Nova Hedwigia 2013 Vol. 96 issue 3–4, 367–381
published online November 20, 2012 Article
© 2012 J. Cramer in Gebr. Borntraeger Verlagsbuchhandlung, Stuttgart, www.borntraeger-cramer.de
Germany. DOI: 10.1127/0029-5035/2012/0069 0029-5035/2012/0069 $ 3.75
Mediterranean old-growth forests: the role of forest type in
the conservation of epiphytic lichens
Giorgio Brunialti1*, Sonia Ravera2 and Luisa Frati1
1 TerraData environmetrics, Spin Off Company of the University of Siena,
Via Bardelloni 19, I-58025 Monterotondo M.mo (GR), Italy
2 Department DiBT, University of Molise, C.da Fonte Lappone, I-86090 Pesche (IS), Italy
With 1 gure and 5 tables
Abstract: The present study investigated the effect of forest type on epiphytic lichen communities
and selected indicator species, useful for long-term monitoring programs in Mediterranean forests.
The results showed that only few species are common to many plots while others are locally rare.
Epiphytic lichen diversity and communities were signiﬁcantly inﬂuenced by forest type: Quercus
cerris-dominated forests hosted a richer lichen ﬂora, Fagus sylvatica-dominated forests showed the
majority of rare species, while mixed forests, though poorly represented in the study area, hosted the
majority of indicator species, revealing the presence of important and exclusive habitats. In particular,
old established forests are characterized by both stand- and tree- continuity, while mixed forests
offer a higher diversity of tree substrates. Our ﬁndings highlight the role of tree substrate variability
for lichen colonisation. The presence of non-dominant tree species contributes to the variability of
habitats and ecological niches. This allows the development of well preserved lichen communities
compared to those of structurally less complex or even monospeciﬁc forests.
Key words: conservation, lichens, old-growth forests, Mediterranean area, species richness.
Species richness and the occurrence of rare species are considered the main criteria
for selecting sites of conservation concern (Nordén et al. 2007). Nevertheless, it is
often difﬁcult to estimate the total biodiversity of a given territory, as it requires
considerable sampling effort and the contribution of a number of experts, and it
is even more complicated in the framework of long-term programmes. Thus, the
selection of indicator species may provide a suitable surrogate for total biodiversity
*Corresponding author; e-mail: email@example.com
estimates, and can be more easily sampled (Noss 1990; Lindenmayer et al. 2000).
The exploitation of forests may produce severe impacts on several components of
biodiversity (Heywood 1995), and the value of mature and old-growth forests for rare
and threatened species conservation is widely accepted (for a review see Humphrey
2005). Amongst the various components of forest biodiversity, epiphytic lichens are
widely used as indicators, being particularly sensitive to human-related alterations of
forests (Aragón et al. 2010), such as intensive management or replacement of native
forests with secondary forests (e.g. Humphrey et al. 2002; Nascimbene et al. 2007;
Fritz et al. 2008; Moning & Müller 2009).
Numerous studies evidenced a high influence of forest structure and habitat
characteristics on lichen communities (e.g. Sillett 1995; Neitlich & McCune 1997). In
particular, they strongly suggest that forest management contributes to the reduction
of lichen biomass and diversity by changing habitat conditions and inﬂuencing the
dynamics of managed forests over a vast range of spatial and temporal scales (e.g.
Dettki & Esseen 2002; McCune et al. 2003; Lemhkhul 2004). Further, the occurrence
and distribution of indicator species (i.e. cyanolichens, fruticose lichens, Caliciales)
or red listed lichens have been related to the inﬂuence of forest structure and age
(Hyvärinen et al. 1992, Gustaffson et al. 2004; McCune et al. 2003; Peck & McCune
1997; Lehmkuhl 2004), of the diversity of other organisms (Nilsson et al. 1995;
Gustaffson et al. 2004), and of different forest management plans (Peck & McCune
1997; McCune et al. 2003, Dettki & Esseen 2002). Given that, the study of the effects
of forest type, structure and continuity on epiphytic lichens is thus important when
managing natural reserves and selecting sites for conservational purposes.
This study is part of the initial survey of a long-term monitoring program that aims
at identifying the main key factors related to old-growth forests within an Italian
National Park (Cilento and Vallo di Diano, South Italy). Given the lack of knowledge
on near-natural state forest ecosystems in the Mediterranean basin, we underline the
importance of detecting, surveying, and conserving these forest stands and those that
are no longer managed, in the absence of human intervention. In fact, despite the
still extant Mediterranean old-growth forests are important habitats for biodiversity
conservation (PESBLD 1995), there are still a few long-term monitoring programs of
the various components of biodiversity (Motta 2002), and those considering cryptogams
are even less (Chiarucci & Bonini 2005; Giordani et al. 2006; Bacaro et al. 2008). In
this context, we are speciﬁcally interested in the inﬂuence of variables affecting the
lichen diversity in Mediterranean deciduous forests. In particular, we intend to answer
the following questions:
(1) do lichen species richness and the occurrence of rare species vary consistently in
relation to forest type?
(2) is it possible to select a list of suitable indicator species, useful to monitor forest
ecosystems within long-term monitoring programs?
To answer these questions, we randomly selected and sampled a number of stands
representing three forest types: Fagus sylvatica-, Quercus cerris-dominated forests and
mixed forests. We hypothesise a strong relation among forest type and lichen diversity
and composition, with particular relevance with rare species. Further, we expect to
ﬁnd out a list of suitable indicators of these features to follow their distribution in the
forthcoming surveys for conservational purposes.
Materials and methods
Study area: The study area comprises 5267 ha, covering the interior forest landscape of the Cilento,
Vallo di Diano and Alburni National Park, south-west Italy (Campania, southern Apennine, Fig. 1).
This is the second largest Italian National Park, stretching between 40°00' and 40°30'N and 14°50'
and 15°00'E, with a total area of 178,172 ha (EUAP 2003). Altitudes range from sea level to
Mt. Cervati (1898 m) in the whole park and from 300 to 1696 m in the survey area. The landscape
is extensively forested, with several scattered little villages.
The geological nature of the rocks is dominated by the "ﬂysch of the Cilento", mostly widespread
near the basin of the river Alento and the main mountains of western Cilento (Mt. Centaurino)
and by the calcareous rocks forming the inner (Alburno-Cervati) and the southern (Mt. Bulgheria,
Mt. Cocuzzo) mountain groups (Amore et al. 1988; Critelli & Le Pera 1990). Holm oak (Quercus
ilex L.) forests, interspersed with Mediterranean shrubland and broadleaves deciduous woods
dominated by Turkey oak (Quercus cerris L.) are found at lower elevations. Beech (Fagus sylvatica L.)
Fig. 1. Study area: Cilento and Vallo di Diano National Park (south Italy), with the 32 sampling plots.
woodlands, occasionally with Silver ﬁr (Abies alba Mill.), occur in upland areas both on ﬂysch and
on calcareous rocks (Corbetta et al. 2004).
The study area encompasses two bioclimatic zones: a transitional zone from the Mediterranean and
the temperate zones (meteorological stations of Sanza, 499 m, and Vallo della Lucania, 521 m) and
the temperate zone (meteorological stations of S. Rufo, 620 m, and Piaggine, 710 m) with a cooler
and more humid climate, where inland areas can be subject to temperature lower than 10°C for three
months per year. The mean annual temperature is 11.6°C, ranging, on average, from 6.0°C to 16.0°C.
Precipitations vary from 730 to 1700 mm year-1, depending on altitude, with a peak in winter and a
period of aridity in summer.
Q. cerris-dominated forests are mainly distributed between 400 and 1000 m and they are mostly
managed by selective or seed tree-cutting, a few areas being unmanaged (Corbetta et al. 2004).
At higher altitudes, between 1000 and 1800 m, forests are dominated by F. sylvatica and mainly
unmanaged or non-intensively managed by selective cutting (Corbetta et al. 2004).
Sampling deSign: A preliminary extensive survey collecting data on structural parameters and vascular
plant diversity was carried out in 132 sites (systematic survey, grid dimension 500 m, for more details,
see Corona et al. 2010). Then, on the basis of a stratiﬁed random sampling, a subsample of 32 forest
plots of 50×50 m dimension was selected out of the total, in order to perform a multi-taxon survey on
vascular plants, bryophytes, lichens, fungi, invertebrates, and vertebrates (for details see Blasi et al.
2010 and Brunialti et al. 2010). The present paper reports the results of the lichen diversity monitoring
study carried out in those 32 plots (Fig. 1), representing overall three forest types (Fagus sylvatica-,
Quercus cerris-dominated forests and mixed forests), in proportion to their area within the park.
lichen Sampling: In each plot, the presence of epiphytic lichen species found on the bole (0–2 m) of
three randomly selected trees (the tree nearest to the centre of three circular 14m-diameter subplots,
diameter breast height – DBH > 16 cm, bole inclination < 30°) was surveyed. A total of 94 trees
were sampled, belonging to 9 tree species: Fagus sylvatica L., Quercus cerris L., Acer opalus Mill.,
Alnus cordata (Loisel.) Desf., Castanea sativa Mill., Quercus frainetto Ten., Quercus pubescens
Willd., Carpinus betulus L. and Ostrya carpinifolia Scop. Species difﬁcult to identify in ﬁeld were
collected for identiﬁcation in laboratory by means of a binocular and microscope (magniﬁcation
up to ×40). For sections of thalli and fruiting bodies, a polarized light microscope with ×4, ×10,
×40, ×60, ×100 objectives with possibility of oil immersion, was used. Chemical spot tests K (10%
aqueous), C (satured aqueous bleach), KC (combination), Iodine, Nitric acid, Pd (5% alcoholic
p-phenylenediamine) and UV response were performed when necessary. Few sterile and leprose
thalli and cryptic species (sensu Hawksworth 2010) whose identiﬁcation requires TLC (Thin Layer
Chromatography) or a molecular approach, remained unclear and are not included in the results.
Nomenclature and ecological characteristics follow Nimis & Martellos (2008). Author’s abbreviations
follow Brummit & Powell (1992).
data analySiS: One-way non parametric Kruskal Wallis ANOVA (Kruskal & Wallis, 1952) was
used to test the effects of environmental categorical variables on lichen species richness. This is
an alternative non-parametric one way ANOVA, which is based on the differences between ranks
instead that between the averages. The analysis was performed with STATISTICA 6.0 (StatSoft
Inc.,Tulsa, Oklahoma, USA).
Compositional differences among forest types were tested using multi-response permutation
procedures (MRPP) using the Sørensen-index as a distance measure and rank transformation of the
distance matrices. The separation between groups was calculated as the chance-corrected within-
group agreement (A) and the p value was used for evaluating how likely an observed difference
was due to chance (A=1 indicates perfectly homogenous groups, while A=0 indicates within-group
heterogeneity equal to that expected by chance). In community ecology, values for A are commonly
below 0.1, even when the observed data differ signiﬁcantly from the expected (McCune & Grace,
2002). An Indicator Species Analysis (ISA; Dufrêne & Legendre, 1997) was used to determine how
strongly each species was associated with each forest type. For each species, the Indicator Value
(INDVAL) ranges from 0 (no indication) to 100 (maximum indication). Statistical signiﬁcance of
INDVAL was tested by means of a Monte Carlo test, based on 10,000 randomizations. ISA and
Monte Carlo test were performed by PC-ORD (McCune & Mefford, 1999).
A total of 142 lichen taxa was found (Table 1). Of these, 9 species (6%) occurred in
more than half of the sampled trees: Lecidella elaeochroma, Lecanora chlarotera,
Phlyctis argena, Parmelia sulcata, Parmelina tiliacea, Pertusaria pustulata, Pertusaria
albescens, Parmelia saxatilis, Lecanora intumescens. Only 20 species (14%) showed
a percentage occurrence more than 50% at site level. Thirty-seven species (26%) were
exclusive of a single site and most of the lichens was present in less than ﬁve sites
(88 species; 62%).
A considerable variability in the ﬂoristic lists was observed among the three forest
types (Table 2), with species richness ranging from 85 lichens found in Fagus sylvatica-
dominated forests and 106 lichens hosted by Quercus cerris stands. If we consider,
instead, the average number of species at site level, mixed forest stands had the highest
biodiversity (35 species). Kruskal Wallis ANOVA showed that lichen species richness
and the abundance of rare species were highly inﬂuenced by the forest type (p<0.05;
Table 3). In particular, mixed forests had the highest lichen diversity (24 species),
followed by Quercus cerris-, and Fagus sylvatica- dominated forests (with 21 and
20 species respectively). MRPP revealed signiﬁcant differences among forest types
(Total: A= 0.17, p<0.001; Table 4). In particular, relevant differences are evident among
lichen composition of Fagus sylvatica-dominated forests and the other forest types.
Thirty-three indicator species were associated with the three forest types (Table 5;
IV> 25; p<0.05). Mixed forests showed the highest number of indicator lichens (24),
followed by Fagus sylvatica-dominated forests (6 species). Only 3 indicator species
were found in relation to Quercus cerris-dominated forests.
Our study was performed in a number of stands showing the structural attributes of
ancient forests (see Blasi et al. 2010). In particular, the concept of forest continuity is
mostly referred to the continuous presence of forest, as well as of so-called "old-growth"
conditions, mainly related to the balance of processes such as mortality, growth, and
decay (Er & Innes 2003). Several conservation studies conﬁrm that a group of lichen
species are mainly conﬁned to old-growth or ancient forest stands, being sensitive to forest
management (Nilsson et al. 1995; Hilmo & Sastad 2001; Nordén et al. 2007). In these
mature habitats forest dwelling species can ﬁnd the suitable ecological features for their
development, above all stand-, tree- and substrate- continuity (see e.g., Nilsson et al. 1995).
Our results show that only few species are common to many plots while others
are locally rare, with little turnover among the forest types. A very rich supply in
microhabitats (mainly related to stand and tree features) show to be important both for
species richness and composition, and also for the presence of rare species, as ﬁrstly
suggested by Barkman (1958) and already pointed out in other situations (e.g. Ohlson
et al. 1997; Peck et al. 2004; Ravera et al. 2006; Lõhmus et al. 2007). This "local
rarity" phenomenon has already been noted in other studies (Humphrey et al. 2000,
2002) and was attributed to the small size of the sampling plot. A similar effect could
Table 1. Species list (142 taxa). For each lichen, occurrence (O) and percentage occurrence (O%)
values are reported at tree and site level respectively. Species are ordered according to the decreasing
value of O% at site level. O% values > 50 are reported in bold.
Species Tree level Site level
O O% O O%
Lecidella elaeochroma (Ach.) M.Choisy 84 89.4 31 96.9
Lecanora chlarotera Nyl. 81 86.2 30 93.8
Phlyctis argena (Spreng.) Flot. 80 85.1 29 90.6
Parmelia sulcata Taylor 76 80.9 29 90.6
Parmelina tiliacea (Hoffm.) Hale 61 64.9 26 81.3
Pertusaria pustulata (Ach.) Duby 61 64.9 23 71.9
Pertusaria albescens (Huds.) M.Choisy & Werner 49 52.1 23 71.9
Parmelia saxatilis (L.) Ach. 52 55.3 21 65.6
Lecanora intumescens (Rebent.) Rabenh. 47 50.0 19 59.4
Pertusaria amara (Ach.) Nyl. 44 46.8 19 59.4
Melanelixia subaurifera (Nyl.) O.Blanco. A.Crespo,
Divakar, Essl., D.Hawksw. & Lumbsch 39 41.5 18 56.3
Pertusaria pertusa (Weigel) Tuck. 41 43.6 18 56.3
Lecanora horiza (Ach.) Linds. 43 45.7 18 56.3
Physcia adscendens (Fr.) H.Olivier 33 35.1 17 53.1
Evernia prunastri (L.) Ach. 30 31.9 17 53.1
Tephromela atra v. torulosa (Flot.) Hafellner 32 34.0 17 53.1
Lepraria sp. 37 39.4 16 50.0
Ramalina sp. 34 36.2 16 50.0
Arthonia radiata (Pers.) Ach. 29 30.9 16 50.0
Aplotomma turgida (A.Massal.) A.Massal. 35 37.2 16 50.0
Melanohalea elegantula (Zahlbr.) O.Blanco.
A.Crespo. Divakar. Essl. D.Hawksw. & Lumbsch 36 38.3 14 43.8
Fuscidea stiriaca (A.Massal.) Hafellner 38 40.4 14 43.8
Melanelixia glabra (Schaer.) O.Blanco. A.Crespo.
Divakar. Essl. D.Hawksw. & Lumbsch 24 25.5 14 43.8
Lecanora allophana Nyl. 34 36.2 13 40.6
Pertusaria ﬂavida (DC.) J.R.Laundon 24 25.5 13 40.6
Lecanora argentata (Ach.) Malme 25 26.6 13 40.6
Phlyctis agelaea (Ach.) Flot. 25 26.6 13 40.6
Cladonia ﬁmbriata (L.) Fr. 21 22.3 12 37.5
Pertusaria coccodes (Ach.) Nyl. 14 14.9 11 34.4
Pertusaria slesvicensis Erichsen 24 25.5 11 34.4
Physconia venusta (Ach.) Poelt 14 14.9 8 27.8
Caloplaca pyracea (Ach.) Th.Fr. 17 18.1 10 31.3
Ramalina farinacea (L.) Ach. 28 29.8 10 31.3
Xanthoria parietina (L.) Th.Fr. 22 23.4 10 31.3
Lecanora hagenii (Ach.) Ach. 21 22.3 10 31.3
Lecanora leptyrodes (Nyl.) Degel. 21 22.3 10 31.3
Lobaria pulmonaria (L.) Hoffm. 26 27.7 10 31.3
Physcia leptalea (Ach.) DC. 15 16.0 10 31.3
Lecanora albella (Pers.) Ach. 18 19.1 10 31.3
Lecanora expallens Ach. 19 20.2 9 28.1
Pertusaria leioplaca DC. 22 23.4 9 28.1
Parmotrema perlatum (Huds.) M.Choisy 10 10.6 7 22.2
Candelariella xanthostigma (Ach.) Lettau 11 18.1 10 21.9
Ramalina fraxinea (L.) Ach. 13 13.8 7 21.9
Parmelina quercina (Willd.) Hale 12 12.8 7 21.9
Phaeophyscia hirsuta (Mereschk.) Essl. 12 12.8 7 21.9
Pyrenula nitida (Weigel) Ach. 14 14.9 7 21.9
Caloplaca cerina (Hedw.) Th.Fr. v. cerina 8 8.5 6 18.8
Ochrolechia subviridis (Høeg) Erichsen 9 9.6 6 18.8
Pertusaria hemisphaerica (Flörke) Erichsen 6 6.4 6 18.8
Pleurosticta acetabulum (Neck.) Elix & Lumbsch 12 12.8 6 18.8
Platismatia glauca (L.) W.L.Culb. & C.F.Culb. 11 11.7 6 18.8
Ramalina fastigiata (Pers.) Ach. 12 12.8 6 18.8
Flavoparmelia caperata (L.) Hale 9 9.6 5 15.6
Physconia distorta (With.) J.R.Laundon 10 10.6 5 15.6
Caloplaca herbidella (Hue) H.Magn. 7 7.4 5 15.6
Catillaria nigroclavata (Nyl.) Schuler 9 9.6 5 15.6
Graphis scripta (L.) Ach. 8 8.5 5 15.6
Ochrolechia balcanica Verseghy 8 8.5 5 15.6
Ochrolechia pallescens (L.) A.Massal. 8 8.5 5 15.6
Physcia aipolia (Humb.) Fürnrh. 10 10.6 5 15.6
Physconia servitii (Nádv.) Poelt 11 11.7 5 15.6
Scoliciosporum umbrinum (Ach.) Arnold 8 8.5 5 15.6
Buellia disciformis (Fr.) Mudd 9 9.6 5 15.6
Melanelixia fuliginosa (Duby) O.Blanco. A.Crespo.
Divakar. Essl. D.Hawksw. & Lumbsch 11 11.7 5 15.6
Pseudevernia furfuracea (L.) Zopf v. furfuracea 6 6.4 5 15.6
Acrocordia gemmata (Ach.) A.Massal. 4 4.3 4 12.5
Hyperphyscia adglutinata (Flörke) H.Mayrhofer &
Poelt 9 9.6 4 12.5
Table 1 continued.
Nephroma laevigatum Ach. 8 8.5 4 12.5
Caloplaca cerinella (Nyl.) Flagey 7 7.4 4 12.5
Caloplaca ferruginea (Huds.) Th.Fr. 7 7.4 4 12.5
Candelariella faginea Nimis, Poelt & Puntillo 7 7.4 4 12.5
Collema furfuraceum (Arnold) Du Rietz 4 4.3 4 12.5
Flavoparmelia soredians (Nyl.) Hale 8 8.5 4 12.5
Mycomicrothelia confusa D.Hawksw. 7 7.4 4 12.5
Parmelia submontana Hale 10 10.6 4 12.5
Parmelina pastillifera (Harm.) Hale 7 7.4 4 12.5
Porina aenea (Wallr.) Zahlbr. 7 7.4 4 12.5
Rinodina sophodes (Ach.) A.Massal. 3 3.2 3 9.4
Candelaria concolor (Dicks.) Stein 3 3.5 3 9.4
Melanohalea exasperata (De Not.) O.Blanco,
A.Crespo, Divakar, Essl., D.Hawksw. & Lumbsch 7 7.4 3 9.4
Normandina pulchella (Borrer) Nyl. 5 5.3 3 9.4
Bacidia arceutina (Ach.) Arnold 3 3.2 3 9.4
Crustose sp. 2 4 4.3 3 9.4
Lecania naegelii (Hepp) Diederich & Van den Boom 3 3.2 3 9.4
Lecanora carpinea (L.) Vain. 8 8.5 3 9.4
Lecidea sp. 2 4 4.3 3 9.4
Punctelia subrudecta (Nyl.) Krog 2 2.1 2 6.3
Arthonia punctiformis Ach. 6 6.4 2 6.3
Chrysothrix candelaris (L.) J.R.Laundon 3 3.2 2 6.3
Leptogium lichenoides (L.) Zahlbr. 2 2.1 2 6.3
Micarea sp. 1 3 3.2 2 6.3
Amandinea punctata (Hoffm.) Coppins & Scheid. 4 4.3 2 6.3
Arthopyrenia salicis A.Massal. 5 5.3 2 6.3
Caloplaca ﬂavorubescens (Huds.) J.R.Laundon 2 2.1 2 6.3
Caloplaca obscurella (Körb.) Th.Fr. 5 5.3 2 6.3
Lecania cyrtella (Ach.) Th.Fr. 3 3.2 2 6.3
Lecanora strobilina (Spreng.) Kieff. 2 2.1 2 6.3
Micarea sp. 2 4 4.3 2 6.3
Nephroma resupinatum (L.) Ach. 3 3.2 2 6.3
Ochrolechia androgyna (Hoffm.) Arnold 2 2.1 2 6.3
Peltigera canina (L.) Willd. 2 2.1 2 6.3
Phaeophyscia ciliata (Hoffm.) Moberg 3 3.2 2 6.3
Phaeophyscia endophoenicea (Harm.) Moberg 2 2.1 2 6.3
Sticta limbata (Sm.) Ach. 2 2.1 2 6.3
Bacidia circumspecta (Vain.) Malme 1 1.1 1 3.1
Punctelia jeckeri (Roum.) Kalb 1 1.1 1 3.1
Crustose sp. 1 1 1.1 1 3.1
Collema ﬂaccidum (Ach.) Ach. 1 1.1 1 3.1
Collema subﬂaccidum Degel. 1 1.1 1 3.1
Degelia plumbea (Lightf.) M.Jørg. & P.James 1 1.1 1 3.1
Dimerella pineti (Ach.) Vězda 2 2.1 1 3.1
Fuscopannaria saubinetii (Mont.) M.Jørg. 1 1.1 1 3.1
Heterodermia obscurata (Nyl.) Trevis. 1 1.1 1 3.1
Leproloma sp. 2 2.1 1 3.1
Lobaria amplissima (Scop.) Forssell v. amplissima 2 2.1 1 3.1
Opegrapha varia Pers. 1 1.1 1 3.1
Opegrapha vulgata Ach. 2 2.1 1 3.1
Pertusaria hymenea (Ach.) Schaer. 1 1.1 1 3.1
Physcia biziana (A.Massal.) Zahlbr. v. biziana 2 2.1 1 3.1
Anaptychia ciliaris (L.) Körb. 1 1.1 1 3.1
Arthonia spadicea Leight. 1 1.1 1 3.1
Bryoria fuscescens (Gyeln.) Brodo & D.Hawksw. 1 1.1 1 3.1
Calicium salicinum Pers. 1 1.1 1 3.1
Caloplaca chrysophthalma Degel. 2 2.1 1 3.1
Collema subnigrescens Degel. 1 1.1 1 3.1
Fuscopannaria mediterranea (Tav.) M.Jørg. 1 1.1 1 3.1
Fuscopannaria olivacea (M.Jørg.) M.Jørg. 1 1.1 1 3.1
Hypogymnia physodes (L.) Nyl. 3 3.2 1 3.1
Koerberia biformis A.Massal. 1 1.1 1 3.1
Lecanora pulicaris (Pers.) Ach. 2 2.1 1 3.1
Lecidea sp. 1 1 1.1 1 3.1
Lecidea erythrophaea Sommerf. 1 1.1 1 3.1
Ochrolechia arborea (Kreyer) Almb. 1 1.1 1 3.1
Ochrolechia dalmatica (Erichsen) Boqueras 1 1.1 1 3.1
Opegrapha ochrocheila Nyl. 1 1.1 1 3.1
Pachyphiale carneola (Ach.) Arnold 1 1.1 1 3.1
Phaeophyscia orbicularis (Neck.) Moberg 2 2.1 1 3.1
Ramalina pollinaria (Westr.) Ach. 1 1.1 1 3.1
Ramalina subgeniculata Nyl. 2 2.1 1 3.1
Rinodina pyrina (Ach.) Arnold 3 3.2 1 3.1
Schismatomma graphidioides (Leight.) Zahlbr. 2 2.1 1 3.1
Table 2. Descriptive statistics in relation to forest type (3 categories: Fagus sylvatica- , Quercus
cerris-dominated forests and mixed forests). Ao= Acer opalus, Ac= Alnus cordata, Cb= Carpinus
betulus, Oc= Ostrya carpinifolia, Cs= Castanea sativa, Fs= Fagus sylvatica, Qc= Quercus cerris,
Qf= Quercus frainetto, Qp= Quercus pubescens.
Forest type # plots Tree species (n) Lichen species
Mean±DS (min-max)* Total
forests 17 Fs (48), Ao (2),
Ac (1) 25.6 ±8.1 (6-41) 85
forests 11 Qc (22), Ao (3),
Cb (2), Qf (2),
Oc (1), Qp (1) 31.9±10.1 (12-50) 106
Mixed forests 4 Ac (6), Cs (3),
Qc (2), Qp (1) 35.5±11.0 (23-47) 89
Total 32 9 tree species 142
* mean lichen species number per site.
also drive our results, since the plots are small, while the survey area is very large and
heterogeneous. Probably, a higher sampling density may lead to a more homogeneous
distribution of the species that were sporadic in this survey (Brunialti et al. 2010).
However, these results give an indication of the environmental heterogeneity of the
studied forests, mainly in relation to old-growth structural features, thus reﬂecting
a general pattern of ecological continuity and the absence of a conspicuous human
impact (Nordén et al. 2007; Fritz et al. 2008).
The main ﬁndings of our study can be summarized in the following points. Firstly,
Fagus sylvatica- dominated forests, compared to the other forest types, show speciﬁc
lichen communities. This is mostly in relation to the better state of conservation of this
forest type (mainly unmanaged or non-intensively managed stands by selective cutting,
Table 3. Kruskal Wallis ANOVA results: lichen species richness (mean ± SD) in relation to categorical
variables. Signiﬁcant p levels are reported in bold.
Variable Categories N
Lichen species p-value
Rare species p-value
Mean ± SD (min-max) Mean ± SD
Forest type a
dominated forests 51 19.7 ± 5.6(4–35)
3.6 ± 1.7(0–8)
dominated forests 31 20.8 ± 5.3(10–32) 1.5 ± 1.6(0–6)
Mixed forests 12 24.2 ± 7.0(13–38) 1.2 ± 1.6(0–4)
a Tree level dataset (N=94)
Corbetta et al. 2004), but also on the presence of mountain lichens (e.g. Lecanora
argentata, L. albella, Fuscidea stiriaca) and species preferring smooth bark, not found
in other forest types. Furthermore, beech stands are a well-lit and very moist habitat,
resulting in light and humidity conditions more suitable for the growth of species of
conservation concern (Rose 1992; Neitlich & McCune 1997; Hilmo & Sastad 2001).
Although our beech stands have a lower vascular plant diversity with respect to the
other two forest types, they show a higher variability in the distribution of diameter
classes (multi-layered tree stands, see Brunialti et al. 2010). The presence of old trees
provides a very rich supply in microhabitats (old-growth qualities), representing an
important refuge for lichens (Brunialti et al. 2010). In contrast, despite their higher
vascular plant and lichen species richness, Turkey oak stands of our study are very
homogeneous with regard to the age of trees (even-aged stands). For this reason, their
homogeneous structure leads to colonization by common species, which are also better
suited to live in the drier habitats of these woods.
A second important result concerns the signiﬁcant contribute to lichen diversity of
mixed forests. This forest type, though poorly represented in the study area, hosts
the majority of indicator species, displaying the presence of important and exclusive
micro-habitats and conﬁrming their role in lichen conservation (Rose 1988; Ravera
et al. 2006; Ravera et al. 2012). Mixed forests are younger than the other two forest
types, but they offer a higher diversity of tree substrates both in terms of texture and
pH. In particular, sporadic or rare tree species such as Alnus cordata host not only
an interesting species richness, but they provide refuge for species of conservation
concern (e.g. Lobarion communities, Rose 1992).
Thus, we can say that both the forest type (i.e. mainly stand structure, affecting light
availability) and the variability of tree substrates are important for the selection of
indicator species. These outcomes are in accordance with several papers indicating the
inﬂuence of both these aspects. Especially, many authors consider factors connected
with tree age and morphology, such as height and bark structure, to be the most
important factors inﬂuencing epiphytes (McCune & Antos 1982; Hyvärinen et al.
1992), while others give more importance to physico-chemical characteristics of the
bark, like pH, water-holding capacity and bark elemental content (Barkman 1958;
Adams & Risser 1971; Loppi & Frati 2004).
Table 4. MRPP results. Effect size A-, and p-values for the non-metric multi-response permutation
procedures (MRPP) applied to the forest types pooled together (Total), as well as for their pairwise
comparisons (FSf=Fagus sylvatica- dominated forests, QCf=Quercus cerris- dominated forests and
Total A=0.17 p<0.001
Table 5. Indicator species (33) in relation to forest type (FSf= Fagus sylvatica- dominated forests,
QCf =Quercus cerris- dominated forests, and Mf= mixed forests). IV= indicator value. p<0.05, **
p<0.01, *** p<0.001
Species Forest type Indicator
Fuscidea stiriaca (A.Massal.) Hafellner FSf 74.5 ***
Aplotomma turgida (A.Massal.) A.Massal. FSf 45.4 **
Lecanora argentata (Ach.) Malme FSf 42.8 **
Tephromela atra v. torulosa (Flot.) Hafellner FSf 35.6 **
Pertusaria pustulata (Ach.) Duby FSf 29.2 *
Lecanora albella (Pers.) Ach. FSf 28.6 *
Ramalina farinacea (L.) Ach. QCf 30.8 *
Lecanora hagenii (Ach.) Ach. QCf 28.3 *
Flavoparmelia soredians (Nyl.) Hale QCf 25.8 *
Catillaria nigroclavata (Nyl.) Schuler Mf 63.8 ***
Mycomicrothelia confusa D. Hawksw. Mf 60.7 ***
Physcia leptalea (Ach.) DC. Mf 54.1 **
Lecanora horiza (Ach.) Linds. Mf 53.7 ***
Xanthoria parietina (L.) Th.Fr. Mf 50.1 **
Rinodina pyrina (Ach.) Arnold Mf 50 ***
Lecanora intumescens (Rebent.) Rabenh. Mf 47.9 ***
Caloplaca obscurella (Körb.) Th.Fr. Mf 47.9 **
Ochrolechia pallescens (L.) A.Massal. Mf 46.2 ***
Lecanora carpinea (L.) Vain. Mf 42.7 **
Physconia servitii (Nádv.) Poelt Mf 41.3 **
Caloplaca herbidella (Hue) H.Magn. Mf 40 **
Lecanora leptyrodes (Nyl.) Degel. Mf 39.3 **
Caloplaca ferruginea (Huds.) Th.Fr. Mf 35.1 *
Physcia adscendens (Fr.) H.Olivier Mf 34.4 *
Caloplaca chrysophthalma Degel. Mf 33.3 *
Phaeophyscia orbicularis (Neck.) Moberg Mf 33.3 **
Pleurosticta acetabulum (Neck.) Elix & Lumbsch Mf 32.6 *
Physconia distorta (With.) J.R.Laundon Mf 31.1 *
Caloplaca cerinella (Nyl.) Flagey Mf 30.8 *
Candelariella xanthostigma (Ach.) Lettau Mf 28 *
Arthopyrenia salicis A.Massal. Mf 26.2 *
Phlyctis argena (Spreng.) Flot. Mf 25.9 ***
Nephroma laevigatum Ach. Mf 25.1 *
Funding was provided by the Cilento and Vallo di Diano National Park and is part of the project
"Monitoraggio alla rete dei boschi vetusti del Parco nazionale del Cilento e Vallo di Diano" with
the coordination of the Department of Plant Biology of "La Sapienza" University, Rome. We thank
an anonymous reviewer for improving the clarity and the effectiveness of the manuscript. We also
thank Dr. Leonardo Rosati for cartographic assistance.
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Manuscript received January 22, 2012; accepted May 18, 2012.