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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
Is the invited manuscript for consideration in a Special
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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.
294 References
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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
423 1, 2 and 3: site number, M: managed, U: unmanaged, ECM: ectomycorrhizal, SAP: saprophytic.
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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454 1, 2 and 3: site number, M: managed, U: unmanaged.
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
461 1, 2 and 3: site number, M: managed, U: unmanaged.
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
464 1, 2 and 3: site number, M: managed, U: unmanaged.
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 - - - - - - - - -
485 1, 2 and 3: site number, M: managed, U: unmanaged, ECM: ectomycorrhizal, SAP: saprophytic.
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.
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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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