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Basidiomata production of ectomycorrhizal and saprophytic agaricoid fungi respond differently to forest management

Journal: Canadian Journal of Forest Research

Manuscript ID cjfr-2018-0215.R3

Manuscript Type: Article

Date Submitted by the Author: 01-Sep-2019

Complete List of Authors: Romano, Gonzalo; Universidad Nacional de la Patagonia San Juan Bosco - Sede EsquelLechner, Bernardo; CONICET, PROPLAME-PRHIDEBGreslebin, Alina; Universidad Nacional de la Patagonia San Juan Bosco - Sede Esquel

Keyword: forest use, Agaricomycetes, Nothofagus pumilio, Patagonia, ecology

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Canadian Journal of Forest Research

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1 Basidiomata production of ectomycorrhizal and saprophytic agaricoid fungi respond

2 differently to forest management

3 Romano Gonzalo MA, B, Lechner Bernardo EC, D, Greslebin Alina GA, E

4 ADepartamento de Biología General, Facultad de Ciencias Naturales, Universidad Nacional de la

5 Patagonia San Juan Bosco. Ruta Nacional 259, Km 16.4, CP9200, Esquel, Chubut, Argentina.

6 BConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Godoy Cruz 2290,

7 CP1425, Ciudad Autónoma de Buenos Aires, Argentina.CUniversidad de Buenos Aires, Facultad

8 de Ciencias Exactas y Naturales, Departamento de Biodiversidad y Biología Experimental

9 (DBBE), Buenos Aires, Argentina. Intendente Guiraldes 2160, Pabellón 2, Laboratorio 7,

10 CP1428, Ciudad Autónoma de Buenos Aires, Argentina.DCONICET, Instituto de Micología y

11 Botánica (InMiBo), Buenos Aires, Argentina. Int. Guiraldes 2160, Pabellón 2, Laboratorio 7,

12 CP1428, Ciudad Autónoma de Buenos Aires, Argentina.

13 E CONICET, Centro de Investigación Esquel de Montaña y Estepa Patagónica (CIEMEP),

14 Esquel, Chubut, Argentina. Gral Roca 780, CP9200, Esquel, Chubut, Argentina.

15

16 Corresponding author:

17 Romano Gonzalo Matias

18 Molinari 1657, Esquel, Argentina.

19 Telephone number: +54 11 4096 1057

20 E-mail: [email protected]

21

22

23

24

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25 Abstract

26 Forest management generates border effects in mature dense forests. How agaricoid fungi

27 species react to this disturbance depends on climatic and site conditions as well as management

28 system and its intensity. We compared abundance and richness of ectomycorrhizal and

29 saprophytic species in managed and unmanaged stands in Nothofagus pumilio forests of

30 Patagonia, Argentina. We found basidiomata abundance and richness of ectomycorrhizal and

31 saprophytic species were favoured by different forest structure and climatic factors.

32 Ectomycorrhizal species basidiomata production was significantly correlated to average relative

33 humidity of the 15 days prior to sampling and number of trees per hectare existing prior to

34 management activities. The latter implies the number of trees that an ecosystem is capable of

35 sustaining is crucial to the establishment of ectomycorrhizal species. Saprophytic species were

36 favoured by the increased amount of woody debris generated by logging together with maximum

37 temperature of the 15 days prior to sampling and annual average precipitations. Our results

38 indicate that agaricoid fungi are not affected by forest management of low to medium intensity,

39 establishing the forestry level that fungal community can tolerate without loss of species in

40 Patagonia.

41 Keywords: forest use; Agaricomycetes; Nothofagus pumilio; Patagonia; ecology.

42 Introduction

43 Nothofagus pumilio (Poepp. & Endl.) Krasser, locally known as lenga, is the dominant species

44 found at timberline and the most economically exploited species in Patagonia (Hueck 1978).

45 Different techniques, including selective and protection systems, have been developed to make

46 sustainable use of these forests (Bava and López Bernal 2005). Selective systems generate

47 uneven-aged stands, as they involve removal of individual or small groups of trees, opening

48 small canopy gaps where the regeneration layer can grow strongly (López Bernal et al. 2012).

49 Protection systems involve removal of bigger clusters of trees, generating larger regeneration

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50 areas resulting in even-aged stands. Forest management generates border effects in mature dense

51 forests. Such an effect is characterised by a lower density of mature trees that leads to higher

52 exposure to solar radiation and wind (Abrego and Salcedo 2014), and an array of changes in

53 several groups of organisms (de Groot et al. 2016).

54 Fungal ecological studies commonly focus in species producing perennial basidiomata (e. g.

55 Abrego and Salcedo 2013, Runnel and Lohmus 2017). Agaricoid fungi produce ephemeral

56 basidiomata, which difficult field sampling and historically led to overlook their ecological

57 importance as part of ectomycorrhizal (ECM) and saprophytic (SAP) communities. However,

58 recent studies include them as potential biodiversity surrogates in forest habitats (Halme et al.

59 2017).

60 For ECM community, environmental variables modelling their abundance and richness remain

61 unclear. Luoma et al. (2004) found that ECM species abundance is less affected by dispersed

62 green-tree retention than by retention of aggregated clusters of trees, mainly because of the

63 survival of living tree root systems. Kutszegi et al. (2015) found no specific association between

64 ECM fungal species and environmental variables for beech forests in West Hungary. Romano et

65 al. (2017b) found precipitations of the driest month is an important variable modelling agaricoid

66 species basidiomata production. For SAP community, the environmental variables modelling

67 their abundance and richness are clearer, with woody debris availability being the most

68 important of them. Silva et al. (2016a) studied the effects of native forest management on the

69 aphylophoroid community of native forests in Patagonia, Argentina. They found a higher

70 abundance of aphylophoroid species basidiomes in managed than in unmanaged stands in

71 Nothofagus pumilio forests in Patagonia, suggesting that these species take advantage of this

72 availability of woody debris (Abrego and Salcedo 2013, Blaser et al. 2013, Runnel and Lohmus

73 2017).

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74 Our objectives were to i.) analyse if forest management common practise in Patagonia has an

75 effects on the agaricoid fungi community and ii.) examine the relation of basidiomata

76 production, a selection of climate variables and forest structure parameters.

77 Materials and Methods

78 Study area

79 Three different Nothofagus pumilio monospecific forests were studied. These sites are 100 kms

80 apart from each other, all located in Chubut province, Argentina (Figure 1): Site 1) Huemules

81 (42° 46’ S, 71° 27’ W); site 2) Guacho lake (43° 49´ S, 71° 28´ W); and site 3) La Plata lake (44°

82 51´ S, 71° 42´ W). Available information of the three sites are mentioned in Table 1. In each

83 forest, a managed stand (M) and an unmanaged stand (U) were selected (six stands in total). The

84 managed stands had been subject to protection system regimes of forest management between

85 1996 and 1998 (Antequera 2002, Claverie et al. 2003). Unmanaged stands have neither

86 documented record of being subjected to management of any kind nor were stumps found.

87 To assess abundance of agaricoid fungi basidiomata and species diversity inside all stands, an

88 area of 2500 m2 was delimited as an experimental plot. In each plot, basidiomata production was

89 recorded in 10 circular units of 4 m radius (50 m2) randomly selected in each sampling season.

90 Between 2012 and 2014 four samplings were conducted: October 2012 (spring), April 2013

91 (fall), October 2013 (spring) and April 2014 (fall). All in all, 40 units were sampled inside each

92 of the six stands.

93 Forest structure parameters

94 For the forest structure characterisation, diameter at breast height (DBH) of all standing trees and

95 number of trees per hectare (DBH> 0.10 m) were measured. Basal area (sum of area of all trees

96 at DBH), number of saplings per square meter (DBH< 0.10 m), percentage of saplings over

97 mature trees, and height of the highest saplings (cm) were assessed in 15 exclusive plots of 0.8 m

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98 radius (5 m2), regularly distributed inside the 2500 m2 plot. Canopy cover was measured with a

99 DSLR camera (Nikon D5100, Thailand) and an 18-milimeter lens (Nikkor, Thailand) in the

100 centre of the same 15 plots where regeneration was measured. Number of trees per hectare and

101 basal area prior to management of the three managed stands were obtained from Subsecretaría de

102 Bosques of Chubut province, and were used to create ratios between both variables (after and

103 before management). Silva et al. (2016a) also kindly provided us with their measurements of

104 volume of fine and coarse woody debris (FWD and CWD, respectively), assessed in 2012.

105 Climatic variables

106 Temperature and relative humidity were measured for air with dataloggers (EL-USB-2 Lascar,

107 UK) in all six stands for the two-year period studied. Because there are no weather stations near

108 any of the forests studied, annual precipitations were obtained from a bioclimatic layer (“Bio12”)

109 used in species distribution modelling (Hijmans et al. 2005, http://www.worldclim.org/). All

110 variables measured are summarized in Table 2.

111 Basidiomata sampling

112 Basidiomata collected were identified morphologically following Mata Hidalgo et al. (2009).

113 Gregarious species (basidiomata production in groups) were considered a single sample if

114 basidiomata were less than 10 cm apart, while solitary species were considered different samples

115 if it were more than 50 cm apart. All species found are treated in Romano et al. (2017a) with

116 detailed numbers of collections.

117 Chao

118 To evaluate whether sampling effort was adequate in characterising the estimated species

119 richness, we estimated asymptotic species richness for each stand using Chao-1 and Chao-2

120 species richness estimators. Species accumulation curves, Chao-1 and Chao-2 were constructed

121 using EstimateS version 9.1.0 (Colwell 2013).

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122 Statistical analyses

123 Statistical analyses were based on agaricoid fungi abundance. By abundance we mean the

124 number of basidiomata of each species. Sampling followed a randomised block design to assess

125 statistical differences in basidiomata abundance between the two contrasting forest management

126 treatments (managed and unmanaged stands). Both site and sampling year were used as blocks,

127 the latter to control temporal variations. To analyse total annual productivity, abundance in each

128 season was summed.

129 For abundance and richness analyses, the database was divided according to species nutrition

130 (Rinaldi et al. 2008) in ectomycorrhizal (ECM) or saprotrophic (SAP). Abundance and richness

131 values had a normal distribution of errors (tested with modified Shapiro-Wilks, Rahman and

132 Govindarajulu 1997) and was analysed with ANOVA. Friedman test was applied to compare

133 species abundance between stands, because the data did not have a normal distribution

134 (Friedman 1937).

135 To compare the alpha diversity of agaricoid fungi, we used Margalef, Pielou, and Simpson

136 indexes (Magurran 1988, Moreno 2001). In addition, principal components analysis (PCA) and a

137 biplot graph were applied to identify variables that most contribute to variability between

138 treatments and sites.

139 Results

140 Effects of forest management on agaricoid fungi

141 A total of 1437 samples of agaricoid fungi were found in four samplings. These samples

142 amounted to 4072 basidiomata. According to the species accumulation curves, the samplings

143 captured, on average, 70% of richness (Figure 2). Chao-1 and Chao-2 predicted that the managed

144 stand of Site 1 (1M) was the richest, followed by the unmanaged stand of Site 2 (2U). The most

145 abundant species was Mycena galericulata (Scop.) Gray (196 samples), followed by Collybia

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146 platensis (Speg.) Singer (126 samples), and Inocybe geophyllomorpha Singer (104 samples). A

147 complete list of all species basidiomata collected can be found in the Appendix A.

148 Basidiomata abundance and richness of ECM and SAP were found to be higher in the managed

149 stands of Sites 1 and 3 than in their respective unmanaged stands (Tables 3 and 4). However, the

150 pattern found in Site 2 was not congruent: while SAP species exhibited a lower abundance and

151 richness in the managed than in the unmanaged stand, ECM species abundance was higher but

152 richness was lower in the managed than in the unmanaged stand. The magnitude of the error

153 made the standard deviation too high to find statistical differences in both variables (Figure 3, p

154 = 0.1199; Figure 4 p = 0.1866).

155 Margalef index was higher in managed than in unmanaged stands in Sites 1 and 3, while the

156 opposite pattern was observed in Site 2. Simpson and Pielou indexes revealed that the

157 unmanaged stand of Site1 had the most uneven community, while the managed stand of Site 2

158 had the most even community (Table 5).

159 Friedman tests were conducted to test the behaviour of species abundance. Of the 158 species

160 recorded, only 11 showed significant differences in abundance between stands (Table 6).

161 Moreover, only a saprotrophic species, Pholiota baeosperma Singer, exhibited higher abundance

162 in unmanaged than in managed stands.

163 Principal components analysis gave two linear combinations which accounted for 0.77 of

164 observed variance. Principal component 1 (PC1) accounted for 46.8% of observed variance,

165 while PC2 accounted for 30.6% (Figure 5, Table 7). PC1 was mostly explained by the

166 combination of forest structure parameters with SAP abundance and richness, which allowed

167 separating managed from unmanaged stands. On the other hand, PC2 was mostly explained by

168 the combination of climatic variables with ECM abundance and richness, which made it possible

169 to separate Site 2 and the managed stand of Site 1 from the rest of the stands.

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170 The variables that contributed most positively to PC1 were SAP abundance and richness as well

171 as CWD volume; and those that contributed most negatively were canopy cover and basal area

172 (after/before). Unmanaged stands were associated with negative values of PC1, while managed

173 stands were mostly associated with positive values (Figure 5).

174 The variables that contributed most to PC2 were ECM abundance and richness together with

175 average relative humidity of the 15 days prior to sampling (“Hmin15”), and number of trees per

176 hectare prior to management (“Trees before”). Finally, maximum temperature of the 15 days

177 prior to sampling (“Tmax15”) together with annual average precipitations contributed negatively

178 to PC2. The Biplot graph function showed no association between ECM and SAP abundance nor

179 richness.

180 Discussion

181 Effects of forest management on agaricoid fungi

182 Patterns of abundance and richness found in all three N. pumilio forests indicate basidiomata

183 production of agaricoid fungi is modified by forest management. Among all species found

184 (Romano et al. 2017a), we highlight two of them: Descolea antarctica Singer was the most

185 abundant species found in ectomycorrhizal root tips of N. pumilio (Kuhar et al. 2017) and it was

186 favoured by forest management. An endemic species, Pholiota baeosperma, was the only one

187 found affected negatively by forest management, showing a high potential to be used as

188 indicator, since it showed significant differences in abundance between managed and unmanaged

189 stands.

190 Differential response according to nutrition

191 Dataset division according to nutrition allowed us to consider different basidiomata production

192 strategies. In this way, we observed basidiomata abundance of both ECM and SAP species was

193 higher in managed forest sites. This increase was expected for SAP species as the management

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194 practise increases the volume of CWD, the substrate preferred by early stages saprophytic

195 species (Hottola et al. 2009, Abrego and Salcedo 2013, Blaser et al. 2013, Runnel and Lohmus

196 2017) but not for later stages CWD decomposition as recorded in Ódor et al. (2006). However,

197 in Site 2 the abundance of SAP was lower in the managed than in the unmanaged stand, even

198 though the volume of CWD was higher in the managed stand. This result contrasts not only with

199 the observed pattern in the other two sites, but also with the pattern observed for SAP

200 aphyllophoroid fungi studied in the same sites (Silva et al. 2016b).

201 Saplings height in the managed stand of Site 2 is the shortest among all managed stands

202 (Appendix A), which may be causing woody debris to be more exposed to dryness by the sun

203 and winds. Although woody debris acts as shelter, hosting mycorrhizal root tips and contributing

204 to maintaining humidity reservoirs (Harvey et al. 1996, Tedersoo et al. 2009, Toledo et al. 2014,

205 Vasutová et al. 2017), such climatic conditions can modify the humidity content of debris in

206 managed forests, which ultimately affects colonization and species succession (Crockatt 2012).

207 This could explain the different basidiomata abundance between SAP agaricoid (this study) and

208 aphyllophoroid species (Silva et al. 2016b), especially if we consider that the latter are more

209 resistant to dryness because of their consistency (Alexopoulos et al. 1996).

210 Because ECM species are associated with tree roots and are highly host-specific, a lower number

211 of trees per hectare was expected to retain a lower amount of diversity and abundance of ECM

212 species (Grebenc et al. 2009, Kutszegi et al. 2015). However, higher abundance was observed in

213 managed stands in all the sites studied. Richness was higher in Sites 1 and 3 but lower in Site 2.

214 Our results can be better understood in the light of findings by Luoma et al. (2004): Although a

215 lower abundance of ECM species was observed in managed forests of Pseudotsuga menziesii

216 (Mirb.) Franco, the loss was less appreciable in forests managed only by removal of patches of

217 trees, similarly to the protection systems used in the forests studied. Luoma et al. (2004)

218 postulated that, as a result of such management, the radicular system of the remaining trees is

219 more widely distributed than in a more aggressive forest management system. In this way, this

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220 kind of “mild” management does not necessarily have a negative effect on ECM species richness

221 (de Groot et al. 2016). The density and distance between remaining mature trees are key factors

222 in a successful recovery of the ecosystem balance (Outerbridge et al. 2009). The remnants of

223 mature trees in managed stands would allow the ECM fungi community to tolerate some degree

224 of use and, as the forests recover from disturbance, they would help to establish tree regeneration

225 (Amaranthus and Perry 1994). Moreover, the combination of a great area covered with the

226 radicular system of N. pumilio and a canopy opening would allow a better penetration of rain,

227 which is an important factor in basidiome production (Fogel 1976, Luoma et al. 2004). Vasutová

228 et al. (2017) found ECM community in Czech Republic forests was affected by altitudinal

229 position and slope, variables we did not take into consideration because they were relatively

230 similar between our sites.

231 Forest regeneration after management

232 Forest use produces edge effect on mature forest sectors. This effect is characterised by a low

233 density of mature trees with the consequent higher solar radiation and winds in managed areas

234 (Abrego and Salcedo 2014). In the edge effect of protection system management, some mature

235 trees are left to protect the future saplings from excessive sun radiation and winds (Schmidt

236 1989). Therefore, a shift in fungal community after forest management takes place is expected

237 (Dickie et al. 2009), reverting gradually as the forest regenerates. It is common to find a

238 relatively high congruence in unmanaged forest stands but a lower congruence in young forests,

239 clearings and intensive managed stands, as pointed out by Hofmeister et al. (2014).

240 Forest structure parameters show that for all three sites, forest management carried out was of

241 low to medium intensity (Appendix A). The managed stands of Sites 1 and 3 have experienced

242 less and taller regeneration than the managed stand of Site 2, indicating that they are in a more

243 advanced regeneration stage, where many of the established plants were lost due to natural

244 thinning process. The managed stand of Site 2, with the highest sapling density, is in an early

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245 regeneration phase, where most established regeneration is still alive because the saplings’ short

246 height does not allow competition for light (Appendix A). Moreover, the pattern observed for

247 richness and abundance in this stand is coherent with such an explanation, given that in an early

248 regeneration phase, the negative effect of the disturbance on the ecosystem and the fungal

249 community would be more evident than in an advanced regeneration phase, like forests of Sites 1

250 and 3. In these forests, the fungal community would respond to the conditions generated by the

251 recently established saplings, which, as we observed, tend to increase basidiomata abundance

252 and richness. In this matter, Toledo et al. (2014) discussed the positive effect of mulch coverage

253 in Nothofagus forests for Cortinarius basidiome production. The earlier regeneration stage of

254 Site 2, even though logging took place at almost the same time, could be related to site

255 conditions.

256 Biodiversity, climatic and forest structure parameters association

257 The PCA analysis allowed us studying how variables interacted and detecting differences in the

258 variables associated with ECM and SAP basidiomata abundance and richness. Main factors

259 affecting basidiomata production in agaricoid fungi are humidity and temperature (Boddy et al.

260 2014). For this reason, it was expected a similar pattern of basidiomata production between SAP

261 and ECM species. However, the biplot showed no correlation between them, which were

262 associated to different forest structure and climatic factors. ECM richness and abundance were

263 positively associated with number of trees per hectare prior to forest management. This positive

264 association implied that the number of trees per hectare that an ecosystem is capable of

265 sustaining is crucial to ECM species. Once the web of tree roots and ECM mycelium is

266 established, the presence of each individual tree becomes less important to its maintenance. Such

267 a result is similar to the hypothesis of Luoma et al. (2004): the area covered by ECM root trees is

268 more important than the density of mature trees itself. SAP species were positively associated

269 with forest management intensity and CWD volume. Maximum temperature of the 15 days prior

270 to sampling and mean annual precipitations were also positively associated with SAP abundance

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271 and richness and negatively with ECM abundance and richness. The pattern observed for SAP

272 fungi is the same found by Salerni et al. (2002), who determined that precipitations – especially

273 those occurring 30 days before samplings – and maximum temperature are the two main

274 variables that affect SAP fungi abundance and richness in Quercus forests in Europe. This

275 exhibits the short term effect of precipitations, while a long term effect of the same variable, like

276 precipitations of the driest month of the year was also found to be driving basidiomata

277 production for both ECM and SAP agaricoid species (Romano et al. 2017b).

278 All in all, basidiomata abundance and richness tends to be higher in managed than in unmanaged

279 stands. The observed differences between stands may be a reflection of basidiomata production

280 patterns rather than differences in species richness. In this way, our results would indicate that

281 agaricoid fungi richness is not affected by forest management of low to medium intensity, as

282 already pointed out by de Groot et al. (2016). In agreement with our results, Hewitt et al. (2018)

283 studied species present at seedlings individual root tips, finding aggregated retention of

284 Nothofagus pumilio has a lower impact on the ECM community than dispersed retention.

285 The addition of soil properties to possible explanatory variables (Vasutová et al. 2017), and

286 studies in which fungal communities can be characterised both at root tips and basidiomata level

287 would surely improve the extent of discussion and conclusions, allowing to better understand

288 what degree of forest management can promote the sustainable usage of natural resources in

289 Patagonia.

290 Acknowledgements

291 This work was supported by Consejo Nacional de Investigaciones Científicas y Técnicas and

292 Agencia Nacional de Promoción Científica y Técnica (FONCyT, PICT 1229), which funded the

293 present research.

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359 Lenga (Nothofagus pumilio) Forests Through Group Selection System. In: “Sustainable Forest

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360 Management - Current Research”, Jorge Martin Garcia and Julio Javier DiezCasero (ed.) 3: 45–

361 66.

362 Luoma, D. L., Eberhart, J. L., Molina, R., and Amaranthus, M. P. 2004. Response of

363 ectomycorrhizal fungus sporocarp production to varying levels and patterns of green-tree

364 retention. For Ecol Manag 202: 337–354.

365 Magurran, A. 1988. Ecological diversity and its measurement. Princeton University Press, New

366 Jersey, 179 p.Mahibbur, R.M., and Govindarajulu, Z. 1997. A modification of the test of Shapiro

367 and Wilks for normality. J Appl Stat 24(2): 219–235.

368 Mata Hidalgo, M., Umaña, L., and Chaves, J . 2009. Documento borrador de referencia

369 Protocolo de manejo de colecciones de hongos. INBio Costa Rica & Norwegian Ministry of

370 Foreign Affairs, 29 p. Available at: http://inbio.ac.cr/web_herbarios/web/pdf/protocolo-

371 hongos.pdf

372 Moreno, C. 2001. Métodos para medir la biodiversidad. MandT–Manuales y Tesis SEA, Vol.1.

373 Zaragoza, 84 p.

374 Ódor, P., Heilmann-Clausen, J., Christensen, M., Aude, E., van Dort, K. W., Piltaver, A., Siller,

375 I., Veerkamp, M. T., Walleyn, R., Standovár, T., van Hees, A. F. M., Kosec, J., Matočec, N.,

376 Kraigher, H., and Grebenc, T. 2006. Diversity of dead wood inhabiting fungi and bryophytes in

377 semi-natural beech forests in Europe. Biol Cons 131(1): 58–71.

378 Outerbridge, R. A., Trofymow, J. A., and Lalumière, A. 2009. Re-establishment of

379 ectomycorrhizae from refugia bordering regenerating Douglas-fir stands on Vancouver Island.

380 Canadian Forest Service, Pacific Forestry Centre, Victoria, British Columbia.Information Report

381 BC-X-418.23 p.

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382 Rahman, M. M., and Govindarajulu, Z. 1997. A modification of the test of Shapiro and Wilk for

383 normality. J App Stat 24(2): 219–236.

384 Rinaldi, A. C., Comandini, O., and Kuyper, T. W. 2008. Ectomycorrhizal fungal diversity:

385 separating the wheat from the chaff. Fung Divers 33: 1–45.

386 Romano, G.M., Greslebin, A.G., and Lechner, B.E. 2017a. Hongos agaricoides de los bosques de

387 Nothofagus pumilio (Chubut, Argentina): Clave y listado de especies. Revista del Museo

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389 http://revista.macn.gob.ar/ojs/index.php/RevMus/article/view/495

390 Romano, G.M.; Greslebin, A.G.; and Lechner, B.E. 2017b. Modelling agaricoid fungi

391 distribution in Andean forests of Patagonia. Nova Hedwigia 105(1-2): 95–120.

392 Runnel, K., and Lohmus, A. 2017. Deadwood-rich managed forests provide insights into the old-

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395 temperature and rainfall on fruiting of macrofungi in oak forests of the Mediterranean area. Israel

396 J Plant Sci 50: 189–198.

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398 Universidad de Chile y CONAF, 19 p.

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401 Conference paper at V Jornadas Forestales Patagónicas. Esquel, Chubut, Argentina.

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404 micobiota y la degradación de la madera. V Jornadas Forestales Patagónicas book, 26–31.

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414 environmental variables drive the community composition of mycorrhizal and saprotrophic fungi

415 at the alpine treeline ecotone. Fungal Ecol 27: 116–124.

416 Tables

Table 1: Study sites characterisation

Site 1 2 3

Elevation a.s.l. (m) 1173 1267 948

Mean annual temperature (º C) 5.93 5.33 5.70

Minimum annual temperature (º C) -10.75 -12.50 -16.25

Mean annual precipitations (mm) 726.24 680.12 871.67

417 1, 2 and 3: site number.

418

Table 2: Climatic, forest structure and biodiversity variables measured

Climatic variables Forest structure parameters Biodiversity

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variables

Ambient

temperature Canopy cover

Number of trees

remaining

Basidiomata

abundance

Relative humidity Saplings percentage Remaining basal area Basidiomata richness

Annual

precipitations

(Bio12) Saplings maximum height

Basal area

(after/before)

Margalef diversity

index

Number of trees per

hectare (current)

Coarse woody debris

(CWD) volume

Simpson Dominance

index

Number of trees per

hectare (before)

Fine woody debris

(FWD) volume

Pielou Evenness

index

Number of trees per

hectare (current/before)

419

420

Table 3: Agaricoid fungi abundance according to nutrition and year of sampling

Total abundance ECM abundance SAP abundanceStand

Year 1 Year 2 Year 1 Year 2 Year 1 Year 2

1M 332 35 148 11 184 24

1U 139 15 60 5 79 10

2M 150 22 114 11 36 11

2U 193 24 99 9 94 15

3M 379 37 88 0 291 37

3U 108 3 37 0 71 3

421 1, 2 and 3: site number, M: managed, U: unmanaged, ECM: ectomycorrhizal, SAP: saprophytic.

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422

Table 4: Agaricoid fungi richness according to nutrition and year of sampling

Total richness ECM richness SAP richnessStand

Year 1 Year 2 Year 1 Year 2 Year 1 Year 2

1M 76 14 42 7 34 7

1U 34 11 23 4 11 7

2M 52 14 33 7 19 7

2U 60 20 38 9 22 11

3M 62 11 29 0 33 11

3U 44 3 16 0 28 3


424

425

Table 5: Comparison of diversity, dominance and evenness of agaricoid fungi between stands

Stand Diversity (Margalef) Dominance (Simpson) Evenness (Pielou)

1M 13.886 0.095 0.757

1U 7.941 0.159 0.738

2M 11.073 0.033 0.919

2U 12.268 0.036 0.893

3M 10.281 0.063 0.806

3U 9.130 0.053 0.895

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426 1, 2 and 3: site number, M: managed, U: unmanaged.

427

428

Table 6: Cumulative samples of species with significant differences in abundance between

stands according to Friedman tests (p<0.0001).

Species M U

Austropaxillus boletinoides (Singer) Bresinsky and Jarosch 16 9

Austropaxillus statuum (Speg.) Bresinsky and Jarosch 23 9

Cortinarius aff. aganochrous 9 3

Cortinarius dissimulans M.M. Moser 8 1

Cortinarius leucoloma M. M. Moser 22 7

Cortinarius simplex E. Horak 14 3

Galerina hypnorum (Schrank) Kühner 17 2

Inocybe fuscocinnamomea Singer 8 2

Inocybe geophyllomorpha Singer 70 34

Mycena desfontainea Singer 15 2

Pholiota baeosperma Singer 4 23

429 M: managed, U: unmanaged.

430

431

Table 7: Variables contribution to principal components 1 and 2

Variable PC1 PC2

ECM abundance 0.13 0.40

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ECM richness 0.06 0.43

SAP abundance 0.35 -0.03

SAP richness 0.30 0.02

Canopy cover -0.33 -0.02

Trees before 0.09 0.33

Remaining trees 0.38 0.04

Remaining BA 0.35 0.14

BA (after/before) -0.32 -0.19

CWD volume 0.32 -0.12

FWD volume 0.18 0.21

Tmax 15 0.21 -0.40

Hmin 15 -0.24 0.31

Annual precipitations 0.19 -0.40

432 ECM: ectomycorrhizal, SAP: saprophytic, Trees before: number of trees before management,

433 Remaining trees: number of trees after management, Remaining BA: basal area of remaining

434 trees after management, BA after/before: ratio between basal area after and before management,

435 CWD: coarse woody debris, FWD: fine woody debris, Tmax15: maximum temperature 15 days

436 prior to sampling, Hmin15: minimum humidity 15 days prior to sampling.

437 Figure captions

438 Figure 1: The three sites sampled during 2012-2014. Argentinian Andean forests in green

439 shading.

440 Figure 2: Cumulative species curves for the studied stands.

441 Figure 3: Basidiomata total abundance of agaricoid fungi in managed and unmanaged stands (p =

442 0.1199). M: managed stands, U: unmanaged stands.

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443 Figure 4: Agaricoid fungi richness in managed and unmanaged stands (p = 0.1866). M: managed

444 stands, U: unmanaged stands.

445 Figure 5: PC1 vs. PC2. Red dots indicate managed stands; green dots indicate unmanaged stands.

446 Trees before: number of trees per hectare before management; Trees after: number of trees per

447 hectare after logging; Remaining BA: basal area after management; BA after/before: ratio

448 between basal area after/before management; Tmax 15: maximum temperature on the 15 days

449 prior to samplings; Hmin 15: minimum humidity on the 15 days prior to samplings.

450 Appendix A

451 Forest structure parameters for all three sites studied (kindly provided by Silva et al. 2016a).

452Number of trees per hectare and basal area

Stand Number of trees per hectare Basal area (m2/ha)

1M 104 20.86

1U 304 49.54

2M 168 35.06

2U 560 74.65

3M 68 20.41

3U 324 42.51

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455

456

457

458 1, 2 and 3: site number, M: managed.

459

460

Coverage and saplings

Stand Coverage

(%)

Saplings

(%)

Saplings

(number/m2)

Saplings max

height (cm)

1M 65 66.7 0.3 181

1U 69 73.3 0.2 21

2M 57 93.3 0.9 42

2U 70 100 1.1 13

3M 44 86.7 0.2 176

Number of trees per hectare and basal area according to forest management

Number of trees per hectare Basal area (m2/ha)Stand

Before After Current Before After Current

1M 376 220 104 59.17 36.25 20.86

2M 477 358 168 75.07 43.36 35.06

3M 482 87 68 47.80 18.50 20.41

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3U 68 93.3 0.5 58


462

463

Woody debris volume (m3/ha)

Stand CWD FWD

1M 506.68 51.2

1U 262.68 61.08

2M 285.48 97.72

2U 123.52 97.24

3M 467.56 124.84

3U 333.76 43.04


465

466 Statistical analyses outputs

467 Total abundance468469

Variable N R2 R2 Aj CVTotal abundance 12 0.76 0.63 64.39

470471 Variance Analysis Table (SC type III)

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473 Richness474475 Variable N R² R² Aj CV 476 Richness 12 0.87 0.79 33.63477478

Variable N R2 R2 Aj CVRichness 12 0.87 0.79 33.63

479480481 Variance Analysis Table (SC type III)

482483

484 List of species found per year and stand

Year 1 Year 2Species

Nutrition 1M 1U 2M 2U 3M 3U 1M 1U 2M 2U 3M 3UArmillaria montagnei SAP 2 - - - - - - - - - - -Arrhenia griseopallida SAP - - 1 - - - - - - - - -Austropaxillus boletinoides ECM 2 - 9 7 5 1 - 1 - - - -

F. V. SC gl CM F p-value

Model 134788.17 4 33697.04 5.67 0.0234

Site 3042.00 2 1521.00 0.26 0.7812

Treatment 18644.08 1 18644.08 3.14 0.1199

Year 113102.08 1 113102.08 19.02 0.0033

Error 41618.08 7 5945.44

Total 176406.25 11

F. V. SC gl CM F p-value

Model 5774.67 4 1443.67 11.43 0.0034

Site 85.17 2 42.58 0.34 0.7248

Treatment 270.75 1 270.75 2.14 0.1866

Year 5418.75 1 5418.75 42.90 0.0003

Error 884.25 7 126.32

Total 6658.92 11

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Austropaxillus statuum ECM 4 2 13 6 6 1 - - - - - -Bolbitius reticulates SAP - 1 - - 5 - - - - - - -Clitocybe patagonica SAP 2 3 2 4 24 5 - - - - - -Clitocybe pleurotus SAP - - - - 41 4 1 - - - - -Clitocybe suaveolens SAP 2 - - 6 18 5 - - - - 1 -Clitocybe subhygrophanoides SAP - - - - - 2 - - - - - -Clitocybe subleptoloma SAP - - - - 1 - - - - - - -Gymnopus aff fuscopurpureus SAP 1 - - - - - - - - - - -Gymnopus fuegianus SAP 1 1 2 21 9 1 - 1 1 - 12 -Gymnopus fuscopurpureus SAP 8 - 2 4 10 6 - - - - - -Collybia platensis SAP 22 2 1 1 62 17 3 3 1 2 11 1Coprinellus truncorum SAP - - - - - 1 - - - - - -Cortinarius aff scolecinus ECM 1 - - - - - - - - - - -Cortinarius aff aganochrous ECM 2 - 2 2 4 1 - - 1 - - -Cortinarius albobrunneus ECM 1 - 2 1 - 1 - 1 - - - -Cortinarius albocanus ECM - - 4 5 - 2 1 - 2 - - -Cortinarius albocinctus ECM 7 2 5 2 3 4 - - - - - -Cortinarius austroduracinus ECM - - 2 3 1 1 - - 1 - - -Cortinarius austrolimonius ECM - - - 1 - - - - - - - -Cortinarius austrolimonius var ochrovelatus ECM - 1 - - - - - - - - - -Cortinarius bulboso-mustellinus ECM - 1 1 - - - - - - - - -Cortinarius caelicolor ECM 1 - - 2 5 - - - - - - -Cortinarius cf myxoduracinus ECM 2 - - - - - 2 - - - - -Cortinarius coleopus ECM 1 - - - - - - - - - - -Cortinarius collariatus ECM - - - 1 1 - - - - - - -Cortinarius concolor ECM 2 - - 2 - - 1 - - - - -Cortinarius cretaceus ECM - - - 4 8 3 1 - - - - -Cortinarius darwinii ECM 3 1 4 3 - - - - - - - -Cortinarius dissimulans ECM 3 - 3 1 2 - - - - - - -Cortinarius egenus ECM 2 1 2 8 1 - - - 1 1 - -Cortinarius elaphinus ECM 20 8 5 4 2 - - - - 1 - -Cortinarius exilis ECM - - 2 - - - - - - - - -Cortinarius fuegianus ECM - - - 1 - - - - - - - -Cortinarius fulvoconicus ECM 4 - - 1 2 - - - - - - -Cortinarius gayi ECM - 1 - 1 - - - - - - - -Cortinarius hebes ECM - - - 1 - - - - - - - -Cortinarius holojanthinus ECM - - 1 - - - - - - 1 - -Cortinarius illitus ECM 1 1 1 - - - - - - - - -Cortinarius inocybiphyllus ECM - - - - 1 1 - - - - - -Cortinarius interlectus ECM - 1 - - - - - - - - - -Cortinarius leucoloma ECM 11 3 6 1 5 3 - - - - - -Cortinarius lignyotus ECM - - - 1 - - - - - - - -Cortinarius magellanicus ECM 1 2 2 - - - - - - - - -Cortinarius maulensis ECM - - - - - - - 1 - - - -Cortinarius melleus ECM 2 - 2 5 1 4 4 - - - - -Cortinarius mustellinus ECM 1 - - - - - - - - - - -

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Cortinarius myxoclaricolor ECM - 1 - - - - - - - - - -Cortinarius napivolvatus ECM - - - 3 - - - - - - - -Cortinarius nothoanomalus ECM 2 3 3 - 1 - - - - - - -Cortinarius obesus ECM - - 1 - - - - - - - - -Cortinarius occentus ECM - - 1 - - - - - - - - -Cortinarius ocellatus ECM 1 - 5 6 1 - - - - - - -Cortinarius parazureus ECM 1 1 1 - 1 - - - - - - -Cortinarius permagnificus ECM - - - 1 - - - - - - - -Cortinarius phaeocephalus ECM 1 - - - - - - - - - - -Cortinarius pseudotriumphans ECM 1 - - - - - - - - - - -Cortinarius roseopurpurascens ECM - - - - - - 1 - - - - -Cortinarius rubrobasalis ECM 1 - - - - - - - - - - -Cortinarius saccharatus ECM - - 3 1 1 - - - - - - -Cortinarius scabrosporus ECM 1 - - 1 - - 1 - 2 1 - -Cortinarius simplex ECM 4 - 7 1 3 2 - - - - - -Cortinarius sp3 ECM 5 - - - - - - - - - - -Cortinarius sp2 ECM 1 - - - - - - - - - - -Cortinarius sp1 ECM - - - - - - - - - 1 - -Cortinarius squamiger ECM 1 - - - - - - - - - - -Cortinarius succineus ECM 1 - - 4 1 2 - - 1 - - -Cortinarius surreptus ECM - - - - 1 - - - - - - -Cortinarius terebripes ECM - - - 2 - - - - - - - -Cortinarius tricholomoides ECM - - - 1 - - - - - - - -Cortinarius variegatulus ECM - - 2 - - - - - - - - -Cortinarius xanthocholus ECM - - - 2 1 - - - - 1 - -Cortinarius xylocinnamomeus var xylocinnamomeus ECM 1 - - - - - - - - 1 - -Crepidotus sp1 SAP 1 - - - - - - - - - - -Crepidotus applanatus SAP 4 - - - 3 1 - - - - 1 -Crepidotus brunswickianus SAP - - - 5 6 2 - - - - - -Crepidotus fulvifibrillosus var Meristocystis SAP 3 2 - - 4 1 - 1 - - - -Cuphophyllus adonis SAP 2 - - - - - - - - - - -Descolea antarctica ECM 11 3 2 2 1 - - - - - - -Entoloma cucurbita ECM - 1 - - - - - - - - - -Entoloma papillatum ECM - - 1 - - - - - - - - -Galerina sp3 SAP - - - - - - - 1 - - - -Galerina sp4 SAP - - 1 - - - - - - - - -Galerina aff tibiicystis SAP 2 - - - - - - - - - - -Galerina gamundiae SAP - - 2 2 11 1 1 - - - 1 -Galerina hypnorum SAP 4 - 6 1 7 1 - - - - - -Galerina riparia SAP - - 1 - - - - - - - - -Galerina sp2 SAP - - - - 5 - - - - - - -Galerina sp1 SAP - - 1 - - - - - - - - -Marasmiellus minutus ECM - 2 - - - - - - - - - -Hemimycena patagonica SAP - - - 1 - - - - - - - -Hydropus dusenii SAP - - - - 3 1 - - - - 1 -Hypholoma frowardii SAP 2 - - - - - - - 2 - - -

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Hypogaea brunnea ECM - 1 - - - - - - - - - -Inocybe bridgesiana ECM - - 3 - - 1 - - - - - -Inocybe cerasphora ECM 1 - - - 1 - - - - - - -Inocybe fuscocinnamomea ECM 5 - 2 - 1 - - 2 - - - -Inocybe geophyllomorpha ECM 34 16 12 8 21 9 - - 3 1 - -Inocybe neuquenensis ECM 1 2 - - - 1 - - - - - -Kuehneromyces cystidiosus SAP 1 - - - - - - - - - - -Laccaria tetraspora ECM 1 - - - - - - - - - - -Lepiota subgracilis SAP 3 - - - - 1 - - - - - -Leucopaxillus sp1 ECM - - 2 - - - - - - - - -Simocybe cf curvipes SAP - - - - - - - - - 1 - -Marasmius aporpus SAP - - - - 2 - - - - - - -Marasmius aff ushuaiensis SAP - - - 1 - - - - - - - -Marasmius hemimycena SAP 1 1 - - 2 4 - - - - - -Marasmius sp2 SAP 1 - - - - - - - - - - -Marasmius sp1 SAP - - - - - 1 - - - - - -Marasmius ushuaiensis SAP - - - 10 4 - 3 - 2 1 - -Melanoleuca cf melaleuca SAP 1 - - - - - - - - - - -Melanoleuca lapataiae SAP 2 - - - - - - - - - - -Melanoleuca sp1 SAP - - 1 - - - - - - - - -Mycena aff dendrocystis SAP - - - - 1 - - - - - - -Mycena atroincrustata SAP - - - 3 13 1 - - - 1 1 -Mycena dendrocystis SAP - - - - 1 - - - 1 - - -Mycena desfontainea SAP 7 - 1 - 7 2 - - - - - -Mycena epipterygia SAP - - - - - 1 - - - - - -Mycena falsidica SAP - - - 2 - 1 1 - - - - -Mycena galericulata SAP 88 57 1 3 27 2 11 - - 2 4 1Mycena haematopus SAP 4 - - - - - - - - - - -Mycena helminthobasis SAP 1 - - 1 - - - - - - - -Mycena patagonica SAP 3 - - 3 1 - - 1 - 2 3 -Mycena pura SAP 1 - - - - 1 - - - - 1 -Mycena sp2 SAP 1 - - - - - - - - - - -Mycena sp3 SAP - - - - 1 - - - - - - -Mycena sp1 SAP - - - - - 1 - - - - - -Mycena sp4 SAP 1 1 - - - - - - - - - -Mycenella margaritispora SAP 1 - 1 - 1 3 - - - - - -Omphalina subhepatica SAP 1 - - - 3 - - - - - - -Phaeomarasmius ciliatus SAP - - - - 1 - - - - - - -Phaeomarasmius limulatellus SAP - - - - 2 - - - - - - -Pholiota baeosperma SAP - 1 4 20 - 1 - - - 1 - -Pholiota cf aurantioalbida SAP - - - - - - - - - 1 - -Pholiota privigna SAP 6 - - - - - - - - - - -Pholiota sp1 SAP - - - - - - - - 1 - - -Pholiota spumosa var crassitunica SAP - - - 1 - - - - - - - -Scytinotus longinquus SAP - - - - - - - - - 1 - -Pluteus spegazzinianus SAP 3 4 5 2 12 2 - 1 3 2 - -Porpoloma sejunctum ECM 1 - - - - - - - - - - -

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Psathyrella falklandica SAP - 6 2 - 1 - - - - - 1 -Psathyrella fuegiana SAP - - - - 1 - - - - - - -Psathyrella sp1 SAP - - 1 - - - - - - - - -Psilocybe coprophila SAP - - - 1 - - - - - - - -Protostropharia semiglobata SAP - - - - - - - - - 1 - -Psilocybe subcoprophila SAP - - - 1 - - - - - 1 - -Resupinatus applicatus SAP - - - - - - - 2 - - - -Resupinatus chilensis SAP - - - - 2 2 - - - - - 1Rhodocollybia butyracea SAP 1 - - 1 - - - - - - - -Entoloma mesites ECM 1 - - - 4 - - - - - - -Entoloma patagonicum ECM - - 3 1 3 - - - - - - -Russula fuegiana ECM 1 1 - 1 - - - - - - - -Russula nothofaginea ECM - 5 - - - - - - - - - -Russula nothofaginea var carminea ECM - - - 2 - - - - - - - -Schizophyllum commune SAP 1 - - - - - 4 - - - - -Simocybe curvipes SAP - - 1 - - - - - - - - -


486

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Figure 1: The three sites sampled during 2012-2014. Argentinian Andean forests in green shading.

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Figure 2: Cumulative species curves for the studied stands.

184x218mm (300 x 300 DPI)

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Figure 3: Basidiomata total abundance of agaricoid fungi in managed and unmanaged stands (p = 0.1199). M: managed stands, U: unmanaged stands.

96x68mm (300 x 300 DPI)

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Figure 4: Agaricoid fungi richnss in managed and unmanaged stands (p = 0.1866). M: managed stands, U: unmanaged stands.

94x68mm (300 x 300 DPI)

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Caption : Figure 5: PC1 vs. PC2. Red dots indicate managed stands; green dots indicate unmanaged stands. Trees before: number of trees per hectare before management; Trees after: number of trees per hectare after logging; Remaining BA: basal area after management; BA after/before: ratio between basal area

after/before management; Tmax 15: maximum temperature on the 15 days prior to samplings; Hmin 15: minimum humidity on the 15 days prior to samplings.

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