High Variability of Fungal Communities Associated with the Functional Tissues and Rhizosphere Soil of Picea abies in the Southern Baltics

Adas Marčiulynas

Climate change, which leads to higher temperatures, droughts, and storms, is expected to have a strong effect on both health of forest trees and associated biodiversity. The aim of this study was to investigate the diversity and composition of fungal communities associated with the functional tissues and rhizosphere soil of healthy-looking Picea abies to better understand these fungal communities and their potential effect on tree health in the process of climate change. The study sites included 30 P. abies stands, where needles, shoots, roots, and the rhizosphere soil was sampled. DNA was isolated from individual samples, amplified using ITS2 rRNA as a marker and subjected to high-throughput sequencing. The sequence analysis showed the presence of 232,547 high-quality reads, which following clustering were found to represent 2701 non-singleton fungal OTUs. The highest absolute richness of fungal OTUs was in the soil (1895), then in the needles (1049) and shoots (1002), and the lowe...

Article High Variability of Fungal Communities Associated with the Functional Tissues and Rhizosphere Soil of Picea abies in the Southern Baltics Adas Marčiulynas 1, *, Diana Marčiulynienė 1 , Valeriia Mishcherikova 1 , Iva Franić 2 , Jūratė Lynikienė 1 , Artūras Gedminas 1 and Audrius Menkis 3 1 2 3 * Citation: Marčiulynas, A.; Marčiulynienė, D.; Mishcherikova, V.; Franić, I.; Lynikienė, J.; Gedminas, A.; Menkis, A. High Variability of Fungal Communities Associated with the Functional Tissues and Rhizosphere Soil of Picea abies in the Southern Baltics. Forests 2022, 13, 1103. https://doi.org/10.3390/f13071103 Academic Editor: Artur Alves Received: 14 May 2022 Accepted: 11 July 2022 Institute of Forestry, Lithuanian Research Centre for Agriculture and Forestry, Liepu˛ Str. 1, LT-53101 Girionys, Lithuania; diana.marciulyniene@lammc.lt (D.M.); valeriia.mishcherikova@lammc.lt (V.M.); jurate.lynikiene@lammc.lt (J.L.); arturas.gedminas@lammc.lt (A.G.) Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Sundsvägen 3, SE-23053 Alnarp, Sweden; iva.franic@slu.se Department of Forest Mycology and Plant Pathology, Uppsala BioCenter, Swedish University of Agricultural Sciences, P.O. Box 7026, SE-75007 Uppsala, Sweden; audrius.menkis@slu.se Correspondence: adas.marciulynas@lammc.lt Abstract: Climate change, which leads to higher temperatures, droughts, and storms, is expected to have a strong effect on both health of forest trees and associated biodiversity. The aim of this study was to investigate the diversity and composition of fungal communities associated with the functional tissues and rhizosphere soil of healthy-looking Picea abies to better understand these fungal communities and their potential effect on tree health in the process of climate change. The study sites included 30 P. abies stands, where needles, shoots, roots, and the rhizosphere soil was sampled. DNA was isolated from individual samples, amplified using ITS2 rRNA as a marker and subjected to highthroughput sequencing. The sequence analysis showed the presence of 232,547 high-quality reads, which following clustering were found to represent 2701 non-singleton fungal OTUs. The highest absolute richness of fungal OTUs was in the soil (1895), then in the needles (1049) and shoots (1002), and the lowest was in the roots (641). The overall fungal community was composed of Ascomycota (58.3%), Basidiomycota (37.2%), Zygomycota (2.5%), Chytridiomycota (1.6%), and Glomeromycota (0.4%). The most common fungi based on sequence read abundance were Aspergillus pseudoglaucus (7.9%), Archaeorhizomyces sp. (3.6%), and Rhinocladiella sp. (2.0%). Pathogens were relatively rare, among which the most common were Phacidium lacerum (1.7%), Cyphellophora sessilis (1.4%), and Rhizosphaera kalkhoffii (1.4%). The results showed that the detected diversity of fungal OTUs was generally high, but their relative abundance varied greatly among different study sites, thereby highlighting the complexity of interactions among the host trees, fungi, and local environmental conditions. Published: 13 July 2022 Publisher’s Note: MDPI stays neutral Keywords: biodiversity; climate change; fungi; Norway spruce; pathogens; tree health with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1. Introduction Norway spruce (Picea abies) is one of the dominant coniferous tree species of north temperate and boreal forests of Europe, and is therefore of tremendous socio-economic importance [1]. Although it can grow under different climatic and edaphic conditions, it is more adapted to cooler climate and most often found on acidic and nutrient-rich soils with a good availability of moisture [2,3]. As P. abies increasingly suffers from different abiotic and biotic damages [4], climate change can be expected to have a major effect on health and distribution range of its forest stands [5,6]. These changes are expected to be due to its sensitivity to changes in the main limiting climatic factors [7,8]. Indeed, climate change modelling shows that the southwestern border of the P. abies distribution in Europe at the Forests 2022, 13, 1103. https://doi.org/10.3390/f13071103 https://www.mdpi.com/journal/forests Forests 2022, 13, 1103 2 of 24 end of this century will coincide with the southern border of boreal vegetation zone as it is known today [9,10]. Therefore, P. abies stands at or outside this zone can be more prone to damages, i.e., something similar what is currently observed in several Central European countries [11]. These damages are likely to be not only due to the limited adaptation of P. abies to changing environmental conditions, but also due to both competition with other newly established tree species and damages caused by indigenous and/or new (invasive) pests and pathogens [12,13]. Interestingly, Bebber et al. [14] showed that in the Northern hemisphere, fungal pathogens expand northwards at a speed of 7.61 ± 2.41 km/year, while physical effects of climate change expand at about 2.7 km/year. Moreover, climate change may also alter the survival and infectivity of fungal pathogens at the same time increasing the susceptibility of host trees, thereby increasing the risk to disease outbreaks. In Northern Europe, the predicted increase of precipitation may favour waterborne pathogens, such as Phytophthora, which can be expected to become more frequent in the future [15]. It may also favour outbreaks of fungal pathogens, which benefit from specific climatic conditions and tree stress. For example, Diplodia sapinea attacks trees subjected to drought stress [16], while outbreaks of Gremmeniella abietina occur after cool and wet summers [17]. Moreover, climate change may lead to the emergence of new virulent strains of fungal pathogens [18]. Several studies on fungal diseases and climate research have revealed that the number of fungal diseases has increased along with climate change and is increasingly recognised as a global threat to important plants [19]. Many different organisms are associated with P. abies [3], but these may also be threatened due to changes in habitat quality and availability. Among these are fungi, which play important roles in forest ecosystems, including nutrient and carbon cycles and may have a significant effect on forest health and sustainability [20,21]. Therefore, fungi are known to have a versatile impact on functioning of both individual trees and entire forest ecosystems [22]. The immense diversity of fungal communities across the landscape, however, is due in part to their extensive variability at small spatial scales, something what can be determined by variety of factors such as environmental conditions, plant species identity and diversity, and physical and chemical properties of the soil [23–25]. For example, climatic factors such as precipitation, which can influence the spore germination, and temperature, which can affect the longevity of spores, are important to the distribution and establishment of fungi [26,27]. Soil properties such as pH is known to have a significant effect on fungal diversity including many taxonomic and functional groups [28]. Moreover, changes in climatic factors may lead to the replacement of native fungal species by new (invasive) species with a greater host range and resilience to climate change [29]. Picea abies is known to be associated with a diverse fungal community [30–32]. Among the most abundant fungi are endophytes, which are ubiquitous in nature and can be found in different tree tissues [33]. Fungal endophytes are generally defined as species that inhabit tissues without causing apparent disease symptoms [22,34]. By contrast, pathogenic fungi may cause tree diseases, resulting in reduced growth or even mortality. They often attack trees, which are affected by other biotic or/and abiotic factors (see above). Dead trees or their dead tissues are often inhabited by fungal saprotrophs, which obtain nutrients by degrading dead organic matter. Saprotrophs include principal decomposers of tree litter and the wood [35,36]. Ectomycorrhizal fungi, which are specialised soil fungi, form beneficial symbioses with tree roots and can be essential for tree growth and nutrition, particularly under harsh environmental conditions [37]. Changes in diversity and composition of fungal communities may often depend not only on environmental conditions, but also on the health and vitality of host trees [38]. On the other hand, fungal communities may also have a major effect on tree health and require further attention. Majority of previous studies on fungal communities associated with P. abies were largely limited to a particular part of the tree such as the phyllosphere [32,39], soil or roots [40,41]. The detection of fungal diversity could also have been limited by some methodological constraints such as, e.g., fungal culturing. The recent development of high-throughput sequencing methods provides powerful tools to explore fungal diversity directly from Forests 2022, 13, 1103 3 of 24 environmental samples. Moreover, it generates semiquantitative information and enables taxonomic identification to the species of higher taxonomic level. The aim of this study was using a holistic approach to investigate the diversity and composition of fungal communities associated with the functional tissues and rhizosphere soil of healthy-looking, but growing under different edaphic and environmental conditions, P. abies stands in Lithuania. This was expected to provide a better understanding about these fungal communities and their potential effect on tree health in the process of climate change. The generated knowledge was also expected to be of practical importance as due to climate change, the territory of Lithuania is predicted to be outside the range of P. abies distribution by the end of this century [9,10]. We hypothesized that across the study sites, fungal communities associated with P. abies are highly variable due to tissue- and sitespecific conditions. Specifically, the diversity of fungal communities in the rhizosphere soil and in tree roots, including ectomycorrhizal (ECM) fungi, are dependent on soil chemical parameters, the forest type, and tree age as forest soils represent a highly heterogenous environment and fungal diversity accumulates over years. ECM diversity is largely driven by soil fertility as their importance for tree nutrition decreases with the increase of soil fertility, leading to the shift in community composition as certain ECM fungi prefer more fertile soils than others. Fungal communities in needles and shoots are similar to each other due to more homogeneous habitats and their proximity, and the dependence on climatic factors. Fungal communities in needles and shoots have a lower species diversity as compared to belowground fungal communities as newly produced needles and shoots are colonised each year after their emergence. 2. Material and Methods 2.1. Study Sites and Sampling The study sites were at 30 P. abies stands distributed throughout the territory of Lithuania (Figure 1, Table 1). These sites were at the same positions as the plots of the Forest Monitoring Level I transnational grid [42], which is used for regular monitoring of stand health, growth, and changes in the forest composition and cover. These sites represent a systematic grid across the country and include a diversity of stand (e.g., age, stand composition, forest site type and vegetation type) and environmental conditions. At each study site, the health condition of P. abies trees was assessed using tree damage categories [43]. Meteorological data were obtained from the nearest meteorological stations. Information on stand characteristics and materials sampled (needles, shoots, roots, and the soil) is in Table 1. The classification of forest site type (Table 1) is based on [44]. The classification describes three components, namely the soil moisture, fertility, and granulometric composition, which are indexed as a combination of three letters (one for each component) as, e.g., Ncl. The first letter refers to soil moisture: N—soils of normal atmospheric moisture, groundwater is usually deeper than 3 m from the surface; L— temporary water-logged and gleyic soils; P—non-drained forest wetlands (characterised based on the thickness of the peat layer). The second letter of the index describes soil fertility: a—very infertile; b—poor fertility; c—moderate fertility; d—high fertility. The third letter of the index shows the granulometric composition: l—light soils (sand, sandy loam, and gravel); s—heavy soils (loam, clay, chalk, dolomite, gypsum); p—binary soils, when a layer of the light soil is on the heavy one (deposited deeper than 50 cm from the surface). Vegetation typology is based on [45], which describes the composition of phytocenosis, i.e., the composition of forest stand, shrubs, grasses, mosses, forest stand productivity, and habitat conditions, using Latin names of grasses and mosses (Table 1). Although those species, which are used for naming, are not always dominant on a particular site, the vegetation type is identified based on the characteristics of the whole vegetation. Forests 2022, 13, 1103 4 of 24 Figure 1. Map of Lithuania (position shown on the north European map in the lower left corner) showing the distribution of Norway spruce (Picea abies) forest stands (in green), where sampling of living shoots, needles, roots, and the rhizosphere soil was carried out. The gradient bar shows the percentage of P. abies trees in the composition of forest stands. At each site, for sampling of soil, the litter layer was removed, and samples were taken in the vicinity of P. abies trees down to 20 cm depth using a 2 cm diameter soil core, which was carefully cleaned between individual samples. Soil samples included five random replicates per site. Each soil sample consisted of ca. 50 g of organic soil layer and ca. 50 g of mineral soil layer. In total, 150 soil samples were collected. Samples of fine roots were excavated in the vicinity of five random P. abies trees. The soil was removed, and each sample included up to seven fine roots with root tips (up to 10 g in total). In total, 150 root samples were collected. Shoot and needle samples were taken from ten random P. abies trees. Telescopic secateurs were used to cut 2-year-old shoots with needles from the middle – the ground). An individual needle sample (one per part of crowns (about 10–12 m above tree) consisted of 25 healthy-looking needles, which were randomly collected from cut shoots using forceps, which were cleaned between individual samples. Shoot samples were prepared by removing remaining needles and cutting them into ca. 5 cm segments. In total, 300 needle and 300 shoot samples were collected. Individual soil, root, shoot, and needle samples were placed separately into plastic bags and labelled. The same day of sampling, mples to were transportedand to placed the laboratory and in −20 °C for samples were transported the laboratory in −20 ◦ C forplaced storage. To determine the chemical and physical properties of the soil, five random soil samples (ca. 200 g) per site were taken in the vicinity of P. abies trees and pooled together. In the laboratory, the collected soil samples were sieved using a 2 × 2 mm sieve to separate fine fraction soil. The pH of the soil was determined in the KCl extract using the potentiometric method (ISO 10390:2005), available phosphorus (P2 O5 ), and potassium K2 O (K) (mg kg−1 soil) using the Egner–Rim–Doming (A-L) method. −1 – – Forests 2022, 13, 1103 5 of 24 Table 1. Characteristics of Picea abies forest stands where needles, shoots, roots, and the rhizosphere soil were sampled. Site No. Geographical Position Stand Characteristics a Forest / Vegetation Type b Tree Species Composition, % c 25◦ 11′ Ncl/ox 55◦ 01′ 24◦ 12′ Lcl/mox 3 54◦ 52′ 23◦ 26′ 4 56◦ 12′ 5 56◦ 00′ 6 Soil Chemical Parameters Age (y) pH (KCl), mol/L P2 O5 , mg/kg 100S 50 3.9 306 100S 52 3.3 56 Pcn/fils 100S 61 2.4 65 21◦ 27′ Lbp/m 90S, 10P 59 3.0 21◦ 07′ Lbl/m 100S 59 2.8 55◦ 54′ 25◦ 13′ Lcs/mox 90S, 10A 67 5.8 7 55◦ 44′ 24◦ 43′ Lcl/mox 90S, 10P 57 8 56◦ 03′ 22◦ 56′ Lds/oxn 100S 48 9 56◦ 11′ 22◦ 23′ Lcp/mox 90S, 10P 58 10 54◦ 52′ 25◦ 42′ Ncl/ox 100S 35 11 55◦ 53′ 24◦ 12′ Ldf/oxn 80S, 20F 62 5.7 12 56◦ 03′ 23◦ 40′ Lds/oxn 90S, 10A 42 4.4 13 55◦ 29′ 24◦ 12′ Lds/oxn 100S 53 4.8 25 14 54◦ 35′ 23◦ 57′ Ncl/ox 100S 47 3.9 27 21 101 32 7.1 15 55◦ 27′ 23◦ 27′ Nds/hox 100S 50 4.0 19 77 942 147 5.3 16 56◦ 03′ 25◦ 42′ Lcp/mox 60S, 30PT, 10B 60 3.7 36 63 286 73 3.6 59 3.8 11 107 791 122 15 86 277 75 N E 1 55◦ 37′ 2 K2 O, mg/kg Ca, mg/kg Mg, mg/kg 43 267 39 242 296 32 12 Meteorological Data Cl, mg/kg Salts, ms/cm Average Temp., ◦ C Precipitation, mm/year 72 3.6 3.35 8.0 508.8 56 5.3 4.33 8.3 614.9 774 279 8.9 11.7 8.6 170 583 136 5.3 7.64 69 264 73 5.3 8.83 15 47 2256 490 3.6 6.49 3.1 8 21 154 28 1.8 5.1 12 38 1472 329 5.3 5.2 16 144 1770 270 5.3 3.8 169 40 176 48 3.6 17 75 2968 630 5.3 11 131 2952 542 7.1 76 1294 197 5.3 4.7 Stand Sanitary Condition Defoliation, % Dechromation, % Dry Branches, % 11.2 5.8 14.5 29.0 13.5 26.0 519.8 13.2 2.3 12.8 8.9 491.7 15.8 4.1 13.5 8.9 491.7 16.3 3.7 13.5 7.7 514.6 18.0 4.8 15.8 2.36 8.1 479.8 24.8 7.0 20.7 13.6 8.1 505.5 16.5 6.8 14.7 4.87 8.0 480.4 18.5 4.0 17.5 2.01 8.0 755.4 18.3 6.2 14.3 12.4 8.1 505.5 16.7 8.0 17.0 26.0 8.1 505.5 9.0 1.5 11.2 8.1 479.8 12.7 3.7 9.3 2.55 8.6 595.2 8.8 3.3 13.8 3.42 7.8 458 18.5 5.3 14.8 3.14 7.7 514.6 18.3 7.2 15.3 3.6 4.95 8.4 617.0 14.3 3.7 12.2 3.6 3.64 8.6 519.8 19.3 7.7 16.8 17 55◦ 28′ 21◦ 57′ Lcp/mox 60S, 20B, 10Q, 10A 18 55◦ 02′ 22◦ 41′ Lcl/mox 60S, 40P 23 2.8 19 54◦ 18′ 25◦ 40′ Ncl/ox 80S, 10Q, 10PT 39 3.8 71 43 157 42 5.3 3.06 8.0 530.6 15.8 2.0 12.7 20 54◦ 18′ 25◦ 40′ Nds/hox 100S 53 5.0 27 48 2584 374 7.1 11.1 8.1 479.8 25.3 16.5 25.7 21 55◦ 10′ 25◦ 42′ Nbl/v 90S, 10P 40 4.1 78 36 238 52 5.3 3.96 7.4 669.2 18.7 8.0 13.8 22 55◦ 19′ 22◦ 27′ Lcp/mox 90S, 10B 55 3.3 118 300 2092 566 7.1 18.5 8.6 591.3 8.7 0.3 12.7 23 55◦ 45′ 21◦ 41′ Ncs/ox 100S 50 4.1 71 123 2043 161 3.6 5.0 8.0 598.7 14.7 3.5 15.0 24 55◦ 44′ 22◦ 25′ Ncl/ox 100S 40 3.5 37 25 212 48 3.6 2.07 8.0 598.7 16.7 6.0 16.7 25 54◦ 44′ 24◦ 42′ Ncl/ox 100S 58 3.8 12 70 416 136 3.6 4.65 7.3 614.9 22.0 7.8 18.3 Forests 2022, 13, 1103 6 of 24 Table 1. Cont. Site No. Geographical Position Stand Characteristics Forest a / Vegetation Type b Tree Species Composition, % c Soil Chemical Parameters Age (y) pH (KCl), mol/L P2 O5 , mg/kg K2 O, mg/kg Ca, mg/kg Cl, mg/kg Salts, ms/cm Average Temp., ◦ C 2362 308 5.3 14.0 8.0 11,508 1184 3.6 8.43 8.0 520 14.2 33 7.7 42 3.6 2.73 8.0 593.2 16.2 2.7 12.8 117 3.6 5.0 8.0 540.9 14.2 3.3 11.2 E 26 54◦ 56′ 24◦ 42′ Lbl/m 80S, 10B, 10P 60 4.7 26 68 27 55◦ 10′ 24◦ 41′ Ncl/ox 60S, 20P, 20PT 50 6.6 544 183 28 55◦ 18′ 25◦ 42′ Pcn/fils 90S, 10B 52 3.0 132 237 2584 29 54◦ 25′ 24◦ 57′ Nbl/v 100S 68 3.4 23 31 161 30 54◦ 25′ 24◦ 27′ Ncl/ox 70S, 20B, 10P 48 3.7 169 53 512 Precipitation, mm/year Stand Sanitary Condition Mg, mg/kg N a Meteorological Data Defoliation, % Dechromation, % Dry Branches, % 535.8 13.7 2.5 10.7 506.9 21.3 5.7 17.2 505.4 19.3 5.2 17.7 N: Normal moisture; L: temporary waterlogged soils; P: wetlands. b: poor fertility; c: moderate fertility; d: high fertility. l: light soil texture; s: heavy soils; p: binary soils [44]. b ox: oxalidosum; oxn: oxalido-nemoroso-Piceetum; m: myrtillosa; mox: myrtillo-oxalidosa; v: vacciniosa; hox: Hepatico-oxalidosa; fils: Filipendulo-mixtoherbosa [45]. c S: Picea abies; P: Pinus sylvestris; B: Betula pendula; A: Alnus incana; F: Fraxinus excelsior; PT: Populus tremula. In each stand, tree species composition is based on the volume. Forests 2022, 13, 1103 7 of 24 2.2. DNA Isolation, Amplification, and Sequencing The principles of the DNA work followed the study by Marčiulynienė et al. [46]. Prior to the isolation of the DNA, each sample (needles, shoots, roots, and the soil) was freeze-dried using a Labconco FreeZone Benchtop Freeze Dryer (Cole-Parmer, Vernon Hills, IL, USA) at −60 ◦ C for two days. After the freeze-drying, ca. 0.03 g dry weight of each needle, shoots or root sample was placed into a 2-mL screw-cap centrifugation tube together with glass beads. No surface sterilization of the samples was carried out. Samples were homogenized using a Fast prep shaker (Bertin Technologies, Montigny-le-Bretonneux, France). The DNA was isolated using CTAB extraction buffer (0.5 M EDTA pH 8.0, 1 M Tris-HCL pH 8.0, 5 M NaCl, 3% CTAB) followed by incubation at 65 ◦ C for 1 h. After the centrifugation, the supernatant was transferred to a new 1.5-mL Eppendorf tube, mixed with an equal volume of chloroform, centrifuged at 10,000 rpm for 8 min, and the upper phase was transferred to new 1.5-mL Eppendorf tubes. Then, an equal volume of 2-propanol was used to precipitate the DNA into a pellet by centrifugation at 13,000 rpm for 20 min. The pellet was washed in 500 µL 70% ethanol, dried, and dissolved in 30 µL sterile milli-Q water. Differently from other samples, ca. 1 g of freeze-dried soil per each sample was used for the isolation of the DNA using a NucleoSpin® Soil kit (Macherey-Nagel GmbH & Co., Düren, Germany) according to the manufacturer’s recommendations. Following the isolation, the DNA concentration in individual samples (needles, shoots, roots, and the soil) was determined using a NanoDrop™ One spectrophotometer (Thermo Scientific, Rodchester, NY, USA) and adjusted to 1–10 ng/µL. Amplification of the ITS2 rRNA region was done using a fungal specific primer gITS7 [47] and a universal primer ITS4 [48], both containing sample identification barcodes. Samples of the same substrate (needles, shoots, roots of the soil) and site were amplified using primers with the same barcode. PCR was performed in 50 µL reactions and consisted of the following final concentrations, 0.25 ng/µL-template DNA, 200 µM of dNTPs; 750 µM of MgCl2 ; 0.025 µM DreamTaq Green polymerase (5 U/µL) (Thermo Scientific, Waltham, MA, USA), and 200 nM of each primer. Amplifications were performed using the Applied Biosystems 2720 thermal cycler. The PCR program started with denaturation at 95 ◦ C for 5 min, followed by 30 cycles of 95 ◦ C for 30 s, annealing at 56 ◦ C for 30 s and 72 ◦ C for 30 s, followed by a final extension step at 72 ◦ C for 7 min. The PCR products were assessed using gel electrophoresis on 1% agarose gel stained with Nancy-520 (Sigma-Aldrich, Stockholm, Sweden). PCR products were purified using 3 M sodium acetate (pH 5.2) (Applichem Gmbh, Darmstadt, Germany) and 96% ethanol mixture (1:2). After quantification of PCR products using a Qubit fluorometer 4.0 (Life Technologies, Stockholm, Sweden), samples were pooled in an equimolar mix and used for PacBio sequencing using two SMRT cells at the SciLifeLab in Uppsala, Sweden. 2.3. Bioinformatics The sequence reads were subjected to control of quality and clustering using the SCATA NGS sequencing pipeline at http://scata.mykopat.slu.se (accessed on 10 September 2021). Quality filtering was done by removing short sequences (<200 bp), sequences with low read quality (Q < 20), primer dimers, and homopolymers, which were collapsed to 3 base pairs (bp) before clustering. Sequences lacking a tag or primer were also removed. The primer and sample barcodes were then removed, but information on the sequence association with the sample was stored as meta-data. The sequences were clustered into different OTUs using single-linkage clustering based on 98% similarity. The most common genotype (real read) for each cluster was used to represent each OTU. For clusters containing two sequences, a consensus sequence was produced. Fungal OTUs were taxonomically identified using the GenBank (NCBI) database and the Blastn algorithm. The criteria used for identification were: sequence coverage >80%; similarity to species level 98–100%, similarity to genus level 94–97%. Sequences not matching these criteria were given unique names. Representative sequences of fungal non-singletons as the Targeted Locus Study project have been deposited in GenBank under accession number KFPS00000000. Fungal functional groups were annotated using the FUNGuild fungal database [49], and, if needed, Forests 2022, 13, 1103 8 of 24 were further refined using information at the MycoBank database. In case the fungus had two possible functional groups, it was classified based on the FUNGuild categorisation. 2.4. Statistical Analyses Rarefaction analysis was performed using Analytical Rarefaction v.1.3 available at http: //www.uga.edu/strata/software/index.html (accessed on 15 November 2021). Correlation analysis of species richness among different study sites and substrates (needles, shoots, roots, and the soil) was carried out in Minitab v. 18.1 (University Park, Pennsylvania, PA, USA). The Shannon diversity index and qualitative Sørensen similarity index were used to characterise the diversity of fungal communities [50,51]. The nonparametric Mann–Whitney test in Minitab was used to test if the Shannon diversity index among different sites and samples was statistically similar or not. The effects of the substrate, environmental variables at a site level, and soil characteristics at a site level on species richness (number of fungal OTUs per sample) were assessed using generalized linear mixed effect models (glmmTMB function from the glmmTMB package [52]). Correlation between predictor variables was assessed using cor function in R [53]. When the correlation coefficient between the two variables was higher than 0.7, only one variable was selected to be used in the final model. Final model contained the following variables as fixed factors: tree composition, age, and defoliation (i.e., stand variables), average annual temperature and annual precipitation (i.e., environmental variables), and soil pH, P2 O5 , K2 O, and salts (i.e., soil variables). The interactions between each variable and the substrate were included in the model to assess if the effects of a variable were consistent across all substrates. The site was included in the model as a random factor. All continuous variables were scaled using the scale function in R [53]. Model predictions were calculated using ggpredict from the package ggeffects [54] in R and plotted using the ggplot function from the ggplot2 package [55]. The composition of fungal communities was studied using non-metric multidimensional scaling (NMDS) based on the Bray–Curtis similarity index. Analyses were carried out using both the complete dataset and the dataset without rare (<50 reads) OTUs. Oneway ANOSIM was performed to test for significant differences among different substrates. Tukey’s method was used for creating a set of confidence intervals between the means. These analyses were performed using Vegan 2.5.7 [56] and Stats 3.6.2 in R [53]. 3. Results High-throughput sequencing and quality filtering showed the presence of 232,548 highquality reads, which following clustering (at 98% similarity level) analysis were found to represent 3016 non-singleton OTUs. Among the non-singletons, 2701 (89.6%) were representing fungi (Supplementary Table S1), while the remaining 315 (10.4%) non-fungal OTUs were excluded. The number of high-quality sequences and fungal OTUs from each study site and substrate is in Table 2. When all sites were taken together, a plot of fungal OTUs vs. the number of fungal sequences resulted in rarefaction curves, which did not reach the asymptote (Figure 2). When the same number of sequences had been taken from different substrates (needles, shoots, roots, and the soil), the species richness was significantly higher in the soil than in other substrates (p < 0.05). Furthermore, the richness of fungal OTUs was significantly higher in the shoots and needles than in the roots (p < 0.05). In a similar comparison, shoots and needles did not differ significantly from each other (p > 0.05). Within each substrate (needles, shoots, roots, and the soil), the richness of fungal OTUs varied greatly among individual study sites (Figure 3). Correlation analysis showed that there was no significant correlation when the richness of fungal OTUs was compared among different substrates (p > 0.05). Forests 2022, 13, 1103 9 of 24 Table 2. Generated high-quality fungal sequences and detected diversity of fungal OTUs in different substrates from 30 Picea abies forest stands in Lithuania. Site No. of Sequences/Fungal OTUs Shannon Diversity Index (H) No. Needles Shoots Roots Soil Needles Shoots Roots Soil 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 4222/65 2533/27 1664/182 2605/241 2215/94 678/51 831/143 -/38/22 722/132 245/80 1020/139 2676/216 2860/203 7090/300 5675/84 865/150 6501/316 2276/232 1127/161 1205/149 5757/102 1447/155 2898/202 2927/208 821/128 1328/172 58/19 259/68 423/104 636/132 425/104 645/91 562/136 406/72 1088/120 247/64 1861/186 594/73 645/117 303/73 446/75 3314/145 98/41 1271/190 109/36 2173/216 11,512/201 2269/189 1312/100 1171/146 1699/145 3994/270 2521/173 2070/162 1642/103 952/132 6703/226 7618/242 1802/192 3136/145 413/87 702/47 139/31 21/7 706/79 277/57 205/38 1086/102 128/39 -/116/41 1047/117 3136/149 3/2 60/22 53/18 273/59 46/26 1041/63 178/24 150/42 84/18 385/63 135/25 417/51 856/76 3314/94 1539/116 807/62 1792/160 4586/295 24/19 1769/310 2327/210 2782/346 1079/171 1104/185 2212/192 1632/220 2796/338 2275/313 2011/292 1295/160 629/158 2450/209 2899/316 119/61 850/184 5301/269 8092/444 86/44 11,181/472 2354/309 3830/310 368/80 7218/410 8181/434 898/121 6811/273 0.34 0.14 4.16 4.36 1.12 1.25 4.28 2.89 4.06 3.67 3.52 3.78 4.14 3.95 4.20 1.01 4.18 4.29 4.06 3.96 0.72 4.06 4.09 4.17 3.89 4.05 2.03 3.21 3.89 3.95 4.01 3.42 3.43 4.11 3.36 3.66 3.81 2.87 3.89 3.44 3.57 3.18 3.27 4.34 3.01 4.30 3.25 4.09 2.53 3.88 3.73 4.08 3.21 4.13 2.99 3.91 3.56 3.54 4.05 2.77 3.27 2.49 1.68 2.55 3.15 3.03 2.92 3.22 3.15 3.16 3.07 3.00 0.64 2.35 2.25 3.12 3.08 2.41 2.59 3.06 1.95 3.03 2.28 2.68 3.06 2.62 3.29 2.60 3.52 4.38 2.92 3.82 4.96 4.78 3.85 4.13 3.00 4.26 4.89 5.01 4.67 4.34 4.41 3.72 4.49 3.62 4.56 3.82 3.99 3.42 4.33 4.87 4.22 3.73 4.12 4.18 3.95 3.02 Total 62,966/1049 60,188/1002 20,443/641 88,951/1895 Figure 2. Rarefaction curves showing the relationship between the cumulative number of fungal OTUs and the number of ITS rRNA sequences in needles, shoots, roots, and the rhizosphere soil. Forests 2022, 13, 1103 10 of 24 Figure 3. Map of Lithuania showing the richness of fungal OTUs associated with (A) needles, (B) shoots, (C) roots, and (D) the rhizosphere soil at different Picea abies sampling sites. By contrast, the species richness was significantly affected by variables reflecting the — soil chemistry. The pH had a similar effect on shoot and root fungi—species richness decreased with increased pH. The opposite trend was for soil fungi, while species richness of fungi in needles remained generally unaffected(χ(χ2 = 73, df = 3, p < 0.05) (Figure 4A). The increase of species richness with increased P2 O5 was only in roots, while fungi in all (χ other substrates showed the decrease of species richness with the increasing Pvalues 2 O5 values 2 (χ = 108, df = 3, p < 0.05) (Figure 4B). The increasing concentration of K2 O increased species richness in needles, but decreased in roots and soil, while fungi in shoots were generally unaffected unaffected (χ (χ2 = 252, df = 3, p < 0.05) (Figure 4C). The species richness increased in root and in the soil with the increasing concentration of salts, while the opposite was for needle and shoot fungi fungi (χ (χ2 = 156, df = 3, p < 0.05) (Figure 4D). and shoot The fungal species richness in roots increased with the stand age, while the opposite was for fungi in needles and the soil. The age of the stand did not affect the species richness in shoots (χ2 = 280, df = 3, p < 0.05) (Figure 4E). The increasing defoliation increased fungal species richness in needles and the soil, while the opposite was in shoots and roots (χ2 = 96, df = 3, p < 0.05) (Figure 4F). Climatic variables also showed a significant effect on species richness that varied depending on the type of substrate (χ2 = 34, df = 3, p < 0.05 and χ2 = 191, df = 3, p < 0.05 for temperature and precipitation, respectively). The fungal species richness in needles was decreasing with the increase of temperature and precipitation. In shoots, the fungal species richness decreased with the increase of temperature but increased with the increase of precipitation. The fungal species richness in roots and soil increased with the increase of precipitation. Although increasing temperature had a positive effect on richness of root fungi, the opposite was for fungi in the soil (Figure 4G,H). Forests 2022, 13, 1103 11 of 24 Figure 4. The relationship between the richness of fungal OTUs in different substrates (needles, shoots, roots, and the soil) of Picea abies and soil pH (A), P2 O5 (B), K2 O (C), salts (D), stand age (E), tree defoliation (F), yearly precipitation (G) and average yearly temperature (H). The semitransparent field around each curve denotes the size of deviation from the mean value. Among all fungal OTUs, 202 (7.5%) were exclusively found in shoots, 167 (6.2%)—in roots, 188 (6.9%)—in needles, 920 (34.1%)—in the soil, and 125 (4.6%) were shared among ness in shoots (χ different substrates (Figure 5). The lowest number of shared OTUs was between the root and shoot samples (11), while the highest number was between the root and soil samples (χ (232) (Figure 5). that varied depending on the type of substrate (χ species richness χ — — — Figure 5. Venn diagram showing the diversity and overlap of fungal OTUs in different substrates, — — collected in Picea— abies stands. Different colours represent different substrates: violet—needles, — red—shoots, blue—roots, and yellow—soil. — — — — Forests 2022, 13, 1103 12 of 24 Taxonomic identification showed that among all samples, Ascomycota accounted for 1575 (58.3%) fungal OTUs, followed by 1005 (37.2%) OTUs of Basidiomycota, 68 (2.5%) of Zygomycota, 42 (1.6%) of Chytridiomycota, 10 (0.4%) of Glomeromycota, and the least common was Neocallimastigomycota, which included one (0.04%) OTU. The distribution and relative abundance of fungal classes varied among different sites and substrates (Figure 6). Among all sites, the most dominant fungal classes in shoots were Dothideomycetes (33.6%), Eurotiomycetes (12.8%), and Tremellomycetes (12.2%). In the needles, these were Sordariomycetes (31.0%) and Dothideomycetes (18.0%), in the roots—Agaricomycetes (37.6%), Leotiomycetes (24.8%), and Archaeorhizomycetes (20.0%), while in the soil—Dothideomycetes (22.8%), Agaricomycetes (22.2%), and Leotiomycetes (15.0%) (Figure 6). Figure 6. Relative abundance (%) of fungal classes in needles, shoots, roots, and the rhizosphere soil of Picea abies. Others denote fungal classes with a relative abundance of <1%. Site numbers to the left are as in Table 1 and Figure 1. The most common fungal OTUs in shoots were Arachnopeziza sp. 5208_27 (6.0% of all high-quality sequences), Rhinocladiella sp. 5208_3 (5.4%), and Lophium arboricola (4.6%), in needles—Aspergillus pseudoglaucus (29.9%), Cyphellophora sessilis (3.8%), Rhizosphaera kalkhoffii (3.5%) and Trichomerium sp. 5208_23 (2.7%), in roots—Archaeorhizomyces sp. 5208_0 (18.4%), Phialocephala fortinii (9.8%), Mycena cinerella (9.5%) and Trechispora sp. 5208_19 (9.4%), and in the soil, these were Phacidium lacerum (3.7%), Agaricomycetes sp. 5208_12 (3.4%), and Archaeorhizomyces sp. 5208_0 (3.3%) (Table 3). Table 3. Occurrence and relative abundance of the 25 most common fungi (shown as a proportion of all high-quality fungal sequences) found in different substrates. The data from different NR137946 Endo sites are combined. 3 Unkn Fungal OTUs Phylum * Genbank Reference Aspergillus pseudoglaucus Archaeorhizomyces sp. 5208_0 Rhinocladiella sp. 5208_3 Arachnopeziza sp. 5208_27 Trichomerium sp. 5208_23 Phacidium lacerum Unidentified sp. 5208_1 A A A A A A A MT582752 MH248043 KM056296 MH558278 NR137946 MN588163 MT595563 Similarity, % 8 100 100 36 98 97 97 100 92 Needles, % Shoots, % Roots, % Soil, % All, % Ecological Role 29.9 2.4 1.7 0.7 2.7 0.6 1.2 0.01 0.3 5.4 6.0 3.9 0.3 3.7 0.1 18.4 0.01 0.2 0.03 0.05 3.3 0.5 0.5 0.4 3.7 1.0 7.9 3.6 2.0 1.9 1.9 1.7 1.6 Other ** Unknown Saprotroph Saprotroph Endophyte Pathogen Unknown Saprotroph Forests 2022, 13, 1103 13 of 24 Table 3. Cont. Fungal OTUs Phylum * Genbank Reference Similarity, % Needles, % Shoots, % Roots, % Soil, % All, % Ecological Role Dothideomycetes sp. 5208_5 Cladosporium herbarum Cyphellophora sessilis Rhizosphaera kalkhoffii Lophium arboricola Chaetothyriales sp. 5208_15 Sporidesmium sp. 5208_41 Agaricomycetes sp. 5208_12 Phialocephala fortinii Microsphaeropsis olivacea Malassezia restricta Clavulina sp. 5208_24 Chaetothyriales sp. 5208_2 Pezizomycotina sp. 5208_65 Mycena cinerella Blumeria graminis f. sp. tritici Trechispora sp. 5208_19 Umbelopsis dimorpha A A A A A A A A A A B B A A B A B Z KX908472 MT635288 KP400571 KY003236 MK159395 KP400572 MT596057 FJ553582 MN947395 MT561396 LT854697 OU498806 JQ342183 KP843512 KT900146 MT162615 JX392812 MT138616 99 100 100 100 100 100 100 99 100 100 100 99 99 96 100 100 99 100 0.6 2.1 3.8 3.5 0.2 1.6 2.1 0.1 0.4 0.6 1.0 0.2 0.4 0.1 0.01 0.002 0.2 0.5 0.9 1.4 1.1 4.6 3.0 2.8 0.01 0.04 1.5 0.6 0.4 3.1 0.01 0.002 0.01 0.1 0.3 0.01 0.07 0.01 0.01 0.01 0.01 9.8 0.1 0.4 0.04 9.5 9.4 0.01 3.3 1.7 0.1 0.5 0.3 0.4 0.1 3.4 0.5 1.5 1.7 2.9 2.4 0.3 0.4 2.4 0.1 2.1 1,5 1.5 1.4 1.4 1.4 1.3 1.3 1.3 1.2 1.1 1.1 1.1 1.1 1.0 0.9 0.9 0.8 0.8 Unknown Saprotroph Pathogen Pathogen Unknown Unknown Saprotroph Unknown Endophyte Other ** Other ** Mycorrhizal Unkonwn Unkonwn Saprotroph Pathogen Saprotroph Endophyte 54.9 39.4 48.4 33.3 42.1 Total of 25 OTUs, % * A—Ascomycota, B—Basidiomycota, Z—Zygomycota. ** Unrelated to plants. The relative abundance of most common plant pathogenic fungal OTUs is shown in Table 4. Plant pathogens were found to be most abundant in needles (9.7%) and soil (6.7%), when in shoots (4.6%), and these were least common in the roots (0.2%). In needles, the most common plant pathogens were C. sessilis (3.8%) and R. kalkhoffii (3.5%), in the soil—P. lacerum (3.8%) and Microsphaeropsis olivacea (1.5%), in shoots—M. olivacea (1.5%) and C. sessilis (1.4%), and in roots—Tapesia lividofusca (0.15%) and Neonectria sp. 5208_421 (0.15%) (Table 4). Table 4. Occurrence and relative abundance of the 15 most common plant pathogenic, mycorrhizal and endophytic fungi (shown as a proportion of all high-quality fungal sequences) found in different substrates of Picea abies. The data from different sites are combined. Fungi Phylum * Genbank Reference Similarity, % Needles, % Shoots, % Roots, % Soil, % All, % A A A A B A A A A B A A B A A MN588163 KP400571 MN547387 MT561396 FJ896135 MN341268 MK762595 MT635276 KT000192 MN902561 LR603781 OL636518 MN906143 MT557415 MT155386 100 100 100 100 99 100 100 100 100 95 100 100 100 99 100 0.6 3.8 3.5 0.6 0.8 0.00 0.2 0.05 0.07 0.1 0.1 0.01 0.01 0.3 1.4 1.1 1.5 0.1 0.8 0.03 0.03 0.2 0.03 0.06 0.01 0.01 0.2 0.01 0.07 0.1 0.01 0.1 0.1 0.1 0.02 0.02 3.7 0.1 0.5 1.5 0.04 0.03 0.5 0.1 0.2 0.03 0.1 0.04 0.01 0.06 0.04 1.7 1.4 1.4 1.2 0.3 0.2 0.2 0.1 0.1 0.07 0.05 0.05 0.03 0.03 0.02 Plant pathogens Phacidium lacerum Cyphellophora sessilis Rhizosphaera kalkhoffii Microsphaeropsis olivacea Exobasidium arescens Coniochaeta hoffmannii Phaeomoniella pinifoliorum Alternaria infectoria Hendersonia pinicola Typhula sp. 5208_156 Neonectria sp. 5208_421 Alternaria alternata Ganoderma applanatum Fusarium sp. 5208_517 Hymenoscyphus fraxineus Forests 2022, 13, 1103 14 of 24 Table 4. Cont. Fungi Phylum * Genbank Reference Similarity, % Total of 15 plant pathogens, % Needles, % Shoots, % Roots, % Soil, % All, % 9.8 5.6 0.7 6.9 6.9 0.02 ** 0.03 ** 0.05 ** - 0.003 ** 0.002 ** 0.002 ** - 2.5 0.005 0.03 2.9 0.005 0.04 0.2 - 2.9 1.9 0.8 1.2 1.2 1.2 0.9 0.06 0.5 0.5 0.4 0.4 0.3 0.2 0.3 1.1 0.7 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.007 5.8 12.7 5.4 2.7 0.4 0.2 0.003 0.003 0.003 0.002 0.005 0.002 3.9 0.0 0.005 0.6 0.002 0.007 0.003 0.002 0.007 - 9.8 0.01 0.7 0.03 0.02 0.02 - 0.4 0.5 2.1 0.05 0.007 0.002 0.003 0.004 0.004 0.002 1.9 1.2 0.8 0.2 0.06 0.005 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.001 3.4 4.5 10.5 3.0 4.2 Mycorrhizal Clavulina sp. 5208_24 Inocybe nitidiuscula Cenococcum geophilum Piloderma lanatum Inocybe geophylla Russula firmula Amphinema sp. 5208_105 Lactarius rufus Tricholoma sp. 5208_110 Inocybe geophylla Tylospora asterophora Amphinema sp. 5208_188 Cortinarius scotoides Piloderma sphaerosporum Inocybe pseudodestricta B B A B B B B B B B B B B B B OU498806 AM882913 HM189724 KP783452 MK961172 DQ422017 KP125811 MK838331 MK607553 MT594793 MG597438 MF352678 MW555551 MK131527 JF908157 99 99 100 100 99 100 100 100 100 100 100 99 99 100 100 Total of 15 mycorrhizal OTUs, % Endophytes Trichomerium sp. 5208_23 Phialocephala fortinii Umbelopsis dimorpha Mollisia scopiformis Mollisia sp. 5208_387 Mollisia sp. 5208_1830 Mollisia novobrunsvicensis Vestigium sp. 5208_802 Mollisia fusca Phialocephala fusca Phialocephala sp. 5208_2177 Phialocephala bamuru Mollisia sp. 5208_3430 Mycroceros sp. 5208_4863 Cadophora sp. 5208_2138 Total of 15 endophyte OTUs, % A A Z A A A A A A A A A A B A NR_137946 MN947395 MT138616 OM337553 OK430930 MG195564 MT026439 NR_121556 LC425049 KU668953 AB671500 MN006138 MG195527 KT186373 KY987540 97 100 100 100 97 96 100 94 98 99 98 97 98 96 97 * A—Ascomycota, B—Basidiomycota, Z—Zygomycota. ** Likely present as spores. The relative abundance of fungal functional groups in different substrates and sites is shown in Figure 7. Among the identified functional groups, the most abundant were saprotrophs: in roots these composed 18.6%, in shoots—18.1%, in the soil—9.4%, and in needles—3.6% (Figure 7). The relative abundance of plant pathogenic fungi was 5.5% in needles, 5.3% in the soil, 5.3% in shoots, and 1.1% in roots. Among all samples and sites, 11.6% of fungal sequences were assigned to “others”, which included fungi that are not associated with plants (mostly animal pathogens). In root and soil samples, the abundance of mycorrhizal fungi was 13.5% and 18.6%, respectively. The relative abundance of endophytes in roots was 10.5%, in the shoots—8.1%, in needles—4.3%, and soil—2.1% (Figure 7). NMDS showed that fungal communities in different substrates of P. abies were largely different, and thus, substrate-specific (p < 0.001) (Figure 8). Analysis of the data with or without rare OTUs (<50 reads) did not have a larger effect on the output of NMDS as both of these were similar. assigned to “others”, which included fungi that are not Forests 2022, 13, 1103 — — — 15 of 24 Figure 7. Relative abundance of fungal functional groups in different substrates (needles, shoots, roots, and the soil) of Picea abies. Other represent fungi (animal pathogens), which are not associated with plants. Site numbers to the left are as in Table 1 and Figure 1. Figure 8. Nonmetric multidimensional scaling (NMDS) of fungal communities showing differences and similarities in needle, shoot, root, and the rhizosphere soil samples of Picea abies. For each substrate, each point in the diagram represents a single sampling site. Forests 2022, 13, 1103 16 of 24 Furthermore, NMDS of fungal communities showed that soil physical parameters (moisture and fertility) did not have a significant effect on the composition of fungal communities in the soil (p > 0.05) (stress value: 0.17) (Figure 9A). However, soil moisture had a significant effect on the composition of fungal communities in needles, shoots, and roots of P. abies growing in wetlands (P) as compared to normal moisture (N) or temporary waterlogged soils (L) (p < 0.05) (Figure 9A). Moreover, soil fertility had a significant effect on the composition of fungal communities in needles and roots of P. abies growing in moderate fertility (c) soils as compared to high fertility (d) soils (p < 0.05) (Figure 9B). Stand age did not have a significant effect on the composition of fungal communities in needles, shoots, roots or the rhizosphere soil (p < 0.05) (Figure 9C). Although forest vegetation type did not have a significant effect on the composition of fungal communities in the soil (p > 0.05), some effects were observed for shoot and root samples. For example, in roots, significant differences in the composition of fungal communities were between the Oxalidosa (ox) vegetation type and Hepatico-oxalidosa (hox), Filipendulo-mixtoherbosa (fils), Vacciniosa (v), Oxalido-nemorosa (oxn) vegetation types (p < 0.05), and between Myrtillo-oxalidosa (mox) vegetation type and hox, fils, v and oxn vegetation types (p < 0.05) (Figure 9D). In shoots, significant differences in the composition of fungal communities were between oxalidosa (ox) vegetation type and hox, v, Myrtillosa (m) vegetation types (p < 0.05). Figure 9. Nonmetric multidimensional scaling (NMDS) of fungal communities detected in needles, shoots, roots, and the rhizosphere soil of Picea abies. For each substrate, each point in the diagram represents a single sampling site. NMDS shows the impact of soil moisture (A), soil fertility (B), stand age (C), and vegetation type (D) on the composition of fungal communities. The Sørensen similarity index of fungal communities ranged between 0.19 and 0.65 — when the comparison was done among different substrates, i.e., shoots vs. needles—0.65, — — — — shoots vs. soil—0.39, shoots vs. roots—0.19, needles vs. soil—0.42, needles vs. roots—0.26 — and soil vs. roots—0.34. In different substrates, the Shannon diversity index of fungal – – communities ranged between 1.68 and 3.29 in the roots, 0.14–4.36 in the needles, 2.53–4.34 – – Forests 2022, 13, 1103 17 of 24 in the shoots, and 2.92–5.01 in the soil (Table 2). The Mann–Whitney test showed that the Shannon diversity index of fungal communities differed significantly among different substrates (p < 0.05). An exception was the needle and shoot samples, which in this respect did not differ significantly from each other (p > 0.05). 4. Discussion We studied fungal communities associated with the functional tissues (needles, shoots, and roots) and the rhizosphere soil of P. abies, which is one of most economically and ecologically important tree species in Central and Northern Europe as it occupies a large geographical area and grows under different environmental conditions [3]. As the present study encompassed several environmental conditions and habitats of P. abies (Table 1), it provided new and in-depth information on the diversity and composition of associated fungal communities in the region. It also revealed the potential effects of different factors on richness and composition of these fungal communities (Figures 4 and 9). The fungal species richness associated with P. abies was found to be high even though some site- and sample-specific variations were observed (Table 2). Interestingly, it was highest in the soil, then in the needles and shoots, and lowest in the roots (Table 2, Figure 2), showing the capacity of each habitat to support fungal diversity. This is not surprising as the fungal species richness in the soil was shown to be particularly high [57,58]. In general, soil fungi can occupy different ecological niches depending on available resources [59]. Organic and mineral nutrients present in the soil create favourable conditions for fungal activities such as decomposition and nutrient assimilation [60,61]. With a high diversity and complexity of fungal communities in the soil, the rate of decomposition and the release of nutrients increases [62], which also stimulates the uptake of nutrients by plants [63,64]. These factors promote tree viability and growth at the same time making them more tolerant to pathogens. Although the majority of fungal OTUs were detected, even higher OUT richness could be revealed with deeper sequencing (Figure 2). Furthermore, in different sites and substrates, the detected diversity of fungal OTUs varied substantially (Figures 3 and 6), thereby highlighting the complexity of fungal colonisation patterns as well as interactions among the host trees, fungi, and local environmental conditions. Although the study included a number of different environmental conditions and habitats (Table 1), the comparison among different sites showed that within each substrate (needles, shoots, roots, and the soil), the richness of fungal OTUs was statistically similar (Figures 5 and 8, Table 2). The richness and composition of fungal communities are known to be affected by a variety of biotic and abiotic factors [65,66]. For example, the soil pH is one of the most important determinants of microbial communities in the soil as their richness and composition varies depending on the pH gradient [67,68]. This is in agreement with results of the present study as the richness of fungal species in the soil increased with the increase of soil pH (Figure 4A). The soil pH was also found to be among principal factors explaining ECM fungal diversity. In many cases, P2 O5 , K2 O and salts were commonly studied as these soil parameters are known to affect plant growth, but information on how these parameters affect the fungal species richness in forest soils is scarce. Therefore, the results of the present study provided new valuable information, namely how these parameters affect the fungal species richness associated with P. abies. Interestingly, the increasing P2 O5 increased the fungal species richness in roots (Figure 4B). This may be due to the fact that phosphorus is essential for plant nutrition and growth, which may increase the allocation of carbohydrates belowground, thereby benefiting root-associated microorganisms [69]. The increasing amounts of K2 O had the most pronounced effect on the richness of fungal species in the needles (Figure 4C) as K2 O is essential for photosynthesis, including such functions as reduced respiration and energy losses, and enhanced translocation of sugars and starch [70]. The tree age had a positive effect of the fungal species richness in roots but not in other substrates. Fungi associated with plant roots were shown to be dynamic throughout plant Forests 2022, 13, 1103 18 of 24 life [71,72]. As the plant develops and matures, the morphology and development of roots change, creating new spaces for the emergence and distribution of mycobiota. Therefore, there should be more different niches suitable for the fungi to establish in the root system of the older plants than in the younger ones [73]. By contrast, the study showed that in needles, the fungal species richness is highest in young and most actively growing trees (Figure 4E). In contrast to our expectations, the tree age had little or no effect on the richness of fungal OTUs, including ECM species, in the soil. The increase of tree defoliation promoted the fungal species richness in needles and soil, but adversely affected these in shoots and roots (Figure 4D). In agreement, it was shown that defoliated trees often have a lower diversity of ECM fungi in the roots and a higher diversity and relative abundance of saprotrophic and pathogenic fungi in the soil [74]. This may be due to the fact that many saprotrophic fungi may feed on dead mycorrhizal structures, but may also benefit from dead organic matter such as dying/dead roots [75]. Changes in soil fungal community in defoliated stands may be due to the fall of dead needles on the ground, what may constitute a new substrate for colonisation, thereby indirectly affect fungal communities [76,77]. The reason for the observed defoliation was not established, but can possibly be due to insect attacks, diseases or climatic factors [38,78]. It was shown that damages caused by insects in the phyllosphere can invoke drastic alteration in fungal communities associated with this habitat [38]. The average annual temperature and annual precipitation were shown to be useful indicators of plant and animal diversity [79]. In the present study, both of these environmental factors had a similar effect on the fungal species richness in roots and needles, but the effect of these factors was different in shoots and in the soil (Figure 4G,H). It was shown before that temperature and precipitation may have a different effect on fungal diversity in different parts of plants [80,81]. Together with the soil pH, the annual precipitation was found to be among major factors describing fungal diversity in the soil, at the same time, demonstrating that the lack of precipitation may result not only in the decline of host trees but also in the decline of fungal diversity. In the present study, NMDS showed that fungal communities were best explained by the substrate (needles, shoots, roots, and the soil) (Figure 8). NMDS also showed that both the forest vegetation type and soil physical properties did not have a significant effect on the composition of soil fungal communities (Figure 9A) even though small differences in soil physical properties can be expected to impact soil fungal communities [82,83]. Moreover, it was shown that well-aerated soils have generally a higher diversity of microorganisms than waterlogged ones [84]. The possibility should not be excluded that P. abies as a dominant tree species, had a major (homogenising) impact on fungal communities in the soil, leading to more similar soil fungal communities at different study sites. By contrast, certain vegetation types and soil physical properties had a significant effect on fungal communities associated with functional tissues of P. abies (Figure 9B,D). These effects can probably be explained by differences in water and nutrient availability, and thus, differences in nutrition of P. abies, which may determine the abundance and composition of associated fungal communities in specific tissues. In roots, these effects were most pronounced for mycorrhizal fungi, while in the aboveground parts—for endophytic fungi (Figure 7). In agreement, it was shown that the abundance of mycorrhizal fungi is affected by different soil properties, the time of sampling and climatic conditions [85,86]. Interactions between trees and fungal endophytes and patterns of colonisation are still not well understood, but generally these fungi are ubiquitous [33]. Although endophytic fungi may colonise tissues without causing symptoms [39,87], these may include different functional groups of fungi such as symbionts, latent pathogens, or saprotrophs [39,88]. Several different fungal phyla were detected among which Ascomycota and Basidiomycota were most common. Ascomycota was found to be more common in the aboveground tissues (needles and shoots), while Basidiomycota—belowground (in roots and soil), even though the difference was not significant. The phylum Ascomycota is the largest in the fungal kingdom, its species has a broad distribution and adapted to a variety of Forests 2022, 13, 1103 19 of 24 habitats [89,90]. A higher abundance of Basidiomycota belowground can be attributed to the presence of basidiomycetous mycorrhizal and saprotrophic fungi, which play key roles in nutrient recycling in forest ecosystems [91,92]. The study also revealed that different tissues and the rhizosphere soil of P. abies were inhabited by a number of plant pathogenic fungi, but their relative abundance was rather low (Figure 7, Table 4), indicating that at the time of sampling, they did not cause any significant damage to the trees. The dominant pathogenic fungi were often substratespecific (Table 4). In needles, the most abundant pathogens were C. sessilis, R. kalkhoffi and E. arescens, which are widespread in Europe. Cyphellophora sessilis can cause characteristic symptoms known as black sooty mould disease, which can occur on needles and shoots of different tree species [38,93,94]. The fungus has a negative effect on the tree’s respiration process and appears to benefit from other tree damages [38]. Interestingly, the occurrence of C. sessilis negatively correlated with the stand age. The abundance of R. kalkhoffi and E. arescens was found to be slightly higher than in other similar studies [38,95]. As these pathogens are often associated with older needles, the sampling strategy, i.e., the use of twoyear-old needles, may have contributed to their higher abundances [95–97]. Microsphaeropsis olivacea (syn. Coniothyrium olivaceum) was the most common pathogen in shoots (Table 4). Although it can occur as an endophyte [98,99], it was also shown to cause brown spine rot in colonised tree tissues [100]. It has a broad host range and geographical distribution, suggesting that it can adapt to a variety of conditions. The predominant establishment in asymptomatic P. abies shoots may suggest that under appropriate conditions, e.g., when trees are stressed, it may become pathogenic, develop rapidly, and cause the disease. Plant pathogenic fungus P. lacerum was among the most common fungi in the soil (Tables 3 and 4). Although it was suggested to be a widespread endophyte [101], it was also shown to be a weak pathogen of P. sylvestris and Juniperus needles [102]. However, the negative effect of P. lacerum on P. abies was not shown before. In the present study, P. lacerum showed a strong positive correlation with P2 O2 , Ca, and Mg, and a strong negative correlation with an average annual temperature. Pathogenic fungi from the genera Alternaria and Fusarium were also among most dominant in the soil (Table 3). These are generally known as soil-borne pathogens, which are commonly found in soils of the temperate climate zone [103,104]. Although their relative abundance was relatively low, climate change and higher temperatures in the soil can be expected to favour the activity and spread of these fungi [105]. Pathogenic fungi were least common in the roots and included representatives from genera such as Neonectria, Hymenoscyphus, Alternaria or Ganoderma (Table 4). Although many of these are generalists and commonly found in tree roots [106], H. fraxineus is a pathogen of Fraxinus spp. in Europe and is not associated with P. abies. The detection of H. fraxineus in different samples of the study was probably due to the presence of its propagules on the surface of different tissues (needles, shoots, or roots) and in the soil as the surface of our samples was not sterilised, and the disease caused by this fungus is active in the area [107]. The soil and tree roots were commonly colonised by mycorrhizal fungi (Table 4, Figure 7), which may also have limited the occurrence and activity of pathogenic fungi [108]. The mechanism for this was suggested to be the secretion of antimicrobial compounds and/or the completion for the space and resources. Moreover, mycorrhizal colonisation may lead to improved tree health due to enhanced nutrition, resulting in higher overall disease tolerance [109,110]. 5. Conclusions The functional tissues and rhizosphere soil of P. abies were inhabited by a speciesrich communities of fungi. Within each substrate, fungal communities appeared to be similar, but several environmental variables had a significant effect on their diversity and community composition. The latter may suggest that fungi in different functional tissues and the rhizosphere soil of P. abies can be affected by climate change to a different extent with consequences for forest health and sustainability. The continuous monitoring of Forests 2022, 13, 1103 20 of 24 fungal diversity and community composition is needed to better understand the short- and long-term effects of climate change in forest ecosystems. Supplementary Materials: The following are available online at https://www.mdpi.com/article/ 10.3390/f13071103/s1, Table S1: Relative abundance (%) of fungal OTUs associated with needles, shoots, roots, and the rhizosphere soil of Picea abies in Lithuania. Author Contributions: Conceptualization, A.M. (Audrius Menkis); methodology, A.M. (Adas Marčiulynas), D.M., A.G., V.M. and A.M. (Audrius Menkis); software, V.M. and I.F.; validation, A.M. (Adas Marčiulynas), D.M. and A.M. (Audrius Menkis); formal analysis, A.M. (Adas Marčiulynas) and I.F; investigation, D.M., J.L., A.G. and V.M.; writing—original draft preparation, A.M. (Adas Marčiulynas); writing—review and editing, D.M., J.L. and A.M. (Audrius Menkis); visualization, D.M. and J.L. All authors have read and agreed to the published version of the manuscript. Funding: This project has received funding from European Social Fund (project No. 09.3.3-LMT-K712-01-0039) under grant agreement with the Research Council of Lithuania (LMTLT). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest. References 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. Schlyter, P.; Stjernquist, I.; Barring, L.; Jonsson, A.M.; Nilsson, C. Assessment of the impacts of climate change and weather extremes on boreal forests in northern Europe, focusing on Norway spruce. Clim. Res. 2006, 31, 75–84. Available online: http://www.jstor.org/stable/24869264 (accessed on 29 January 2022). [CrossRef] Seppä, H.; Alenius, T.; Bradshaw, R.H.; Giesecke, T.; Heikkilä, M.; Muukkonen, P. Invasion of Norway spruce (Picea abies) and the rise of the boreal ecosystem in Fennoscandia. J. Ecol. 2009, 97, 629–640. [CrossRef] Caudullo, G.; Tinner, W.; de Rigo, D. Picea abies in Europe: Distribution, Habitat, Usage and Threats; San-Miguel-Ayanz, J., de Rigo, D., Caudullo, G., Houston Durrant Mauri, A., Eds.; European Atlas of Forest Tree Species; Publication Office of the European Union: Luxembourg, 2016; pp. 114–116. Horgan, T.; Keane, M.; McCarthy, R.; Lally, M.; Thompson, D.; O’Carroll, J. A Guide to Forest Tree Species Selection and Silviculture in Ireland; National Council for Forest Research and Development (COFORD): Dublin, Ireland, 2003. Farjon, A. Handbook of the World’s Conifers: Revised and Updated Edition; Brill: Leiden, The Netherlands, 2017; Volume 1, pp. 21–24. Bradshaw, R.H.W.; Holmqvist, B.H.; Cowling, S.A.; Sykes, M.T. The effects of climate change on the distribution and management of Picea abies in southern Scandinavia. Can. J. For. Res. 2000, 30, 1992–1998. [CrossRef] Eckstein, D.; Krause, C. Dendroecologlcal Studies on Spruce Trefs to Monitor Environmental Changes Around Hamburg. IAWA J. 1989, 10, 175–182. [CrossRef] Lovelius, N.V. Dendroindication of Natural Processes and Anthropogenic Influenses; World and Family: St.-Peterburg, Russia, 1997; 320p. Hanewinkel, M.; Cullmann, D.A.; Schelhaas, M.-J.; Nabuurs, G.-J.; Zimmermann, N.E. Climate change may cause severe loss in the economic value of European forest land. Nat. Clim. Chang. 2013, 3, 203–207. [CrossRef] Zimmermann, N.E.; Normand, S.; Pearman, P.B.; Psomas, A. Chapter III: Future ranges in European tree species. In Adapting to Climate Change in European Forests–Results of the MOTIVE Project; Pensoft Publishers: Sofia, Bulgaria, 2013; 108p. Jandl, R. Climate-induced challenges of Norway spruce in Northern Austria. Trees For. People 2020, 1, 100008. [CrossRef] Vitasse, Y.; Hoch, G.; Randin, C.F.; Lenz, A.; Kollas, C.; Körner, C. Tree recruitment of European tree species at their current upper elevational limits in the Swiss Alps. J. Biogeogr. 2012, 39, 1439–1449. [CrossRef] Grigor’ev, A.A.; Moiseev, P.A.; Nagimov, Z.Y. Dynamics of the timberline in high mountain areas of the nether-polar Urals under the influence of current climate change. Russ. J. Ecol. 2013, 44, 312–323. [CrossRef] Bebber, D.P.; Ramotowski, M.A.; Gurr, S.J. Crop pests and pathogens move polewards in a warming world. Nat. Clim. 2013, 3, 985–988. [CrossRef] Woodward, S.; Bodles, W.J.; Oszako, T. Occurence of phytophthora species in European forests. Folia For. Pol. Ser. A For. 2005, 47, 5–12. Sherwood, P.; Villari, C.; Capretti, P.; Bonello, P. Mechanisms of induced susceptibility to Diplodia tip blight in drought-stressed Austrian pine. Tree Physiol. 2015, 35, 549–562. [CrossRef] [PubMed] Barklund, P.; Rowe, J. Gremmeniella abietina (Scleroderris lagerbergii), a primary parasite in a Norway spruce dieback. Eur. J. For. Pathol. 1981, 11, 97–108. [CrossRef] Forests 2022, 13, 1103 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 21 of 24 Garrett, K.A.; Dendy, S.P.; Frank, E.E.; Rouse, M.N.; Travers, S.E. Climate change effects on plant disease: Genomes to ecosystems. Annu. Rev. Phytopathol. 2006, 44, 489–509. [CrossRef] [PubMed] Fisher, M.C.; Henk, D.; Briggs, C.J.; Brownstein, J.S.; Madoff, L.C.; McCraw, S.L.; Gurr, S.J. Emerging fungal threats to animal, plant and ecosystem health. Nature 2012, 484, 186–194. [CrossRef] [PubMed] Luchi, N.; Capretti, P.; Feducci, M.; Vannini, A.; Ceccarelli, B.; Vettraino, A.M. Latent infection of Biscogniauxia nummularia in Fagus sylvatica: A possible bioindicator of beech health conditions. iForest Biogeosci. For. 2015, 9, 49–54. [CrossRef] Raaijmakers, J.M.; Paulitz, T.C.; Steinberg, C.; Alabouvette, C.; Moënne-Loccoz, Y. The rhizosphere: A playground and battlefield for soilborne pathogens and beneficial microorganisms. Plant Soil 2009, 321, 341–361. [CrossRef] Carroll, G. Fungal endophytes in stems and leaves: From latent pathogen to mutualistic symbiont. Ecology 1988, 69, 2–9. [CrossRef] LeBlanc, N.; Kinkel, L.L.; Kistler, H.C. Soil fungal communities respond to grassland plant community richness and soil edaphics. Microb. Ecol. 2015, 70, 188–195. [CrossRef] Peay, K.G.; Kennedy, P.G.; Talbot, J.M. Dimensions of biodiversity in the Earth mycobiome. Nat. Rev. Microbiol. 2016, 14, 434–447. [CrossRef] Zhang, Z.; Zhou, X.; Tian, L.; Ma, L.; Luo, S.; Zhang, J.; Li, X.; Tian, C. Fungal communities in ancient peatlands developed from different periods in the Sanjiang Plain, China. PLoS ONE 2017, 12, e0187575. [CrossRef] Von Weissenberg, K. Effect of temperature on dormancy, activation and long-term storage of teliospores of Melampsora pinitorqua. Folia For. 1980, 422, 32–36. Desprez-Loustau, M.L.; Capron, G.; Dupuis, F. Relating germination dynamics of Melampsora pinitorqua teliospores to temperature and rainfall during overwintering. Eur. J. For. Pathol. 1998, 28, 335–347. [CrossRef] Tedersoo, L.; Anslan, S.; Bahram, M.; Drenkhan, R.; Pritsch, K.; Buegger, F.; Padari, A. Regional scale in depth analysis of soil fungal diversity reveals strong pH and plant species effects in Northern Europe. Front. Microb. 2020, 11, 1953. [CrossRef] [PubMed] Bajpai, A.; Johri, B.N. Climate Change is Real: Fungal Perspective. Kavaka 2019, 53, 12–21. [CrossRef] Huse, K.J. The distribution of fungi in sound-looking stems of Picea abies in Norway. Eur. J. Plant Pathol. 1981, 11, 1–6. [CrossRef] Müller, M.M.; Hallaksela, A.M. Diversity of Norway spruce needle endophytes in various mixed and pure Norway spruce stands. Mycol. Res. 1998, 102, 1183–1189. [CrossRef] Müller, M.M.; Hallaksela, A.M. Fungal diversity in Norway spruce: A case study. Mycol. Res. 2000, 104, 1139–1145. [CrossRef] Terhonen, E.; Blumenstein, K.; Kovalchuk, A.; Asiegbu, F.O. Forest tree microbiomes and associated fungal endophytes: Functional roles and impact on forest health. Forests 2019, 10, 32. [CrossRef] Petrini, O. Fungal endophytes of tree leaves. In Microbial Ecology of Leaves; Springer: New York, NY, USA, 1991; pp. 179–197. Rosling, A. Responses of Ectomycorrhizal Fungi to Mineral Substrates. Ph.D. Thesis, Swedish University of Agricultural Sciences, Uppsala, Sweden, 2003. Baldrian, P.; Kolařík, M.; Štursová, M.; Kopecký, J.; Valášková, V.; Větrovský, T.; Žifčáková, L.; Šnajdr, J.; Rídl, J.; Vlček, Č.; et al. Active and total microbial communities in forest soil are largely different and highly stratified during decomposition. ISME J. 2012, 6, 248–258. [CrossRef] Smith, S.E.; Read, D.J. Mycorrhizal Symbiosis; Academic Press: London, UK, 1997. Menkis, A.; Marčiulynas, A.; Gedminas, A.; Lynikienė, J.; Povilaitienė, A. High-throughput sequencing reveals drastic changes in fungal communities in the phyllosphere of Norway spruce (Picea abies) following invasion of the spruce bud scale (Physokermes piceae). Microb. Ecol. 2015, 70, 904–911. [CrossRef] Rajala, T.; Velmala, S.M.; Tuomivirta, T.; Haapanen, M.; Müller, M.; Pennanen, T. Endophyte communities vary in the needles of Norway spruce clones. Fungal Biol. 2013, 117, 182–190. [CrossRef] [PubMed] Uroz, S.; Oger, P.; Tisserand, E.; Cébron, A.; Turpault, M.-P.; Buée, M.; de Boer, W.; Leveau, J.H.J.; Frey-Klett, P. Specific impacts of beech and Norway spruce on the structure and diversity of the rhizosphere and soil microbial communities. Sci. Rep. 2016, 6, 27756. [CrossRef] [PubMed] Schön, M.E.; Nieselt, K.; Garnica, S. Belowground fungal community diversity and composition associated with Norway spruce along an altitudinal gradient. PLoS ONE 2018, 13, e0208493. [CrossRef] Seidling, W.; Hansen, K.; Strich, S.; Lorenz, M. Part I: Objectives, Strategy and Implementation of ICP Forests. In Manual on Methods and Criteria for Harmonized Sampling, Assessment, Monitoring and Analysis of the Effects of Air Pollution on Forests; UNECE ICP Forests Programme Co-Ordinating Centre, Ed.; Thünen Institute of Forest Ecosystems: Eberswalde, Germany, 2017; pp. 1–12, + Annex; Available online: http://www.icp-forests.net/page/icp-forests-manual (accessed on 23 February 2022). Ozolinčius, R.; Stakėnas, V. Tree condition assessment. In Monitoring of Ecosystem in Lithuania; Ozolinčius, R., Armolaitis, K., Augustaitis, A., Kairiūkštis, L., Stakėnas, V., Vaičys, M., Eds.; Lututė: Kaunas, Lithuania, 1999; p. 308. (In Lithuanian) Vaičys, M. Miško dirvožemiu˛ klasifikacija. In Lietuvos Dirvožemiai; Mokslas: Vilnius, Lithuania, 2001; pp. 1040–1043. (In Lithuanian) Karazija, S. Lietuvos Miško Tipai; Mokslas: Vilnius, Lithuania, 1988; pp. 46–48. Marčiulynienė, D.; Marčiulynas, A.; Lynikienė, J.; Vaičiukynė, M.; Gedminas, A.; Menkis, A. DNA-metabarcoding of belowground fungal communities in bare-root forest nurseries: Focus on different tree species. Microorganisms 2021, 9, 150. [CrossRef] [PubMed] Forests 2022, 13, 1103 47. 48. 49. 50. 51. 52. 53. 54. 55. 56. 57. 58. 59. 60. 61. 62. 63. 64. 65. 66. 67. 68. 69. 70. 71. 72. 73. 74. 22 of 24 Ihrmark, K.; Bodeker, I.T.M.; Cruz-Martinez, K.; Friberg, H.; Kubartova, A.; Schenck, J.; Strid, Y.; Stenlid, J.; Brandstrom-Durling, M.; Clemmensen, K.E.; et al. New primers to amplify the fungal ITS2—Evaluation by 454-sequencing of artificial and natural communities. FEMS Microbiol. Ecol. 2012, 82, 666–677. [CrossRef] [PubMed] White, T.J.; Bruns, T.; Lee, S.; Taylor, J. Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In PCR Protocols: A Guide to Methods and Applications; Innis, M.A., Gelfand, D.H., Sninsky, J.J., White, T.J., Eds.; Academic Press: San Diego, CA, USA, 1990; pp. 315–322. Nguyen, N.H.; Song, Z.; Bates, S.T.; Branco, S.; Tedersoo, L.; Menke, J.; Schilling, J.S.; Kennedy, P.G. FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild. Fung. Ecol. 2016, 20, 241–248. [CrossRef] Shannon, C.E. A mathematical theory of communication. Bell Syst. Tech. J. 1948, 27, 379–423. [CrossRef] Magurran, A.E. Ecological Diversity and Its Measurement; Princeton University Press: Princeton, NJ, USA, 1988; 192p. Brooks, M.E.; Kristensen, K.; van Benthem, K.J.; Magnusson, A.; Berg, C.W.; Nielsen, A.; Skaug, H.J.; Maechler, M.; Bolker, B.M. GglmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling. R J. 2017, 9, 378–400. Available online: https://journal.r-project.org/archive/2017/RJ-2017-066/index.html (accessed on 23 February 2022). [CrossRef] R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2021. Lüdecke, D. ggeffects: Tidy Data Frames of Marginal Effects from Regression Models. J. Open Source Softw. 2018, 3, 772. [CrossRef] Wickham, H. ggplot2: Elegant Graphics for Data Analysis; Springer: New York, NY, USA, 2016; ISBN 978-3-319-24277-4. Available online: https://ggplot2.tidyverse.org (accessed on 23 February 2022). Oksanen, J.; Blanchet, F.G.; Kindt, R.; Legendre, P.; Minchin, P.R.; O’hara, R.B.; Simpson, G.L.; Solymos, P.; Stevens, M.H.H.; Wagner, H. Community Ecology Package. R Package Version 2. 2013. Available online: https://cran.r-project.org/web/packages/ vegan/index.html (accessed on 24 February 2022). Hawksworth, D.L. The fungal dimension of biodiversity: Magnitude, significance, and conservation. Mycol. Res. 1991, 95, 641–655. [CrossRef] Finlay, R.D. Ecological aspects of mycorrhizal symbiosis: With special emphasis on the functional diversity of interactions involving the extraradical mycelium. J. Exp. Bot. 2008, 59, 1115–1126. [CrossRef] [PubMed] Hartmann, M.; Frey, B.; Mayer, J.; Mäder, P.; Widmer, F. Distinct soil microbial diversity under long-term organic and conventional farming. ISME J. 2015, 9, 1177–1194. [CrossRef] [PubMed] Ponge, J.F. The soil as an ecosystem. Biol. Fertil. Soils 2015, 51, 645–648. [CrossRef] Van der Heijden, M.G.; Wagg, C. Soil microbial diversity and agro-ecosystem functioning. Plant Soil 2013, 363, 1–5. [CrossRef] Kivlin, S.N.; Smith, A.P.; Sulman, B.N.; Buscardo, E. Forest Rhizosphere Interactions: Cascading Consequences for EcosystemLevel Carbon and Nutrient Cycling. Front. For. Glob. Chang. 2021, 4, 33. [CrossRef] Kembel, S.W.; O’Connor, T.K.; Arnold, H.K.; Hubbell, S.P.; Wright, S.J.; Green, J.L. Relationships between phyllosphere bacterial communities and plant functional traits in a neotropical forest. Proc. Natl. Acad. Sci. USA 2014, 111, 13715–13720. [CrossRef] Bowles, T.M.; Acosta-Martínez, V.; Calderón, F.; Jackson, L.E. Soil enzyme activities, microbial communities, and carbon and nitrogen availability in organic agroecosystems across an intensively-managed agricultural landscape. Soil Biol. Biochem. 2014, 68, 252–262. [CrossRef] Lagomarsino, A.; Grego, S.; Kandeler, E. Soil organic carbon distribution drives microbial activity and functional diversity in particle and aggregate-size fractions. Pedobiologia 2012, 55, 101–110. [CrossRef] Borowik, A.; Wyszkowska, J. Soil moisture as a factor affecting the microbiological and biochemical activity of soil. Plant Soil Environ. 2016, 62, 250–255. [CrossRef] Bååth, E.; Anderson, T.H. Comparison of soil fungal/bacterial ratios in a pH gradient using physiological and PLFA-based techniques. Soil Biol. Bioch. 2003, 35, 955–963. [CrossRef] Rousk, J.; Bååth, E.; Brookes, P.; Lauber, C.; Lozupone, C.; Caporaso, G.; Knight, R.; Fierer, N. Soil bacterial and fungal communities across a pH gradient in an arable soil. ISME J. 2010, 4, 1340–1351. [CrossRef] [PubMed] McCormack, M.L.; Guo, D. Impacts of environmental factors on fine root lifespan. Front. Plant Sci. 2014, 5, 205. [CrossRef] [PubMed] Armstrong, D.L.; Griffin, K.P.; Danner, M. Better Crops with Plant Food; IPNI: Norcross, GA, USA, 1998; Volume LXXXII. Houlden, A.; Timms-Wilson, T.M.; Day, M.J.; Bailey, M.J. Influence of plant developmental stage on microbial community structure and activity in the rhizosphere of three field crops. FEMS Microbiol. Ecol. 2008, 65, 193–201. [CrossRef] [PubMed] Mougel, C.; Offre, P.; Ranjard, L.; Corberand, T.; Gamalero, E.; Robin, C.; Lemanceau, P. Dynamic of the genetic structure of bacterial and fungal communities at different developmental stages of Medicago truncatula Gaertn. cv. Jemalong line J5. New Phyt. 2006, 170, 165–175. [CrossRef] [PubMed] Marschner, P.; Crowley, D.; Rengel, Z. Rhizosphere interactions between microorganisms and plants govern iron and phosphorus acquisition along the root axis—Model and research methods. Soil Biol. Bioch. 2011, 43, 883–894. [CrossRef] Castano, C.; Hernandez-Rodriguez, M.; Geml, J.; Eberhart, J.; Olaizola, J.; Oria-de-Rueda, J.A.; Martin-Pinto, P. Resistance of the soil fungal communities to medium-intensity fire prevention treatments in a Mediterranean scrubland. For. Ecol. Manag. 2020, 472, 118–217. [CrossRef] Forests 2022, 13, 1103 75. 76. 77. 78. 79. 80. 81. 82. 83. 84. 85. 86. 87. 88. 89. 90. 91. 92. 93. 94. 95. 96. 97. 98. 99. 100. 101. 102. 103. 23 of 24 Brabcová, V.; Nováková, M.; Davidová, A.; Baldrian, P. Dead fungal mycelium in forest soil represents a decomposition hotspot and a habitat for a specific microbial community. New Phytol. 2016, 210, 1369–1381. [CrossRef] Nilsson, L.O.; Wallander, H. Production of external mycelium by ectomycorrhizal fungi in a Norway spruce forest was reduced in response to nitrogen fertilization. New Phytol. 2003, 158, 409–416. [CrossRef] Cigan, P.W.; Karst, J.; Cahill, J.F.; Sywenky, A.N.; Pec, G.J.; Erbilgin, N. Influence of bark beetle outbreaks on nutrient cycling in native pine stands in western Canada. Plant Soil. 2015, 390, 29–47. [CrossRef] Przybył, K.; Karolewski, P.; Oleksyn, J.; Łab˛edzki, A.; Reich, P.B. Fungal diversity of Norway spruce litter: Effects of site conditions and premature leaf fall caused by bark beetle outbreak. Microb Ecol. 2008, 56, 332–340. [CrossRef] Hawkins, B.A.; Field, R.; Cornell, H.V.; Currie, D.J.; Guégan, J.F.; Kaufman, D.M.; Kerr, J.T.; Mittelbach, G.G.; Oberdorff, T.; O’Brien, E.M.; et al. Energy, water, and broad-scale geographic patterns of species richness. Ecology 2003, 84, 3105–3117. [CrossRef] Ahlholm, J.; Helander, M.; Elamo, P.; Saloniemi, I.; Neuvonen, S.; Hanhimäki, S.; Saikkonen, K. Micro-fungi and invertebrate herbivores on birch trees: Fungal mediated plant–herbivore interactions or responses to host quality? Ecology 2002, 5, 648–655. [CrossRef] Chareprasert, S.; Piapukiew, J.; Thienhirun, S.; Whalley, A.J.; Sihanonth, P. Endophytic fungi of teak leaves Tectona grandis L. and rain tree leaves Samanea saman Merr. World J. Microbiol. Biotechnol. 2006, 22, 481–486. [CrossRef] López-Bucio, J.; Pelagio-Flores, R.; Herrera-Estrella, A. Trichoderma as biostimulant: Exploiting the multilevel properties of a plant beneficial fungus. Sci. Hortic. 2015, 196, 109–123. [CrossRef] Rouphael, Y.; Franken, P.; Schneider, C.; Schwarz, D.; Giovannetti, M.; Agnolucci, M.; De Pascale, S.; Bonini, P.; Colla, G. Arbuscular mycorrhizal fungi act as biostimulants in horticultural crops. Sci. Hortic. 2015, 196, 91–108. [CrossRef] Schjønning, P.; Thomsen, I.K.; Petersen, S.O.; Kristensen, K.; Christensen, B.T. Relating soil microbial activity to water content and tillage-induced differences in soil structure. Geoderma 2011, 163, 256–264. [CrossRef] Singh, B.K.; Nunan, N.; Ridgway, K.P.; McNicol, J.; Young, J.P.W.; Daniell, T.J.; Prosser, J.I.; Millard, P. Relationship between assemblages of mycorrhizal fungi and bacteria on grass roots. Envir. Microb. 2008, 10, 534–541. [CrossRef] Guo, X.; Gong, J. Differential effects of abiotic factors and host plant traits on diversity and community composition of rootcolonizing arbuscular mycorrhizal fungi in a salt-stressed ecosystem. Mycorrhiza 2014, 24, 79–94. [CrossRef] Sieber, T.N. Endophytic fungi in forest trees: Are they mutualists? Fungal Biol. Rev. 2007, 21, 75–89. [CrossRef] Saikkonen, K. Forest structure and fungal endophytes. Fungal Biol. Rev. 2007, 21, 67–74. [CrossRef] 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. Nature 2006, 443, 818–822. [CrossRef] [PubMed] Bar-On, Y.M.; Phillips, R.; & Milo, R. The biomass distribution on Earth. Proc. Natl. Acad. Sci. USA 2018, 115, 6506–6511. [CrossRef] [PubMed] Read, D.J.; Perez-Moreno, J. Mycorrhizas and nutrient cycling in ecosystems—A journey towards relevance? New Phyt. 2003, 157, 475–492. [CrossRef] [PubMed] Netherway, T.; Bengtsson, J.; Krab, E.J.; Bahram, M. Biotic interactions with mycorrhizal systems as extended nutrient acquisition strategies shaping forest soil communities and functions. Basic Appl. Ecol. 2021, 50, 25–42. [CrossRef] Arias, M.M.D.; Batzer, J.C.; Harrington, T.C.; Wong, A.W.; Bost, S.C.; Cooley, D.R.; Ellis, M.A.; Hartman, J.R.; Rosenberger, D.A.; Sundin, G.W.; et al. Diversity and biogeography of sooty blotch and flyspeck fungi on apple in the eastern and midwestern United States. Phytopathology 2010, 100, 345–355. [CrossRef] Zhuang, J.; Zhu, M.; Zhang, R.; Yin, H.; Lei, Y.; Sun, G.; Gleason, M.L. Phialophora sessilis, a species causing flyspeck signs on bamboo in China. Mycotaxon 2010, 113, 405–413. [CrossRef] Nguyen, D.; Boberg, J.; Ihrmark, K.; Stenström, E.; Stenlid, J. Do foliar fungal communities of Norway spruce shift along a tree species diversity gradient in mature European forests? Fungal Ecol. 2016, 23, 97–108. [CrossRef] Livsey, S.; Barklund, P. Lophodermium piceae and Rhizosphaera kalkhoffii in fallen needles of Norway spruce (Picea abies). Eur. J. For. Pathol. 1992, 22, 204–216. [CrossRef] Scattolin, L.; Montecchio, L. Lophodermium piceae and Rhizosphaera kalkhoffii in Norway spruce: Correlations with host age and climatic features. Phytopathol. Mediterr. 2009, 48, 226–239. Hormazabal, E.; Astudillo, L.; Schmeda-Hirschmann, G.; Rodríguez, J.; Theoduloz, C. Metabolites from Microsphaeropsis olivacea, an endophytic fungus of Pilgerodendron uviferum. Z. Naturforsch. C 2005, 60, 11–21. [CrossRef] Lazarević, J.; Menkis, A. Fungal diversity in the phyllosphere of Pinus heldreichii H. Christ-an endemic and high-altitude pine of the Mediterranean Region. Diversity 2020, 12, 172. [CrossRef] Razaghi, P.; Zafari, D. First report of Microsphaeropsis olivacea causing brown spine rot on Alhagi maurorum in Iran. Plant Pathol. 2016, 98, 685. [CrossRef] Crous, P.W.; Quaedvlieg, W.; Hansen, K.; Hawksworth, D.L.; Groenewald, J.Z. Phacidium and Ceuthospora (Phacidiaceae) are congeneric: Taxonomic and nomenclatural implications. Ima Fungus 2014, 5, 173–193. [CrossRef] [PubMed] Di Cosmo, F.; Nag Raj, T.R.; Kendrick, W.B. A Revision of the Phacidiaceae and Related Anamorphs [New Taxa]; Mycotaxon: New York, NY, USA, 1984; p. 234. Ribeiro, T.H.C.; Fernandes-Brum, C.N.; de Souza, C.R.; Dias, F.A.N.; Almeida-Junior, O.D.; Regina, M.D.A.; Chalfun-Junior, A. Transcriptome analyses suggest that changes in fungal endophyte lifestyle could be involved in grapevine bud necrosis. Sci. Rep. 2020, 10, 9514. [CrossRef] Forests 2022, 13, 1103 24 of 24 104. Elvira-Recuenco, M.; Cacciola, S.O.; Sanz-Ros, A.V.; Garbelotto, M.; Aguayo, J.; Solla, A.; Díez, J.J. Potential interactions between invasive Fusarium circinatum and other pine pathogens in Europe. Forests 2020, 11, 7. [CrossRef] 105. Orr, R.; Nelson, P.N. Impacts of soil abiotic attributes on Fusarium wilt, focusing on bananas. Appl. Soil Ecol. 2018, 132, 20–33. [CrossRef] 106. Menkis, A.; Vasiliauskas, R.; Taylor, A.F.S.; Stenström, E.; Stenlid, J.; Finlay, R. Fungi in decayed roots of conifer seedlings from forest nurseries, afforested clearcuts and abandoned farmland. Plant Pathol. 2006, 55, 117–129. [CrossRef] 107. Striganavičiūtė, G.; Žiauka, J.; Sirgedaitė-Šėžienė, V.; Vaitiekūnaitė, D. Priming of Resistance-Related Phenolics: A Study of Plant-Associated Bacteria and Hymenoscyphus fraxineus. Microorganisms 2021, 9, 2504. [CrossRef] 108. Conrath, U.; Beckers, G.J.; Flors, V.; García-Agustín, P.; Jakab, G.; Mauch, F.; Mauch-Mani, B. Priming: Getting ready for battle. Mol. Plant-Microbe Interact. 2006, 19, 1062–1071. [CrossRef] 109. Jung, S.C.; Martinez-Medina, A.; Lopez-Raez, J.A.; Pozo, M.J. Mycorrhiza-induced resistance and priming of plant defenses. J. Chem. Ecol. 2012, 38, 651–664. [CrossRef] 110. Cameron, D.D.; Neal, A.L.; van Wees, S.C.; Ton, J. Mycorrhiza-induced resistance: More than the sum of its parts? Trends Plant Sci. 2013, 18, 539–545. [CrossRef] [PubMed]

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