inhabiting fungal communities, but adaptat

Environmental Microbiology (2018) 00(00), 00–00

doi:10.1111/1462-2920.14081

Increasing N deposition impacts neither diversity nor functions of deadwood-inhabiting fungal communities, but adaptation and functional redundancy ensure ecosystem function

Witoon Purahong ,1*† Tesfaye Wubet,1,2† € rn Hoppe,1,6† Tiemo Kahl,3,4† Tobias Arnstadt,5† Bjo 1,7 Guillaume Lentendu, Kristin Baber,8 Tyler Rose,3 € rgen Bauhus,3 Harald Kellner,5 Martin Hofrichter,5 Ju 1 1,2 € ger and François Buscot Dirk Kru 1 Department of Soil Ecology, UFZ-Helmholtz Centre for Environmental Research, Theodor-Lieser-Str. 4, Halle (Saale), D-06120, Germany. 2 German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Deutscher Platz 5e, Leipzig, D-04103, Germany. 3 University of Freiburg, Faculty of Environment and Natural Resources, Chair of Silviculture, Tennenbacherstr. 4, Freiburg im Breisgau, D-79085, Germany. 4 Biosphere Reserve Vessertal-Thuringian Forest, Brunnenstr. 1, Schmiedefeld am Rennsteig, D-98711, Germany. 5 €t Dresden – International Institute Technische Universita (IHI) Zittau, Department of Bio- and Environmental Sciences, Markt 23, Zittau, D-02763, Germany. 6 Julius Ku€ hn-Institute – Federal Research Centre for Cultivated Plants, Institute for National and International Plant Health, Messeweg 11/12, Braunschweig, D38104, Germany. 7 Department of Ecology, University of Kaiserslautern, Erwin€ dinger-Straße, Kaiserslautern, 67663, Germany. Schro 8 Department of Systematic Botany and Functional Biodiversity, University of Leipzig, Institute of Biology Johannisallee 21-23, Leipzig, D-04103, Germany. Summary Nitrogen deposition can strongly affect biodiversity, but its specific effects on terrestrial microbial communities and their roles for ecosystem functions and processes are still unclear. Here, we investigated the Received 3 January, 2017; revised 13 February, 2018; accepted 20 February, 2018. *For correspondence: E-mail witoon.purahong@ ufz.de; Tel. 149 345 558 5207; Fax 149 345 5585 449. †These authors contributed equally to this work.

impacts of N deposition on wood-inhabiting fungi (WIF) and their related ecological functions and processes in a highly N-limited deadwood habitat. Based on high-throughput sequencing, enzymatic activity assay and measurements of wood decomposition rates, we show that N addition has no significant effect on the overall WIF community composition or on related ecosystem functions and processes in this habitat. Nevertheless, we detected several switches in presence/absence (gain/loss) of wood-inhabiting fungal OTUs due to the effect of N addition. The responses of WIF differed from previous studies carried out with fungi living in soil and leaf-litter, which represent less N-limited fungal habitats. Our results suggest that adaptation at different levels of organization and functional redundancy may explain this buffered response and the resistant microbialmediated ecosystem function and processes against N deposition in highly N-limited habitats.

Introduction Nitrogen deposition is one of the most important drivers for changes in biodiversity (Isbell et al., 2013). Intensive agriculture as well as domestic and industrial combustion of fossil fuels have significantly increased mean N deposition rates, which has been found to have detrimental effects on the diversity of bacteria, fungi, plants and invertebrates (Lilleskov et al., 2001; Stevens et al., 2006; Edwards et al., 2011; Van Diepen et al., 2011) and subsequently on ecosystem services (Millennium Ecosystem Assessment, 2005). In terrestrial ecosystems, fungi are important decomposers living above- and below-ground as well as at the plant-soil interface (Chapman and Newman, 2010; Goldmann et al., 2015; Purahong et al., 2016). Modifications of their diversity and/or community composition have been found to influence ecosystem functions and services such as nutrient cycling and decomposition (Hoppe et al., 2016). Ectomycorrhizal fungal (ECM) diversity also declines along gradients of N deposition, although the

C 2018 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd. V

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

2 W. Purahong et al. specific responses of the individual mycobiont species range from nitrophilic through neutral to nitrophobic (Lilleskov et al., 2001). Deadwood is considered to be an important nutrient pool and a key structural component of forest ecosystems (Rajala et al., 2012). Deadwood contributes approximately 8% (73 petagrams) of C stocks of global forest ecosystems (Pan et al., 2011). It comprises both readily decomposable substrates and complex biopolymers such as cellulose, hemicelluloses and lignin as well as chitin from dead arthropod and fungal residues, which are harder to degrade (Hoppe et al., 2016). So far, only fungi are known to have the potential of integral deadwood mineralization. Both angiosperm and conifer deadwoods have very high C:N ratios (377 in Fagus sylvatica, 630 in Picea abies), thus microbial extraction or utilization of N from deadwood ought to be very difficult (Hoppe et al., 2016). Although the C:N ratio decreases over time due to the relative accumulation of N (Rinne et al., 2016), at the late decomposition stage it still remains very high (i.e., 194 in F. sylvatica and 423 in P. abies) compared with other substrates such as soils (ranging from 9 in Greyzems to 26 in Histosols) or leaf-litter [ranging from 54 6 38 (mean 6 SD) in tropical regions to 79 6 30 in the Mediterranean] (Batjes, 1996; Aerts, 1997; Hoppe et al., 2016). In addition, considering that C:N ratios of fungal mycelia are low (i.e., 9–20) (Wal et al., 2016) and that lander et al., 2003; Brabcova production of wood degradation enzyme requires high amount of N, this would mean high demand of N for woodinhabiting fungi (WIF) is expected (Hoppe et al., 2016). Thus, this N limitation may have direct effects on WIF community and functionality (i.e., enzyme production) and should make the fungal communities (WIF) colonizing deadwood rather sensitive to N deposition. To the best of our knowledge, this effect has rarely been studied, but in view of the results mentioned above on fungal communities in substrates with less N limitation, we can hypothesize that under a high N deposition scenario, the WIF diversity reduces through a shift in competition in favour of those species that are more nitrophilic. This in turn should also have negative effects on ecosystem processes such as enzyme activities and decomposition rate in deadwood. Further support for this hypothesis is evidenced by long term N deposition having been shown to cause a shift in soil fungal community composition and a reduction of the expression of genes coding ligninolytic enzymes in a Northern hardwood forest (Edwards et al., 2011). The oxidative enzymes important for lignin modification and decomposition are also reduced under N deposition in leaf-litter with high lignin content (Frey et al., 2004; Sinsabaugh et al., 2005; Ma et al., 2014). High N concentrations may have adverse effects through facilitating complexation of phenolic compounds (Berg, 2000).

In the present study we tested the effects of N deposition (i) on WIF diversity and community composition, (ii) on those potential enzyme activities important for C and N acquisitions and wood decomposition and (iii) on wood decomposition rates across 12 tree species in Central European forests (Supporting Information Fig. S1). WIF were selected because of their importance for decomposition processes and nutrient cycling in forest ecosystems. Furthermore, we used deadwood in order to understand the responses of fungi to N deposition in a highly N-limited habitat with C:N ratio ranging from 300 to more than 900 (Supporting Information Fig. S2). The results on fungal diversity and community composition obtained from deadwood may be completely different from results that have been obtained for soils and leaf-litter where N is less limited (Treseder, 2008; Edwards et al., 2011; Meunier et al., 2016). Different tree species also vary in their concentrations of nitrogen and other nutrients (Bantle et al., 2014), so they provide a gradient which can enable us to better understand the effect of N deposition on biodiversity, ecosystem function (potential enzyme activities) and ecosystem processes (wood decomposition) across a broad spectrum of habitats. Results Fungal diversity and functional assignments A total of 1 312 176 quality filtered sequences of fungal internal transcribed spacer (ITS) were obtained after quality trimming and removal of non-target and chimeric sequences. The sequence read counts were normalized to the smallest read number per sample (2001 reads). These were then clustered into 3821 fungal OTUs, from which 2957 were of low abundance (singletons to quadrupletons). Removal of these rare OTUs did not cause any effect on community composition (see section on ‘Bioinformatics analysis’), so only the 864 abundant fungal OTUs were retained for further statistical analysis. The samplebased rarefaction curves indicated saturation of fungal diversity at the analyzed sequencing depth for most samples, and thus we used the observed Shannon diversity directly for further analyses (Supporting Information Fig.S3). The OTU taxonomic distribution was characterized by the high contribution of Basidiomycota (relative abundance 5 61.2%; presence/absence 5 34.3%) and Ascomycota (relative abundance 5 38.6%; presence/ absence 5 62%) phyla, while the Zygomycota, Cryptomycota (Rozellida), Chytridiomycota and Glomeromycota together contributed little (relative abundance 5 0.2%; presence/absence 5 3.7%) to the overall WIF community (Supporting Information Figs. S4 and S5). This is also consistent when considering the taxonomic distributions of 722 and 657 abundant fungal OTUs for 2011 and 2013 sampling times (Supporting Information

C 2018 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd., V

Environmental Microbiology, 00, 00–00

N deposition in highly N-limited habitat 3 Table 1. Number of wood-inhabiting fungal OTUs from 2011 and 2013 sampling times showing the most frequently detected OTUs of different ecological functional groups.

Functional group

Total OTUs (%)

OTU 2011 (%)

OTU 2013 (%)

Most frequently detected taxa 2011 (%)

Most frequently detected taxa 2013 (%)

Arbuscular mycorrhiza

2 (0.2)

2 (0.3)

2 (0.3)

Animal parasite

4 (0.5)

4 (0.6)

2 (0.3)

Acaulosporaceae Otu_0643 (0.002), Glomeraceae Otu_0825 (0.001) Trichosporon Otu_0317 (0.009)

Ectomycorrhiza

17 (2)

14 (2)

12 (2)

Lichenicolous

1 (0.1) 4 (0.5) 13 (2) 60 (7)

1 (0.1) 4 (0.6) 12 (2) 50 (7)

0 (0) 3 (0.5) 11 (2) 46 (7)

Acaulosporaceae Otu_0643 (0.003), Glomeraceae Otu_0825 (0.002) Beauveria Otu_029 (0.025), Trichosporon Otu_0317 (0.011), Beauveria Otu_0450 (0.01) Sebacina Otu_0105 (0.203), Thelephora Otu_0381 (0.015), Inocybe Otu_0350 (0.015) Skyttea Otu_0477 (0.009)

Sarea Otu_0392 (0.008)

Saprotroph

555 (64)

460 (64)

417 (63)

Sarea Otu_0447 (0.005), Sarea Otu_0392 (0.004) Hypocrea Otu_0082 (0.299), Cuniculitrema Otu_0044 (0.174) Eutypa Otu_0013 (1.859), Cryptosphaeria Otu_0050 (0.855), Eutypa Otu_0028 (0.590) Bjerkandera Otu_0001 (8.270), Stereum Otu_0002 (7.940), Hypholoma Otu_0004 (5.026), Stereum Otu_0005 (5.010), Trametes Otu_0003 (4.893), Armillaria Otu_0010 (3.614), Heterobasidion Otu_0009 (3.472)

Unknown

208 (24) 864 (100)

175 (24) 722 (100)

164 (25) 657 (100)

Lichenized Mycoparasite Plant pathogen

Summary

Dermateaceae Otu_0016 (2.956) Bjerkandera Otu_0001 (8.270), Stereum Otu_0002 (7.940), Hypholoma Otu_0004 (5.026), Stereum Otu_0005 (5.010), Trametes Otu_0003 (4.893), Armillaria Otu_0010 (3.614), Heterobasidion Otu_0009 (3.472)

Figs. S6–S9). Detailed taxonomic distributions are available as Supporting Information (Supporting Information Figs. S4–S9). We identified eight functional groups within the WIF communities of the 12 tree species: saprotrophs (555 OTUs), plant pathogens (60 OTUs), ectomycorrhizal fungi (ECM; 17 OTUs), mycoparasites (13 OTUs), animal parasites (4 OTUs), lichenized fungi (4 OTUs), arbuscular mycorrhizal fungi (2 OTUs), lichenicolous fungi (1 OTU) and fungi with unknown functions (208 OTUs). The number of wood-inhabiting fungal OTUs from the samples taken in 2011 and 2013, and the most frequently detected OTUs of different ecological functional groups are shown in Table 1. In all tree species, saprotrophs were frequently detected. Highly detected white rot and general saprotrophic WIF OTUs in the control and N addition treatments were shown in Table 2.

Clavulina Otu_0097 (0.257), Octaviania Otu_0157 (0.118), Melanogaster Otu_0175 (0.089) –

Cuniculitrema Otu_0044 (0.879) Eutypa Otu_0013 (1.697), Eutypa Otu_0028 (1.381) Trametes Otu_0003 (5.151), Hypholoma Otu_0004 (5.008), Hypoxylon Otu_0007 (3.909), Bjerkandera Otu_0001 (3.904), Hypoxylon Otu_0008 (3.884), Cadophora Otu_0006 (3.248), Megacollybia Otu_0012 (3.120), Resinicium Otu_0011 (3.046) Lecythophora Otu_0017 (2.558), Ascomycota Otu_0020 (2.036) Trametes Otu_0003 (5.151), Hypholoma Otu_0004 (5.008), Hypoxylon Otu_0007 (3.909), Bjerkandera Otu_0001 (3.904), Hypoxylon Otu_0008 (3.884), Cadophora Otu_0006 (3.248), Megacollybia Otu_0012 (3.120), Resinicium Otu_0011 (3.046)

The fungal community composition of the initial wood samples was significantly influenced by tree species (P < 0.01, Supporting Information Table S1) but two halves of the wood samples were not significantly different (P > 0.05; Supporting Information Table S1). The result was confirmed by using one-way PERMANOVA to compare the fungal community composition in wood samples used for the control and the N addition treatments in each tree species (P > 0.05; Supporting Information Table S1). The two halves of each log exhibited consistently similar fungal diversity and enzyme activity patterns (P > 0.05; Supporting Information Table S2). The differences of WIF communities among different tree species were persistent until the end of the experiment (P < 0.001, Table 3). WIF communities of the initial wood samples (2011) were significantly different from those at the end of the experiment (2013) (P < 0.001, Supporting Information Table S3).



Quercus spp.

Prunus avium

Populus spp.

Fraxinus excelsior

Fagus sylvatica

Carpinus betulus

Deciduous Betula pendula

Tree species

White rotter: BjerkanderaOtu_0001, TrametesOtu_0003, ArmillariaOtu_0010, SistotremaOtu_0023, HyphodermaOtu_0024, HyphodermaOtu_0091 General saprotroph: CadophoraOtu_0006, LeptodontidiumOtu_0022, PhialocephalaOtu_0039, CadophoraOtu_0072, LophiostomaOtu_0084, CryptosporiopsisOtu_0090, LachnumOtu_0198 White rotter: StereumOtu_0018, HyphodermaOtu_0024 General saprotroph:

White rotter: TrametesOtu_0003, StereumOtu_0002, ArmillariaOtu_0010, HyphodermaOtu_0024, HyphodermaOtu_0128, SistotremaOtu_0023, General saprotroph: PhialocephalaOtu_0039, LeptodontidiumOtu_0022, AscocoryneOtu_0035, MycenaOtu_0040, AnnulohypoxylonOtu_0066, SordarialesOtu_0106, White rotter: BjerkanderaOtu_0001, StereumOtu_0005, ArmillariaOtu_0010, SistotremaOtu_0023, General saprotroph: HypoxylonOtu_0007, LeptodontidiumOtu_0022, PhialocephalaOtu_0039, AnnulohypoxylonOtu_0066 White rotter: BjerkanderaOtu_0001, SistotremaOtu_0023, HyphodermaOtu_0024 General saprotroph: HypoxylonOtu_0007, AnnulohypoxylonOtu_0014, PhialocephalaOtu_0039, AnnulohypoxylonOtu_0053, CaproniaOtu_0094, CatenuliferaOtu_0088, AtractiellalesOtu_0131, CaproniaOtu_0228 White rotter: – General saprotroph: CadophoraOtu_0006, HypoxylonOtu_0007, HypoxylonOtu_0008, AscocoryneOtu_0035, ExidiopsisOtu_0036, LasiosphaerisOtu_0037, LophiostomaOtu_0084, CadophoraOtu_0072, CaproniaOtu_0120, SordarialesOtu_0245, CrepidotusOtu_0325 White rotter: HyphodermaOtu_0024 General saprotroph: CadophoraOtu_0006, LeptodontidiumOtu_0022, AscocoryneOtu_0035, LasiosphaerisOtu_0037, PholiotaOtu_0038, CoprinellusOtu_0057, PodosporaOtu_0071, HypocrealesOtu_0077, SordarialesOtu_0106

Detected in both control and N addition

Highly detected fungal OTUs in control or N addition

Table 2. Highly detected fungal OTUs in control or N addition across 12 tree species.

White rotter: – General saprotroph: MycenaOtu_0040, MycenaOtu_0046,

White rotter: ArmillariaOtu_0010 General saprotroph: SordarialesOtu_0168

White rotter: BjerkanderaOtu_0001 General saprotroph: HypoxylonOtu_0007, ExidiopsisOtu_0036, CaproniaOtu_0094, ExidiopsisOtu_0111 White rotter: PhanerochaeteOtu_0114, CeriporiaOtu_0185 General saprotroph: MycenaOtu_0031

White rotter: HypholomaOtu_0063 General saprotroph: –

White rotter: – General saprotroph: CalycinaOtu_0240

White rotter: – General saprotroph: SebacinalesOtu_0372

White rotter: PhlebiaOtu_0034, MycoaciaOtu_0064, HyphodermaOtu_0128 General saprotroph:- –

White rotter: DentipellisOtu_0052, SkeletocutisOtu_0048, PhlebiaOtu_0122 General saprotroph: RamariaOtu_0030, NemaniaOtu_0147 White rotter: – General saprotroph: HymenoscyphusOtu_0172, AuricularialesOtu_0351

White rotter: – General saprotroph: AnnulohypoxylonOtu_0053, AscocoryneOtu_0173, MortierellaOtu_0470

White rotter: FibulorhizoctoniaOtu_0049, CorticiaceaeOtu_0164 General saprotroph: –

Newly detected in N addition

White rotter: PolyporusOtu_0041, StereumOtu_0187 General saprotroph: ZignoellaOtu_0087

White rotter: HyphodermaOtu_0205, SkeletocutisOtu_0267 General saprotroph: –

Detected only in control

4 W. Purahong et al.




Pseudotsuga menziesii

Pinus sylvestris

Picea abies

Coniferous Larix decidua

Tilia spp.

Tree species

Table 2. cont.

White rotter: StereumOtu_0002, ResiniciumOtu_0011, SistotremaOtu_0023, StereumOtu_0033, HyphodermaOtu_0047, FibulorhizoctoniaOtu_0049, FibulorhizoctoniaOtu_0086 General saprotroph: LeptodontidiumOtu_0022, AtractiellalesOtu_0025, PhialophoraOtu_0021, CollophoraOtu_0029, AscocoryneOtu_0035, InfundichalaraOtu_0045, MelanchlenusOtu_0085, OidiodendronOtu_0100, MeliniomycesOtu_0101 White rotter: HypholomaOtu_0004, SistotremaOtu_0023, SistotremaOtu_0265 General saprotroph: CadophoraOtu_0006, AmylostereumOtu_0015, PhialophoraOtu_0021, AtractiellalesOtu_0025, FomitopsisOtu_0026, AntrodiaOtu_0056, CadophoraOtu_0059, ZignoellaOtu_0087, MeliniomycesOtu_0101, AscocoryneOtu_0173, CyphellopsisOtu_0027, LeuconeurosporaOtu_0366 White rotter: HypholomaOtu_0004, HeterobasidionOtu_0009, SistotremaOtu_0023, HyphodermaOtu_0024, FibulorhizoctoniaOtu_0049, SistotremastrumOtu_0058, General saprotroph: CadophoraOtu_0006, PhialophoraOtu_0021, LeptodontidiumOtu_0022, AscocoryneOtu_0035, InfundichalaraOtu_0045, MelanchlenusOtu_0085, HelotiaceaeOtu_0108, HelotiaceaeOtu_0129, OrbiliaOtu_0171, MucronellaOtu_0215 White rotter: HypholomaOtu_0004, SistotremaOtu_0023, FibulorhizoctoniaOtu_0049 General saprotroph: MegacollybiaOtu_0012, PhialophoraOtu_0021, LeptodontidiumOtu_0022, AscocoryneOtu_0035, PhialocephalaOtu_0039, AntrodiaOtu_0056, InfundichalaraOtu_0045, CryptosporiopsisOtu_0090, ChalaraOtu_0181, MeliniomycesOtu_0101

MegacollybiaOtu_0012, LeptodontidiumOtu_0022, CollophoraOtu_0029, AscocoryneOtu_0035, MoristromaOtu_0060, SaccharomycetalesOtu_0061, BotryosphaeriaOtu_0042, HelotiaceaeOtu_0159, HelotiaceaeOtu_0229 White rotter: PolyporusOtu_0081, HyphodermaOtu_0091, PolyporusOtu_0113 General saprotroph: CadophoraOtu_0006, CyphellopsisOtu_0027, PhialophoraOtu_0021, ExidiopsisOtu_0036, MycenaOtu_0040, LophiostomaOtu_0084, PhialophoraOtu_0118, AtractiellalesOtu_0131, TubariaOtu_0182.

White rotter: SistotremastrumOtu_0058 General saprotroph: –

White rotter: StereumOtu_0002 General saprotroph: –

White rotter: – General saprotroph: AtractiellalesOtu_0025, RamariaOtu_0030

White rotter: ResiniciumOtu_0011 PhlebiellaOtu_0194 General saprotroph: AmylostereumOtu_0015 MycenaOtu_0046

White rotter: PeniophoraOtu_0043 General saprotroph: -

White rotter: ArmillariaOtu_0010, HypochniciumOtu_0070 General saprotroph: MycenaOtu_0054

White rotter: HyphodermaOtu_0024, HyphodermaOtu_0119 General saprotroph: LentinusOtu_0092

Newly detected in N addition

White rotter: HeterobasidionOtu_0009 General saprotroph: AcremoniumOtu_0133

White rotter: – General saprotroph: MycenaOtu_0076

White rotter: IschnodermaOtu_0051 General saprotroph: ZignoellaOtu_0087

Detected only in control CoprinellusOtu_0057, PodosporaOtu_0143, BulleraOtu_0289

Detected in both control and N addition

Highly detected fungal OTUs in control or N addition

N deposition in highly N-limited habitat 5


6 W. Purahong et al. Table 3. Effects of N addition and tree species on fungal community composition and diversity (total and selected fungal community which exclude arbuscular mycorrhiza, animal parasite, lichenicolous, lichenized and mycoparasite), overall enzyme activity pattern and wood decomposition (CO2 emission) rates. Total fungal community

Selected fungal community

Total fungal diversity

Selected fungal diversity

Enzyme activity pattern

Decomposition rate

Factor

F

P

F

P

F

P

F

P

F

P

F

P

N addition Tree species N addition x Tree species

0.93 2.90 0.78

0.665 0.001 1.000

0.91 2.95 0.79

0.736 0.001 1.000

0.16 2.14 0.56

0.695 0.028 0.854

0.12 2.36 0.56

0.726 0.015 0.858

1.01 3.31 0.78

0.358 0.001 0.790

0.74 4.91 0.20

0.391 0.001 0.997

Nitrogen deposition in deadwood 15

We detected a strong enrichment of the N signal in the N addition treatment, indicating that the deposited N was successfully incorporated into all deadwood samples (Fig. 1). The different tree species showed variable d15N values, ranging from 6.21& in Quercus spp. to 99.55& in P. sylvestris logs (Fig. 1), and the values were found to be significantly and negatively correlated with wood density (q 5 20.47, P 5 0.0047; Supporting Information Fig. S10). In the control, d15N values were mostly negative and close to zero ranging from 27.35& in P. abies to 4.28& in Populus spp. (Fig. 1). This suggests that the applied N had been transported and diffused into the deadwood and that the experimental setup was appropriate to test the impact of N addition on fungal diversity and community composition of deadwood. At the end of the experiment, we detected a significant increase of N content in Betula pendula deadwood logs (P 5 0.020) due to N deposition, while for other 11 tree species the differences were not significant (P > 0.05) (Fig. 2).

P 5 0.665) (Table 3). In contrast, tree species significantly affected both WIF diversity (Ftree species 5 2.14, P 5 0.028) and community composition (Ftree species 5 2.90, P < 0.001) but in both cases no significant interaction between N addition and tree species was found (P 5 0.854–1.000). Testing across all 12 tree species, we confirmed that N addition had no effect either on WIF diversity (P 5 0.056–0.978) or on community composition (P 5 0.258–1.000) (Table 4; Fig. 3). Further analysis of the effect of N addition on the WIF community composition of each major functional group (saprotrophs, white rot saprotrophs and plant pathogens) showed no significant effect (P > 0.05, Supporting Information Table S4). We also analyzed the effect of N addition on selected WIF diversity and community composition which we excluded some WIF functional groups that may not active and directly involve in decomposition process (arbuscular mycorrhizal fungi, mycoparasites, animal parasites, lichenized fungi and lichenicolous fungi). The results were highly consistent with those using the completed WIF community (Tables 3 and 4).

Effect of nitrogen deposition on WIF diversity and community composition

Adaptation and functional redundancy of WIF

Nitrogen addition had no significant effect on WIF diversity (Two-way ANOVA; FN addition 5 0.16, P 5 0.695) or community composition (Two-way PERMANOVA; FN addition 5 0.93,

Although the overall WIF community composition was not significantly different between N addition treatment and control, at the OTU level we found a strong shift in the Fig. 1. Mean 6 SE (n 5 3) of d15N (&) in different tree species. C, control (no nitrogen addition, black bars); N, nitrogen addition treatment, red bars. Different letters indicate significant differences (P < 0.05) between control and N addition treatment. The asterisk (*) above letter ‘a’ indicates marginal significant differences (P < 0.1).



N deposition in highly N-limited habitat 7 Fig. 2. Mean 6 SE (n 5 4) of total N in deadwood of different tree species at the end of the experiment. C, control (no nitrogen addition, black bars); N, nitrogen addition treatment, red bars. Different letters indicate significant differences (P < 0.05) between control and N addition treatment.

relative abundances of some frequently detected taxa, some highly detected OTUs were not detected in the N treatment, while new OTUs appeared (Table 2). N uptake by WIF in the N deposition treatment was revealed by a strong enrichment of the d15N signal both in the vegetative mycelium (Armillaria sp.) and fruiting bodies (Bjerkandera adusta, Fomitopsis pinicola and Stereum hirsutum) (Fig. 4). White rot and general saprotrophic WIF were among the most frequently detected functional groups in both N addition treatment and control. Comparisons of these frequently detected WIF OTUs revealed that – regardless of the deadwood types (broadleaf deciduous vs. coniferous) and for all 12 tree species tested – there was

functional redundancy between the WIF communities in the N addition treatment and control. The functional redundancy of WIF community in N addition treatment as compared with control came from both newly detected WIF OTUs in N addition treatment and the N adapted WIF OTUs. For example, in F. sylvatica (broadleaf deciduous), the white rot fungi Dentipellis Otu_0052, Skeletocutis Otu_0048 and Phlebia Otu_0122, which were detected at high frequency in the controls, were not detected in the N addition treatment. Rather, we frequently detected other white rot fungi (Phlebia Otu_0034 and Mycoacia Otu_0064). In P. abies (coniferous), Heterobasidion Otu_0009 was a frequently detected white rot fungus in the control but remained undetected in the N addition

Table 4. Effects of N addition (pairwise comparisons) on fungal community composition and diversity, overall enzyme activity pattern and wood decomposition (CO2 emission) rates across 12 tree species.

Tree species Deciduous Betula pendula Carpinus betulus Fagus sylvatica Fraxinus excelsior Populus spp. Prunus avium Quercus spp. Tilia spp. Coniferous Larix decidua Picea abies Pinus sylvestris Pseudotsuga menziesii

Total fungal community

Selected fungal community

Total fungal diversity

Selected fungal diversity

Enzyme activity pattern

F

P

F

P

t

P

t

P

F

P

t

P

0.76 0.72 1.01 1.14 0.88 0.82 0.78 0.64

0.853 1.000 0.426 0.258 0.752 0.804 0.896 1.000

0.74 0.75 1.06 1.16 0.87 0.83 0.75 0.65

0.894 0.949 0.420 0.267 0.794 0.799 0.950 1.000

23.04 1.09 1.96 1.13 0.65 1.21 0.90 21.08

0.056 0.357 0.146 0.339 0.561 0.314 0.434 0.361

23.05 1.12 2.08 1.17 0.47 1.11 0.90 21.04

0.056 0.344 0.130 0.325 0.669 0.348 0.433 0.376

2.10 0.17 0.70 0.40 0.82 1.31 0.21 1.48

0.316 0.752 1.000 0.780 0.538 0.269 0.784 0.366

20.84 20.58 20.69 0.13 0.24 22.06 21.43 20.14

0.463 0.600 0.540 0.908 0.824 0.132 0.249 0.896

0.59 0.67 0.57 1.00

0.943 0.966 1.000 0.598

0.60 0.67 0.56 1.03

0.933 0.960 1.000 0.491

0.10 20.65 20.03 20.52

0.929 0.562 0.978 0.637

0.03 20.65 20.03 20.55

0.981 0.564 0.979 0.621

0.25 1.79 0.92 0.13

0.943 0.278 0.807 0.946

21.32 0.18 21.02 1.12

0.278 0.871 0.383 0.346

CO2 emission rate



8 W. Purahong et al.

Fig. 3. Non-metric multidimensional scaling ordinations (with convex hulls) for wood-inhabiting fungal communities (A–D) and overall enzyme patterns (E–H), and actual decomposition rates (mean 6 SE; I – L). C, control (no nitrogen addition, black); N, nitrogen addition treatment, red. C 2018 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd., V


N deposition in highly N-limited habitat 9 Fig. 4. d15N in mycelium (Armillaria sp) and fruiting bodies (Bjerkandera adusta, Fomitopsis pinicola and Stereum hirsutum) of some dominant woodinhabiting fungi detected in this experiment. C, control (no nitrogen addition, black bars); N, nitrogen addition treatment, red bars.

treatment, where we frequently detected another white rot fungus Peniophora Otu_0043. Nitrogen adapted white rot and general saprotrophic WIF, which were frequently detected in control and/or N deposition treatment were shown in Table 2. Effect of nitrogen deposition on enzyme activities Enzyme activities were consistent with WIF diversity and community composition. We found that N addition, as well as the interaction between N addition and tree species, had no significant effect on patterns of enzyme activities (Two-ways PERMANOVA, FN addition 5 1.01, P 5 0.358; Ftree species x N addition 5 0.78, P 5 0.790) (Table 3). Tree species significantly affected patterns of enzyme activities (Ftree species 5 3.31, P < 0.001) but N addition treatment had no effect on patterns of enzyme activities (P 5 0.269–1.000) across all the 12 tree species (Table 4; Fig. 3). Activities of specific enzymes were consistent with the overall patterns of enzyme activities (Supporting Information Table S5). Effect of N deposition on CO2 emission rate (actual wood decomposition rate) CO2 emission rates were consistent with other measures of the WIF community and enzyme activities. We found that N addition as well as the interaction between N addition and tree species had no significant effect on CO2 emission rates (Two-way ANOVA, 2013: FN addition 5 0.74, P 5 0.391; Ftree species x N addition 5 0.20, P 5 0.997; Table 3). Tree species significantly affected CO2 emission rates (Ftree species 5 4.91, P < 0.001). Again, we confirmed that N

addition had no effect on CO2 emission rates (P 5 0.132– 0.908) across all 12 tree species studied (Table 4; Fig. 3). Discussion Effects of N addition on WIF community, enzyme activities and wood decomposition rates: unique response in a highly N-limited deadwood habitat Our study indicates that N deposition has no significant effect on the community of WIF and microbial-mediated ecosystem functions (activities of degradative enzymes) and processes (wood decomposition rates as determined by CO2 emission rates) under our experimental conditions (2 years nitrogen deposition at 40 kg N ha21 year21). Nitrogen addition was found to have no significant effect across different major functional groups of WIF including saprotrophs, white rot saprotrophs and plant pathogens. These results contradict our initial hypothesis and also the majority of results obtained from other studies that have investigated the effects of N addition on microbial communities (Lilleskov et al., 2001; Treseder, 2008; Stevens et al., 2010; Van Diepen et al., 2011; Dean et al., 2014). Nevertheless, at OTU level we found that some WIF OTUs in the control and N addition treatment were gain or loss due to N addition. In soil, a meta-analysis investigating the effect of N additions on microbial (bacterial and fungal) biomass using 82 published field studies in five biomes (agriculture, boreal forest, desert, temperate forest and temperate grassland) showed an overall decline of microbial abundances in many ecosystems (Treseder, 2008). Soil fungal community composition, abundances and/or diversity of various functional groups, including saprotrophs (Edwards et al.,



10 W. Purahong et al. 2011), ectomycorrhizas (Lilleskov et al., 2001) and arbuscular mycorrhizas (Van Diepen et al., 2007; 2010; 2011), were also reported to exhibit significant shifts and reductions following N addition. The induced alteration of fungal communities and biomass by N addition has been reported to be associated with the suppression of ligninolytic gene expression and a reduction of phenol oxidase activity (related to a lignin-modification enzyme) in the soil, which directly affects microbial-mediated functions (lignin transformation, decomposition and humification) (Frey et al., 2004; Edwards et al., 2011). In leaf-litter, fungal diversity responses to N addition depend on the biomes in which it occurs (tropical vs. temperate forests) (Kerekes et al., 2013). Although b-1,4-N-acetyl-glucosaminidase and phenol oxidase activities have been found to be suppressed by N addition, for phenol oxidase, such a negative effect has been found to be substrate (high C:N leaf litter) and stand age dependent (Ma et al., 2014). In contrast to these results, we found that N addition had no significant effects on WIF community composition or on microbial-mediated ecosystem functions and processes. The discrepancy between our results and previous studies may be related to microbial adaptation and functional redundancy within the complex WIF community. Furthermore, the situation in soil and leaf-litter (structure and physicochemical properties) is rather different to that in large pieces of deadwood; thus we would expect the N-effect in wood to differ (Batjes, 1996; Aerts, 1997; Stokland et al., 2012; Hoppe et al., 2016). In studies made in soils, the study sites have long been exposed to N deposition where significant and persistent differences in N concentrations were measured (Frey et al., 2004; Van Diepen et al., 2007; 2010; Edwards et al., 2011) while in wood (our study), the experiment has been conducted for 2 years and total N content were only significant increase in Betula pendula. Although some recent molecular studies indicate a clear succession in WIF communities, some saprotroph WIF from later successional stages are already present in the wood in earlier stages of decomposition (Rajala et al., 2012; Hiscox et al., 2015). It is still unclear, if these WIF are then actively involved in decomposing deadwood or whether they become active only later in the decomposition process. Such inactive fungi could be present in the wood of either the control or N addition treatment, which may explain partly the lack of differences in fungal diversity, community composition and function in our study. However, in our study we have also accessed the microbial-mediated ecosystem functions (enzymes) and processes (actual decomposition rates) and matched these results with the fungal community analysis. The good agreement of these results indicates that the lack of differences in fungal diversity, community composition and function between N addition treatment and control are likely attributable to adaptation and functional redundancy of WIF.

Adaptation and functional redundancy of WIF may maintain microbial-mediated ecosystem functions and processes against N deposition in highly N-limited habitats Microbial adaptation is defined as ‘the ability of microbes to endure the selective pressures of their environment’ (Patel and Rosenthal, 2007). Theoretically, microbes can adapt to environmental changes in many ways depending on which organizational level of life we are looking at. Specifically, at the levels of individuals and populations microbes can adapt to selective pressures through physiological changes and genetic evolution respectively (Schimel et al., 2007; Sleight and Lenski, 2007). At the community level, adaptions to environmental changes may occur though shifts in the composition and to a certain extent by regulating activities (e.g. of enzymes) up or down rcenas-Moreno et al., 2009; Edwards et al., 2011). In (Ba our case, the selective pressure was N addition. Background N deposition has been 10–15 kg N ha21 per €n region) for growing season in our study area (Hainich-Du many decades, thus we may already have lost a great number of WIF species (Schwarz et al., 2014). Through this selection process, the remaining WIF may already have become adapted to high N deposition by having changed their physiology and genetic evolution (Schimel et al., 2007; Allison et al., 2013). This could explain why increased N-deposition, as we applied it in this experiment, might have had no significant effect. Our data support this assumption, as evidenced by our detection of a strong enrichment of d15N in both mycelium and fruiting bodies of dominant WIF. This implies that the remaining WIF (especially the dominant ones) can efficiently assimilate at least a part of the available N from an N addition treatment and use it for their growth and reproduction. A previous study on the effect of N deposition on wood decomposition by two cord-forming fungi (Hypholoma fasciculare and Phanerochaete velutina) showed that adding a small amount of N to wood (2.8 kg N ha21 year21) in a low N deposition area (Wytham, UK; 2.9 kg N ha21 year21) can increase the wood decomposition rate (Bebber et al., 2011). This may be related partly to microbial adaptation, as the two cord-forming fungi used for this experiment had not experienced or adapted to N addition (either by physiology or genetic evolution). Thus adding N in the N-limited substrate can trigger or stimulate these fungi to use more N for their metabolism and enzyme production, which can increase the wood decomposition rate (priming effect) (Bebber et al., 2011). Such priming effects are known from compost in response to sugars and/or N (Kuzyakov, 2010). The size and characteristic of wood samples (beech wood blocks, 2 cm cubes) used in this experiment, as well as the initial inoculation with two cordforming fungi, may also partly account for differences



N deposition in highly N-limited habitat 11 between the results of that experiment and our study. Indeed, we found that Hypholoma spp. have high relative abundances in the N addition treatment in Quercus spp., P. abies and Pseudotsuga menziesii, thus suggesting that Hypholoma spp. might have benefited from N addition, but the positive response to N addition varied among different tree species and WIF taxa. In the genus Hypholoma, there are both wood and litter/moss dwelling species, thus these fungi may represent hybrid forms of wood-rotters and litterskova et al., 2007; de Boer et al., decomposers (Vala 2010). Since the latter are less affected by N than are the corticoid wood-rotters such as Phanerochaete, it is not surprising that Hypholoma dominates the N-treated deadwood (in particular that of the broad-leafed species). A negative priming effect from N addition was also reported in a woody substrate, when the microbial community switches from complex substances (i.e., lignocellulose) to more readily available substrates (Qiao et al., 2016). Nevertheless, these three experiments have been designed with different objectives, set in different contexts and have used various approaches (e.g., field vs. laboratory studies) (Bebber et al., 2011; Qiao et al., 2016). In the present study, we aimed to understand the effects of N deposition on WIF communities and their related ecosystem functions and processes using unmodified or only slightly modified deadwood (large size, without bark removal at the beginning of the experiment and with the natural initial fungal community). Thus adaptation of WIF by shifting the community composition and or relative abundances of some WIF OTUs in responses to N deposition was expected. We did find a strong shift in the relative abundances (from presence to absence and vice versa) of some frequently detected WIF OTUs in control and N addition treatments in the respective tree species. Shifts in the relative abundances of WIF OTUs between treatment pairs through gain and loss of abundance are a common phenomenon as the consequences of anthropogenic disturbances, which often result in the homogenization of the community composition (Wardle et al., 2011; Purahong et al., 2014a). Although we found extreme shifts of the relative abundances of some WIF OTUs (disappearing from control or newly detected with high relative abundances in N addition treatment), especially white rot fungi, we did not observe any effect of N addition on specific (10 enzymes) and overall patterns of enzyme activities, or on the wood decomposition rates. These results are consistent across all 12 tree species tested in this study. White rot fungi secrete a range of hydrolytic and oxidative enzymes and are thus considered to be very important for wood decomposition (Kellner et al., 2014; Arnstadt et al., 2016; Hoppe et al., 2016; Noll et al., 2016). The inconsistent effect of N addition in the presence/absence of white rot fungi on the one hand, and no effect on the enzyme pattern on the

other hand, could be partly explained by the potential functional redundancies within WIF communities, in which different white rot fungi and other general saprotrophs provided similar functions in the control and N addition treatments. Moreover, most white rot fungi have sets of ligninolytic enzymes, that is, different isoenzymes, some of which may be secreted at high N levels but others under N limitation (Sarkar et al., 1997; Knop et al., 2014). A relationship between resource availability (i.e., N addition) and fungal diversity has been proposed, in theory, to follow the productivity–diversity hypothesis as indicated by a unimodal function: the availability of resources restricts species diversity (Kerekes et al., 2013). Specifically in our experiment, fungal diversity should increase with N availability up to a point (where more fungal species meet their minimum N requirements) and then decrease as N continues to increase. However, our work provides evidence that, due to microbial adaptation and the presence/absence of key fungal species, the observed relationship may not follow the productivity–diversity hypothesis or prolong the saturation point by stabilizing or maintaining fungal diversity. The changes of some key WIF OTUs are not sufficient to significantly change the WIF community composition at P < 0.05. Effect of tree species on WIF community, enzyme activities and decomposition rate In this experiment, the original tree species significantly affected fungal diversity, community composition, enzyme activities and wood decomposition rates. This is expected and consistent with previous studies (Kahl et al., 2015; Arnstadt et al., 2016; Baldrian et al., 2016; Purahong et al., 2018; Noll et al., 2016). Besides the general saprotrophs and white rot saprotrophs, which were frequently detected in most tree species, other functional groups such as plant parasites (broadleaf deciduous: Eutypa Otu_0028 and Pestalotiopsis Otu_0132; coniferous: Sporothrix Otu_0155), mycoparasites (broadleaf deciduous: Cuniculitrema Otu_0044) and ectomycorrhizal fungi (coniferous Clavulina Otu_0097) were also frequently detected in logs of some tree species. Frequently detection of fungal plant parasites in deadwood supports the idea that these fungi may have a saprophytic phase and deadwood may thus serve as an inoculum source of plant pathogenic fungi (Maharachchikumbura et al., 2014). In F. excelsior, we found no white rot WIF among the 12 most detected WIF and highly represented by Hypoxylon spp. (Hypoxylaceae, Xylariales). This can be explained by the priority effect hypothesis and the competition among WIF (Liers et al., 2006; Fukasawa et al., 2009; Dickie et al., 2012; Hiscox et al., 2015; Hoppe et al., 2016). A detailed explanation for this aspect is given in the Supporting Information (Appendix S2).



12 W. Purahong et al. N transfers in deadwood Data from the 15N analysis in our experiment provide some evidence on how N is transferred and incorporated into deadwood. However, although we applied additional 15 N to the wood surfaces, we sampled wood from the inner part of the deadwood (after bark removal) after 6 months. As we detected significantly higher 15N ratios across most tree species, the applied 15N must have transferred across, persisted in and been incorporated into the wood samples. A previous study hypothesized that WIF may translocate N from a N addition treatment and use it for their metabolism resulting in non-significantly different total N in controls compared with N addition treatments (Bebber et al., 2011). Our results support this hypothesis as we detected the strong enrichment of 15N in both mycelia and fruiting bodies of WIF. In addition, we suggest that N can also be transferred and incorporated into the wood by diffusion as we found a significantly negative correlation between wood density and d15N. Conclusions In this study, we found that N deposition in a highly Nlimited habitat has no significant effect on overall microbial community composition and related ecosystem function and processes. However, more similar studies in which N concentrations and biomes are varied will have to be performed to confirm this finding. The results from the present study differ from previous work that investigated the effect of N deposition in soil and leaf-litter under less N-limited systems. Several of the frequently detected WIF OTUs exhibited a differential shift in their relative abundances, or were enriched or lost in the N addition treatment. Our results indicate that substrate adaptation and functional redundancy may drive these contrasting responses and maintain microbial-mediated ecosystem functions and processes against N deposition in highly N-limited habitats. N deposition rates have dramatically increased recently in many regions around the globe; thus, a better understanding of microbial adaptation and functional redundancy may play a crucial role in our development of strategies to mediate the effect of N deposition on microbial-mediated ecosystem functions and processes. Experimental procedures Study site and experimental setup The nitrogen deposition experiment was set up at four forest €n region in Central Germany, sites across the Hainich-Du including the Hainich National Park and its surroundings (about 1300 km2; 518160 N 108470 E). This experiment forms part of the German Biodiversity Exploratories (Fischer et al., €ller et al., 2011). In this area, the forests 2010; Hessenmo mainly grow on Luvisol and Stagnosol over limestone bedrock; soil pH is weakly acidic (5.1 6 1.1; mean 6 SD) and annual

mean temperature and precipitation range from 6.58C to 88C and 500 to 800 mm respectively. Broadleaf deciduous trees (mainly European beech, F. sylvatica) are dominant and cover about 83% of the total forest area, while a smaller percentage (17%) are coniferous forests dominated by Norway spruce (P. €ller et al., 2011). We selected four sites abies) (Hessenmo (100 m 3 100 m) classified as beech dominated forests, which were located between 0.40 and 28.71 km apart. The N deposition experiment was set up in September 2011. The general experimental design was based on a pairwise sampling technique: 2 treatments (control and N addition) 3 12 tree species 3 4 replicates (located at different forest sites). At each site, 12 early-decay deadwood logs from 12 species were used including both broadleaf deciduous and coniferous trees: broadleaf deciduous – birch (Betula pendula Roth, Betulaceae), hornbeam (Carpinus betulus L., Betulaceae), beech (Fagus sylvatica L., Fagaceae), ash (Fraxinus excelsior L., Oleaceae), aspen (Populus spp., Salicaceae), cherry [Prunus avium (L.) L., Rosaceae], oak (Quercus spp., Fagaceae) and lime tree (Tilia spp., Malvaceae); conifers – (larch, Larix decidua Mill., Pinaceae), Norway spruce [Picea abies (L.) H.Karst., Pinaceae], pine (Pinus sylvestris L., Pinaceae) and Douglas fir [Pseudotsuga menziesii (Mirb.) Franco, Pinaceae] trees. These deadwood logs were all freshly cut at € ringen forests) the end of 2008 within the same region (Thu and placed in the forest floor in 2008–2009. Average initial C/ N ratios in the sapwood of deadwood used in this experiment ranged from approximately 242 (L. decidua, C. betulus and Quercus spp.) to 1569 (P. sylvestris) (Bantle et al., 2014). More information about this deadwood decomposition experiment is published elsewhere (Kahl et al., 2015). All deadwood logs, which were in the early stage of decomposition at the beginning of the experiment (2 years decomposed deadwood), [diameter (mean 6 SD): 0.31 m 6 0.059 m] were sawn into 0.40 m lengths and cut longitudinally into two equal halves to be used for the N addition and control respectively. We used 0.40 m deadwood instead of the whole log in order to reduce the heterogeneity of WIF community and enzyme activities within the log, and so give better control of any spatial heterogeneity in the experiment. These wood sample pairs were then placed into separate plastic containers (Supporting Information Fig. S1). In each container, the wood samples were placed on small tile squares to allow air circulation underneath the log segments. Wood samples were excluded from the soil to avoid (i) the addition of N and contamination of 15N to the surrounding soil, and (ii) the reallocation of N from soil into the deadwood log by fungal mycelia (Boberg et al., 2014). To simulate N deposition, 5 ml of 40 g l21 NH4 NO3 was uniformly hand sprayed onto each wood sample each month, which simulates an additional annual N deposition rate of about 40 kg N ha21 year21. The control samples were sprayed with 5 ml distilled water. The assumed N deposition rate is similar to the rates reported for Germany (ca., 16–44 kgN ha21 year21) (Stevens et al., 2010). By simulating a N deposition rate of 40 kg N ha21 year21 [with runoff fluxes of 2–3 g N year21 m22 of projected log area (Bantle et al., 2014) and N utilization by WIF], we did not expect a significant increase of N content in the wood logs at the end of the experiment, but did expect changes in the WIF communities and decomposition rates (Fig. 2). Nevertheless, we detected a significant increase of N content due to N



N deposition in highly N-limited habitat 13 deposition in Betula pendula. Low N deposition rates of 2.8 kg N ha21 year21 have already been shown to affect these properties and processes significantly in Fagus wood samples (Bebber et al., 2011). To analyze N incorporation into deadwood and its transport within deadwood by fungal mycelia, we applied 15N labelled NH4 NO3 (10 atom %) in three of four replicate sites (one site was used as negative control for this labelling treatment) in March 2012. Deadwood, fungal mycelia and fruiting bodies of some specific fungi were sampled in September 2012.

Wood sampling and measurement of the actual wood decomposition rate Wood samples were collected at the beginning of the experiment (September 2011) and after 2 years (October 2013) using a cordless drill (Makita BDF 451) equipped with a wood auger (diameter: 10 mm, length 450 mm), which was dipped into alcohol, flamed and wiped with ethanol between drillings to avoid cross-contamination (Purahong et al., 2014a,b). To eliminate the fungal spores deposited to deadwood (without colonization), we remove a small layer of the outer part of deadwood before drilling. The drill was operated slowly and oriented towards the centre of the log at an angle of approximately 908 in relation to a vertical line perpendicular to the stem axis (two drills per each log); in order to avoid overheating the sample, the operation was paused periodically (Purahong et al., 2014a). Wood samples were frozen, transported on ice (ca. 08C) to the laboratory within 3 h and stored at 2208C. Each wood sample was homogenized and ground into a fine powder with the aid of liquid nitrogen using a swing mill (Retsch, Haan, Germany). Actual wood decomposition rates were measured in May 2013 (1 year and 8 months after establishing the experiment) using a closed chamber system that consists of a custommade chamber for the inclusion of a log segment and a device for measuring CO2 concentrations (non-dispersive infrared CO2 sensor, CARBOCAPGMP343, Vaisala, Helsinki, Finland) inside the chamber as described in detail elsewhere (Kahl et al., 2015). The CO2 emission rate of each deadwood piece was calculated based on the slope of the linear CO2 concentration increase in the chamber. In order to detect any delayed response in wood decomposition rates to N deposition we repeated the CO2 emission rate measurement in October 2014 (3rd year). Results of the two measurements were consistent (Supporting Information Tables S6 and S7). The wood samples collected at the beginning of the experiment were used to determine the initial fungal community composition and enzyme activities in each half log in order to assess any priority effect (i.e., initial colonizers can determine the subsequent community composition by excluding or interacting with later-arriving species) (Cline and Zak, 2015). Many studies have determined the influence of priority effects on the assessment of wood-inhabiting fungal communities and the related consequences for ecological functions such as enzyme activities and decomposition rates (Fukami et al., 2010; Dickie et al., 2012; Hiscox et al., 2015). In the present study, such a priority effect could be ruled out from interpretations of our results as we found that each half of the wood sample pair (from the same wood log) comprised similar

fungal communities (see section on ‘Results’). We sampled for material to analyze the effects of N deposition on fungal community and enzyme activities after 2 years, and for effects on wood decomposition rates after approximately 2–3 years, because a recent study has shown N deposition to affect beech wood decomposition after only 10 months (Bebber et al., 2011).

Total N and

15

N analysis and enzyme activity assays

Wood samples were analyzed for concentrations of N (%), and 15N abundance using an Elemental Analyzer (Carlo Erba CHN 1115, Italy) coupled online to an Isotope Ratio Mass Spectrometer (EA-IRMS, Delta V, Thermo Fisher Scientific, The United States). Variations in the isotopic ratio of 15N/14N are expressed in per mil (&) as described in detail in Blasko et al. (2015). A total of 10 enzyme activities was measured as described in detail elsewhere with (Arnstadt et al., 2016; Noll et al., 2016), with 7 hydrolytic enzymes important for carbon acquisition [b-glucosidase (EC 3.2.1.21), cellobiohydrolase (EC 3.2.1.91), endoglucanase (EC 3.2.1.4), xylanase (EC 3.2.1.8) and xylosidase (EC 3.2.1.37)], nitrogen supply [chitinase (EC 3.2.1.14) and peptidase (EC 3.4.11.1)] and 3 oxidative enzyme activities important for lignin modification and degradation [laccase (EC 1.10.3.2), general peroxidase (EC 1.11.1.7/14/16 representing distinct protein families showing manganese independent activity) and manganese peroxidase (EC 1.11.1.13), MnP].

DNA isolation and fungal community analysis by 454 pyrosequencing DNA was extracted from 100 mg of each homogenized wood sample using the ZR Soil Microbe DNA MiniPrep kit (Zymo Research, Irvine, CA), according to the manufacturer’s instructions. The presence and quantity of genomic DNA was checked using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Dreieich, Germany) and the extracts were then stored at 2208C. Fungal amplicon libraries were obtained for pyrosequencing using custom fusion primers. We used the primer pair ITS1F and ITS4 to amplify the fungal internal transcribed spacer (ITS) rRNA region (White et al., 1990; Gardes and Bruns, 1993). The custom primers were constructed with the barcodes and sequencing primers attached at the ITS4 primers for unidirectional sequencing (Wubet et al., 2012; Lentendu et al., 2014). PCR conditions are shown in the Supporting Information (Appendix S1). Amplification products were visualized with eGels (Life Technologies, Grand Island, New York). Products were then pooled in equimolar amounts and each pool was cleaned with Diffinity RapidTip (Diffinity Genomics, West Henrietta, New York) and size selected using Agencourt AMPure XP (Beckman Coulter, Indianapolis, IN) following Roche 454 protocols (454 Life Sciences, Branford, CT). Size-selected pools were then quantified, and 150 ng of DNA were hybridized to Dynabeads M-270 (Life Technologies, Norway) to create single stranded DNA. Single stranded DNA was diluted and used in emPCR, which were performed and subsequently enriched for amplicon sequencing following the established manufacturer’s protocols (454 Life Sciences).



14 W. Purahong et al. Bioinformatics analysis The raw demultiplexed reads were first quality trimmed using MOTHUR 1.33.3 (Schloss et al., 2009). Reads satisfying the following criteria were considered for further analyses: holding one of the expected barcodes with a maximum of 1 mismatch; the forward primer with a maximum of 4 mismatches; a minimum length of 350 nt; a minimum average quality of 20 Phred score; containing homopolymers with a maximum length of 8 nt; and without ambiguous nucleotides. The quality filtered reads were shortened to their first 350 bases and normalized to the smallest read number per sample. Potential chimaeras were removed using UCHIME 4.2.40 (Edgar et al., 2011) as implemented in MOTHUR. Unique sequences were sorted according to decreasing abundance and were clustered into OTUs using CD-HIT-EST 4.5.4 (Fu et al., 2012) at a threshold of 97% pairwise similarity. Fungal ITS OTU representative sequences were first classified against the dynamic version of ~ ljalg et al., the UNITE fungal ITS sequence database (Ko 2013). The sequences with only fungi identification were further classified against the full version of the UNITE database in order to improve their taxonomic annotation. Rare OTUs (singletons to quadrupletons) could potentially have originated from sequencing errors (Kunin et al., 2010) and were therefore removed from the dataset. We used a Mantel test based on Bray–Curtis (relative abundance data) or Jaccard (presence/ absence data) distance measures with 999 permutations to assess the correlation between the whole matrix and the abundant or the presence/absence OTU matrix excluding the rare OTUs. Since we found no significant effect of the rare taxa removal (RMantel 5 0.985–1.000, P 5 0.001), we used the relative abundance and the presence/absence values of the abundant OTUs (OTUs with > 4 reads) for further statistical analyses. Representative sequences of the fungal OTUs were assigned into functional or ecological groups on the basis of sequence similarity using the default parameters of the GAST algorithm (Huse et al., 2008) against the reference dataset provided by Tedersoo et al. (2014). The raw sequence datasets are available in the European Nucleotide Archive under the study number PRJEB15650 (http://www.ebi.ac.uk/ena/ data/view/PRJEB15650).

Statistical analyzes To assess the coverage of the sequencing depth and fungal diversity (total and selected fungal diversity which excluded arbuscular mycorrhizal fungi, mycoparasites, animal parasites, lichenized fungi and lichenicolous fungi), individual rarefaction analysis and Shannon diversity analyses were performed for each sample using the ‘diversity’ function in PAST (Hammer et al., 2001). All datasets relating to fungal diversity, enzyme activities, CO2 emission rates and N content in deadwood were tested for normality and equality of variances using the Jarque–Bera test. Comparison of N content in deadwood between control and N addition treatment for each tree species was analyzed using paired sample t-tests. The effects of tree species and N addition on fungal diversity and CO2 emission rates were analyzed using two-way ANOVA implemented in PAST. The effects of tree species and N addition on fungal community composition (presence/absence data) and overall

enzyme activity patterns were analyzed using two-way permutational multivariate analysis of variance (two-way PERMANOVA) and non-metric multidimensional scaling (NMDS) based on the Jaccard (fungal community) and Euclidean (enzyme activity patterns) distance measures using PAST. The effects of tree species, N addition and their interactive effect on each individual enzyme activity were analyzed using permutational two-way ANOVA with the function aovp using the package ‘lmPerm’ version 1.1–2 (Wheeler, 2010) in R. We used the same analyses to test the presence of any priority effect by assessing the initial fungal diversity and community composition, as well as patterns of enzyme activities from each half of the wood that was used as control and N addition treatment. The effects of N addition on fungal community composition, overall enzyme activity pattern and CO2 emission rates for logs of each tree species were analyzed using one-way PERMANOVA or paired sample t-tests. To investigate the correlation between wood density and d15N (&), non-parametric correlation (Spearman’s rho test) was performed using PAST. Comparisons of d15N and concentration of N in wood samples between control and N addition treatment were done using permutational t-tests. The analysis in R was performed using R version 3.2.2 (R Development Core Team, 2011).

Acknowledgements The work has been (partly) funded by the DFG Priority Programme 1374 ‘Infrastructure-Biodiversity-Exploratories’ (KR 3587/1-1, KR 3587/3-2, BA 2821/9-2, BA2821/9-3, BU 941/ 17-1, HO 1961/5-1, HO 1961/5-2). We thank the managers of the three Exploratories – Kirsten Reichel-Jung, Swen Renner, Katrin Hartwich, Sonja Gockel, Kerstin Wiesner and Martin Gorke for their work in maintaining the plot and project infrastructure; Christiane Fischer and Simone Pfeiffer for giving support through the central office; Michael Owonibi for managing the central data base; and Markus Fischer, Eduard Lin€ ller, Jens Nieschulze, Daniel senmair, Dominik Hessenmo €ning, Ernst-Detlef Schulze, Wolfgang W. Prati, Ingo Scho Weisser and the late Elisabeth Kalko for their role in setting up the Biodiversity Exploratories project. The founders had no role in the study design, data collection and analysis, decision to publish or the preparation of the manuscript. We thank Peter Otto for his help during field sampling. We thank Katalee Jariyavidyanont for her help with DNA extraction and sequence library preparation.

Data accessibility Data and material availability: most relevant data are within the article and in the Supporting Information. The raw sequence datasets are available in the European Nucleotide Archive under the study number PRJEB15650 (http:// www.ebi.ac.uk/ena/data/view/PRJEB15650). Authors’ contributions T.K., D.K., B.H., J.B., M.H., F.B. and W.P. conceived and designed the experiments. W.P., T.A., T.R., K.B. and T.K. performed the field experiments. W.P. performed the



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Supporting information Additional Supporting Information may be found in the online version of this article at the publisher’s web-site: Appendix S1. PCR conditions. Appendix S2. Priority effect hypothesis and the competition among WIF in Fraxinus excelsior. Table S1. Comparison of the initial WIF diversity and community composition of the two halves of the initial wood samples. Table S2. Comparison of the initial specific and overall enzyme activity patterns of the two halves of the initial wood samples. Enzyme: G 5 b-glucosidase, CBH 5 cellobiohydrolase, EC 5 endoglucanase, X 5 xylanase, XD 5 xylosidase, GA 5 chitinase, LE 5 peptidase, Lac 5 laccase, MiP 5 general peroxidase and MnP 5 manganese peroxidase. Tree species: BU 5 Fagus sylvatica, DGL 5 Pseudotsuga menziesii, EI 5 Quercus spp., FI 5 Picea abies, KB 5 Prunus avium, LI 5 Tilia spp. and PA 5 Populus spp.. C 5 control, N 5 N addition. P values: - P > 0.1 (not significant), . P < 0.1(marginal significant), *P < 0.05, **P < 0.01, ***P < 0.001. Table S3. Comparison of the initial WIF community composition (2011) and at the end of the experiment (2013) for control treatment. Table S4. Effect of N addition on the WIF community composition of different major functional groups (saprotrophs, white rot saprotrophs and plant pathogens). Table S5. Effect of nitrogen deposition on specific enzyme activities. Enzyme: G 5 b-glucosidase, CBH 5 cellobiohydrolase, EC 5 endoglucanase, X 5 xylanase, XD 5 xylosidase, GA 5 chitinase, LE 5 peptidase, Lac 5 laccase, MiP 5 general peroxidase and MnP 5 manganese peroxidase. Tree species: BI 5 Betula pendula, BU 5 Fagus sylvatica, EI 5 Quercus spp., HBU 5 Carpinus betulus, KB 5 Prunus avium, KI 5 Pinus sylvestris, LI 5 Tilia spp. and



18 W. Purahong et al. PA 5 Populus spp.. C 5 control, N 5 N addition. P values: P > 0.1 (not significant), . P < 0.1(marginal significant), *P < 0.05, **P < 0.01, ***P < 0.001. Table S6. Effects of N addition and tree species on wood decomposition (CO2 emission) rates between two sampling times (May 2013 and October 2014). Table S7. Effects of N addition (pairwise comparisons) on wood decomposition (CO2 emission) rates between two sampling times (May 2013 and October 2014) across 12 tree species. Fig. S1. Experimental setup. Fig. S2. Mean 6SE (n 5 4) of C: N ratio of wood samples of different tree species in 2012 (Tree species: BI 5 Betula pendula, HBU 5 Carpinus betulus, BU 5 Fagus sylvatica, ES 5 Fraxinus excelsior, PA 5 Populus spp., KB 5 Prunus avium, EI 5 Quercus spp., LI 5 Tilia spp. LA 5 Larix decidua, FI 5 Picea abies, KI 5 Pinus sylvestris, DGL 5 Pseudotsuga menziesii). Fig. S3. Individual rarefaction curves of wood-inhabiting fungi detected in each deadwood sample.

Fig. S4. Wood-inhabiting fungal taxonomic distributions based on abundance data for two sampling times combined (September 2011 and October 2013). Fig. S5. Wood-inhabiting fungal taxonomic distributions based on presence/absence data for two sampling times combined (September 2011 and October 2013). Fig. S6. Wood-inhabiting fungal taxonomic distributions based on abundance data for first sampling (September 2011). Fig. S7. Wood-inhabiting fungal taxonomic distributions based on presence/absence data for first sampling (September 2011). Fig. S8. Wood-inhabiting fungal taxonomic distributions based on abundance data for second sampling (October 2013). Fig. S9. Wood-inhabiting fungal taxonomic distributions based on presence/absence data for second sampling (October 2013). Fig. S10. Spearman’s rank correlation between d15N (&) values and wood density (q 5 20.47, P 5 0.0047).

