Fungal fruitbodies and soil macrofauna as indicators of land use

Agroforest Syst DOI 10.1007/s10457-010-9359-y

Fungal fruitbodies and soil macrofauna as indicators of land use practices on soil biodiversity in Montado Anabela Marisa Azul • Sara Margarida Mendes Jose´ Paulo Sousa • Helena Freitas

•

Received: 22 January 2010 / Accepted: 28 October 2010 Ó Springer Science+Business Media B.V. 2010

A. M. Azul (&) H. Freitas Department of Life Sciences, Centre for Functional Ecology, University of Coimbra, PO Box 3046, 3001-401 Coimbra, Portugal e-mail: [email protected]

cutting practices followed by soil tillage (M), in comparison with cutting practices with no soil tillage (Cu) and the control (C). The ECMF Laccaria laccata and Xerocomus subtomentosus exhibited a close relation with C and Cu plots while the saprobes, e.g., Entoloma conferendum, were associated to Ca and M plots. Most species associated to Cu plots were present in C plots during the 2 years, but not in Cu after the cutting practices (in the second year of sampling). Regarding soil macrofauna, higher values of taxa and species richness were observed in C and Cu plots in the first year of sampling. The ant species Aphaenogaster senilis and several Staphylinid morphospecies exhibited a close relation with M plots, whilst most spider families were directly associated to C and Cu plots. After the shrub cutting practices, higher values of taxa and species richness of soil macrofauna were observed in M and Ca plots; the presence of species with a high competitive ability to colonize disturbed areas faster might explain the results. Contrary to the frutibodies production and diversity, species richness and abundance within soil macrofauna were identical between Cu and C in 2004. Thus, fruiting macromycetes and soil macrofauna diversity and abundance in Montado’s, appear highly sensitive to land use and somewhat reflected a trend of severity to the current shrub management practices.

S. M. Mendes J. P. Sousa Department of Life Sciences, IMAR-CMA, University of Coimbra, PO Box 3046, 3001-401 Coimbra, Portugal

Keywords Fungal fruit-body Soil macrofauna Quercus suber L. Ecosystems monitoring Land use Montado

Abstract The impacts of land use on soil biodiversity are still poorly understood, although soil fungi and macrofauna are recognized to provide benefits to ecosystems. Here, we tested whether land use practices used to control shrub density influences the fruiting macromycetes (ectomycorrhizal-forming fungi— ECMF—and saprobes) and soil macrofauna diversity and abundance in Montado ecosystems. To address this influence, we conducted a 2-years’ period monitoring of fungi fruitbodies and macrofauna in sixteen experimental plots in Montado landscape in southern Portugal. A total of 4,881 frutibodies (57 taxa of ECMF and 64 taxa of saprobic fungi) and 3,667 soil invertebrates (73 species and morphospecies) were monitored in the experimental plots. There was greater losses in sporocarps production and taxa composition, particularly the ECMF, in plots where shrub density was controlled by permanent grazing (Ca) or involving

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Introduction Quercus suber L. (cork oak) woodlands cover 23% of the total forest area in Portugal (737 9 103 ha; DGRF 2007). The cork oak woodlands are widespread in the Mediterranean basin and cover about 2.2 million ha in Europe (Portugal, Spain, France, and Italy) and North Africa (Morocco, Algeria, and Tunisia). Most of cork oak woodlands in Portugal are under agro-silvopastoral exploitation, traditionally called Montado, that is characterized by open oak formations of evergreen oaks (Q. suber and Quercus rotundifolia L.), pastures and agricultural fields as undercover, traditionally in a rotation scheme that includes fallows. The Montados are well adapted to the Mediterranean environment and represent a good example of sustainable agroforestry practice in Europe (Council of Europe 1992) by combining two key aspects of land management: production and conservation, and due to their social and economic outcomes (Pinto-Correia and Vos 2004; Scarascia-Mugnozza et al. 2000). Changes in land management over the twentieth century are thought to have contributed to Montado landscape degradation (Joffre et al. 1999; Nunes et al. 2005; Pinto-Correia 1993), with a significant decline in cork oaks and plant and animal biodiversity (Da Silva et al. 2008; Hector et al. 1999). Although successfully managed Montados remain, others are increasingly being reforested with other tree species considered more lucrative by forest managers (e.g., Pinus pinea for the production of pine acorns; Eucalyptus globulus, for the production of cellulose for the pulp industry), whilst other Montados are abandoned and subject to shrub intrusion highly susceptible to fire (Nunes et al. 2005). In both cases, a collapse of this highly-adapted and diverse Mediterranean-type ecosystem is observed. Evaluating the impacts of management actions on forests using bioindicators is widely recommended by European programs (Delbaere et al. 2002; EPBRS 2002a, b). Plant mutualists, such as mycorrhizal fungi, and saprobes are widespread and are thought to maintain the structure and diversity of natural communities, influencing the performance of individual plants but also altering plant community structure, plant productivity, and nutrient cycling (Smith and Read 2008). Ectomycorrhizal (ECM) develop symbiotic structures on fine root tips and form a complex belowground

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network that benefits plant communities by facilitating and influencing seedling establishment, by altering plant–plant interactions and by supplying and recycling nutrients (van der Heijden and Horton 2009), while saprobic fungi are more specialized in decomposing dead organic plant material. In this context, a previous study reported that ECM fungal community associated to cork oak is quite diverse in both community structure and species composition, and affected by seasons, land use and cork oak mortality (Azul 2002; Azul et al. 2010). Soil fauna is also gaining importance in biodiversity assessment studies due to its active role on soil processes and its sensitive response to changes in the soil system (Bruyn 1997; Frouz 1999; Knoepp et al. 2000; Rainio and Niemela¨ 2003; Sauberer et al. 2004). Soil organisms are representative of soil conditions whether it’s physical, chemical or biological processes we’re trying to assess (Blakely et al. 2002; Breure et al. 2005). This means that soil organisms could be used as indicators of soil quality; soil invertebrates, one of the most abundant and diverse groups of soil organisms, for example, often react very quickly to environmental changes, with very sensitive responses (Bruyn 1997; Nickel and Hildebrandt 2003; Perner and Malt 2003; Rainio and Niemela¨ 2003). Some soil invertebrate indicators are already being used to assess certain conditions (Beck et al. 2005; Hodkinson and Jackson 2005; Ja¨nsch et al. 2005; Knoepp et al. 2000; Lavelle et al. 2006; Nahmani et al. 2006; Rombke et al. 2005; Ruiz Camacho et al. 2009; Sochova´ et al. 2006; Souty-Grosset et al. 2005; Tischer 2005; Velasquez et al. 2007). Several studies conducted in cork oak and holmoak woodlands have been published (Cammell et al. 1996; Da Silva et al. 2008; Deharveng et al. 2000; Rego and Dias 2000; Sousa et al. 1997) but none of these focused specifically on fungi and macrofauna as indicators of the impacts of land use. Understanding and predicting the consequences of land use in soil biodiversity is emerging as one of the grand challenges for sustainable forest management, under climate change (European Environment Agency 2004) and heavy mortality of evergreen oaks (Brasier 1996; Brasier and Scott 2008). In this work, we propose to investigate the performance of fruiting macromycetes of ectomycorrhizal (ECMF) and saprobic fungi and soil macrofauna as indicators of land use in Montado ecosystems, an approach that can yield

Agroforest Syst

insight into the link between management practices and diversity descriptors of key soil components: fungi and macrofauna.

Materials and methods Study site Field-work was conducted in a Montado landscape, located in Foros de Vale de Figueira (Montemor-oNovo, Portugal) (388410 1000 N, 88200 2300 W) (Fig. 1). The climate is typically Mediterranean, with a severe summer drought (2–4 months) and mild humid winters, with precipitation mainly from autumn to mid spring. The mean temperature ranges from 7.5°C (mean average in January) to 24°C (mean average in July). Soils are classified as orthic luvisols with organic layers varying accordingly with land use and the year of perturbation; pH ranges from 4.5 to 5.7.

Fig. 1 Location of the Montado landscape in Montemor-oNovo: Alentejo region (southern Portugal)

Montado landscape is dominated by Quercus suber (40 to 60 trees per ha), but Quercus rotundifolia is also present, shrub strata (mainly Cistus salvifolius L., C. crispus L. and C. ladanifer L.) with plants with 4–5 years of age, occupying 65% of the total vegetation cover density. Cork is the main lucrative economical activity and it is harvested every 9-year period; cattle breeding represent the second profitable activity. Land use is focused on practices to control shrubs density to reduce the risk of fire. Experimental design Sixteen experimental plots of 20 9 20 m were selected randomly among four Montado areas, each one with a different shrub management practice. The four treatments include: the control (C), with no shrub-cutting in the preceding 5 years, including the 2 years (2003 and 2004) study period; the cut plots (Cu), with mechanized cutting practices that cut the shoot of the plants and left it on the ground without till the soil afterwards; the cattle plots (Ca), with shrubs artificially maintained at low densities by permanent grazing of cows and sheep; and the mobilized plots (M), with mechanized practices with soil tillage that remove the completely the plants (Fig. 2). Shrub management practices were performed in Cu and M plots in the beginning of autumn 2004. Fruiting macromycetes of ECMF and saprobic fungi were monitored every 10 days during the peak fruiting period, from September to December, in 2003 and 2004. The plots were distributed erratically among four Montado areas and fruiting incidence per plot was assumed to be totally independent from the fruiting incidence of the neighbouring plots. Fungal fruitbodies were counted and mapped but not geo-referenced. Macromycetes were identified to species level to species level in most cases, according to Bon (1988), Courtecuisse and Duhem (1995) and Moreno et al. (1986); the unidentified species were also considered. The list of all taxa observed is presented in Appendix (Table 3). Taxa abundance of fungal fruitbodies was estimated as the cumulative number of individuals produced by a given taxon for each plot. The quantification method for sporocarps was chosen instead of biomass analysis because of the limitations inherent to sizes and biomass measurements among mushrooms, which frequently obscure fructification of smaller

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Fig. 2 Experimental areas selected in the Montado (C control, Cu shrub density controlled by cutting practices without soil tillage, Ca shrub density controlled by permanent grazing, M shrub density controlled by cutting practices followed by tillage of soil)

individuals. Species frequency refers to the percentage within the experimental areas in which a given species fruited at least once during the entire sampling period. Sporocarps production was defined as the total number of fruitbodies counted over the study period. Regarding soil macrofauna, sampling took place in Autumn 2003 and Autumn 2004, for a period of 10 days. For each year, nine pitfall traps were settled on each plot, following a nested design. Samples were brought to laboratory and biological material was sorted and identified to species level (when this was not possible, morphospecies level was used). Data analysis Fungi fruit bodies and soil macrofauna abundance and number of taxa at each stand were compared by an ANOVA, followed by a Newman–Keuls test when differences were found. In both cases, data was log transformed prior to analysis whenever normality or homoscedasticity criteria were not met (Zar 1996). For each zone, species diversity indices (Shannon–Wiener and Simpson) were calculated according to Magurran (1988). To evaluate differences between stands regarding community composition, ANOSIM (Analysis of

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Similarity) were performed based on the Bray–Curtis similarity index (Clarke and Gorley 2006). Data was log transformed prior to analysis. This analysis was done on PRIMER 5 for Windows software (Clarke and Gorley 2006). Multivariate techniques were also used to associate taxa to stands: two correspondence analyses (CA), one per sampling year, were performed for fungi fruitbodies (stands were used as dummy environmental variables) and two principal component analyses (PCA), one per sampling year, were performed for soil macrofauna data. Biological data used in these analyses was also log transformed. The statistical significance of the canonical axes was evaluated by a Monte Carlo permutation test. Both CA and PCA were performed in CANOCO 4.5 software (Ter Braak and Smilauer 1998).

Results Fruiting macromycetes Abundance and biodiversity descriptors A total of 4,881 fungal fruitbodies (57 ECMF taxa and 64 saprobe taxa; Table 3 in Appendix) were assessed

Agroforest Syst Table 1 Fruitbodies abundance and diversity descriptors 2003

2004

Fruitbodies S

H0

D

Fruitbodies S

H0

D

C

1167

55 2.86

9.41 983

30 2.35 6.29

Cu

980

55 2.84

7.64 340

20 1.47 2.4

Ca

668

25 2.23

5.39 395

13 2.07 6.52

M

316

38 2.88 12.31

32

5 1.42 3.88

0

S number of observed taxa, H Shannon diversity index, D Simpson diversity index, C control, Cu cutting practices using machinery with no soil tillage, Ca permanent grazing by cattle, M shrub management using machinery followed by soil tillage 1000

ECMF

900

2003 2004

800

N.° of fruit bodies

in the 16 experimental plots; 3,131 fruit bodies in 2003 (114 taxa, 54 ECMF and 60 saprobes; Table 3 in Appendix) and 1,750 fruit bodies in 2004 (55 taxa, 31 ECMF and 24 saprobes; Table 3 in Appendix). Overall, 33 families were observed in the 16 experimental plots during the 2-year sampling period; being the families Russulaceae (20 taxa), Agaricaceae (15 taxa), Tricholomataceae (11 taxa), Thelephoraceae (9 taxa) and Amanitaceae (8 taxa) the best represented (see Table 3 in Appendix). These five families contributed with 52% of total taxa observed. Fruiting ECMF fungi comprised 67% of total fruit bodies, represented by 17 genera, mainly members of Russula, Tomentella, Amanita and Lactarius (Table 3 in Appendix). The ECMF Astraeus hygrometricus (Pers.) Morg. and Laccaria laccata (Scop.: Fr.) Berk. & Broome were the most abundant with 1,008 and 721 fruit bodies, respectively, that corresponded to 35% of the total fruiting macromycetes production (Table 3 in Appendix). The saprobic community was represented by 42 genera, mainly members of Clitocybe, Agaricus and Coprinus (Table 3, in Appendix). The families Agaricaceae (13 taxa) and Tricholomataceae (11 taxa) were the best represented, accounting for 57% of the saprobic taxa (Table 3, in Appendix). Fruiting macromycetes community included 16 edible mushroom taxa (50% ECM) that produced up to 23% of total fruit bodies (Table 3, in Appendix). No significant differences were observed on the number of fruit bodies between the 16 plots, in 2003. However, in the second year sampling (after the shrub cutting), significant differences were observed for the four Montado areas on both abundance (F = 7.17, P\ 0.05) and taxa number (F = 6.85, P\0.05). In the first year sampling, the control (C) and the Montado areas with shrub density controlled by cutting practices with no soil tillage (Cu), both with plants with 4–5 years of age and shrub strata occupying 65–75% of total vegetation cover, presented higher values in macromycetes richness and abundance (Table 1; Fig. 3). Lower values in fruit bodies richness and abundance were observed in the plots where shrubs density and growth are cut followed by soil tillage (M) and in the plots where shrub management is conducted by permanent grazing of cattle (Ca), respectively (Table 1; Fig. 3). However, after the removal of understory shrubs in the second year sampling the number of taxa and fruitbodies production decreased all throughout the Cu and M plots (Table 1; Fig. 4).

700

2003 2004

600 500 400 300 200 100 0 C

Cu

Ca

M

Fig. 3 Variation in ectomycorrhizal-forming fungal community abundance as result of current techniques applied to control shrub density in the Montado areas (columns represent the mean and symbols the total abundance of fungal fruit bodies, respectively; abbreviations as in Fig. 2)

Changes in fruitbodies diversity and composition among shrub management practices Multivariate analysis clearly distinguished C and Cu plots from Ca and M plots in 2003 (Fig. 5). Along axis 1 (explaining 37.5% of the community compositional variability) there’s a clear separation between the—at the time—the C and Cu plots, and the Ca and M plots. In that sampling year, the ECMF Laccaria laccata and Xerocomus subtomentosus were closely related with C and Cu plots, whilst the saprobe Entoloma conferendum was associated to Ca plots. In 2004, the analysis performed (Fig. 6) separated the four areas along Axis 1 (explaining 43.4% of the

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Agroforest Syst

1.0

Saprobes 500

Sco

M

2003 2004

N.° of fruit bodies

400

2003 2004

300

Gsp

200 Aph Boa Cge Hci Lau Lch Lla

100

0

C C

Cu

Ca

Lqu Lpe Mme Pez Rcy Rfo

M Xsu Mqu Rfi

Fig. 4 Variation in saprobic fungi community abundance as result of land use practices to control shrub density in the Montado areas (columns represent the mean and symbols the total abundance of fungal fruit bodies, respectively; abbreviations as in Fig. 2)

Tve

Iri Ahy

Cu

Xhy Eco Mpr Bae Cpu

0.8

Cru Pca

Man

-0.6

Pve

Ca

Lmo Pba

-0.4

Gsp Fve Cfr Lmo Cru Cpu Cph Cpi Cge Pba Eco Cpl Aca

Ca

Fig. 6 Correspondence analysis using the four experimental areas as dummy variables for fruit bodies data collected in 2004 (abbreviations of experimental areas as in Fig. 2; see the codes in Table 3 in Appendix)

Tbi

Soil macrofauna

M

Xsu Ahy Iri Mqu Hci Lpe

Cu

Abundance and biodiversity descriptors

Lla Lvo Rso

C

Tat Lch

Aph Ava Bas Ctr Lau Mme Pez Rfi

Ram Rcy Rde Rfe Rkr Rua Rfo Rfr

Ame Bpl

Pse

Pan

-0.6

Cmi

-0.2

1.0

Fig. 5 Correspondence analysis using the four experimental areas as dummy variables for fruit bodies data collected in 2003 (abbreviations of experimental areas as in Fig. 2; see the codes in Table 3 in Appendix)

community compositional variability), from the C plots to the M plots. Most taxa associated to C and Cu plots before the cutting practices occurred in the C plots but no longer in the Cu plots in 2004.

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0.8

Regarding soil macrofauna, 3,667 individuals were caught in the traps: 1,799 individuals (53 species and morphospecies) in 2003 and 1,868 individuals (34 species and morphospecies) in 2004. Shrub management techniques did affect significantly both the abundance (F = 4.82, P \ 0.05 for 2003 and F = 13.27, P\0.05) and the number of taxa observed per plot (F = 4.79, P\0.05 in 2003 and F = 7.87, P\0.05 in 2004). C and Cu plots presented the highest species richness in 2003, followed by the M and Ca plots (Table 2). In 2004, a decrease in species richness and abundance was observed in all plots (with the exception of Ca plot). However no significant differences were noticed in species diversity (Shannon) from one year to the other. In the second year of sampling, higher values of taxa abundance and species richness were observed in the M and Ca plots.

Agroforest Syst Table 2 Soil macrofauna abundance and diversity descriptors 2003

2004 H0

Individuals S C

372

D

38 2.59

Individuals S

H0

D

6.59

132

20 2.34

5.54

Cu 519

41 3.01 13.95

132

19 2.6

11.65

Ca 242

29 2.77 12.01 1182

24 1.1

1.66

M 666

33 2.44

27 2.21

4.69

6.76

420

Abbreviations as in Table 1

Changes in community composition among shrub management practices

1.0

Multivariate analysis separated the plots with shrub cut with machinery intervention followed by soil tillage (M) from the remaining plots in 2003 (Fig. 7). Along axis 1 (explaining 51.8% of the community compositional variability) there’s a clear separation between the M plots and the other plots, whilst Axis 2 (explaining 27.2% of the community compositional variability) separates the Ca plots from the other two shrub control techniques and C plots; using both axes, three different groups were observed—one with the, at the time, undisturbed stands (Cu and C), another with the Ca plots and the third one regarding the M plots. An

ANOSIM (Global R = 0.839, P \ 0.01) corroborated the differences in community composition observed and the pairwise tests performed revealed significant differences between all plots (P \ 0.001 for every comparison made). In this first sampling period, ant species Aphaenogaster senilis and several Staphylinid morphospecies were closely related to the M plots, whilst most of spider families were associated to less disturbed areas (Cu and C plots). In the second year of sampling, the Principal Component Analysis performed (Fig. 8) clearly separated Ca and M plots from the remaining two stands along Axis 1 (explaining 72.6% of the speciesenvironment relation). Differences in community composition among areas were evaluated with an ANOSIM (Global R = 0.587, P \ 0.01), which corroborated the differences observed. Pairwise tests revealed significant differences between all stands (P \ 0.001 for every comparison made), confirming that, even though C and Cu plots appear to be closer on the Principal Component Analysis, there were four different groups corresponding to the four plots in the study. In the second year of sampling, ant species Aphaenogaster senilis was still closely related to the M plots as well as Staphylinid morphospecies and most Coleoptera. Species from some spider families, like Lycosidae, and Thomisidae, were more related to the M and Ca plots.

Scy

Lc10

Cu

Gna

Dip Gr2 Gr1

Lc13

Clg

Csc

Has Mtr

Lc1 Pnt

Ppy Ta1

Ppy

Xa4

Or1 Iso Cau Cam Mss Ld1 Chi Xys Col Opi Nem Cur Al1 Cre Tes Or2 Hcl Or4 Ox2

C

Stg

OI1 Hym

Typ St1

1.0

Ppa

Lin Mst

Mhi

Zel

Zoa

St9 Ase

Ox2

Aib

OI2

C

Ap1

Stg St6

Cu

Ld1 Pah Zor

Ppa

Agi

Csc

Fsa

Agi Ths Mei Ox1

Lin Bub

Pti

Sil

Gas

Ara St9 Ap5

Lc15 Las

Lc21

Ozp Ala

Ase

M -1.1

Ca

-1.0

Lc7

Tet OI4 Aib

Ox1

-1.0

Ca

Cha

M

Pti

1.0

Fig. 7 Correspondence analysis using the four experimental areas as dummy variables for soil macrofauna data collected in 2003 (abbreviations of experimental areas as in Fig. 2; fauna codes are present in Table 4 in Appendix)

-1.0

1.5

Fig. 8 Correspondence analysis using the four experimental areas as dummy variables for soil macrofauna data collected in 2004 (abbreviations of experimental areas as in Fig. 2; fauna codes are present in Table 4 in Appendix)

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Discussion In this work we assessed soil macromycetes and macrofauna diversity descriptors in Montado landscape to evaluate the influence of land use practices to control shrub density on soil biodiversity. Our study revealed that shrub management influences the species richness and abundance of fruiting macromycetes and soil macrofauna. Our results demonstrated that Montado’s under extensive silvopastoral exploitation comprise high taxonomical diversity in fruiting macromycetes. Other studies documented higher diversity in ECMF community in old-growth forests dominated by Quercus ilex L. (Richard et al. 2004) and coniferous (O’Dell et al. 1999; Peter et al. 2001; Fernańdez-Toirań et al. 2006). The lower values in ECMF diversity may be explained by our monitoring study limited to 2-years’ period. Richard et al. (2004) showed that in a Q. ilex old-growth forest fruiting macromycetes patterns was remarkably irregular, with 61.4% of the ECMF taxa occurring one time during 3-years’ period. On contrary, the saprobic community in Montado landscape (S = 64; Table 3 in Appendix) was identical to the oldgrowth Q. ilex forest (S = 68; Richard et al. 2004). This may be explained by the differential responses of ECMF and saprobes to land use practices, and the relatively low accumulation of favorable substrates to decomposers. Also phenological patterns and physical parameters, such climatic conditions are well known to influence fungi fructification. The family Russulaceae covered 16.5% of the fruiting fruit bodies diversity (and 35% of ECMF). A comparable tendency for the dominance of Russulaceae species was observed belowground in Montado landscape (Azul 2002; Azul et al. 2010). The dominance of Russulaceae above- and below-ground was reported in Mediterranean (Bergemann and Garbelotto 2006; Courty et al. 2008; Richard et al. 2004, 2005) and Temperate forests (Lilleskov et al. 2004; Tedersoo et al. 2003), and it may be explained by the fact that this ECMF family comprises a large range of species and high diverse ecological requirements. The taxonomical diversity and cosmopolitan distribution within Russulaceae further impose a better understanding of the putative role of these mutualist fungi in soil processes in mediterranean ecosystems, e.g., stabilization following disturbance (Costa et al. 2009; Pinto-Correia 1993), drought stress (European

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Environment Agency 2004) and/or diseases (Brasier and Scott 2008). Disturbances caused by cutting practices have been showed to have significant impacts in the ECMF community diversity and composition (Byrd et al. 2000; Hagerman et al. 1999; Smith et al. 2005). It is expected that the removal of understory vegetation affect the ECM fungal community (Azul 2002; Azul et al. 2010) with costs to the sporocarps production. In our study, most of the ECMF taxa associated to cutting practices with no soil tillage (Cu) plots were present in the control (C) plots during the 2-years’ period, but not in Cu after the shrub cutting practices were performed (2004), indicating that ectomycorrhizal macrofungal composition and fungal networks are indubitably affected by shrub management. The ECMF L. laccata and X. subtomentosus were closely related with less disturbed plots (C and Cu in 2003; C in 2004) while the saprobes were associated to Ca and M plots. This corroborates the hypothesis that land use practices allowing for autochthonous shrubs preservation, such as Cistus spp., are important to sustain ECMF diversity. However, the direct effects of shrub control techniques in the specific mycobiont–phytobiont associations and the activity of the interacting mycelial systems of ECMF and saprobes and soil moisture conditions remain poorly understood but are extremely important in scenarios of drought-climate change and oak mortality. Cattle husbandry represents the second profitable activity in Montado areas in study. Our results revealed that cattle grazing were rather efficient to control shrub density and growth. Nevertheless, caution in the interpretation of these results is recommended since perceptible effects on fruitbodies production and diversity were found, particularly on ECMF community (cumulative richness of ECMF taxa in C plots was 3 times higher than in Ca plots). Cattle grazing even with restricted number of individuals imply multiple ecological consequences related to the plant species responses to herbivory (Ayres et al. 2004) and to the nitrogen inputs provided by animals (Avis et al. 2003; Edwards et al. 2004; Trudell et al. 2004), and may directly affect the sporocarp production. The use of heavy machinery and livestock are also known to cause soil compaction, affecting soil water content and plant growth (Hamza and Anderson 2005). Our results call for further investigations to

Agroforest Syst

evaluate the implications of livestock and nitrogen inputs on ECMF community fruiting patterns. Regarding soil macrofauna overall analysis showed that different scenarios of shrub management cause effects in soil macrofauna communities. The changes observed were not only in terms of species richness and abundance but also in terms of community composition. Understory vegetation management appears to be one of the factors causing a community composition shift (from 2003 to 2004), and its effect combined with the mobilization of the soil induce a more significant effect than the shrub cut alone. It is known that certain groups (or species within them), like Formicidae, Coleoptera or Araneae tend to respond to changes in the structure of their habitat, especially when its architecture is one of the factors changing (Grill et al. 2005; Retana and Cerda´ 2000). Our results are in agreement with previous studies, that showed that some groups, like ants, exhibit a positive relation with the percentage of vegetation cover in Mediterranean systems (Retana and Cerda´ 2000). Other groups, like spiders, show a good correlation with the management intensity (Perner and Malt 2003) and its richness is strongly and negatively affected by an intensification of management. The structure of the surrounding vegetation is also an important factor when it comes to spiders (Grill et al. 2005; McAdam et al. 2007; New 2005)—web-building and active ground predator spiders are closely related with a well structured understory vegetation cover (Cu plots in 2003; C plots in 2003 and 2004), but species recognized as colonizers (like some from Thomisidae family) are more associated with more open areas and, therefore, are more associated with the Cu plots in 2004 and M and Ca plots in the 2-years period. Coleoptera families appeared to be associated to areas where intensive management was adopted (soil mobilization and cattle ranching). This is in agreement with the findings of Vanbergen et al. (2005), who showed the preference of some Coleoptera families for open areas. In the case of Scarabaeidae our results agree with Verdu´ et al. (2007) that reported the strong association of this group with grazed areas. Although, in the second year of sampling, the highest values for species richness were observed in the M and Ca plots, this may have been an effect of opportunistic species, which were able to colonize the areas with new habitat configuration resulting from the management intervention. Some species (namely Aphaenogaster iberica, Aphaenogaster

senillis, Crematogaster scutellaris and Staphylinidae morphospecies 9) have very high abundances in the M and Ca plots; these taxa are known to be among the opportunistic fauna (Andersen and Sparling 1997; da Silva et al. 2009; Dauber and Wolters 2005; Thorbek and Bilde 2004), which take advantage of severe changes that lead to the ‘‘disappearance’’ of dominant taxa in an ecosystem after a disturbance (like shrub cut or tillage); in the absence of competition from these formerly dominant groups, opportunistic fauna uses its ability to colonize the area that now presents different features. Overall, our study revealed that a considerable variation in soil biodiversity in Montado ecosystems is explained by the current practices used to control shrub density. This variation in soil biodiversity was observed in terms of species richness and abundance but also in community’s composition of both fruiting macromycetes and soil macrofauna. Our results showed that shrub management based on cutting practices without soil tillage revealed to be less severe when comparing with permanent grazing or shrub management with tillage of soil afterwards. Although results cannot be generalized for other forestry ecosystems, fruiting macromycetes and soil macrofauna were measurable and reproducible in Montado’s, also to be sensitive indicators of soil components population’s vulnerability use, and somewhat reflected a trend of severity, to the current techniques used to control shrub density. We believe that fruiting macromycetes and soil macrofauna may be useful indicators and extremely important tools for explaining the ecological impacts of land use in forestry ecosystems. Our results imply further studies to understand the impacts of these soil biodiversity changes regarding their role in ecosystems functions and the plant physiological response to major aspects of cork oak sustainability in future: production and health. Acknowledgments Financial support was provided by FCTMCTES (Portuguese Foundation for Science and Technology) and European fund FEDER, project POCTI/AGG/42349/2001. AM Azul was supported by an individual grant from FCTMCTES (SFRH7BPD/5560/2001).

Appendix See Appendix Tables 3 and 4.

123

123 Amanitaceae Amanitaceae Amanitaceae

Amanita muscaria (L.) Lam.

Amanita pantherina (DC.) Krombh.

Amanita phalloides (Vaill. ex Fr.) Link

ECMF

ECMF

ECMF

ECMF

Broad HR Broad HR

Broad HR

Tricholomataceae Edible Saprobe – Tricholomataceae Edible Saprobe – Tricholomataceae Edible Saprobe – Tricholomataceae –

Edible Saprobe –

Agaricaceae Tricholomataceae –

–

Agaricaceae

Marasmiaceae Bolbitiaceae Bolbitiaceae Agaricaceae Agaricaceae Agaricaceae

Bovista plumbea Pers.

Clitocybe fragans (With.) P. Kumm. Clitocybe geotropa (Bull.: Fr.) Que´l.

Clitocybe gibba (Pers.) Kumm.

Clitocybe phaeophthalma (Pers.) Kuyper

Clitocybe squamulosa (Pers.) Fr.

Collybia butyracea (Bull ex Fr.) Quel.

Conocybe pubescens (Gill.) Kuhn.

Conocybe rubiginosa Watling Coprinus comatus (O.F. Mu¨ll.) Pers.

Coprinus domesticus (Bolt.: Fr) S.F. Gray Coprinus micaceous (Bull.) Fr.

– –

–

–

–

–

Broad HR

Broad HR

Saprobe – Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

ECMF

ECMF

Thermophilic

Bovista aestivalis (Bonord.) Demoulin

ECMF

Broad HR

Edible ECMF

Boletus satanas Lenz

–

Boletaceae Boletaceae

Boletus edulis Bull.

– Saprobe – Edible ECMF Thermophilic

Saprobe –

ECMF

ECMF

Broad HR

Broad HR

Broad HR

Broad HR

Thermophilic

Broad HR

Bisporella citrina (Batsch) Korf and S.E. Carp. Helotiales Boletus aereus Bull. Boletaceae

–

–

Edible ECMF

–

–

–

–

Auriculariaceae

Amanitaceae

Amanita franchetii (Boud.) Fayod

ECMF

Saprobe –

Edible ECMF

Diplocystidiaceae –

Amanitaceae

Amanita caesarea (Scop.) Pers.

–

–

Auricularia mesenterica (Dicks.) Pers.

Amanitaceae

Amanita battarrae (Boud.) Bon

Astraeus hygrometricus (Pers.) Morg.

Agaricaceae

Agaricus xanthodermus Genev.

Edible Saprobe –

Amanitaceae

Agaricaceae

Agaricus silvicola (Vittad.) Peck

Saprobe –

Host range

Edible Saprobe –

–

Amanitaceae

Agaricaceae

Agaricus campestris L.: Fr.

Amanita vaginata (Bull.) Lam.

Agaricaceae

Agaricus augustus Fr.

Edible Habit

Amanita rubescens Pers

Family

Taxon

4 1 (3, 0)

3 1 (2, 0)

35 1 (4, 0)

1 1 (1, 0)

1 1 (1, 0)

0 0 (0)

0 0 (0)

6 1 (3, 0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

FR

A

FR

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

Ca

0 0 (0) 0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

1 1 (1, 0)

66 2 (1, 3)

0 0 (0)

0 0 (0)

11 1 (2, 0)

1 1 (0, 1)

2 2 (1, 1)

1 1 (1, 0) 14 2 (2, 3)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0) 0 0 (0)

0 0 (0)

9 1 (1, 0) 0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

1 1 (1, 0)

0 0 (0)

0 0 (0)

43 1 (2, 0)

0 0 (0)

0 0 (0)

FR

CD

Ahy

Ava

Aru

Aph

Apa

Amu

Afr

Ace

Aba

Bae

Bsa

Bed

Bic Boa

0 0 (0)

Cfr

10 1 (2, 0) Bpl

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0) 0 0 (0)

12 1 (2, 0) Ame

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

1 1 (1, 0) Axa

3 1 (1, 0) Asi

9 1 (1, 0) Aca

2 1 (1, 0) Aau

A

M

0 0 (0) 0 0 (0)

0 0 (0)

30 2 (3, 2)

17 2 (3, 1)

0 0 (0)

0 0 (0)

37 1 (2, 0)

0 0 (0)

Cph

Cru

Cpu

0 1 (0) Cdo 14 1 (1, 0) Cmi

4 1 (1, 0) Cco

0 0 (0)

0 0 (0)

1 1 (1, 0) Cbu

2 1 (1, 0) Csq

0 1 (0)

1 1 (1, 0) Cgi

22 1 (4, 0) 13 1 (2, 0) Cge

14 1 (3, 0)

0 0 (0)

17 2 (3, 2) 102 1 (0, 3)

0 0 (0)

0 0 (0)

0 0 (0) 0 0 (0)

1 1 (1, 0)

241 2 (3, 3) 531 2 (3, 4) 236 2 (3, 1)

5 1 (4, 0)

0 0 (0)

20 2 (4, 3)

0 0 (0)

2 1 (0, 2)

1 1 (1, 0)

5 2 (2, 3)

7 2 (3, 3)

0 0 (0)

1 1 (1, 0)

0 0 (0)

0 0 (0)

A

A

FR

Cu

C

Table 3 List of taxa in the four experimental stands and information related to their fruiting pattern during the period 2003–2004

Agroforest Syst

Strophariaceae Strophariaceae

Gymnopilus spectabilis (Fr.) Sing.

Auriscalpiaceae Agaricaceae Tricholomataceae Tricholomataceae Agaricaceae Agaricaceae Agaricaceae Marasmiaceae Marasmiaceae

Lepiota josserandii Bon and Boiffard

Lepista nuda (Schumach.) Sing.

Lepista sordida (Schumach.) Sing.

Lycoperdon molle Pers.

Lycoperdon perlatum Pers.

Macrolepiota procera (Scop.) Sing.

Marasmius androsaceus (L.) Fr. Marasmius quercophilus Pouz.

Russulaceae

Lactarius volemus (Fr.) Fr.

Lentinellus cochleatus (Pers.) P. Karst.

Russulaceae Russulaceae

Lactarius quietus (Fr.) Fr.

Russulaceae

Lactarius aurantiacus (Pers.) Gray

Lactarius chrysorrheus Fr.

Tricholomataceae Russulaceae

Lactarius atlanticus Bon

Hymenochaetaceae – Inocybaceae –

Hymenochaete rubiginosa (Dicks.) Le´v. Inocybe rimosa (Bul.) P. Kumm.

Laccaria laccata (Scop.) Cke.

Hygrophoraceae

Hygrocybe conica (Scop.) P. Kumm.

–

Hebeloma sp.1

Saprobe –

–

–

ECMF

ECMF

ECMF

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Quercus sp

Quercus sp

Quercus sp

Broad HR

Broad HR

Broad HR

Saprobe – ECMF Broad HR ECMF

0 0 (0)

1 1 (1, 0)

0 0 (0)

0 0 (0)

2 1 (1, 0)

0 0 (0)

0 0 (0)

96 1 (4, 0)

1 1 (1, 0)

0 0 (0)

0 0 (0)

FR

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

12 1 (2, 0)

0 0 (0)

11 1 (2, 0)

5 2 (3, 1)

A

A

FR

Cu

C

Edible Saprobe – – Saprobe –

0 0 (0) 112 2 (1, 3)

5 1 (0, 4)

14 2 (3, 2)

0 0 (0)

0 0 (0)

0 0 (0)

1 1 (1, 0)

0 0 (0)

7 1 (4, 0)

16 1 (0, 3)

39 2 (4, 2)

41 2 (2, 3)

0 0 (0)

640 2 (3, 4)

0 0 (0) 7 2 (2, 3)

0 0 (0)

5 2 (2, 1)

0 0 (0) 31 2 (2, 3)

1 1 (0, 1)

11 1 (3, 0)

0 0 (0)

4 1 ()

0 0 (0)

0 0 (0)

0 0 (0)

14 1 (4, 0)

0 0 (0)

0 0 (0)

23 1 (4, 0)

0 0 (0)

50 1 (3, 0)

0 0 (0) 53 2 (3, 4)

0 0 (0)

0 0 (0)

Cistus specific 210 2 (2, 3) 113 1 (2, 0)

Saprobe –

ECMF

ECMF

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Edible Saprobe –

–

–

–

–

–

Angiosperms

Broad HR

Saprobe –

ECMF

ECMF

Edible ECMF

–

–

–

–

Host range

Saprobe –

Edible ECMF

–

–

Strophariaceae Strophariaceae

Hebeloma cistophilum Mre.

–

–

–

Ganodermataceae

Gymnopilus penetrans (Fr.) Murrill

–

Ganoderma applanatum (Pers.) Pat.

Crepidotus variabilis (Pers.) Kumm.

–

–

–

Inocybaceae

Crepidotus mollis (Bull ex Fr.) Kum.

Physalacriaceae

Inocybaceae

Cortinarius trivialis Lge.

–

Flammulina velutipes (Curt.) Sing.

Cortinariaceae

Cortinarius amoenolens Henry ex Orton

– –

–

Cortinariaceae

Coprinus plicatilis (Curt.) Fr.

Edible Habit

Entoloma conferendum (Britzelm.) Noordel. Entolomataceae

Agaricaceae Agaricaceae

Coprinus picaceus (Bull.) Fr.

Family

Taxon

Table 3 continued

FR

FR

CD

Ctr

Cam

Cpl

Cva Fve 0 0 (0)

Gpe

1 1 (1, 0) Gap

0 0 (0)

4 1 (0, 1) Eco

0 0 (0)

1 1 (1, 0) Cmo

0 1 (0)

0 1 (0)

0 1 (0)

2 1 (1, 0) Cpi

A

M

He1

Hci

0 0 (0) Hru 1 1 (1, 0) Iri

2 1 (1, 0) Hco

0 1 (0)

0 0 (0)

0 0 (0) 0 0 (0)

30 1 (0, 3)

4 1 (2, 0)

50 2 (2, 3)

0 0 (0)

1 1 (0, 1)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

3 1 (3, 0)

Lau

Lat

Lqu

Lmo

Lso

Lnu

Ljo

17 1 (1, 0) Man 60 1 (1, 0) Mqu

3 1 (3, 0) Mpr

1 1 (1, 0) Lpe

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

1 1 (1, 0) Lco

1 1 (1, 0) Lvo

0 1 (0)

1 1 (1, 0) Lch

0 0 (0)

0 0 (0)

13 1 (1, 0) 18 1 (1, 0) Lla

2 1 (1, 0) 8 1 (3, 0)

0 0 (0)

0 0 (0)

8 1 (1, 0)

72 2 (1, 1) 14 1 (0, 1) Gsp

0 0 (0)

0 0 (0)

23 1 (1, 0)

284 2 (4, 2)

1 1 (1, 0)

0 0 (0)

0 0 (0)

0 0 (0)

34 1 (3, 0)

14 2 (4, 2)

A

Ca

Agroforest Syst

123

123 Saprobe – Saprobe –

– –

– – – –

Tricholomataceae Meripilaceae Mycenaceae Hygrophoraceae Marasmiaceae Strophariaceae

Psathyrellaceae Pezizaceae Pezizaceae Phanerochaetaceae – Sclerodermataceae – Polyporaceae Phanerochaetaceae – Agaricomycete Russulaceae Russulaceae Russulaceae Russulaceae Russulaceae Russulaceae Russulaceae Russulaceae Russulaceae Russulaceae Russulaceae Russulaceae

Omphalina sp.

Omphalotus olearius (DC.) Sing.

Panaeolus antillarum (Fr.) Dennis

Panaeolus semiovatus (Sow.) Lundell and Nannf. Strophariaceae Panaeolus sphinctrinus (Fr.) Que´l. Strophariaceae Psathyrellaceae

Meripilus giganteus (Pers.) P. Karst. Mycena inclinata (Fr.) Que´l.

Psathyrella velutina (Pers. ex Fr.) Sing.

Psathyrella candolleana (Fr.: Fr.)

Peziza sp.

Peziza badia Pers.: Fr.

Phanerochaete sanguinea (Fr.) Pouzar Pisolithus arhizus (Scop.) Rauschert.

Polyporus arcularius (Batsch.) Fr.

Pulcherricium caeruleum (Schrad.) Parm.

Rickenella fibula (Bull.) Raithel.

Russula sp. 1

Russula sp. 2

Russula sp. 3

Russula sp. 4

Russula amoena Que´l.

Russula amoenolens Romagn.

Russula cyanoxantha (Shaeff.) Fr.

Russula delica Fr.

Russula fellea (Fr.) Fr.

Russula foetens (Pers.) Pers.

Russula fragilis Fr. Russula krombholzii Shaeff.

– –

–

–

–

Broad HR

Broad HR

ECMF

ECMF

ECMF

ECMF

ECMF

ECMF

ECMF ECMF

ECMF

ECMF

ECMF

Broad HR Broad HR

Broad HR

Broad HR

Broad HR

Broad HR

Broad HR

Broad HR

–

–

–

–

Saprobe –

Saprobe –

Saprobe –

Saprobe – ECMF Broad HR

ECMF

ECMF

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Edible ECMF

–

–

–

–

–

–

–

–

–

–

–

–

–

–

Saprobe – Saprobe –

Melanoleuca melanoleuca (Pers.) Murr.

– –

Marasmiaceae Tricholomataceae

4 1 (1, 0)

2 1 (0, 1)

0 0 (0) 0 0 (0)

0 0 (0)

16 1 (2, 0)

1 1 (1, 0)

0 0 (0)

3 1 (2, 0)

5 2 (1, 1)

3 1 (2, 0)

11 1 (4, 0) 2 1 (0, 2) 21 1 (3, 0) 25 1 (3, 0)

78 2 (3, 4)

20 1 (3, 0)

26 1 (4, 0)

86 2 (4, 3) 24 1 (4, 0)

78 1 (4, 0) 32 1 (4, 0)

0 0 (0)

0 0 (0)

5 1 (2, 0)

4 1 (3, 0) 16 1 (3, 0)

1 1 (1, 0)

FR

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

1 1 (1, 0)

0 0 ()

1 1 (1, 0)

0 0 (0)

A

Ca

0 0 (0) 0 0 (0)

0 0 (0)

3 1 (3, 0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0) 0 0 (0)

2 1 (1, 0) 26 2 (2, 1)

4 1 (1, 0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

24 1 (1, 0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

FR

53 2 (3, 3) 50 2 (3, 4)

5 2 (1, 2)

0 0 (0)

0 0 (0) 1 1 (1, 0)

0 0 (0)

21 2 (1, 1)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

34 2 (1, 1)

22 2 (1, 1)

0 0 (0)

0 0 (0)

27 2 (3, 2)

0 0 (0)

1 1 (1, 0)

A

A

FR

Cu

Host range C

Melanoleuca brevipes (Bull.) Pat.

Edible Habit

Megacollybia platyphylla (Pers.) Kotl. and Pouz.

Family

Taxon

Table 3 continued

FR

Ool

Omp

Min

Mgi

Mme

Mbr

Mpl

CD

Pba

Pez

0 0 (0) 0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

Rfr Rkr

Rfo

Rfe

Rde

Rcy

Rua

Ram

Ru4

Ru3

Ru2

Ru1

Rfi

Puc

Poa

1 1 (1, 0) Psa 1 1 (1, 0) Par

0 0 (0)

0 0 (0)

17 1 (1, 0) Pca

21 1 (1, 0) Pve

2 1 (1, 0) Psp

43 1 (2, 0) Pse

14 1 (1, 0) Pan

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 1 (0)

A

M

Agroforest Syst

ECMF ECMF

– – –

– –

Stereaceae Stereaceae Thelephoraceae

Thelephoraceae Thelephoraceae Thelephoraceae Thelephoraceae Thelephoraceae Thelephoraceae Polyporaceae Polyporaceae Tremellaceae Tremellaceae Tremellaceae Polyporaceae Tricholomataceae Pluteaceae Boletaceae Boletaceae Xylariaceae

Stereum reflexum D. A. Reid

Tomentella atramentaria Rost., Bot. Tidsskr.

Tomentella brevispina (Bourd. and Galz.) M.J. Lar. Thelephoraceae Thelephoraceae

Stereum hirsutum (Wild.) Pers.

Tomentella sublilacina Ellis and Holw.) Wakef.

Tomentella subtestacea Bourdot and Galin, Bull.

Tomentella stuposa (Link) Stalpers

Tomentella sp1

Tomentella sp2 Tomentella sp3

Tomentella sp4

Trametes hirsuta (Wulf.) Lloyd

Trametes versicolor (L.) Lloyd

Tremella encephala Pers.

Tremella foliacea Pers.

Tremella mesenterica Retz.

Trichaptum biforme (Fr.) Ryvarden

Tricholoma sulphurum (Bull.) P. Kumm.

Volvariella speciosa (Fr.) Sing.

Xerocomus chrysenteron (Bull.) Que´l. Xerocomus subtomentosus (L.) Que´l.

Xylaria hypoxylon (L.) Grev.

Thermophilic

Broad HR

–

– –

–

Broad HR

Broad HR

Broad HR

Broad HR

Broad HR

Broad HR

Broad HR

Broad HR Saprobe –

ECMF

ECMF

Saprobe –

ECMF

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

Saprobe –

ECMF

ECMF ECMF

ECMF

ECMF

ECMF

ECMF

ECMF

ECMF

Saprobe –

Saprobe –

ECMF

ECMF

Saprobe –

Broad HR

Broad HR

Broad HR

Host range

0 0 (0)

FR

0 0 (0)

14 2 (1, 4)

3 1 (0, 1)

0 0 (0)

2 1 (0, 1)

0 0 (0)

1 1 (1, 0)

1 1 (1, 0)

0 0 (0)

2 1 (2, 0)

0 0 (0)

0 0 (0)

0 0 (0) 0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

2 1 (2, 0)

5 1 (3, 0)

0 0 (0)

0 0 (0)

1 1 (1, 0)

6 1 (3, 0)

FR

0 0 (0)

0 0 (0)

0 0 (0) 0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

A

Ca

51 2 (1, 2)

3 1 (2, 0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

4 2 (1, 1)

6 2 (1, 2)

FR Roc

CD

Rxe

Spo

Sci

Sre Tbr

To4

To2 To3

To1

Tst

Tos

Tsu

Tfo

Ten 2 1 (0, 1) Tme

0 0 (0)

0 0 (0)

6 1 (0, 2) Tve

1 1 (1, 0) Thi

0 0 (0)

0 0 (0) 0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 0 (0)

0 1 (0)

1 1 (1, 0) Tat

0 0 (0)

4 1 (0, 2) Shi

0 0 (0)

0 0 (0)

6 1 (0, 3) Sco

0 0 (0)

4 1 (2, 0) Rso

0 0 (0)

A

M

0 0 (0)

5 2 (2, 3)

0 0 (0)

0 0 (0)

0 0 (0)

Tsu

0 0 (0)

0 0 (0)

0 0 (0)

Xhy

Xsu

Xch

1 1 (1, 0) Vsp

0 0 (0)

10 1 (1, 0) 25 1 (3, 0) Tbi

0 0 (0)

0 0 (0)

0 0 (0)

6 2 (1, 2) 12 1 (0, 3)

0 0 (0)

1 1 (0, 1)

1 1 (1, 0) 3 1 (3, 0)

1 1 (1, 0)

3 2 (2,1)

2 2 (1, 1)

2 2 (1, 1)

2 2 (1, 1)

7 2 (3, 1)

0 0 (0)

4 1 (1, 0)

1 1 (1, 0)

1 1 (1, 0)

0 0 (0)

6 1 (2, 0)

43 1 (4, 0) 23 1 (2, 0)

1 1 (1, 0)

A

A

FR

Cu

C

A fruitbody abundance determined as the number of the specimens over the two fruiting seasons in the 16 experimental plots, FR fruiting regularity determined as the number of seasons of fruitbodies occurrence, with the the total number of plots occupied in each fruiting season given in parenthesis, CD codes used in multivariate analysis

–

–

–

–

–

–

–

–

–

–

– –

–

–

–

–

–

Sclerodermataceae –

Scleroderma polyrhizum (J.F. Gmel.) Pers.

–

Schizophyllaceae

Edible ECMF

Sclerodermataceae –

Russula xerampelina (Schaeff.) Fr.

– –

Scleroderma citrinum Pers.

Russulaceae

Russula sororia (Fr.) Romagn

Edible Habit

Schizophyllum commune (L.) Fr.

Russulaceae Russulaceae

Russula ochroleuca (Pers.) Fr.

Family

Taxon

Table 3 continued

Agroforest Syst

123

Agroforest Syst Table 4 List of soil macrofauna taxa collected in the study Taxon (Species/morphospecies)

Order (sub-order)

Family (sub-family)

FC

Aphaenogaster gibbosa (Latreille, 1798)

Hymenoptera (Apocrita)

Formicidae (Myrmicinae)

Agi

Aphaenogaster iberica Emery, 1908



Aib

Aleocharinae morphospecies 1 Alopecosa albofasciata (Brulle´, 1832)

Coleoptera Araneae

Staphylinidae (Aleocharinae) Lycosidae

Al1 Ala

Aphidinae morphospecies 1

Hemiptera

Aphididae (Aphidinae)

Ap1

Aphidinae morphospecies 5

Hemiptera

Aphididae (Aphidinae)

Ap5

Araneae morphospecies 1

Araneae

n.d.

Ara

Aphaenogaster senilis Mayr, 1853



Ase

Bubas morphospecies 1

Coleoptera

Scarabaeidae

Bub

Camponotus morphospecies 1


Formicidae (Formicinae)

Cam

Crematogaster auberti Emery, 1869



Cau

Chasmatopterus morphospecies 1

Coleoptera

Scarabaeidae

Cha

Chilopoda morphospecies 1

Chilopoda

n.d.

Chi

Calathus granatensis Vuillefroy, 1866

Coleoptera

Carabidae

Clg

Coleoptera morphospecies 1

Coleoptera

n.d.

Col

Crematogaster morphospecies 1



Cre

Crematogaster scutellaris (Olivier, 1792)



Csc

Curculionidae morphospecies 1

Coleoptera

Curculionidae

Cur

Diplopoda morphospecies 1 Formica sanguinea Latreille, 1798

Diplopoda Hymenoptera (Apocrita)

n.d. Formicidae (Formicinae)

Dip Fsa

Gastropoda morphospecies 1

Gastropoda

n.d.

Gas

Gnaphosidae morphospecies 1

Araneae

Gnaphosidae

Gna

Gryllidae morphospecies 1

Orthoptera (Ensifera)

n.d.

Gr1

Gryllidae morphospecies 2

Orthoptera (Ensifera)

n.d.

Gr2

Hahnia morphospecies 1

Araneae

Hahniidae

Has

Carabus (Hadrocarabus) lusitanicus (Fabricius, 1801)

Coleoptera

Carabidae

Hcl

Hymenoptera morphospecies 1


n.d.

Hym

Isopoda morphospecies 1

Isopoda

n.d.

Iso

Lasius morphospecies 1



Las

Coleoptera larvae morphospecies 1

Coleoptera

n.d.

Lc1


Coleoptera

n.d.

Lc10


Coleoptera

n.d.

Lc13


Coleoptera

n.d.

Lc15

Coleoptera larvae morphospecies 21 Coleoptera larvae morphospecies 7

Coleoptera Coleoptera

n.d. n.d.

Lc21 Lc7 Ld1

Diptera larvae morphospecies 1

Diptera

n.d.

Linyphiidae morphospecies 1

Araneae

Linyphiidae

Lin

Meioneta pseudorurestris (Wunderlich, 1980)

Araneae

Linyphiidae

Mei

Messor hispanicus Santschi, 1919



Mhi

Messor morphospecies 1



Mss

Messor structor (Latreille, 1798)



Mst

Carabus (Macrothorax) rugosus Fabricius, 1792

Coleoptera

Carabidae

Mtr

Nemesia morphospecies 1

Araneae

Nemesidae

Nem

Caelifera morphospecies 68

Orthoptera (Caelifera)

n.d.

OI1



n.d.

OI4

123

Agroforest Syst Table 4 continued Taxon (Species/morphospecies)

Order (sub-order)

Family (sub-family)

FC

Opiliones morphospecies 1

Opiliones

n.d.

Opi



n.d.

Or1

Caelifera morphospecies 2 Caelifera morphospecies 4

Orthoptera (Caelifera) Orthoptera (Caelifera)

n.d. n.d.

Or2 Or4

Oxytelinae morphospecies 1

Coleoptera

Staphylinidae (Oxytelinae)

Ox1

Oxytelinae morphospecies 2

Coleoptera

Staphylinidae (Oxytelinae)

Ox2

Ozyptila pauxilla (Simon, 1870)

Araneae

Thomisidae

Ozp

Pardosa hortensis (Thorell, 1872)

Araneae

Lycosidae

Pah

Laemostenus (Pristonychus) terricola (Herbst, 1784)

Coleoptera

Carabidae

Pnt

Pheidole pallidula (Nylander, 1849)



Ppa

Plagiolepis pygmaea (Latreille, 1798)



Ppy

Ptinidae morphospecies 1

Coleoptera

Ptinidae

Pti

Scydmaenidae morphospecies 1

Coleoptera

Scydmaenidae

Scy

Silvanidae morphospecies 1

Coleoptera

Silvanidae

Sil

Staphylininae morphospecies 1

Coleoptera

Staphylinidae (Staphylininae)

St1


Coleoptera


St6


Coleoptera


St9

Steropus globosus (Fabricius, 1792)

Coleoptera

Carabidae

Stg

Tachyporinae morphospecies 1 Tegenaria morphospecies 1

Coleoptera Araneae

Staphylinidae (Tachyporinae) Theridiidae

Ta1 Tes

Tetramorium morphospecies 1



Tet

Theridion morphospecies 1

Araneae

Theridiidae

Ths

Typhoeus morphospecies 1

Coleoptera

Geotrupidae

Typ

Xantholininae morphospecies 4

Coleoptera

Staphylinidae (Xantholininae)

Xa4

Xysticus morphospecies 1

Araneae

Thomisidae

Xys

Zelotes morphospecies 1

Araneae

Gnaphosidae

Zel

Zodarion alacre (Simon, 1870)

Araneae

Zodariidae

Zoa

Zora silvestris Kulczynski, 1897

Araneae

Zoridae

Zor

Taxa is alphabetically listed according to FC; FC fauna code used on multivariate analysis; n.d. not determined

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