AN ABSTRACT OF THE THESIS OF
Lucas J. Longway for the degree of Master of Science in Forest Ecosystems and Society
presented on November 13, 2015
Title: Comparing Ectomycorrhizal Communities of Understory Giant Chinquapin
(Chrysolepis chrysophylla) and Overstory Pinaceae Trees in a Mixed Conifer Forest
in Central Oregon
Abstract approved:
_________________________________________________________________________
Jane E. Smith
Giant chinquapin (Chrysolepis chrysophylla) is an evergreen hardwood often found as a
shrubby understory component of coniferous forests in the Pacific Northwest United
States. Due to its ability to sprout quickly after disturbances such as fire and logging it is
often viewed as a pest by forest managers. Like its associated overstory conifers, giant
chinquapin forms ectomycorrhizae. However, the ectomycorrhizal fungus communities
associated with giant chinquapin found in the Pacific Northwest have not been
investigated. To further explore giant chinquapin’s ecological roles in central Oregon’s
forests we compare ectomycorrhizal communities associated with giant chinquapin and cooccurring overstory Pinaceae trees in the Pringle Falls Experimental Forest, central
Oregon. Ectomycorrhizal communities of Pinaceae trees had a greater taxa richness than
those found associated with giant chinquapin. However, 57% (8 of 14) of the taxa found in
31% (5/16) of study areas on Pinaceae trees were found associated with giant chinquapin.
Four taxa (Cenococcum geophilum 1 & 2, Piloderma 2, Byssoccorticium 1), likely
important for host water and nutrient access, were found in 31% of study areas associated
with both chinquapin and Pinaceae hosts. Sixty-four percent (23 of 36) of the
ectomycorrhizal taxa found on giant chinquapin associated with Pinaceae trees and every
genus associated with giant chinquapin in our study has been reported to form
ectomycorrhizae with Pinaceae trees in this or other studies. Based on these results, it is
likely that giant chinquapin is supporting a subset of the ectomycorrhizal community
associated with Pinaceae hosts. Giant chinquapin, with its ability to quickly sprout after
disturbance, could be beneficial to local conifer seedlings as a source of ectomycorrhizal
innoculum should overstory conifers decrease as a a result of a stand replacing disturbance.
©Copyright by Lucas J. Longway
November 13, 2015
All Rights Reserved
Comparing Ectomycorrhizal Communities of Understory Giant Chinquapin (Chrysolepis
chrysophylla) and Overstory Pinaceae Trees in a Mixed Conifer Forest in Central Oregon
by
Lucas J. Longway
A THESIS
submitted to Oregon State University
in partial fulfillment of
the requirements for the degree of
Master of Science
Presented November 13, 2015
Commencement June 2016
Master of Science thesis of Lucas J. Longway presented on
November 13, 2015
APPROVED:
_________________________________________________________________________
Major Professor, representing Forest Ecosystems and Society
_________________________________________________________________________
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.
_________________________________________________________________________
Lucas J. Longway, Author
ACKNOWLEDGEMENTS
I would like to express my sincere appreciation to my major professor, Jane E. Smith for
guiding me through the ups and downs of executing a scientific study and obtaining a
master’s degree. My heartfelt thanks also goes to my committee members, Paul Anderson
Jeff Hatten, and Daniel Luoma, who have offered invaluable support throughout this
process. I would also like to thank everyone who helped with data collection and sample
processing, Donaraye McKay, Elizabeth Bowman, Joseph Cagle. I would also like to
express my gratitude to my lab mates Ariel Cowan, Maria Osuna Garcia and Benjamin
Hart, my partners in PCR, Richard Cronn, Joyce Eberhart, Tara Jennings, Thomas Mullins
and my map expert Lucy Romeo, for helping, listening and offering feedback every step of
the way. For teaching me things I really needed to know, I would like to thank Lisa Ganio,
Bruce McCune, Shawn O’Neil, and Matthew Powers. For thesis formatting help I would
like to thank Jerry Mohr. For meeting with me every week for precisely 3.2 bajillon weeks
and talking about numbers, I would like to thank Ariel Muldoon.
Finally, I would like to thank my friends and my family for supporting me though this
process. My wife, Kelly Longway, deserves a medal of honor and perhaps a Master's in
‘keeping Lucas alive’ and for her I am eternally grateful. Last, but most certainly not least,
I would like to thank Sam and Napoleon.
TABLE OF CONTENTS
Page
STUDY OVERVIEW AND RELATED TOPICS ................................................................1
USDA Forest Service Pringle Falls Experimental Forest ..............................................................1
History & Research ....................................................................................................................1
PFEF Geologic History ..............................................................................................................1
Soil .............................................................................................................................................2
Climate & Vegetation ................................................................................................................2
Fire .................................................................................................................................................3
Fire Adapted Environments in the Pacific Northwest................................................................3
Fire & Climate Change ..............................................................................................................4
Ecosystem Changes with Fire & Ectomycorrhizal Refuge Plants .............................................5
Overarching Study .....................................................................................................................6
Mycorrhiza .....................................................................................................................................7
History........................................................................................................................................7
Mycorrhizal Classification .........................................................................................................8
Ecological Roles ......................................................................................................................10
EMF, Nitrogen & Phosphorus..................................................................................................10
Growth, Reproduction, Molecular Advances...........................................................................14
Common Mycorrhizal Networks..............................................................................................15
Generalists & Specialists..........................................................................................................16
Chinquapin ...................................................................................................................................16
Biology & Ecology ..................................................................................................................16
Economic Significance.............................................................................................................17
Cultural Significance................................................................................................................17
Ecosystem Services..................................................................................................................18
Chinquapin & Fire ..................................................................................................................18
Competition..............................................................................................................................19
Chinquapin Ectomycorrhiza.....................................................................................................20
Pinaceae........................................................................................................................................21
Pacific Northwest Genera and Species ....................................................................................21
Economic Significance.............................................................................................................21
Pinaceae Range & Biology ......................................................................................................22
Summary ......................................................................................................................................26
STUDY MANUSCRIPT......................................................................................................32
Introduction ..................................................................................................................................32
Materials & Methods....................................................................................................................35
Study Area................................................................................................................................35
Climate .....................................................................................................................................35
Vegetation ................................................................................................................................35
Soils..........................................................................................................................................36
Study Design ............................................................................................................................36
Vegetation & Soil Moisture .....................................................................................................37
Soil Sampling & Nutrients .......................................................................................................38
Ectomycorrhiza Root Collection & Host Identification...........................................................38
Statistical Analyses ..................................................................................................................41
Results ..........................................................................................................................................42
Vegetation Community ............................................................................................................42
EMF Communities ...................................................................................................................43
EMF Community Comparisons ...............................................................................................43
EMF Communities & Environmental Variables......................................................................44
Discussion ....................................................................................................................................45
EMF Community & Soil Nutrients ..........................................................................................46
EMF Community Comparisons ...............................................................................................47
EMF & Fire..............................................................................................................................49
Limitations & Future Directions ..............................................................................................50
Conclusions & Implications.....................................................................................................51
BIBLIOGRAPHY................................................................................................................67
LIST OF FIGURES
Figure
Page
1. Study area overview and design....................................................................... 52
2. Lookout Mountain study area .......................................................................... 53
3. Box and whisker plot of basal area (m2/ha) of overstory Pinaceae trees. ........ 54
4. Basal area (m2/ha) of overstory Pinaceae trees per plot by elevation (m). ...... 55
5. Pinaceae basal area (m2/ha) per plot ................................................................ 56
6. Taxa found on both Pinaceae hosts and giant chinquapin by frequency of occurrence on transect pairs. ............................................................................ 60
7. Species rarefaction curves and 95% confidence intervals ............................... 61
8. Number of ascomycetes and basidiomycetes on transect pairs ....................... 62
9. Dominant EMF taxa or EMF taxa.................................................................... 63
10. Frequencey of all EMF taxa found by transect pair......................................... 64
11. NMDS showing EMF taxa in transect space. .................................................. 66
LIST OF TABLES
Table
Page
1. Comparisons of EMF genera found associated with Pinaceae and chinquapin to genera found on hosts phylogenetically related to chinquapin. 27
2. Environmental variable measurements ............................................................ 57
3. Spearman ranked correlation coefficient (ρ) of pH correlated with
chinquapin percent cover ................................................................................. 57
4. Spearman ranked correlation coefficients (ρ) of environmental variables
correlated to Pinaceae basal area (m2/ha)......................................................... 57
5. Spearman ranked correlation coefficients (ρ) for environmental variables
correlated with each other ................................................................................ 58
6. Root tip success summary. ............................................................................... 58
7. Count and percent of unique and shared fungal taxa found by host. ............... 58
8. Count and percent of unique and shared fungal taxa. ...................................... 58
9. Count and percent of total fungal taxa found by host. ..................................... 59
10. Spearman ranked correlation coefficients (ρ) for Pinaceae EMF descriptors
that were correlated with environmental variables .......................................... 65
11. Spearman ranked correlation coefficients (ρ) for Chinquapin EMF
descriptors that were correlated with environmental variables........................ 65
LIST OF APPENDICES
Page
APPENDICES ....................................................................................................................88
Appendix A ................................................................................................................................. 89
Appendix B ...............................................................................................................................103
Selected Scatterplots Involving Environmental Variables ....................................................103
Selected Scatterplots Involving EMF Variables and Root tip Counts ..................................112
Selected Scatterplots Involving Overstory Pinaceae Basal Area ..........................................121
LIST OF APPENDIX FIGURES
Figure
Page
1. Scatter plot of chinquapin % cover vs. pH per transect pair. ......................... 103
2. Scatter plot of bray phosphorus (mg/kg) vs. pH per transect pair. ................ 104
3. Scatter plot of bray phosphorus (mg/kg) vs. elevation (m) per transect pair . 105
4. Scatter plot of total elevation (m) vs. phosphorus (mg/kg) per transect pair . 106
5. Scatter plot of total nitrogen (%) vs. mineralizable nitrogen (mg/kg) per transect pair .................................................................................................... 107
6. Scatter plot of average volumetric soil moisture (m3/m3) vs. mineralizable nitrogen (mg/kg)............................................................................................. 108
7. Scatter plot of total phosphorus (mg/kg) vs. Bray phosphorus (mg/kg) per transect pair .................................................................................................... 109
8. Scatter plot of total carbon (%) vs. mineralizable nitrogen (mg/kg) per transect pair. ................................................................................................... 110
9. Scatter plot of total nitrogen (%) vs. total carbon (%) per transect pair. ....... 111
10. Scatter plot of Pinaceae root tips vs. Pinaceae EMF Shannon’s Diversity per transect pair. ................................................................................................... 112
11. Scatter plot of Pinaceae root tips vs. chinquapin root tips per transect pair. . 113
12. Scatter plot of Pinaceae root tips vs. Pinaceae EMF richness per transect pair.................................................................................................................. 114
13. Scatter plot of Pinaceae root tips vs. chinquapin EMF Shannon’s Diversity
per transect pair. ............................................................................................. 115
14. Scatter plot of Pinaceae root tips vs. chinquapin EMF Richness per transect pair.................................................................................................................. 116
15. Scatter plot of chinquapin root tips vs. chinquapin EMF richness per
transect pair. ................................................................................................... 117
16. Scatter plot of chinquapin root tips vs. Pinaceae EMF richness per transect pair.................................................................................................................. 118
17. Scatter plot of chinquapin root tips vs. chinquapin EMF Shannon’s diversity
per transect pair. ............................................................................................. 119
18. Scatter plot of chinquapin root tips vs. Pinaceae EMF Shannon’s diversity
per transect pair. ............................................................................................. 120
19. Scatter plot of elevation (m) vs. grand fir basal area (m2/ha) per transect pair.................................................................................................................. 121
20. Scatter plot of Bray phosphorus (mg/kg) vs. lodgepole pine basal area
(m2/ha) per transect pair. ................................................................................ 122
21. Scatter plot of Pinaceae EMF Shannon’s diversity vs. lodgepole pine basal
area (m2/ha) per transect pair. ........................................................................ 123
22. Scatter plot of Pinaceae EMF richness vs. lodgepole pine basal area (m2/ha)
per transect pair .............................................................................................. 124
LIST OF APPENDIX TABLES
Table
Page
1. EMF taxa found on Lookout Mountain. .......................................................... 89
2. Full Spearman ranked correlation (ρ) tables of environmental variables correlated with each other ................................................................................ 98
3. Spearman ranked correlation coefficients (ρ) for comparing environmental variables to chinquapin EMF variables.......................................................... 100
4. Spearman ranked correlation coefficients (ρ) for comparing environmental variables to Pinaceae EMF variables ............................................................. 101
5. Spearman ranked correlation coefficients (ρ) for most frequently occurring
Pinaceae overstory species compared to environmental and EMF variables (n = 12)........................................................................................................... 102
1
STUDY OVERVIEW AND RELATED TOPICS
USDA Forest Service Pringle Falls Experimental Forest
History & Research
Thornton T. Munger founded the Pringle Falls Experimental Forest (PFEF), the
first experimental forest in the Pacific Northwest, in 1931 (Camp and Youngblood 2006).
It was comprised of the Pringle Butte unit (3,043 ha) and was established to provide a large
scale study area in which to investigate the best silvicultural practices for spacing,
thinning, and fertilization of ponderosa pine in order to achieve the greatest growth and
yield (Camp and Youngblood 2006). In 1936 the Lookout Mountain unit (1,413 ha) was
added to the forest (Adams et al. 2004, Youngblood 2009). From inception through 1993,
119 scientific publications have come out of the PFEF area (Youngblood 1995), including
studies focusing on competition effects to ponderosa pine from shrubs and studies
investigating the negative effects of insect pathogens to forest health (Camp and
Youngblood 2006). Current studies taking place at Pringle Falls tend to focus on
investigating long-term processes that influence forest structure and composition (Adams
et al. 2004).
PFEF Geologic History
The Pringle Falls Experimental Forest, located within the Deschutes National
Forest, is part of the Sierra Nevada – Cascade Mountain physiographic province;
specifically the Middle Cascades section (Simpson 2007). The province is volcanically
influenced, containing several large volcanoes and many smaller cinder cones (Simpson
2007). Lookout Mountain, a 300,000-year-old shield volcano (Adams et al. 2004), has
bedrock of mixed basalts, andesites, and rhyolites, underlying approximately 50-125 cm of
andisolic soils layers (Larsen 1976).
2
Soil
The upper layers of soil on the mountain are comprised mainly of ash and tephra
from the Mt. Mazama eruption 6,600 years ago. (Camp and Youngblood 2006). The ash
layer is approximately 0.5 to 2 m (2 to 3 ft) thick on the study site (Adams et al. 2004;
Simpson 2007). According to a report on the first official soil survey at Pringle Falls
(Tarrant 1947), the soils are classified under the Lapine soil series, which is an Ashy­
pumiceous, glassy Xeric Vitricryand, meaning that the soils are composed of volcanic ash
and pumice, while also being glassy, excessively well drained, dry, cold and andisolic in
nature (Soil Survey Staff 2014). These soils tend to be limited in plant available
phosphorus and nitrogen and relatively low in organic matter content as well (Adams et al.
2004; Soil Survey Staff 2014). Additionally, the permanent plant wilting point of these
soils is at 15 to 16% soil moisture (NCSS 2015). Despite these harsh soil conditions the
majority of the area is classified as highly productive forestland by the USDA Forest
Service (Larsen 1976).
Climate & Vegetation
The Lookout Mountain unit experiences an average of 1020 mm of precipitation a
year, which is greater than the immediately surrounding areas such as Pringle Butte, which
receives only 610mm (24 in) on average annually (Adams et al. 2004). Most of this
precipitation falls as snow (Adams et al. 2004). Precipitation is seasonal in this area and
the soils tend to be moister during the spring snowmelt than during the dry and warm
summer months. On average summer high temperatures range from 21° to 35° C (Adams
et al. 2004).
Forest composition present on Lookout Mountain varies with elevation and aspect;
ponderosa pine dominant stands occupy the lower elevations, gradually shifting to mixed
conifer stands higher on the mountain (Adams et al. 2004). In 2011 the mixed conifer
stands on Lookout Mountain were found to contain, grand fir (Abies grandis (Dougl. ex D.
Don) Lindl.), subalpine fir (Abies lasiocarpa (Hook.) Nuttall), California red fir (Abies
3
magnifica A. Muray), lodgepole pine (Pinus contorta Dougl. ex Loudon), sugar pine
(Pinus lambertiana Dougl.), western white pine (Pinus monticola Douglas ex D. Don),
ponderosa pine (Pinus ponderosa Dougl. ex Laws.), Douglas-fir (Pseudotsuga menziesii
(Mirb.) Franco), and mountain hemlock (Tsuga mertensiana (Bong.) Carr.).
Understory shrubs and shrubby trees found on Lookout Mountain were: antelope
bitterbrush (Purshia tridentata (Pursh.) DC.), wax currant (Ribes cereum Dougl.), bitter
cherry (Prunus emarginata (Dougl. ex Hook) D. Dietr.), pinemat manzanita
(Arctostaphylos nevadensis A. Gray), greenleaf manzanita (Arctostaphylos patula Greene),
snowbrush ceanothus (Ceanothus velutinus Dougl. ex Hook.), and giant chinquapin
(Chrysolepis chrysophylla (Dougl. ex Hook.) Hjelmq.) (henceforth referred to as
‘chinquapin’).
The forests on the mountain within the study site fall into three classifications:
Pinus ponderosa/Purshia tridentata-Ceanothus velutinus (CPS-312) at the lowest
elevations does not support chinquapin; Mixed conifer/Ceanothus velutinus-Arctostaphylos
patula (CWS-112) at mid-elevation does support chinquapin; and Mixed
Conifer/Ceanothus velutinus-Carex stoliferus (CWS-115) at the highest elevation in the
study site also supports chinquapin (Volland 1985; Youngblood 2009).
Fire
Fire Adapted Environments in the Pacific Northwest
Fire is a common ecological disturbance in the Pacific Northwest (Agee 1993).
Many of the drier ecosystems in the Pacific Northwest are fire adapted, meaning the
vegetation communities have ways to survive fires or recolonize quickly after fire (Agee
1993). Fire in an ecosystem is typically described via particular fire regimes, which are
complex interactions among fire frequency, size, intensity, severity, type, and seasonality
(Flannigan et al. 2000); fire frequency is the average time between fires, size is the area
burned, intensity is the amount of energy released from fuels, severity is the amount and
type of fuel consumed, type is where the fire is located in the forest (crown, surface,
4
ground), and seasonality is when in the year the fire takes place (Flannigan et al. 2000). All
of these factors are linked and influenced by weather and topography (Flannigan et al.
2000).
Specific ecosystems tend to develop with specific fire regimes (Agee 1993). For
instance, the ponderosa pine dominated forests and the mixed conifer stands found on the
Lookout Mountain unit were historically relatively well adapted to fire with a return
interval of 7 to 20 years (Adams et al. 2004). In areas like Pringle Falls, frequent burns
were usually low-intensity and served to maintain a low fuel level by thinning understory
trees and seedlings. However, fire regimes changed drastically in 1910 after large forest
fires in the Northwestern United States caused policy makers in Washington to change the
primary goal of the nascent U.S. Forest Service to fire suppression in order to preserve
forest resources and timber for industry and human use (Fitzgerald 2005; Silcox 1911;
Southard 2011). In fact, the last stand replacing fire to burn through the Lookout Mountain
area of Pringle Falls was in 1845, however part of the mountain burned in 1914 as well
(Youngblood 2009, Final 2010). These fires gave rise to the 166 and 97-year-old stands
that were present on the mountain until 2011 (Youngblood 2009, Final 2010). No standreplacing or large fires have burned through the area since 1914 and without the routine
maintenance of fire, the forest on Lookout Mountain, like many of the forests in the
western United States, has become dense, brushy, and a risk for large burns (Fitzgerald
2005; Youngblood 2009, Final 2010).
Fire & Climate Change
In addition to the problem of dense forests, global climate change also impacts fire
regimes (Running 2006; Krawchuck et al. 2009; Adams 2013). In the Pacific Northwest,
summers have been warming, winter precipitation has been decreasing, and spring
snowmelt has been happening earlier in the year (Running 2006; Westerling et al. 2006).
Fire seasons from 1987 to 2003 have become longer than those in 1970 to 1986 by an
average of 78 days (Westerling et al. 2006). Increase in fire season length from the mid
5
1980s to 2003, due to longer and warmer summers, has increased the land area burned in
the United States by more than six times the average from 1970 to 1986 (Westerling et al.
2006). Correspondingly, there has been increasing frequency of large, highly destructive
fires in the western United States and in other areas worldwide (Westerling et al. 2006;
Running 2006; Adams 2013). Future climate models have predicted increased summer
warming with increased winter precipitation for the Pacific Northwest United States (Mote
& Salathé 2010). Despite increasing winter precipitation, the increase in summer warming
combined with earlier spring snowmelt will likely exacerbate current fire risks, leading to
greater frequency of fire (Westerling et al. 2006).
Ecosystem Changes with Fire & Ectomycorrhizal Refuge Plants
Small, frequently occurring, low intensity fires are necessary for optimal ecosystem
function for ponderosa pine dominated forests of the Pacific Northwest (Fitzgerald 2005).
However, fuel loading from extreme fire suppression has led to conditions where fires have
the capacity to become large and severe (Fitzgerald 2005). These large fires can remove or
kill the majority of above-ground vegetation and significantly change vegetation structure
and soil properties (Adams et al. 2013). However, even less severe fires can cause large
ecosystem changes, such as leaving trees weakened and susceptible to beetle attack
(McHugh et al. 2003; Fitzgerald 2005) and fungal attack (Gara et al. 1985; Parker et al.
2006).
In the case of stand replacing fires, years may elapse before the historically
dominant forest species can re-establish dominance in a stand (Savage and Mast 2005).
Part of ensuring that overstory dominant species can recolonize a burned site is
maintaining appropriate underground fungal partners, or mycorrhiza, for them. Most tree
and plant species are dependant on mycorrhizal fungi for growth (Smith and Read 2008).
All trees in the Pinaceae form a particular type of mycorrhizal partnership called
ectomycorrhiza (ECM) (Brundrett 2009). When much of the vegetation in a forest is
removed, such as in a large burn, the initial diversity of local ectomycorrhizal fungal
6
populations may decrease (Visser 1995; Bruns et al. 2002b). There are, however, several
ways in which ectomycorrhizal fungi (EMF) may quickly re-enter a system. Some EMF
have moderately heat resistant spores which can survive some fires and quickly recolonize
roots of germinating seedlings (Baar et al. 1999; Peay et al. 2009). Vegetative mycelium
and spores from nearby undisturbed areas can act as innoculum (Horton et al. 1998;
Hagerman et al. 1999; Krannabetter et al. 1999; Nara and Hogetsu 2004; Dickie and Reich
2005; Hewitt et al. 2013). Additionally, certain fire adapted plant species may be able to
act as a refuge for EMF species (Molina et al. 1992; Hewitt et al. 2013). This ability is due
to their root systems and underground burls remaining relatively intact after fire, allowing
them to resprout (Kauffman and Martin 1990). Chinquapin, a shrubby evergreen member
of the beech family (Fagaceae) that grows beneath Pinacaeae trees on much of Lookout
Mountain, may serve as an EMF refuge after fires in central Oregon.
Overarching Study
The dense state – increasing the likelihood of mountain pine beetle (Dendroctonus
ponderosae Hopkins) attack or stand replacing fire, of this outdoor laboratory combined
with its rich history of scientific study, inspired the U.S. Forest Service to begin a large
study testing fuel reduction methods to restore the forest to an open state (Youngblood
2009). This ongoing study began in 2011 on the Lookout Mountain unit of the PFEF. This
study split the Lookout Mountain unit into four blocks, which were then each subdivided
into five treatment units (Youngblood 2009). The five treatments consisted of a control
treatment and four thinning treatments combined with understory mastication and
prescribed burning. Prior to these treatments a nine-hectare (ha) sampling unit, comprised
of twenty-five points arranged on a 50 × 50 m grid, was established on each treatment unit
for gathering pre-treatment data (Youngblood 2009). At each point, a central circular plot
(.04 ha) was delineated for vegetation surveys, and two parallel transects (17 m long and
22.5 m apart), one on either side of the circular vegetation plot, were established in a
randomly selected cardinal direction for the placement of soil moisture tubes (Youngblood
7
2009). Treatments were applied between 2011 and 2015. Post treatment data on the
sampling units is ongoing.
The large fuel reduction study incorporates many simultaneously occurring smaller
studies. One of these studies was conducted to observe the response of the understory
shrub, chinquapin, to forest thinning and fuel reduction techniques (Youngblood 2009,
Anderson and Smith 2011). Chinquapin, with its propensity to sprout and spread after
disturbance, competes with overstory conifers for nutrients and water (Barrett et al. 1983;
McKee 1990; Kauffman and Martin 1990; Donato et al. 2009; Meyer 2012). Additionally,
chinquapin can contribute to fuel loads and is considered moderately flammable
(Weatherspoon and Skinner 1987). Chinquapin is an ectomycorrhizal-forming shrub, but
little is known with regards to its mycorrhizal symbionts. A key aspect of this study was to
investigate the differences in EMF community composition and/or diversity between the
overstory Pinaceae and the understory chinquapin hosts to see if, after fires or other
disturbance, chinquapin could serve as an EMF refuge plant for future germinating
Pinaceae trees. This study also explored the response of EMF communities to
environmental variables with the hypothesis that EMF communities would be influenced
by soil nutrients, specifically nitrogen and phosphorus, regardless of host.
Mycorrhiza
History
The mycorrhizal lifestyle for fungi is ancient and found globally (Smith and Read
2008; Kohler et al. 2015). The earliest evidence of mycorrhizal-like fungi comes from 460
million year old fossils from the mid-Ordovician Guttenberg Formation (Redecker et al.
2000). The fossilized spores and hyphae found resemble those from the extant group
Glomales (Redecker et al. 2000). Approximately 60 million years later in the Lower
Devonian an arbuscule, concrete evidence of a mycorrhizal association, was fossilized in
the Rhynie Chert in Scotland (Remy et al. 1994; Strullu-Derrien et al. 2014). This finding
indicates that arbuscular mycorrhizae (AM) were likely the first mycorrhizal type to arise
8
(Remy et al. 1994; van der Heijden et al. 2015). However, there is evidence that fungi from
the Mucoromycotina may have been forming mutualisms at nearly the same time as AM
fungi since fossils of Mucoromycotina associating with early land plants were recently
found in the 400 million-year-old Rhynie Chert (Strullu-Derrien et al. 2014).
Many mycorrhizal fungi were originally saprophytic or parasitic in nature and
gradually lost some to most of their capacity to degrade complex molecules and therefore
began to form symbiotic relationships with plant roots as an alternative (Tedersoo et al.
2010; Kohler et al. 2015). The ECM condition has arisen from the loss of saprotrophy
independently in at least 78 to 82 individual lineages of fungi according to Tedersoo and
Smith (2013). The earliest fossil record of an ECM root tip was found in the middle
Eocene Princeton Chert in British Colombia and dates back to 50 million years ago
(LePage et al. 1997). However, Berbee and Taylor (2001) found that early EMF lineages
could have arisen as far back as 200 million years ago. Regardless, ECM development was
much later than that of AM (van der Heijden et al. 2015).
Mycorrhizal Classification
The classification of mycorrhizal types has evolved as understanding of the
mycorrhizal associations has increased. In 1885 Frank coined the term ‘mycorrhiza’ or
‘fungus-root’ (Frank 2005). Others have subdivided mycorrhiza into different groups, but
Peyronel et al. (1969) grouped mycorrhiza into three main categories (endomycorrhiza,
ectomycorrhiza, and ectendomycorrhiza), based on physiological characters of the root and
fungus interaction. With increased understanding of mycorrhizal associations, the
classification scheme has expanded to include seven types (arbuscular (AM),
ectomycorrhiza (ECM), ectendomycorrhiza, arbutoid, monotropoid, ericoid and orchid)
(Smith and Read 2008). However, an alternative classification lists only five types
(vesicular-arbuscular (VAM), ectomycorrhizal (ECM), orchid, ericoid, and subepidermal),
which then contain subcatagories (Brundrett 2004). In this classification scheme, the
9
arbutoid and monotropoid types are placed as sub-categories of ectomycorrhiza and the
ectendomycorrhiza are deemed a morphotype and not a true category (Brundret 2004).
Regardless of categorical hierarchy, there tend to be typical physiological
characters associated with types, or sub-categories, of mycorrhiza (Brundrett 2004; Smith
and Read 2008). VAM (AM) are formed by aseptate fungi and found within the root
cortical cells of plants and can be either linear or coiling types (Smith and Read 2008).
They form arbuscules (nutrient exchange sites) within plant cells and vesicles (Brundrett
2004; Smith and Read 2008). They are most common when considering all vascular land
plants (Brundrett 2009). In contrast, ECM form a fungal sheath encompassing the roots
and a Hartig net for nutrient transfer is formed by hyphae penetrating between, but not
within, hosts plant root cells. However, in Brundrett’s (2004) classification the transfer
cell, monotropoid, and arbutoid sub-catagories of ECM there is hyphal penetration of plant
cells. ECM associations are highly important due to the widespread and dominant nature of
key hosts such as conifers and many hardwoods (Brundrett 2009). Despite differing
interpretations of their hierarchical classification, arbutoid and monotropoid associations
form with plants in the Ericales and Monotropoideae respectively (Smith and Read 2008).
Smith and Read (2008) classify ectendomycorrhizae as mycorrhizae that have a developed
Hartig net and root cell penetration, but with a reduced or absent sheath. Both Smith and
Read (2008) and Brundrett (2004) agree on the classification of ericoid and orchid
mycorrhizae, the former usually associating with plants in the Ericales and the latter
forming with Orchidales. However, Smith and Read (2008) point out that ericoid
mycorrhizae also form with bryophytes and Brundrett (2004) further sub-divides the orchid
mycorrhizae into categories based on hyphal location and commensalist vs. exploitative
nutritional status.
Many mycorrhizal fungi can form different kinds of associations depending on the
identity of the host plant (Smith and Read 2008). For instance, the same fungus can form
ecto-, arbutoid-, monotropoid, or orchid mycorrhizae (Smith and Read 2008). This
variability would suggest that the mycorrhizal form is determined by both the host and the
fungus and is highly versatile.
10
Ecological Roles
Mycorrhizal fungi are generally essential for plant growth, with more than 80% of
all flowering plant species being mycorrhizal (Smith and Read 2008; Brundrett 2009;
Simard and Austin 2010). When considering AM and ECM associations, seedlings of
various trees are typically not viable without appropriate fungal partners (Smith and Read
2008). In general, AM and ECM fungi assist in the uptake of plant essential nutrients such
as phosphorus and nitrogen (Read and Perez-Moreno 2003; Smith and Read 2008), and
allow for expedited uptake of water during dry periods due to improved nutrition and to
smaller diameter hyphae which have greater surface area for absorption than larger roots
(Lehto 1992; Auge 2001 (AM); Smith and Read 2008 (ECM)). Mycorrhizae also confer
benefits to the host plant such as protection from some fungal pathogens and some
protection from heavy metal contamination (Newsham et al. 1995; Leyval et al. 1997;
Regvar 2010). Additionally, mycorrhizae as beneficiaries of plant fixed atmospheric
carbon, are essential in terrestrial ecosystems as they facilitate the connection between
above ground and below ground nutrient cycles (Simard and Austin 2010).
EMF, Nitrogen & Phosphorus
Plant uptake of nitrogen, a limiting soil nutrient in many temperate forest
ecosystems, can be enhanced via EMF colonization (Finlay et al. 1992; Smith and Read
2008). Rygiewitz et al. (1984) found that Douglas-fir, Sitka spruce (Picea sitchensis
(Bong.) Carr.) and western hemlock (Tsuga heterophylla (Raf.) Sarg.) had increased
ammonium uptake when colonized by Hebeloma crustuliniforme (Bull. ex St. Amans.)
Quél. in comparison to non-mycorrhizal trees. Most EMF can utilize inorganic (nitrate and
ammonium), organic, or both sources of nitrogen, however, different taxa have varying
abilities in regards to the forms of nitrogen they best utilize (Finlay et al. 1988; Finlay et al.
1992). Finlay et al. (1992) investigated the abilities of ten EMF taxa to utilize various
forms of inorganic nitrogen in pure culture and found that they all grew well on
ammonium and less well on nitrate, despite variability in strain response. However,
11
Hebeloma crustuliniforme, Laccaria proxima (Boud.) Pat., and Paxillus involutus (Batsch)
Fr. grew only slightly less well on nitrate in comparison to ammonium (Finlay et al. 1992).
Finlay et al. (1988) investigated the uptake of ammonium specifically, and allowed
mycelium of Paxillus involutus, Pisolithus arhizus (Scop.) Rauschert (prev. tinctorius),
Rhizopogon roseolus (Corda) Th. Fr. and Suillus bovinus (L.) Roussel, growing in
association with Pinus sylvestris L., to access peat sources labeled with 15N ammonium.
They showed that labeled glutamate/glutamine and aspartate/asparagine were present in
significant amounts in every fungus species except for P. involutus (Finlay et al. 1988).
Bending and Read (1995) investigating organic N uptake, performed a similar experiment,
and found that when mycelium from Suillus bovinus and Thelephora terrestris Ehrh., in
association with Pinus sylvestris, colonized organic soil layers from a pine forest, the
organic nitrogen content of the soil decreased significantly for both fungi in comparison to
controls. However, it seemed that S. bovinus was able to utilize more organic nitrogen than
T. terrestris (Bending and Read 1995). Piloderma species have been found growing in
dense and extensive mycelial mats in organic soil horizons where they alter local nutrient
uptake (Kluber et al. 2010; Kluber et al. 2011; Zeglin et al. 2012; Phillips et al. 2012).
Kluber et al. (2011) found that Piloderma mats maintained greater concentrations of a
chitin degrading enzyme, providing greater access to organic N, than non-mat soils
throughout the year. In a similar study, Kluber et al. (2010) found that mycorrhizal mats,
some formed by Piloderma sp., in organic soil horizons and in mineral soils, maintained
greater levels of chitinase, pheneloxidase and phosphatase in comparison to non-mat soils.
Interestingly, the mats found in organic layers were comprised of different fungal species
and had different enzyme expression than mats found in mineral layers (Kluber et al.
2010). Additionally, Phillips et al. (2012) investigated respiration rates of Piloderma
mycorrhizal mats and found that respiration was increased by an average of 16% in
comparison to non-mat soils and that enzyme levels were positively correlated with
respiration rates in mat soils.
EMF have the capacity to alter nitrogen nutrition, but soil nitrogen levels can also
impact EMF community richness, structure and composition (Lilleskov et al. 2002; Avolio
12
et al. 2009; Kranabetter et al. 2009a; b; LeDuc et al. 2013). For instance, increases in
inorganic soil nitrogen caused a decrease in fungal diversity in a white spruce (Picea
glauca (Moench) Voss) forest in Alaska (Lilleskov et al. 2002). The decrease in fungal
diversity was likely because the spruce trees had a surplus of nitrogen and began to invest
in mycorrhizal fungi that were less specialized at nitrogen uptake (Lilleskov et al. 2002).
However, nitrogen deposition (gaseous ammonia) was exaggerated in the study area due to
anthropogenic factors (Lilleskov et al. 2002). In a forest with a natural nitrogen gradient,
Kranabetter et al. (2009b) found that EMF richness of fruiting bodies first increased and
then decreased as combined soil inorganic and organic nitrogen increased from 10 to 60 kg
ha-1 and that different EMF species had different tolerances for amounts and types of soil
nitrogen. Additionally, at the same study site, Kranabetter et al. (2009a) found that EMF
detected belowground increased in richness along a foliar nitrogen gradient of 9 to 15 g
kg-1 while individual species differed in percent colonization of root tips. Similarly, LeDuc
et al. (2013) investigated EMF community shifts along a fifty-one year chronosequence
after stand-replacing fire in jack pine (Pinus banksiana Lamb.) dominated stands in
Michigan. They found that the community shifted from one dominated by Suillus brevipes
(Peck) Kuntze and Thelephora terrestris towards one of greater complexity (increases of
Clavulina J. Schröt., Cortinarius (Pers.) Gray, and Russula Pers. taxa) over time and as
organic nitrogen and amino acid nitrogen increased; however the mechanism behind this
relationship was unclear (LeDuc et al. 2013). It seems that the type of nitrogen added to a
system and host tree species may also play key roles in EMF response as Avolio et al.
(2009) found that additions of organic nitrogen to oak seedlings actually increased total
root colonization in comparison to controls whereas mixed results were seen on pine
seedlings receiving organic nitrogen inputs.
Phosphorus (P) is also a key nutrient for plant growth and like nitrogen, can be a
limiting soil nutrient (Attiwill and Adams 1993; Plassard and Dell 2010; Binkley and
Fisher 2013). Generally plants and mycorrhiza solubilize and take up inorganic forms of
phosphorus (Pi) such as orthophosphates (Smith and Read 2008; Plassard and Dell 2010)
but many ectomycorrhizal fungi have the capacity to take up organic forms of phosphorus
13
(Po) as well (Dighton 1991; Cairney 2011). EMF fungi can take up Pi in solution via
specific P transporters (Tatry et al. 2009) or by exuding low weight molecular acids that
weather soil minerals and solubilize soil Pi (Barker et al. 1998; Landeweert et al. 2001;
Hagerberg et al. 2003; Plassard and Dell 2010). They utilize P from organic phosphorus
(Po) sources by secreting phosphatases into the soil that act to free Po from organic
complexes (Perez-Moreno and Read 2000; Courty et al. 2006; Plassard and Dell 2010).
This capacity for mycorrhizal fungi to improve plant P nutrition (Chalot et al. 2002;
Plassard and Dell 2010) can be essential in soils influenced by volcanic ash, since
phosphorus sources are often bound to ash surfaces (Appelt et al. 1975; Andregg 1988;
Page-Dumroese 2007).
Different EMF taxa have different capacities for both organic and inorganic P
uptake (Wallander 2000; Courty et al. 2005; Cairney 2011). Taxa in several genera
(Cortinarius, Hebeloma, Lactarius, Paxillus, Piloderma, Pisolithus and Suillus) release
significant amounts of low weight molecular acids (Courty 2010, Plassard and Dell 2010),
central in mineral weathering processes (Drever and Stillings 1997) that free Pi.
Specifically, Wallander (2000) found in a pot experiment that a strain of Suillus variegatus
(Sw.) Kuntze and an unidentified fungus positively influenced P nutrition in Pinus
sylvestris seedlings when apatite was the only source of P. Mahmood et al. (2002) found
that a Piloderma species may have been important for Pi acquisition from granulated wood
ash based on the frequency of granule colonization in a fertilization study in a Norway
spruce (Picea abies (L.) Karst.) stand in Sweden. As for utilization of Po sources, Courty et
al. (2006) found that three dominant EMF (Lactarius quietus (Fr.) Fr., Cortinarius
anomalus (Fr.) Fr., Xerocomus chrysenteron (Bull.) Quél.) in an oak (Quercus spp. L.)
forest in France followed similar trends in phosphatase production throughout the year. In
a similar study, Courty et al. (2005) investigated enzymatic activity of ten EMF taxa at
different soil layers in an oak forest and found that many taxa displayed differential
enzymatic activity depending on soil layer. Interestingly, Lactarius quietus (Fr.) Fr.
showed increased phosphatase moving from the A1 to the A2 layer, while Cortinarius
olivaceofuscus Kühner showed a decrease in phosphatase activity from A1 to A2 (Courty
14
et al. 2005). From a community stand point, Baxter and Dighton (2005) found that
increased EMF diversity positively improved Po uptake by Pinus rigida P. Mill. seedlings,
but that the EMF community composition did not impact P uptake.
Growth, Reproduction, Molecular Advances
Ectomycorrhizal host plants generally dominate the forests of boreal and temperate
areas like the Pacific Northwest (Smith and Read 2008). In central Oregon the forests are
mainly composed of coniferous ECM forming hosts and often maintain components of
understory trees, which associate with EMF (Simpson 2007; van der Heijden et al. 2015).
The majority of EMF that reproduce sexually do so by forming epigeous or hypogeous
fruiting bodies that release spores. New ECM colonization can come about via spore
germination as well as by colonization by extra-radical mycelium from other plant roots
(Baar et al. 1999; Horton et al. 1999; Bruns et al. 2002a; Peay et al. 2009). Some EMF are
not known to produce a fruiting body and tend to multiply via asexual means, like
Cenococcum geophilum Fr. which tends to spread via sclerotia (Massicotte et al. 1992).
Molecular methods for identifying fungal species from ECM plant root tips became
prevalent in the mid-1990s and revolutionized the understanding of belowground
mycorrhizal communities (Smith and Read 2008). Prior to this time, estimates of EMF
diversity from sporocarp studies were useful for understanding food web functions and for
comparison of current with historic studies to identify trends in fungal communities, but
they incompletely documented diversity (Smith et al. 2002). Gardes and Bruns (1996)
sampled EMF sporocarps found above-ground and ECM root tips below-ground in a
bishop pine (Pinus muricata D. Don) stand for four years and found that sporocarps were
not adequately representative of the belowground EMF community. However, while we
now know that many trees host a great diversity of EMF we are still only scratching the
surface of how these fungal communities function and the role of each fungus within an
ecosystem. In a pioneering continent-wide study, Talbot et al. (2014) found that many
15
EMF perform similar roles across ecosystems and that functional convergence was
common in North America.
Common Mycorrhizal Networks
An EMF individual can colonize more than one host, and because many plants in
PNW forests are ECM forming, high probability exists for extensive EMF connections
among plants (Amaranthus and Perry 1994; Simard 1997; Smith and Read 2008). Common
mycorrhizal networks are important infrastructures that contribute to below and
aboveground community success. Simard et al. (1997a) found that labeled carbon could
travel bi-directionally between the hosts Betula papyrifera Marsh. and Douglas-fir via an
established mycorrhizal network. Another function of CMNs is possibly connecting larger
trees with seedlings or germinants that would provide them with mycorrhizal innoculum
and may be important for resource sharing (Teste et al. 2009). Teste et al. (2009)
investigated this possibility in a dry Douglas-fir forest in Canada and found that CMNs
were important for nutrient transfer and survival of germinated seedlings. In addition to
positive effects from nutrient transfers, Bingham and Simard (2011) found that laboratory
seedlings placed under drought stress had a greater survival rate when connected via a
CMN to another seedling that had access to adequate water, than those not connected to
CMNs. Beiler et al. (2010) did not investigate water or nutrient movement via CMN, but in
a mapping study found that mycorrhizal networks formed by Rhizopogon spp. in a
Douglas-fir forest were extensive and served to promote new Douglas-fir seedling
establishment and development. Aside from nutrient and water transfer and facilitation of
regeneration, CMNs may play a role in plant responses to pathogens as it has been shown
that CMNs comprised of AM fungi can facilitate transport of signals from infected plants
to non-infected plants (Song et al. 2010; Babikova 2013). Song et al. (2010) facilitated
formation of a CMN between pairs of tomato plants (Lycopersicon esculentum Mill.) with
Glomus mosseae (T.H. Nicolson & Gerd.) Gerd. & Trappe and when a pathogen was
introduced onto one tomato plant, genes for defensive enzymes were upreglated in the
16
other. Similar results were reported with bean plants (Vicia faba L.) connected by a CMN
and attacked by aphids (Acyrthosiphon pisum Harris). The function, frequency, and extent
of these networks continues to be explored, however there is evidence that they are
essential to forest ecosystems.
Generalists & Specialists
Two categories of EMF as far as host associations are concerned are generalists and
specialists. Generalist fungi can associate with many different plant species, and specialists
associate with a single species or genus (Molina et al. 1992). One exception to
specialization is in cases of epiparisitsm where fungi that would be host-specialists, are
also associated with achlorophylous heterotrophic (Monotropoideae, Epidendroideae,
Orchidoideae, Vanilloideae) plants that utilize carbon transferred from associated
autotrophic plants for all or part of their lives (Luoma 1987; Smith and Read 2008). An
example of this is Rhizopogon subcaerulescens A.H. Sm., which is specific to Pine hosts,
but is the only fungus known to associate with Pterospora andromedea Nutt., a myco­
heterotropic plant in the Monotropoideae (Leake 1994). However, in general, CMNs
between dissimilar host species would be comprised of generalist fungi. One of the
ecological advantages of having generalist fungi in an EMF community is that if there are
disturbances that damage one forest patch or particular host tree then sufficient fungal
innoculum may be present on the roots of nearby trees for the recolonization of newly
germinating seedlings (Hagerman et al. 1999; Kranabetter et al. 1999; Nara and Hogetsu
2004).
Chinquapin
Biology & Ecology
Chinquapin ranges from west-central Washington south to northern California,
however it is most prevalent in Oregon and California (McKee 1990; Niemiec et al. 1995;
17
Meyer 2012). There are two growth forms of chinquapin, a tree form and a shrub form
(McKee 1990; Niemiec et al. 1995). Generally, neither growth form occurs in pure stands,
but is instead often found mixed with conifers (McKee 1990; Niemiec et al. 1995). The
tree form tends to grow on sites with more precipitation than sites where the shrub form is
found and it is generally found from Lane County, OR south to Marin County, CA (McKee
1990). The shrub form of chinquapin can grow in harsh conditions and is often found at
high elevations and dry sites with rocky soils, such as parts of the Cascade Range and just
east of the Cascade Range in central Oregon (McKee 1990; Niemiec et al. 1995).
Chinquapin flowers from June to midwinter (McDonald 2008) and produces
mature seed in the fall two years later (Neimiec et al. 1995; Baldwin et al. 2012). It is
evergreen, sclerophyllous and relatively shade tolerant (Keeler-Wolf 1988; Neimiec et al.
1995; Hunter 1997). Chinquapin rooting habits have not been studied in detail, however it
has been reported that they initially develop a deep taproot and then, as they age, further
develop a spreading lateral root system (Neimeic et al. 1995).
Economic Significance
The tree form of chinquapin can be used for furniture making or paneling, however
it is not often cultivated for this purpose as low volumes from mixed stands are generally
not worth milling (McKee 1990; Niemiec et al. 1995). Whereas the wood machines and
sands easily, it can be difficult to work with if not air-dried prior to kiln drying because of
its propensity to check (Niemiec et al. 1995).
Cultural Significance
Chinquapin nuts and sometimes leaves have been eaten or used as tea by at least
seven indigenous tribes in the PNW (Coville 1897; Chesnut 1902; Schenck and Gifford
1952; Mahar 1953; Gifford 1967; Baker 1981). The Southwestern Pomo people of the
Sonoma County area of California purportedly ate chinquapin nuts when they were
available, however the nuts were recorded as being from the tall coastal tree growth form
18
of chinquapin (Gifford 1967). Chesnut (1902) recorded that chinquapin nuts were also
occasionally eaten by the Native Americans in Mendocino County, California, but were
reportedly eaten more frequently by Native Americans further north. An example is the
more northerly Klamath, Yurok and Tolowa tribes eating the nuts (Coville 1897; Baker
1981). Additionally, it seems the Paiute people of the Warm Springs Indian Reservation
used the leaves for tea (Mahar 1953). The Karok tribe in Humboldt and Siskiyou Counties,
California, also ate the nuts, but nuts from tanoak (Notholithocarpus densiflorus (Hook. &
Arn.) Manos, Cannon & S.H. Oh) were preferred (Schenck and Gifford 1952).
Ecosystem Services
Chinquapin in the central Oregon forests is important for a variety of ecosystem
services. It recovers quickly from damage and is useful for ameliorating effects of erosion
in watersheds after fire disturbance (McKee 1990; Meyer 2012). Additionally, it is one of
the only mid-level trees on Lookout Mountain to provide mast for small mammals, birds
and insects (McDonald et al. 1983; McKee 1990; Neimeic et al. 1995). It is also one of the
few hosts of the golden hairstreak butterfly (Habrodais grunus Boisduval) (Shoal 2009).
Chinquapin provides cover for birds and small mammals. On the west side of the
Oregon Cascades sightings of Red-breasted nuthatch (Sitta canadensis Linnaeus),
Empidonax flycatchers (dusky (E. oberholseri Phillips or Hammond’s (E. hammondii
Xantus de Vesey)), and Pine siskin (Carduelis pinus A. Wilson) were positively associated
with small and medium sized chinquapin trees (Gilbert and Allwine 1991b). Presence of
red tree voles (Arborimus longicaudus True) and Pacific shrews (Sorex pacificusi Coues)
was positively associated with chinquapin as well (Gilbert and Allwine 1991a).
Chinquapin & Fire
Chinquapin, with its ability to regenerate from root crowns, burls and root sprouts
(Kauffman 1986), can generally withstand fires (McKee 1990, Kauffman and Martin 1990;
Niemiec et al. 1995; McDonald 2008). Chinquapin’s aboveground vegetation tends to die
in fire, causing basal diameter, crown volume, cover and aboveground biomass to decrease
19
after fire, but vigorous spouting, especially of larger individuals occurs within 2 seasons
(Kauffman and Martin 1990; Donato et al. 2009). Kauffman and Martin (1990) found that
on average 27% to 78% of chinquapin individuals exposed to prescribed burns survived
and resprouted, depending on the season of the burn (early fall vs. early spring). Donato et
al. (2009) showed that larger trees were more likely to survive and resprout after burning.
Kauffman (1986) found that chinquapin possesses root meristematic tissue in the mineral
soil that would partially account for its regenerating capabilities.
Despite the evidence that chinquapin can survive and flourish after forest fire, there
are conflicting results about how well chinquapin recovers after severe fire. Donato et al.
(2009) report that chinquapin survived and showed no change in resprouting ability after
two severe forest fires (occurring within 15 years of each other) compared to its respouting
ability after one severe forest fire in the Klamath-Siskiyou Mountains in Oregon. In
contrast, Halpern and Spies (1995) report that chinquapin in plots in the H. J. Andrews
Experimental Forest in Oregon that were logged and heavily burned in 1963, did not
resprout or recolonize the site even up to 27 years later. These contrasting results may be
because different environmental factors affecting chinquapin’s tolerance to fire. For
example, Kauffman and Martin (1990) found that fuel consumption, season, shrub size,
and growth stage all impacted shrub survival after prescribed fires in the Sierra Nevada.
Competition
Chinquapin is controlled in plantations to prevent water, nutrient, or shade induced
stress that negatively affects conifer seedling growth (McKee 1990; Nambiar and Sands
1993; Zhang et al. 2006). However, Keys and Maguire (2005) synthesized results from
three studies and concluded that initial shrub cover in ponderosa pine stands facilitates pine
germinant survival for the first one or two summers of growth. Thus, although reasons to
control chinquapin in silvicultural situations are valid, reasons to retain it include providing
valuable mast and cover for small mammals and birds (McKee 1990), enhancing survival
20
of some Pinaceae germinants (Keyes and Maguire 2005), and potentially supporting
mycorrhizal communities on which Pinaceae species depend (Kauffman and Martin 1990).
Chinquapin Ectomycorrhiza
Investigation of chinquapin EMF communities in the Pacific Northwest is
rudimentary, although it has been reported to be a host for matsutake (Tricholoma
magnilevare (Peck) Redhead) (Lefevre 2002). However, because chinquapin is
phylogenetically related to old-world Lithocarpus Blume, old and new world Quercus L.,
Castanea Mill. in the northern hemisphere, Notholithocarpus Manos, Cannon & S.H. Oh,
and Asian Castanopsis (D. Don) Spatch (Manos et al. 2008, Oh & Manos 2008), we
hypothesized that the EMF communities on chinquapin might resemble those on species
found in these genera. Unfortunately, detailed studies of the mycorrhizal associations of
southeast Asian Lithocarpus pachylepis A. Camus and Lithocarpus xylocarpus (Kurz)
Markgraf, chinquapin’s nearest phylogenetic neighbors (Manos et al. 2008), have not yet
been undertaken. However, there have been studies investigating ECM communities on
Castanopsis fargesii Franchet in southwest China (Wang et al. 2011), a Castanopsis forest
in central Nepal (Christensen 2009), Quercus liaotungensis Koidz. in northern China
(Wang et al. 2012), Quercus garryana Dougl. ex Hook. in southern Oregon (Valentine et
al. 2004), Notholithocarpus densiflorus in northern California (Bergemann and Garbelotto
2006), and on Castanea dentata (Marshall) Borkh. in western Wisconsin and Ohio (Palmer
et al. 2008; Bauman 2010). Lactarius Pers., Russula Pers., Tomentalla G.H. Cunn., Boletus
L., and Scleroderma Pers. were found with oaks in the compared literature almost
ubiquitously (Table 1). On average, 14 genera were found associated with these oaks, with
a minimum of six being found on Castanopsis fargessii and a maximum of 35 being found
on Notholithocarpus densiflorus (Table 1). The oaks investigated had an average of 6
unique genera, with a minimum of zero and a maximum of 22. Differences in methods for
EMF identification or study location were not taken into account in this summary.
21
Pinaceae
Pacific Northwest Genera and Species
Coniferous trees in the Pinaceae dominate the forests of the PNW, including those
of central Oregon (Simpson 2007). This family encompasses many economically,
ecologically, and socially valuable trees (Campbell et al. 2002; Campbell et al. 2003).
Six Pinaceae genera are represented in Oregon’s forests (fir (Abies Mill.), larch
(Larix Mill.), spruce (Picea A. Dietrich), pine (Pinus L.), Douglas-fir (Pseudotsuga Carr.),
and hemlock (Tsuga (Endlicher) Carr.)) (Campbell et al. 2002; Campbell et al. 2003).
Douglas-fir dominates most of the forests in western Oregon (Campbell et al. 2003).
However, significant percentages of hemlocks, firs, and pines inhabit western forests as
well (Campbell et al. 2002). Central and eastern Oregon forests are often dominated by
ponderosa pine but also maintain other Pinaceae genera (Campbell et al. 2003). In Oregon
some of the most economically and ecologically valuable trees in the Pinaceae are
Douglas-fir and ponderosa pine (Lowerey 1984; Gale et al. 2012).
Economic Significance
The logging industry in Oregon was built around fast growing conifer trees,
particularly Douglas-fir, hemlocks, and pines such as ponderosa pine (Lowerey 1984; Gale
et al. 2012). These giants provided for generations of individuals and a thriving logging
industry (Graham and Jain 2005; Andrews and Kutara 2005). Oregon has been, and
continues to be a top producer of U.S. timber (Andrews and Kutara 2005; Gale et al.
2012). The logging industry took several economic hits in the past two to three decades,
due to changes in Federal land regulation and the economic downturn in the mid 2000’s
(Gale et al. 2012). In 2007 Oregon’s timber production started to decline, reaching a low
point in 2009 and reports showed that by 2010 the industry had lost approximately 14,400
jobs and $527 million since the downturn (Gale et al. 2012; Oregon 2015). However,
timber production rebounded and reached pre-recession levels by 2013 (Oregon 2015).
Despite variability in timber harvests, the standing timber volume of Oregon’s forests in
22
2010 remained unchanged from the volume available in 1953 (Gale et al. 2012). The
industry has undergone major operational changes, but continues to play a large economic
role in the state providing for 76,000 jobs statewide and generating $5.2 billion in revenue
per year (Gale et al. 2012). This figure represents 11% of the statewide economic base
(Gale et al. 2012).
Harvests have declined in federally owned forest lands throughout Oregon in the
past 20 to 30 years due to changes in federal land management and listing of threatened
species such as the northern spotted owl (Strix occidentalis caurina (Xantus de Vesey) and
the marbled murrelet (Brachyramphus marmoratus (Gmelin)) (Gale et al. 2012).
Specifically, harvests of pine from federally owned forests in Oregon have declined from
18% of the harvest in the 1980’s to only 4% in 2008, likely due to reduced harvest of
pondersoa pine in central and eastern Oregon (Gale et al. 2012). This transition is likely
because federal agencies have shifted towards multiple-objective management of forests
including: timber production, wildlife habitat, ecosystem services, and recreation (Hessel
1988). It is recognized that central Oregon’s pine dominated forests are an important
region of the PNW forests aside from timber harvests as they are responsible for storing at
least 33kg m-2 of carbon (Birdsey 1992; Turner et al. 1995; Smithwick et al. 2002),
generating state recreational revenue (Loomis 2005) as well as being important habitat for
wildlife (Gilbert and Allwine 1991a; b; Woodward 2011).
Pinaceae Range & Biology
The most abundant Pinaceae species found in the study site on Lookout Mountain
are ponderosa pine, lodgepole pine, western white pine, and grand fir. Despite all being in
the same family, each of these species is unique and occupies a different niche within
forest ecosystems (Burns et al. 1990). Below are summaries of each species range and
biology.
23
Ponderosa pine (Pinus ponderosa Dougl. ex Laws.)
Ponderosa pine is a three needle pine, (sometimes having only 2 needle fascicles
depending on race), that ranges from Canada south to Mexico and east to Nebraska from
the Pacific Ocean (Oliver and Ryker 1990). Ponderosa pine is known to be competitive on
relatively dry sites (Oliver and Ryker 1990). Ponderosa pine’s drought tolerance partially
stems from the ability to increase transpiration rates when heat stressed due to its deep root
system (Kolb and Robberecht 1996). Ponderosa pine seedlings invest early in growing a
deep taproot (Berndt and Gibbons 1958; Larson 1963). Roots of mature trees can grow to
depths of more than two meters in loose soils or even down to 12 m if there are fissures in
the bedrock (Oliver and Ryker 1990). Additionally, they produce a large lateral root
system that can extend out past the crown in open stands, but is less extensive in dense
stands (Oliver and Ryker 1990). Ponderosa pine also tolerates lower soil nutrient levels
and requires lower levels of foliar N and P than some other conifers (Oliver and Ryker
1990).
Ponderosa pine is also highly resistant to fire due to its thick bark and ability to
survive even after fifty percent of its crown has been singed (Oliver and Ryker 1990). This
resistance has helped it retain dominance, despite shade intolerance, in some areas due to
the lesser ability of some other conifers to withstand fires (Oliver and Ryker 1990).
Historically one of the major timber producing species of the western United
States, Ponderosa pine has been used to make doors, paneling, moldings, poles, posts,
plywood, pulp and for a myriad of other uses. (Lowerey 1984).
Lodgepole pine (Pinus contorta Dougl. ex Loud.)
Lodgepole pine is a two needle pine found from the Yukon Territory of Canada
south to Baja California and east to the Black Hills of South Dakota from the Pacific
Ocean (Lotan and Critchfield 1990). On Lookout Mountain, lodgepole pine is found
mainly at the lower and mid elevations (Results Section). In general lodgepole pine grows
better on moister soils than ponderosa pine, however it thrives in a variety of different
24
environmental conditions and is capable of growing in relatively infertile soils (Horton
1956; Lotan and Critchfield 1990). Root systems develop more slowly and are generally
shallower than those of ponderosa pine (Lotan and Critchfield 1990). A first year
seedling’s root system is generally shallow and lacks a deep taproot (Noble 1979). Root
systems also tend to be fairly shallow in rocky areas (Lotan and Critchfield 1990).
Lodgepole pine is often found on andisolic soils, such as those on Lookout
Mountain, throughout their range in central Oregon (Lotan and Critchfield 1990). Similar
to ponderosa pine, lodgepole pine is shade intolerant (Lotan and Critchfield 1990).
However, lodgepole pine is not as fire tolerant as ponderosa pine due to thinner bark
(Lotan and Critchfield 1990). The species adapts to fire via quick regeneration post fire
from serrotinous cones (cones that open with heat) (Lotan and Critchfield 1990). However,
the degree of serotiny in lodgepole stands can vary based on previous fire history and
genetics (Lotan 1967; 1976; Parchman et al. 2012).
Lodgepole pine wood is used for framing, paneling, posts, poles, railroad ties and
wood pulp (Lotan and Critchfield 1990).
Western white pine (Pinus monticola Dougl. ex D. Don)
Western white pine is a five needle pine that ranges from southern British
Columbia south along the Cascade Range into California (Graham 1990). Additionally, a
separate population occurs in northern Idaho and extends into southern Canada (Graham
1990). On Lookout Mountain western white pine is found only at high elevations (Results
Section). Throughout its range it is found mainly in relatively moist areas like streambeds
and northern slopes (Graham 1990).
Western white pine develops a relatively shallow root system with the bulk of
absorptive mass located in the top 65cm of soil (Graham 1990). Additionally, development
of roots and shoots is slow in seedlings, and despite being relatively shade tolerant,
development is slower when they are shaded (Graham 1990). This species tends to be
present in mixed stands and is often seral and non-dominant (Graham 1990).
25
Western white pine is less fire resistant than ponderosa pine, due to thinner bark
and relatively flammable foliage (Starker 1934; Graham 1990). However, as a seral
species, it depends on fire to reduce competition for establishment (Graham 1990).
Western white pine timber is used for specialty work like trims, moldings and cabinets due
to its non-resinous nature and more generally for plywood (Graham 1990).
Grand fir (Abies grandis (Dougl. ex D. Don) Lindl.)
Grand fir is found from southern British Colombia, Canada south to the Pacific
coast in northern California (Foiles et al. 1990). It is prevalent west of and throughout the
Cascades in Washington and Oregon (Foiles et al. 1990). Additionally, a large population
of the subvariety, A. grandis var. idahoensis Silba, is present in northern Idaho extending
north into southern Canada (Silba 1990; Foiles et al. 1990).
Grand fir is generally found with other conifers, and on moist sites, it can be a
competitive component of the overstory (Foiles et al. 1990). In the Oregon pumice zone
this species can grow well on shallow and exposed mountain ridges as long as there is
enough moisture (Foiles et al. 1990). When growing in drier areas, grand fir compensates
by growing a deep root system and can be fairly resistant to drought and heat injury (Foiles
et al. 1990). In seedlings, deep taproots tend to develop much faster if grown in full sun
(Foiles et al. 1990). While grand fir can be shade tolerant, seedlings are initially more
susceptible to drought when grown in shade due to their shallower root systems (Foiles et
al. 1990).
When grand fir is found on dry sites, it tends to be more fire resistant than
individuals grown in mesic areas (Foiles et al. 1990). This fire resistance is due to the
development of thicker bark and deeper roots in dry areas (Foiles et al. 1990). Generally,
since grand fir is a soft wood, its industrial uses are limited to wood pulp production,
however it is also cultivated for use as Christmas trees (Foiles et al. 1990).
26
Summary
The Lookout Mountain unit of the PFEF is an ideal location for the study of
Pinaceae and chinquapin EMF communities. The area has been extensively studied as a
result of its incorporation into the PFEF (Youngblood 1995) and its disturbance history is
well known (Youngblood 2009). The PFEF is representative of other volcanically
influenced Pinaceae dominated forests in central Oregon. Because PFEF is an area prone to
frequent fire (Adams et al. 2004), and possibly stand replacing fire due to climate change
(Westerling et al. 2006) and fuel accumulation (Youngblood 2009), makes the
investigation of chinquapin as a possible EMF refuge plant viable and relevant for this
location.
27
Table 1. Comparisons of EMF genera found associated with Pinaceae and chinquapin to genera found on hosts
phylogenetically related to chinquapin. Host species abbreviations and reviewed literature citations below table.
Fungal Genus
Amanita
Amphinema
Byssocorticium
Cenococcum
Cortinarius
Elaphomyces
Gautieria
Hygrophorus
Hysterangium
Inocybe
Lactarius
Leucogaster
Leucophleps
Lyophyllum
Melanogaster
Phellodon
Phialocephala
Piloderma
Pseudotomentella
Ramaria
Rhizopogon
Russula
Pinaceae
Chinq.
CADA a & b
CAFAc
CAfor.d
NODEe
QUGA f
POg
QULI h
QUsp.a
QUsp.i
RT
RT
RT
RT
FB
RT
RT
FB & RT
RT
RT
RT
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
28
Table 1 (Continued)
Sebacina
Sistotrema
Suillus
Thelephora
Tomentella
Tomentellopsis
Tricholoma
Wilcoxina
Alpova
Antrodiella
Astraeus
Aureoboletus
Austroboletus
Balsamia
Bankera
Barssia
Boletellus
Boletinus
Boletopsis
Boletus
Brauniellula
Cadophora
Camarophyllus
Cantharellus
Capronia
Ceratobasidium
Pinaceae
*
*
*
*
*
*
*
*
Chinq.
*
CADA a & b
*
CAFAc
CAfor.d
*
*
*
*
*
NODEe
*
QUGA f
POg
*
QULI h
*
QUsp.a
QUsp.i
*^
*
*
*
*
*
*
*^
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
29
Table 1 (Continued)
Pinaceae
Chalara
Chalciporus
Choiromyces
Chromelosporium
Chroogomphus
Clavulina
Coltricia
Cortinomyces
Craterellus
Cryptococcus
Dentinum
Destuntzia
Divide
Endogone
Entoloma
Galiella
Genabea
Genea
Geoglossum
Geopora
Gomphidius
Gomphus
Gymnomyces
Gyroporus
Hebeloma
Helvella
Humeria
Chinq.
CADA a & b
CAFAc
CAfor.d
NODEe
*
QUGA f
POg
QULI h
Qusp.a
Qusp.i
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
30
Table 1 (Continued)
Pinaceae
Hydnellum
Hydnoplicata
Hydnotrya
Hydnotryopsis
Hydnum
Hymenogaster
Laccaria
Lachnum
Leccinum
Lyophyllum
Macowanites
Marasmius
Neonectria
Pachyphloeus
Peziza
Phialocephela
Phialophora
Phylloporus
Pisolithus
Scleroderma
Tarzetta
Tricholoma
Tuber
Chinq.
CADA a & b
CAFAc
CAfor.d
NODEe
*
QUGA f
POg
QULI h
QUsp.a
QUsp.i
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
31
Table 1 (Continued)
Pinaceae
Tylopilus
Xerocomus
Chinq.
CADA a & b
CAFAc
CAfor.d
*
NODEe
QUGA f
*
POg
*
QULI h
QUsp
.a
QUsp.i
*
^Sebacinales & Thelephoraceae found
CADA = Castanea dentate, CAFA = Castanopsis fargesii, CAfor. = Castanopsis forest, NODE =Notholithocarpus densiflorus, QUGA = Quercus garryanna, PO = Pine-Oak, QULI = Quercus liaotungensis, QUsp. = Quercus spp.
a
Palmer et al. 2008, bBauman 2010, cWang et al. 2011, dChristensen 2009, eBergemann and Garbelotto 2006, fValentine et al.
2004, gDokmai et al. 2015, hWang et al. 2012, iMorris et al. 2009
32
STUDY MANUSCRIPT
Introduction
The forests of the western United States support recreational pursuits (Loomis
2005), provide vital wildlife habitat (Woodward et al. 2011), sequester carbon (Smithwick
et al. 2002) and sustain a timber industry (Gale et al. 2012). With climate change
occurring, these forests need to be adaptable and resilient if they are to thrive. Resilience is
the capacity for an ecosystem to accommodate change while still retaining its core
characteristics and function (Walker and Salt 2006). Several climate models predict
warmer and drier summers and wetter winters in the Pacific Northwest (Mote and Salathé
2010). These changes will likely alter regional fire regimes, defined as the interactions
among fire frequency, size, intensity, severity, type, and seasonality (Flannigan et al. 2000;
Dale et al. 2001; Hardy et al. 2001; Rogers et al. 2011). One potential way to achieve
resiliency in these forests is to ensure that mycorrhizal fungus communities, belowground
partners to trees, are maintained in the probable increases in disturbance from fire.
Mycorrhizal fungi form a mutually beneficial, obligatory symbiosis with most tree
species. The fungus obtains soil nutrients and water for the tree and the tree provides
simple sugars for the fungus (Smith and Read 2008). In the Pacific Northwest, trees in the
Pinaceae dominate the forests and form a type of mycorrhiza called ectomycorrhiza. The
fungi that participate in these relationships are called ectomycorrhizal fungi (EMF). More
than 6,000 fungal species form ectomycorrhizal associations (Brundrett et al. 2002). It is
well known that many trees, including the trees in the Pinaceae, would be untenable
without their belowground EMF partners (Smith and Read 2008). Therefore, the health of
these forests, and the industries that rely on them, rests partially upon the functionality of
the EMF belowground community.
Many Oregon forests are managed for timber production (Gale 2012) as well as
recreation (Loomis 2005). Historically, in order to preserve forest resources, fire has been
suppressed causing a build-up of fuels (Review 2001; Sommers et al. 2011; Rogers et al.
33
2011). The increased fuel load combined with the hotter and drier summers predicted by
climate change models will likely cause an increase in large and severe fires (Rogers et al.
2011). These changes may already be occurring; Kasischke and Stocks (2000) report that
the land area being burned annually in the United States has increased by three times from
1970 to 2000. For Pacific Northwest forests specifically, Rogers et al. (2011) estimate that
area burned by fire in the next 100 years will increase from 76% to 310% with an increase
in both burn intensity and severity.
Severe fires can have a negative impact on the diversity of EMF communities and
the recovery of complex EMF communities can be a long-term process. Stand replacing
fires remove or kill the majority of above ground vegetation, significantly changing the
vegetation structure (Sommers et al. 2011). As the ectomycorrhizal relationship is
generally obligatory for both the fungal partner and the plant host, damage or death of the
host from fire or other disturbances can also lead to decreased diversity in the EMF
communities necessary for future tree growth and health (Barker et al. 2013). EMF
communities can recolonize a site from heat-resistant soil spores (Baar et al. 1999; Peay et
al. 2009), windborne spores (Bruns et al. 2002b), or from mycelium adjacent to EMF hosts
(Horton et al. 1999). Depending on environmental factors, it can take at least a decade for a
community to fully recover (Treseder et al. 2004). For instance, Treseder et al. (2004)
found that it took up to 15 years for EMF communities to return to pre-burn levels of
colonization in an Alaskan forest after severe fire. In contrast, Barker et al. (2013) reported
that Douglas-fir seedlings planted in a low severity and high severity burn site were fully
colonized by EMF after just one year. Although the seedlings were fully colonized after a
year, the number of frequently occurring EMF taxa decreased at the high severity site, with
only Wilcoxina and Rhizopogon species dominating the community (Barker et al. 2013).
Typically, EMF form mycorrhizae with more than one host species within an
ecosystem (Molina and Trappe 1982a; Molina et al. 1992; Simard et al. 1997b; Kennedy et
al. 2003) and plants of the same or different species can be linked by their EMF hyphae
(Molina and Trappe 1982b, Amaranthus and Perry 1994; Simard 2009). Therefore, an
EMF community may be maintained through a disturbance event by refuge plants, species
34
of ectomycorrhizal plants that persist after disturbance, typically by resprouting (Baar et al.
1999; Hagerman et al. 2001). Hagerman et al. (2001) found that manzanita (Arctostaphylos
uva-ursi (L.) Spreng.) maintained a similar mycorrhizal community to the overstory
Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) even three years after the Douglas-fir
had been harvested. In a similar study, Nara and Hogetsu (2004) found that a shrubby
willow (Salix) pioneer species, which forms ectomycorrhizal associations, acted to
facilitate fungal inoculation of birch (Betula) and larch (Larix) species in a primary
succession area of a volcanic desert in Japan. Giant chinquapin (Chrysolepis chrysophylla
(Douglas ex Hook.) Hjelmq.) is one possible refuge plant found in the mixed conifer
forests of central Oregon.
Giant chinquapin (henceforth ‘chinquapin’) is an evergreen, sclerophyllous
understory shrub that infrequently achieves small tree stature in the forests of central
Oregon. It is typically viewed as competition for soil nutrients and water (Nambiar and
Sands 1993) to the timber producing trees in the Pinaceae (Meyer 2012). Chinquapin
contributes to fuel loads and is considered moderately flammable (Weatherspoon and
Skinner 1987). It can also shade seedlings of cultivated coniferous species, reducing initial
conifer growth (Meyer, 2012). Since chinquapin sprouts from stumps and roots it generally
recovers quickly after cutting or fire damage (McKee 1990; Kauffman and Martin 1990;
Niemiec et al. 1995; Donato et al. 2009). Due to these characteristics chinquapin is often
controlled in managed forests (Meyer 2012).
As an ectomycorrhizal host spieces, chinquapin may help to support the diversity of
essential fungal root symbionts in an ecosystem. If Pinaceae trees and chinquapin support
similar EMF communities, the quick sprouting nature of chinquapin may allow it to
maintain the EMF community after disturbances that damage overstory trees such as a
stand replacing fire. Resprouting chinquapin could act as a refuge plant and provide fungal
innoculum and access to mycorrhizal networks for germinating or out-planted Pinaceae
seedlings, making it an essential part of early ecosystem recovery.
Our objective was to determine whether or not chinquapin could serve as an EMF
refuge plant. We investigated the similarity of EMF communities of overstory Pinaceae
35
trees and understory chinquapin in the fire prone, mid to high elevation forests on Lookout
Mountain in central Oregon. Specifically, we wanted to know if EMF communities on
Pinaceae hosts and chinquapin were similarly rich (number of taxa) and diverse
(Shannon’s Diversity) and if the EMF community composition was similar between hosts.
We also explored the response of EMF communities to environmental variables with the
hypothesis that EMF communities would be influenced by soil nutrients, specifically
nitrogen and phosphorus, regardless of host.
Materials & Methods
Study Area
We conducted this study on the Lookout Mountain unit in the Pringle Falls
Experimental Forest (PFEF) within the Deschutes National Forest in central Oregon. The
study site elevations range from about 1400 m to 1700 m (Deschutes National Forest
2001). The majority of the sampling locations face in an easterly direction, from 68 ° to
187 ° (Deschutes National Forest 2001). Maps of the study area can be seen in Figures 1
and 2.
Climate
The PFEF, located just east of the Oregon Cascade Range, generally experiences
relatively dry weather with most precipitation falling as snow (Adams et al. 2004).
Standing at 1900 m, Lookout Mountain receives 1020 mm of precipitation a year on
average (Adams et al. 2004). High temperatures in the summer range from 21 to 32 °C and
nights are cool with frost possible during the growing season (Adams et al. 2004).
Vegetation
The Lookout Mountain Unit of the PFEF is dominated by ponderosa pine (Pinus
ponderosa Dougl. ex Laws.) at mid and lower elevations of the study site. As elevation
36
increases the forest shifts to a mixed-conifer stand maintaining: grand fir (Abies grandis
(Dougl. ex D. Don) Lindl.), rocky mountain fir (A. lasiocarpa (Hook.) Nuttall), red fir (A.
magnifica A. Muray), lodgepole pine (Pinus contorta Dougl. ex Loudon), sugar pine (P.
lambertiana Dougl.), western white pine (P. monticola Douglas ex D. Don), ponderosa
pine (P. ponderosa), Douglas-fir (Pseudotsuga menziesii), and mountain hemlock (Tsuga
mertensiana (Bong.) Carr.).
The forests on the mountain fall into three classifications: Pinus ponderosa/Purshia
tridentata-Ceanothus velutinus (CPS-312) which is at the lowest elevations and does not
support chinquapin; Mixed conifer/Ceanothus velutinus-Arctostaphylos patula (CWS-112)
which is at mid-elevation and does support chinquapin; and Mixed Conifer/Ceanothus
velutinus-Carex stoliferus (CWS-115) which is at the highest elevation in the study site
and also supports chinquapin (Youngblood 2009, Volland 1985).
Soils
The soils in the area are defined as Ashy-pumiceous, glassy Xeric Vitricryands as
described in the Lapine Soil Series (Soil Survey Staff 2014). The area was heavily
influenced by the Mt. Mazama eruption approximately 6,600 years ago (Youngblood
1995). Mazama ash fallout accumulates up to half a meter in some areas of the PFEF
(Adams et al. 2004). This ash layer adds to the andisolic nature of the soils and contributes
to its excessively well-drained and nutrient poor properties (Busse and Riegel 2004; Soil
Survey Staff 2014).
Study Design
The current study was devised as a complementary investigation to an experiment
focusing on increasing resilience of the forest via thinning the overstory to different
densities then masticating and underburning the groundcover (Youngblood 2009). This
larger study was set up as a randomized complete block design that split Lookout
Mountain into four blocks which were then each subdivided into five treatment units
37
(Youngblood 2009). On each treatment unit, a nine-hectare (ha) sampling unit, comprised
of twenty-five points arranged on a 50 × 50 m grid was established (Youngblood 2009).
Finally, around each point, a central circular plot (400m2) was delineated for vegetation
surveys, and two parallel transects (17 m long and 22.5 m apart), one on either side of the
circular vegetation plot, were established in a randomly selected cardinal direction
(Youngblood 2009) (Fig. 1). As a part of this larger study, soil moisture measurements
were conducted on one transect for a subset of the vegetation plots containing chinquapin.
To decide which transects would be used for soil moisture measurement, central vegetation
plots from a pool of all vegetation plots containing chinquapin, were chosen randomly
until two vegetation plots per chinquapin containing sampling unit were chosen; then one
transect of the transect pair was randomly selected. Since treatment units and sampling
units were arranged on Lookout Mountain based on elevation and overstory basal area
(BA) class, the selected vegetation plots and the associated pairs of transects covered the
range of elevations in the study site and all but the extreme ends of the range of overstory
BA. For our study of EMF we sampled the 16 pairs of transects where one transect was
used for volumetric soil moisture measurement (Fig. 2).
Vegetation & Soil Moisture
On each transect selected for volumetric soil moisture measurment, two soil
moisture tubes (PVC pipe, 5 cm diameter) were installed to a maximum depth of 75 cm
and then capped. Volumetric soil moisture data used in this study were collected every two
weeks during July and August 2012 with frequency domain reflectometry using a Troxler
Century 200 moisture meter (Troxler Electronic Laboratories, Inc. Research Triangle Park,
NC).
Vegetation surveys were conducted on the central circular vegetation plots (400m2)
during July and August of 2011 or during July, August, and September of 2012. Overstory
and understory vascular plants were all counted and identified to species (Youngblood
2009). Percent cover for understory plants was ocularly estimated (1% resolution from 1­
38
10% cover, 5% resolution from 11-100% cover) and the diameter at breast height (1.37m)
of overstory trees was measured to the nearest 0.1 cm with a diameter tape (Youngblood
2009).
Soil Sampling & Nutrients
In July and August of 2012, we obtained soil and root tips for ectomycorrhizal
community analysis by collecting four soil cores (10 cm depth, 5 cm diameter) (AMS, Inc.,
American Falls, ID) at least two meters apart on each transect. We preferentially targeted
chinquapin roots and so ensured a ≥ 75% chinquapin canopy cover over the square meter
of grount surrounding each soil core location. We collected mineral soil to a 10 cm depth
at each of these sampling locations and combined soil from each sampling location in a
transect transect for chemical analyses. All samples were transported on ice to the
laboratory after which they were stored at -20 °C for a maximum time of nine months.
For processing, the soil samples were thawed and sieved to 2 mm, and the fine
fraction was air-dried for at least five days and then finely ground (200-150 mesh) in a
BICO Model UA Pulverizer (Preiser Scientific, St. Albans, WV, Louisville, KY & Beijing,
China). Soil pH was measured in the 1:2 soil to water method (Horneck et al. 1989) via an
accuFlowTM pH Combination Electrode with accupHastTM (Fisher ScientificTM, Pittsburgh,
PA). Measurements of Bray phosphorus (Bray P), total phosphorus (Total P), ammonium
(NH4-N), incubation nitrogen (Inc. N), mineralizable nitrogen (Min. N), total carbon (%C)
and total nitrogen (%N) were performed by the Central Analytical Laboratory at Oregon
State University utilizing the methods found in Horneck et al. (1989).
Ectomycorrhiza Root Collection & Host Identification
Ectomycorrhizal root tips were selected from soil samples that were washed
through a series of 2 mm and 1 mm soil sieves (U.S.A. Standard Testing Sieves) to remove
silt and sand particles. The remaining roots were placed in petri dishes, viewed with a
Stemi SV6 stereomicroscope (Carl Zeiss Microscopy, LLC, Thornwood, NY) and hand­
39
sorted to separate live ectomycorrhizal root tips from dead organic material and remaining
soil particles. The live root tips from each sample were spread evenly on a 39 ×18 cm tray
overlaid with a 4 × 4 cm numbered grid (36 total grid squares). The root tip closest to the
center of 12 randomly chosen grid squares was selected for further processing. Additional
root tips were selected from each sample if they appeared to be unique morphotypes that
had not been selected in the random pick. This method resulted in approximately 12
random root tips with an average of 4.5 extra root tips per sample, for a total of 1,724 root
tips. Once root tips were selected, they were cleaned of all clinging organic material,
described, and then ground in 0.5 ml microcentrifuge tubes. The remaining fine roots and
root tips were air dried, then oven dried at 37 °C for a maximum of three days and weighed
to the nearest 0.0001 g. The DNA from the ground root tips was extracted with an altered
method of Extract-N-AmpTM (Sigma Aldrich, St. Louis, Missouri) procedure created by L.
Kluber (Unpublished 2010). This method called for the addition of 10 µl of Extract-NAmpTM extraction solution to the ground root tip. Next, the samples were vortexed, spun
and incubated at 90 °C for 10 minutes. Then 20 µl of Extract-N-AmpTM dilution solution
was added and the samples were vortexed and frozen or taken through the next steps of a
Polymerase Chain Reaction (PCR). The extracted DNA was taken through the process of
PCR twice in order to identify both the tree host and the fungus. Fungal specific primers
ITS1F (Gardes and Bruns 1993) and ITS4 (White et al. 1990) and plant specific
chloroplast primers trnH and psbA were used (Sang et al. 1997; Tate and Simpson 2003).
The PCR program for the fungal primers was as follows: 33 cycles of amplification (94 °C
30 s, 50 °C 1 min, 72 °C 1:30 min) with a total volume of 40 µl per reaction (23.95 µl
deionized H2O, 10 µl 5× PCR buffer, 4 µl 10× dNTPs, 0.4 µl of each primer, 0.85 µl
MgCl, 0.4 µl BSA, 0.32 µl GoTaq® (Promega, Madison, Wisconsin)). The PCR program
for the plant specific primers was as follows: 31 cycles of amplification (94 °C 30 s, 62 °C
1 min, 72 °C 1:30 min) with a total volume of 20 µl per reaction (12.9 µl deionized H2O, 4
µl 5× PCR buffer, 2 µl 10× dNTPs, 0.2 µl each primer, 0.5 µl MgCl, 0.2 µl BSA, 0.23
GoTaq®). After the PCR, the resulting products were electrophoresed through 2.5% agar
gels at 100 V for approximately two hours to check that the DNA had amplified. Once
40
imaged under ultraviolet light (AlphaImager EC, Alpha Innotech Corp. (acquired by Cell
Biosciences, Inc.), Santa Clara, CA) the DNA bands for the plant primers could be
assigned to either overstory Pinaceae trees or to chinquapin trees simply based on height of
the bands in relation to control DNA from host leaves and needles. The fungal PCR
products were imaged and those that showed amplified fungal DNA in a bright single band
on the gel, indicating the presence of one fungus in the sample, were cleaned with ExoSapIT® ((Affymetrix, Santa Clara, California) 1 µl PCR product and 6 µl ExoSap-IT®) and
2.5 µl of the resulting solution was run through a 2.5% agarose gel at 100 V for
approximately 1.5 hours. Based on the images of the resulting gel, a 12 µl solution of DNA
template, deionized water, and 1.2 µl of 10 µM primer was created. To prepare the samples
for sequencing, 5 µl of the DNA template and primer solution for each sample were placed
into plates and each was mixed with 5 µl of a solution composed of: 2 µl deionized water,
1 µl ABI BigDye® Terminator 3.1 (Applied Biosystems, Foster City, California), 1.5 µl
5X buffer, 0.5 µl dimethyl sulfoxide (DMSO). The plates were then placed in a Peltier
Thermal cycler (BioRad DNAEngine PTC-100, MJ Research, Inc., St. Bruno, Quebec,
CAN) and the following program was executed: initial step of 96 °C for 5 minutes
followed by 25 cycles of amplification (96 °C 30 s, 50 °C 15 s, 60 °C 4 min) with a total
volume of 10 µl per reaction. Fungal samples were sent to either the Center for Genome
Research and Biocomputing (CGRB) at Oregon State University or the Advanced Genetic
Technologies Center (AGTC) at the University of Kentucky for Sanger sequencing. All
samples were sequenced on an Applied BiosystemsTM ABI 3730 DNA analyzer
(ThermoFisher Scientific, Pittsburgh, PA). The resulting sequence files were uploaded into
the program GeneiousTM (version 7.1.7, Biomatters Ltd.). The sequences were trimmed to
remove basepairs below a 0.05 error probability limit. A total of 762 sequences were then
assembled with the Geneious Assembler via DeNovo assembly and sequences were
aligned according to 97% similarity. Consensus sequences were formed from the 99
resulting consensus sequence groups and these were compared to sequences in the
GenBank nucleotide database using the National Center for Biotechnology Information's
(NCBI) Basic Local Alignment Search Tool (BLAST) program. BLAST results were
41
filtered to remove target sequences labeled as ‘clonal’ or ‘metagenomic’. Species names
were assigned to the consensus sequences based on a 97% or above percent similarity to
the target sequences. Higher taxonomic names were assigned to consensus sequences
which did not as closely match the best target sequences or which matched several
species/genera equally well.
Statistical Analyses
The tree host and fungal community data were initially explored using summary
statistics to create graphs and identify possible trends. Spearman’s rank correlation
coefficient was used to assess possible relationships among the measured variables (A.
Muldoon pers comm. 2015). The observational nature of the study prevented the extensive
use of typical test based statistics. However, the number of ascomycete taxa compared to
basidiomycete taxa found on both Pinaceae hosts and chinquapin was compared using a
two-sided t-test in RStudio® (RStudio Team 2013, version 0.98.1056).
Despite efforts to sample preferentially under chinquapin shrubs, the majority of
root tips collected came from overstory conifer trees. In order to adequately compare the
taxa richness between the two hosts despite the unbalanced sample size we selected 6
transect pairs from the Pinaceae and 5 from chinquapin where identification of the EMF
fungi was greater than 55% and 60%, respectively. Using these data we generated species
rarefaction curves to estimate the likely number of taxa we would have found if we had
greater fungal identification success for the 16 total transect pairs (Colwell 2013,
EstimateS version 9.1.0).
In order to determine whether or not the EMF communities found on Pinaceae and
chinquapin hosts differed in composition and structure, we performed a Blocked MultiResponse Permutation Procedure (MRBP) in PC-ORDTM (version 6, MJM Software
Design) (McCune and Mefford 2011) with the fungal community matrix blocked by
transect pair and grouped by host tree. Then to visualize the communities and assess
impacts of environmental variables, we performed a Non-metric Multidimensional Scaling
(NMDS) on the presence-absence taxa data for both host groups considered separately
42
(McCune and Mefford 2011). The Pinaceae matrix used for this test was comprised of
fungi found in three or more transects and the chinquapin matrix included fungi found in
two or more transects. The distance matrices used for the NMDS analysis were calculated
with a Sørensen distance measure from a random starting configuration where ties were
penalized according to Kruskal’s secondary approach. Final solutions were tested against a
Monte Carlo randomization test (500 runs). When NMDS was successful, bi-plot overlays
were added to the plots to assess the effect of measured environmental variables on the
distribution of the taxa. Environmental variables that were correlated with an r2 value of
20% or more for the Pinaceae community and 15% or more for the chinquapin community
were considered significantly explanatory of the variation in the data.
Results
Vegetation Community
Of the Pinaceae community, ponderosa pine had the greatest basal area with an
average of 37.6 m2/ha per vegetation plot (Fig. 3). It was also dominant (greatest basal
area) or co-dominant in all plots except for the second to highest elevation plot where
western white pine and grand fir shared dominance (Fig.4). Grand fir basal area increased
with elevation and it shared dominance with ponderosa pine at the highest elevation plot
(Fig. 4). Lodgepole pine was present with a relatively low basal area in nearly 75% of the
vegetation plots, but had the greatest basal area at the lowest elevation site that also had the
highest level of Bray phosphorus. Red fir was entirely absent from the lower elevations
and only a minor component at the highest elevations. Chinquapin was found on all
transect pairs in the study and ranged in percent cover from 1.5% to 85% per transect pair.
The most diverse Pinaceae communities in the study were found in unit 12, at the
highest elevations, whereas the least diverse Pinaceae community was in vegetation plots
31_22 and 33_12, which contained only ponderosa pine (Fig. 5). It should be noted that
data on overstory Pinaceae was not available for vegetation plots 11_18 and 11_20.
43
Of the 11 environmental variables used in this analysis (Table 2), chinquapin
percent cover was positively correlated with pH (Table 3). In the Pinaceae, basal area of
grand fir was positively correlated with elevation (Table 4) and basal area of lodgepole
pine was positively correlated with plant available P (Table 4). Additionally, elevation and
total and plant available P were negatively correlated (Table 5).
EMF Communities
In total, we collected 1724 root tips, 1186 from Pinaceae trees, 384 from
chinquapin and 154 from unidentified trees and shrubs (Table 6). Of the 787 mycorrhizal
root tips assigned to a taxon, 77% (603/787) were Pineaceae roots and 23% (184/787) were
chinquapin roots (Table 6). In all but one pair of transects, a greater number of Pineaceae
root tips were found than chinquapin root tips.
Ninety-nine consensus sequences were assembled from 762 sequence reads. An
additional 59 taxa were found only once throughout the study and could not be assigned to
a consensus sequence but were of identifiable quality. Pinaceae hosts and chinquapin
shared 23 EMF taxa (Table 7 and Fig. 4); a greater number of taxa asssociated only with
Pinaceae hosts than only with chinquapin (Table 8). Overall, 92% of the detected EMF
taxa were associated with Pinaceae hosts and 23% were associated with chinquapin (Table
9) (See Appendix A, Table S1 for taxa list).
EMF Community Comparisons
The rarefaction analysis showed that there would be a significant difference in the
EMF community richness between Pinaceae and chinquapin if sample size had been equal
and if fungal identification rate had been ≥ 55% for Pinaceae root tips and ≥ 60% for
chinquapin root tips (Fig. 7). When compared with a Blocked Multi-Response Permutation
Procedure (PC-ORD v.6) the EMF communities found on Pinaceae roots and chinquapin
roots were slightly more different than would be expected by chance (A= 0.07, p =
44
0.0001). However, the effect value (A statistic) is so low as to make this test relatively
meaningless (McCune and Grace 2002).
Basidiomycetes comprised the majority of the EMF community on both Pinaceae
and chinquapin hosts (Fig. 8). At the transect pair level, on average, significantly more
basidiomycetes than ascomycetes associated with both host groups (Pinaceae: paired t-test,
t = -9.3, df = 15, p < 0.001, chinquapin: paired t-test, t = -2.8, df = 15, p = 0.04). However,
as Figure 5 and the t-tests show, the difference in occurence between ascomycetes and
basidiomycetes is much greater in Pinaceae than in chinquapin.
The Pinaceae and chinquapin EMF communities were dominated by Cenococcum
geophilum 1, which occurred on Pinaceae in all pairs of transects (Fig. 9). Piloderma 2, the
second most dominant EMF on chinquapin, occurred on Pinaceae hosts in a similar
number of transect pairs (Fig. 9). The dominant taxa, those that occur on either host group
in 31% (5/16) or more transect pairs, are shown in Figure 9.
The EMF communities on chinquapin and Pinaceae hosts were both relatively
diverse with an average Shannon’s Diversity of 1.7 (±0.5 SD) for chinquapin and 2.9 (±0.3
SD) for Pinaceae per transect pair. However, the majority of taxa found on Pinaceae and
chinquapin were rare, with more than half of each respective community being found in
fewer than five transect pairs (Fig. 10).
EMF Communities & Environmental Variables
Pinaceae EMF species richness and Shannon’s diversity were not well correlated
with any of the measured environmental variables (Appendix A, correlation table S4).
However, Pinaceae EMF richness and Shannon’s diversity were positively correlated with
the number of Pinaceae root tips collected and negatively correlated with the number of
chinquapin root tips collected (Table 10). Similarly, species richness and Shannon’s
diversity for chinquapin EMF were positively correlated with the number of chinquapin
root tips collected and negatively correlated with the number of Pinaceae root tips
collected (Table 11). Additionally, the number of taxa shared by Pinaceae hosts and
45
chinquapin per transect pair ranged from 1 to 5 and did not correlate well with any of the
measured environmental variables (Appendix A, correlation table S2).
Non-metric Multidimensional Scaling (NMDS) of the Pinaceae EMF community
indicated that a three-dimensional solution best represented the data, with a minimum
stress of 18.8 after 127 iterations. The final solution passed the Monte Carlo randomization
test (Monte Carlo, 200 random runs, p = 0.02). Axes 1, 2, and 3, accounted for 29.9%,
19.2%, and 18.6% of the variation respectively (Fig. 11a). The bi-plot overlays show
variables with a significance of r2 ≥ 18% that are affecting the distribution of the EMF
taxa. A three-dimensional solution, with a minimum stress of 16.1 after 88 iterations, also
best represented the chinquapin EMF community. The final solution passed the Monte
Carlo randomization test (Monte Carlo, 200 random runs, p = 0.02). Axes 1, 2, and 3,
accounted for 23.5%, 18.4%, and 32.7% of the variation respectively (Fig. 11b). The biplot overlays show variables with a significance of r2 ≥ 15% that are affecting the
distribution of the EMF taxa.
In the case of Pinacaee EMF total phosphorus had the greatest effect, whereas for
the chinquapin EMF community Bray (plant available) phosphorus was most important.
However, in both ordinations, the majority of the shared dominant taxa were present in
areas of lower relative phosphorus (Fig. 11ab).
Discussion
Despite preferentially sampling beneath chinquapin shrubs we found a greater
abundance of Pinaceae root tips than chinquapin root tips overall (Table 6). Sampling to a
depth of 10cm in forests east of the Cascade Mountain Range in Oregon has typically
yielded abundant Pinaceae root tips (Smith et al. 2004; 2005; Garcia et al. in press).
However, deeper sampling of the soil profile may have resulted in greater numbers of
chinquapin roots. Lopez et al. (2001) found that in a Mediterranean Quercus ilex L. forest
with hot, dry summers, fine root numbers measured for each 10cm interval to a depth of 60
46
cm tended to decrease with increasing depth but were greater in the 10-20 cm stratum than
between 0 and 10cm.
Unexpectedly, there appeared to be a negative relationship between pH and Bray P,
however, the trend is likely influenced by one data point of very low pH (see Appendix B
Fig. S2) and thus the possibility of this relationship should be further investigated. In
general, P decreased with increasing elevation and this relathionship is likely linked with
the vegetative communities and carbon cycling. Volcanically influenced soils tend to easily
bind P sources, however soil organic matter (SOM) also binds to soil particles and can act
as a buffer, freeing more P (Anderegg and Naylor 1988). Certain volcanic soils can
preferentially bind P over SOM (Appelt et al. 1975), however the slight decrease in soil C
with increasing elevation and increase with increasing plant available P on Lookout
Mountain would suggest that it is acting as a buffer and making phosphorus more
available.
EMF Community & Soil Nutrients
Total P and plant available P influenced the fungal communities of Pinaceae hosts
and chinquapin, respectively (Fig. 11). The most frequently found shared fungi,
Byssocorticium 1, Cenoccocum geophilum 1 and 2, and Piloderma 2 were all found more
frequently in mid to low P areas except for C. geophilum 1 (Fig. 11). Piloderma species
have been linked with improved host P nutrition (Jongmans and van Breeman 1997;
Tuason and Arocena 2009). Jongmans and van Breeman (1997) found evidence that a
Piloderma species was directly impacting plant inorganic P nutrition via dissolution of soil
rocks and rock fragments. Further, Tuason and Arocena (2009) found that Piloderma
fallax (Lib.) Stalpers produced increased amounts of oxalate when grown in a P limited
culture. In addition to improving access to P, mat-forming Piloderma species have been
found to improve nitrogen nutrition in Douglas-fir forests (Kluber et al. 2010; 2011;
Phillips et al. 2012; Zeglin et al. 2012). It is likely therefore, that their prevalence in low P
47
locations for Pinaceae and chinquapin hosts is due to preferential carbon allocation from
the host in exchange for improved P and possibly, N uptake.
The dominant strains Cenococcum geophilum 1 and 2 are likely important for soil
water uptake specifically as it has been well documented that C. geophilum is prevalent in
dry environments (Pigott 1982; Buée et al. 2005) where it improves host survival by
increasing host plant water potential (Hasselquist et al. 2005). Byssocorticium 1 may also
be assisting in plant water uptake. Shi et al. (2002) found that Byssocorticium atrovirens
was abundant on Fagus sylvatica L. across five ecotypes in Italy, independent of drought
status. Whereas this finding does not confirm that Byssocorticium was helpful to its hosts
in more extreme drought areas, it does suggest that Byssocorticium taxa show
environmental plasticity and a certain tolerance for water stress.
We did not see a response in the EMF community to the local N gradient.
However, Lilleskov et al. (2002) found that excessively high levels of soil nitrogen, which
can be caused by deposition from industry, can decrease EMF diversity (Lilleskov et al.
2002). Our local N gradient ranged from 3 to 29 mg/kg, whereas Lilleskov et al. (2002)
investigated a mineral N gradient of 13 to 243 mg/kg. The comparatively small N gradient
on Lookout Mountain was likely the reason we did not see an EMF response.
EMF Community Comparisons
Nine taxa (Byssocorticium 1, Cenococccum geophilum 1, 2, and 3, Cortinarius 13,
Elaphomyces 1, Hygrophorus 1, Inocybe 1, and Piloderma 2) associated with giant
chinquapin in five or more transect pairs were considered dominant. With the exception of
Elaphomyces 1 and Inocybe 1, these taxa also associated with Pinaceae hosts in our study.
However, Elaphomyces and Inocybe have been found in association with ponderosa pine
and Douglas-fir (Barroetaveña et al. 2007) and are likely not unique to chinquapin in our
study area.
Eleven infrequently detected taxa (representing: Cortinarius, Hygrophorus,
Hysterangium, Inocybe, Melanogaster, and Tomentella) associated with giant chinquapin
48
were not found with Pinaceae hosts. However, it is unlikely they are unique to chinquapin
as they all have been found associated with ponderosa pine and Douglas-fir (Barroetaveña
et al. 2007). Generally EMF distribution is patchy (Horton and Bruns 2001; Korkama et al.
2006), suggesting that the presence of chinquapin contributes to maintaining EMF
diversity in our central Oregon site.
Cenococcum geophilum 3, was found more often on chinquapin roots than on
Pinaceae roots (5 transect pairs vs. 1 transect pair) despite the discrepancy in sample size.
This apparent difference in association may be because fewer fungi associated with
chinquapin, which led to greater opportunity for a less competitive strain of C. geophilum
to gain a foothold, or because of a slight preference of this strain for chinquapin roots over
Pinaceae roots. Given the small sample size and observational nature of this study, further
research would be needed to test these hypotheses.
Eighty-four percent (122/145) of taxa found on Pinaceae hosts, but not on
chinquapin (See Appendix A, table S1 for taxa lists), comprised 13 genera: Gautieria,
Leucogaster, Leucophleps, Lyophyllum, Phellodon, Phialocephala, Pseudotomentella,
Rhizopogon, Sistotrema, Suillus, Tomentellopsis, Tricholoma, and Wilcoxina that are
known to associate with Pinaceae hosts (Table 1) (Jumpponen and Trappe 1998).
Rhizopogon and Suillus are generally restricted to hosts in the Pinaceae so their absence
from the chinquapin community was expected (Molina and Trappe 1982a; Molina et al.
1992; Molina and Trappe 1994, Bruns et al. 2002a). The remaining fungal genera have
been found associated with roots of tree genera with close phylogenetic relationships to
chinquapin (Manos et al. 2008; Oh and Manos 2008) and are displayed in Table 1 (Fogel
1979; Walker 2003; Dickie et al. 2009; Jumponnen et al. 2010); or in the case of
Leucogaster, found fruiting in a mixed Pinus-Quercus forest in Mexico (Cázares et al.
1992). With greater sampling effort these genera may have been detected on chinquapin.
The EMF community associated with Pinaceae hosts was 75% more species rich
(Fig. 7) and more diverse (Shannon’s Diversity) than the chinquapin EMF community.
This difference in richness and diversity is likely due to finding more Pinaceae root tips
than chinquapin root tips, but may partially be because more host-specialist fungi associate
49
with species in the Pinaceae than with chinquapin and because we sampled from multiple
host species in the Pinaceae.
A total of 23 shared taxa associated with chinquapin and Pinaceae hosts (Fig. 6).
These taxa represent 64% of the chinquapin EMF community, but only 16% of the
Pinaceae EMF community. The majority of the taxa associated with chinquapin also
associated with Pinaceae hosts suggesting that further sampling of chinquapin roots would
likely show an increase in the number of shared taxa. However, an increase in shared taxa
may not occur if further sampling included Pinaceae roots, as the Pinaceae EMF species
rarefaction curve indicated that the community was not entirely sampled. The most
frequently found taxa occurred on both Pinaceae and chinquapin hosts, but these common
taxa were often found on fewer transect pairs when associated with chinquapin. These
results show that chinquapin maintains a sub-set of the EMF community associated with
Pinaceae trees, including several fungi important for improved water uptake and P
nutrition.
EMF & Fire
EMF are an important component of the forest recovery process after fire (Baar et
al. 1999; Bruns et al. 2002b). Different methods of EMF recolonization after burns likely
exert influence on post burn EMF community structure and complexity. Baar et al. (1999)
found that fungal taxa, such as Rhizopogon species, with resistant spores or propagules in
the soil profile were the most abundant after stand replacing wildfire in a Pinus muricata
D. Don forest on the California coast. Similarly, early stage colonizers like Hebeloma
(Deacon and Flemming 1992) were found in a post-burn area and likely recolonized by
airborne spores (Baar et al. 1999). Additionally, fungi already present on mature hosts can
recolonize a site via mycelial spread or spores from fruiting bodies formed next to the
mature host, which can be important for the retention and spread of complex EMF
communities (Krannabetter et al. 1999). Vegetative spread of fungi from mature hosts to
regenerating seedlings presents the possibility for the formation of common mycorrhizal
50
networks, which can improve plant survival due to water (Bingham and Simard 2011) and
nutrient transfer (Simard et al. 1997a; Teste and Simard 2009). Retaining diverse EMF
communities throughout a potential burn site via fire resistant ectomycorrhizal forming
hosts could be beneficial to the long-term maintenance of plant communities.
A shrubby, sprouting, fire-resistant ectomycorrhizal forming birch (Betula nana
L.), was able to retain a viable EMF community after fire in Arctic tundra (Hewitt et al.
2013). Hewitt et al. (2013) found similar EMF communities on sites with un-burned shrubs
and sites with shrubs that had resprouted after burning. They concluded, based on the
typically late-stage nature of the dominant EMF species detected (Russula, Lactarius,
Inocybe), that the EMF had been maintained in a mycelial state through the fire (Hewitt et
al. 2013). Similarly, Horton et al. (1999) showed that fungi forming arbutoid mycorrhizae
with the shrub species manzanita (Arctostaphlos uva-ursi) assisted in establishment in
Douglas-fir seedlings in Chaparral communities in central California. Further, as found by
Hagerman et al. (2001), the maintenance of diverse mycorrhizal community by manzanita
three years after overstory removal is strong evidence supporting the idea that an
understory species could serve as an EMF refuge plant after disturbance to the overstory.
As a stump and root sprouter, chinquapin is highly resilient to fire (McKee 1990;
Kauffman and Martin 1990), and can re-sprout even after repeated severe burns (Donato et
al. 2009). This ability to retain live roots may mean that it is capable of maintaining EMF
partners after fire despite the temporary halting of photosynthetic C flowing to the roots.
Bauhus (1994, cited in Bauhus and Bartsch 1996) found that two years after cutting, Fagus
sylvatica L. stumps maintained live fine roots.
Limitations & Future Directions
This observational study provides important insight into the EMF of a poorly
investigated ectomycorrhizal host on one mountain in central Oregon. The PFEF is
representative of many forests in central Oregon and these results can be cautiously applied
to different situations and conditions. We now have a glimpse of the EMF community
51
associated with chinquapin and its relation to Pinaceae EMF communities, but there is
likely much left to learn and further studies investigating this topic in different locations
and environments would be beneficial. Additionally, investigations of the chinquapin EMF
after fire or clearing could further elucidate if chinquapin can serve as an EMF refuge plant
and innoculum source for Pinaceae seedlings after disturbance.
Conclusions & Implications
Pinaceae hosts and chinquapin maintain a similar EMF community that is
dominated by fungi known to improve plant nutrition (Jongmans 1997; Tuason and
Arocena 2009; Kluber et al. 2011) and survival under moisture stress (Hasselquist et al.
2005). This information is important for management decisions regarding forests
comprised of these trees in central Oregon, as chinquapin is often controlled to reduce fire
risks and competition for the more economically valuable pine species (Barrett et al. 1983).
Although competition by understory shrubs is a valid concern (Busse et al. 1996; Zhang et
al. 2006), chinquapin could factor into maintaining the health of Pinaceae-dominated
forests in several ways. Keys and Maguire (2005) synthesized results from three studies
and concluded that initial shrub cover in ponderosa pine stands facilitates pine germinant
survival for the first one or two summers. Additionally, because chinquapin is a root and
stump sprouting species (Barrett et al. 1983; McKee 1990) and associates with many of the
dominant EMF taxa found with Pinaceae hosts, it could play a vital role as a refuge plant
in keeping a remnant EMF community in place after disturbances such as fire, harvest
damage, or removal of overstory Pinaceae. Considering the similarities found between the
EMF communities on chinquapin and the associated Pinaceae overstory, an investigation
to identify if chinquapin could maintain a diverse EMF community (including key players
such as C. geophilum and Piloderma sp.) and be able to function as a source of fungal
innoculum for future Pinaceae seedlings after disturbance, would be beneficial.
52
http://0.tqn.com/d/gonw/1/0/U/w/- / - /oregonstatetopo.gif
Figure 1. Study area overview and design. a) Oregon Map, Blue square = Lookout Mountain area; b) Lookout
Mountain study area, Yellow squares = EMF sampling areas; c) Study transect pair diagram, Blue/shaded circles =
soil moisture tube approximate locations. Central circle = overstory vegetation survey area.
53
Figure 2. Lookout Mountain study area. Yellow squares = Location of vegetation plots and
transect pairs where soil moisture and EMF were sampled.
54
Pinus ponderosa
Tree Species
Pinus monticola
Pinus contorta
Abies magnifica
Abies grandis
0
20
40
60
Basal Area (m / ha)
Figure 3. Box and whisker plot of basal area (m2/ha) of overstory Pinaceae trees, where the
upper and lower hinges of box = 1st and 3rd quartiles of the data, the mid-box line = 2nd
quartile and the whiskers = 1.5* IQR (inter-quartile distance, the distance between the 1st
and 3rd quartile). Outliers are beyond the 1.5*IQR cutoff. When a box is defined by only
two data points the ends of the whiskers are the data points and the box is located mid-way
between them. Dot-plot overlay shows basal area per species per vegetation plot.
55
60
Basal Area (m2/ha) per Plot
Name
Abies grandis
Abies magnifica
Pinus contorta
40
Pinus monticola
Pinus ponderosa
Total BA
20
0
1400
1500
1600
1700
Elevation (m)
Figure 4. Basal area (m2/ha) of overstory Pinaceae trees per vegetation plot by elevation (m). (n = 14)
56
12_20 12_24 14_16
14_6
15_2
15_24
25_2
25_20 31_12 31_22
32_14
32_2
33_12 33_16
Pinus ponderosa
Species
Pinus monticola
Pinus contorta
Abies magnifica
Abies grandis
0 204060 0 204060 0 204060 0 204060 0 204060 0 204060 0 204060 0 204060 0 204060 0 204060 0 204060 0 204060 0 204060 0 204060
Basal Area (m /ha)
Figure 5. Pinaceae basal area (m2/ha) per vegetation plot (excepting those in plots 11_18 and 11_20)
57
Table 2. Environmental variable measurements averaged across 16 study transect pairs.
Means are listed with standard deviations in parentheses.
Elevation (m)
Aspect (º)
pH
Vol. Water (m3/m3)
Bray P (mg/kg)
Total P (mg/kg)
Mineralizable N (mg/kg)
Total C (%)
Total N (%)
Root Biomass (g)
Chinquapin Cover (%)
Average
1553 (94.6)
102.9 (31.4)
5.76 (0.21)
0.042 (0.018)
19.82 (2.05)
922.94 (149.81)
10.98 (7.12)
3.47 (1.21)
0.08 (0.03)
0.20 (0.05)
Minimum
1401
68.43
5.16
0.001
15.38
712.41
3.1
1.74
0.03
0.15
Maximum
1703
186.1
6.04
0.073
40.88
1333.35
28.64
5.38
0.14
0.3
44.2 (24.0)
1.5
85.2
Dates
Collected
7-8/2012
7-8/2012
7-8/2012
7-8/2012
7-8/2012
7-8/2012
7-8/2012
7-8/2012
7-8/2011 or
7-9/2012
Table 3. Spearman ranked correlation coefficient (ρ) of pH correlated with chinquapin
percent cover (Plots in Appendix B). Bold = relationship strong enough to merit attention.
pH
Chinquapin % Cover
0.51
Table 4. Spearman ranked correlation coefficients (ρ) of environmental variables
correlated to Pinaceae basal area (m2/ha). (Plots in Appendix B). Bold = relationship
strong enough to merit attention.
Elevation (m)
Bray P (mg/kg)
Pinaceae EMF Richness
Pinaceae EMF Shannon’s Div.
Abies grandis
0.76
-0.26
-0.27
-0.27
Pinus contorta
-0.35
0.83
-0.52
-0.50
Pinus ponderosa
-0.01
-0.24
0.00
-0.03
58
Table 5. Spearman ranked correlation coefficients (ρ) for environmental variables
correlated with each other (Plots in Appendix B). Bold = relationship strong enough to
merit attention. See Appendix A table S2 for full table.
pH
Elevation (m)
Bray P (mg/kg)
Total P (mg/kg)
Mineralizable N (mg/kg)
Total C (%)
Total N (%)
pH
1.00
0.32
-0.50
0.06
-0.46
-0.32
-0.47
Avg. Vol. Water (m3/m3)
Pinaceae root tips
Chinquapin root tips
-0.08
0.26
0.11
Elevation
(m)
Bray P
(mg/kg)
Mineralizable N
(mg/kg)
Total C (%)
1.00
-0.72
-0.61
0.12
-0.46
-0.44
1.00
0.58
0.03
0.49
0.47
1.00
0.59
0.64
1.00
0.93
0.43
-0.33
0.26
-0.41
0.12
-0.21
0.66
-0.05
-0.28
0.24
0.13
-0.19
Table 6. Root tip success summary.
Pinaceae
Count
1186
603
Initial Sample
Final Output
Success Rate
%
69
77
51%
Chinquapin
Other
Total Tips
Count
384
184
Count
154
-
% Count
9
1724
787
46%
%
22
23
48%
Table 7. Count and percent of unique and shared fungal taxa found by host.
Pinaceae
Unique
Shared
Total
Count
122
23
145
Chinquapin
% of Total
84
16
100
Count
13
23
36
% of Total
36
64
100
Table 8. Count and percent of unique and shared fungal taxa.
Unique to Host
Shared
Total
Count
135
23
158
% of Total
85
15
100
59
Table 9. Count and percent of total fungal taxa found by host.
Pinaceae
Giant Chinquapin
Total
Count
145
36
158
% of Total
92
23
Taxa
60
Cenococcum geophilum 1
Byssocorticium 1
Cortinarius 1
Cenococcum geophilum 2
Piloderma 2
Piloderma 1
Russula 1
Cortinarius 4
Byssocorticium 2
Lactarius resimus
Cortinarius 5
Cortinarius laetissimus
Piloderma 5
Cortinarius 6
Piloderma olivaceum 2
Helotiales 1
Piloderma olivaceum 3
Helotiales 2
Cortinarius 12
Russula 3
Hygrophorus 1
Cenococcum geophilum 3
Cortinarius 13
Host
Pineaceae
Chinquapin
0
5
10
15
Frequency of taxa by transect pair
Figure 6. Taxa found on both Pinaceae hosts and giant chinquapin by frequency of occurrence on transect pairs.
200
200
150
150
Estimated Number of Taxa
Estimated Number of Taxa
61
100
100
50
50
0
0
4
8
Transect Pairs
12
16
4
8
Transect Pairs
12
16
Figure 7. Species rarefaction curves and 95% confidence intervals for a) Pinaceae (estimated from six transect pairs with a ≥ 55%
fungal identification rate), and b) chinquapin (estimated from five transect pairs with a ≥ 60% fungal identification rate)
0
5
Number of Taxa
10
15
20
25
62
Ascomycete
Basidiomycete
Ascomycete
Basidiomycete
Figure 8. Number of ascomycetes and basidiomycete taxa on transect pairs for a) Pinaceae (paired t-test, t=-9.3, df = 15, p < 0.001,
and b) chinquapin (paired t-test, t = -2.8, df = 15, p = 0.04). Boxplots represent the distribution of fungal taxa where the upper and
lower hinges of box = 1st and 3rd quartiles of the data, the mid-box line = 2nd quartile and the whiskers = 1.5* IQR (inter-quartile
distance, the distance between the 1st and 3rd quartile). Outliers are beyond the 1.5*IQR cutoff.
63
a.
b.
Cenococcum geophilum 1
Cenococcum geophilum 1
Byssocorticium 1
Piloderma 2
Cortinarius 1
Cenococcum geophilum 2
Inocybe 1
Wilcoxina rehmii
Hygrophorus 1
Taxa
Taxa
Piloderma 2
Sistotrema alboluteum
Russula 1
Rhizopogon salebrosus 1
Elaphomyces 1
Cortinarius 13
Rhizopogon ochraceorubens
Byssocorticium 1
Piloderma 1
Suillus tomentosus
Cenococcum geophilum 3
Cortinarius 4
Cenococcum geophilum 2
Cortinarius 3
0
5
10
Frequency of taxa by transect pair
15
0
5
10
15
Frequency of taxa by transect pair
Figure 9. Dominant EMF taxa or EMF taxa associated with a) Pinaceae and b) Chinquapin hosts that occurred on five or more
transect pairs. Filled arrows indicate shared dominant taxa. Clear arrows indicate shared taxa.
64
b.
Taxa
Taxa
a.
4
8
12
Frequency of taxa by transect pair
16
3
6
9
Frequency of taxa by transect pair
Figure 10. Frequencey of all EMF taxa found by transect pair for a) Pinaceae hosts and b) chinquapin
65
Table 10. Spearman ranked correlation coefficients (ρ) for Pinaceae EMF descriptors that
were correlated with environmental variables (Plots in Appendix B). Bold = relationship
strong enough to merit attention.
C tips
P tips
Richness
Shannon’s
Diversity
-0.5
0.88
-0.52
0.88
Table 11. Spearman ranked correlation coefficients (ρ) for Chinquapin EMF descriptors
that were correlated with environmental variables (Plots in Appendix B). Bold =
relationship strong enough to merit attention.
C tips
P tips
Richness
Shannon’s
Diversity
0.89
-0.68
0.89
-0.65
66
a.
b.
Cenococcum geophilum 2
Cenococcum geophilum 2
Total P
Cenococcum geophilum 1
Byssocorticium 1
Axis 3 (r = 32.7%)
Axis 3 (r = 18.6%)
Piloderma 2
Piloderma 2
Byssocorticium 1
Bray P
Cenococcum geophilum 1
Axis 2 (r =19.2%)
Axis 1 (r =23.5%)
Figure 11. NMDS showing EMF taxa in transect space. Triangles = dominant taxa shared by Pinaceae and chinquapin. Circles =
EMF taxa. a) Pinaceae EMF. Environmental variable shown as bi-plot overlay has r2 ≥ 20%. b) Chinquapin EMF. Environmental
variable shown as bi-plot overlay has r2 ≥ 15%.
67
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APPENDICES
89
Appendix A
Table S1. EMF taxa found on Lookout Mountain. Bold = only on chinquapin, Shaded = on chinquapin & Pinaceae
Consensus #
Taxa
GenBank Target Name
#ACN
Max ID
# of P
transect
pairs
# of C
transect
pairs
94
Agaricomycetes 1
Amphinema sp.
JN943925.1
94%
1
0
124
Agaricomycetes 2
Amphinema sp.
JN943925.1
90%
1
0
125
Agaricomycetes 3
Hydnum sp.
FN669208.1
94%
1
0
133
Agaricomycetes 4
Sistotrema sp.
KF218963.1
97%
1
0
47
Amanita aprica
Amanita aprica
KF561972.1
99%
1
0
153
Amanita pantherina
Amanita pantherina
EU525997.1
100%
1
0
121
Amphinema 1
Amphinema sp.
JN943898.1
99%
1
0
23
Amphinema byssoides
Amphinema byssoides
JQ711816.1
99%
3
0
135
Ascomycota 1
Ascomycota sp.
JQ711841.1
87%
0
1
98
Basidiomycete 1
Basidiomycete sp.
DQ365644.1
93%
1
0
6
Byssocorticium 1
Byssocorticium atrovirens
AJ889936.1
92%
10
6
21
Byssocorticium 2
Byssocorticium atrovirens
AJ889936.1
89%
4
4
1
Cenococcum geophilum 1
Cenococcum geophilum
JX145390.1
97%
16
11
5
Cenococcum geophilum 2
Cenococcum geophilum
JQ711896.1
99%
9
5
9
Cenococcum geophilum 3
Cenococcum geophilum
AY394919.1
99%
1
5
4
Cortinarius 1
Cortinarius hemitrichus
DQ097870.1
99%
9
2
90
Consensus #
Taxa
GenBank Target Name
#ACN
Max ID
# of P
transect
pairs
# of C
transect
pairs
81
Cortinarius 10
Cortinarius sp.
FN669181.1
95%
0
1
92
Cortinarius 11
Cortinarius cf biformis
HQ604700.1
99%
2
0
29
Cortinarius 12
Cortinarius fulvscens
GQ159914.1
99%
2
4
11
Cortinarius 13
Cortinarius acutus
GQ159881.1
100%
1
6
88
Cortinarius 14
Cortinarius fulvscens
HQ604731.1
96%
1
0
103
Cortinarius 15
Cortinarius sp.
GQ159878.1
89%
1
0
130
Cortinarius 16
Cortinarius caput-medusae
HQ845170.1
93%
0
1
142
Cortinarius 17
Cortinarius casimiri
HQ604719.1
98%
1
0
151
Cortinarius 18
Cortinarius sp.
FJ717589.1
99%
1
0
152
Cortinarius 19
Cortinarius obtusus
GQ159764.1
87%
1
0
59
Cortinarius 2
Cortinarius malachius
KJ705143.1
100%
2
0
154
Cortinarius 20
Cortinarius ferrugineovelatus
NR_131875.1
99%
1
0
158
Cortinarius 21
Cortinarius caput-medusae
HQ845170.1
95%
0
1
132
Cortinarius 22
Cortinarius sp.
FJ717527.1
97%
1
0
134
Cortinarius 23
Cortinarius casimiri
GQ159814.1
98%
1
0
22
Cortinarius 3
Cortinarius candelaris
GQ159883.1
99%
5
0
18
Cortinarius 4
Cortinarius acutovelatus
AY669655.1
99%
5
1
42
Cortinarius 5
Cortinarius sp.
GQ159878.1
99%
4
1
44
Cortinarius 6
Cortinarius casimiri
HQ604719.1
99%
3
2
91
Table S1. (Continued)
Consensus #
Taxa
GenBank Target Name
#ACN
Max ID
# of P
transect
pairs
# of C
transect
pairs
43
Cortinarius 7
Cortinarius colymbadinus
NR_131819.1
98%
2
0
86
Cortinarius 8
Cortinarius volvatus
NR_130287.1
99%
0
1
83
Cortinarius 9
Cortinarius sp.
EU821651.1
99%
1
0
99
Cortinarius acutus
Cortinarius acutus
FJ157002.1
98%
1
0
48
Cortinarius alboviolaceus
Cortinarius alboviolaceus
JF899552.1
99%
0
2
137
Cortinarius boulderensis
Cortinarius boulderensis
NR_121207.1
99%
1
0
77
Cortinarius clandestinus
Cortinarius clandestinus
GQ159862.1
99%
1
0
150
Cortinarius firmus
Cortinarius firmus
AF389163.1
99%
1
0
31
Cortinarius laetissimus
Cortinarius laetissimus
GQ159898.1
99%
3
1
93
Cortinarius limonius
Cortinarius limonius
GQ159869.1
99%
1
0
148
Cortinarius obtusus
Cortinarius obtusus
FJ717550.1
100%
1
0
24
Cortinarius pingue
Cortinarius pingue
GQ159874.1
99%
3
0
15
Elaphomyces 1
Elaphomyces sp.
JQ272414.1
97%
0
6
112
Gautieria 1
Gautieria sp.
AF377089.1
94%
1
0
45
Gautieria monticola 1
Gautieria monticola
AF377094.1
99%
2
0
34
Gautieria monticola 2
Gautieria monticola
AF377075.1
99%
2
0
73
Gautieria monticola 3
Gautieria monticola
AF377101.1
98%
1
0
19
Helotiales 1
Melinomyces sp.
KC007335.1
97%
2
3
92
Table S1. (Continued)
Consensus #
Taxa
GenBank Target Name
#ACN
Max ID
# of P
transect
pairs
# of C
transect
pairs
26
Helotiales 2
Melinomyces bicolor
AY394885.1
98%
2
2
101
Helotiales 3
Helotiales sp.
EU880594.1
99%
1
0
7
Hygrophorus 1
Hygrophorus persoonii
JF908067.1
91%
1
6
96
Hygrophorus 2
Hygrophorus persoonii
JF908067.1
87%
0
2
126
Hygrophorus 3
Hygrophorus unicolor
AY242857.1
87%
1
0
127
Hygrophorus aureus
Hygrophorus aureus
JF908076.1
97%
1
0
72
Hygrophorus cf subalpinus
Hygrophorus cf subalpinus
JN021041.1
99%
1
0
89
Hygrophorus purpurascens
Hygrophorus purpurascens
HQ650731.1
99%
1
0
140
Hysterangium separabile
Hysterangium separabile
EU563921.1
98%
0
1
20
Inocybe 1
Inocybe flocculosa var. flocculosa
HQ604185.1
99%
0
6
49
Inocybe 2
Inocybe albietis
HQ604165.1
99%
1
0
97
Inocybe 3
Inocybe nitidiuscula
HQ604085.1
82%
0
1
100
Inocybe 4
Inocybe flocculosa var. flocculosa
HQ604084.1
97%
1
0
116
Inocybe 5
Inocybe nitidiuscula
HQ604260.1
90%
1
0
149
Inocybe 6
Inocybe pupureobadia
JN580875.1
94%
1
0
107
Inocybe silvae-herbaceae
Inocybe silvae-herbaceae
NR_119991.1
99%
1
0
108
Lactarius 1
Lactarius deliciosus
JQ711835.1
94%
1
0
157
Lactarius 2
Lactarius deliciosus
JQ711835.1
92%
1
0
93
Table S1. (Continued)
Consensus #
Taxa
GenBank Target Name
#ACN
Max ID
# of P
transect
pairs
# of C
transect
pairs
50
Lactarius deliciosus
Lactarius deliciosus var. deterrimus
EF685051.1
99%
3
0
8
Lactarius resimus
Lactarius resimus
JF899563.1
99%
4
1
37
Lactarius rufus
Lactarius rufus
JQ712001.1
99%
1
0
51
Lactarius xanthogalactus
Lactarius xanthogalactus
EU726293.1
99%
1
0
114
Leucogaster 1
Leucogaster microsporus
EU846312.1
91%
1
0
67
Leucophleps 1
Leucophleps spinispora
AY621788.1
79%
2
0
63
Leucophleps 2
Leucophleps spinispora
AY621775.1
79%
2
0
80
Leucophleps 3
Leucophleps spinispora
AY621784.1
76%
1
0
129
Leucophleps 4
Leucophleps spinispora
AY621796.1
80%
1
0
64
Leucophleps spinispora
AY621764.1
99%
3
0
102
Lyophyllum 1
Leucophleps spinispora
Lyophyllum semitale var.
intermedium
KP192604.1
99%
1
0
74
Melanogaster 1
Melanogaster sp.
KC152159.1
96%
2
0
106
Melanogaster 2
Melanogaster intermedius
EU784372.1
82%
0
1
91
Pezizaceae 1
Sarcosphaera coronaria
DQ200843.1
89%
2
0
87
Phellodon melaleucus
Phellodon melaleucus
AY228355.1
99%
1
0
110
Phialocephala 1
Phialocephala cf. fortinii
KM460828.1
99%
1
0
111
Phialocephala 2
Phialocephala sp.
JX243870.1
94%
2
0
105
Phialocephala 3
Phialocephala sp.
KJ542273.1
94%
1
0
94
Table S1. (Continued)
Consensus #
Taxa
GenBank Target Name
#ACN
Max ID
# of P
transect
pairs
# of C
transect
pairs
60
Phialocephala fortinii 1
Phialocephala fortinii
KJ817278.1
98%
4
0
131
Phialocephala fortinii 2
Phialocephala fortinii
KF850367.1
99%
1
0
10
Piloderma 1
Piloderma olivaceum
JQ11915.1
93%
6
2
155
Piloderma 10
Piloderma olivaceum
JQ711915.1
87%
1
0
2
Piloderma 2
Piloderma sp.
JQ711935.1
99%
7
8
69
Piloderma 3
Piloderma sp.
JQ711984.1
88%
1
0
85
Piloderma 4
Piloderma sp.
FN669236.1
90%
2
0
40
Piloderma 5
Piloderma olivaceum
JQ711802.1
88%
3
1
58
Piloderma 6
Piloderma olivaceum
JQ711915.1
93%
3
0
68
Piloderma 7
Piloderma sp.
JQ711984.1
96%
2
0
136
Piloderma 8
Piloderma sp.
JQ711951.1
90%
1
0
138
Piloderma 9
Piloderma fallax
DQ365665.1
93%
1
0
70
Piloderma byssinum 1
Piloderma byssinum
KF359605.1
99%
2
0
95
Piloderma byssinum 2
Piloderma byssinum
DQ365683.1
100%
1
0
25
Piloderma lanatum
Piloderma lanatum
JQ711873.1
99%
4
0
41
Piloderma olivaceum 1
Piloderma olivaceum
JQ11915.1
97%
3
0
57
Piloderma olivaceum 2
Piloderma olivaceum
JQ711901.1
99%
3
1
30
Piloderma olivaceum 3
Piloderma olivaceum 3
JQ11924.1
99%
2
2
95
Table S1. (Continued)
Consensus #
Taxa
GenBank Target Name
#ACN
Max ID
# of P
transect
pairs
# of C
transect
pairs
118
Pseudotomentella 1
Pseudotomentella sp.
AB848560.1
88%
1
0
141
Pseudotomentella nigra
Pseudotomentella nigra
AF274770.1
98%
1
0
76
Ramaria 1
Ramaria sp.
EU444537.1
94%
2
0
90
Ramaria 2
Ramaria sp.
DQ365606.1
99%
1
0
147
Ramaria 3
Ramaria sp.
DQ365629.1
99%
1
0
62
Ramaria largentii
Ramaria largentii
EU652343.1
99%
1
0
27
Rhizopogon 1
Rhizopogon evadens
KJ595006.1
99%
4
0
28
Rhizopogon 2
Rhizopogon luteorubescens
GQ267482.1
99%
3
0
113
Rhizopogon 3
Rhizopogon bacillisporus
EU837230.1
84%
1
0
120
Rhizopogon 4
Rhizopogon luteorubescens
GQ267482.1
87%
1
0
122
Rhizopogon 5
Russula sp.
EF458016.1
95%
1
0
128
Rhizopogon 6
Rhizopogon sp.
DQ680181.1
96%
1
0
146
Rhizopogon 7
Rhizopogon roseolus
AJ810045.1
87%
1
0
36
Rhizopogon arctostaphyli
Rhizopogon arctostaphyli
NR_121275.1
99%
4
0
14
Rhizopogon ochraceorubens
Rhizopogon ochraceorubens
AF062928.1
99%
6
0
17
Rhizopogon salebrosus 1
Rhizopogon salebrosus
KC170128.1
98%
6
0
38
Rhizopogon salebrosus 2
Rhizopogon salebrosus
HQ914265.1
99%
2
0
3
Russula 1
Russula aff. subsect. Nigricantinae
JX030254.1
99%
6
1
96
Table S1. (Continued)
Consensus #
Taxa
GenBank Target Name
#ACN
Max ID
# of P
transect
pairs
# of C
transect
pairs
39
Russula 2
Russula nigricans
DQ367915.1
99%
2
0
71
Russula 3
Russula ochraceorivulosa
JQ902087.1
85%
2
1
66
Russula cascadensis
Russula cascadensis
EU526006.1
99%
1
0
16
Russula tenuiceps
Russula tenuiceps
DQ974756.1
99%
2
0
12
Russula turci
Russula turci
JQ11969.1
98%
3
0
145
Sebacina 1
Sebacina vermifera
JQ711842.1
96%
1
0
79
Sebacina vermifera
Sebacina vermifera
JQ711843.1
98%
2
0
46
Sistotrema 1
Sistotrema pistilliferum
KF218964.1
96%
3
0
32
Sistotrema 2
Sistotrema sp.
FN669255.1
95%
1
0
13
Sistotrema alboluteum
Sistotrema alboluteum
AJ606043.2
98%
6
0
78
Suillus 1
Suillus sp.
JQ711888.1
98%
1
0
139
Suillus 2
Suillus variegatus
JX907819.1
95%
1
0
75
Suillus placidus
Suillus placidus
KM882921.1
98%
2
0
35
Suillus tomentosus
Suillus tomentosus
FJ845441.1
99%
5
0
56
Thelephora terrestris
Thelephora terrestris
HM189958.1
99%
1
0
115
Thelephoraceaea 1
Thelephoraceae sp.
JX243818.1
73%
2
0
54
Tomentella 1
Tomentella sp.
JQ711794.1
99%
2
0
53
Tomentella 2
Tomentella bryophila
JQ711917.1
95%
2
0
97
Table S1. (Continued)
Consensus #
Taxa
GenBank Target Name
#ACN
Max ID
# of P
transect
pairs
# of C
transect
pairs
55
Tomentella 3
Tomentella badia
JQ711987.1
98%
3
0
52
Tomentella 4
Tomentella sp.
U92537.1
99%
2
0
65
Tomentella 5
Tomentella ramosissima
JX129141.1
97%
1
0
104
Tomentella 6
Tomentella sp.
AJ534914.1
95%
1
0
119
Tomentella 7
Tomentella bryophila
JQ711917.1
95%
1
0
143
Tomentella atramentaria
Tomentella atramentaria
DQ974772.1
98%
0
1
123
Tomentella bryophila
Tomentella bryophila
JQ711917.1
99%
1
0
109
Tomentellopsis 1
Tomentellopsis zygodesmoides
AJ410761.1
96%
1
0
144
Tomentellopsis submollis
Tomentellopsis submollis
JQ711898.1
98%
1
0
61
Tricholoma 1
Tricholoma myomyces
JN389299.1
99%
1
0
84
Tricholoma 2
Tricholoma equestre
HM590873.1
93%
1
0
117
Tricholoma 3
AF458435.1
99%
1
0
156
Tricholoma 4
Tricholoma ustale
Tricholoma saponaceum var.
saponaceum
DQ370440.1
86%
1
0
82
Tricholoma focale
Tricholoma focale
DQ367920.1
99%
2
0
33
Wilcoxina rehmii
Wilcoxina rehmii
AF266708.1
99%
8
0
98
Table S2. Full Spearman ranked correlation (ρ) tables of environmental variables correlated with each other (n=16). Bold =
relationships strong enough to merit attention, values presented in Results section.
pH
pH
Elevation (m)
Aspect (º)
Bray P (mg/kg)
Total P (mg/kg)
Mineralizable N
(mg/kg)
Incubation N (mg/kg)
%C
%N
Root Biomass (g)
Chinq. % Cover
Avg. Vol. Water
(m3/m3)
Shared EMF (count)
Chinq. Root tips
Pina. Root tips
Basal Area/plot
-0.5
-0.72
-0.28
1
0.58
Total P
(mg/kg)
0.06
-0.61
-0.13
0.58
1
Mineralizable N
(mg/kg)
-0.46
0.12
0.46
0.03
-0.21
Incubation N
(mg/kg)
-0.42
0.16
0.48
-0.01
-0.26
0.46
0.48
0.19
0.11
0.38
-0.43
0.03
-0.01
0.49
0.47
-0.11
-0.34
-0.21
-0.26
0.32
0.22
0.21
-0.17
1
0.98
0.59
0.64
-0.22
-0.37
0.98
1
0.62
0.65
-0.28
-0.31
0.38
0.11
-0.08
0.17
0.24
-0.41
0.09
-0.21
0.12
-0.36
-0.29
0.08
0.09
0.2
-0.25
0.66
-0.09
-0.28
-0.05
0.18
0.66
0.03
-0.19
-0.1
0.17
1
0.32
-0.19
-0.5
0.06
Elevation (m)
0.32
1
0.24
-0.72
-0.61
Aspect (º)
-0.19
0.24
1
-0.28
-0.13
-0.46
-0.42
-0.32
-0.47
0.2
0.51
0.12
0.16
-0.46
-0.44
0.01
0.3
-0.08
0.06
0.11
0.26
0.09
0.43
0.07
0.26
-0.33
0.38
Bray P
(mg/kg)
99
Table S2. (Continued)
Avg. Vol.
Water
(m3/m3)
-0.08
0.43
0.38
-0.41
-0.29
Shared
EMF
(count)
-0.32
-0.46
0.19
0.49
0.32
-0.47
-0.44
0.11
0.47
0.22
0.2
0.01
0.38
-0.11
0.21
Chinq. %
Cover
0.51
0.3
-0.43
-0.34
-0.17
0.59
0.62
1
0.93
-0.23
-0.25
0.64
0.65
0.93
1
-0.42
-0.28
-0.22
-0.28
-0.23
-0.42
1
0.12
-0.37
-0.31
-0.25
-0.28
0.12
1
0.66
0.66
0.24
0.25
0.08
0.05
-0.09
0.03
0.04
0.09
-0.22
0.09
-0.28
-0.19
-0.19
-0.13
-0.29
0.38
-0.05
-0.1
0.13
-0.01
0.28
-0.38
0.18
0.17
0.12
0.09
0.02
0.16
0.24
0.04
-0.19
0.13
0.12
0.25
0.09
-0.13
-0.01
0.09
0.08
-0.22
-0.29
0.28
0.02
0.05
0.09
0.38
-0.38
0.16
1
-0.05
-0.08
-0.18
0.17
-0.05
1
0.47
-0.14
-0.22
-0.08
0.47
1
-0.7
0.05
-0.18
-0.14
-0.7
1
0.04
0.17
-0.22
0.05
0.04
1
%C
pH
Elevation (m)
Aspect (º)
Bray P (mg/kg)
Total P (mg/kg)
Mineralizable N
(mg/kg)
Incubation N (mg/kg)
%C
%N
Root Biomass (g)
Chinq. % Cover
Avg. Vol. Water
(m3/m3)
Shared EMF (count)
Chinq. Root tips
Pina. Root tips
Basal Area/plot
Root
Biomass
(g)
%N
0.06
0.07
0.11
0.09
0.08
Chinq. root
tips
0.11
0.26
-0.08
-0.21
0.09
Pine root
tips
0.26
-0.33
0.17
0.12
0.2
Basal
Area/plot
0.09
0.38
0.24
-0.36
-0.25
100
Table S3. Spearman ranked correlation coefficients (ρ) for comparing environmental variables to chinquapin EMF variables (n =
16). Bold = relationships strong enough to merit attention, values presented in Results section.
Richness
Shannons Div.
Simpsons Div.
Chinq. Root tips
Pine Root tips
Basal Area/plot
pH
0.16
0.15
0.09
0.11
0.26
0.09
Elevation
(m)
0.36
0.3
0.2
0.26
-0.33
0.38
Aspect (º)
-0.18
-0.2
-0.21
-0.08
0.17
0.24
Bray P
(mg/kg)
-0.12
-0.07
0.01
-0.21
0.12
-0.36
Total P
(mg/kg)
0.07
0.12
0.15
0.09
0.2
-0.25
Mineralizable N
(mg/kg)
-0.28
-0.18
-0.04
-0.28
-0.05
0.18
Incubation N
(mg/kg)
-0.2
-0.1
0.02
-0.19
-0.1
0.17
%C
-0.27
-0.12
0.05
-0.19
0.13
0.12
Table S3. (Continued)
Richness
Shannon’s
Div.
Simpson’s
Div.
Chinq. Root
tips
Pine Root tips
Basal
Area/plot
%N
-0.16
Root
Biomass
(g)
-0.34
Chinq. %
Cover
0.34
Avg. Vol.
Water
(m3/m3)
-0.09
-0.03
-0.44
0.28
0.13
-0.55
-0.13
-0.01
0.09
1
Shannon’s
Div.
0.95
Simpson’s
Div.
0.82
Chinq.
Root tips
0.89
Pine
Root tips
-0.68
Basal
Area/plot
-0.03
-0.02
0.95
1
0.95
0.89
-0.65
-0.05
0.13
0.04
0.82
0.95
1
0.78
-0.58
-0.08
-0.29
0.28
0.38
-0.38
-0.08
-0.18
0.89
-0.68
0.89
-0.65
0.78
-0.58
1
-0.7
-0.7
1
0.05
0.04
0.02
0.16
0.17
-0.03
-0.05
-0.08
0.05
0.04
1
Richness
101
Table S4. Spearman ranked correlation coefficients (ρ) for comparing environmental variables to Pinaceae EMF variables (n = 16).
Bold = relationships strong enough to merit attention, values presented in Results section.
Richness
Shannon’s Div.
Simpson’s Div.
Chinq. Root tips
Pine Root tips
Basal Area/plot
pH
0.28
0.24
0.19
0.11
0.26
0.09
Elevation
(m)
-0.33
-0.34
-0.36
0.26
-0.33
0.38
Aspect (º)
0.25
0.22
0.2
-0.08
0.17
0.24
Bray P
(mg/kg)
-0.08
-0.03
0.02
-0.21
0.12
-0.36
Total P
(mg/kg)
0.16
0.14
0.12
0.09
0.2
-0.25
Mineralizable N
(mg/kg)
-0.06
-0.02
0.01
-0.28
-0.05
0.18
Incubation N
(mg/kg)
-0.08
-0.03
0.01
-0.19
-0.1
0.17
%C
0.07
0.12
0.16
-0.19
0.13
0.12
Table S4. (Continued)
Richness
Shannon’s
Div.
Simpson’s
Div.
Chinq. Root
tips
Pine Root tips
Basal
Area/plot
%N
-0.01
Root
Biomass
(g)
0.19
Chinq. %
Cover
-0.35
Avg. Vol.
Water
(m3/m3)
-0.1
0.04
0.14
-0.35
0.08
0.09
-0.13
-0.01
0.09
Shannon’s
Diversity
1
1
Simpson’s
Diversity
0.98
-0.1
1
1
1
-0.52
0.88
-0.16
-0.36
-0.09
0.98
1
1
-0.55
0.88
-0.17
-0.29
0.28
0.38
-0.38
-0.08
-0.18
-0.5
0.88
-0.52
0.88
-0.55
0.88
1
-0.7
-0.7
1
0.05
0.04
0.02
0.16
0.17
-0.14
-0.16
-0.17
0.05
0.04
1
Richness
Chinq.
Root tips
-0.5
Pine
Root tips
0.88
Basal
Area/plot
-0.14
102
Table S5. Spearman ranked correlation coefficients (ρ) for most frequently occurring Pinaceae overstory species compared to
environmental and EMF variables (n = 12). Bold = relationships strong enough to merit attention, values presented in Results
section.
Tree Count
Basal Area
pH
Elevation (m)
Aspect (º)
Bray P (mg/kg)
Total P (mg/kg)
Mineralizable N (mg/kg)
Incubation N (mg/kg)
%C
%N
Root Biomass (g)
Chinq. % Cover
Avg. Vol. Water (m3/m3)
Shared EMF (count)
Chinq. Richness
Chinq. Shannon's Div.
Chinq. Simpson's Div.
Pina. Richness
Pina. Shannon's Div.
Pina. Simonson's Div.
Chinq. Root tips
Pine Root tips
Abies grandis
Basal Area
0.93
1.00
0.49
0.76
-0.13
-0.26
-0.22
0.09
0.01
-0.28
-0.38
0.29
0.14
0.46
-0.48
-0.24
-0.18
-0.12
-0.27
-0.27
-0.25
-0.44
0.11
Pinus contorta
Basal Area
0.42
1.00
-0.47
-0.35
-0.33
0.83
0.26
-0.19
-0.18
0.41
0.33
0.01
0.15
-0.47
-0.07
-0.20
-0.17
-0.14
-0.52
-0.50
-0.48
-0.28
0.00
Pinus ponderosa
Basal Area
-0.05
1.00
-0.12
-0.01
0.40
-0.24
0.01
0.19
0.20
0.28
0.26
0.08
0.05
0.12
0.02
0.04
-0.02
-0.09
0.00
-0.03
-0.07
0.30
-0.01
103
Appendix B
Selected Scatterplots Involving Environmental Variables
●
6.0
●
●
●
● ● ●
●●
●
5.8
●
●
pH
●
5.6
●
●
5.4
5.2
●
0
20
40
Chinquapin % Cover
60
80
Fig. S1 Scatter plot of chinquapin % cover vs. pH per transect pair.
104
●
40
●
●
B ra y Phospho
r u s (m g /k g )
35
30
●
25
●
●
20
●
●
● ●
●
●
●
●
15
5.2
5.4
5.6
5.8
●
●
6.0
pH
Fig S2 Scatter plot of pH vs. bray phosphorus (mg/kg) per transect pair.
105
●
40
●
●
B r a y P h o s p h o ru s (m g /k g )
35
30
25
●
●
●
●
●
20
●
●
●
1400
1500
●
●
●
15
●
●
1600
1700
Elevation
Fig. S3 Scatter plot of bray phosphorus (mg/kg) vs. elevation (m) per transect pair.
106
●
T o ta l P h o s p h o ru s (m g /k g )
1200
●
●
1000
●
●
●
●●
●
●
●
●
800
●
●
●
●
1400
1500
1600
1700
Elevation (m)
Fig. S4 Scatter plot of elevation (m) vs. total phosphorus (mg/kg) per transect pair.
107
●
●
Mineralizable Nitrogen (mg/kg)
20
●
●
●
●
●
10
●
●
0.025
●
●
●
●
●
●
0.050
0.075
Total Nitrogen (%)
0.100
0.125
Fig. S5 Scatter plot of total nitrogen (%) vs. mineralizable nitrogen (mg/kg) per transect pair.
108
Mine ralizable Nitrogen (mg/kg)
●
●
●
●
20
●
●
●
●
●
●
●
●
10
●
●
●
●
●
●
●
●
0.00
0.02
●
● ●
●
●
●
●
●
●
●
●
●
0.04
Avg. Vol. Soil Moisture (m /m )
0.06
Fig. S6 Scatter plot of average volumetric soil moisture (m3/m3) vs. mineralizable nitrogen
(mg/kg).
109
●
40
●
●
Bray Phosphorus (mg/kg)
35
30
●
25
●
●
●
●
20
●
●●
●
●
●
15
800
●
●
1000
Total Phosphorus (mg/kg)
1200
Fig. S7 Scatter plot of total phosphorus (mg/kg) vs. Bray phosphorus (mg/kg) per transect pair.
110
●
●
Mineralizable Nitrogen (mg/kg)
20
●
●
●
●
●
10
●
●
●
●
●
●
●
●
●
2
3
4
5
Total Carbon (%)
Fig. S8 Scatter plot of total carbon (%) vs. mineralizable nitrogen (mg/kg) per transect pair.
111
●
●
●
5
●
●
Total Carbon (%)
4
●
●
●
●
●
●
3
●
2
●
●●
●
0.025
0.050
0.075
Total Nitrogen (%)
0.100
0.125
Fig. S9 Scatter plot of total nitrogen (%) vs. total carbon (%) per transect pair.
112
Selected Scatterplots Involving EMF Variables and Root tip Counts
●
●●
3.2
●
●
●
●
●
●
Pina. EMF Shannon’s Div.
3.0
●
●
2.8
●
2.6
●
●
●
●
2.4
10
20
30
40
Pinaceae root tips/transect pair
50
60
Fig. S10 Scatter plot of Pinaceae root tips vs. Pinaceae EMF Shannon’s Diversity per transect
pair.
113
●
30
Chinquapin root tips/transect pair
●
●
20
●
●
●
●
●
10
●
●
●
●
●
●
10
20
30
40
Pinaceae root tips/transect pair
●
50
●
60
Fig. S11 Scatter plot of Pinaceae root tips vs. chinquapin root tips per transect pair.
114
●
●●
25
●
●
●
●
●
Pinaceae EMF Richness
●
20
●
●
15
●
●
●
●
●
10
20
30
40
Pinaceae root tips/transect pair
50
60
Fig. S12 Scatter plot of Pinaceae root tips vs. Pinaceae EMF richness per transect pair.
115
●
●
2.5
●
●
Chinq. EMF Shannon’s Div
2.0
●
●●
●●
●
1.5
●
●
●
●
●
1.0
●
10
20
30
40
Pinaceae root tips/transect pair
50
60
Fig. S13 Scatter plot of Pinaceae root tips vs. chinquapin EMF Shannon’s Diversity per transect
pair.
116
●
●
Chinquapin EMF Richness
12
●
8
●
●
●●
●●
●
●
4
●
●
●
●
●
10
20
30
40
Pinaceae root tips/transect pair
50
60
Fig. S14 Scatter plot of Pinaceae root tips vs. chinquapin EMF Richness per transect pair.
117
●
●
Chinquqpin EMF Richness
12
●
8
●
●
●●
●
4
●●
●
●
●
●
10
20
Chinquapin root tips/transect pair
30
Fig. S15 Scatter plot of chinquapin root tips vs. chinquapin EMF richness per transect pair.
118
●
25
●
●
●
●
●●
Pinaceae EMF Richness
●
●
20
●
●
15
●
●
●
●
●
10
20
Chinquapin root tips/transect pair
30
Fig. S16 Scatter plot of chinquapin root tips vs. Pinaceae EMF richness per transect pair.
119
●
●
2.5
●
●
Chinq. EMF Shannon’s Div.
2.0
●
●●
●
●●
1.5
●
●
●
1.0
●
10
20
Chinquapin root tips/plot
30
Fig. S17 Scatter plot of chinquapin root tips vs. chinquapin EMF Shannon’s diversity per
transect pair.
120
●
●
2.5
●
Chinq. EMF Shannon’s Div.
2.0
●
●
●●
●●
●
1.5
●
●
●
1.0
●
10
20
Chinquapin root tips/plot
30
Fig. S18 Scatter plot of chinquapin root tips vs. Pinaceae EMF Shannon’s diversity per transect
pair.
121
Selected Scatterplots Involving Overstory Pinaceae Basal Area
30
●
Grand Fir Basal Area (m2/ha)
20
●
10
●
●
●
0
●
1400
●●
●
1500
1600
1700
El evation (m)
Fig. S19 Scatter plot of elevation (m) vs. grand fir basal area (m2/ha) per transect pair.
122
●
Lodgepole Pine Basal Area (m2/ha)
15
10
●
5
●
●
●
0
●
●●
15
●
●
20
30
25
Bray Phosphorus (mg/kg)
35
40
Fig. S20 Scatter plot of Bray phosphorus (mg/kg) vs. lodgepole pine basal area (m2/ha) per
transect pair.
123
●
Lodgepole Pine Basal Area (m /ha)
15
10
●
●
5
●
●
●
●●●
0
2.6
2.8
3.0
Pinaceae EMF Shannon's Div.
●
3.2
Fig. S21 Scatter plot of Pinaceae EMF Shannon’s diversity vs. lodgepole pine basal area
(m2/ha) per transect pair.
124
●
Lodgepole Pine Basal Area (m /ha)
15
10
●
●
5
●
●
●
● ● ●
0
16
20
Pinaceae EMF Richness
●
24
Fig. S22 Scatter plot of Pinaceae EMF richness vs. lodgepole pine basal area (m2/ha) per
transect pair.
125