with the canopy tree Oreomunnea mexicana. We predicted that an increase in N

availability would have strong impact on EM fungal community composition and infection by (i)

shifting the EM fungal community from one characterized by taxa with previously described

associations with low inorganic N environments (i.e., nitrophobic taxa) to one increasingly

characterized by abundant nitrophilic taxa, (ii) reducing the activity of enzymes associated with

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organic N acquisition, (iii) reducing the EM colonization of root tips consistent with a reduction

of C transfer from the host tree.

Methods

Study site

The study was located in a primary lower montane forest (1000–1400 m.a.s.l.) in the

Fortuna Forest Reserve in western Panama (hereafter, Fortuna; 8°45 N, 82°15 W). Climate

records indicate that the mean annual temperature for Fortuna ranges from 19 to 22˚C (Cavelier

1996) and annual rainfall averages ca. 5800–9000 mm (Andersen et al., 2012). Ambient N

deposition from rainfall in the area is 5 kg N ha−1 y−1 (Adamek et al. 2009, Koehler et al. 2009).

Soils at this site are infertile Ultisols derived from rhyolite (Table 4.1). The focal species,

Oreomunnea mexicana, is an EM canopy tree distributed from Mexico to Panama at 900–2600

m.a.s.l. (Stone, 1972) and forms monodominant stands at the study site (Corrales et al. 2016 a,b).

Nitrogen addition experiment

The N addition experiment consists of a paired-plot design with eight 40 × 40 m plots.

Four plots have been fertilized with urea (CO(NH2)2) at an annual rate of 125 kg N ha-1 divided

into four applications per year. The four remaining plots are untreated controls (Adamek et al.

2009). The experiment was started in February 2006 and it had been fertilized for 9 years at the

time of the study. Seven of the eight plots (four control and three fertilized) contain individuals

of the focal species Oreomunnea mexicana, including seedlings, saplings and adults.

Oreomunnea individuals > 10 cm DBH accounted for 15.5 ± 10.8 % of the total number of

individuals and 28.2 ± 13.4 % of the total basal area of the plots (Dalling et al. unpublished

data).

Soil data collection

Samples of the surface 0-10 cm of mineral soil were collected in nine points separated by

10 m inside each plot (nine internal interception points of 10 × 10 subplots) using a soil corer

and were pooled to generate one sample per plot prior to analysis. Ammonium, nitrate, and

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phosphate were measured using resin bags. Four resin bags containing 5 g of mixed-bed anion

and cation exchange resins (Dowex Marathon Mr-3) sealed inside 220 µm polyester mesh were

buried 2 cm beneath the soil surface in the central point of four 20 × 20 subplots and in the

central point of the plot. Bags were buried during October 2013. After incubation in situ for 21

days the resin bags were collected, rinsed with deionized water to remove adhering soil,

extracted with 75 mL of 0.5 M HCl, and then nitrate (+nitrite), ammonium, and phosphate were

determined by automated colorimetry on a Lachat QuikChem 8500 (Hach Ltd., Loveland, CO,

USA). Readily exchangeable phosphate (Resin P) was determined by extraction with anion-

exchange membranes (Turner and Romero 2009).

Microbial N was determined by chloroform fumigation and extraction in K2SO4 by

standard procedures (Brookes et al. 1985, Vance et al. 1987) following Turner and Wright

(2014). Microbial P was determined by hexanol fumigation and extraction with anion-exchange

membranes following Kouno et al. (1995) as modified in Turner and Romero (2010). Dissolved

organic carbon (DOC) and total dissolved N were determined simultaneously in K2SO4 extracts

on a TOC-VCHN analyzer (Shimadzu, Columbia, MD) after five-fold dilution of the extracts.

The activities of six hydrolytic enzymes were determined using fluorogenic substrates as

described previously (Turner 2010, Turner and Romero 2010). The enzymes and substrates were:

(i) acid phosphomonoesterase (Enzyme Commission (EC) number 3.1.3.2) assayed with 4-

methylumbelliferyl phosphate; (ii) phosphodiesterase (EC 3.1.4.1) assayed with bis-(4-

methylumbelliferyl) phosphate; (iii) β-glucosidase (EC 3.2.1.21) assayed with 4-

methylumbelliferyl β-D-glucopyranoside; and (iv) N-acetyl β-D-glucosaminidase (EC 3.2.1.52)

assayed with 4-methylumbelliferyl N-acetyl β-D-glucosaminide; (v) β-xylanase (EC 3.2.1.37)

assayed with 4-methylumbelliferyl β-D- xylopyranoside; (vi) cellulose 1,4- β-cellobiosidase (EC

3.2.1.91) assayed with 4-methylumbelliferyl β- D-cellobiopyranoside.

Substrates were purchased from Glycosynth Ltd (Warrington, UK) and dissolved in 0.4 %

methylcellosolve (2-methoxyethanol; 0.1 % final concentration in the assay) and then processed

following Turner and Wright (2014). Plates were incubated for 30 min at 26 °C to approximate

the daytime temperature in the upper 10 cm of soil in montane forests in western Panama (Ben

Turner Pers obs). The reaction was terminated by adding 50 µL of 0.5 M NaOH (final solution

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pH > 11) and the fluorescence determined immediately on a FLUOstar Optima multi-detection

plate reader (BMG Labtech, Offenburg, Germany), with excitation at 360 nm and emission at

460 nm. Control wells were prepared for each substrate and contained substrate, buffer, and 1

mM NaN3 (no soil suspension). Blank wells contained soil suspension and buffer only (no

substrate). Standard wells contained buffer, 1 nmol methylumbelliferone (MU), and either soil

suspension or 1 mM NaN3 to account for the reduction of fluorescence in the presence of soil

(quenching). All enzyme activities are expressed as nmol MU g-1 soil (dry weight) min-1.

Sampling of ectomycorrhizas

To assess whether N addition had an impact on the EM fungal community, fine roots

from Oreomunnea were collected from N fertilized and control plots. Fine roots were collected

from three Oreomunnea adult trees, five saplings (40-100 cm height), and five seedlings (5-20

cm height) per plot for a total of 91 individuals. Two lateral roots were excavated 2-3 m from the

trunk of each adult tree until fine roots that were clearly connected to the tree were found. The

entire root system of each focal seedling and sapling was collected.

Fine roots were stored in plastic bags and refrigerated within 2 h of collection. Each

sample was carefully cleaned with tap water and cut into 2 cm pieces. Eighty centimeters of total

fine root length representing multiple root branches were collected from adults, 40 cm from each

sapling, and the entire root system of each focal seedling for a total of 192 samples (Table 4.2).

All roots obtained were included in field collections even if EM fungal infection was not visible

macroscopically. Samples were preserved in 2% CTAB in -20˚C until ready for DNA extraction.

In addition to the roots collected for DNA extraction, 20 cm of fine root of three adults, five

samplings and the entire root system of five seedlings was preserved in 96% ethanol for

quantification of EM fungal colonization.

DNA extraction and sequencing of the EM fungi

To identify EM fungi DNA was extracted from about 0.1 mg of ground root tissue from

each sample using the MOBIO PowerSoil DNA isolation kit (MoBio, Carlsbad, CA USA)

following the manufacturer instructions. PCR was performed using a mixture of six forward

primers (in equimolar concentration) analogous to ITS3 and a degenerate reverse primer

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analogous to ITS4 (hereafter referred to as ITS4ngs) following Tedersoo et al. (2014;

Supplemental material).

Amplicons were subjected to ligation of Illumina adaptors using two variants of the

TruSeq DNA PCR-free HT Sample Prep kit (Illumina Inc., San Diego, CA, USA). All samples

were sequenced in a 150 single Illumina MiSeq 2x300 paired-end run at the Estonian Genome

Center at University of Tartu.

Bioinformatics

Paired-end sequencing (2 × 300 bp) in the Illumina MiSeq sequencer resulted in 722 649

reads. Quality filtering and selection of representative sequences were done using methods

explained in supplementary material. Representative sequences for each OTU were

taxonomically assigned using BLASTn searches (options: word size = 7, gap penalty = -1, gap

extension penalty = -2 and match score = 1) retrieving the 10 best BLASTn matches. The

UNITE 7.0 beta data set (https://unite.ut.ee/repository.php) and Sanger sequences from fruiting

bodies and root tips collected in previous studies at the study area (including sequences from

Corrales et al. 2016 and Corrales et al. unpublished data) were used as a reference for BLASTn

taxonomic assignment of ITS.

Only OTUs with a match of > 80% with families previously reported as ectomycorrhizal

by Tedersoo et al. (2010) in the Blastn taxonomic assignment were included in the final database

for analysis. For the results and discussion we will refer to OTUs as “species” since 97% is a

broadly accepted cut off that usually represents species concept in EM fungi (Kõljalg et al.

2013).

Root staining and frequency of infection

A subsample of root tissue was saved to evaluate EM colonization. EM colonization was

evaluated in roots cleared in 10% KOH and stained with trypan blue. Infection of four randomly

chosen 2.0-cm root sections per seedling was assessed using the grid-line intersect method as

modified by McGonigle et al. (1990).

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Soil nutrients and enzyme activity was compared between treatments using ANOVA.

Phosphate, Microbial N : P, phosphodiesterease, and enzyme C : P were log transformed to

improve normality; other variables were normally distributed. Enzyme activity was compared

between treatments using raw data and also after standardization dividing enzyme activity by soil

microbial C.

OTUs with fewer than 10 sequences (n = 655) were excluded from alpha and beta

diversity analyses to provide a robust data set to compare EM fungal communities among N

treatments and host developmental stages (Smith and Peay 2014; Brown et al. 2015). Species

accumulation curves with the remaining 387 OTUs were used to compare richness among

developmental stages, and between the nitrogen addition treatment and control. Curves were

rarefied based on the smallest number of samples per developmental stage and per treatment

(Table 4.2). Alpha diversity indexes (Pielou evenness index and Fisher alpha) were calculated

per plot based of an equal number of samples and compared using ANOVA including treatment

(N addition and control) and developmental stage as fixed effects and plot as a random effect

after checking for equality of variance and residuals using Levene’s and Shapiro-Wilk test. The

Pielou index was calculated following Pielou (1966).

Nonmetric Multidimensional Scaling (NMDS) was used to compare EM fungal

community composition among N treatments and developmental stages. NMDS analyses were

based on Bray-Curtis dissimilarity matrices using abundance data for individual roots, and for

samples pooled per plot. The significance of differences between N treatments and

developmental stages was determined using permutational analyses of dissimilarity (ADONIS)

using 1000 permutations and a Euclidean distance matrix (Oksanen et al. 2008).

Principal component analysis (PCA) was applied separately on two soil datasets

(nutrients and enzymes), resulting in two axes of variation for soil nutrients (describing 78.77%

and 17.31% respectively of the total variance) and one axis for soil enzymes (describing 98.63%

of the total variance). Due to the high correlation between some variables, the nutrient and

enzyme dataset included a subsample of the measured soil variables that showed less than 50%

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correlation with any other variable in the data set. The soil variables included were: resin P (mg

P kg-1), NH4 (µg bag-1 day-1), NO3 (µg bag-1 day-1), PO4 (µg bag-1 day-1), DOC (mg C kg-1),

microbial N (mg N Kg-1), and microbial C : N (Table 4.1). The enzyme dataset included

phosphomonoesterase (MUP, nmol MU g-1 min-1), β-D-glucosaminidase (BG, nmol MU g-1 min-

1), xylanase (XYL, nmol MU g-1 min-1), cellobiohydrolase (CELLO, nmol MU g-1 min-1), and

enzyme N:P (Table 4.1). Enzyme N:P (Enz N:P) ratio represents the ratio between N-acetyl β-D-

glucosaminidase (an enzyme targeting organic N) and phosphomonoesterease (an enzyme

targeting organic P). Correspondingly, enzyme C:N (Enz C:N) refers to the ratio between β-

glucosidase (an enzyme targeting C) to N-acetyl β-D-glucosaminidase. The first axes of the

resulting PCA for the soil nutrient dataset (PC1.nut) and the first axis of the soil enzyme dataset

(PC1.enz) were used in the NMDS analysis of samples pooled per plot to find correlations

between soil variables and changes in the EM community composition with N treatments (Ter

Braak, 1995). To further explore the relationship between changes in EM community

composition and enzyme activity, a permutational analyses of dissimilarity (ADONIS, Oksanen

et al. 2008) was used with 200 permutations using the species abundance matrix per plot and a

subset of independent enzymes variables. All statistical analyses were carried out using the

package vegan 2.0-6 in R 2.15.1 (R Development Core Team 2011).

A GLM with Poisson errors was used to compare number of OTUs between treatments,

while negative binomial errors were used to test the effect of N addition on the relative

abundance of the eight most abundant individual genera, including treatment as a fixed effect. A

GLM with gamma errors was used to test whether enzyme activity was associated to the

abundance of the five most abundant genera. The goodness of fit of the models was determined

using a chi-squared test. Only the five most abundant genera were included in the multiple

regressions based on the degrees of freedom available.

To test for the effect of nitrogen addition, developmental stage and its interaction on the

abundance of the 100 most abundant species, a multivariate GLM analysis was performed using

manyglm in mvabund 3.10.4 package in R using a negative binomial model and sequence count

data following Peay et al. (2015). This analysis runs a univariate analysis to check for responses

of individual species to treatment effects (Wang et al. 2012). The univariate ANOVA analysis

was run using the “adjust” option that corrects probability values for multiple testing using a

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step-down resampling procedure (Wang et al., 2012). Species with probability values lower than

0.07 were considered significant due to the lower power of the univariate ANOVA compared to

multivariate ANOVA (Wang et al. 2012).

Finally, two-way ANOVA including treatment (N addition and control) and

developmental stage (seedling, sapling, and adult) as fixed effects and plot as a random effect

was used to assess the effect of developmental stage and N addition treatment on EM

colonization frequency.

Results

Changes in soil fertility and enzyme activity with N addition

Among soil chemical variables, only nitrate differed significantly between treatments,

with two-fold higher concentrations in N addition plots (Table 4.1). The activity of

phosphomonoesterase was significantly higher in control plots, while the β-glucosidase and N-

acetyl-glucosaminidase ratio (enzymatic C : N ratio) was significantly lower in control than N

addition plots (Table 4.1). However, none of the treatment effects on enzyme activity were

significant after standardization by microbial biomass (phosphomonoesterase F1,5 = 0.6, P = 0.5;

enzymatic C:N ratio F1,5 = 0.07, P = 0.8). Phosphomonoesterase activity was positively

correlated with activities of phosphodiesterase and N-acetyl-glucosaminidase, and negatively

correlated with the enzymatic C : N ratio (Table 4.3).

Diversity patterns

Illumina sequencing of Oreomunnea roots revealed high EM species richness for both the

four control plots and three N fertilized plots with 318 and 344 species respectively. The

community was dominated by Basidiomycota with 352 species and 19 genera; Ascomycota was

represented by 35 species and 3 genera. Russula was the most species-rich genus with 128

species, followed by Lactarius (47 spp), Tomentella (44 spp) and Cortinarius (36 spp). Overall,

215 of the species obtained by Illumina sequencing (56%) had as their closest match Sanger

sequences from fruiting body voucher specimens or root tips from the study area. Thirty-two

OTUs belonging to Cantharellaceae, Elaphomycetaceae, Russulaceae, and Thelephoraceae with

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a percentage of match > 80% were left as “unidentified” species. In terms of abundance, Russula,

Tomentella, Cortinarius, Cenococcum, Lactarius, Clavulina, Elaphomyces, and Laccaria were

the most abundant genera and accounted for 87% of the total number of reads.

Species diversity and evenness were not significantly different between control and N

fertilized plots (Figure 4.1, Table 4.4). In contrast, there were significant differences when

comparing across developmental stages, driven by significantly higher species diversity and

evenness in saplings compared to seedlings and adults based on Tukey HSD, P < 0.05 (Figure

4.1, Table 4.4).

EM fungal community composition differed between control and N fertilized plots when

pooling samples per plot (Adonis R2 = 0.22, F1,6 = 1.43, P = 0.005) or using individual samples

(Adonis R2 = 0.01, F1,191= 2.65, P = 0.005, Figure 4.2). This difference between treatments was

also reflected in the NMDS ordination where control plots grouped separately from N fertilized

plots (Figure 4.3a). In contrast, species composition did not differ among developmental stages

based on ADONIS analysis (Adonis R2 = 0.01, F2, 189 = 1.03, P = 0.34; Figure 4.3b).

None of the soil nutrient PCA axes showed a significant correlation with axes of EM

fungal community composition derived from the NMDS ordination. However, the first PCA axis

of the soil enzyme dataset (PC1.enz) was significantly correlated with the first two axes of the

NMDS (R2 = 0.84, P = 0.012; Figure 4.3a). PC1.enz accounted for 98.6% of the variation in soil

enzyme variables. The ADONIS analysis including individual soil variables and the species

abundance matrix showed that changes in phosphomonoesterase activity (MUP) were

significantly correlated with changes in EM species composition (Table 4.5).

Changes in abundance and species richness with N addition

Nitrogen addition did not affect species richness for any of the EM genera based on the

GLM results (Table 4.6). When the same analysis was done using abundance data, Cortinarius

showed a significant reduction from 15% of sequence reads to 6% with N addition (z = -3.57, P

<0.001). In contrast, Laccaria and Lactarius responded positively to N addition, increasing from

1% to 10% (z = 3.43, P < 0.001) and 5% to 9% (z = 2.27, P = 0.02), respectively (Figure 4.4,

Table 4.6).

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At the species level, the multivariate GLM showed a significant effect of N addition (P =

0.001), developmental stage (P = 0.001), and their interaction (P = 0.001) on the abundance

distribution of the 100 most abundant species. The univariate ANOVA to test for differences in

abundance of individual species showed a significant effect of treatment on the abundance of

eight species. Laccaria sp. (OTU 20), Cortinarius sp. (OTU 87), Tomentella sp. (OTU 126), and

an unidentified Cantharellaceae (OTU 45) showed higher abundance in N addition plots; while

Cortinarius obtusus (OTU 137), two Cortinarius (species both identified as Cortinarius

junghuhnii OTUs 18 and 85), and Tomentella sp. (OTU 22) showed lower abundance in N

addition plots (Table 4.7). None of the genera showed a significant correlation with any of the

soil nutrients measured except for Lactarius that showed a positive association with nitrate (data

not shown).

The univariate ANOVA to test for changes in abundance of individual species also found

changes in abundance of eight species associated to different plant developmental stages. Three

species of Cortinarius (OTUs 18, 28, and 85), and an unidentified Cantharellaceae (OTU 45)

showed significantly higher abundance in seedlings compared with saplings and adult

individuals. Cenococcum sp. (OTU16) and Tomentella sp. (OTU22) showed a significantly

higher abundance in saplings and just one species of Tomentella (OTU 61) showed a higher

abundance in adult trees.

Association between genera and enzyme activity

The activities of phosphomonoesterase and phosphodiesterase were positively associated

with Cortinarius and negatively associated with Russula abundance. Phosphomonoesterase

activity was also associated positively with Cenococcum abundance (Table 4.8). The remaining

enzymes were not associated with any of the genera included in the model.

Effect of N addition and developmental stage in EM colonization

EM colonization in Oreomunnea root tips was significantly lower in the N addition

treatment (F1,64 = 19.9, P < 0.0001), but did not differ across development stages (F4,64 = 2.3, P =

0.07; Figure 4.5). There was no interaction between N addition treatment and developmental

stage (F2,64 = 1.03, P = 0.36).

96

Discussion

To our knowledge, this is the first study to explore the effects of long-term N addition on

tropical EM fungal communities. Our results indicate that N addition can induce changes in the

EM fungal community, with alterations in the relative abundance of fungal genera known to

differ in their enzymatic activity. Over the long term, changes in enzyme activity resulting from

altered EM communities might be expected to influence key ecosystem processes, including soil

carbon storage and the cycling of N and P.

Effect of N addition on species richness, community composition and EM colonization

Nitrogen addition did not have an effect on the number of EM species associated with

Oreomunnea roots. This result is consistent with studies in temperate forest showing no effect of

N addition on species richness in short-term N addition experiments (less than 5 y, Lilleskov et

al. 2011). However, a significant reduction in species richness has been found along N

deposition gradients in Europe that have been monitored for more than 40 years (Lilleskov et al.

2011, Suz et al. 2014), and therefore a future reduction in richness at our site is possible.

The nine years of N addition, however, were sufficient to significantly change EM

community composition. Both N addition treatment and enzyme activity were significantly

correlated with the NMDS axes of the EM community suggesting an effect of N on community

composition and function. The significant association of EM fungal community composition and

phosphomonoesterase activity could be interpreted as a change in the activity of enzymes

associated with access to phosphate (phosphomonoesterase, phosphodiesterase) and nitrogen (N-

acetyl-glucosaminidase) given the high correlation among these enzymes.

Changes in community composition also reflected altered abundance of some EM genera.

Laccaria and Lactarius had significantly higher relative abundance with N addition plots while

Cortinarius had significantly lower abundance. Likewise, regression analysis showed that

Lactarius was positively correlated with soil nitrate. These patterns are congruent with broader

affinities for N reported for these genera. In studies from temperate forest in Europe and North

America Laccaria and Lactarius consistently exhibit a positive response to high N availability,

and therefore represent “nitrophilic” genera, (Lilleskov et al. 2011) while Cortinarius has been

97

reported as showing a consistent negative association with N availability, and has therefore been

considered to be "nitrophobic" (Lilleskov et al. 2002, Wright et al. 2009, Lilleskov et al. 2011,

Suz et al. 2014). In turn N affinity reflects hyphal exploration traits: Lactarius, Laccaria, and

Tomentella have hydrophilic short and medium distance exploration types and seem to use labile

forms of soil N (Lilleskov et al. 2011) while Cortinarius has hydrophobic medium-distance

fringe exploration and seems to use organic N sources and associates with less fertile soils.

Interestingly, Russula abundance did not correlate with any of the soil variables included in this

study. This likely reflects high variability in resource acquisition traits in this genus (see Chapter

5). Russula species have been reported as showing both negative and positive responses to N

availability (Avis 2003, Avis et al. 2008, Cox et al. 2010). A study of Russula communities

across forest sites varying in N availability at the landscape level at Fortuna also showed

significant differences in the phylogenetic relatedness of Russula between sites with high and

low fertility consistent with environmental filtering (Corrales et al. 2016a). Intrageneric variation

in N affinity was also observed in this study. Cortinarius sp. (OTU 87) showed a positive

association with N addition while Cortinarius obtusus (OTU 137) showed a negative response

(Table 4.7).

Ectomycorrhizal colonization was reduced by N addition as expected (Arnebrant and

Söderström 1992, Egli 1996, Treseder and Allen 2000, Peter et al. 2001). This could have been

caused by a reduction in the C supply from Oreomunnea to its associated ectomycorrhizas or a

reduction in mycelium abundance in the soil (Wallander and Nylund 1992, Wallenda and Kotke

1998, Peter et al. 2001, Frey et al. 2004, Nilsson and Wallander 2003, Nilsson et al. 2007).

Lower EM mycelium abundance in the soil could also be an explanation for the lower enzyme

activity found in soils in the N addition plots.

Changes in soil enzyme activity with N addition

Nitrogen addition was associated with significant changes in soil enzyme activity.

Notably phosphomonoesterase activity was lower in the N addition plots. Also, there was a

significantly higher enzyme C : N ratio in N addition plots representing lower N-acetyl-

glucosaminidase activity (that targets N compounds) compared with β-glucosidase (that targets

byproducts of cellulose). A lower N-acetyl-glucosaminidase activity was expect due to a higher

98

availability of soil inorganic N for plants and microorganisms (Midgley and Phillips 2014).

Lower phosphomonoesterase activity in N addition plots is opposite to the expectations since the

production of phosphatase requires a high investment of N (Olander and Vitousek, 2000).

However Marklein and Houlton (2012) in a meta-analysis of the response of phosphatase to N

and P addition found that even though the average response of soil phosphatase was positive, 26

of the 85 studies included in the analysis showed a negative response of phosphatase to N

addition. These authors hypothesize that soil fertility, duration of the fertilization, soil organic

matter content, C : N : P ratio, and microbial community composition could be possible causes

for the negative response (Marklein and Houlton, 2012).

Lower enzyme activity in N addition plots may indicate a down-regulation of

phosphatase production from plant roots, a reduction in EM fungal associated enzymes, or may

simply reflect the size of the microbial biomass pool in the N addition treatment.

Ectomycorrhizal fungi have been shown to release phosphatase in pure culture (Louche et al.

2010) and to actively deplete organic phosphorus sources (Read and Perez-Moreno 2003). In

addition, phosphatase activity has been shown to increase with the formation of ectomycorrhizal

associations (Ali et al. 2009, van Aarle and Plassard 2010) and to show a higher activity in the

rhizosphere soil around EM root tips (Buée et al. 2005, Courty et al. 2006). Consistent with

reduced EM phosphatase activity, we observed significantly lower EM colonization of

Oreomunnea roots in N addition plots (Figure 4.5). However, the fact that there were no

differences in enzyme activity between treatments after standardization by microbial biomass

could mean that a reduction in overall microbial biomass caused the reduction in enzyme activity

in the N addition plots, rather than a direct down-regulation of enzyme production.

Ectomycorrhizal functional response to N addition

Although the enzymatic activity of EM taxa was not measured directly, covariation in

soil enzyme activity and EM community composition suggests a functional response to N

addition. Overall, phosphomonosterase and phosphodiesterase activity was positively associated

with the abundance of Cortinarius and negatively associated with the abundance of Russula.

This supports previous findings of higher enzymatic capability to access organic N and P from

99

soil organic matter and litter reported for Cortinarius species (Agerer 2001, Nygren and Rosling

2009, Lilleskov et al. 2011).

Implications of anthropogenic N deposition for tropical montane forest

Tropical montane forests have been shown to have a strong short-term response to

moderate nutrient inputs including a reduction of investment in below-ground biomass and

changes in tree species composition (Homeier et al. 2012, Dalling et al. 2015). Consequently, the

predicted increase in N availability in tropical ecosystems resulting from urbanization and

agricultural intensification (Hietz et al. 2011) could cause significant changes in plant species

composition and soil C storage (Homeier et al. 2012, Dalling et al. 2015). With regard to

mycorrhizal associations, soils supporting EM dominated forest tend to have a higher soil

organic matter content compared to soils supporting arbuscular mycorrhizal dominated forest

probably due to stronger competition of EM fungi with free-living decomposer communities for

organic sources of N present in litter (Averill et al. 2014). Changes in the EM community

composition and soil enzyme activity with N addition could have important implications in soil

C storage, and ecosystem N cycling, ultimately affecting forest productivity and diversity. Our

results indicate that N addition could cause a decrease in the abundance of “nitrophobic” EM

fungal species and reduce soil enzyme activity associated with the absorption of organic N and P

in tropical montane forest. A reduction in EM fungal taxa specialized in organic N and P

absorption (e.g., Cortinarius) along with a decrease in EM colonization of host plants could

cause a decrease in the abundance of EM associated plants that could have feedback effects on

decomposition rates and soil C storage. More research focusing in the interaction of the EM

fungi and the decomposer communities under different environmental conditions, and on EM

fungal enzyme activity including peroxidase, chitinase, laccase, and leucine aminopeptidase

could improve our understanding of the implications of N addition on soil processes under EM

dominated tropical forest.

100

Figures and Tables

Figure 4.1 Species-accumulation curves of EM fungi for N treatments and developmental stages

including OTUs with > 10 reads.

Number'of'samples'

Num

ber'o

f'OTU

s'Num

ber'o

f'OTU

s'

Seedlings'Saplings'Adults'

101

Figure 4.2. NMDS using EM fungal species associated to Oreomunnea root tips (stress = 0.13)

for nitrogen treatment based on sequence abundance from individual samples including

seedlings, saplings, and adults. Adonis analysis R2 = 0.01, F1,191 = 2.65, P = 0.005.

+N#Control#

NMDS1#

NMDS

1#

102

Figure 4.3 NMDS using EM fungal species associated to Oreomunnea root tips. A) NMDS

(stress = 0.09) for nitrogen treatment based on sequence abundance pooling species from all

samples in each 40 × 40 plot and the first PCA axis for soil enzyme activity (PC1.enz), B)

NMDS for developmental stages (stress = 0.09) using individual samples.

NMDS

2&NMDS

2&

NMDS1&

B&

PC1.enz&

A&

&&&&&&&&Control&

Seedlings&Saplings&Adults&

&&&&&+&N&

103

Figure 4.4 Changes in relative abundance of the eight most abundant genera associated to

Oreomunnea mexicana roots in control and nitrogen fertilized plots. Error bars represent

standard error of the mean.

Abundance (mean no. of sequences)

0 10 20 30 40 50

+NControl

Cenococcum(

Clavulina!!

Cor$narius!! *!

*!

*!

Elaphomyces!!

Laccaria!!

Lactarius!!

Russula!!

Tomentella!!

Genus!rela+ve!abundance!(%)!

+N!Control!

104

Figure 4.5 Mean percent EM colonization (± 1 SE) of Oreomunnea mexicana roots of adults,

saplings, and seedlings in control and nitrogen addition plots.

P < 0.0001

0

25

50

75

100

A_C A_N SAP_C SAP_N SEE_C SEE_NTreatment

EM %

col

oniz

atio

n

Adults'

P'<'0.001' Control''+N'

Saplings' Seedlings'

EM'colon

iza<o

n'(%

)'

105

Table 4.1 Mean and standard error of soil characteristics control and nitrogen fertilized (+N)

plots at Fortuna Forest Reserve, Panama. The probability value (P) was calculated using Anova

analysis.

Soil variables Control + N P

Soil nutrients

pH 4.62 ± 0.09 4.51 ± 0.08 0.3

Resin P (mg P Kg-1) 1.60 ± 0.42 0.97 ± 0.22 0.6

NH4 (µg bag-1 day-1) 29.7 ± 6.9 40.3 ± 7.4 0.9

NO3 (µg bag-1 day-1) 16.7 ± 2.8 37.9 ± 6.1 0.02*

PO4 (µg bag-1 day-1) 1.06 ± 0.40 2.53 ± 0.82 0.7

DOC (mg C Kg-1) 417 ± 23 365 ± 34 0.5

Microbial C (mg C Kg-1) 1134 ± 170 797.8 ± 94.2 0.4

Microbial N (mg N Kg-1) 237.3 ± 28.8 180.8 ± 19.6 0.3

Microbial P (mg P Kg-1) 34.3 ± 4.9 34.5 ± 1.98 0.9

Microbial C:N 4.61 ± 0.31 4.46 ± 0.25 0.7

Microbial C:P 37.01 ± 8.06 24.28 ± 4.29 0.5

Microbial N:P 7.82 ± 1.53 5.38 ± 0.75 0.4

Soil enzymes

Phosphomonoesterase (MUP, nmol MU g-1 min-1) 169.30 ± 16.5 117.32 ± 14.9 0.05*

Phosphodiesterase (BIS, nmol MU g-1 min-1) 32.73 ± 7.25 20.99 ± 3.28 0.1

β-glucosidase (BG, nmol MU g-1 min-1) 6.89 ± 0.64 6.36 ± 0.75 0.5

N-acetyl-glucosaminidase (NA, nmol MU g-1 min-1) 7.54 ± 1.21 6.60 ± 1.80 0.2

β-xylanase (XYL, nmol MU g-1 min-1) 2.48 ± 0.35 2.79 ± 0.17 0.6

Cellobiohydrolase (CELLO, nmol MU g-1 min-1) 0.64 ± 0.04 0.85 ± 0.17 0.9

BG:NA (Enzymatic C:N) 0.98 ± 0.08 1.19 ± 0.16 0.04*

BG:MUP (Enzymatic C:P) 0.04 ± 0.001 0.06 ± 0.01 0.3

NA:MUP (Enzymatic N:P) 0.04 ± 0.005 0.05 ± 0.007 0.9

106

Table 4.2 Number of root samples sequenced per plot and per developmental stage of

Oreomunnea. Replicate samples were collected from three adult trees, five saplings, and five

seedlings per plot.

Plot Adult Saplings Seedlings Total

51 11 9 6 26

52 16 8 5 29

53 11 10 6 27

54 12 8 7 27

55 12 10 5 27

56 12 10 5 27

58 12 12 5 29

Total 86 67 39 192

107

Tables 4.3. Correlation analysis between soil enzymes. Values in bold represent significant

correlation.

Enzyme MUP BIS BG NA XYL CELLO EnzC.N EnzC.P EnzN.P MUP 1.00

BIS 0.93 1.00

BG 0.52 0.61 1.00

NA 0.83 0.90 0.81 1.00

XYL 0.31 0.57 0.59 0.54 1.00 CELLO 0.11 0.21 0.84 0.46 0.62 1.00

EnzC.N -0.76 -0.74 -0.24 -0.75 -0.15 0.13 1.00 EnzC.P -0.45 -0.34 0.50 -0.08 0.25 0.78 0.63 1.00

EnzN.P 0.06 0.22 0.71 0.58 0.32 0.61 -0.24 0.51 1.00

108

Table 4.4 Diversity indexes for EM fungi associated with the roots of Oreomunnea mexicana for

N addition treatments and Oreomunnea developmental stages. Values for N treatments were

computed based on plot averages pooling samples from all individuals in each plot.

Developmental stages means were computed using individual samples.

Diversity

index

Total

OTU

Fisher’s

alpha

Pielou

Evenness

+N 344 139.48 0.6

Control 318 116.77 0.57

df

6 6

P

0.117 0.103

Adults

4.96 0.51

Saplings

5.85 0.58

Seedlings

4.38 0.52

df

2 2

P

< 0.001 < 0.01

109

Table 4.5 ADONIS analysis including the species abundance matrix and an independent subset

of soil enzymes to explore relationship between EM species composition and soil enzyme

activity. Abbreviations as in Table 1.

R2 (%) F value NMDS

MUP 23.2 1.62 0.02*

BG 14.1 0.98 0.53

XYL 18.1 1.26 0.17

CELLO 14.6 1.02 0.44

EnzN:P 15.8 1.11 0.35

110

Table 4.6 The ten most abundant ectomycorrhizal fungal genera found in roots of Oreomunnea

mexicana and their distribution among nitrogen fertilized (N) and control plots (C) at the Fortuna

Forest Reserve, Panama. The number of OTUs in each genus (No. OTUs) was quantified based

on OTUs with more than 10 reads in the total database. The relative abundance of each genus

(RA) was calculated as the percentage of the total sum of reads of the OTUs in the genus divided

by the total number of read in the plot. The probability values for relative abundance are based

on a negative binomial generalized linear model analysis. The probability values of the number

of OTUs are based on a generalized linear model with Poisson errors. The genera with

significant differences between N fertilized and control plots are shown in bold.

P Plot 51 (C) Plot 52 (N) Plot 53 (N) Plot 54 (C) Plot 55 (N) Plot 56 (C) Plot 58 (C)

Genus

No.

OTUs RA

No.

OTUs RA

No.

OTUs RA

No.

OTUs RA

No.

OTUs RA

No.

OTUs RA

No.

OTUs RA

No.

OTUs RA

Cenococcum 0.48 0.06 14 10.68 11 2.43 12 7.87 11 9.70 9 6.45 15 10.42 10 5.06

Clavulina 0.28 0.15 6 4.41 9 6.82 4 1.45 3 1.86 8 4.11 6 10.77 5 13.57

Cortinarius 0.54 <0.001 25 13.50 25 9.74 21 3.78 21 10.73 10 5.04 18 21.09 19 14.49

Elaphomyces 0.24 0.87 13 8.27 6 4.33 8 4.84 10 8.40 8 10.30 11 4.12 6 1.14

Laccaria 0.68 <0.001 4 0.45 7 10.74 6 3.81 7 3.39 5 15.72 5 0.94 5 0.88

Lactarius 0.15 0.02 33 3.53 40 9.57 36 10.71 26 4.79 36 8.32 37 5.75 28 6.42

Russula 0.23 0.35 67 28.37 87 33.98 85 25.86 69 34.93 52 18.61 63 24.88 69 36.06

Tomentella 0.68 0.12 23 13.09 25 16.44 27 32.34 20 9.70 20 10.49 20 5.20 27 14.06

111

Table 4.7 Species showing significant changes in abundance across treatment (T),

developmental stage (DS), and their interaction, direction of the response, and their closest match

in the local sequence database or GenBank database. ID% refers to the percentage of sequence

match with the closest match in GenBank and the e-value refers to the probability of finding a

match by chance when searching the GenBank database. Data are for the 100 most abundant

taxa; P values are corrected for multiple comparisons using step-down resampling procedure (see

methods).

Species OTU Effect Response

to N P

Accession

number Family ID% e-value

Laccaria sp. 0020 T + 0.04 AC863-FB Hydnangiaceae 99% 4.29533e-157

Cortinarius sp. 0087 T + 0.04 DQ102685 Cortinariaceae 93% 5.37017e-127

Unknown 0045 T,

T*DS

+ 0.07,

0.004

JQ991671 Cantharellaceae 89% 1.26704e-132

Tomentella sp. 0126 T + 0.005 AB587786 Thelephoraceae 93% 1.10285e-140

Cortinarius obtusus 0137 T - 0.01 AC509-RT Cortinariaceae 98% 7.35007e-159

Tomentella sp. 0156 T - 0.006 EF411110 Thelephoraceae 96% 1.57522e-153

Cenococcum sp. 0016 T * DS ns 0.027 FJ440882 Gloniaceae 98% 7.65076e-125

Cortinarius junghuhnii 0018 T * DS - 0.02 AC412-RT Cortinariaceae 99% 5.98332e-162

Tomentella sp. 0022 T * DS ns 0.06 AC316-RT Thelephoraceae 99% 2.15756e-162

Cortinarius junghuhnii 0085 T * DS - 0.07 AC412-RT Cortinariaceae 98% 2.10525e-158

Tomentella sp. 0183 T * DS ns 0.07 AC316-RT Thelephoraceae 99% 1.65929e-161

Tomentella sp. 0061 DS 0.06 UDB004090 Thelephoraceae 92% 2.16885e-131

Cortinarius sp. 0028 DS 0.03 AC604-RT Cortinariaceae 97% 1.05797e-144

112

Table 4.8 Multiple regression models for enzyme activity and soil abiotic variables. GLM were

run using a gamma error distribution for a continuous positive response variable. Variables with

stars denote significance based on the > |z| value.

Enzyme Intercept Cenococcum Cortinarius Lactarius Russula Tomentella

MUP 4.58 0.0001* 0.00013***

- -0.00003**

-

BIS 2.09 - 0.0002 ** - -0.00007* - NA - - - - - - BG - - - - - - XYL - - - - - - CELLO - - - - - -

113

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Chapter 5: Variation in stable isotopes of Russula species associated with Oreomunnea mexicana in a tropical montane forest

Introduction

A knowledge of fungal functional traits is essential to predict fungal responses to

environmental factors (McGill 2006, Petchey and Gaston 2006) and to understand the role of

fungi in ecosystem processes (Crowther et al. 2014, Koide et al. 2014, Aguilar-Trigueron et al.

2015, Treseder and Lennon 2015). Fungal functional traits are features of mycelial morphology

and physiology that result in differences in the capacity for carbon (C) storage and nutrient

uptake (Hobbie and Agerer 2010). For ectomycorrhizal (EM) fungi these traits include

differences in the capacity to absorb organic vs inorganic nitrogen (N), in the amount of C

allocated to biomass for nutrient transport (rhizomorphs), and in water stress tolerance (Koide et

al. 2014). Recent work has shown that these functional traits underlie variation in the

composition of EM communities and is reflected in the isotopic composition of fungal tissue

(Courty et al. 2010, Hobbie and Agerer 2010, Hasselquist and Högberg 2014).

The isotopic composition of fruiting bodies can be a useful tool to differentiate

saprotrophic (SAP) and EM fungi (Mayor 2009). During the transfer of nitrogen from fungal

tissue to plant roots a fractionation occurs where 14N is preferentially transferred to the host

plant. This results in an average 6.7‰ enrichment of fruiting bodies of EM fungi relative to those

of saprophytic fungi (Hobbie and Hogbert 2012). The amount of N transferred from EM fungi to

the host plant is also correlated with the δ15N composition of EM fruiting bodies (Hogbert et al.

1999a), and has been proposed as a proxy for the EM fungal sink strength for N in boreal forest

(Hasselquist and Högberg 2014). In addition, higher δ15N in fruiting bodies has also been

associated with the presence of a hydrophobic mantle, long distance hyphal exploration types,

foraging for N at deeper soil horizons, and greater enzymatic capabilities to acquire N from

organic sources (Hobbie and Agerer 2010, Lilleskov et al. 2011, Hobbie et al. 2012, Hobbie et al.

2014). In contrast, species that show lower δ15N generally have a hydrophilic mantle, short

distance exploration types, forage for N in the soil organic layer, and have lower enzymatic

capabilities (Hobbie and Agerer 2010, Lilleskov et al. 2011, Hobbie et al. 2012, Hobbie et al.

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2014). Finally fruiting bodies with higher δ15N are also associated with sites with lower nitrogen

availability (Hobbie and Agerer 2010; Figure 5.1).

In addition to N, the δ13C of fruiting bodies can also be used to distinguish between

ectomycorrhizal and saprophytic fungi since their carbon sources (plant sugars for EM fungi, and

cellulose and lignin for saprophytic fungi), have contrasting δ13C signatures (Högberg et al.

1999b). As with N, variation in δ13C reflects additional sources of variation, depending on the

δ13C composition of their host plant (Högberg et al. 1999b). First, EM fungi that receive C from

plants from the forest overstorey tend to have higher δ13C than EM fungi receiving C from plants

growing in the forest understory (Högberg et al. 1999b). Second, plants exposed to drought stress

have been shown to have a higher δ13C signature than plants growing in more humid conditions,

which could also affect EM fungi δ13C composition (Högberg et al. 1999b, Figure 5.1).

To date, the diversity patterns and functional ecology of EM fungi in tropical forest and

their influence in ecosystem processes remain, for the most part, poorly understood. The aim of

this study was to explore community and intra-generic variation in the isotopic composition of

Russula species found along a gradient of soil inorganic N availability in a Panamanian montane

forest. Russula is an important component of many EM fungal communities in the tropics, often

having the highest species richness in fruiting body and root tip inventories (e.g., Peay et al.

2010; Smith et al. 2011; Tedersoo et al. 2011, Corrales et al. 2016). This genus is also highly

variable in response to N fertilization with some species increasing in their abundance in high N

environments, while others decrease (Lilleskov et al. 2002; Avis et al. 2003; Avis et al. 2008,

Lilleskov et al. 2011). These differences in response among Russula species may reflect

interspecific niche differentiation due to differences in species functional traits. Consistent with

resource based niche partitioning, Corrales et al. (2016) reported that Russula species found in

soils with low fertility had a greater than expected phylogenetic distance from Russula species

found in high fertility soils in Oreomunnea forest in Panama. It may be possible therefore that

Russula species with different resource acquisition capabilities colonize habitats with contrasting

fertility.

Oreomunnea mexicana (Juglandaceae) is an EM tree distributed through Central America

and locally accounting for up to 70% of individuals and basal area in the forests where it occurs.

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At the Fortuna Forest Reserve in western Panama it has been shown that Oreomunnea inhabits

soils with both high and low soil fertility and associates with diverse EM fungal communities, of

which Russula is the dominant genus. At Fortuna, the presence of monodominant Oreomunnea

forest is associated with reduced inorganic N availability, which has been hypothesized to result

from competition between EM fungi and free-living saprotrophs for N. Here we analyze the δ15N

and δ13C of Russula fruiting bodies and its correlation with EM (principally Oreomunnea) host

abundance and soil inorganic N availability (Corrales et al. 2016b). We hypothesized that: (1)

Russula found in low N sites will possess greater enzymatic capabilities to uptake N from

organic sources, resulting in higher δ15N in fruiting bodies than sites with high N availability. (2)

High N availability will reduce the amount of C that the host plant supplies to EM fungi,

resulting in Russula fruiting bodies from N addition plots and sites with natural high inorganic N

availability that are more enriched in δ13C than Russula from sites with low inorganic N. (3) If

the enzymatic capabilities of Russula species are a conserved trait, then more closely related

species will have a more similar isotopic signature than more distantly related species no matter

which environment they inhabit. (4) Based on the proposed competition between EM and

saprophytes we predicted that Oreomunnea abundance will be highly correlated with soil

inorganic N availability across a wider gradient of N availability than described by Corrales et al.

(2016b).

Methods

Study area

The study focused on stands of Oreomunnea mexicana (Juglandaceae) in four watersheds

(Alto Frio, Honda, Hornito, and Zarceadero) in a primary lower montane forest (1000–1400

m.a.s.l.; Figure 5.2 and Table 2.1 in Corrales et al. 2016a) in the Fortuna Forest Reserve in

western Panama (8˚45’ N, 82˚15’W, Corrales et al. 2016a). Oreomunnea is a mid-elevational

canopy tree distributed from southern Mexico to western Panama at 900–2600 m.a.s.l. (Stone

1972). It produces ca. 100 mg, wind-dispersed fruits, which can generate high-density seedling

patches in the understory. Oreomunnea is locally dominant at some of our study sites, accounting

for up to 70% of individuals and stand basal area (Corrales et al. 2016a). Other EM tree species

that are present in the study area are Quercus insignis, Q. cf lancifolia, and Coccoloba spp.

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These species do not form monodominant forests and are found in low abundance in some of the

study sites. Climate records indicate that the mean annual temperature for Fortuna ranges from

19 to 22 °C (Cavelier 1996). Annual rainfall averages ca. 5800 mm at our sites in Hornito, Alto

Frio, and Zarceadero, and 9000 mm at our sites in Honda, although all were drier during our

study period (Table 5.1). Hornito and Alto Frio typically have 1–2 months per year with <100

mm of precipitation; in contrast, no months with <100 mm of rainfall have been recorded at

Honda, or Zarceadero (Andersen et al. 2012; J. Dalling unpublished data).

The selected sites were located under Oreomunnea dominated forest and differ markedly

in soil characteristics (Corrales et al. 2016a). The sites were classified as high, medium, and low

soil inorganic nitrogen (N) availability based on the sum of resin-extractable ammonium and

nitrate (Table 5.1; Andersen et al. 2010, Corrales et al. 2016a). A total of 148 resin bags

containing 5 g of mixed-bed anion and cation exchange resins (Dowex Marathon Mr-3 Supelco,

Bellefonte, PA, USA) sealed inside 220 µm polyester mesh were buried 2 cm beneath the soil

surface at each site in Oreomunnea forest. Bags were buried during August 2014. After

incubation in situ for 18 days, the resin bags were collected, rinsed with deionised water to

remove adhering soil, extracted with 75 mL of 0.5 M HCl, and then nitrate (+ nitrite) and

ammonium were determined by automated colorimetry on a Lachat QuikChem 8500 (Hach Ltd.,

Loveland, CO, USA). Oreomunnea basal area in these sites was measured in one 50 × 20 m plot

at each site where all Oreomunnea trees were measured and recorded in July 2011 and July

2014.

In addition, seven 40 × 40 plots belonging to a N addition experiment in the Honda

watershed were included as collection sites (four control plots and three N addition plots), where

125 kg N ha-1 have been applied annually over nine years (for description of the N addition

experiment see Chapter 3 and Adamek et al. 2009). Resin bags were buried in these plots during

October 2013 and August 2015 and were incubated for 18 days. Oreomunnea basal area was

measured in all the plots in 2015 (Dalling et al. unpublished data).

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Collection of the Russula fruiting bodies

Russula fruiting bodies were collected over a four year period between January 2012 and

June 2015. Macromorphology of fresh fruiting bodies was recorded in the field, and a sample of

tissue was preserved in 96% ethanol for DNA extraction from a subsample of the collections

(Table 5.1). Vouchers of fruiting bodies are deposited at the University of Arizona Robert L.

Gilbertson Mycological Herbarium (MYCO-ARIZ) and at the herbarium of University of

Central Oklahoma (UCO). Russula voucher collections were identified based on their

morphology and names assigned when possible. Because of the high diversity and challenging

taxonomy of Russula, and the possibility that collections represent new species, most species

names were assigned based on sequence similarity with a 97% similarity threshold used to

classify OTUs (explained below).

DNA extraction and amplification

Genomic DNA was extracted using the REDExtract-N-Amp plant PCR kit (following the

manufacturer’s instructions; Sigma-Aldrich). Primers ITS1F and ITS4B were used for species

identification following Corrales et al. (2016a).

Phylogenetic analysis

Phylogenetic relationships were inferred using 113 sequences from Russula fruiting

bodies collected at the study site and 31 sequences downloaded from GenBank as in Corrales et

al. (2016a). Four sequences from voucher specimens of Stereum hirsutum (Willd.) Pers.

(AY854063), Amylostereum laevigatum (Fr.) Boidin (AY781246), Gloeocystidiellum porosum

(Berk. & M.A. Curtis) Donk (AY048881), and Bondarzewia montana (Quél.) Singer

(DQ200923) were used for the outgroup following Miller and Buyck (2002) and Buyck et al.

(2008). Sequences were aligned using MUSCLE (Edgar 2004). The resulting alignment was

edited using Gblocks 0.91b (Castresana 2002) to exclude positions that were poorly or

ambiguously aligned. The final data set consisted of 580 characters and 144 terminal taxa. The

tree was inferred using maximum likelihood analysis using the GTR+I+Gamma model of

evolution and the bootstrap support was assessed using 1000 bootstrap replicates using the Ape

package in R (Paradis et al. 2004).

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Pagel’s λ was used to measure phylogenetic dependence of the isotopic composition and was

calculated using the function phylosig in the package phytools 0.1.2 in R (Revell 2012)

Stable isotopic composition analysis

A small piece of dry fruiting body (dried at 60˚C) was sampled from the stipe and pileus

of 93 Russula collections, and from nine saprophytic fungi collected at the same locations (Table

5.1). Samples were finely ground using glass beads in a TissueLyser II machine (QIAGEN, Inc.)

and then analyzed for C and N concentrations and stable isotope ratios (δ13C and δ15N) by

continuous flow isotope ratio mass spectrometry using an elemental analyser (Costech

Analytical, Valencia, California 4010) coupled to a Delta-V Advantage isotope ratio mass

spectrometer (Thermo Fisher Scientific, Bremen, Germany). Run imprecision for δ13C and δ15N

was typically < 0.2 ‰. To augment the database on saprophytic fungi, eight data points from

samples collected from Fortuna, published in Mayor et al. (2014) were included in the SAP

average.


To test for the effect of soil N availability on fruiting body isotopic composition a nested

ANOVA was done using isotopic composition (δ13C and δ15N) as dependent variables and sites

nested within N fertility level (LN: Low N, MN: Medium N, HN: High N, C: Control plots from

N addition experiment, N: N addition plots in N experiment) as independent variables.

Differences among soil N levels were calculated using a post-hoc Tukey’s test in R. We used

type II Major Axis (MA) regression to fit N content (N%) of fruiting bodies with δ15N using the

lmodel2 package in R (Legendre, 2011) following Heineman et al. (2016). δ15N was transformed

using the multiplicative inverse function (1/x) to improve linearity. In addition, a MA regression

between δ13C and δ15N was fitted to check for coupling between N and C transfer between EM

plant and EM fungi.

To test the effect of inorganic N availability on Russula fruiting body δ15N, a linear

regression was run using δ15N as a dependent variable and soil inorganic N availability

(measured with resin bags) as the independent variable. To test the effect of host abundance on

Russula δ15N, a linear regression was run using δ15N as a dependent variable and Oreomunnea

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basal area as independent variable after logarithmic transformation of both variables. To test the

effect of inorganic N availability and host abundance on Russula fruiting body δ13C, two linear

regressions with no variable transformations were run using δ13C as the dependent variable,

Oreomunnea basal area and soil inorganic N availability as independent variable, and mean

annual dry season rainfall (recorded from January to April during 2013 and 2014) as a covariate

to account for changes in water availability in the plant δ13C signature.

Results

Russula community

During the four years of the study, 161 Russula fruiting bodies were collected and 108

(68%) were sequenced (Table 5.1). The 108 sequenced collections were grouped into 52 OTUs

based on 97% similarity. The average number of Russula OTUs per site was 12, with the lowest

richness in the N addition plots (5 OTUs; Table 5.1). The Russula phylogenetic tree was well

supported based on the bootstrap values (Figure 5.3).

Effect of soil inorganic nitrogen availability on C and N isotope ratios of the Russula

community

There was high variation in the isotopic signature of Russula OTUs, ranging for δ13C

from -22.05 (in AC422 OTU S25) to -27.92 (in CO 5478 what OTU S7) and for δ15N from 1.06

(in AC648 what OTU S37) to 10.00 (in AC422 OTU S25, Figure 5.4).

The isotopic composition of δ13C (F4,79 = 2.70, P = 0.03) and δ15N (F4,79 = 3.63, P =

0.009) differed significantly among soils with different inorganic N availability. The δ13C of

Russula fruiting bodies collected from soil with naturally high inorganic N availability showed

significantly higher δ13C than Russula collected in sites with lower inorganic N availability or in

the N addition plots (Figure 5.5a). The δ15N of Russula fruiting bodies collected from the site

with the lowest soil inorganic N availability showed a significantly higher δ15N than Russula

collected in sites with higher N availability (Figures 5.5b).

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The community average δ13C of Russula fruiting bodies from the sites with the highest natural

soil inorganic N were closer to δ13C values of tropical saprophytic fungi (SAPF) while the

community average δ15N of Russula from the N fertilization plots were closer to the SAPF δ15N

values (Figure 5.6).

The community average δ15N was not significantly correlated with soil inorganic N

availability (R2 = 0.60, P = 0.08,) while δ13C was correlated with soil inorganic N availability

when using mean annual dry season precipitation as a covariate (R2 = 0.96, P = 0.02).

Community average δ15N was significantly negatively correlated with community average %N in

fruiting bodies (R2 = 0.99, P < 0.001; Figure 5.7A) and positively correlated with the abundance

of the host species Oreomunnea (R2 = 0.95, P = 0.002; Figure 5.7B). The abundance of

Oreomunnea was also negatively correlated with soil inorganic N availability (R2 = 0.70, P =

0.048; Figure 5.7C). The community average δ13C correlated with host tree abundance when

using mean annual dry season precipitation as a covariate (R2 = 0.92, P = 0.041). Finally,

Russula community δ15N was significantly correlated with δ13C when using precipitation during

the dry season as a covariate (R2 = 0.84, P = 0.048)

Based on Pagel’s λ, there was a significant phylogenetic dependence of δ15N (λδ15N =

0.66, P = 0.03), but not of δ13C (λδ13C = 6.61e-5, P > 0.99) in Russula fruiting bodies (Figure 5.8).

Discussion

Determinants of variation in Russula isotopic composition

Here we provide evidence that the δ15N of Russula fruiting bodies increases in proportion

to the abundance of Oreomunnea mexicana. In turn, Oreomunnea abundance increased with

decreasing soil inorganic N availability. Due to fractioning of N isotopes, EM fungi become

more enriched in 15N when they transfer more N to their host (Hogberg et al. 1999a). The greater

enrichment of δ15N in Russula fruiting bodies with an increase in host abundance and a decrease

in inorganic N availability is therefore consistent with higher N transfer rate from Russula to

their host plant under conditions of decreasing inorganic N availability. Changes in δ15N could

also be associated with differences in the soil depth at which EM access N (Hobbie et al. 2014).

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However as this study was limited to a single EM genus interspecific differences in EM foraging

patterns may be smaller than would be observed for the whole EM community.

The δ13C of the Russula communities was also correlated with Oreomunnea abundance,

suggesting a higher transfer of C from Oreomunnea to Russula in sites with higher Oreomunnea

abundance. However, the correlation with Oreomunnea abundance was only significant when

dry season precipitation was used as a covariate. Drought stress has been shown to increase the

δ13C signature in plants (Farquhar et al. 1989, Ehleringer et al. 1993). High nitrogen (HN) sites at

Fortuna (Hornito and Alto Frio, Table 5.1) typically have 1–2 months per year with < 100 mm of

precipitation; in contrast no months with < 100 mm of rainfall have been recorded in the other

sites (Corrales et al. 2016a). The higher δ13C of Russula fruiting bodies in HN sites compared to

other sites is therefore likely to be associated with seasonal drought stress.

Isotopic evidence for EM effects on ecosystem N cycling

The significant correlation between δ15N and δ13C along with increase of δ15N and

decrease in δ13C with host abundance indicates a coupling of tree C allocation to EM fungi with

EM fungi N transfer to Oreomunnea. Hasselquist and Hogberg (2014) proposed that EM

community δ15N could potentially be used as a relative index of EM fungal sink strength. This is

because in sites with low N availability, trees transfer more C to EM fungi in exchange for N,

and that C can then be invested in the production of more fungal biomass including fruiting

bodies. Sites with higher fungal biomass will in turn have a higher demand for soil N

immobilizing a higher proportion of soil N in their biomass. As a consequence, higher N transfer

from EM fungi to the host plant will result in higher 15N fractionation making EM fruiting bodies

more δ15N enriched and foliar δ15N more depleted.

Conditions of low soil inorganic N availability under EM dominated forest are proposed

to result from competition between EM fungi and the community of free living saprotrophs

(Averill et al. 2014, Corrales et al. 2016). Collectively, these results suggest that EM fungi

creating soil conditions that increase Oreomunnea dependency on EM fungal N via a feedback

loop (Figure 5.9). We would predict that sites with lower inorganic N availability and higher

δ15N in Russula fruiting bodies (i.e., the low N site) will have a higher fungal biomass and

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therefore EM fungi will retain a larger amount of ecosystem N. This would imply that higher C

allocation from the tree to EM fungal species could decrease N availability for free-living

saprotrophs and non-EM plant species creating a positive feedback loop contributing to increased

abundance of Oreomunnea mexicana in sites with lower inorganic N availability (Figure 5.9).

Evidence for EM mediated positive feedback has been found in boreal forest, where EM fungi

may sustain rather than alleviate N limitation making their host plant more dependent of EM

fungal N (Näsholm et al. 2013, Franklin et al. 2014).

Effect of N addition on isotopic composition

There were no significant differences in the mean isotopic composition of fruiting bodies

from the control and N addition plots. These results contrast with those found from the sites

differing in natural soil inorganic N availability and suggest that an increase in N availability

over 9 years did not reduce C allocation from the host plant to Russula species. However, N

addition did seem to affect the number of Russula species producing fruiting bodies. Although

the transects located in the control and N addition plots were visited the same number of times,

only 17 collections belonging to 5 OTUs were found from N addition plots while 36 collections

belonging to 17 OTUs were found in control plots (Table 5.1). This change in Russula OTU

richness with N addition however was not reflected in the belowground community characterized

using Illumina sequencing in Oreomunnea root samples from the same plots (Corrales et al.

Chapter 4).

Interspecific variation in Russula isotopic composition

At Fortuna, interspecific variation of Russula δ15N showed significant phylogenetic

signal (Figure 5.8), with more closely related species showing more similar δ15N than more

distantly related species. These results are consistent with findings from Tedersoo et al. (2012),

who reported a strong effect of genetic distance on enzymatic activity, root tip mantle

morphology, and exploration type in Russula collected from an African lowland tropical forest.

However there was no correlation between isotopic composition and enzyme activity in this

study, probably due to differences in the isotopic composition of EM fungi in root tips compared

with fruiting bodies. We would expect that changes in the δ15N composition of Russula at our

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study site could be explained at least partially by differences in species enzymatic capabilities

since species with greater access to organic N are expected to have higher δ15N content in their

fruiting bodies (Lilleskov et al. 2002).

It has also been shown that exploration type and mycelium hydrophobicity are associated

with differences in the N sources that EM species can access (Hobbie and Agerer 2010, Hobbie

et al. 2014). In general, hydrophobic species usually belong to long distance exploration types,

forage N at deeper soil horizons, and have higher enzymatic capabilities and δ15N, while

hydrophilic species show the opposite pattern (Hobbie and Agerer 2010, Lilleskov et al. 2011,

Hobbie et al. 2012, Hobbie et al. 2014). Hobbie et al. (2014), in a labeling experiment at the

Duke Forest FACE experiment, found that Russula and Lactarius that are usually classified as

hydrophilic genera showed lower δ15N compared with hydrophilic taxa as expected. However,

some hydrophilic genera (Laccaria and Amanita) showed a high δ15N similar to hydrophobic

species presumably due to exploration of deeper soil horizons. In addition, it has been shown that

organic N uptake is enzymatically costly for EM fungi and requires a high glucose supply from

the host plant (Lindahl and Tunlid 2014). We would therefore expect hydrophobic taxa to

receive more C from the host plant and to be more depleted in δ13C than hydrophilic taxa.

Russula has previously been classified as a hydrophilic genus with an average δ15N of

3.2±0.3 ‰ (Hobbie and Högbert 2012). However, the large range of variation in δ13C (-27.9 to -

22.05) and δ15N (1.06‰ to 10‰) found in this study suggests that Russula may be considerably

more functionally diverse than is generally recognized. Russula species have been reported to

have a variety of exploration types ranging from contact and short distance to medium distance

smooth types (Table 5.2, Agerer and Rambold 2004). Examination of mantle hydrophobicity

data reported on DEEMY database (www.deemy.de) also supports this; 29 Russula specimens

are reported as hydrophobic and 24 as hydrophilic (Table 5.2). In addition, Russula species have

been shown to exhibit contrasting abundance changes in response to N addition and N deposition

(Lilleskov et al. 2011). Collectively, this evidence indicates that Russula species vary widely in

their functional traits. This may be particularly true in tropical ecosystems where collections

records indicate that Russula is the most diverse EM genus.

130

Conclusions and future directions

The δ15N and δ13C isotopic composition of EM fruiting bodies is a useful tool with

potential to connect EM fungal species composition to ecosystem function. Here we demonstrate

that the isotopic composition of the Russula community reflects changes in host abundance and

inorganic N availability, presumably reflecting increased host demand for EM fungal N supply

with a reduction in soil inorganic N availability. Corrales et al. (2016b) demonstrated that the

presence of Oreomunnea mexicana and therefore its associated EM fungi is associated with a

reduction in soil inorganic N availability. Here we provide evidence that this is consistent with

an increase in N sequestration by EM fungi in sites with higher host abundance. Since host

abundance, N availability, and N transfer from EM fungi to the host (reflected in fruiting body

δ15N) all change in the same direction isotopes provide further evidence that the formation of

Oreomunnea dominated forest is facilitated by its associated EM fungi (Figure 5.9).

The high interspecific variation in Russula isotopic composition and it association with

other functional traits may explain why Russula abundance and diversity did not change with N

addition in Corrales et al. (Chapter 3). N addition may have increased the abundance of

nitrophilic species and reduced the abundance of nitrophobic species while richness at the genus

level was unchanged.

Future studies focusing on tropical Russula exploration types coupled with an N15

labeling experiment should be done to corroborate the soil depth at which Russula species forage

for nutrients and their actual exploration types and mantle properties. Functional trait databases

should also be enriched with more information on tropical species to improve our ability to

associate species composition with ecosystem function.

131

Figures and Tables

Figure 5.1. Direction of reported changes in δ15N and δ13C of EM fruiting bodies.

Arrows show only direction of the expected change but are not proportional to the

magnitude of those changes.

2

3

4

5

6

-26.0 -25.5 -25.0 -24.5 -24.0d13C

d15N

HF#

MF#

+N#

LF#

C#

SAP#

Forages#N

#at#d

eepe

r#soil#horizo

n#

Transfers#m

ore#N#to

#plant#

Higher#access#to#organic#N#so

urces##

Saprop

hy@c#A##Hydroph

ilic##A##Hydroph

obic##

Ectomycorrhizal##################################Saprophy@c#(plant#sugars)########################################(cellulose)##

δ13#C##

δ15 N##

##A#######Plant#drought#stress######+#Understorey##################Overstorey#

Högberg#et#al.#(1999)#

Hobbie#and#Högberg#(2012)#

More#δ13C#enriched#

More#δ1

5 N#dep

leted#

More#δ13C#depleted#

More#δ1

5 N#enriche

d#

132

Figure 5.2. Upper panel, location of Fortuna Forest Reserve, Panama. Lower panel, sampling

sites at Fortuna: LN, site with low inorganic noitrogen availability (Zarceadero); MN, sites with

medium N availability (Honda A and B); HN, sites with high N availability (Hornito and Alto

Frio); C and +N nitrogen addition and control plots, Upper panel reproduced with modifications

from Andersen et al. (2010)

LN#MN#

C#and#+N#

HN#

133

Figure 5.3 Results of maximum likelihood analysis of Russula obtained from fruiting bodies in Oreomunnea mexicana-dominated stands at Fortuna, Panama, and representative taxa chosen from GenBank as described in the text. Values in the branches represent bootstrap support. Sequences are annotated sequencing code.

AC52

AC132

AC198

AC269

AC270

AC272

AC305

AC317

AC318

AC329

AC331

AC334

AC336

AC430

AC434

AC457

AC497

AC501

AC507

AC516

AC517

AC518

AC520

AC521

AC522

AC528

AC531

AC545

AC572

AC578

AC579

AC581

AC580

AC588

AC591

AC587

AC603

RUSX71

RUSD32

RUSL87

RUSP86

RUSC57

RUSI40RUSV51

RUSS78

RUSX42

RUSF27

RUSA64

RUSI24

RUSP93

RUSP52

RUSG31

RUSF69

RUSP35

RUSO98

RUSC59

RUSC58

RUSV36RUSN64

RUSP85

RUSF17

RUSS19

RUSR22

RUSB35

RUSV39

RUSS71

RUSU41

RUSU52

STEH63AMYL46

GLOP81BONM23

AC335

AC503

AC511

AC691

AC706

AC707

AC716

AC719

AC720

AC723

AC724

AC769

AC783

AC792

AC801

AC803

AC805

AC815

AC819

AC822

AC823

AC830

AC834

AC856

AC858

AC864

AC865

AC872

AC874

AC878

AC881

AC893

AC896

AC907

AC911

AC912

AC917

AC927

AC1030

AC1031

AC1035

AC1044

AC1046

AC1047

AC1048

AC1049

AC1053

AC1054

AC1056

AC1058

AC1063

AC1064

AC1079

AC1083

AC1084

C AC688

C AC1040

AC271AC431AC448AC523AC527AC584

AC369

AC403AC416AC590

AC827AC859

AC837AC850

AC895

Root

100

78

69

32

10043

60

55

80

68

100

46

100

69

80

55

85

88

10090

100

57

50

50

8572

10088

97

99100

99

100

67

10060

94

10091

58

57

54

66 9966

89

100

93

72100

100100

74

97 10094

54100

82

94

76

10094

100

89

100

82

10051

100

49

52

82100

99

91

86

9578

89

53

69100

84

55

100

52

100

89

66

99

93

50

5990

92

50

96

58

68

47

63

93

93

64

70100

94

30

79

75

73

93

95

100

64

85

100

99

90

10091

34

78

74

95

86

60

39

100

100

100

90

134

Figure 5.4 OTU mean values for (A) δ13C and (B) δ15N. Dot colors represent sites with

contrasting soil inorganic N availability.

-22

-26

-30

-34

OTUS 97%

d13C

S7 C006 S36 S40 S5 S6 S1 C0019 S35 S3 S41 C0035 S31 S37 S33 S42 C003 S28 S29 C0020 S39 S26 S4 S27 S30 S38 S32 S25

C+NLNHNC_N

02468

OTUS 97%

d15N

S37 S32 S30 S35 S4 S29 S33 C0020 C003 S39 S26 S3 S41 C0035 C0019 S1 S36 S38 C006 S40 S31 S6 S42 S7 S27 S28 S5 S25

C+NLNHNC_N

-22

-26

-30

-34

OTUS 97%

d13C

S7 C006 S36 S40 S5 S6 S1 C0019 S35 S3 S41 C0035 S31 S37 S33 S42 C003 S28 S29 C0020 S39 S26 S4 S27 S30 S38 S32 S25

C+NLNHNC_N

02468

OTUS 97%

d15N

S37 S32 S30 S35 S4 S29 S33 C0020 C003 S39 S26 S3 S41 C0035 C0019 S1 S36 S38 C006 S40 S31 S6 S42 S7 S27 S28 S5 S25

C+NLNHNC_N

A"

B"

δ13$C$$

δ15N

$$

135

Figure 5.5 Russula fruiting bodies community average for (A) δ13C and (B) δ15N in soil

low (LN), medium (MN), and high (HN) inorganic N availability levels and for the

control and N addition plots (C and +N). Error bars represent ± 1SE of the mean.

-26.0

-25.5

-25.0

-24.5

-24.0

LN MN C HN +NTreatment

d13C

2

4

6

8

LN MN C HN +NTreatment

d15N

*"*"

LN"""""""""""""MN""""""""""""""C""""""""""""""HN"""""""""""""+N"

δ13 C"(‰

)""

δ15 N"(‰

)"

A" B"

a"

ab"

b"

ab"ab"

ab"ab"

b"

a"a"

Site"(ordered"by"N"availability)"LN"""""""""""""MN""""""""""""""C""""""""""""""HN"""""""""""""+N"

Site"(ordered"by"N"availability)"

136

Figure 5.6 Russula community average isotopic values for sites with low (LN), medium

(MN), and high (HN) inorganic N levels, and for control (C) and N addition (+N) plots

and for a comparison group of saprophytic fungi (SAP). Vertical and horizontal error bars

represent ± SE.

HF#

LN#

+N#

MN#

C#

SAP#

δ15 N#(‰

)#

δ13C#(‰)#

137

Figure 5.7 Linear regressions between (A) 1/ Russula community average of δ15N vs average percentage of N of fruiting bodies per site, (B) Natural logarithm Oreomunnea basal area vs Natural logarithm of Russula community average of δ13C, (C) Soil inorganic N availability vs Oreomunnea basal area.

2.0 2.5 3.0 3.5 4.0 4.5

1.2

1.4

1.6

1.8

2.0

LN Oreomunnea BA (m2/ha)

LN R

ussu

la c

omm

unity

d15

N

0.18 0.20 0.22 0.24 0.26

3.5

4.0

4.5

5.0

5.5

1 / Community d15 N

Com

mun

ity N

% in

frui

ting

bodi

es R2 = 0.99, P < 0.001

1"/"Russula"community"δ15N"

A"

B"

Russula"commun

ity"δ

15N"

0 10 20 30 40 50 60 70

010

2030

4050

60

Soil inorganic N (µg N/bag)

Ore

omun

nea

BA (m

2/ha

) R2= 0.70, P= 0.048C"

Oreomunnea"BA"(m2/ha)"

Oreom

unnea"BA

"(m2 /ha)"

R2"="0.95,"P"="0.002"

R2"="0.99,"P"<"0.001"

R2"="0.70,"P"="0.048"

138

Figure 5.8 Maximum likelihood phylogeny of Russula obtained from fruiting bodies and

trimmed to include only samples with isotope data. Bubbles at the tree tips represent

δ13C, δ15N. The size of the bubble is at scale with the δ13C, δ15N average values per OTU.

Annotations at tree tips correspond to the closest matching sequence in GenBank and the

sample collection number.

AC691AC864AC917AC865AC896AC1056AC1046AC803AC927AC707AC719AC1053AC1079AC706AC858AC724AC783AC1048AC872AC893AC878AC716AC801AC823AC827AC859AC805AC830AC881AC723AC769AC856AC1031

d13C

d15N

AC691AC864AC917AC865AC896AC1056AC1046AC803AC927AC707AC719AC1053AC1079AC706AC858AC724AC783AC1048AC872AC893AC878AC716AC801AC823AC827AC859AC805AC830AC881AC723AC769AC856AC1031

d13C

d15N

Russula nigricans (CO5211) Russula nigricans (AC626) Russula sp. (AC508) Russula atropurpurea (AC424) Russula aff. betularum (AC648) Russula sp. (AC574) Russula sp. (AC336) Russula sp. (AC629) Russula sp. (AC494) Russula sp. (AC518) Russula sp. (AC561) Russula sp. (AC449) Russula sp. (AC645) Russula sp. (AC614) Russula lutea (AC640) Russula corallina (CO5430) Russula sp. (AC558) Russula cf. favrei (AC381) Russula xerampelina (AC616) Russula cf. flavisiccans (AC454) Russula lepida (CO5478) Russula lepida (CO5435) Russula sp. (AC342) Russula sp. (AC462) Russula sp. (AC552) Russula cyanoxantha (AC554) Russula cf. cyanoxantha (CO5429) Russula variata (CO5440) Russula cerolens (AC601) Russula cerolens (AC632) Russula crassotunicata (AC607) Russula sp. (AC591) Russula sp. (AC422)!!

δ13C

!

δ15N

!

λδ13C!=!6.61e-5,!P!=!1!λδ15N!=!0.66,!P!=!0.03!*!!

139

Figure 5.9 Feedback loop to explain monodominance of Oreomunnea mexicana based on

the ‘microbial competition for nitrogen hypothesis’ (Corrales et al. 2016b) and EM

fruiting bodies δ15N. Abbreviations: Ectomycorrhizal (EM).

Hypothesis*for*EM*mediated*N*sequestra5on*

High%abundance%of%Oreomunnea)

High%abundance%of%EM%fungi%

EM%fungi%compete%with%saprophy8c%fungi%slowing%down%decomposi8on%rates%

and%reducing%the%availability%of%inorganic%nitrogen%in%the%soil%

Lower%soil%inorganic%N%availability%and%higher%

Oreomunnea%abundance%increase%demand%for%N%transfer%from%EM%fungi%

to%Oreomunnea%%

Increased%N%transfer%from%EM%fungi%is%coupled%with%increased%C%transfer%from%Oreomunnea%to%EM%fungi%suppor8ng%more%fungal%biomass%and%increasing%

N%sequestra8on%

Increase%survivorship%and%growth%rate%of%

Oreomunnea%seedlings%N*

C*

140

Table 5.1 Total soil inorganic N, dry season rainfall (Jan-April), and number of Russula

fruiting body collections, ITS sequences, OTUs, samples with isotope data and samples

with both isotope and sequence data per site. F and P values from ANOVA analysis

including all sites and a post-hoc Tukey’s test (as super indexes) are given for δ13C and

δ15N.

Fertility Sites Total soil N

(µg N/ bag)

Total rain dry season

(mm)

No. Collections

ITS sequences

No. OTUS Isotopes Both

High N Alto Frio, Hornito

40.48 97.75 43 20 17 25 2

Medium N Honda A, B

25.42 209.70 34 28 8 7 6

Low N Zarceadero 2.74 189.42 25 15 12 16 1

Control1 Plots 51, 54, 56, 58

33.65 209.70 36 29 17 31 24

N addition1 Plots 52, 53, 55

55.71 209.70 17 16 5 11 10

Total 158 108 52 93 43 1Control and N addition plots are from an N fertilization experiment established at the medium N site

141

Table 5.2 Summary of exploration type and presence of mantle hydrophobicity of all the

Russula species included in the DEEMY database (Agerer and Rambold 2004-2016).

Exploration type Hydrophobic Hydrophilic Both No information Total

Contact 1 18 1 11 31 Contact/Short distance

2

2

Medium distance smooth 22 2

2 26 Short distance 6 2 1

9

Total 29 24 2 13 68

142

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146

Chapter 6: Conclusions

Main results and mechanisms facilitating monodominance of Oreomunnea mexicana

Results from Chapter two reveal that species diversity of EM fungi associated with

Oreomunnea is high and suggests that tropical EM fungal communities can be as species-rich as

those found in temperate forests (Diédhiou et al. 2014; Henkel et al. 2012; Smith et al. 2011).

Consistent with the few previous studies of EM fungal communities in tropical forests, we

observed strong community dissimilarity of EM fungi across sites.

Results from Chapter three shows that ectomycorrhizal communities play an important

role in soil nutrient dynamics due to their ability to acquire organic nitrogen via extracellular

enzymes. After running experiments to test for presence of EM networks and positive plant-soil

feedback our results suggest that neither of those mechanisms account for monodominance in

our study system. Instead, I found that Oreomunnea dominated forest is associated with lower

availability of soil ammonium and nitrate than nearby arbuscular mycorrhizal dominated forest.

This reduction in inorganic N availability is most likely associated with a tightened N cycle, with

low rates of nitrification, denitrification and gaseous N losses from the soil organic layer. I

propose that reduced N availability, driven by the depletion of readily mineralizable N from soil

organic matter by EM fungi, could confer Oreomunnea seedlings a competitive advantage over

AM or non-mycorrhizal species accounting for the dominance of this species.

Results from Chapter four suggest that nine years of N addition can cause a decrease in

the abundance of EM species adapted to low N availability and reduce soil enzyme activity

associated with the mineralization of organic N and P in tropical montane forest. A reduction in

the abundance of EM fungal taxa specialized in organic N and P absorption (e.g., Cortinarius)

along with a decrease in EM colonization of host plants could cause a decrease in the abundance

of EM associated plants with potential feedback effects on decomposition rates and soil C

storage.

147

Results from Chapter five demonstrate that the δ13C and δ15N of the Russula community

reflect changes in Oreomunnea mexicana abundance and inorganic N availability, presumably as

a consequence of increased host demand for EM fungal N in response to a reduction in soil

inorganic N availability. I also demonstrated that the presence of Oreomunnea mexicana and its

associated EM fungi is correlated with a reduction in soil inorganic N availability consistent with

an increase in N sequestration by EM fungi in sites with higher host abundance. Given that sites

with lower inorganic N availability also show evidence of higher C transfer from the host plant,

EM fungi will have a higher fungal biomass and therefore will retain a larger amount of

ecosystem N. This would imply that higher C allocation from the tree to EM fungal species

could decrease N availability for free-living saprotrophs and non-EM plant species creating a

positive feedback loop contributing to increased abundance of Oreomunnea mexicana in sites

with lower inorganic N availability. This finding provides further evidence that the formation of

Oreomunnea dominated forest is facilitated by its associated EM fungi.

Implications of EM dominated tropical montane forest for N cycling and soil C storage

Tropical forests play a critical role in the global C cycle. They account for almost 40

% of global net primary productivity, store approximately 25 % of global biomass C, and

contribute 10 % of global soil C (Post et al. 1982, Townsend et al. 2011). Consequently, the

impact of global environmental change on tropical forest ecosystem function and feedbacks on

biogeochemical cycling is are important aspects of climate regulation at regional and global

scales this century (Malhi et al. 2008).

In general, the presence of EM fungi has been associated with reduced litter

decomposition rates and increased accumulation of soil organic matter due to strong competition

between EM fungi and the community of free-living saprotrophs for N (Averill et al. 2014). This

has been amply demonstrated in temperate forest, and has been termed the “mycorrhizal-

associated nutrient economy” where AM and EM dominated forest differ significantly in their

nitrogen, phosphorus, and carbon cycling (Phillips et al. 2013, Brzostek et al. 2015, Rosling et al.

2016). Here we provide evidence that indicates that the “mycorrhizal-associated nutrient

economy” model can also be applied to tropical montane forest. Here we demonstrate that soils

under Oreomunnea mexicana monodominant forest have lower inorganic N than those under

148

adjacent AM-dominated forest. At a pan-tropical scale, Oreomunnea mexicana, and other

tropical monodominant EM trees such as Quercus spp, are predicted to have a significant impact

on global C storage.

Future directions on tropical ectomycorrhizal research

Understanding the ecology of complex inter-kingdom interactions like mycorrhizas

will contribute to advancing the frontiers of knowledge in biological science. EM associations

are the living interface between plants and soils and therefore play an important role in

regulating nutrient cycles in many forests (Alexander and Lee 2005). It is becoming increasingly

clear that EM fungal species exhibit inter- and intrageneric variation in their morphology and

physiology (Courty et al. 2010). Understanding fungal functional traits, including response and

effect traits, is essential to predicting the influence of fungi on ecosystem processes (Koide et al.

2014). In particular, EM fungal functional traits may have a strong influence on terrestrial C

cycling (Averill et al. 2014, Tresseder et al. 2012). Studies of how EM fungal community

composition and functional traits are coupled with soil C storage in tropical forest may therefore

improve predictions for C emissions in tropical forest and provide insights into how to manage

tropical forests for C sequestration.

The influence of Oreomunnea mexicana on nutrient cycling is likely context-dependent

and factors such as soil fertility, precipitation, temperature, and fungal community composition

may all be important. Because montane tropical forests are under increasing anthropogenic

pressure and are forecast to be strongly impacted by climate change, it is critical that we study

how these changes will impact the EM fungal communities associated with Oreomunnea and

other Juglandaceae and understand the role of both plants and fungi in nutrient cycling. Future

research should build on this work in tropical forest to further integrate fungal community

dynamics with ecosystem properties at larger spatial and temporal scales. Research should also

focus on understanding how shifts in fungal community composition caused by natural

environmental variation, climate change, or N deposition could differentially affect fungal taxa

with different functional traits, and as a consequence influence soil biogeochemical cycling.

149

Analysis of the isotopic composition of Russula fruiting bodies was shown here to be a

useful tool for understanding the role of EM fungal communities on ecosystem processes. Future

studies focusing on tropical EM fungal species exploration types coupled with 15N labeling

experiments should be done to corroborate the soil depth at which EM fungal species forage for

nutrients and it associations with their exploration types and mantle properties. Functional trait

databases should be enriched with more information on tropical species to improve our ability to

associate species composition with ecosystem function.

150

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Averill C, Turner BL, Finzi AC (2014) Mycorrhiza-mediated competition between plants and decomposers drives soil carbon storage. Nature 505: 543–545.

Brzostek ER, Dragoni D, Brown ZA, Phillips RP (2015) Mycorrhizal type determines the magnitude and direction of root-induced changes in decomposition in a temperate forest. New Phytologist 206: 1274–1282.

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