Next Article in Journal
Effects of Light Intensity and Girdling Treatments on the Production of Female Cones in Japanese Larch (Larix kaempferi (Lamb.) Carr.): Implications for the Management of Seed Orchards
Previous Article in Journal
A Design for Addressing Multiple Ecosystem Services in Forest Management Planning
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Forests
Volume 11
Issue 10
10.3390/f11101109
forests-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Soil Fungal Communities under Pinus patula Schiede ex Schltdl. & Cham. Plantation Forests of Different Ages in Ethiopia

by
Demelash Alem
1,2,
Tatek Dejene
2,
Juan Andrés Oria-de-Rueda
1,
József Geml
3,4 and
Pablo Martín-Pinto
1,*
1
Sustainable Forest Management Research Institute, University of Valladolid (Palencia), Avda. Madrid 44, 34071 Palencia, Spain
2
Ethiopian Environment and Forest Research Institute, Forest Products Innovation Research Directorate, P.O. Box 24536, 1000 Addis Ababa, Ethiopia
3
Biodiversity Dynamics Research Group, Naturalis Biodiversity Center, Darwinweg 2, P.O. Box 9517, 2300 RA Leiden, The Netherlands
4
MTA-EKE Lendület Environmental Microbiome Research Group, Eszterházy Károly University, Leányka u. 6, H-3300 Eger, Hungary
*
Author to whom correspondence should be addressed.
Forests 2020, 11(10), 1109; https://doi.org/10.3390/f11101109
Submission received: 3 September 2020 / Revised: 11 October 2020 / Accepted: 14 October 2020 / Published: 19 October 2020
(This article belongs to the Section Forest Ecology and Management)
Browse Figures
Versions Notes

Abstract

:
The cultivation of plantation forests is likely to change the diversity and composition of soil fungal communities. At present, there is scant information about these communities in Ethiopian plantation forest systems. We assessed the soil fungal communities in Pinus patula Schiede ex Schltdl. & Cham. stands aged 5, 11, or 36-years-old using DNA metabarcoding of ITS2 amplicons. The ecological conditions of each plot, such as climate, altitude, and soil, were similar. Stand age and soil fertility influenced soil fungal species diversity and ecological guilds. In total, 2262 fungal operational taxonomic units were identified, of which 2% were ectomycorrhizal (ECM). The diversity of ECM fungi was higher in the 5 and 36-year-old stands than in the 11-year-old P. patula stands. Contrary to our expectations, a high level of ECM species diversity was observed in young stands, suggesting that these ECM species could compensate for the effects of nutrient stress in these stands. Our results also suggested that the abundance of plant pathogens and saprotrophs was not affected by stand age. This study provides baseline information about fungal community changes across tree stands of different ages in P. patula plantations in Ethiopia that are likely related to ECM fungi in young stands where relatively low soil fertility prevails. However, given that the plots were established in a single stand for each age class for each treatment, this study should be considered as a case study and, therefore, caution should be exercised when applying the conclusions to other stands.

1. Introduction

A recent review of forestry in Ethiopia revealed that deforestation is a continuous process [1]. When all forest use was included, a deforestation rate of 0.93% per year was calculated in 2010 [2,3]. Despite this, establishing plantations of fast-growing exotic tree species is becoming a major part of forestry practice in Ethiopia [4,5]. Exotic tree species plantations are now estimated to cover 1,000,000 ha of land [5,6]. One of these introduced tree species is Pinus, which is mainly being grown to meet the increasing demand for woody raw materials [6,7,8]. As a consequence, Pinus patula Schiede ex Schltdl. & Cham. has received attention largely as a suitable tree for the production of round wood (timber), poles, and posts [5,9], although it also used as a source of resin and turpentine oil constituents [10].
Soil fungi drive many ecosystem processes and, hence, are a vital part of the soil microbial community [11,12]. Pinus trees form obligate symbiotic relations with mycorrhizal fungi, which are vital for host nutrition, survival and productivity in forest systems [13]. Root associations with mycorrhizal fungi are beneficial for most plants because they not only increase their access to nutrients and water in the soil but also enhance their stress tolerance [14]. Similarly, mutualistic fungi use carbohydrates from the host tree for their survival [15]. Mycorrhizal associations also increase host tree resistance to pathogens [16,17]. Previous studies have also reported that there tends to be a greater accumulation of organic matter belowground in forests with ectomycorrhizal (ECM) associations than in other forests [18,19]. Furthermore, decomposition in forests is often limited by competition for nitrogen (N) between ECM and free-living saprotrophic fungi [18,20,21]. Mycorrhizal fungi mediate interactions between plants and other soil microorganisms, such as pathogens and mycorrhizosphere mutualists that produce vitamins, and provide protection against antagonists [14]. Saprotrophic fungi also play a crucial role in the decomposition of organic materials [22]. Thus, knowledge of fungi and their community structure in the soil of plantation forests are important because the trees and fungal synergies could determine many vital ecosystem services such as nutrient cycling [23].
The composition and structure of fungal communities are affected by diverse interacting biotic and abiotic factors [11,23], including host plant succession [24,25,26]. As a forest develops, the composition of the associated fungal communities also changes [27,28]. For example, early-stage fungi emerge from spores in the spore bank that were already in the soil prior to the establishment of the plantation, whereas late-stage fungi are more prevalent as conditions change as the plantation matures [29]. Both early- and late-stage fungi are involved in the stabilization of the soil and the rehabilitation of soil microflora [30]. Furthermore, changes in edaphic variables due to forest growth affect the abundance and diversity of soil fungi and, thereby, dictate the fungal community composition [31,32]. Previous studies have assessed changes in soil fungal communities across stand ages by performing DNA analyses [33,34] and fruit body surveys [35]. We have also previously shown that the fungal community composition differs at different stages of forest development in Ethiopian forests [8,24,36].
Ethiopian fungal flora remains unexplored, as most regions and habitats in the country have been seldom studied and reports regarding fungi diversity rarely exist. This is due to a lack of research infrastructures as well as to a lack of fungal taxonomists and specialists in fungal ecology. Likely as a result, fungi are not included in the biodiversity database of the country. Previous studies conducted on Pinus tree species in Ethiopia have focused on ways to assist the management and development of Pinus plantations. However, studies on the soil microbial community, including fungi associated with Pinus plantations, are very limited. Sporocarps associated with a P. patula plantation during a single rainy season have previously been reported [8]. Although sporocarps represent a unique step in the complex life of fungi [8], they do not reflect the entire soil biota [37,38]. However, the maintenance of a vital soil biota is essential for many woodland ecosystems because energy reaches the forest floor mainly through the degradation of organic matter and the recycling of vital elements found in animal and plant remains [24,39]. Furthermore, a rich soil biodiversity guarantees the presence of vital habitats, the integrity of the soil structure and water-holding capacity, soil fertility, and plant growth [40]. In the present study, we sampled soil from different age groups of P. patula plantations. We hypothesized that, as stand age increased, soil fertility would decrease. In addition, we expected that soil would become increasingly colonized by roots and associated symbionts and, hence, that root-associated fungal species would be more dominant in soils in older P. patula stands than in younger stands. Thus, in older stands, there is more organic matter and lower N than other edaphic elements. Given the potential changes in edaphic variables with increasing stand age [41], we expected that changes in the soil fungal community would also occur. Thus, the main aim of this study was to provide baseline information about the soil fungal communities that occur along a chronosequence of P. patula plantations in Ethiopia. We hypothesized that substantial change in the composition of soil fungal communities would be detected along the chronosequence of P. patula plantations. Specifically, we hypothesized that: (1) there would be changes in the total fungal diversity and community composition, and (2) that the ecological guilds would change along the chronosequence of P. patula plantations in the study area.

2. Materials and Methods

2.1. Study Area

The study was conducted in P. patula stands in Wondo Genet, Ethiopia. Wondo Genet is approximately 265 km from the Ethiopian capital, Addis Ababa (Figure 1). The study site ranged from 7°06′ North to 7°07′ North and from 38°37′ East to 38°42′ East, and was 1600 to 2580 meter (m) above sea level [42,43]. The climate of the study area is characterized by the Woyna Dega agro-climatic zone, which has a bimodal rainfall pattern: a rainy season in spring followed by the main rainy season in summer, with a mean annual rainfall of 1210 millimeter (mm) [43,44]. The mean annual temperature is 20 °C [43,44]. The study area has a slightly undulating topography and an Andisol soil with a sandy loam texture [45] that has an average pH value of 5.7 [46].
The native vegetation that originally grew in the study area was destroyed before the inception of the nearby college of forestry (1976) by logging and clearance for cultivation [10]. However, in recent decades, a mass planting scheme of exotic tree species has been undertaken, resulting in approximately 100 ha of non-native plantations of Cupressus lusitanica Mill., Grevillea robusta A. Cunn. ex R.Br., and P. patula in the study area [10,47]. In P. patula plantations, stands of three different ages (i.e., 5, 11, and 36-years-old) were selected and three 2 × 50 m plots were established in each stand age category [27,29], with a minimum distance of approximately 120 m between plots within a stand [28]. All plots were similar in terms of their ecological conditions such as climate, altitude, and soil.
The three stands were far enough apart (minimum 4 km) that they are not interacting and they could be clearly differentiated with the silvicultural treatments applied to them. For example, weeding and slashing were conducted for the 5 and 11-year-old stands while thinning was applied for the 36-year-old stands in the study area [8].

2.2. Collection of Soil Samples for Molecular Analysis

In total, nine transects, one in each of the 2 × 50 m plots, running perpendicular to the slope, were established [28,48]. Five cores 5 m apart were extracted along the centerline of each transect using a cylindrical soil borer (2 cm radius, 20 cm deep, and 250 cm3) [49] to collect samples with spatial variability while minimizing the likelihood of repeatedly sampling the same genet. Before these cores were sampled, the litter layer, which comprised intact and partially decomposed leaves, was removed because the fungal community in leaves tends to differ from that in soil [50]. The five cores from each transect, comprising well-decomposed organic layers and mineral soils, were pooled to produce a composite soil sample of each transect. Next, the cores were dried, sieved through a 1-mm mesh and then ground to a fine powder using a mortar and pestle. A subsample of each composite sample was stored at −20 °C while awaiting molecular analysis.

2.3. Molecular Analysis

A PowerSoil™ DNA Isolation Kit (MoBio laboratories Inc., Carlsbad, CA, USA) was used to extract DNA from 0.25 g of soil per sample. PCR reactions of each sample were carried out in triplicate to minimize PCR biases. PCR reactions were performed in 20 μL reaction volumes containing 11.22 μL of Modified Quantization (MQ) water, 1.60 μL of DNA template, 2.00 μL of 10× buffer, 1.40 μL of MgCl2 (50 mM), 1.60 μL of dNTPs (10 mM), 0.50 μL of Bovine Serum Albumin (BSA) (2%), 0.80 μL of reverse and forward primers (10 μM), and 0.08 μL of Platinum Taq polymerase (Invitrogen, Carlsbad, CA, USA). The following PCR conditions were used: an initial denaturation step at 94 °C for 3 min; then 35 cycles of 94 °C for 45 s, 50 °C for 1 min, and 72 °C for 1.5 min; ending with one cycle of 72 °C for 10 min. To amplify the ITS2 rDNA region, we used the forward primer fITS7 [51] and the barcoded reverse primer ITS4 [52]. Sample-specific Multiplex Identification DNA-tags were used to label the ITS4 primer. Each set of PCR replicates also included a negative control comprising MQ water instead of DNA that underwent PCR under the same experimental conditions and was shown to be amplicon-free on a gel. Ion torrent sequencing was performed at the Naturalis Biodiversity Center using the sequencing Ion 318TM Chip to obtain the greatest possible sequencing coverage.

2.4. Collection of Soil Samples for Chemical Analysis

To examine the relationship between soil fungal composition and edaphic variables, soil samples were extracted from the center and the four corners of every plot after removing plant material and debris from the surface. Soil down to a depth of 20 cm was extracted using an auger and spade. The samples were mixed thoroughly to create a composite sample before placing approximately 500 g of soil in a plastic bag for laboratory analysis. After air-drying the soil in the shade, standard extraction methods (i.e., diethylene triamine pentaacetic acid extraction, KH2PO4 extraction, Olsen, Kjeldahl digestion Walkley Black, and ammonium acetate) and instrumental analysis were used to determine the pH, organic matter, cation exchange capacity, sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), N, available phosphorus (P), and the physical properties (% of sand, silt, and clay) of the soil.
Soil analysis was conducted by Water Works Design and Supervision Enterprises, Laboratory Service Subprocess, Soil Fertility Section at Addis Ababa, Ethiopia. Soil pH and electrical conductivity were determined by analyzing a soil:water (1:2.5) suspension and the supernatant from the same suspension with the aid of a pH meter and an electrical conductivity meter, respectively [53]. The organic carbon content of the soil was determined using wet digestion [54]. The Kjeldahl procedure was used to determine the total N content in soils [55]. Sodium bicarbonate (0.5 M NaHCO3) was used as an extraction solution to determine the available P [56]. Available Na, available K, Ca, and Mg were also determined. To assess soil particle size we used a hydrometer [57] and sodium hexametaphosphate (Calgon solution) was used as a dispersing agent. After calculating the proportions of sand, silt, and clay, the soil was assigned a textural class name using ASTM free software, Version 4, Available: http://www.astm.org. The results of the soil analysis are presented in Table 1.

2.5. Bioinformatic Analysis

Raw sequence reads comprising demultiplexed sample reads were obtained from the Ion Torrent output. Primers and poor-quality ends were removed based on a 0.02 error probability limit in Geneious Pro 8.1.8 (BioMatters, Auckland, New Zealand). Next, all sequences were truncated to 200 bp and then filtered with USEARCH v.8.0 [58] to discard sequences with an expected error of >1. The remaining sequences were collapsed into unique sequence types on a per-sample basis using USEARCH v.8.0 [58] while preserving read counts. First, we discarded singleton sequence types before grouping the remaining 187,332 high-quality sequences into 2262 operational taxonomic units (OTUs) with USEARCH at a 97% sequence similarity level while simultaneously excluding 3161 sequences representing 67 OTUs with <70% similarity or <150 bp pairwise alignment length to a fungal sequence. Sequences were assigned to taxonomic groups based on pairwise similarity searches against the curated UNITE+INSD fungal ITS sequence database, which contains identified fungal sequences with assignments to species hypothesis groups [59]. The FUNGuild database (http://www.funguild.org) was initially used to perform functional classification of OTUs at the genus level and it was manually checked afterwards. OTUs with >90% similarities to a fungal SH with known ecological function were assigned either to plant pathogens, mycoparasites, animal parasite, ECM fungi, arbuscular mycorrhizal, and saprotrophs functional groups. For genera that are known to comprise species from multiple functional guilds, their ecological function was assigned individually based on available ecological information for the matching SH in the UNITE database.

2.6. Statistical Analysis

To normalize the OTU table for subsequent statistical analyses, we rarefied the number of high-quality fungal sequences to the smallest library size (1951 reads). The resulting matrix contained 1216 fungal OTUs representing 17,559 high-quality sequences. Thus, the analyses used sequence read abundance data, which is not necessarily equivalent to true biological abundance. Shannon’s diversity index, H = −Σpi(lnpi) [60], was estimated for each stand, where pi indicates the relative abundance of fungal OTUs [61]. We also calculated Simpson’s diversity, D = 1 − Σ (pi2), where pi is the importance probability in element i, and the Evenness, J = H′/H′max, where H′ is the number derived from the Shannon diversity index and the H’max is the maximum possible value of H’ [62]. We also estimated the richness values of all fungal OTUs (S) based on stand type. The Biodiversity RGUI package [63] in R was used to calculate all the diversity measures [64], such as diversity indices and richness.
Ordination of community data was carried out by performing detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) using CANOCO version 5.0 [65] based on a Hellinger-transformed abundance data matrix. The relative sequence read abundance contribution of each ecological group to community composition was assessed using the relative abundance of the fungal OTUs. A Monte Carlo Permutation test was used to test the statistical significance of the environmental variables (999 permutations). Correlation between the CCA axes scores and edaphic variables were assessed using linear regression. We also tested whether fungal compositions were statistically different across forest stands of different ages using the multiple-response permutation procedure (MRPP) and permutation-based nonparametric MANOVA (PerMANOVA) [66]. Data were subjected to 4999 iterations per run using the Sørensen similarity (Bray–Curtis index) and a random number to start. To identify which fungal species were most responsible for the patterns observed and to calculate the percentage contribution of fungal taxa to significant dissimilarities among the three stands, we undertook an analysis of similarity percentages (SIMPER) [67,68].

3. Results

3.1. Diversity of Fungal OTUs

A total of 187,332 high-quality sequences were grouped into 2262 OTUs. We obtained between 1951 and 37,245 high-quality reads from each sample. The OTUs were assigned to six fungal phyla. The majority of the OTUs belonged to the Ascomycota (58%), followed by the Basidiomycota (26%). The Chytridiomycota, Glomeromycota, Rozellomycota, and Zygomycota made up to 4%, 3%, 1% and 2% of the total OTUs, respectively, and approximately 7% of OTUs were not assigned to a fungal phylum.
Saprotrophs were the most abundant species found in P. patula plantations, comprising 41% of the fungal community, followed by plant pathogens (7%) and ECM species (2%). Less abundant groups were categorized as animal parasites, arbuscular mycorrhizal fungi, mycoparasites, and endophytes. These groups were excluded from further analysis. About 48% of the species were not categorized into any of these functional groups.
The highest mean values for Shannon and Simpson diversity indices for the ECM and saprotrophic fungi were found in 5-year-old stands. Contrary trend was observed for plant pathogens which showed higher diversity in 36-year-old stands. On the other hand, the estimated evenness values of the ECM (range 0.24 to 0.30), plant pathogens (range 0.21 to 0.24), and saprotrophic fungi (range 0.12 to 0.25), showed that each functional groups distributed uniformly in each of the three stands.
The relative abundance of ECM fungi was greater in the 11-year-old P. patula stand, whereas the plant pathogens obtained higher mean values in the 5-year-old stands. By contrast, the relative abundances of saprotrophic fungi were homogeneous along the chronosequence of P. patula stands.

3.2. Fungal Community Composition and Edaphic Variables

PerMANOVA analyses indicated that the composition of fungal OTUs in stands of different ages were significantly different (F = 2.76, p = 0.013). MRPP tests also confirmed that the plantation age effect was significant, with a distance effect size of A = 0.017 and p = 0.006. More specifically, the composition of 5 and 36-year-old stands differed from the 11-year-old stand, as indicated by the Sørensen average distance measures (Table 2). In addition, SIMPER analysis indicated that the overall between-group dissimilarity based on Bray-Curtis measures was 76.09% for the 5 and 11-year-old stands, 77.67% for the 5 and 36-year-old stands and 83.58% for the 11 and 36-year-old stands (Table S1).
From the canonical correspondence analysis (CCA) (Figure 2), the eigenvalues indicated that the variability in terms of fungal guild composition, explained by the gradients associated with the first two axes, is high. Together they explained 29.47% of the accumulative variance of fungal guild data. With respect to the edaphic variables, potassium (K) and magnesium (Mg) correlated the most strongly with fungal community composition (Figure 2). The correlation of these edaphic variables with CCAs was evident based on fungal guild Hellinger-transformed abundance data (Table 3).
Compared with the 5 and 36-year-old stands, we found that a relatively greater proportion of the ECM guild was associated with the 11-year-old stand. By contrast, the saprophytes, mycoparasites, and animal parasites were mainly found associated with the 5- and 36-year-old stands. Based on the cumulative contribution to the dissimilarity of stands, the SIMPER analysis also identified fungal species that typified and distinguished between the soil fungal communities associated with the three P. patula plantation age groups (Table S1). Wilcoxina sp., Schizothecium sp., and Pustularia sp. were among the most influential species detected in the soil analyses and cumulatively made the greatest contribution to the differences observed between the three stands, accounting for more than 38.63% of the observed dissimilarity value (Table S1).
When ECM fungi were analyzed separately, the simple term effects in CCA (Figure 3b) revealed that plantation age and the soil fertility variable P significantly influenced the composition of the ECM fungal community in the forest study area (Table 4). The CCA revealed that both axes explained about 45.82% of the cumulative variation in interactions between ECM fungal composition, soil fertility variables and plantation age. The PerMANOVA analysis also indicated that there were species compositional differences between stands in terms of ECM fungi (F = 3.21, p = 0.003).
Several species belonging to the orders Gomphales, Sebacinales, and Thelephorales were associated with plots in the oldest stand, where the soil is characterized by relatively high fertility (based on the organic matter content and the C/N ratio). In 5 and 11-year-old stands, which are characterized by low soil fertility (based on organic matter content and the C/N ratio), the species belonging to the order Cantharellales formed an association with other fungal species (Figure 3). Species in the orders Boletales, Pezizales and Agaricales were associated with all age groups of P. patula plantations (Figure 3).

4. Discussion

4.1. Diversity of Fungal OTUs

Fungi have been described as the most interesting, enigmatic and species-rich organisms on Earth [69]. The use of molecular methods in recent years has dramatically increased the number of fungal OTUs detected worldwide [70]. In this study, we detected a total of 2262 high-quality OTUs, of which 1303 OTUs (58%) belonged to the Ascomycota, the largest phylum of fungi [71], indicating the dominance of Ascomycota in the P. patula forests investigated in this study. Fungi often interact with other organisms, forming beneficial or mutualistic associations. Conifers in the Pinaceae usually form symbiotic relationships with ECM fungi. Thus, ECM fungi were likely to play an important role in the P. patula plantations in our study area. However, of the total OTUs identified at genus level and classified by ecological function, 41% were saprotrophs, 7% were plant pathogens, and only 2% were ECM fungi. An explanation for the small proportion of ECM fungi detected might be that the plantation area was located in a non-ECM biome area. The native vegetation that originally grew in the study area was destroyed many years ago by logging and clearance for crop cultivation [10]. Therefore, fungal symbionts compatible with P. patula may be absent in the native fungal community in the soil, enabling ECM fungi introduced to the plantation area along with P. patula to co-invade the soil habitat [72]. However, the ecological function of 48% of the fungi identified in this study is unknown, indicating that we have hardly scratched the surface in terms of understanding the role played by fungi in these plantation forest systems. It might also an indication for the lack of scientific studies on the local fungal flora in the country. Thus, they are highlighting the need for further studies in the study area.

4.2. Diversity of Functional OTUs along the Chronosequence of Stands

The Shannon and Simpson diversity indices were determined to explain variations in the soil fungal functional groups at different stages of P. patula stand development. Only ECM fungi showed differences in their diversity among the stand age groups. Initially, we expected that as stands developed, soil fertility would decrease over time and that these conditions would lead to higher ECM fungal diversity along the chronosequence. By contrast, the soil fertility of young P. patula stands was expected to be higher than that of old stands and, therefore, the trees were expected to exert less influence on the fungal microbiome. However, our investigations revealed that the 5 and 36-year-old stands had more diverse ECM fungi in their soils than the 11-year-old stand and were more fertile. Despite this, the relative proportion of ECM abundance was higher in the 11-year-old stand than in the 5 and 36-year-old stands due to the dominance of some ECM species in the 11-year-old stand.
Soil microorganisms, including fungi, are influenced by stand development in several ways [73,74]. As the stand develops, the amount of tree cover directly modifies the amount of light available, which affects the composition of the understory, which regulates carbon allocation, nutrient cycling and soil water content [75]. The relatively higher diversity indices of ECM fungi in the 5-year-old stand than in the 11-year-old stand may possibly be explained by the less developed tree canopy at the earlier stage of stand development, which may have allowed diverse ECM fungi to interact extensively with the root systems of understory plants [75]. Another explanation for the relatively higher diversity indices of ECM fungi in the 5-year-old stand may be the previous land use of the plantation area. Deacon and Fleming [76] demonstrated that when afforestation takes place on land initially used for other purposes, the ECM fungal spores are the fundamental inoculum during the early stage of ECM succession. In this case, prior to the establishment of P. patula plantations, the study area was previously used for agricultural purposes, which might have contributed to the diversity of ECM fungi in young stands of P. patula trees due to the primary succession of ECM fungi through inocula in the spore bank derived from other nearby mycorrhizal-associated plantations such as Eucalyptus sp. L’Hér. plantations [24,36].
The relatively higher diversity indices of ECM species in the 36-year-old stand than in the 11-year-old stand may reflect a difference in the management of the 36-year-old stand. Chen et al. [77] indicated that thinning could increase the relative abundance of mycorrhizal fungi because thinning opens up the forest canopy, which increases soil temperature and moisture [78]. Thinning may therefore have a positive effect on microbial activity [79] because soil temperature and moisture influence the reaction of microbial enzymes and, thus, shift the microbial community composition by altering substrates and extracellular enzyme activity [80]. Dove and Keeton [81] and Tomao et al. [82] have suggested that fungal diversity can be conserved or even increased using forest management practices that enhance the structural complexity of stands and the late-successional characteristics of the forest and by carrying out low-impact logging operations. In this study, the 36-year-old stand had undergone thinning as part of a management operation in the study area [8], which could have enhanced the root growth of the remaining trees [83,84], providing new environments for soil microbes, which could lead to an improvement in fungal diversity through root attachments. Castaño et al. [12] observed that the species diversity of soil fungi remained stable after thinning, regardless of its intensity, when sufficient host trees and functional roots from thinned trees were retained. This finding has been supported by a number of different reports. For example, according to Mölder et al. [85], thinning could maintain a high level of ECM fungal diversity in mature stands. Chen et al. [86] and Dang et al. [75] also hypothesized that when thinning operations are performed, light availability, water, and nutrients increase, which improves the forest microclimatic conditions and, hence, the diversity of ECM fungi could be improved by this type of management practice. Furthermore, Goldmann et al. [87] reported that ECM fungi were less diverse in unmanaged forests than in highly managed stands. Thus, we suggest that forest management practices such as thinning could be one of the factors that impact ECM fungal diversity along the chronosequence of P. patula stands, although this should be further studied.

4.3. Fungal Composition and Edaphic Variables

Forest soils contain a diverse range of fungal species. The composition of soil fungal communities is influenced by different factors, such as dispersal, plant diversity, soil properties, land use, and climate, which are key components of forest systems [88,89]. Specifically, different fungal species are likely to respond to environmental drivers in different ways, depending on their characteristic traits [90,91], and, thus, in turn, the composition of soil fungal communities is directly correlated with soil fertility and plant growth status [92]. Mycorrhizal species are a particularly important part of the soil fungal community because they form a beneficial symbiotic association with plants, providing them with nutrients in return for photosynthetically fixed carbon [93], which is especially relevant under nutrient-limited conditions [94]. ECM fungi also play a key role in alleviating the drought stress of the host tree [95]. The composition of ECM fungi in the soil is also correlated with soil fertility and the growth status of the host trees [92,96]. In this study, we found that both stand age and soil fertility were factors that affected the fungal community composition in our study area. Our ordination analysis indicated that the 36-year-old stand and the 5-year-old stand had distinctive soil fungal communities, characterized by a relatively high number of ECM species. Previous studies have related similar findings regarding fungal community composition to several factors, such as changes in soil fertility [24], changes in root density [97], specific life-history events that have occurred since the stand was established or changes in microclimate conditions [12]. For example, less litter accumulation in young P. patula stands resulted in less organic matter and a lower C/N ratio in the 5 and 11-year-old stands in this study compared with the 36-year-old stand. This situation leads to trees having a greater dependence on mycorrhizal fungal associations for enhanced nutrient and water uptake and availability [24]. Similarly, the greater diversity of ECM species in young stands may indicate that suitable symbionts are present. However, older stands have a greater capacity to reduce fluctuations in temperature and to maintain adequate moisture levels [98,99,100], which is particularly important for the occurrence of ECM fungi. The abundance of ECM fungi in older stands is generally greater than in younger stands, which could be facilitated by the root systems of old trees, which could increase the chances of ECM associations forming [85], thereby facilitating the easy uptake of nutrients by trees [94]. Thus, the distinct composition of ECM fungi in young and old stands might not only be related to site quality factors, such as soil fertility, but also to stand age factors (e.g., the increasing area of tree root exploration in the soil with stand age); however, this needs to be investigated further. Given that the amount of organic matter, available P, and the C/N ratio of 5 and 11-year-old stands showed no greater difference in their values, this may have enabled 11-year-old stands to develop an association with only a limited number of ECM fungi, but a higher relative abundance of these ECM fungi, which could indicate increased dependence of P. patula trees on a limited number of dominant symbiont species. In any case, the survival of P. patula in soils in which ECM species comprise only a small proportion of the microbial community, together with other factors, supports the view that P. patula is well adapted to the conditions in this study area; however, this also needs further study.
Fertile soil contains nutrients that enable the growth and development of a soil fungal community [101]. Thus, in turn, the fungi are directly influenced by edaphic parameters [102,103,104]. In this study, edaphic cation elements, such as Mg and K, were also correlated with the overall fungal community from the whole data set, which indicates that soil cation concentrations could influence the composition of the fungal community [105]. Cations in general play an important part in a number of physicochemical processes, such as photosynthesis [106] and, thus, can affect plant photosynthesis and, hence, the amount of carbon that is available to soil fungi and bacteria [107]. Of the various cations, Ca is one of the main edaphic factors that influence the structure of soil fungal communities worldwide [108]. Other edaphic elements have also been reported to influence the composition of fungal communities in forest systems. For example, in this study, available P and tree age influenced the composition of mycorrhizal fungi (Table 4), which was similar to the findings reported by Rosenstock et al. [109]. The composition of fungi in the soil particularly that of mycorrhizal fungi, can also be influenced by N availability [110]. High levels of available N could decrease the dependency of the host plant on mycorrhizal fungi, which could reduce the amount of carbon allocated to fungi [111], which eventually could cause competition among the fungal species and could lead to changes in their composition [96,110]. In this study, the C/N ratio of soil in 5 and 11-year-old stands was relatively low compared with that of 36-year-old P. patula stands (Table 1). This result is inconsistent with Wang and Wang [96] who reported that a high C/N ratio negatively influenced fungal community structure, probably because a high concentration of N restrains the expansion of fungi. Our results also confirmed this, in the sense that the fungal diversity was low in stands where the soil C/N ratio was high, indicating that a high C/N ratio might not favor the fungal community in the forests in the study area. Soil organic matter could also impact the composition of soil fungal communities because fungi generally extend their mycelia at the soil–litter interface [112]. The amount of organic matter affects the water holding capacity of soil and nutrient availability, which could affect mycelial outgrowth and network formation [113,114]. However, soil acidity can also influence the composition of soil fungal communities [115,116] through its influence on spore germination and mycelial development [117].
Fungi have different life-history strategies and, in plantations, early colonizer fungal species that relish disturbance colonize first, followed by superior competitors that can outcompete the early colonizer species in older stands where resources are getting scarcer. In this study, we found that some fungal species associated with P. patula trees were detected at all age stages of tree development, such as those belonging to the genera Tomentella, Ramaria, and Inocybe. These genera have several hundreds of species, many still undescribed, and their strategies do not seem to be conserved at the genus level. Of these, Tomentella and Inocybe are cosmopolitan species that inhabit Eucalyptus plantations in Ethiopia [24]. Species of Rhizopogon were also associated more with younger stands (5- and 11-year-old stands) in this study, which supports previous findings that they are early colonizer fungal species [118]. The Rhizopogon species are known as spore bank species that facilitate the establishment of trees in formerly non-forest habitats. Other taxa belonging to the genera Amanita have also been reported in our P. patula plantation forests. These fungi species are well-known for their association with conifer forests as the genera is characteristic of late-stage pine stands that are 30–40 years old [119,120].

5. Conclusions

Our study explained the soil fungal community composition associated with a P. patula plantation in Ethiopia. The diversity value of vital fungi such as ECM was relatively higher in the youngest stand than in the two older stands. Stand age and soil fertility were also found to affect fungal community composition. Some ECM fungi were found as early colonizer species in the young stand and were replaced by superior competitor species as the P. patula stands developed.
The overall low level of ECM species richness detected in the P. patula stands is probably because this is a plantation of an ECM tree in a non-ECM biome. Due to the importance of fungi in plantation forest system, the results of this study could be relevant for the promotion and conservation of forests in Ethiopia through the promotion of non-wood forest products such as fungi, which could also provide food resources for poor populations during times of food scarcity. Thus, it is imperative to investigate how soil fungal communities respond to management regimes such as thinning and clear-cutting. The high diversity and relative abundance of plant pathogenic fungi detected in this study also highlights the need to protect Ethiopian plantations from plant diseases and pests.
Although the ecological conditions of all studied plots were similar in terms of climate, altitude, and soil, the results of this study should be considered as a case study, given that the plots were established in a single stand for each age class for each treatment and, therefore, the applicability of any conclusions to other stands should be treated with caution. Furthermore, additional scientific investigations of the plantation forest ecosystem are needed in order to consolidate the Ethiopian fungal biodiversity database.

Supplementary Materials

The following are available online at https://www.mdpi.com/1999-4907/11/10/1109/s1, Table S1: Summary of the Similarity Percentage (SIMPER) analysis showing contrasts between the cumulative total contribution (50% cut-off) and the contribution (%) of the most influential fungal operational taxonomic units to the dissimilarity of the soil fungi detected in three Pinus patula stands of different age groups in a plantation in Wondo Genet, Ethiopia.

Author Contributions

Conceptualization, P.M.-P., J.A.O.-d.-R. and T.D.; methodology, J.G., P.M.-P. and T.D.; software, D.A., P.M.-P. and T.D.; validation, P.M.-P.; formal analysis, P.M.-P., J.G. and T.D.; investigation, P.M.-P., T.D. and D.A.; data curation, D.A.; writing—original draft preparation, T.D. and D.A.; writing—review and editing, P.M.-P., T.D. and J.A.O.-d.-R. All authors have read and agreed to the published version of the manuscript.

Funding

This research work was partially supported by the Erasmus Mundus-Dream project grant and by the project SUSTIFUNGI_ET (Sustfungi_Eth:2017/ACDE/002094) funded by the Spanish Agency for International Development and Cooperation. This work was also co-funded by the Spanish Ministry of Education and Culture under a Salvador de Madariaga grant agreement, n° PRX17/00315.

Acknowledgments

We would like to express our gratitude to the people involved in the field work of this study.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Gebru, T. Deforestation in Ethiopia: Causes, Impacts and Remedy. Int. J. Eng. Dev. Res. 2016, 4, 204–209. [Google Scholar]
  2. FAO. Global Forest Resources Assessment. Rome, Italy. Available online: http://www.fao.org/3/i1757e/i1757e00.htm (accessed on 1 September 2020).
  3. Zewdie, M.; Tesfaye, A.; Girma, Y. Management Plan for Forest Plantations of WGCF-NR; Final Document; WGCF-NR: Wondo Genet, Ethiopia, 2010. [Google Scholar]
  4. Moges, Y. The Experiences of REDD+ for Ethiopian Condition, 1st ed.; Technology Dissemination Workshop: Dama, Ethiopia, 2015. [Google Scholar]
  5. Tesfaye, M.A.; Gardi, O.; Anbessa, T.B.; Blaser, J. Aboveground biomass, growth and yield for some selected introduced tree species, namely Cupressus lusitanica, Eucalyptus saligna, and Pinus patula in Central Highlands of Ethiopia. J. Ecol. Environ. 2020, 44, 1–18. [Google Scholar] [CrossRef] [Green Version]
  6. Bekele, M. Forest Plantations and Woodlots in Ethiopia. African For. Forum. 2011, 1, 52. [Google Scholar]
  7. Gezahgne, A. Diseases of Exotic Plantation Forestry Trees in Ethiopia. Ph.D. Thesis, University of Pretoria, Pretoria, South Africa, 2003. [Google Scholar]
  8. Dejene, T.; Oria-De-Rueda, J.A.; Martín-Pinto, P. Fungal diversity and succession following stand development in Pinus patula Schiede ex Schltdl. & Cham. plantations in Ethiopia. For. Ecol. Manag. 2017, 395, 9–18. [Google Scholar] [CrossRef]
  9. Tt, B. Climate-growth Relationship of Pinus patula Schldl. et Cham. in Wondo Genet, South Central Ethiopia. J. Clim. Weather. Forecast. 2016, 4, 1–8. [Google Scholar] [CrossRef] [Green Version]
  10. Teshome, T. Analysis of resin and turpentine oil constituents of Pinus patula grown in Ethiopia. Ethiop. e-J. Res. Innov. foresight. 2011, 3, 38–48. [Google Scholar]
  11. Canini, F.; Zucconi, L.; Pacelli, C.; Selbmann, L.; Onofri, S.; Geml, J. Vegetation, pH and Water Content as Main Factors for Shaping Fungal Richness, Community Composition and Functional Guilds Distribution in Soils of Western Greenland. Front. Microbiol. 2019, 10, 2348. [Google Scholar] [CrossRef]
  12. Castaño, C.; Alday, J.G.; Lindahl, B.D.; De Aragón, J.M.; De-Miguel, S.; Colinas, C.; Parladé, J.; Castaño, C.; Bonet, J.A. Lack of thinning effects over inter-annual changes in soil fungal community and diversity in a Mediterranean pine forest. For. Ecol. Manag. 2018, 424, 420–427. [Google Scholar] [CrossRef]
  13. Fernandez, C.W.; Nguyen, N.H.; Stefanski, A.; Han, Y.; Hobbie, S.E.; Montgomery, R.A.; Reich, P.B.; Kennedy, P.G. Ectomycorrhizal fungal response to warming is linked to poor host performance at the boreal-temperate ecotone. Glob. Chang. Biol. 2016, 23, 1598–1609. [Google Scholar] [CrossRef] [PubMed]
  14. Tedersoo, L.; Bahram, M.; Zobel, M. How mycorrhizal associations drive plant population and community biology. Science 2020, 367, eaba1223. [Google Scholar] [CrossRef]
  15. Lindahl, B.D.; Ihrmark, K.; Boberg, J.; Trumbore, S.E.; Högberg, P.; Stenlid, J.; Finlay, R.D. Spatial separation of litter decomposition and mycorrhizal nitrogen uptake in a boreal forest. New Phytol. 2006, 173, 611–620. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Dahlberg, A.; Schimmel, J.; Taylor, A.F.; Johannesson, H. Post-fire legacy of ectomycorrhizal fungal communities in the Swedish boreal forest in relation to fire severity and logging intensity. Biol. Conserv. 2001, 100, 151–161. [Google Scholar] [CrossRef]
  17. Dalong, M.; Luhe, W.; Guoting, Y.; LiQiang, M.; Chun, L. Growth response of Pinus densiflora seedlings inoculated with three indigenous ectomycorrhizal fungi in combination. Braz. J. Microbiol. 2011, 42, 1197–1204. [Google Scholar] [CrossRef] [Green Version]
  18. Averill, C.; Turner, B.L.; Finzi, A.C. Mycorrhiza-mediated competition between plants and decomposers drives soil carbon storage. Nat. Cell Biol. 2014, 505, 543–545. [Google Scholar] [CrossRef] [PubMed]
  19. Lin, G.; McCormack, M.L.; Ma, C.; Guo, D. Similar below-ground carbon cycling dynamics but contrasting modes of nitrogen cycling between arbuscular mycorrhizal and ectomycorrhizal forests. New Phytol. 2016, 213, 1440–1451. [Google Scholar] [CrossRef] [PubMed]
  20. Orwin, K.H.; Kirschbaum, M.U.F.; John, M.G.S.; Dickie, I.A. Organic nutrient uptake by mycorrhizal fungi enhances ecosystem carbon storage: A model-based assessment. Ecol. Lett. 2011, 14, 493–502. [Google Scholar] [CrossRef]
  21. Sterkenburg, E.; Clemmensen, K.E.; Ekblad, A.; Finlay, R.D.; Lindahl, B.D. Contrasting effects of ectomycorrhizal fungi on early and late stage decomposition in a boreal forest. ISME J. 2018, 12, 2187–2197. [Google Scholar] [CrossRef] [Green Version]
  22. Baldrian, P.; Voříšková, J.; Dobiášová, P.; Merhautová, V.; Lisá, L.; Valášková, V. Production of extracellular enzymes and degradation of biopolymers by saprotrophic microfungi from the upper layers of forest soil. Plant. Soil 2010, 338, 111–125. [Google Scholar] [CrossRef]
  23. Shanmugam, S.G.; Kingery, W.L. Changes in soil microbial community structure in relation to plant succession and soil properties during 4000 years of pedogenesis. Eur. J. Soil Biol. 2018, 88, 80–88. [Google Scholar] [CrossRef]
  24. Castaño, C.; Dejene, T.; Mediavilla, O.; Geml, J.; Oria-De-Rueda, J.A.; Martín-Pinto, P. Changes in fungal diversity and composition along a chronosequence of Eucalyptus grandis plantations in Ethiopia. Fungal Ecol. 2019, 39, 328–335. [Google Scholar] [CrossRef]
  25. Dickie, I.A.; Martínez-García, L.B.; Koele, N.; Grelet, G.-A.; Tylianakis, J.M.; Peltzer, D.A.; Richardson, S.J. Mycorrhizas and mycorrhizal fungal communities throughout ecosystem development. Plant. Soil 2013, 367, 11–39. [Google Scholar] [CrossRef]
  26. Krüger, C.; Kohout, P.; Janoušková, M.; Püschel, D.; Frouz, J.; Rydlová, J. Plant Communities Rather than Soil Properties Structure Arbuscular Mycorrhizal Fungal Communities along Primary Succession on a Mine Spoil. Front. Microbiol. 2017, 8, 719. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Gassibe, P.V.; Fabero, R.F.; Hernández-Rodríguez, M.; Oria-De-Rueda, J.A.; Martín-Pinto, P. Fungal community succession following wildfire in a Mediterranean vegetation type dominated by Pinus pinaster in Northwest Spain. For. Ecol. Manag. 2011, 262, 655–662. [Google Scholar] [CrossRef]
  28. Luoma, D.L.; Frenkel, R.E.; Trappe, J.M. Fruiting of Hypogeous Fungi in Oregon Douglas-Fir Forests: Seasonal and Habitat Variation. Mycologia 1991, 83, 335. [Google Scholar] [CrossRef]
  29. Hernández-Rodríguez, M.; Oria-De-Rueda, J.A.; Martín-Pinto, P. Post-fire fungal succession in a Mediterranean ecosystem dominated by Cistus ladanifer L. For. Ecol. Manag. 2013, 289, 48–57. [Google Scholar] [CrossRef]
  30. Claridge, A.W.; Trappe, J.M.; Lunney, D. Managing habitat for mycophagous (fungus-feeding) mammals: A burning issue? In Conservation of Australia’s Forest Fauna; Royal Zoological Society of New South Wales: Mosman, Australia, 2004; pp. 936–946. [Google Scholar]
  31. Reazin, C.; Morris, S.; Smith, J.; Cowan, A.; Jumpponen, A. Fires of differing intensities rapidly select distinct soil fungal communities in a Northwest US ponderosa pine forest ecosystem. For. Ecol. Manag. 2016, 377, 118–127. [Google Scholar] [CrossRef]
  32. Yang, T.; Adams, J.M.; Shi, Y.; He, J.-S.; Jing, X.; Chen, L.; Tedersoo, L.; Chu, H. Soil fungal diversity in natural grasslands of the Tibetan Plateau: Associations with plant diversity and productivity. New Phytol. 2017, 215, 756–765. [Google Scholar] [CrossRef] [Green Version]
  33. Blaalid, R.; Carlsen, T.; Kumar, S.; Halvorsen, R.; Ugland, K.I.; Fontana, G.; Kauserud, H. Changes in the root-associated fungal communities along a primary succession gradient analysed by 454 pyrosequencing. Mol. Ecol. 2011, 21, 1897–1908. [Google Scholar] [CrossRef]
  34. Clemmensen, K.E.; Finlay, R.D.; Dahlberg, A.; Stenlid, J.; Wardle, D.A.; Lindahl, B.D. Carbon sequestration is related to mycorrhizal fungal community shifts during long-term succession in boreal forests. New Phytol. 2014, 205, 1525–1536. [Google Scholar] [CrossRef]
  35. Bonet, J.A.; González-Olabarria, J.R.; De Aragón, J.M. Mushroom production as an alternative for rural development in a forested mountainous area. J. Mt. Sci. 2014, 11, 535–543. [Google Scholar] [CrossRef]
  36. Dejene, T.; Oria-De-Rueda, J.A.; Martín-Pinto, P. Fungal diversity and succession under Eucalyptus grandis plantations in Ethiopia. For. Ecol. Manag. 2017, 405, 179–187. [Google Scholar] [CrossRef]
  37. Ortega-Martínez, P.; Martinez-Pena, F. A sampling method for estimating sporocarps production of wild edible mushrooms of social and economic interest. Investig. Agrar. Sist. Recur. For. 2008, 17, 228. [Google Scholar] [CrossRef] [Green Version]
  38. Tóth, B.B.; Barta, Z. Ecological studies of ectomycorrhizal fungi: An analysis of survey methods. Fungal Divers. 2010, 45, 3–19. [Google Scholar] [CrossRef]
  39. Nielsen, U.; Ayres, E.; Wall, D.; Bardgett, R. Soil biodiversity and carbon cycling: A review and synthesis of studies examining diversity–function relationships. Eur. J. Soil Sci. 2011, 62, 105–116. [Google Scholar] [CrossRef]
  40. Brussaard, L.; De Ruiter, P.C.; Brown, G.G. Soil biodiversity for agricultural sustainability. Agric. Ecosyst. Environ. 2007, 121, 233–244. [Google Scholar] [CrossRef]
  41. Desalegn, T.; Gonzalo, J.; Turrion, M.-B. Effects of short-rotation Eucalyptus plantations on soil quality attributes in highly acidic soils of the central highlands of Ethiopia. Soil Use Manag. 2016, 32, 210–219. [Google Scholar] [CrossRef]
  42. Belaynesh, Z. Perceptions of Forest Resource Changes in and Around Wondo Genet Catchment and its Near Future Impacts. Master’s Thesis, Wondo Genet College of Forestry, Wondo Genet, Ethiopia, 2002. [Google Scholar]
  43. Costa, A.D.A.; Morato, S.; Roque, A.C.; Tinós, R. A computational model for exploratory activity of rats with different anxiety levels in elevated plus-maze. J. Neurosci. Methods 2014, 236, 44–50. [Google Scholar] [CrossRef] [PubMed]
  44. Zerga, B.; Berta, A. Preference, purpose, and pattern of Eucalyptus tree farming in Eza Wereda, Ethiopia. J. Soc. Sci. Humanit. Res. 2016, 3, 30–38. [Google Scholar]
  45. Eriksson, H.; Stern, M. A Soil Study at Wondo Genet Forestry Resources Institute, Ethiopia. Available online: https://agris.fao.org/agris-search/search.do?recordID=SE19880048966 (accessed on 1 September 2020).
  46. Eshetu, Z.; Högberg, P. Reconstruction of Forest Site History in Ethiopian Highlands Based on 13 C Natural Abundance of Soils. Ambio 2000, 29, 83–89. [Google Scholar] [CrossRef]
  47. Bekele, T.; Kassa, K.; Mengistu, T.; Debele, M.; Melka, Y. Working with communities to address deforestation in the Wondo Genet catchment Area, Ethiopia: Lessons learnt from a participatory action research. Res. J. Agric. Environ. Manag. 2013, 2, 448–456. [Google Scholar]
  48. Smith, J.E.; Molina, R.; Huso, M.M.; Luoma, D.L.; McKay, D.; Castellano, M.A.; Lebel, T.; Valachovic, Y. Species richness, abundance, and composition of hypogeous and epigeous ectomycorrhizal fungal sporocarps in young, rotation-age, and old-growth stands of Douglas-fir (Pseudotsuga menziesii) in the Cascade Range of Oregon, U.S.A. Can. J. Bot. 2002, 80, 186–204. [Google Scholar] [CrossRef] [Green Version]
  49. De La Varga, H.; Agueda, B.; Martínez-Peña, F.; Parladé, J.; Pera, J. Quantification of extraradical soil mycelium and ectomycorrhizas of Boletus edulis in a Scots pine forest with variable sporocarp productivity. Mycorrhiza 2011, 22, 59–68. [Google Scholar] [CrossRef] [PubMed]
  50. Voříšková, J.; Brabcová, V.; Cajthaml, T.; Baldrian, P. Seasonal dynamics of fungal communities in a temperate oak forest soil. New Phytol. 2013, 201, 269–278. [Google Scholar] [CrossRef]
  51. Ihrmark, K.; Bödeker, I.T.; Cruz-Martinez, K.; Friberg, H.; Kubartova, A.; Schenck, J.; Strid, Y.; Stenlid, J.; Brandström-Durling, M.; Clemmensen, K.E.; et al. New primers to amplify the fungal ITS2 region - evaluation by 454-sequencing of artificial and natural communities. FEMS Microbiol. Ecol. 2012, 82, 666–677. [Google Scholar] [CrossRef]
  52. White, T.J.; Burns, T.; Lee, S.; Taylor, J. Amplication and Direct Sequencing of Fungal Ribosomal RNA Genes for Phylogenetics. In PCR Protocols: A Guide to Methods and Applications; Michael, A.I., Gelfand, D., Sninsky, J., White, T.J., Eds.; Academic Press: New York, NY, USA, 1990; pp. 315–322. [Google Scholar]
  53. Reeuwijk, L. Procedures for Soil Analysis. International Soil Reference and Information Centre, Wageningen, The Netherlands. Available online: https://www.boku.wzw.tum.de/fileadmin/downloads/wrb/ISRIC_TechPap09_2002.pdf (accessed on 1 September 2019).
  54. Walkley, A.; Black, I.A. An examination of the digestion method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Sci. 1934, 34, 29–38. [Google Scholar] [CrossRef]
  55. Kim, J.; Kreller, A.C.R.; Greenberg, M.M. Preparation and Analysis of Oligonucleotides Containing the C4‘-Oxidized Abasic Site and Related Mechanistic Probes. J. Org. Chem. 2005, 70, 8122–8129. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  56. Methods of Soil Analysis, Part 2. Available online: https://books.google.com.hk/books?hl=zh-CN&lr=&id=PtvWDwAAQBAJ&oi=fnd&pg=PR15&dq=Methods+of+Soil+Analysis&ots=TwMB-l4x6H&sig=RcejRQxwEv3YDFWz9evUT5y9ye4&redir_esc=y#v=onepage&q=Methods%20of%20Soil%20Analysis&f=false (accessed on 3 September 2020).
  57. Bouyoucos, G.H. A Reclamation of the Hydrometer for Making Mechanical Analysis. Agron. J. 1951, 43, 434–438. [Google Scholar] [CrossRef] [Green Version]
  58. Edgar, R.C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010, 26, 2460–2461. [Google Scholar] [CrossRef] [Green Version]
  59. Kõljalg, U.; Nilsson, R.H.; Abarenkov, K.; Tedersoo, L.; Taylor, A.F.S.; Bahram, M.; Bates, S.T.; Bruns, T.D.; Bengtsson-Palme, J.; Callaghan, T.M.; et al. Towards a unified paradigm for sequence-based identification of fungi. Mol. Ecol. 2013, 22, 5271–5277. [Google Scholar] [CrossRef] [Green Version]
  60. Shannon, C.E. A mathematical theory of communication. ACM SIGMOBILE Mob. Comput. Commun. Rev. 2001, 5, 3–55. [Google Scholar] [CrossRef]
  61. Taylor, D.; Kent, M.; Coker, P. Vegetation Description and Analysis: A Practical Approach. Geogr. J. 1993, 159, 237. [Google Scholar] [CrossRef]
  62. Magurran, A.E. Ecological Diversity and Its Measurement; Springer Science and Business Media LLC: Berlin/Heidelberg, Germany, 1988. [Google Scholar]
  63. Kindt, R.; Coe, R. Tree diversity analysis. In A Manual and Software for Common Statistical Methods for Ecological and Biodiversity Studies; World Agroforestry Centre (ICRAF): Nairobi, Kenya, 2005. [Google Scholar]
  64. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2019. [Google Scholar]
  65. Smilauer, P.; Lepš, J. Multivariate Analysis of Ecological Data Using CANOCO 5; Cambridge University Press (CUP): Cambridge, UK, 2014. [Google Scholar]
  66. Anderson, M.J. A new method for non-parametric multivariate analysis of variance. Austral. Ecol. 2001, 26, 32–46. [Google Scholar] [CrossRef]
  67. Clarke, K.R. Non-parametric multivariate analyses of changes in community structure. Austral. Ecol. 1993, 18, 117–143. [Google Scholar] [CrossRef]
  68. Parravacini, V.; Micheli, F.; Montefalcone, M.; Villa, E.; Morri, C.; Bianchi, C.N. Rapid assessment of epibenthic communities: A comparison between two visual sampling techniques. J. Exp. Mar. Biol. Ecol. 2010, 395, 21–29. [Google Scholar] [CrossRef]
  69. Purvis, A.; Hector, A. Getting the measure of biodiversity. Nat. Cell Biol. 2000, 405, 212–219. [Google Scholar] [CrossRef]
  70. Wu, B.; Hussain, M.; Zhang, W.; Stadler, M.; Liu, X.; Xiang, M. Current insights into fungal species diversity and perspective on naming the environmental DNA sequences of fungi. Mycology 2019, 10, 127–140. [Google Scholar] [CrossRef] [Green Version]
  71. James, T.Y.; Kauff, F.; Schoch, C.L.; Matheny, P.B.; Hofstetter, V.; Cox, C.J.; Celio, G.; Gueidan, C.; Fraker, E.; Miadlikowska, J.; et al. Reconstructing the early evolution of Fungi using a six-gene phylogeny. Nat. Cell Biol. 2006, 443, 818–822. [Google Scholar] [CrossRef]
  72. Urcelay, C.; Longo, S.; Geml, J.; Tecco, P.; Nouhra, E. Co-invasive exotic pines and their ectomycorrhizal symbionts show capabilities for wide distance and altitudinal range expansion. Fungal Ecol. 2017, 25, 50–58. [Google Scholar] [CrossRef]
  73. Mitchell, R.; Keith, A.M.; Potts, J.M.; Ross, J.; Reid, E.; Dawson, L.A. Overstory and understory vegetation interact to alter soil community composition and activity. Plant. Soil 2011, 352, 65–84. [Google Scholar] [CrossRef] [Green Version]
  74. Peralta, R.M.; Ahn, C.; Gillevet, P.M. Characterization of soil bacterial community structure and physicochemical properties in created and natural wetlands. Sci. Total. Environ. 2013, 443, 725–732. [Google Scholar] [CrossRef]
  75. Dang, P.; Gao, Y.; Liu, J.; Yu, S.; Zhao, Z. Effects of thinning intensity on understory vegetation and soil microbial communities of a mature Chinese pine plantation in the Loess Plateau. Sci. Total. Environ. 2018, 630, 171–180. [Google Scholar] [CrossRef] [PubMed]
  76. Deacon, J.W.; Fleming, L.V. Interactions of Ectomycorrhizal Fungi. In Mycorrhizal Functioning an Integrative Plant-Fungal Process; Allen, M., Ed.; Chapman and Hall: New York, NY, USA, 1992; pp. 249–300. [Google Scholar]
  77. Chen, J.; Xu, H.; He, D.; Li, Y.; Luo, T.; Yang, H.; Lin, M. Historical logging alters soil fungal community composition and network in a tropical rainforest. For. Ecol. Manag. 2019, 433, 228–239. [Google Scholar] [CrossRef]
  78. Wang, Y.; Wei, X.; Del Campo, A.D.; Winkler, R.; Wu, J.; Li, Q.; Liu, W. Juvenile thinning can effectively mitigate the effects of drought on tree growth and water consumption in a young Pinus contorta stand in the interior of British Columbia, Canada. For. Ecol. Manag. 2019, 454, 117667. [Google Scholar] [CrossRef]
  79. Pang, X.; Bao, W.; Zhu, B.; Cheng, W. Responses of soil respiration and its temperature sensitivity to thinning in a pine plantation. Agric. For. Meteorol. 2013, 171, 57–64. [Google Scholar] [CrossRef]
  80. Hassett, J.E.; Zak, D.R. Aspen Harvest Intensity Decreases Microbial Biomass, Extracellular Enzyme Activity, and Soil Nitrogen Cycling. Soil Sci. Soc. Am. J. 2005, 69, 227. [Google Scholar] [CrossRef]
  81. Dove, N.C.; Keeton, W.S. Structural Complexity Enhancement increases fungal species richness in northern hardwood forests. Fungal Ecol. 2015, 13, 181–192. [Google Scholar] [CrossRef]
  82. Tomao, A.; Bonet, J.A.; Castaño, C.; De-Miguel, S. How does forest management affect fungal diversity and community composition? Current knowledge and future perspectives for the conservation of forest fungi. For. Ecol. Manag. 2020, 457, 117678. [Google Scholar] [CrossRef]
  83. Grant, C.D.; Norman, M.A.; Smith, M.A. Fire and Silvicultural Management of Restored Bauxite Mines in Western Australia. Restor. Ecol. 2007, 15, S127–S136. [Google Scholar] [CrossRef]
  84. Lin, W.; Chen, W.; Wang, P. Effects of forest thinning on diversity and function of macrofungi and soil microbes. Sydowia 2011, 63, 67–77. [Google Scholar]
  85. Mölder, A.; Streit, M.; Schmidt, W. When beech strikes back: How strict nature conservation reduces herb-layer diversity and productivity in Central European deciduous forests. For. Ecol. Manag. 2014, 319, 51–61. [Google Scholar] [CrossRef]
  86. Chen, X.; Wang, N.; Chen, X.; Wang, J.; Diao, J.-J.; Zhang, J.-Y.; Guan, Q.-W. Soil microbial functional diversity and biomass as affected by different thinning intensities in a Chinese fir plantation. Appl. Soil Ecol. 2015, 92, 35–44. [Google Scholar] [CrossRef]
  87. Goldmann, K.; Schöning, I.; Buscot, F.; Wubet, T. Forest Management Type Influences Diversity and Community Composition of Soil Fungi across Temperate Forest Ecosystems. Front. Microbiol. 2015, 6, 1300. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  88. Liang, Y.; He, X.; Chen, C.; Feng, S.; Liu, L.; Chen, X.; Zhao, Z.; Su, Y. Influence of plant communities and soil properties during natural vegetation restoration on arbuscular mycorrhizal fungal communities in a karst region. Ecol. Eng. 2015, 82, 57–65. [Google Scholar] [CrossRef]
  89. Rillig, M.C.; Aguilar-Trigueros, C.A.; Bergmann, J.; Verbruggen, E.; Veresoglou, S.D.; Lehmann, A. Plant root and mycorrhizal fungal traits for understanding soil aggregation. New Phytol. 2014, 205, 1385–1388. [Google Scholar] [CrossRef] [PubMed]
  90. Crowther, T.W.; Stanton, D.W.G.; Thomas, S.M.; A’Bear, A.D.; Hiscox, J.; Jones, T.H.; Voříšková, J.; Baldrian, P.; Boddy, L. Top-down control of soil fungal community composition by a globally distributed keystone consumer. Ecology 2013, 94, 2518–2528. [Google Scholar] [CrossRef]
  91. Koide, R.T.; Fernandez, C.W.; Malcolm, G. Determining place and process: Functional traits of ectomycorrhizal fungi that affect both community structure and ecosystem function. New Phytol. 2014, 201, 433–439. [Google Scholar] [CrossRef]
  92. Cozzolino, V.; Di Meo, V.; Monda, H.; Spaccini, R.; Piccolo, A. The molecular characteristics of compost affect plant growth, arbuscular mycorrhizal fungi, and soil microbial community composition. Biol. Fertil. Soils 2015, 52, 15–29. [Google Scholar] [CrossRef]
  93. Smith, S.E.; Read, D. Mycorrhizal Symbiosis; Elsevier: Amsterdam, The Netherlands, 2008. [Google Scholar]
  94. Read, D.J.; Perez-Moreno, J. Mycorrhizas and nutrient cycling in ecosystems—A journey towards relevance? New Phytol. 2003, 157, 475–492. [Google Scholar] [CrossRef]
  95. Mohan, J.E.; Cowden, C.C.; Baas, P.; Dawadi, A.; Frankson, P.T.; Helmick, K.; Hughes, E.; Khan, S.; Lang, A.; Machmuller, M.; et al. Mycorrhizal fungi mediation of terrestrial ecosystem responses to global change: Mini-review. Fungal Ecol. 2014, 10, 3–19. [Google Scholar] [CrossRef]
  96. Wang, Q.-K.; Wang, S.-L. Soil microbial properties and nutrients in pure and mixed Chinese fir plantations. J. For. Res. 2008, 19, 131–135. [Google Scholar] [CrossRef]
  97. Peay, K.G.; Garbelotto, M.; Bruns, T.D. Evidence of dispersal limitation in soil microorganisms: Isolation reduces species richness on mycorrhizal tree islands. Ecology 2010, 91, 3631–3640. [Google Scholar] [CrossRef] [PubMed]
  98. Fernández-Toirán, L.; Ágreda, T.; Olano, J.M. Stand age and sampling year effect on the fungal fruit body community in Pinus pinaster forests in central Spain. Can. J. Bot. 2006, 84, 1249–1258. [Google Scholar] [CrossRef]
  99. Pinna, S.; Gévry, M.-F.; Coté, M.; Sirois, L. Factors influencing fructification phenology of edible mushrooms in a boreal mixed forest of Eastern Canada. For. Ecol. Manag. 2010, 260, 294–301. [Google Scholar] [CrossRef]
  100. Toivanen, T.; Markkanen, A.; Kotiaho, J.S.; Halme, P. The effect of forest fuel harvesting on the fungal diversity of clear-cuts. Biomass Bioenergy 2012, 39, 84–93. [Google Scholar] [CrossRef]
  101. Siciliano, S.D.; Palmer, A.S.; Winsley, T.; Lamb, E.; Bissett, A.; Brown, M.V.; Van Dorst, J.; Ji, M.; Ferrari, B.C.; Grogan, P.; et al. Soil fertility is associated with fungal and bacterial richness, whereas pH is associated with community composition in polar soil microbial communities. Soil Biol. Biochem. 2014, 78, 10–20. [Google Scholar] [CrossRef]
  102. Drenovsky, R.; Vo, D.; Graham, K.; Scow, K. Soil Water Content and Organic Carbon Availability Are Major Determinants of Soil Microbial Community Composition. Microb. Ecol. 2004, 48, 424–430. [Google Scholar] [CrossRef] [PubMed]
  103. Lauber, C.L.; Strickland, M.S.; Bradford, M.A.; Fierer, N. The influence of soil properties on the structure of bacterial and fungal communities across land-use types. Soil Biol. Biochem. 2008, 40, 2407–2415. [Google Scholar] [CrossRef]
  104. Lauber, C.L.; Hamady, M.; Knight, R.; Fierer, N. Pyrosequencing-Based Assessment of Soil pH as a Predictor of Soil Bacterial Community Structure at the Continental Scale. Appl. Environ. Microbiol. 2009, 75, 5111–5120. [Google Scholar] [CrossRef] [Green Version]
  105. Song, J.; Chen, L.; Chen, F.-M.; Ye, J. Edaphic and host plant factors are linked to the composition of arbuscular mycorrhizal fungal communities in the root zone of endangered Ulmus chenmoui Cheng in China. Ecol. Evol. 2019, 9, 8900–8910. [Google Scholar] [CrossRef] [Green Version]
  106. He, J.; Tedersoo, L.; Hu, A.; Han, C.; He, D.; Wei, H.; Jiao, M.; Anslan, S.; Nie, Y.; Jia, Y.; et al. Greater diversity of soil fungal communities and distinguishable seasonal variation in temperate deciduous forests compared with subtropical evergreen forests of eastern China. FEMS Microbiol. Ecol. 2017, 93. [Google Scholar] [CrossRef] [Green Version]
  107. Shi, L.-L.; Mortimer, P.E.; Slik, J.W.F.; Zou, X.-M.; Xu, J.-C.; Feng, W.-T.; Qiao, L. Variation in forest soil fungal diversity along a latitudinal gradient. Fungal Divers. 2013, 64, 305–315. [Google Scholar] [CrossRef]
  108. Tedersoo, L.; Bahram, M.; Põlme, S.; Kõljalg, U.; Yorou, N.S.; Wijesundera, R.; Ruiz, L.V.; Vasco-Palacios, A.M.; Thu, P.Q.; Suija, A.; et al. Global diversity and geography of soil fungi. Science 2014, 346, 1256688. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  109. Rosenstock, N.P.; Berner, C.; Smits, M.M.; Krám, P.; Wallander, H. The role of phosphorus, magnesium and potassium availability in soil fungal exploration of mineral nutrient sources in Norway spruce forests. New Phytol. 2016, 211, 542–553. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  110. Zhao, A.; Liu, L.; Xu, T.; Shi, L.; Xie, W.; Zhang, W.; Fu, S.; Feng, H.; Chen, B.-D. Influences of Canopy Nitrogen and Water Addition on AM Fungal Biodiversity and Community Composition in a Mixed Deciduous Forest of China. Front. Plant Sci. 2018, 9, 9. [Google Scholar] [CrossRef]
  111. Liu, M.; Sui, X.; Hu, Y.; Feng, F. Microbial community structure and the relationship with soil carbon and nitrogen in an original Korean pine forest of Changbai Mountain, China. BMC Microbiol. 2019, 19, 1–14. [Google Scholar] [CrossRef] [Green Version]
  112. Boddy, L.; Hynes, J.; Bebber, D.P.; Fricker, M.D. Saprotrophic cord systems: Dispersal mechanisms in space and time. Mycoscience 2009, 50, 9–19. [Google Scholar] [CrossRef]
  113. Zakaria, A.J.; Boddy, L. Mycelial foraging by Resinicium bicolor: Interactive effects of resource quantity, quality and soil composition. FEMS Microbiol. Ecol. 2002, 40, 135–142. [Google Scholar] [CrossRef]
  114. Harrington, T.J. Relationships Between Macrofungi and vegetation in the Burren. Biol. Environ. Proc. R. Ir. Acad. 2003, 103, 147–159. [Google Scholar] [CrossRef]
  115. An, G.-H.; Miyakawa, S.; Kawahara, A.; Osaki, M.; Ezawa, T. Community structure of arbuscular mycorrhizal fungi associated with pioneer grass species Miscanthus sinensisin acid sulfate soils: Habitat segregation along pH gradients. Soil Sci. Plant. Nutr. 2008, 54, 517–528. [Google Scholar] [CrossRef] [Green Version]
  116. Wei, C.; Yu, Q.; Bai, E.; Lü, X.; Li, Q.; Xia, J.; Kardol, P.; Liang, W.; Wang, Z.; Han, X. Nitrogen deposition weakens plant-microbe interactions in grassland ecosystems. Glob. Chang. Biol. 2013, 19, 3688–3697. [Google Scholar] [CrossRef]
  117. Rousk, K.; Bååth, E.; Brookes, P.C.; Lauber, C.L.; Lozupone, C.; Caporaso, J.G.; Knight, R.; Fierer, N. Soil bacterial and fungal communities across a pH gradient in an arable soil. ISME J. 2010, 4, 1340–1351. [Google Scholar] [CrossRef]
  118. Glassman, S.I.; Levine, C.R.; DiRocco, A.M.; Battles, J.J.; Bruns, T.D. Ectomycorrhizal fungal spore bank recovery after a severe forest fire: Some like it hot. ISME J. 2015, 10, 1228–1239. [Google Scholar] [CrossRef] [PubMed]
  119. Chu-Chou, M.; Grace, L.J. Mycorrhizal fungi of Eucalyptus in the North Island of New Zealand. Soil Biol. Biochem. 1982, 14, 133–137. [Google Scholar] [CrossRef]
  120. Visser, S. Ectomycorrhizal fungal succession in jack pine stands following wildfire. New Phytol. 1995, 129, 389–401. [Google Scholar] [CrossRef]
Forests 11 01109 g001 550
Figure 1. Maps showing the location of the study area, Wondo Genet, in the Sidama region of Ethiopia.
Figure 1. Maps showing the location of the study area, Wondo Genet, in the Sidama region of Ethiopia.
Forests 11 01109 g001
Forests 11 01109 g002 550
Figure 2. (a) Detrended correspondence analyses and (b) canonical correspondence analysis (CCA) ordination plots based on Hellinger-transformed abundance data of fungal guilds detected in the soil of three Pinus patula stands of different ages. Plots shown in the same color are in the same stand (black, plots in the 5-year-old stand; yellow, plots in the 11-year-old stand; red, plots in the 36-year-old stand). Edaphic variables are shown in green. The percentages of explained variation by each axis are shown in (b).
Figure 2. (a) Detrended correspondence analyses and (b) canonical correspondence analysis (CCA) ordination plots based on Hellinger-transformed abundance data of fungal guilds detected in the soil of three Pinus patula stands of different ages. Plots shown in the same color are in the same stand (black, plots in the 5-year-old stand; yellow, plots in the 11-year-old stand; red, plots in the 36-year-old stand). Edaphic variables are shown in green. The percentages of explained variation by each axis are shown in (b).
Forests 11 01109 g002
Forests 11 01109 g003 550
Figure 3. (a) Detrended correspondence analyses and (b) canonical correspondence analysis (CCA) ordination plots based on Hellinger-transformed abundance data of mycorrhizal fungal species at the order level of fungal communities associated with three age groups of Pinus patula stands in the study area in Ethiopia. Plots shown in the same color are in the same stand (yellow, plots in the 5-year-old stand; black, plots in the 11-year-old stand; red, plots in the 36-year-old stand). Edaphic variables are shown in green. The percentages of cumulative explained variation by each axis are shown in (b).
Figure 3. (a) Detrended correspondence analyses and (b) canonical correspondence analysis (CCA) ordination plots based on Hellinger-transformed abundance data of mycorrhizal fungal species at the order level of fungal communities associated with three age groups of Pinus patula stands in the study area in Ethiopia. Plots shown in the same color are in the same stand (yellow, plots in the 5-year-old stand; black, plots in the 11-year-old stand; red, plots in the 36-year-old stand). Edaphic variables are shown in green. The percentages of cumulative explained variation by each axis are shown in (b).
Forests 11 01109 g003
Table
Table 1. Selected chemical properties of soil samples from the study plots in Pinus patula plantations in Wondo Genet area, Ethiopia.
Table 1. Selected chemical properties of soil samples from the study plots in Pinus patula plantations in Wondo Genet area, Ethiopia.
Soil Chemical PropertiesStand Age
5 Years11 Years36 Years
pH-KCl (1:2.5)6.04 ± 0.195.42 ± 0.205.44 ± 0.44
Exch. Na+ (meq/100 g of soil)0.85 ± 0.030.78 ± 0.051.10 ± 0.49
Exch. K+ (meq/100 g of soil)1.32 ± 0.250.42 ± 0.080.77 ± 0.05
Exch. Ca2+ (meq/100 g of soil)22.62 ± 3.8213.66 ± 2.9916.01 ± 7.23
Exch. Mg2+ (meq/100 g of soil)7.96 ± 1.164.36 ± 0.426.66 ± 1.15
Organic matter5.96 ± 0.687.27 ± 0.8413.33 ± 0.98
Nitrogen (%)0.83 ± 0.070.71 ± 0.060.34 ± 0.02
Available P (mg P2O5/kg soil)35.70 ± 5.0236.99 ± 8.1038.56 ± 7.46
C/N3.61 ± 0.285.17 ± 0.4119.56 ± 2.11
Note: Values shown are means ± the standard deviation.
Table
Table 2. Average forest group distances calculated using Sørensen distance matrices to determine whether soil fungal compositions were statistically different across Pinus patula stands of three different ages in Wondo Genet, Ethiopia. The average value of all three stand ages ± the standard deviation is also shown.
Table 2. Average forest group distances calculated using Sørensen distance matrices to determine whether soil fungal compositions were statistically different across Pinus patula stands of three different ages in Wondo Genet, Ethiopia. The average value of all three stand ages ± the standard deviation is also shown.
GroupForest Stand TypeSørensen Average Group Distance
15-year-old stand0.60
211-year-old stand0.39
336-year-old stand0.63
Average 0.54 ± 0.13
Table
Table 3. Canonical correspondence analysis based on simple term effects showing the significance (p < 0.05) of edaphic variables when considering the Hellinger transformed data of the entire fungal guilds at the level of fungal community in the study area.
Table 3. Canonical correspondence analysis based on simple term effects showing the significance (p < 0.05) of edaphic variables when considering the Hellinger transformed data of the entire fungal guilds at the level of fungal community in the study area.
Edaphic VariablesDfSum of SquaresR2Fp
K10.0180.36526.8250.010
Mg10.0210.4257.5180.008
Table
Table 4. Canonical correspondence analysis based on simple term effects showing the significance (p < 0.05) of edaphic variables when considering the Hellinger transformed data of ectomycorrhizal species at the order level of fungal community in the study area.
Table 4. Canonical correspondence analysis based on simple term effects showing the significance (p < 0.05) of edaphic variables when considering the Hellinger transformed data of ectomycorrhizal species at the order level of fungal community in the study area.
VariableSimple Term Effects
Explains %Pseudo-Fp
Age26.82.600.010
Phosphorus19.02.100.052
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Alem, D.; Dejene, T.; Oria-de-Rueda, J.A.; Geml, J.; Martín-Pinto, P. Soil Fungal Communities under Pinus patula Schiede ex Schltdl. & Cham. Plantation Forests of Different Ages in Ethiopia. Forests 2020, 11, 1109. https://doi.org/10.3390/f11101109

AMA Style

Alem D, Dejene T, Oria-de-Rueda JA, Geml J, Martín-Pinto P. Soil Fungal Communities under Pinus patula Schiede ex Schltdl. & Cham. Plantation Forests of Different Ages in Ethiopia. Forests. 2020; 11(10):1109. https://doi.org/10.3390/f11101109

Chicago/Turabian Style

Alem, Demelash, Tatek Dejene, Juan Andrés Oria-de-Rueda, József Geml, and Pablo Martín-Pinto. 2020. "Soil Fungal Communities under Pinus patula Schiede ex Schltdl. & Cham. Plantation Forests of Different Ages in Ethiopia" Forests 11, no. 10: 1109. https://doi.org/10.3390/f11101109

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop