Factors associated with seedling establishment on logs of different
fungal decay types – a seed sowing experiment
Yu Fukasawa*, Hiroyuki Kitabatake
Laboratory of Forest Ecology, Graduate School of Agricultural Science,
Tohoku University, 232-3 Yomogida, Naruko, Osaki, Miyagi 989-6711, Japan
*Corresponding author
Email: yu.fukasawa.d3@tohoku.ac.jp, Tel: +81 229 84 7397, Fax: +81 229
84 6490
Acknowledgements
The authors thank staffs of the Yamagata forest office for providing
research permission. The authors are greatful to Yoshihisa Suyama,
Wataru Koga, Chie Masuda, Yumena Morikawa, Satsuki Kimura, Yuki
Kawasaki, Hiroya Taguchi, Chinatsu Tokuhiro, Mana Motomiya, Atsuki
Shimura, Yasuyuki Komagata, and Masanori Suzuki for their assistance in
field works and advises in statistical analyses. Thanks are extended to
Ayumi Matsuo, Shun Hirota, Daiki Takahashi, and Kunihiro Okano for their
support in molecular methods, and Yoshimi Yokoyama for running ion
chromatography. This study was finantially supported by Inamori
Foundation.
Author contributions
YF: conceptualization, methodology, writing–original draft and review,
supervision, funding acquisition, HK: methodology, writing–review. Both
authors contributed to the article and approved the submitted version.
Data availability
The data presented in this study are available on request from the
corresponding author.
Conflict of interest
The authors declare that the research was conducted in the absence of
any commercial or financial relationships that could be construed as a
potential conflict of interest. Experimental research and field
studies on fungi including the collection of fungal material, are
complied with relevant institutional, national, and international
guidelines and legislation.
Abstract
1. Activities of wood decomposer fungi alter abiotic and biotic
properties of deadwood, which are important for tree seedling
regeneration on nurse logs. However, the effects were seldom evaluated
experimentally.
2. In this study, we examined germination, growth, and survival of six
arbuscular mycorrhizal and six ectomycorrhizal tree species on three
substrates (brown rot logs, white rot logs, and soil) by seed sowing
experiments in a mixed forest dominated by Pinus densiflora andQuercus serrata . We also analyzed fungal communities in these
substrates by rDNA ITS1 sequencing.
3. Some significant substrate effects were found on seedling performance
when comparing wood decay types, but these were not clearly consistent
across mycorrhizal status of the seedlings. Nevertheless, seedlings of
arbuscular mycorrhizal trees tended to show better growth on brown rot
logs than on white rot logs, whereas ectomycorrhizal tree seedlings
tended to survive better on white rot logs and soil compared to brown
rot logs.
4. The fungal community was significantly different across three
substrates. Richness of Operational Taxonomic Units (OTUs) of arbuscular
mycorrhizal fungi was largest in brown rot logs, whereas OTU richness of
ectomycorrhizal fungi was largest in soil.
5. Synthesis: The effects of fungal wood decay type on nurse log
regeneration of tree seedlings might be partly attributable to water
content and fungal communities in the logs. Particularly, rich
communities of arbuscular mycorrhizal fungi in brown rot logs could
assist in the growth of arbuscular mycorrhizal tree seedlings.
Keywords
coarse woody debris, microsites for tree regeneration, mycorrhizal type,Pinus densiflora , plant-soil feedback, rot type, wood-inhabiting
fungi
Introduction
Nurse logs play a vital role in the regeneration process of forest
trees. That is important not only in boreal and subalpine coniferous
forests but also in temperate and tropical broadleaf forests (Christie
and Armesto 2003; Doi et al. 2008; Harmon and Franklin 1989; Papaik and
Canham 2006; Sanchez et al. 2009). Decaying logs provide regeneration
microsites with better light conditions, reduced litter accumulation,
less root competition, and abundant water content. These conditions are
particularly advantageous for small-seeded species with limited energy
reserves for initial growth, which can still become canopy dominants
(Lusk 1995). A better understanding of the mechanisms and factors
associated with tree regeneration nurse logs is crucial for predicting
future forest dynamics under global climate change.
The properties of the logs affecting seedling regeneration have been the
subject of long-standing discussions. For instance, logs must be thick
to host many seedlings (Takahashi 1994). Well-decayed logs that are
softened, moistened, and covered with abundant moss provide better
microsites for seedlings compared to undecayed, hard logs without moss
layer (Fukasawa and Ando 2018; Mori et al. 2004; Iijima and Shibuya
2010). Additionally, the tree species of the logs must be taken into
account (Orman et al. 2016). Furthermore, the decay type of the logs
caused by fungal decomposers has recently gained attention as an
important factor influencing seedling regeneration (Fukasawa 2021).
Decay type categorizes the physicochemical properties of decaying wood
due to decomposer fungi, which exhibit species-specific or
strain-specific preferences for different wood components, such as
lignin, cellulose, and hemicellulose (Fukasawa 2021). Decay type of
basidiomycetes, a phylogenetic group of fungi with strong wood decay
abilities, traditionally fall into two categories: brown rot and white
rot (Eaton and Hale 1993). In white rot, lignin is selectively or
simultaneously decayed along with cellulose and hemicellulose, resulting
in fibrous, soft, spongy wood due to the decay of lignin binding the
cell walls (Araya 1993). In contrast, brown rot mainly targets cellulose
and hemicellulose while leaving lignin with little modification, causing
brown rot wood to become brown in colour and with a blocky texture.
Brown rot process requires acidic conditions (Espejo & Agosin, 1991),
making brown rot wood more acidic than white rot wood (Fukasawa, 2012).
Differences in wood decay type can significantly affect seedling
communities on the logs and potentially lead to niche separation among
dominant tree seedlings in a local context (Fukasawa et al. 2017).
However, the factors determining the impact of decay types on tree
seedling regeneration are not well-explored.
A review of previous field studies has reported that tree seedlings
mainly associated with arbuscular mycorrhizal (AM) fungi tend to
regenerate more frequently on brown rot logs than on white rot logs
(Fukasawa 2021). In contrast, seedlings mainly associated with
ectomycorrhizal (ECM) fungi tend to regenerate more frequently on white
rot logs than on brown rot logs (Fukasawa 2021). These mycorrhizal types
are formed by distinct fungal groups and are associated with different
phylogenetic groups of trees (Smith and Read 2008). Mycorrhizal fungi
are abundant in decayed wood in forests, especially in later decay
stages (Rajala et al. 2011, 2012, 2015), and are essential for seedling
colonization on the logs (Marx and Walters 2006; Fukasawa 2012).
Tedersoo et al. (2008) reported that wood decay type influences
ectomycorrhizal communities associated with the roots of tree seedlings
growing on the logs. Therefore, the difference in mycorrhizal fungi in
logs of different decay types might explain the effect of wood decay
type on seedling regeneration on the logs. However, communities of
arbuscular mycorrhizal fungi have not been compared between white rot
and brown rot logs, nor has seedling performance on logs of different
decay types been compared among seedlings of different mycorrhizal
types.
In the present study, we evaluated the effects of abiotic and biotic
properties of three microsites: brown rot logs, white rot logs, and
soil, for tree seedling establishment in a secondary mixed forest. We
achieved this by sowing seeds of six arbuscular mycorrhizal and six
ectomycorrhizal tree species in the field. Fungal communities in the
logs were analyzed using metabarcoding of fungal DNA directly extracted
from wood sampled from each microsite. We hypothesized that
ectomycorrhizal fungal species, which posses organic matter decay
abilities, occur more frequently in white rot logs than in brown rot
logs due to the high availability of cellulose and hemicellulose in
white rot logs. Conversely, arbuscular mycorrhizal fungi, which
generally lack organic matter decay abilities, were hypothesized to
occur more frequently in brown rot logs. The high concentration of
recalcitrant lignin in brown rot logs may reduce colonization by
saprotrophic fungi (Lindner et al. 2011), allowing arbuscular
mycorrhizal fungi to thrive without competitive exclusion as long as
there were host plant roots. Seedling establishment, particularly in its
early stages, is determined by three key processes: germination,
survival, and growth. We predicted that seedlings of arbuscular
mycorrhizal trees would exhibit better growth and survival on brown rot
logs than on white rot logs or in soil. In contrast, seedlings of
ectomycorrhizal trees would perform better on white rot logs than on
brown rot logs or in soil due to the relative dominance of their
mycorrhizal symbionts.
Materials and methods
Study site
This study was conducted in a secondary forest dominated by oak
(Quercus serrata ), pine (Pinus densiflora ), and cedar
(Cryptomeria japonica ) in Mt. Chitose (38°14′N 140°21′E, altitude
245 m) located in the northern part of the central island of Japan. The
site features a gentle northwestern slope with a mean total annual
precipitation of 1207 mm, a mean annual temperature of 12.1°C (for the
period 1991–2020, according to the Japan Meteorological Agency), and a
maximum snow depth of approximately 1 m at the nearest weather station
(Yamagata; 38°15′N 140°21′E, altitude 153 m). This area of interest is a
shrine forest under the managed of the Forestry Agency of Japan.
Pine wilt disease, attributed to the North American native pinewood
nematode Bursaphelenchus xylophilus , was first observed in this
area in 1982 and led to significant dieback in P. densiflora over
the past few decades. To prevent the spread of pine wilt disease, the
region has undergone deadwood management, including the felling of
infected trees and fumigation with pesticides such as
methylcarbamodithioic acid ammonium (NCS). Notably, this forest floor
lacks dwarf bamboo Sasa spp., which typically dominates the
understory of many Japanese forests. Previous studies conducted in this
site have reported that seedlings of C. japonica , P.
densiflora , Clethra barbinervis , and Ilex crenata were
frequently observed on P. densiflora logs (Fukasawa et al. 2017).
These studies also revealed that the growth and survival of C.
japonica seedlings showed negative associations with white rot logs
compared with brown rot logs (Fukasawa & Komagata 2017).
Seed-sowing experiment
In an approximately 1 ha tract at the study site, we selected 62P. densiflora logs (diameter 19–62 cm, length 62–200 cm) at ten
different locations. These logs were well-decayed, falling into decay
class IV within a five-class decay system (Fukasawa 2012). They were
categorized into one of two decay types—-30 white rot logs and 32
brown rot logs—-based on visual criteria (Araya 1993). To prepare the
logs, we removed moss layer and surface vegetations from all the logs
(we did not record the species of these), plowed and flattened the tops
using a hand axe. Some of the logs had plant roots inside, including
remainings of surface vegetation and that grew from soil. We remain with
these roots because removing all of these roots were impossible. We set
up multiple 5 cm x 5 cm quadrats on the logs by surrounding them with
polyvinyl chloride plates (9 mm height with slits, AooYoo, ShenZhen,
China) (Fig. 1). Similar quadrats were established on the ground soil at
the same ten locations after removing the litter layer.
Mature seeds of six arbuscular mycorrhizal and six ectomycorrhizal tree
species were collected from the study site or nearby regions (Table 1).
Exceptions were Abies veitchii , Betula ermanii ,Chamaecyparis obtusa , and Cryptomeria japonica seeds,
which were obtained from the public seed collection of the Forestry and
Forest Products Research Institute (Ibaraki, Japan), and Picea
jezoensis seeds were sourced from a private company (H.I.Tree C’s,
Saitama, Japan) because it was hard to collect sufficient number of
seeds due to a non-masting season in the study area. In November 2019
(for 21 white rot and 23 brown rot logs) or in November 2020 (for
additional logs of 9 white rot and 9 brown rot), seeds were sown in the
quadrats, with 35–120 seeds per quadrat depending on the species. We
prepared nine replicate quadrats for each species on each of the three
substrates (brown rot log, white rot log, and soil). In total, 19,170
seeds were sown. To protect the seeds from wind and potential predation
by small mammals during the winter, the quadrats were covered with 4 mm
mesh nets, securely fastened with metal pegs onto the substrates (Fig.
1).
Starting from the following spring (either April 2020 or 2021), we
recorded seed germination and survival for two growing seasons for seeds
sown in 2019 and one growing season for seeds sown in 2020, continuing
until October 2021. In each quadrat, we recorded the number of live
seedlings without individual tagging. These recordings were conducted 13
times in 2020 (from April to November) and 10 times in 2021 (from April
to October), including observations every two weeks from April to August
and monthly thereafter.
In October 2021, all the seedlings were harvested and transported to the
laboratory. Fresh shoot lengths were measured, and the dried weights of
shoots and roots were recorded after drying for more than three days in
70 ˚C. In the case of several seedlings, fresh root subsamples were
taken to determine the colonization rate of mycorrhizal fungi.
Physicochemical properties of logs and soil
The canopy openness above each log and soil quadrat was documented by
capturing hemispherical images on a cloudy day in June 2020 (for 44 logs
and 10 soil subplots) and in June 2021 (for additional 18 logs). This
was accomplished using a Canon EOS Kiss X5 camera equipped with a
circular fisheye lens (4.5 mm F2.8 EX DC, SIGMA, Kanagawa, Japan). To
compute the canopy openness, we employed computer software called
CanopOn 2 (available at http://takenaka-akio.org/etc/canopon2/).
Additionally, the water content of the logs and soil subplots were
measured using a portable soil moisture meter DIK-31F (Daiki, Saitama,
Japan) during each seedling survey. The time-series data for water
content were averaged for each substrate and subsequently used for the
following analyses.
In September 2020 (for 44 logs and 10 soil quadrats) and September 2021
(for additional 18 logs), samples of the substrate were obtained either
manually using a rubber glove or a knife due to the softness of the log
surfaces. From each substrate (individual logs and soil quadrat), three
samples were collected and then combined to create a single sample
(totally 72 combined samples), approximately 50 mL each. These samples
were transported back to the laboratory and kept in a fridge at around 8
˚C for a week, pending chemical analysis.
The samples were pulverized using a blender WB-1 (Osaka chemical, Osaka,
Japan) to pass throught a 5 mm mesh. Crushed samples (ca. 60 mL) were
subjected to extraction with 200 mL of deionized water in 250 mL
polyethylene bottles for 1 h of shaking (100 rpm on a Shaker MK201D
(Yamato Scientific, Tokyo, Japan). The pH of the extract was measured
using a potable pH meter (LAQUAtwin-pH-11B, HORIBA, Kyoto, Japan). The
extract was subsequently filtered using filter paper 5C (ADVANTEC,
Tokyo, Japan) and a syringe filter DISMIC25CS (ADVANTEC, Tokyo, Japan).
The filtrate was analyzed using an Ion Chromatography system Shim-pack
IC (Shimadzu, Kyoto, Japan) with 0.6 mM
Na2CO3/12mM NaHCO3 as
the anion eluent and 2.5 mM oxalic acid as the cation eluent, at a
separation column temperature of 40ºC. The ion concentrations (Na⁺,
NH₄⁺, K⁺, Cl⁻, NO₃⁻, SO₄²⁻, Mg²⁺, Ca²⁺) were expressed as per 100
g-dried substrate bases. A principal component analysis was conducted to
visually represent the variance in nutrient ion composition and project
it onto PC vectors (Supplementary Fig. S1).
Fungal communities in logs and soil
In September 2020 (for 44 logs 10 soil quadrats) and September 2021 (for
additional 18 logs), substrate samples were collected using a knife.
Three samples were taken from each substrate and then combined into a
single sample (totally 72 combined samples), approximately 30 mL each.
To prevent cross-contamination among samples, the knife was sterilized
with 70% ethanol and a burner flame. The collected samples were
transported back to the laboratory in a cooler bag with ice and stored
at –30˚C until DNA extraction.
DNA extraction was carried out from 0.2 g of white rot and brown rot
dead wood and 0.3 g of soil freeze-dried samples using the ISOIL for
Beads Beating kit (Nippon Gene, Tokyo, Japan) in accordance with
manufacture’s protocol. Out of a total of 72 samples, DNA extraction was
unsuccessful for 7 samples (4 white rot and 3 brown rot samples). For
sequencing of the fungal internal transcribed spacer 1 (ITS1) region, we
employed the MiSeq sequencing platform with 250 x 2 paired-end reads
(Illumina, San Diego, CA, USA). This was done using a two-step PCR
protocol with ITS1F_KYO1/ITS2_KYO2 primers (Toju et al. , 2012),
where the primary amplification included tails for adding indices and
Illumina flow cell adapters in the secondary amplification. We used
positive and negative controls in the PCR, and positive controls in the
MiSeq sequencing. The ITS region is widely recognized as the formal
fungal barcode (Schoch et al. , 2012; Kauserud 2023). For more
details on sample preparation for MiSeq sequencing, please refer to the
Supplementary methods.
A total of 4,004,674 reads were obtained after MiSeq sequencing run and
chimera check. The data have been deposited in the Sequence Read Archive
of the DNA Data Bank of Japan, with accession numberDRA????????????? . The sequence reads underwent trimming
with a minimum quality value of 30, and the 5’- and 3’- primer sequences
were subsequently removed from the trimmed reads. Following this, the
trimmed reads were denoised using Claident (Tanabe and Toju, 2013) with
Assams assembler v0.2.2015.05.10 (Tanabe, 2015). A chimera check was
conducted using Claident software with reference to the UNITE database
(https://unite.ut.ee, accessed 16th October 2023). The quality-filtered
sequences were then classified into molecular OTUs and taxonomically
identified using the Claident fungal ITS database (fungi_its_genus),
structured after the International Nucleotide Sequence Database
(http://www.insdc.org, accessed 3rd December 2019). This classification
was performed at a threshold similarity of 97%, a widely recognized
standard for the fungal ITS region (Osono, 2014).
We excluded one white rot and one soil sample with less than 1,000
reads. For each sample, OTUs with less than 0.1% of the total number of
reads per sample were removed. Following the filtering process, a total
of 3,843,172 reads were retained. Since the OTU numbers reached
saturation in this dataset (Supplementary Fig. S2), we did not conduct
rarefaction for individual samples to adjust for differences in sequence
length. Singleton OTUs were also eliminated from subsequent analyses. As
a result, each of the 373 filtered OTUs from 63 samples (25 white rot,
29 brown rot, and 9 soil samples) was cross-referenced with the FUNGuild
database and assigned to one of the 11 functional groups: arbuscular
mycorrhizal (AM), brown-rot (Bro), ectomycorrhizal (ECM), ericoid
mycorrhizal (Erm), fungal parasite (Fup), plant pathogen (Plp), soft-rot
(Sof), undefined saprotroph (Sap), white-rot (Whi), and wood decay with
unknown decay type (Wod) and unknown functions (Unk)
(https://github.com/UMNFuN/FUNGuild, accessed 1st July 2018; Nguyen et
al., 2016) (Supplementary Table S1).
Colonization rate of mycorrhizal fungi
The colonization rate (%) of mycorrhizal fungi in the root system of
individual seedlings was assessed. For arbuscular mycorrhizal tree
species, one seedling was randomly selected from each quadrat on every
substrate (n = 9). The roots were initially washed with a 0.005%
aerosol OT solution (Wako, Osaka, Japan) in a voltex for 1 min, followed
by a 10-min treatment in a hypersonic waterbath. Subsequently, they were
rinsed with deionized water twice and cleared by heating in 10% KOH at
100 ºC for over 1 h. After this, cleared roots were rinsed with
deionized water, bleached in 0.5% H2O2solution for 20 min, followed by another rinse with deionized water, and
then fixed in 2% HCl for more than 10 min. The fixed roots were stained
with trypan blue and preserved in lactoglycerol (lactic acid 525 mL,
glycerin 37.8 mL, deionized water 37.2 mL). Colonization was assessed
following the method of McGonigle et al. (1990) under 200x magnification
to determine the percentage of root length colonized by arbuscular
mycorrhizal fungal structures, including arbuscules, coils, and
vesicles.
For ectomycorrhizal trees species, three seedlings were selected from
each quadrat on each substrate (n = 27). The colonization rate (%) of
ectomycorrhizal fungi was calculated as the percentage of
ectomycorrhizal root tips in relation to the total root tips (88.8 tips
in average). This assessment was made through direct observation of root
systems under a binocular microscope with less than 45x magnification
(SZ2–ILST, Olympus, Tokyo, Japan).
Statistical analysis
All statistical analyses were performed using R version 4.0.5 (R core
team 2021). To compare the physicochemical properties of substrates,
seed germination rate, seedling survival rate, and the measurements of
shoot length, dry weight, and mycorrhizal colonization of seedlings
among the three substrate categories (white rot log, brown rot log, and
soil), we employed the Steel-Dwass test with the nparcomp command
from the nparcomp package. Data from Alnus hirsuta were
excluded from comparison due to very low germination and survival rates.
For the visualization of fungal taxonomic composition in the substrates,
we utilized the heat_tree command from the metacoderpackage (Foster et al. , 2017). We based our analysis on the
occurrence data (presence/absence) of fungal OTUs, as the numbers of
sequence reads do not usually reflect the relative abundance of taxa in
a sample (Skelton et al. , 2019b). To assess the dissimilarities
in fungal communities between the samples, we calculated the Raup-Crick
index and created non-metric multidimensional scaling (NMDS) ordination
plots for all surveyed samples using the metaMDS command from thevegan package (Oksanen, 2016). The significance of differences in
community composition among the substrates was determined by
permutational multivariate analysis of variance (PERMANOVA), with 10,000
permutations, using the adonis command (Anderson, 2001).
Additionally, community variance between samples (calculated using thebetadisper command) was compared among substrates using analysis
of variance (ANOVA) with the anova command. The envfitcommand was used to assess the significance of correlations between
environmental variables and fungal community composition. Among the
environmental variables listed in Table 2, we selected canopy openness,
pH, water content, and nutrient_PC1 for analysis after removing highly
correlated variables to reduce multicollinearity.
Fungal OTU richness at each substrate was compared using iNEXT (Chao et
al., 2016). Occurrence frequencies of fungal OTUs belonging to specific
functional categories, such as arbuscular mycorrhizal fungi,
ectomycorrhizal fungi, and plant pathogens, were determined as the
percentage of logs on which the OTUs of the focal function were detected
relative to the total log numbers. We compared the occurrence
frequencies of these functional categories among the substrates using
Fisher’s exact probability test and Ryan’s post hoc comparison
(http://aoki2.si.gunma-u.ac.jp/R/src/p_multi_comp.R). These categories
were chosen due to their potential effects on seedling growth and
mortality (Bayandala et al. 2016; Wulantuya et al. 2020). Indicator
species analysis was applied to the OTUs assigned to functions to
determine whether their occurrences were indicative of particular
substrates, using the multipatt command from theindicspecies package (Caceres and Jansen 2015).
Generalized linear models (GLMs) and generalized linear mixed models
(GLMMs) were employed to analyze the relationships between environmental
variables and seedling performance (germination, survival, and growth).
In addition to the five factors that showed significant correlations
with fungal communities in the NMDS ordination analysis (substrate,
canopy openness, pH, water content, nutrient_PC1), the OTU richness of
AM or ECM fungi in the fungal community survey was also set as fixed
variables. We began by analyzing combined data for AM or ECM trees using
GLMM. The OTU richness of AM and ECM fungi were used as factors for
models of AM and ECM trees, respectively. For the model explaining
germination rate, a matrix of germinated and non-germinated seed numbers
[cbind(germinated, non-germinated)] in each quadrat was set as the
dependent variable. For the model explaining survival rate, a matrix of
survived and dead seedling numbers [cbind(survived, dead)] in each
quadrat was set as the dependent variable. Binomial distributions (logit
link) were assumed, and unmeasured effects of seedling species and
sowing year were set as random factors for germination and survival
models. For the models explaining seedling growth, shoot length and
dried weight of each seedling were set as dependent variables. Gaussian
distribution (identity link) was assumed for the shoot length model,
while the dry weight model used a Gamma distribution (log link). The
unmeasured effects of substrate identity, seedling species, and sowing
year were set as random factors. The best model was selected based on
the lowest Akaike Information Criterion (AIC) using backward elimination
in the dredge function from the MuMIn package (Burnham and
Anderson 2002). For germination and survival models, corresponded AIC
(AICc) was used given the small sample size (Burnham and Anderson 2002).
Subsequently, we analyzed data for individual seedling species by using
GLM and GLMM. The same sets of variables used in the models for the
combined data of mycorrhizal type were applied to these models. For
models explaining germination rate and survival rate, we assumed
quasi-Poisson (log link) and quasi-binomial (logit link) distributions,
respectively, due to their large data variations (Faraway 2006). The
best models were selected based on the lowest AIC or AICc as described
above. Pearson’s correlation coefficients among the variables were all
below 0.7, and the variance inflation factors of the models were less
than 5, indicating low levels of multicollinearity.
Pearson’s correlation coefficients between colonization rate of
mycorrhizal fungi and seedling growth (shoot length, dry weight) were
calculated for each tree species, except for Alnus seedlings from
which we could not obtain enough seedlings.
Results
Physicochemical properties of the substrates
Canopy opennes was irrelevant among the three substrates (Fig. 2). Brown
rot logs had higher water content compared to white rot logs and soil.
Soil exhibited a higher pH than the logs. Among the nutrient ions,
concentrations of Na+,
NH4+, and K+ were
significantly higher in white rot logs than in brown rot logs and soil
(Fig. 3). In contrast, SO42–concentration in soil was higher than in the logs.
Cl–, NO3–, and
Ca2+ concentrations did not differ across the
substrates. PO43– concentration was
too low to detect quantitatively (< 0.5 mg/L).
Fungal community in the substrates
In total, 373 OTUs were detected, including 192 Ascomycota, 116
Basidiomycota, 13 Glomeromycota, and 9 Mucoromycota, along with 43 of
unknown taxonomy (Table S1, Fig. S3). Leotiomycetes, Sordariomycetes,
and Eurotiomycetes were the dominant classes in Ascomycota.
Agaricomycetes was the most dominant class in Basidiomycota. Among the
373 OTUs, 109 were assigned to one of the ten functional groups.
Undefined saprotroph (Sap) contained the largest number of OTUs (47
OTUs), followed by ectomycorrhizal (ECM, 15 OTUs), arbuscular
mycorrhizal (AM, 13OTUs), soft rot (Sof, 12 OTUs), white rot (Whi, 7
OTUs), and plant pathogen (Plp, 7 OTUs). The OTU richness of all fungi
was nearly saturated against the number of samples (Fig. 4A), with brown
rot logs hosting the largest number of fungal OTUs. This was also the
case for AM (Fig. 4B), while in the ECM group, soil host the largest
number of OTUs (Fig. 4C). Differences in the OTU richness of Plp across
the substrates were unclear due to a large overlap in the confidence
intervals (Fig. 4D).
NMDS ordination plot and PERMANOVA showed that fungal communities
significantly (P < 0.001) differed across the
substrates (Fig. 5A), although dispersion differed across the substrates
(P = 0.03). The sampling year had no effect on fungal communities
(PERMANOVA, R2 = 0.05, P = 0.07). Among the tested environmental
variables, pH, water content, and nutrient_PC1 of the substrates had
significant associations with fungal communities (Fig. 5A). The effects
of water content and nutrient_PC1 were consistent but the effect of pH
was not evident in the dataset focusing on logs (i.e. excluding soil
samples) (Fig. 5B). The diameter and length of the logs were not
significantly associated with fungal communities.
Forty OTUs were detected as indicative for one of the three substrates
(Table 3). The number of indicative OTUs for brown rot logs, white rot
logs, and soil were 34, 22, and 76, respectively. All substrates
included indicative Sap OTUs. In contrast, all three AM OTUs were found
in brown rot samples, and all 12 ECM OTUs were found in soil samples. An
indicative Bro OTU (Leucogyrophana sp.) and an indicative Whi OTU
(Sistotremastrum sp.) were found in brown rot samples and white
rot samples, respectively.
Seedling demography
Among the total 19,170 seeds sown, 3,562 (18.6%) seeds germinated. Of
the 12 tree species tested, Padus grayana and Pinus
densiflora showed germination rates of >50% on all
substrates (Fig. 6A). Ilex crenata , Cryptomeria japonica ,Abies veitchii , Carpinus laxiflora , and Betula
ermanii showed germination rates of 20–30%. However,Chamaecyparis obtusa , Toxicodendron trichocarpa ,Picea jezoensis , Clethra barbinervis , and Alnus
hirsuta showed germination rates of <10%. Data ofAlnus hirsuta were not included in the following analysis due to
its very low germination rate. None of the 12 tree species showed a
significant difference in germination rate across the three substrates.
The seedling species names were represented by their genus names
hereafter.
Among the seeds sown in Novermber 2019, Abies , Carpinus ,
and Padus had already germinated by the first recording on April
16, 2020. The populations decreased gradually during the first gworing
season, and remained constant thereafter, even after winter (Fig. S4A).Cryptomeria , Clethra , Pinus , and Picea had
germination peaks in June, with their population decreasing during
summer but remaining constant thereafter, even after winter. Among the
seeds sown in Novermber 2020, Chamaecyparis , Ilex , andToxicodendron showed high survival rates (Fig. S4B, Fig. 6B).Betula germinated from April to May and decreased its population
to approximately 50% of the original germinants by autumun (Fig. S4B).Ilex germinated from June to July and maintained a high survival
rate during the first growing season (Fig. S4B).
At the time of seedling harvest in October 2021, 32.7% of the seedlings
sown in November 2019 had survived, and 75.8% of the seedlings sown in
November 2020 had survived, resulting in a total of 1,422 seedlings
harvested. Padus seedlings showed a significantly lower survival
rate on white rot logs compared to soil (Fig. 6B). Carpinusseedlings exhibited a significantly lower survival rate on brown rot
logs compared to soil (Fig. 6B). The dry weight of Cryptomeriaseedlings was larger on brown rot logs and soil compared to white rot
logs (Fig. 7A). The dry weights of Padus and Carpinusseedlings were larger on soil compared to logs. In contrast, the dry
weight of Toxicodendron seedlings was larger on the logs compared
to soil. The shoot lengths of Clethra , Cryptomeria ,Padus , and Pinus seedlings were larger on brown rot logs
and soil compared to white rot logs (Fig. 7B). The shoot lengths ofCarpinus and Betula seedlings were larger on soil compared
to logs. The colonization rate of arbuscular mycorrhizal fungi was
generally high among all the six AM tree species tested and tended to be
lower on white rot logs compared to brown rot logs and soil, although
the difference between brown rot and white rot logs was not significant,
except for Ilex (Fig. 7C). The colonization rate of
ectomycorrhizal fungi was higher on soil compared to logs inAbies and Picea seedlings. Pinus seedlings showed a
significantly higher colonization rate of ECM fungi on brown rot logs
and soil compared to white rot logs. Betula seedlings exhibited a
significantly higher colonization rate of ECM fungi on white rot logs
and soil compared with brown rot logs. The colonization rate of ECM
fungi in Carpinus seedlings was not significantly different
across the substrates.
Factors related with seedling performance
GLMM results indicated that substrate was selected in the model
explaining germination rate, survival rate, and shoot length of AM tree
species and survival rate of ECM tree species (Table 4). Germination
rate of AM trees was significantly larger on white rot logs and soil
than on brown rot logs (Table 5). Survival rate of AM trees was
significanlty larger on soil than on brown rot and white rot logs. Shoot
length of AM trees was significantly larger on soil than on white rot
logs and was marginally (P < 0.1) larger on brown rot
logs than on white rot logs. Survival rate of ECM trees was
significantly larger on white rot logs and soil compared with brown rot
logs. The water content of the substrates was commonly selected as a
positive factor for the germination and survival of both AM and ECM
trees (Table 4). Canopy openness was selected as a positive factor for
dry weight but as a negative factor for the germination of both AM and
ECM trees.
GLMs (for germination and survival) and GLMMs (for dry weight and shoot
length) for each tree species indicated that the relationships between
seedling performance and environmental factors varied among tree
species. Substrate had a significant association with the survival rates
of Cryptomeria , Padus , and Carpinus , the dry weight
of Cryptomeria , and the shoot length of Padus (Table 6).
The dry weight of Cryptomeria seedlings was larger on brown rot
logs compared to white rot logs (Table 7). The survival rate ofCryptomeria seedling was larger on soil compared to brown rot
logs. The survival rate and shoot length of Padus seedlings were
larger on soil compared to brown rot and white rot logs. Among the
environmental factors, water content of the logs had the most widespread
association with seedling performance, except for Chamaecyparis ,Ilex , and Picea (Table 6). The associations were mostly
positive, but in the case of Carpinus seedlings, shoot length was
negatively associated with the water content of the logs. The
association with canopy openness varied among seedling species and
performance. The dry weights of Chamaecyparis , Ilex ,Abies , and Pinus were positively associated with canopy
openness. Similarly, the shoot length of Chamaecyparis ,
germination of Picea , and the survival of Pinus showed
positive associations with canopy openness. However, the germination ofClethra and Toxicodendron and the survival of Abiesexhibited negative associations with canopy openness. The pH of the logs
had positive associations with the dry weight of Abies andPinus , the germination of Picea , and the shoot length ofPinus , and a negative association with Ilex germination.
The OTU richness of mycorrhizal fungi had negative associations with the
dry weight of Cryptomeria and the germination of Picea .
Nutrient_PC1 did not have any significant associations with seedling
performance.
In the seedlings of Cryptomeria , Padus , Pinus andBetula , significantly positive correlations were found between
their shoot length and mycorrhizal colonization rate (Fig. 8; Table S1).
Similarly, significantly positive correlations were found between the
dry weight of Abies and Pinus seedlings and their
ectomycorrhizal colonization rate. None of the AM tree seedling showed
significant relationships in dry weight with their arbuscular
mycorrhizal colonization rate.
Discussion
The present study revealed that the difference in wood decay type
affects the germination and growth of AM tree seedlings and the survival
of ECM tree seedlings (Table 5). In the cases of AM trees, shoot length
of the seedlings of Clethra , Cryptomeria , andChamaecyparis tend to be larger on brown rot logs than on white
rot logs. Similarly, the dry weight of Cryptomeria seedlings was
significantly larger on brown rot logs than on white rot logs (Table 7).
As the shoot length of Cryptomeria and Padus seedlings
were positively associated with the colonization rate of AM fungi on
their roots, which tended to be larger in brown rot logs than white rot
logs, a part of the better growth of AM trees on brown rot logs might be
attributable to the high colonization rate of AM fungi on seedling roots
in brown rot logs in this site. Colonization by AM fungi is essential
for nutrient acquisition particularly in substrates with poor nutrient
contents such as decaying logs (Fukasawa 2012), and also for protection
against pathogens for host plants (Filion et al. 1999). The reason for
the rich communities of AM fungi in brown rot logs is not clear. One
possible explanation is the effects of pre-experimental vegetation on
the logs. In the present study, we used P. densiflora logs in
decay class IV found in the study site, and such logs usually have some
vegetation on them. If the logs were brown rot, the vegetation was
dominated by AM trees like Cryptomeria japonica (Fukasawa
et al. 2017) and Clethra barbinervis (Fukasawa 2012). The
dominance of AM trees certainly induces the dominance of AM fungi
belowground (Sawada et al. 2023), which in turn benefits the successful
establishment of AM tree seedlings (Seiwa et al. 2020). Alternatively,
recalsitrant lignin-accumulated brown rot logs might not be a good
substrate for decomposer fungi (Lindner et al. 2011), leaving room for
AM fungi without competitive exclusion. In contrast, white rot logs,
rich in cellulose and hemicellulose, might be dominated by decomposer
fungi. Actually, the colonization rate of AM fungi was significantly
larger on brown rot logs than on white rot logs in Ilex seedlings
(Fig 7) and this trend was common among the six AM seedlings even though
there’s no statistical significance. Similarly, previous study reported
a higher AM colonization rate on Cryptomeria seedlings in brown
rot compared to white rot wood in laboratory pot experiments (Fukasawa
and Kitabatake 2022).
In addition to the colonization rate, the functions of AM fungi could be
promoted in brown rot logs. An important function of AM fungi is
absorbing phosphorus from the substrate and providing it to host plants
(Smith and Read 2008). During the wood decay process, brown rot fungi
employ oxidative reactions of Fe (II) to Fe (III) called the Fenton
Reaction to produce hydroxyl radicals, which play a key role in the
brown rot type of wood decay (Eaton and Hale 1993). Thus, wood decayed
by brownb rot fungi, such as Rhodonia (=Postia )placenta , contains rich iron (Ostrofsky et al. 1997). Since Fe
(III) ions react easily to form chemical bonds with phosphorus ions,
forming iron phosphate (FePO4), the result is that P is
absorbed on the surface of the hydrous Fe (III) oxide fine particles,
which are insoluble in water and not directly available to plants
(Nanzyo et al. 2004). However, AM fungi are capable of using iron
phosphate and making it available to host plants (Bolan and Robson
1987). Although iron ion concentration was not measured in this study,
such a unique iron ion condition in brown rot logs might benefit AM
trees in their nutrition. Our preliminary investigation into bacterial
communities in deadwood found predominant OTUs of iron-reducing
bacteria, Aciditerrimonas sp., in brown-rot logs but not in white
rot logs and soil (data not shown), indicating that iron may play a role
in the biotic systems in brown rot logs. This new hypothesis should be
further evaluated by field and laboratory experiments.
Another explanation for the better growth and survival of AM tree
seedlings on brown rot logs might be their high water content (Fig. 2).
It is known that wood decayed by brown-rot fungi significantly increases
its water absorption capacity (Karppanen et al. 2008). Water content
certainly had positive effects not only on growth and survival but also
on germination of AM trees (Clethra , Cryptomeria ,Padus , Toxicodendron ) and ECM trees (Abies ,Pinus , Betula ) (Table 4, 6). Since the seed-sowing
experiments were conducted in the field, we cannot separately evaluate
the effects of AM fungi and water content on tree seedlings.
Nevertheless, in laboratory pot experiments where water conditions were
standardized across substrates, we also reported that the AM
colonization rate of Cryptomeria seedlings was higher in brown
rot wood than in white rot wood (Fukasawa and Kitabatake 2022). Thus,
the rich AM fungal community in brown rot logs might be crucial for the
better seedling performance on bworn rot logs, at least forCryptomeria seedlings. Water content has been rarely compared
between brown rot and white rot logs previously, and it is not certain
if brown rot logs are always wetter than white rot logs. White rot beech
logs contain a high amount of water when they are well-decayed in the
woods (Fukasawa et al. 2009).
In contrast to the better performance of AM tree seedlings on brown rot
logs and soil compared to white rot logs, we detected a positive effect
of white rot on seedling survival of ECM trees compared with brown rot
(Table 5). However, significant difference was not observed in any
certain ECM trees (Fig. 6). Furthermore, the colonization rate of ECM
fungi was not larger on white rot logs than on brown rot logs, except
for Abies and Betula (Fig. 7), rather larger on brown rot
logs than white rot logs in Pinus seedlings. Similarly, the OTU
richness of ECM fungi was the smallest in white rot logs (Fig. 4). These
results indicated that the effect of substrates on ECM seedling
performance was less consistent across the seedling species compared
with AM trees, and thus it is not clear why the survival of ECM tree
seedlings tended to be higher on white rot logs in this site. One
possible explanation is the positive effect of pH on ECM tree seedlings
(Table 4, 6). Although it was not survival but germination and growth,
wood pH was positively associated with the dry weight of Abiesand Pinus seedlings, shoot length of Pinus seedlings, and
germination of Picea seedlings (Table 6). Such a positive effect
of pH was not observed in AM tree seedlings, rather it was negative on
their germination (Table 4). Although wood pH was not significantly
different between brown rot and white rot logs in the present study, it
was known that brown rot logs have a lower pH than white rot logs
because brown rot fungi produce organic acids such as oxalic acid during
their wood decay process (Espejo and Agosin 1991; Fukasawa and
Kitabatake 2022). Thus, the positive relationships between wood pH and
ECM tree seedlings were in line with our hypothesis that ECM tree
seedlings show better regeneration on white rot logs than on brown rot
logs. However, the reason why wood pH affects positively on seedling
germination of ECM trees but affects negatively on seedling germination
of AM trees is not clear. One possible explanation is the indirect
effects of pH and wood chemical quality on biotic interactions across
plants, mycorrhizal fungi, and associated bacterial communities. Recent
studies have reported that rhizosphere bacterial communities are
important for the functioning of both AM (Sawada et al. 2023; Xu et al.
2023) and ECM (Wang et al. 2022) fungi on host plants, and such
interactions are strongly influenced by litter chemistry and
litter-mediated soil properties (Heděnec et al. 2023).
All 12 tree species used in the present study were reported to
frequently regenerate as seedlings on decaying logs (Fukasawa 2021).
However, none of the tree species showed better performance on the logs
(regardless of brown rot or white rot) compared to the soil in the
present study. This is probably because some of the advantages on
germinating and growing on the logs were reduced in this study. For
example, the accumulated thick litter layer on the ground, which
prevents the germination and growth of small seedlings, was removed, and
bare soil was prepared for seeds. In addition, light condition (canopy
openness) was not significantly different among the microsites. Although
the water content of soil was significantly lower than that of brown rot
logs, such difference might not be critical for seedling performance in
the present study, at least, not detrimental to seedling performance on
soil. Furthermore, the OTU richness of plant pathogenic fungi was not
significantly different among the three microsites (Fig. 4), and
negative effects of plant pathogenic fungi on seedling performance on
soil (Cheng and Igarashi 1987; O’Hanlon-Manners and Kotanen 2004) were
not observed in the present study, probably attributable to the dry soil
of the study site. In line with the previous studies, concentrations of
nutrients such as potassium and chloride ions were higher in white rot
logs (Fukasawa et al. 2017; Ostrofsky et al. 1997; Takahashi et al.
2000) than in brown rot logs and soil. However, remarkable effects of
nutrients on seedling performance were not observed. These results
suggest that the difference in nutrient condition among brown rot logs,
white rot logs, and soil might not be the primary factor determining
seedling performance on those substrates.
The present study comprehensively evaluated the abiotic and biotic
factors associated with decaying logs of different decay types and soil
in relation to tree seedling regeneration. The results indicated that
seedlings of AM trees showed better growth on brown rot logs than on
white rot logs, which was in line with previous field data and supported
our hypothesis. This association might be at least partly attributable
to rich communities of AM fungi in brown rot logs. In contrast, ECM tree
seedlings tended to survive better on white rot logs and soil compared
to brown rot logs, supporting our hypothesis, but the tendency was less
consistent across the six AM trees tested, and the mechanism was not
clear. Further analysis of other groups of microbes such as bacteria may
be valuable for exploring biotic mechanisms of seedling regeneration on
logs of different decay types and soil. Additionally, evaluating
seedling performance on these microsites for a larger number of tree
species is necessary to reach more general conclusions. Furthermore,
laboratory pot experiments with standardized water conditions and
substrate sterilization are needed to evaluate the importance of abiotic
factors for seedling performance.
References
Araya K (1993) Relationship between the decay types of dead wood and
occurrence of Lucanid beetles (coleoptera: lucanidae). Appl Entomol Zool
28: 27–33.
Averill C, Turner BL, Finzi AC (2014) Mycorrhiza-mediated competition
between plants and decomposers drives soil carbon storage. Nature 505:
543–545.
Bayandala, Fukasawa Y, Seiwa K (2016) Roles of pathogens on replacement
of tree seedling in heterogeneous light environments in a temperate
forest: a reciprocal seed sowing experiment. J Ecol 104: 765–772.
Bolan NS, Robson AD (1987) Effects of vesicular-arbuscular mycorrhiza on
the availability of iron phosphates to plants. Plant and Soil 99:
401–410.
Burnham KP, Anderson DR (2002) Model selection and multimodel inference:
a practical information-theoretic approach. 2nd ed.
New York, Springer-Verlag.
Chao A, Ma KH, Hsieh TC. 2016. iNEXT (iNterpolation and EXTrapolation
Online: Software for Interpolation and Extrapolation of Species
Diversity. Program and User’s Guide published at
http://chao.stat.nthu.edu.tw/wordpress/software_download/.
Cheng D, Igarashi T (1987) Fungi associated with natural regeneration ofPicea jezoensis Carr. in seed stage – their distribution on
forest floors and pathogenicity to the seeds. Res Bull Coll Exp For Fac
Agric Hokkaido Univ 44:175-188.
Christie DA, Armesto JJ (2003) Regeneration microsites and tree species
coexistence in temperate rain forest of Chiloé Island, Chile. J Ecol 91:
776–784.
Eaton RA, Hale MDC (1993) Wood: decay, pests and protection. Chapman &
Hall.
Espejo E, Agosin E (1991) Production and degradation of oxalic acid by
brown rot fungi. Applied Environmental Microbiology , 57,
1980–1986.
Faraway, J.J. (2006) Extending the linear model with R: Generalized
linear, mixed effects and nonparametric regression models. Chapman &
Hall/CRC, Boca Raton, pp. 25–54, pp. 115–133.
Filion M, St-Arnaud M, Fortin JA (1999) Direct interaction between the
arbuscular mycorrhizal fungus Glomus intraradices and different
rhizosphere microorganisms. New Phytologist 141: 525–533.
Fukasawa Y (2012) Effects of wood decomposer fungi on tree seedling
establishment on coarse woody debris. Forest Ecology and
Management , 266, 232–338
Fukasawa Y (2021) Ecological impacts of fungal wood decay types: a
review of current knowledge and future research directions. Ecol Res 36:
910–931
Fukasawa Y, Ando Y (2018) Species effects of bryophyte colonies on tree
seedling regeneration on coarse woody debris. Ecol Res 33: 191–197.
Fukasawa Y, Kitabatake H (2022) Which is the best substrate to
regenerate? A comparative pot experiment for tree seedling growth on
decayed wood and in soil. Forests 13: 1036.
Fukasawa Y, Komagata Y (2017) Regeneration of Cryptomeria
japonica seedlings on pine logs in a forest damaged by pine wilt
disease: effects of wood decomposer fungi on seedling survival and
growth. Journal of Forest Research 22: 375–379.
Fukasawa Y, Osono T, Takeda H (2009) Dynamics of physicochemical
properties and occurrence of fungal fruit bodies during decomposition of
coarse woody debris of Fagus crenata . J For Res 14: 20–29.
Fukasawa Y, Komagata Y, Ushijima S (2017) Fungal wood decomposer
activity induces niche separation between two dominant tree species
seedlings regenerating on coarse woody debris. Canadian Journal of
Forest Research , 47, 106–112.
Harmon ME, Franklin JF (1989) Tree seedling on logs in Picea-Tsuga
forest of Oregon and Washington. Ecology 70: 48–59.
Heděnec P, Zheng H, Siqueira DP, Lin Q, Peng Y, Schmidt IK, Frøslev TG,
Kjøller R, Rousk J, Vesterdal L (2023) Tree species traits and
mycorrhizal association shape soil microbial communities via litter
quality annd species mediated soil properties. For Ecol Manage 527:
120608.
Hoppe B, Krüger D, Kahl T, Arnstadt T, Buscot F, Bauhus J, Wubet T
(2015) A pyrosequencing insight into sprawling bacterial diversity and
community dynamics in decaying deadwood logs of Fagus sylvaticaand Picea abies . Scientific Reports 5: 9456.
Iijima H, Shibuya M (2010) Evaluation of suitable conditions for natural
regeneration of Picea jezoensis on fallen logs. J For Res 15:
46–54.
Karppanen O, Venäläinen M, Harju AM, Laakso T (2008) The effect of
brown-rot decay on water adsorption and chemical composition of Scots
pine heartwood. Ann For Sci 65: 610.
Kauserud H (2023) ITS alchemy: on the use of ITS as a DNA marker in
fungal ecology. Fung Ecol 65: 101274.
Lusk CH (1995) Seed size, establishment sites and species coexistence in
a Chilean rain forest. J Veg Sci 6: 249–256.
Marx LM, Wakters MB (2006) Effects of nitrogen supply and wood species
on Tsuga canadensis and Betula alleghaniensis seedling
growth on decaying wood. Can J For Res 36: 2873–2884.
McGonigle TP, Miller MH, Evans DG, Fairchild GL, Swan JA (1990) A new
method which gives an objective measure of colonization of roots by
vescular-arbuscular mycorrhizal fungi. New Phytologist 115: 495–501.
Mori A, Mizumachi E, Osono T, Doi Y (2004) Substrate-associated seedling
recruitment and establishment of major conifer species in an old-growth
subalpine forest in central Japan. For Ecol Manage 196: 287–297.
Nanzyo M, Kanno H, Obara S (2004) Effects of reducing conditions on P
sorption of soils. Soil Science and Plant Nutrition 50: 1023–1028.
O’Hanlon-Manners DL, Kotanen PM (2004) Logs as refuges from fungal
pathogens for seeds of eastern hemlock (Tsuga canadensis ).
Ecology 85:284–289
Oksanen, J., Blanchet, F.G., Kindt, R., Legendre, P., Minchin, P.R.,
O’Hara, R.B., et al. (2016) Vegan: Community Ecology Package. R
package version 2.3.4. https:// cran.r-project.org/package=vegan.
Orman O, Adamus M, Szewczyk J (2016) Regeneration processes on coarse
woody debris in mixed forests: do tree germinants and seedlings have
species-specific responses when grown on coarse woody debris? J Ecol
104: 1809–1818.
Ostrofsky A, Jellison J, Smith KT, Shortle WC (1997) Changes in cation
concentrations in red spruce wood decayed by brown rot and white rot
fungi. Canadian Journal of Forest Research 27: 567–571.
Papaik MJ, Canham CD (2006) Species resistance and community response to
wind disturbance regimes in northern temperate forests. J Ecol 94:
1011–1026.
Rajala, T., Peltoniemi, M., Hantula, J., Mäkipää, R., & Pennanen, T.
(2011). RNA reveals a succession of active fungi during the decay of
Norway spruce logs. Fungal Ecology , 4, 437–448.
Rajala, T., Peltoniemi, M., Pennanen, T., & Mäkipää, R. (2012). Fungal
community dynamics in relation to substrate quality of decaying Norway
spruce (Picea abies [L.] Karst.) logs in boreal forests.FEMS Microbiology Ecology , 81, 494–505.
Rajala, T., Tuomivirta, T., Pennanen, T., & Mäkipää, R. (2015). Habitat
models of wood-inhabiting fungi along a decay gradient of Norway spruce
logs. Fungal Ecology , 18, 48–55.
Rosseel Y (2012) Lavaan: an R package for structural equation modeling.
Journal of Statistical Software 48: 1–36.
Sanchez E, Gallery R, Dalling JW (2009) Importance of nurse logs as a
substrate for the regeneration of pioneer tree species on Barro Colorado
Island, Panama. J Trop Ecol 25: 429–437.
Sawada K, Inagaki Y, Sugihara S, Kunito T, Murase J, Toyota K, Funakawa
S (2023) Conversion from natural coniferous forests to cedar plantations
increase soil nitrogen cycling through changing microbial community
structures. Applied Soil Ecology 191: 105034.
Seiwa K, Negishi Y, Eto Y, Hishita M, Masaka K, Fukasawa Y, Matsukura K,
Suzuki M (2020) Successful seedling establishment of arbuscular
mycorrhizal-compared to ectomycorrhizal-associated hardwoods in
arbuscular cedar plantations. Forest Ecology and Management 468: 118155.
Smith SE, Read DJ (2008) Mycorrhizal symbiosis. Third edition. Academic
Press, Cambridge, USA)
Steidinger BS, Crowther TW, Liang J et al. (2019) Climatic controls of
decomposition drive the global biogeography of forest–tree symbiosis.
Nature 569: 404–408.
Tedersoo, L., Suvi, T., Jairus, T., & Kõljalg, U. (2008). Forest
microsite effects on community composition of ectomycorrhizal fungi on
seedlings of Picea abies and Betula pendula .Environmental Microbiology , 10, 1189–1201.
Wulantuya, Masaka K, Bayandala, Fukasawa Y, Matsukura K, Seiwa K (2020)
Gap creation alters the mode of conspecific distance-dependent seedling
establishment via changes in the relative influence of pathogens and
mycorrhizae. Oecologia 192: 449–462.
Xu Y, Chen Z, Li X, Tan J, Liu F, Wu J (2023) The mechanism of promoting
rhizosphere nutrient turnover for arbuscular mycorrhizal fungi
attributes to recruited functional bacterial communities. Molecular
Ecology 32: 2335–2350.
Wang YH, Hou LL, Wu XQ, Zhu ML, Dai Y, Zhao YJ (2022) Mycorrhiza halper
bacterium Bacillus pumilus HR10 improves growth and nutritional
status of Pinus thunbergii by promoting mycorrhizal
proliferation. Tree Physiology 42: 907–918.
Figure captions