AN ABSTRACT OF THE THESIS OF
Maria Osuna Garcia for the degree of Master of Science in Forest Science presented on
June 28, 2013.
Title: Examining Ectomycorrhizal Communities of Ponderosa Pine and Lodgepole Pine
in the South-central Oregon Pumice Zone
Abstract approved:
_____________________________________________________________________
Jane E. Smith
Background information is presented that provides historical perspectives on the
field of mycology in the Pacific Northwest and its role in forest management. The series
of events and decisions that have led to previous studies (or lack of studies) in the field
also dictate the directions of current research. Culture, philosophy, and history all play a
role in the questions that may be asked today. Examining the past gives light to the
questions that are asked in the present and future.
Forest ecosystems of the Pacific Northwest are changing as a result of climate
change. Rise of global temperatures, decline of winter precipitation, earlier loss of
snowpack, and increased summer drought are altering the range of Pinus contorta. As
environmental conditions change, Pinus ponderosa may establish within the historic
Pinus contorta range. Successful pine species migration will be constrained by the
distribution or co-migration of ectomycorrhizal fungi (EMF).
Knowledge of the linkages among soil fungal diversity, community structure, and
environmental factors is critical to understanding the organization and stability of pine
ecosystems. The objectives of this study are to establish an informational foundation of
the EMF communities of P. ponderosa and P. contorta in the Deschutes National Forest
and to examine soil characteristics associated with community composition. We
examined EMF root tips of P. ponderosa and P. contorta in soil cores and conducted soil
chemistry analysis for P. ponderosa.
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©Copyright by Maria Osuna Garcia
June 28, 2013
All Rights Reserved
Examining Ectomycorrhizal Communities in Ponderosa Pine and Lodgepole Pine in the
South-central Oregon Pumice Zone
by
Maria Osuna Garcia
A THESIS
submitted to Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of Science
Presented June 28, 2013
Commencement June 2014
Master of Science thesis of Maria Osuna Garcia presented on June 28, 2013.
APPROVED:
_____________________________________________________________________
Major Professor, representing Forest Science
_____________________________________________________________________
Head of the Department of Forest Ecosystems and Society
_____________________________________________________________________
Dean of the Graduate School
I understand that my thesis will become part of the permanent collection of Oregon State
University libraries. My signature below authorizes release of my thesis to any reader
upon request
_____________________________________________________________________
Maria Osuna Garcia, Author
ACKNOWLEDGEMENTS
I would like to thank my advisor Dr. Jane E. Smith, for giving me the opportunity
to work on this project. Jane, thank you for your kindness and your patience throughout
the years. I would also like to thank my committee members Dr. Paul Doescher and Dr.
Melanie Jones for their support throughout this process. I am grateful to Dr. Dan Luoma
for providing support, mentorship, and advice. I am also thankful to Dr. Bruce McCune
for providing the resources to tackle the datasets that came along with this project. I
would also like to thank all the people at the Corvallis Forestry Sciences Lab that assisted
me throughout the project: Levi Davis, and Tara Jennings, Doni McKay, and Joyce
Eberhart.
I am thankful for my support system at home, Norman Forsberg and Alexandra
Hesbrook; you are wonderful friends and have been there for me through some of my
biggest challenges. Thank you for your love and support. I would also like to thank Ed
Mitchell for being willing to spend his time teaching me about community analysis and
getting me closer to being successful. Of course, I would like to thank my family for
risking their lives, crossing the border, and starting a new life in a foreign country, so that
I could have better opportunities such as this one. All the hard work that went into this
project is done in their honor.
Most importantly, I would like to thank my undergraduate advisor Dr. Kathleen
Treseder because she was gracious enough to give an undergrad a chance to be involved
in science and the opportunity to learn about the world of forestry. I also want to thank
all the members in the Treseder lab for teaching me so much, and the California Alliance
for Minority Participation Program at the University of California, Irvine for providing
the funds to make it possible for me to make it this far. Finally, I am grateful for the
National Science Foundation Graduate Research Fellowship Program and the USDA
Forest Service Pacific Northwest Research Station, Land and Watershed Management
Program for providing financial support for this endeavor.
TABLE OF CONTENTS
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LIST OF FIGURES
Figure
Page
Figure 1. Map showing general area of study site in Central Oregon and distribution of
sampling sites in the Deschutes National Forest.......................................................... 45'
Figure 2. Percent occurrence of dominant ectomycorrhizal fungus operational taxonomic
units in Pinus ponderosa by soil core (black) and site (grey)...................................... 46'
Figure 3. Percent occurrence of dominant ectomycorrhizal fungus operational taxonomic
units in Pinus contorta by soil core (black) and site (grey). ........................................ 47'
Figure 4. NMS ordination of Pinus ponderosa and Pinus contorta soil cores in EMF
species space. ............................................................................................................... 48'
Figure 5. NMS ordination of ponderosa pine sites in EMF species space with
superimposed joint plot. ............................................................................................... 49'
Figure 6. Linear relationship between Mineralizable N and species richness ............. 52'
LIST OF TABLES
Table
Page
Table 1. Pinus ponderosa Sites.................................................................................... 31'
Table 2. Operational Taxonomic Units of Pinus ponderosa ....................................... 32'
Table 3. Operational Taxonomic Units of Pinus contorta........................................... 41'
Table 4. Codes for environmental variables and respective correlations with ordination
axes. ............................................................................................................................. 50'
Table 5. Soil Chemistry, Pinus ponderosa. ................................................................. 51'
Examining Ectomycorrhizal Communities of Lodgepole Pine and
Ponderosa Pine in the South-central Oregon Pumice Zone
CHAPTER 1 – HISTORICAL PERSPECTIVES
Many years ago, when Oregon State University was still Oregon’s Agricultural
College, a budding mycologist, by the name of Helen Margaret Gilkey began what
became an epidemic in mycological research in the Pacific Northwest (Trappe 1975).
Although Gilkey was originally trained in the botanical sciences, her endeavors in
mycology were largely influenced by a truffle mycologist at the University of
California, Berkeley by the name of Professor W.A. Setchell, who was known to
collect truffles under eucalyptus trees in Berkeley, California. In 1918, promptly after
publishing her doctoral thesis, Gilkey was hired as a faculty member of Oregon
Agricultural College alongside another newly hired budding mycologist, Sanford
Myron Zeller (Trappe et al. 2009). The interesting bit is that neither was hired as a
truffle taxonomist, but rather as pathologists, yet thus began a series of investigations
that laid the foundation for mycological research in the Pacific Northwest.
Although Gilkey and Zeller’s research dealt primarily with the taxonomic
investigation of truffle species, it had been well known (since 1887) that the
microscopic fungi which associated with the roots of trees were responsible for the
development of truffles and mushrooms (Trappe and Berch 1985). This infection of
tree roots by microscopic fungi, is termed “mycorrhizal symbiosis.” The word
“mycorrhiza” is derived from the Greek word roots mycos- and rhiza-, which translate
respectively to fungus and root. Mycorrhizal fungi establish beneficial relationships
2
with trees such as Douglas-fir and pine all over the Pacific Northwest. The
relationship is described as symbiotic, because the host tree provides photosynthates to
the colonized fungi in exchange for nutrients, such as nitrogen and phosphorus, in the
soil. Ectomycorrhizal fungi (EMF) form an external sheath of hyphae around the fine
roots of the host tree and extend mycelium outward into the soil, reaching larger
volumes of soil than roots of trees alone could access. In addition, EMF are a critical
component of the forest ecosystem because they link aboveground and belowground
components of biogeochemical cycles in forest ecosystems (Treseder and Allen 2000),
protect roots from pathogens, and help maintain soil structure (Amaranthus 1998).
The first correct recognition of the symbiotic nature of EMF occurred in 1885
by Albert Bernhard Frank in Prussia (Trappe et al. 2009). Even though the
microscope had already been well established as an essential tool for conducting
scientific research well before the period of Gilkey and Zeller, mycologists gravitated
towards examining sporocarps rather than mycorrhizae. Likely, it was much more
feasible to track and investigate fungi by unearthing hypogeous fruiting bodies than to
look at the colonized roots of trees. Furthermore, there was an economic and culinary
incentive to digging up certain species of truffles from the ground, which helped to
support the research endeavors of Oregon’s earliest mycologists.
Zeller and Gilkey continued their research on truffle taxomomy in Oregon for
thirty years, and Gilkey continued publishing documents on truffle taxonomy even
after her retirement in 1951, up until 1963. Mycologists, Alexander H. Smith and
Rolfe Singer began exploring western fungi in Oregon and Idaho well before 1958
3
(Singer and Smith 1958) and by 1966 Smith published what was “A Preliminary
Account of the North American Species Rhizopogon.” Here, I would like to emphasize
the word “Preliminary,” because it is astounding that after several decades of research,
mycologists working in the Pacific Northwest had only begun to scratch the surface of
the intricate science that involved identification of hypogeous fungi. With that
publication, Smith officially established Rhizopogon as “the world’s largest and most
complex of all truffle genera” and by his death in 1986, was touted as having
“established a legacy of advancing our knowledge” of truffle fungi in the Pacific
Northwest (Trappe et al. 2009).
Defining the Pacific Northwest
In the book The Pacific Northwest, An Interpretive History, it is recognized
that a consensus of the Pacific Northwest boundaries is difficult to come by (pg 1) but
a map recognizing the “Major Cities and Towns of the Pacific Northwest” is presented
with major cities mainly encompassing all of Idaho, Washington and Oregon
(Schwantes 1996). In “Diversity, Ecology, and Conservation of Truffle Fungi in
Forests of the Pacific Northwest,” where a lot of truffle and mycological history can
be found, the Pacific Northwest is defined as an area that consists of Northern
California, most of Oregon, Washington, most of Idaho, and a portion of Montana and
British Columbia (Trappe et al. 2009). Yet, in publications on mycology by the
Pacific Northwest Research Station, the majority of studies that are identified as
pertaining to the Pacific Northwest have taken place in an area sandwiched between
the coast range and the Cascade Mountains primarily in stands of Douglas-fir. In
4
Oregon, the highest concentration of areas in which mycological studies take place is
west of the Cascades in Douglas-fir stands (Fogel 1976). A contributing factor to
keeping research west of the Cascade Range was the establishment of the HJ
Andrew’s Experimental Forest, which encouraged mycologists at Oregon State
University and at the Pacific Northwest Research Station to set up studies in old
growth Douglas-fir (Hunt and Trappe 1987; Luoma 1988; Luoma et al. 1991; Smith et
al. 2002).
When it comes to belowground investigations of mycorrhizal fungi east of the
Cascade Range, the studies are but a handful. The very first account of the evaluation
of mycorrhizae on pine was by Ernest Wright, professor of forest pathology at Oregon
State University (Trappe, Personal communication, (Wright 1957), in a study that
examined survival of mycorrhizal associated and non-mycorrhizal associated
ponderosa pine seedlings in the Deschutes National Forest. In 1963, a study was
published that was the first attempt to identify mycorrhizal fungi in ponderosa pine
(Pinus ponderosa) and lodgepole pine (Pinus contorta) in the Pacific Northwest, with
conclusions indicating Cenococcum graniforme, now named Cenococcum geophilum,
as the dominant mycorrhizal species (Wright 1963). Even though C. graniforme was
identified as the dominant species, Wright‘s research is limited because it does not
describe many of the other species that make up the community composition of the
root systems of pine. It may be the case, that C. graniforme resulted as a highlighted
species in comparison to other species because C. graniforme ectomycorrhizae exhibit
unique and distinct morphological characteristics that are easily identifiable in
5
comparison to other EMF. In 1971, Wright once again delves into mycorrhizal
research and attempts to describe EMF on Douglas-fir and ponderosa pine. Again
there is an emphasis on C. graniforme as the dominant mycorrhizal type and any
mycorrhizae encountered in the study that deviated from the morphology of C.
graniforme are identified as “other” (Wright 1971). In addition, it is imperative to
point out that Wright’s research was decades prior to the use of molecular tools, which
allow researchers to make a more thorough examination of microscopic organisms
such as mycorrhizae colonizing the roots of trees.
The utilization of molecular tools and development of protocols to examine
fungi at a molecular level revolutionized the field of mycology because scientists
interested in studying belowground fungal communities could now identify EMF root
tips down to genus and/or species. Amplification and direct sequencing of fungal
DNA (White et al. 1990) gave mycologists the ability to break free from the
limitations of having to rely on morphological characteristics to identify particular
fungi in forest stands. Furthermore, the incorporation of DNA technology in fungal
research made it more feasible to explore larger geographic areas and provide a
thorough investigation of the community structure of fungal species colonizing forest
soils. Molecular tools also lifted the limitation of having to rely on fruiting bodies as
a way to identify fungi and remain tied to a particular geographic area where fruiting
bodies are plentiful.
Breaking Through to the Other Side
It was not until 1997 that studies of EMF in eastern Oregon were once again
6
picked up by researchers investigating post-fire Pezizales and EMF communities of
ponderosa pine in the Blue Mountains of eastern Oregon (Smith et al. 2004; Fujimura
et al. 2005; Smith et al. 2005). At this point in time, researchers aimed at examining a
mycorrhizal fungi in ponderosa pine using molecular tools. The execution of these
studies was largely influenced by an incentive to understand fire dynamics in a system
that had been pushed out of balance due in part to limited understanding of the
ecological role of fire in forest ecosystems and to the relentless “Smokey the Bear
Syndrome,” a Euro-American belief that all fire is destructive and strong efforts
should be made to contain or eliminate it (Boyd 1999). A streak of fire suppression in
eastside forests led to high fuels and a higher risk of stand replacing fire; a state of
imbalance for an ecosystem that benefits from burning (Forest History Society 2013).
A shift in the popular mentality of the need for fire suppression and a shift in the
Forest Service policies incited a desire to understand the role of fire in forest
ecosystems, and with that came prescribed burn treatments which once again opened
up a window of opportunity to take a look at the effects of fire on mycorrhizal fungi
that lay buried underneath the earth’s surface (Smith et al. 2004; Smith et al. 2005).
Similarly today, we are faced with a new dilemma and a desire to restore and
repair ecosystem processes that have been affected by our actions. In the last decade,
there has been a tremendous shift in attitudes concerning the impacts of anthropogenic
activities, which are causing a change in the earth’s climate. Climate change is no
longer a topic that concerns only atmospheric chemists and earth system scientists, but
a topic that is now relevant to politicians, farmers, forest managers, and even citizens
7
of the world. In 2010, a study was published that suggested that there would be a
strong decline in lodgepole pine by the end of the 21st century (Coops and Waring
2011). This brings us to the current research, which aims to characterize the EMF
community composition of ponderosa pine and lodgepole pine in the Deschutes
National Forest.
Projected climate change models suggest that lodgepole pine will decline in the
NW United States by the end of the 21st century (Coops and Waring 2011) and
variations in climatic conditions, including earlier spring warming, may favor
establishment of ponderosa pine within the historic lodgepole pine range (Coops and
Waring 2011). Climate change may also affect soil moisture levels and thereby
influence fungal communities. Successful pine species migration will be constrained
by the distribution or co-migration of fungal symbionts, so knowledge of the linkages
among soil fungal diversity, community structure, and environmental factors is critical
to understanding the organization and stability of pine ecosystems (Simard and Austin
2010). In addition, EMF are a critical component of the forest ecosystem because they
link aboveground and belowground components of biogeochemical cycles in forest
ecosystems (Treseder and Allen 2000). Nitrogen (N), phosphorus (P), and carbon (C)
are key nutrients in soil systems and are important for fungal nutrition. The
availability of these nutrients is known to control mycorrhizal abundance because
plants will invest more C in mycorrhizal fungi when N and P are limiting to plant
growth (Mosse and Phillips 1971; Treseder 2004). Conversely, mycorrhizal abundance
is expected to decline if N or P availability increases in the soil, resulting in C-limited
8
mycorrhizae (Read 1991). Belowground biogeochemical dynamics contributing to the
availability of N, P, and C in the soil may in turn drive EMF community composition
(Lilleskov et al. 2002) so it is important to analyze the biogeochemical structure of the
soil and how it affects the formation of EMF communities.
We need to understand the state of ecosystems now so that we can predict how
they may respond to climate change scenarios and so that we can better manage the
system to meet particular objectives. Not only will this study provide information that
will help forest managers deal with climate change scenarios, but will help expand
mycological research in the Pacific Northwest by crossing the boundaries of the
Cascade Range and establish an informational foundation about the state of EMF
community structure of pine in pumice soils of the Deschutes National Forest.
'
9
CHAPTER 2 - ECTOMYCORRHIZAL COMMUNITIES OF PONDEROSA PINE
AND LODGEPOLE PINE IN THE SOUTH-CENTRAL OREGON PUMICE ZONE
Introduction
Forest ecosystems of the Pacific Northwest are changing as a result of the
effects of climate change (Vose et al. 2012). The rise of global temperatures, decline
of winter precipitation, earlier loss of snowpack, and increased summer drought are
altering the range of economically and ecologically important tree species, such as
lodgepole pine (Pinus contorta Douglas ex Loudon)---a species that thrives in lowtemperature zones also known as “frost pockets”. Additional stressors, such as
concurrent bark beetle infestations, are contributing to the demise of this widely
distributed early seral-stage tree species. In fact, a recent study based on climate
change models suggests that lodgepole pine will decline in the NW United States by
the end of the 21st century (Coops and Waring 2011). As climate change transforms
the lodgepole pine zone into a warmer drier environment, drought tolerant tree species
such as ponderosa pine (Pinus ponderosa Lawson) may establish within the historic
lodgepole pine range (Coops and Waring 2011).
Pine species migration is a complex process that requires the examination of
ecological linkages such as the belowground and aboveground components of a forest
ecosystem. For a tree species to most effectively compete in a particular region,
environmental conditions such as temperature, precipitation, water-availability,
photosynthetic capacity, and soil conditions must be at an optimal level to favor one
10
tree species over another. In addition, trees need to form symbiotic relationships with
mycorrhizal fungi for optimal survival and growth (Jones and Smith 2004). Successful
pine species migration will be constrained by the distribution or co-migration of
belowground fungal symbionts (Perry et al. 1990). The impacts of climate change may
change belowground fungal communities (Pickles et al. 2012) so that they may be a
limiting factor in tree migration. Furthermore, knowledge of the linkages among soil
fungal diversity, community structure, and environmental factors is critical to
understanding the organization and stability of pine ecosystems (Simard and Austin
2010).
Mycorrhizal fungi establish obligate beneficial relationships with pine. The
relationship is termed symbiotic, because the host tree provides photosynthates,
sources of carbon (C), to the colonized fungi in exchange for nutrients in the soil such
as nitrogen (N) and phosphorus (P). Ectomycorrhizal fungi (EMF) form an external
sheath of hyphae around the fine roots of the host tree and extend mycelium outward
into the soil reaching further ground than roots of trees alone could access (Smith and
Read 2008). Furthermore, EMF are a critical component of the forest ecosystem
because they link aboveground and belowground components of biogeochemical
cycles in forest ecosystems (Treseder and Allen 2000). Specifically, fungi are known
to be important players in the decomposition and mineralization of organic matter
(Schimel and Bennett 2004). Nitrogen, P, and C are key nutrients in soil systems and
are important for fungal nutrition. The availability of these nutrients is known to
control mycorrhizal abundance because plants will invest more C in mycorrhizal fungi
11
when N and P are limiting to plant growth (Mosse and Phillips 1971; Treseder 2004).
Conversely, mycorrhizal abundance is expected to decline if N or P availability
increases in the soil, resulting in C-limited mycorrhizae (Read 1991). Belowground
biogeochemical dynamics contributing to the availability of N, P, and C in the soil
may in turn drive EMF community composition (Lilleskov et al. 2002; Treseder 2004)
so it is important to analyze the biogeochemical structure of the soil and how it affects
the formation of EMF communities.
Many of the factors that contribute to the formation of EMF communities in
soil systems are based on specificity phenomenon of mycorrhizal fungi (Molina et al.
1992). In specificity phenomenon theory, mycorrhizal fungi may vary in host range
from narrow (associating only with a single plant genus or family) (Massicotte et al.
1994; Bruns et al. 2002) to broad (associate across a diversity of plant genera,
families, and orders) (Molina and Trappe 1982). Conversely, host-receptivity defines
the numbers and diversity of mycorrhizal fungi that are accepted by a particular host.
Ecological specificity is a result of biotic and abiotic factors that control the ability for
plants to form relationships with particular fungi in the soil and also plays a role in
EMF community formation (Molina et al. 1992). The interactions among hostspecificity, host receptivity, and ecological specificity are important to consider when
examining the formation of EMF communities in host specific soil systems. Indeed,
mycorrhizae play a key role in the establishment of plant species in a particular
environment and the presence or absence of particular mycorrhizal fungi might
determine the composition of plant species in forest stands.
12
Common mycorrhizal networks (CMN), defined as the interconnection of
mycorrhizal fungal hyphae and two or more root systems via mycorrhizal fungal
hyphae (Simard and Durall 2004), may also be important for the establishment of new
seedlings in a forest stand. Common mycorrhizal networks may be beneficial to plant
communities when they help distribute resources between plants within the
community and may increase the rate at which new seedlings become infected by
fungal symbionts. If CMNs already exist in stands of ponderosa pine and lodgepole
pine, the transition from a lodgepole pine dominated stand to a ponderosa pine
dominated stand is likely to occur.
Lodgepole pine is currently a widely distributed tree species in eastern Oregon.
The Pinus contorta Zone, found on the pumice plateau, formed as a result of the
eruption of Mount Mazama 6,600 years ago (Volland 1985). Previous studies of
lodgepole pine EMF species in other systems have found Cenococcum geophilum,
Thelephora spp., Mycelium Radicis Atrovirens, Suillus spp., Russula spp., and
Piloderma spp. dominating the community composition (Bradbury 1998; Durall et al.
1999; Byrd et al. 2000; Douglas et al. 2005; Jones et al. 2012). The Pinus ponderosa
Zone extends in a 35-40 mile wide range within the pumice/ash deposits from Mount
Mazama, located south of Bend, OR (Simpson 2007). Overall, very few studies of
EMF on ponderosa pine have been conducted (Kotter and Farentinos 1984; Stendell et
al. 1999; Barroetavena et al. 2005; 2007), and even fewer studies on the mycorrhizal
fungi of pine in Oregon have been conducted east of the Cascade range (Wright 1957;
Wright 1963; Wright 1971; Smith et al. 2004; Fujimura et al. 2005; Smith et al. 2005).
13
No previous studies have utilized molecular tools to examine community composition
and structure of EMF of ponderosa pine and lodgepole pine in the Deschutes National
Forest in Central Oregon.
The dry forests of Central Oregon are ideal for examining fungal microbial
communities that associate with pines. The objectives of this observational study are
to establish an informational foundation of the EMF communities of ponderosa pine
and lodgepole pine in Central Oregon and investigate the role of soil chemistry and its
effects on EMF community structure. We specifically focus our efforts on the
examination of soil chemistry relationships with ponderosa pine because it is one of
the tree species expected to replace lodgepole pine under future climate change
conditions. The information gathered through this study will provide insights into the
driving forces behind the formation of EMF communities in pine, supplementing the
current knowledge for developing management strategies in a system anticipated to
shift with impending climate change.
Methods
Study Area
This study was conducted east of the Oregon Cascade mountain range in the
Deschutes National Forest (Oregon, USA; Figure1). Sites consisted of intermixed
lodgepole pine and ponderosa pine stands of the south-central Oregon pumice zone.
Understory shrub communities include Arctostaphylos patula Greene, Purshia
tridentata Pursh DC, Festuca idahoensis Elmer, and Ceanothus velutinus Douglas ex
14
Hook (Franklin and Dyrness 1988).
Sampling Design
Locations of intermixed ponderosa pine and lodgepole stands in the Deschutes
National Forest were acquired (Chaylon Shuffield, personal communication (Shuffield
2011), and utilized to establish 17 sites for this study (Figure 1). Site centers were
recorded using GPS (Table 1). Randomly selected trees were flagged, painted, and
their GPS coordinates were recorded. A random number table and the second hand of
a watch randomly determined soil core collection sites. A total of 5 soil cores were
collected from 5 ponderosa trees in each of the 17 sites for a total of 85 cores. Since
we sampled from intermixed stands, a ponderosa pine tree needed to be at least 3
canopy diameter lengths away from any lodgepole pine tree in order to meet our
sampling criteria. In addition, 26 lodgepole pine cores were collected from pure
lodgepole stands within the general area of our ponderosa pine stands in the Deschutes
National Forest to compare and contrast the EMF communities of ponderosa pine.
Soil Core Collection
The upper duff layer, consisting primarily of pine needles, was removed and a
soil corer (5 cm diameter) was used to sample to a depth of 10 cm. Each core was
placed into a zip-lock plastic bag and kept in a cooler on ice while in the field and at
4°C during the week of collection. Soil cores were transported back to the lab within 1
day and stored in a cold room (4°C) until processing. All soil core samples were
collected July 2011.
15
Processing of Soil Cores
Soil cores were processed from July 2011 through September 2011. Soil was
sieved (2 mm) out of each core sample and the remaining roots were washed with
water and examined with stereomicroscopy at 10x magnification. All live EMF root
tips were collected per core and grouped based on morphological characteristics such
as color, shape, and surface hyphal formations (Agerer 1993). The total number of
EMF root tips in each core was recorded for 5 soil cores from each site. One tip of
each morphotype per core was washed in a fine sieve using water, placed into a 0.5mL
tube, air-dried overnight, and used for DNA extraction.
DNA extraction, amplification, and sequencing
DNA was extracted from dried EMF root tips using the Sigma Extract-NAmp™ kit (Sigma, Dorset, UK). A crushed dried root tip was placed into a 0.5mL
tube and 10 µl of extraction solution was added. The sample was then incubated at
95°C for 10 min in a thermocycler (BioRad DNA Engine PTC 0200). Following the
incubation, 20 µl of dilution solution was added to the extraction solution and lightly
vortexed. Samples were stored at -20°C until amplification by Polymerase Chain
Reaction (PCR). DNA amplification was carried out in 15 ul reactions using Promega
GoTaq™ and universal fungal primers ITS1f and ITS4 (White et al. 1990).
Amplifications were performed with initial denaturation at 95°C for 2 min, followed
by 35 cycles of 94°C for 30 s, 50°C for 1 min, and 72°C for 1 min. 30 s, with a final
extension of 72°C for 10 min. Successful PCR products were purified using ExoSAPIT™ (USB, Cleveland, OH, USA). Positive amplicons were directly sequenced at the
16
University of Washington on an ABI 3730xl DNA analyzer using ABI reagents
(Applied Biosystems Foster City, CA) and Sanger sequencing determined fungal
species affinities.
Chromatograms were examined, edited, and corrected manually using the
Geneious Pro 5.5.6 Program. Sequences were assembled into Contigs using the
Assembly feature of Geneious and setting the maximum overlap identity parameter to
97%. Sequences were entered into The National Center for Bioscience Informatics
(NCBI) Basic Local Alignment Search tool (BLAST) to determine fungal sequence
identities. Names were assigned to OTU’s using a sequence similarity criteria of
!97% for species, !95% for genera, and "95% to family. When possible, sequences
that were 97% or more identical were assigned the same OTU. Sequences were further
examined using the alignment feature of Geneious Pro. Parameters were set to use
MAFFT v6.814b alignment tool and setting the algorithm to “Auto.” Once aligned,
sequences were manually cross-checked to determine whether they could be assigned
to the same OTU. For this analysis, BLAST hits for Cenococcum geophilum were
grouped into one OTU.
Soil Chemistry
For soil chemistry analysis soil was sieved (2 mm) from each core sample,
composited by site, homogenized, and air-dried. All soil chemistry analyses were
conducted at the Oregon State University Central Analytical Lab following the
methods of Horneck et al. (1989) (Horneck et al. 1989). Soil pH was tested using a
1:2 soil to water ratio. The dilute acid-fluoride method was used to analyze Bray-P.
17
Ammonium (NH4) and nitrate (NO3)were extracted using the KCL extraction method
(Horneck et al. 1989) and quantified using the Alpkem Flow Solution autoanalyzer.
Mineralizable N was measured using the anaerobic incubation method. Total N was
measured using the Kjeldahl procedure. Total Kjeldahl P (TKP) was digested in a
solution of sulfuric acid, potassium sulfate and a catalyst. The resulting
orthophosphate was determined using an Astoria Pacific flow solution analyzer (Will
Austin, Personal Communication). Carbon and N were measured using pure oxygen
combustion on the Leco CNS-2000 Macro Analyzer.
Statistical Analysis
Data Structure
The presence-absence matrices constructed for this analysis are based on a
total of 81 out of 85 ponderosa pine cores because 4 out of the 85 cores failed to give
reliable sequences for use in this analysis. All matrices that include lodgepole pine
data have a total of 26 cores in the matrix.
Multivariate Analyses of OTU presence and absence
PC-ORD software version 6.0 (McCune and Mefford 2011) was utilized to run
non-parametric multivariate statistical analysis. Multi-response Permutation
Procedures (MRPP) (Mielke and Berry 2001) with Sørensen distance measure were
used to test the null hypothesis of no difference between groups (EMF fungal species
OTUs of lodgepole pine and ponderosa pine). The Sørensen's distance is a relative
distance measure and is typically used to analyze presence/absence data (McCune et
al. 2002). MRPP analysis provides a p value for a test of the hypothesis of no
18
difference between groups and an A statistic that represents the chance-corrected
within group agreement and is a measure of effect size (McCune et al. 2002). When
A=0, the groups are no more or less different than expected by chance; when A=1 all
sample units are identical within each group. A stratified random sample approach was
used to account for differences in the number of samples between ponderosa pine and
lodgepole pine. The “Random Sample” option of PC-ORD was used to select 26
random cores out of the total 81 ponderosa pine cores. A bootstrapped confidence
interval was calculated for the MRPP statistic to estimate the variability within by
repeatedly sampling the data over 1000 iterations. Non-metric multidimensional
scaling was used to provide a graphical representation of community relationships
between ponderosa pine and lodgepole pine, where points closer to one another on the
ordination have more similar EMF fungal communities than points further apart. The
Sørensen distance measure was used to calculate similarities in communities and the
settings in PC-ORD were set on “Autopilot Mode” which includes a random starting
configuration and a maximum number of iterations of 500 with 100 runs with real
data. The final instability criterion was set to 0.000001. An NMS ordination with the
same configurations was also generated for ponderosa pine communities and a joint
plot of environmental variables was superimposed on the ordination.
The number of EMF types per soil core (species richness) was used as
response variables. One-factor ANOVA was used for comparisons among sites.
Linear regression was used to examine relationships between species richness and soil
chemistry. To meet the assumptions of normality and constant variance (Sabin and
19
Stafford 1990), species richness was square-root transformed. Analyses were carried
out with StatView software v5.1 (SAS Institute 1999).
Results
Ectomycorrhizal Community Structure of Ponderosa Pine and Lodgepole Pine
This observational study, conducted to determine the similarities or differences
between the EMF communities of ponderosa pine and lodgepole pine, yielded 440
usable DNA sequences (Tables 2 & 3). Dominant OTUs of both pine species in this
system were Cenococcum geophilum Fr. , Inocybe flocculosa Saccardo, and
Rhizopogon salebrosus A.H. Smith (Figures 2 & 3).
EMF commmunities did not differ between ponderosa pine and lodgepole pine
at the species level (MRPP: A=0.001 90% CI -0.0024<A<0.006). Six percent of 1000
bootstrap samples demonstrated a significant difference in community composition
between pine species (Figure 4). However, there was a weak difference between the
EMF communities of ponderosa pine and lodgepole pine at the species level when
singletons (OTUs that occurred only once) were eliminated from the dataset (MRPP:
A=0.01, 90% CI -0.0042<A<0.049). Fifty percent of the 1000 bootstrap samples
demonstrated a significant difference in community composition between pine
species.
20
Soil Chemistry of Ponderosa Pine
Soil chemistry variables with the highest variability across sites were NO3,
NH4, mineralizable N, Bray-P, and C with relative standard deviations greater than
23%. In contrast, we observed low variability in pH across our sites with a relative
standard deviation of about 3% (Table 4).
Environmental relationships of EMF communities on Ponderosa Pine
Our NMS ordination resulted in three dimensions and explained 70% of the
variation in the dataset. Axis one explained 17% of the variation, axis two explained
25% of the variation, and axis three explained 28% of the variation. The strongest
environmental variables related to ponderosa pine EMF composition were
mineralizable N, Bray-P, NO3, NH4, C, TKP, and elevation. Elevation was positively
correlated with axis 1 and NO3 and NH4 were negatively correlated with axis 1.
Mineralizable N and Bray-P were positively correlated with axis 3 (Figure 5, Table 5).
We found a significant linear relationship with mineralizable N and squareroot EMF species richness. Mean square-root EMF species richness treated as
dependent on mineralizable N produced a regression model of Y= 1.436+ 0.21*X;
R2=0.234, p=0.04 (Figure 6).
Discussion
Dominant EMF fungi of ponderosa pine and lodgepole pine
The Ascomycete Cenococcum geophilum was widespread across sites and the
most encountered EMF in ponderosa pine and lodgepine cores. These findings are
consistent with the morphological examination of root tips by Ernest Wright (Wright
21
1963; Wright 1971). It is not surprising that Cenococcum was a dominant type in our
study since Cenococcum geophilum [Cenococcum graniforme (Sow.) Fred & Winge]
is considered the world’s most recognized and widely distributed ectomycorrhizal
fungus (Massicotte et al. 1992). Our results also indicated that Basdiomycete fungi
Rhizopogon salebrosus and Inocybe flocculosa were dominant in our pine forests. The
results of this study are consistent with other studies that have reported Rhizopogon
spp. on pine. Rhizopogon spp. are typical in Pinus and the genus is considered the
largest of hypogeous EMF fungi with the largest assemblage of species occurring in
Pinaceae dominated areas of the Pacific Northwest (Massicotte et al. 1999; Kennedy
and Bruns 2005).
It has been demonstrated, in greenhouse experiments, that ponderosa pine has
the ability to associate with several Rhizopogon species including R. arctostaphylli, R.
ellenae, R. subcaerulescens, R. truncatus, R. rubescens, and R. flavofibrillosus
(Massicotte et al. 1999). While our results are consistent with those of the greenhouse
study at the genus level, our field studies indicate that there is an inconsistency with
the types of mycorrhizae that colonize pine roots in vitro vs. in situ at the species
level.
Inocybe flocculosa has not been previously identified as a species that
associates with ponderosa pine in studies based on the observations of sporocarps
(Barroetavena et al. 2007). This study, however, was able to capture the
Basidomycete EMF as a dominant species. The use of molecular tools may have been
the contributing factor to this finding. Overall, the results of this study are consistent
22
with the idea that dominance by a few species may be a common feature of EMF
fungal communities (Gehring et al. 1998).
Common mycorrhizal networks
The result of no difference between the EMF community of the two pines
supports the hypothesis that the ponderosa pine and lodgepole pine may be forming
CMN in the Deschutes National Forest. Common mycorrhizal networks may be
especially important for an ecosystem that is expected to transition with climate
change because established CMN may be beneficial for the survival of replacement
tree seedlings such as those of ponderosa pine. Previous studies demonstrate that
EMF networks may help enhance EMF seedling survival and growth (Nara 2006;
McGuire 2007) and may facilitate distribution of resources within the system (Simard
and Durall 2004). Furthermore, CMN studies have shown that seedlings that can tap
into CMN are more likely to survive in stressed or harsh environments (Borchers and
Perry 1990; Horton et al. 1999; Marler et al. 1999). Thus, ponderosa pine seedlings
may have a better chance of survival due to the presence of mycorrhizal networks
established previously by lodgepole pine.
Relationship of elevation and EMF communities
Our NMS analysis indicates that elevation may be a factor driving community
structure in ponderosa pine. Some studies suggest that elevation gradients are
correlated with xeric to mesic gradients in ecosystems (Allen and Peet 1990) but
further study would be needed to determine whether there is a correlation between the
elevation gradient and a moisture gradient in these sites.
23
Soil Chemistry
Fungi are versatile and can exist over a wide pH range (pH 4-9) (Brady and
Weil 1996). The pH of the soils sampled in this study ranged between 6.27-6.91 in
ponderosa pine sites. Macronutrient and micronutrient availability in soil is related to
pH and plant available N increases when the pH of the soil is above 5.5 (Brady and
Weil 1996). Phosphorus is more plant available when soil pH is between 6-7, because
iron and aluminum phosphate become more soluble in the soil (Brady and Weil 1996).
The presence of nitrogen-fixing understory shrubs such as Ceonothus velutinus and
Purshia tridentata may also be contributing to N enrichment of these soils (Busse et
al. 2007), but further studies would need to be conducted to examine the effects of
nitrogen fixation on biogeochemical cycles and in order to confirm interactions of the
understory shrub community with pine roots. The results of the NMS analysis suggest
that mineralizable N, NO3, NH4, Bray-P, TKP and C are the main biogeochemical
driving factors for the community composition in ponderosa pine sites. Nitrogen, P,
and C are essential nutrients that are used by EMF fungi and the results of this study
are consistent with other studies indicating that N, P, and C are driving
biogeochemical factors of EMF communities in soil (Lilleskov et al. 2002; Treseder
2004).
24
Relationship between mineralizable N and species richness
The results of simple linear regression suggest that species richness increases
as mineralizable N increases. Time-point of sample collection may have been the
factor leading to this result. Mineralizable N is a measure of the fraction of organic
nitrogen that can potentially be mineralized by soil microbes to produce NH4 and NO3
(Robertson et al. 1999). Most mineralization occurs during the growing season when
the soil is moist and warm. Central Oregon consists of dry ecosystems with the
growing season spanning between late May through June. Our samples were collected
in July when the soils were dry and water availability was low. We may have detected
an increase in species richness because at our sample time-points, micro-organisms
did not have conditions conducive to mineralizing organic nitrogen into plantavailable inorganic forms. Thus, tree species may have invested in different species of
fungi as a strategy because they may have been N-limited. Alternatively,
belowground competition may be driving the relationship between species richness
and mineralizable N. In a system where mycorrhizal fungi are present, root nitrifiers,
heterotrophs, and other microbial organisms may also exist. If there is a release of
inorganic N as a result of mineralization, it cannot be assumed that this will be taken
up by mycorrhizal fungi and tree roots alone (Brady and Weil 1996). Fungi may have
to compete with all organisms in the system for inorganic nitrogen (Norton and
Firestone 1996), thus, trees may invest in many species of fungi as a way to create a
competitive advantage.
25
Conclusions
We found that ponderosa pine and lodgepole pine, located within the
Deschutes National Forest, share the same dominant EMF fungal species. This
finding supports the conclusion that ponderosa pine may be able to successfully
establish within the historic lodgepole pine range in a climate change scenario and
dominant EMF assemblages may be conserved. However, temporal studies would be
necessary to confirm this. Ponderosa pine and lodgepole pine might be forming CMN
in the soil system and knowledge of the presence of fungal networks in the Deschutes
National Forest may prove helpful to forest managers. For example, if an assisted
migration approach is considered as a management strategy (Kranabetter et al. 2012),
EMF networks may help enhance EMF seedling survivorship and growth in this
system. In addition, the biogeochemistry and nutrient availability data presented in
this research may be useful to determine optimal conditions for the survival of
ponderosa pine in this system. Furthermore, the results of this study indicate that the
availability of C, N, and P in this system will be important for the formation of EMF
communities, which in turn are essential for the survival of migrating tree species.
26
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31
Table 1. Pinus ponderosa Sites
Pinus Ponderosa Site Locations and Elevations
Site
4380
BHB
C1
C4ER
C6A
C6B
C7
C8
DEAD LOG
FIN. BUTTE
FIRE BUTTE
HWY31
ICE CAVE
KB
LB
MOFF. BUTTE
PB
Latitude (N)
43°43'46"
43°26'06"
43°44'34"
43°36'00"
43°39'43"
43°40'11"
43°45'29"
43°41'57"
43°35'04"
43°36'36"
43°38'52"
43°28'24"
43°35'07"
43°26'06"
43°46'45"
43°30'29"
43°47'28"
Longitude (W)
121°34'15"
121°17'04"
121°45'00"
121°42'05"
121°51'33"
121°50'51"
121°38'51"
121°22'38"
120°54'59"
121°23'22"
120°59'11"
121°23'26"
121°03'15"
121°21'02"
121°10'45"
121°27'11"
121°25'07"
Elevation (M)
1306
1438
1358
1315
1400
1396
1345
1451
1546
1480
1561
1435
1490
1452
1829
1326
1322
32
Table 2. Operational Taxonomic Units of Pinus ponderosa
Site
Tree
Sample #
Accession #
Analysis Name
Max Identity
4380
1
223
FN550920.1
Inocybe tarda
92%
4380
2
244
JN943885.1
Cenococcum geophilum
97%
4380
2
240
AF377094.1
Gautieria 2
94%
4380
2
245
AM882713.2
Inocybe 14
94%
4380
2
241
FN669236.1
Piloderma 20
90%
4380
3
216
JN943885.1
Cenococcum geophilum
95%
4380
3
212
FN550920.1
Inocybe contig 3
95%
4380
3
218
FN550920.1
Inocybe contig 3
95%
4380
3
219
DQ469291.1
Piloderma 3
91%
4380
3
215
AY880931.1
Rhizopogon salebrosus
97%
4380
3
213
EF458011.1
Rhizopogon salebrosus
97%
4380
3
217
AJ534914.1
Tomentella 2
92%
4380
3
214
AF349699.1
Tricholoma 4
88%
4380
6
234
HM189968.1
Tomentella 4
94%
4380
7
211
HQ604314.1
Inocybe lanuginosa
97%
BHB
1
560
JN943893.1
Cenococcum geophilum
96%
BHB
1
567
HQ604726.1
Cortinarius fulvescens
94%
BHB
1
562
HQ604516.1
Inocybe flocculosa
97%
BHB
1
559
GQ267482.1
Rhizopogon luteorubescens
98%
BHB
1
566
GQ267482.1
Rhizopogon luteorubescens
97%
BHB
1
563
HQ914339.1
Rhizopogon salebrosus
98%
BHB
1
561
FJ845443.1
Tricholoma 6
89%
BHB
1
558
FJ845443.1
Tricholoma myomyces
99%
BHB
2
580
EU427331.1
Cenococcum geophilum
99%
BHB
2
584
HQ604726.1
Cortinarius fulvescens
91%
BHB
2
585
JF908023.1
Geopora 2
87%
BHB
2
581
HQ604404.1
Inocybe 2
94%
BHB
2
582
HQ914339.1
Rhizopogon 12
96%
BHB
2
583
AJ534914.1
Tomentella 2
92%
BHB
3
554
FN669236.1
Piloderma 24
91%
BHB
3
556
AJ534914.1
Tomentella 2
94%
BHB
5
571
EU427331.1
Cenococcum geophilum
99%
BHB
5
569
JN655614.1
Phialocephala 6
95%
BHB
5
572
L54107.1
Suillus pseudobrevipes
97%
33
BHB
6
549
JN943885.1
Cenococcum geophilum
97%
BHB
6
541
JF908130.1
Inocybe 1
93%
BHB
6
544
DQ469291.1
Piloderma 3
91%
BHB
6
550
HQ914321.1
Rhizopogon salebrosus
95%
BHB
6
545
AY880941.1
Suillus brevipes
99%
BHB
6
548
AB286068.1
Tricholoma 2
81%
C1
1
206
AJ515418.1
Rhizopogon 19
85%
C1
1
202
AF377175.1
Rhizopogon15
94%
C1
3
176
AY010281.1
Piloderma 1
80%
C1
3
179
HQ914321.1
Rhizopogon salebrosus
97%
C1
3
177
HM189966.1
Thelephora terrestris
97%
C1
3
180
HM189966.1
Thelephora terrestris
97%
C1
3
171
HQ215826.1
Tomentella 7
94%
C1
6
195
AY239347.1
Gymnomyces 1
94%
C1
6
192
AY239317.1
Gymnomyces 2
85%
C1
6
194
JQ711951.1
Piloderma spp
89%
C1
7
196
JF899555.1
Hebeloma sacchariolens
98%
C1
4
187
HQ604084.1
Agaricales 1
89%
C1
4
188
FN669188.1
Cortinarius 9
94%
C1
4
189
AF377167.1
Rhizopogon arctostaphyli
93%
C4-ER
3
153
DQ469291.1
Piloderma 2
90%
C4-ER
3
155
JF834358.1
Russula 4
92%
C4-ER
4
136
JF908784.1
Boletopsis 1
95%
C4-ER
4
131
EF457902.1
Boletopsis grisea
98%
C4-ER
4
132
DQ680181.1
Rhizopogon 20
96%
C4-ER
5
146
JN943894.1
Cenococcum geophilum
92%
C4-ER
5
140
HQ604213.1
Inocybe auricoma
99%
C4-ER
5
142
HQ604213.1
Inocybe auricoma
98%
C4-ER
5
147
FN550920.1
Inocybe contig 3
95%
C4-ER
6
M149
HQ604516.1
Inocybe flocculosa
99%
C4-ER
6
148
EU846312.1
Leucogastraceae OTU1
88%
C4-ER
7
163
JN943898.1
Amphinema 5
94%
C4-ER
7
166
JN943905.1
Amphinema 8
96%
C4-ER
7
164
FN669208.1
Hydnum 1
93%
C4-ER
7
168
JF908112.1
Inocybe 16
95%
C4-ER
7
169
AF377167.1
Rhizopogon arctostaphyli
94%
34
C6A
1
31
HQ604813.1
Inocybe jacobi
99%
C6A
1
33
HQ604813.1
Inocybe jacobi
99%
C6A
1
34
AY880944.1
Rhizopogon 8
88%
C6A
2
762
JN943898.1
Amphinema 7
92%
C6A
2
761
EU103612.1
Phialocephala 5
93%
C6A
3
770
JN943893.1
Cenococcum geophilum
95%
C6A
4
763
EU669372.1
Rhizopogon elipsoporus
97%
C6A
5
769
EU563921.1
Hysterangium 2
82%
C6A
5
767
GU067764.1
Phialocephal fortinii
83%
C6A
5
766
DQ365663.1
Piloderma 6
96%
C6A
5
765
DQ365674.1
Piloderma 9
95%
C6B
1
96
JN943898.1
Amphinema 5
97%
C6B
1
95
AY606311.1
Cadophora 2
96%
C6B
1
94
FN550919.1
Inocybe 3
96%
C6B
1
97
GQ249398.1
Suillus volcanalis
99%
C6B
4
98
JN943893.1
Cenococcum geophilum
81%
C6B
4
99
EU862208.1
Clavulina 1
90%
C6B
4
101
AF377167.1
Rhizopogon arctostaphyli
100%
C6B
5
104
JF834355.1
Russula albonigra
99%
C6B
6
93
JX561240.1
Sistotrema sp.
97%
C6B
6
91
FJ845443.1
Tricholoma 5
87%
C6B
7
90
EU526006.1
Russula cascadensis
99%
C7
1
291
JN943898.1
Amphinema 6
97%
C7
1
290
AF058303.1
Rhizopogon burlinghamii
73%
C7
1
289
EU669372.1
Rhizopogon ellipsoporus
96%
C7
1
M286
U83467.1
Tomentella spp.
88%
C7
4
264
FN669236.1
Piloderma 21
93%
C7
4
266
HM190011.1
Tomentellopsis 1
92%
C7
4
265
AF266708.1
Wilcoxina rehmii 1
97%
C7
5
255
DQ469291.1
Piloderma 13
82%
C7
5
257
EU837230.1
Rhizopogon bacillisporus
97%
C7
6
281
FJ039589.1
Cortinarius 4
92%
C7
6
279
AF377167.1
Rhizopogon arctostaphyli
98%
C7
6
280
JQ711917.1
Tomentella bryophila
92%
C7
6
276
HM590873.1
Tricholoma 1
85%
35
C7
7
253
EU427331.1
Cenococcum geophilum
95%
C7
7
M248
HQ604516.1
Inocybe 9
95%
C7
7
251
JF834352.1
Russula 3
87%
C8
1
18
HQ604726.1
Cortinarius fulvescens
84%
C8
1
15
DQ097870.1
Cortinarius hemitrichus
99%
C8
1
20
AF071440.1
Rhizopogon ochraceorubens
98%
C8
2
27
EU427331.1
Cenococcum geophilum
99%
C8
2
30
AF377094.1
Gautieria 1
91%
C8
2
29
GQ249393.1
Suillus quiescens
81%
C8
2
28
AF266708.1
Wilcoxina rehmii 1
99%
C8
3
21
DQ822822.1
Rhizopogon salebrosus
96%
C8
3
26
AF266708.1
Wilcoxina rehmii 1
99%
C8
5
55
EU427331.1
Cenococcum geophilum
99%
C8
5
49
HQ604726.1
Cortinarius fulvescens
93%
C8
5
52
EF685051.1
Lactarius delciosus
90%
C8
5
53
EF685051.1
Lactarius deliciosus
97%
C8
5
56
DQ469291.1
Piloderma 11
91%
C8
5
48
EU669372.1
Rhizopogon ellipsoporus
99%
C8
5
51
EU669372.1
Rhizopogon ellipsoporus
99%
C8
5
50
AF377157.1
Rhizopogon salebrosus
99%
C8
4
43
JN943910.1
Amphinema 9
97%
C8
4
44
JN943910.1
Amphinema 9
99%
C8
4
45
JN943910.1
Amphinema 9
99%
C8
4
35
EU427331.1
Cenococcum geophilum
95%
C8
4
38
AF377167.1
Rhizopogon arctostaphyli
100%
C8
4
36
L54107.1
Suillus pseudobrevipes
96%
C8
4
37
GQ249398.1
Suillus volcanalis
99%
C8
4
39
GQ249398.1
Suillus volcanalis
98%
C8
4
47
GQ249398.1
Suillus volcanalis
99%
DL
1
608
EU427331.1
Cenococcum geophilum
93%
DL
1
612
DQ093752.1
Cenococcum geophilum
93%
DL
1
613
GQ159814.1
Cortinarius 11
93%
DL
1
610
HQ604726.1
Cortinarius fulvescens
93%
DL
1
611
JF907866.1
Cortinarius vernus
98%
DL
1
606
AY880931.1
Rhizopogon 14
95%
DL
1
607
AJ534914.1
Tomentella 2
93%
36
DL
1
603
FJ845443.1
Tricholoma 7
86%
DL
2
597
JN943885.1
Cenococcum geophilum
97%
DL
2
601
HQ283095.1
Geopora 1
90%
DL
2
598
HQ604216.1
Inocybe glabrescens
99%
DL
2
602
AF377157.1
Rhizopogon salebrosus
98%
DL
2
599
AJ534914.1
Tomentella 1
91%
DL
2
600
FJ845443.1
Tricholoma myomyces
99%
DL
3
591
EU346870.1
Cenococcum geophilum
94%
DL
3
594
HQ604731.1
Cortinarius 6
96%
DL
3
595
AY309962.1
Hebeloma collariatum
97%
DL
3
593
JN022511.1
Hysterangium 3
76%
DL
3
596
FN550920.1
Inocybe contig 3
95%
DL
4
630
JN943885.1
Cenococcum geophilum
95%
DL
4
631
GQ159814.1
Cortinarius 11
93%
DL
4
M629
HQ604516.1
Inocybe 13
96%
DL
4
625
FN550919.1
Inocybe 3
94%
DL
4
627
EU669319.1
Rhizopogon 1
82%
DL
4
628
FJ845443.1
Tricholoma myomyces
99%
DL
7
617
JN943962.1
Cortinarius 2
87%
DL
7
616
HQ604731.1
Cortinarius fulvescens
97%
DL
7
621
HQ604731.1
Cortinarius fulvescens
97%
DL
7
624
FN550919.1
Inocybe 3
94%
DL
7
623
HQ604516.1
Inocybe 7
92%
DL
7
615
HQ604516.1
Inocybe flocculosa
97%
DL
7
618
HQ604516.1
Inocybe flocculosa
97%
DL
7
619
AJ534914.1
Tomentella 2
93%
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
1
758
JN943885.1
Cenococcum geophilum
94%
1
759
GQ159869.1
Cortinarius 8
78%
1
756
HM190137.1
Helotiales 3
80%
1
M750
HQ604516.1
Inocybe flocculosa
98%
1
753
EF685051.1
Lactarius 3
96%
1
752
AY078133.1
Phialocephala 1
85%
1
751
AY010280.1
Piloderma fallax
97%
1
757
AF062927.1
Rhizopogon 6
95%
1
754
HM189968.1
Tomentella 4
93%
37
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
FIN.
BUTTE
1
755
HM189968.1
Tomentella 4
95%
2
738
DQ365653.1
Piloderma 5
90%
2
739
HM240541.1
Russula 2
92%
2
740
HM240541.1
Russula 2
87%
2
741
AF377195.1
Tricholoma 8
79%
3
748
EU427331.1
Cenococcum geophilum
92%
3
743
FN669173.1
Clavulina 2
97%
3
749
FN669173.1
Clavulina 3
95%
3
745
HQ604719.1
Cortinarius casimiri
99%
3
744
DQ365674.1
Piloderma 8
87%
3
742
AF377167.1
Rhizopogon arctostaphyli
94%
3
746
AF377167.1
Rhizopogon arctostaphyli
96%
4
735
HM060322.1
Inocybe strobilomyces
100%
4
730
DQ469285.1
Piloderma 10
87%
4
732
AY010280.1
Piloderma fallax
98%
4
734
AJ810045.1
Rhizopogon 10
84%
7
736
HQ201354.1
Agaricales 4
90%
7
737
JN943893.1
Cenococcum geophilum
94%
FIRE
1
686
JN133916.1
Amphinema 3
82%
FIRE
1
685
EU821662.1
Cortinarius 5
90%
FIRE
1
684
HQ604600.1
Inocybe 15
89%
FIRE
2
693
JN133916.1
Amphinema 4
82%
FIRE
2
690
EU427331.1
Cenococcum geophilum
93%
FIRE
2
688
AY669679.1
Cortinarius 1
91%
FIRE
2
694
HQ604726.1
Cortinarius fulvescens
93%
FIRE
3
703
HQ604090.1
Agaricales 5
90%
FIRE
3
704
HQ604719.1
Cortinarius casimiri
96%
FIRE
3
702
FN550920.1
Inocybe tarda
94%
FIRE
4
705
DQ469291.1
Piloderma 15
76%
FIRE
4
708
HQ914256.1
Rhizopogon salebrosus
96%
FIRE
4
706
FJ876183.1
Tomentella 3
94%
FIRE
5
697
JF899555.1
Hebeloma sacchariolens
98%
FIRE
5
M696
HQ604516.1
Inocybe flocculosa
97%
38
FIRE
5
695
HQ914265.1
Rhizopogon salebrosus
94%
HWY31
2
M107
HQ604516.1
Inocybe 8
93%
HWY31
3
113
AF377157.1
Rhizopogon salebrosus
98%
HWY31
3
110
AB263122.1
Rhodotorula 1
88%
HWY31
3
112
JF834356.1
Russula 1
79%
HWY31
3
111
AF266708.1
Wilcoxina rehmii 1
99%
HWY31
4
114
JN943885.1
Cenococcum geophilum
95%
HWY31
4
115
FN669236.1
Piloderma 18
95%
HWY31
5
124
FN550920.1
Inocybe tarda
94%
HWY31
5
125
JF695015.1
Rhizopogon 17
96%
HWY31
7
122
FN669212.1
Inocybe 18
95%
HWY31
7
M119
FN669236.1
Piloderma 25
83%
HWY31
7
120
AF377157.1
Rhizopogon salebrosus
98%
HWY31
7
121
HM189969.1
Tomentella 5
92%
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
1
513
JN943925.1
Amphinema 10
93%
1
512
JN943885.1
Cenococcum geophilum
95%
1
511
JN580857.1
Inocybe silvae-herbaceae
97%
1
514
EF685051.1
Lactarius deliciosus
100%
2
522
JN943926.1
Amphinema 2
100%
2
516
JN943893.1
Cenococcum geophilum
93%
2
515
HQ604726.1
Cortinarius fulvescens
97%
2
521
HQ604242.1
Inocybe subcarpta
98%
2
520
DQ469291.1
Piloderma 14
89%
2
518
DQ365674.1
Piloderma 7
94%
2
517
AF071440.1
Rhizopogon ochraceorubens
98%
2
519
AF377157.1
Rhizopogon salebrosus
98%
3
504
JN943893.1
Cenococcum geophilum
92%
3
505
GQ267482.1
Rhizopogon luteorubescens
98%
3
508
AF062934.1
Rhizopogon vulgaris
97%
3
510
EF644117.1
Tomentella 8
96%
4
499
HQ604515.1
Agaricales 2
87%
4
M498
HQ604516.1
Agaricales 6
95%
4
M501
HQ604516.1
Inocybe 11
90%
39
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
ICE
CAVE
4
503
AJ534914.1
Tomentella 2
92%
6
528
EF685047.1
Lactarius barrowsii
98%
6
526
HM036610.1
Phialocephala 3
80%
6
523
L54107.1
Suillus pseudobrevipes
96%
6
527
L54107.1
Suillus pseudobrevipes
97%
KB
1
62
EU427331.1
Cenococcum geophilum
99%
KB
1
64
FN550920.1
Inocybe tarda
90%
KB
1
63
AF377167.1
Rhizopogon arctostaphyli
100%
KB
3
84
EF685051.1
Lactarius deliciosus
100%
KB
3
88
EF685051.1
Lactarius deliciosus
94%
KB
3
82
DQ469291.1
Piloderma 12
88%
KB
3
86
AF377167.1
Rhizopogon arctostaphyli
100%
KB
3
83
AF377157.1
Rhizopogon salebrosus
99%
KB
3
85
AF377157.1
Rhizopogon salebrosus
99%
KB
3
87
AF266708.1
Wilcoxina rehmii 1
99%
KB
4
77
EU427331.1
Cenococcum geophilum
99%
KB
4
81
HQ604719.1
Cortinarius casimiri
95%
KB
4
79
GU166481.1
Helotiales 2
93%
KB
4
78
FN550920.1
Inocybe contig 3
95%
KB
5
68
HM190137.1
Phialocephala fortini
98%
KB
7
69
HQ604726.1
Cortinarius fulvescens
92%
KB
7
71
HM176572.1
Hypocrea 1
85%
KB
7
66
AF377157.1
Rhizopogon salebrosus
99%
KB
7
74
FJ845443.1
Tricholoma myomyces
99%
KB
3
80
AB211277.1
Cenococcum geophilum
86%
LB
1
417
HQ604516.1
Inocybe flocculosa
97%
LB
1
423
AY010280.1
Piloderma fallax
98%
LB
1
422
AY880938.1
Suillus pseudobrevipes 1
98%
LB
2
424
HQ604806.1
Inocybe jacobi
98%
LB
2
425
HQ604806.1
Inocybe jacobi
96%
LB
2
427
FR827862.1
Sacosphaera
88%
LB
3
M436
HQ604516.1
Inocybe flocculosa
100%
LB
3
435
HQ914321.1
Rhizopogon salebrosus
97%
LB
4
440
AJ810038.1
Rhizopogon 3
95%
MOF.
BUTTE
2
303
AF377167.1
Rhizopogon arctostaphyli
96%
40
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
MOF.
BUTTE
2
312
AF377157.1
Rhizopogon salebrosus
99%
2
308
AJ534914.1
Tomentella 2
92%
2
306
AJ889982.1
Tomentella cf. sublilacina
90%
2
305
FJ845443.1
Tricholoma myomyces
99%
2
307
FJ845443.1
Tricholoma myomyces
99%
2
302
EF458013.1
Wilcoxina 2
96%
2
304
AF266708.1
Wilcoxina Rehmii 1
97%
3
M296
HQ604516.1
Inocybe flocculosa
98%
3
297
AJ534914.1
Tomentella 1
94%
3
299
AJ534914.1
Tomentella 2
94%
3
301
AM086447.1
Tomentellopsis 2
93%
3
300
FJ845443.1
Tricholoma myomyces
99%
5
318
FN550920.1
Inocybe contig 3
95%
5
320
FN550920.1
Inocybe contig 3
95%
5
317
EU819536.1
Tricholoma 10
86%
5
319
AF266708.1
Wilcoxina rehmii 1
98%
PB
1
373
HQ604726.1
Cortinarius fulvescens
94%
PB
1
371
AY010280.1
Piloderma 4
95%
PB
1
374
AF377167.1
Rhizopogon arctostaphyli
100%
PB
1
372
GQ267482.1
Rhizopogon luteorubescens
94%
PB
2
362
JN943885.1
Cenococcum geophilum
96%
PB
2
364
HQ604726.1
Cortinarius fulvescens
98%
PB
2
356
AF377167.1
Rhizopogon arctostaphyli
98%
PB
2
367
GQ267482.1
Rhizopogon luteorubescens
97%
PB
4
M333
HQ604516.1
Inocybe flocculosa
96%
PB
4
327
GQ406458.1
99%
PB
4
331
GQ406458.1
PB
4
329
GQ267482.1
Laccaria amethysteooccidentalis
Laccaria amethysteooccidentalis
Rhizopogon 2
PB
4
328
AF377167.1
Rhizopogon arctostaphyli
98%
PB
6
336
HQ604084.1
Inocybe 4
95%
PB
6
340
FJ845418.1
Lactarius deliciosus
98%
PB
6
342
AF071440.1
Rhizopogon ochraceorubens
98%
PB
6
338
AF377157.1
Rhizopogon salebrosus
98%
99%
75%
41
Table 3. Operational Taxonomic Units of Pinus contorta
Site
Tree
Sample #
Accession #
Analysis Name
Max Identity
BHB
PICO
575
EU427331.1
Cenococcum geophilum
99%
BHB
PICO
573
JF908249.1
Inocybe 20
94%
BHB
PICO
578
AY606285.1
Phialocephala 2
90%
BHB
PICO
576
DQ469291.1
Piloderma 2
90%
BHB
PICO
574
FJ845443.1
Tricholoma myomyces
99%
C1
PICO
182
HQ604719.1
Cortinarius casimiri
99%
C1
PICO
183
HQ604719.1
Cortinarius casimiri
99%
C1
PICO
181
HQ604242.1
Inocybe subcarpta
99%
C4-ER
PICO
159
JN943891.1
Cenococcum geophilum
96%
C4-ER
PICO
162
HQ604806.1
Inocybe jacobi
97%
C4-ER
PICO
158
AF274770.1
Pseudotomentella 1
96%
C4-ER
PICO
161
AJ810040.1
Rhizopogon 9
95%
C6A
PICO
5
EU427331.1
Cenococcum geophilum
99%
C6A
PICO
8
GU234029.1
Cortinarius inconspicuus
98%
C6A
PICO
6
AY880931.1
Rhizopogon salebrosus
97%
C6A
PICO
2
FJ845440.1
Suillus brevipes
99%
C6A
PICO
1
GQ249389.1
Suillus brevipes 2
90%
C6A
PICO
9
HM189964.1
Thelephora terrestris
99%
C6A
PICO
7
HM189966.1
Thelephora terrestris
97%
C7
PICO
275
JN943893.1
Cenococcum geophilum
89%
C7
PICO
267
FJ845440.1
Suillus brevipes
96%
C7
PICO
273
HM189966.1
Thelephora terrestris
97%
C7
PICO
269
HQ215807.1
Tomentella 6
96%
C7
PICO
270
HQ215807.1
Tomentella 6
96%
C7
PICO
271
HQ215807.1
Tomentella 6
93%
C8
PICO
M58
HQ604516.1
Inocybe 12
94%
C8
PICO
58
HQ604516.1
Inocybe 5
94%
C8
PICO
60
HQ604516.1
Inocybe flocculosa
97%
C8
PICO
59
AF071438.1
Rhizopogon 11
89%
C8
PICO
61
DQ517421.1
Tricholoma 3
90%
DAVIS
PICO1
416
HQ604516.1
Inocybe flocculosa
97%
DAVIS
PICO1
411
FN669236.1
Piloderma 22
94%
DAVIS
PICO1
415
HM189966.1
Thelephora terrestris
97%
42
DAVIS
PICO2
387
FJ039683.1
Cortinarius viridipes
97%
DAVIS
PICO2
382
DQ469291.1
Piloderma olivaceum
97%
DAVIS
PICO2
385
EF458015.1
Rhizopogon ochraceorubens
97%
DAVIS
PICO2
386
AF377157.1
Rhizopogon salebrosus
97%
DAVIS
PICO2
389
FJ845441.1
Suillus tomentosus 2
96%
DAVIS
PICO3
398
DQ365632.1
Hysterangium 1
87%
DAVIS
PICO3
392
JN580876.1
Inocybe17
90%
DAVIS
PICO3
390
FJ845430.1
Russula densifola
99%
DAVIS
PICO3
391
FJ845430.1
Russula densifola
99%
DAVIS
PICO4
380
GQ162811.1
Amphinema 1
96%
DAVIS
PICO4
376
FN550919.1
Inocybe 3
94%
DAVIS
PICO4
379
AM490946.1
Pseudotomentella humicola
100%
DAVIS
PICO4
381
AF062927.1
Rhizopogon 7
96%
DAVIS
PICO4
375
DQ822822.1
Rhizopogon salebrosus
97%
DAVIS
PICO4
377
EF458017.1
Suillus tomentosus 1
97%
DAVIS
PICO5
406
HQ604726.1
Cortinarius fulvescens
93%
DAVIS
PICO5
401
JF908076.1
Hygrophorus 1
95%
DAVIS
PICO5
399
AJ515411.1
Rhizopogon 18
90%
DAVIS
PICO5
402
M91613.1
Rhizopogon 21
92%
DAVIS
PICO5
404
AF377157.1
Rhizopogon salebrosus
93%
DAVIS
PICO5
409
DQ822822.1
Rhizopogon salebrosus
99%
PICO
715
EU557316.1
Cadophora 1
94%
PICO
716
JN943885.1
Cenococcum geophilum
94%
PICO
729
GQ159818.1
Cortinarius 10
84%
PICO
718
HQ650744.1
Cortinarius 12
95%
PICO
723
AF389170.1
Cortinarius 7
96%
PICO
728
HQ604213.1
Inocybe auricoma
94%
PICO
714
DQ469291.1
Piloderma 16
77%
PICO
722
FN669236.1
Piloderma 17
84%
PICO
724
AY010280.1
Piloderma fallax
98%
PICO
727
AY880945.1
Rhizopogon 5
81%
PICO
717
EF458011.1
Rhizopogon salebrosus
97%
PICO
725
DQ822822.1
Rhizopogon salebrosus
97%
Fin.
Butte
Fin.
Butte
Fin.
Butte
Fin.
Butte
Fin.
Butte
Fin.
Butte
Fin.
Butte
Fin.
Butte
Fin.
Butte
Fin.
Butte
Fin.
Butte
Fin.
Butte
43
Fin.
Butte
Fin.
Butte
PICO
720
AY880931.1
Rhizopogon salebrosus
95%
PICO
712
JQ711917.1
Tomentella bryophila
99%
Fire
PICO
682
GU166481.1
Helotiales 1
92%
Fire
PICO
672
JN655616.1
Helotiales 4
87%
Fire
PICO
670
HQ604235.1
Inocybe 21
91%
Fire
PICO
673
AF377167.1
Rhizopogon arctostaphyli
96%
Fire
PICO
680
EU837230.1
Rhizopogon bacillisporus
94%
Fire
PICO
675
U83487.1
Thelephora 1
96%
Fire
PICO
674
AJ889980.1
Thelephora 2
94%
Fire
PICO
677
AF274770.1
Thelephoraceae 1
86%
Fire
PICO
678
AF274770.1
Thelephoraceae 2
83%
HD
PICO1
476
FJ845418.1
Lactarius deliciosus
97%
HD
PICO2
M495
HQ604516.1
Inocybe flocculosa
97%
HD
PICO2
496
AF377177.1
Rhizopogon 16
91%
HD
PICO2
493
GQ267482.1
Rhizopogon luteorubescens
93%
HD
PICO2
494
AJ534914.1
Tomentella 2
93%
HD
PICO2
492
EF458013.1
Wilcoxina 3
88%
HD
PICO2
490
AF266708.1
Wilcoxina rehmii 1
97%
HD
PICO3
459
GQ401354.1
Amanita 1
89%
HD
PICO3
464
FN550920.1
Inocybe contig 3
95%
HD
PICO3
461
DQ822823.1
Rhizopogon vulgaris
96%
HD
PICO3
467
AJ534914.1
Tomentella 2
94%
HD
PICO4
473
FJ717527.1
Cortinarius 3
86%
HD
PICO4
471
HQ604516.1
Inocybe flocculosa
97%
HD
PICO4
470
FN669236.1
Piloderma23
90%
HD
PICO5
479
FN550920.1
Inocybe 22
88%
HD
PICO5
481
FN550920.1
Inocybe 23
94%
HD
PICO5
478
AY606285.1
Phialocephala 4
81%
HD
PICO5
480
EU669372.1
Rhizopogon ellipsoporus
94%
HWY31
PICO
129
HQ604813.1
Inocybe jacobi
99%
ICE
PICO
530
JF908175.1
Agaricomycete 1
79%
ICE
PICO
537
JN943893.1
Cenococcum geophilum
83%
ICE
PICO
531
HQ604809.1
Inocybe jacobi
99%
ICE
PICO
533
DQ469291.1
Piloderma 3
91%
44
ICE
PICO
536
HQ914321.1
Rhizopogon salebrosus 2
97%
ICE
PICO
535
AF158017.1
Rhizopogon smithii
99%
ICE
PICO
529
AJ534914.1
Tomentella 1
92%
ICE
PICO
539
AF266708.1
Wilcoxina rehmii 1
98%
KB
PICO
70
EU427331.1
Cenococcum geophilum
99%
KB
PICO
482
JN943894.1
Cenococcum geophilum
90%
KB
PICO
485
AF377173.1
Rhizopogon 13
79%
KB
PICO
486
AF377134.1
Rhizopogon 4
72%
KB
PICO
75
FR838002.1
Sistorema
90%
KB
PICO
M487
FJ845443.1
Tricholoma myomyces
97%
KB
PICO
72
AF266708.1
Wilcoxina Rehmii 1
99%
LB
PICO
M457
HQ604516.1
Inocybe 10
93%
LB
PICO
456
AY880941.1
Suillus brevipes
99%
PICO1
654
JF899547.1
Amanita 2
81%
PICO1
653
JN943893.1
Cenococcum geophilum
94%
PICO1
656
AJ534914.1
Tomentella 2
90%
PICO1
655
AF377209.1
Tricholoma 9
92%
PICO1
657
EF458013.1
Wilcoxina 4
92%
PICO3
649
HQ604516.1
Agaricales 3
85%
PICO3
650
HQ604516.1
Inocybe flocculosa
95%
PICO3
648
HM485339.1
Tuber2
89%
PICO4
634
HQ604213.1
Inocybe auricoma
91%
PICO4
640
HQ604213.1
Inocybe auricoma
95%
PICO4
M637
HQ604516.1
Inocybe flocculosa
98%
PICO4
636
DQ822823.1
Rhizopogon 22
86%
PICO4
635
HM485339.1
Tuber1
88%
PICO5
643
EF685058.1
Lactarius 1
77%
Mof.
Butte
Mof.
Butte
Mof.
Butte
Mof.
Butte
Mof.
Butte
Mof.
Butte
Mof.
Butte
Mof.
Butte
Mof.
Butte
Mof.
Butte
Mof.
Butte
Mof.
Butte
Mof.
Butte
Mof.
Butte
Figure 1. Map showing general area of study site in Central Oregon and distribution of sampling sites in the Deschutes
National Forest
45
Figure 2. Percent occurrence of dominant ectomycorrhizal fungus operational taxonomic units in Pinus ponderosa by soil core
(black) and site (grey). Ectomycorrhizal fungus analysis names are represented along the x-axis.
90%
Dominant OTUs in Pinus ponderosa
% Occurence
80%
70%
60%
50%
core
site
40%
30%
20%
10%
0%
46
Figure 3. Percent occurrence of dominant ectomycorrhizal fungus operational taxonomic units in Pinus contorta by soil core
(black) and site (grey). Ectomycorrhizal fungus analysis names are represented along the x-axis.
(!"#
Dominant OTUs in Pinus contorta
'$"#
% Occurrence
'!"#
core
site
&$"#
&!"#
%$"#
%!"#
$"#
!"#
47
Figure 4. NMS ordination of Pinus ponderosa and Pinus contorta soil cores in EMF species space.
48
Figure 5. NMS ordination of ponderosa pine sites in EMF species space with superimposed joint plot. Vectors show direction
and magnitude of correlation between sample units and environmental variables. Axis 1 explained 17% of the variation and
Axis 2 explained 25% of the variation. Proportion of variance represented by each axis is based on the r 2 between distance in
the ordination space and distance in the original space. Environmental variables with an r2 greater than 0.150 are plotted.
49
Table 4. Codes for environmental variables and respective correlations with ordination axes. Figure 5 displays these variables
in conjunction with EMF communities ordination of ponderosa pine graph.
50
Table 5. Soil Chemistry for Ponderosa Pine
Site
pH
Bray-P
NO3-N
NH4-N
Mineralizable N
C
TKN
TKP
4380
6.8
37
0.2
0.2
10.7
1.55
509.2
749.2
BHB
6.6
42
0.5
0.4
18.1
1.47
470.3
585.2
C1
6.7
32
0.6
0.6
13.5
1.94
508.9
664.9
C4ER
6.5
37
0.3
0.4
9.7
1.92
530.9
561.5
C6A
6.4
33
0.2
0.2
11.9
2.71
680.0
525.0
C6B
6.6
34
0.3
0.3
10.5
1.91
464.6
548.2
C7
6.4
63
0.3
0.5
18.2
2.68
615.4
888.1
C8
6.7
55
0.2
0.3
21.7
1.75
546.5
705.0
DEAD LOG
6.6
33
0.9
0.4
24.1
1.03
563.5
423.4
FIN. BUTTE
6.3
60
0.5
0.5
14.7
2.43
748.1
739.5
FIRE BUTTE
6.7
37
0.6
0.3
23.8
1.21
536.0
468.9
HWY 31
6.8
80
0.6
0.3
22.8
2.18
644.3
569.5
ICE CAVE
6.6
54
0.2
0.6
22.2
1.58
467.7
550.0
KB
6.3
65
9.0
1.4
33.1
2.54
914.6
473.3
LB
6.9
31
0.4
0.3
9.1
1.64
571.7
579.1
MOFF. BUTTE
6.6
71
0.9
0.8
27.1
2.49
821.3
534.8
PB
6.8
49
0.4
0.2
12.5
1.48
413.5
671.2
Average
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51
Figure 6. Linear relationship between mineralizable N and species richness.
52