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Plant Biosystems - An International Journal Dealing
with all Aspects of Plant Biology: Official Journal of the
Societa Botanica Italiana
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Lichens and bryophytes as indicators of old‐growth
features in Mediterranean forests
G. Brunialti a , L. Frati a , M. Aleffi b , M. Marignani a c , L. Rosati d , S. Burrascano c & S.
Ravera e
a TerraData Environmetrics, Department of Environmental Science , University of Siena ,
Italy
b Department of Environmental Science, Section of Botany and Ecology, Bryology Lab ,
University of Camerino , Italy
c Department of Plant Biology of “La Sapienza” University , Italy
d Department of Biology DBAF , University of Basilicata , Italy
e Department S.T.A.T. , University of Molise , Italy
Published online: 03 Mar 2010.
To cite this article: G. Brunialti , L. Frati , M. Aleffi , M. Marignani , L. Rosati , S. Burrascano & S. Ravera (2010) Lichens
and bryophytes as indicators of old‐growth features in Mediterranean forests, Plant Biosystems - An International
Journal Dealing with all Aspects of Plant Biology: Official Journal of the Societa Botanica Italiana, 144:1, 221-233, DOI:
10.1080/11263500903560959
To link to this article: http://dx.doi.org/10.1080/11263500903560959
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Plant Biosystems
,
Vol. 144, No. 1, March 2010, pp. 221–233
ISSN 1126-3504 print/ISSN 1724-5575 online © 2010 Società Botanica Italiana
DOI:
10.1080/11263500903560959
OLD-GROWTH FORESTS: AN ECOSYSTEM APPROACH
Lichens and bryophytes as indicators of old-growth features in
Mediterranean forests
G. BRUNIALTI
1
, L. FRATI
1
, M. ALEFFI
2
, M. MARIGNANI
1,3
, L. ROSATI
4
,
S. BURRASCANO
3
, & S. RAVERA
5
1
TerraData Environmetrics, Department of Environmental Science, University of Siena, Italy,
2
Department of Environmental
Science, Section of Botany and Ecology, Bryology Lab, University of Camerino, Italy,
3
Department of Plant Biology of “La
Sapienza” University, Italy,
4
Department of Biology DBAF, University of Basilicata, Italy, and
5
Department S.T.A.T.,
University of Molise, Italy
Taylor and Francis
Abstract
This study is focused on the selection of variables affecting lichen and bryophyte diversity in Mediterranean deciduous
forests. Plots representing two forest types (
Fagus sylvatica
and
Quercus cerris
forests) and two forest continuity categories
(old-growth (OG) and non-OG forests) were selected in the Cilento and Vallo di Diano National Park (Italy). The presence
and the abundance of bryophytes and epiphytic lichens were recorded. Structural variables of the forests and vascular plant
species richness have been used as predictors. A strong positive correspondence between the two groups of organisms was
found. Higher species richness and the distribution of rare species are related to OG stands, while a qualitative (species
composition) rather than a quantitative (species richness) difference between the two forest types was observed. Some
species elsewhere considered as indicators of forest continuity, such as
Lobaria pulmonaria
,
Antitrichia curtipendula
, and
Homalothecium sericeum
, are associated with OG forests, independently from forest type, suggesting that they can be
regarded as suitable indicators also in Mediterranean forests. Finally, our results suggest that old trees, high levels of basal
area, a broad range of diameter classes, and high understory diversity are the main structural features affecting cryptogamic
communities, while no correlation was found with the occurrence of deadwood.
Keywords:
Bryophytes, diameter classes, forest continuity, lichens, rare species, species richness
Introduction
According to Peterken (1996), old-growth (OG)
forests are those developed during long periods
without relevant human impact and natural cata-
strophic disturbances with distinctive features in
terms of, for example, forest continuity, structural
heterogeneity, volumes of deadwood, and the
presence of old trees.
The value of mature and OG forests for biodiver-
sity and especially for rare and threatened species
conservation is widely accepted (for a review, see
Humphrey 2005).
Attempts have been made to discriminate OG
stands in terms of species composition, function,
and structure (Humphrey 2005). For instance, in
northern Europe, several OG-related cryptogams
and vascular plants, along with structural elements
of the forest, are consistently adopted for scientifi-
cally supporting the selection of woodland key habi-
tats to be protected (Gustafsson et al. 1999; Uliczka
& Angelstam 2000; Nordén et al. 2007; Fritz et al.
2008). In addition, there is a large agreement on the
fact that forest continuity should be the prime crite-
rion for the selection of forest reserves (Nilsson &
Ericson 1992; Nilsson et al. 1995). 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). However, several authors stressed the
difficulty in defining and separating continuity from
other ecological factors (Nordén & Appelqvist 2001;
Rolstad et al. 2002; Fritz et al. 2008). Indeed, in
Correspondence: G. Brunialti, TerraData Environmetrics, Department of Environmental Science, University of Siena, Via P.A. Mattioli 4, I-53100 Siena,
Italy. Tel: +39 0577 235415. Fax: +39 0577 232896. Email: brunialti@terradata.it
Downloaded by [Universita Studi la Sapienza], [S. Ravera] at 06:58 17 June 2014
222
G. Brunialti et al.
practical terms, it is often difficult to obtain a work-
ing definition of forest continuity because of the
many aspects related to this parameter (e.g., stand-,
tree-, substrate-, deadwood-continuity; see e.g.,
Nilsson et al. 1995). In general, the lack of historical
documentation on forest continuity (age of the
forests) and management during the centuries points
out the need of indicators or surrogates for this
parameter, although their selection may be problem-
atic (Nilsson et al. 1995; Rolstad et al. 2002; Nordén
et al. 2007). In this context, lichens and bryophytes
are widely used in conservation surveys since they
are sensitive to forest management and since several
species are mainly confined to OG or ancient forest
stands (Rose 1976; Nilsson et al. 1995; Gustafsson
et al. 1999; Hilmo & Sastad 2001; Nordén et al.
2007).
As highlighted by the Pan-European Strategy for
Biological and Landscape Diversity, the still extant
Mediterranean OG forests are important habitats for
biodiversity conservation (PESBLD 1995). Never-
theless, 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 Italy, many natural
reserves include several OG forests potentially
important for cryptogam conservation. Nevertheless,
contrary to what is done in the temperate and boreal
forests, little is known about the processes that regu-
late the development of cryptogams in Mediterra-
nean environments (see e.g., Martínez et al. 2006;
Nascimbene et al. 2006, 2007; Belinchón et al.
2007).
This study is the initial survey of a long-term
monitoring program that aims at identifying the
main key factors related to OG forests. Given the
lack of knowledge on near-natural state forest
ecosystems in the Mediterranean basin, we under-
line the importance of detecting, surveying, and
conserving these forest stands and those that are no
longer managed, in the absence of human interven-
tion. In this context, we are specifically interested in
the selection of the variables affecting the diversity of
lichens and mosses and the presence of rare species
in Mediterranean deciduous forests.
In particular, we intend to answer the following
questions: (1) Do lichen and bryophyte communi-
ties vary consistently in relation to environmental
variables linked to OG forests? (2) What is the rela-
tionship between the diversity of these taxa and
vascular plants in OG stands? (3) Are rare and
endangered species mainly associated with OG
features? (4) What, if any, association exists between
lichen and bryophyte communities?
To answer these questions, we randomly selected
and sampled a number of stands representing two
forest types (
Fagus
sylvatica
and
Quercus
cerris
forests) and two forest continuity categories (OG
and non-OG forests).
Materials and methods
Study area
The study area comprises 5267 ha, covering the
interior forest landscape of the Cilento and Vallo di
Diano National Park, south-west Italy (Campania,
southern Apennine, Figure 1). This is the widest
Italian National Park, stretching between 40
°
00
′
and
40
°
30
′
N and 14
°
50
′
and 15
°
0
′
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 land-
scape is extensively forested, with several scattered
little villages.
Figure 1. Study area: Cilento and Vallo di Diano National Park (south Italy).
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 (
Q. cerris
L.) are found at lower eleva-
tions. Beech (
F. sylvatica
L.) woodlands, occasion-
ally 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).
For further details on oak and beech forest vegeta-
tion on “flysch substrata” see also Rosati et al.
(2005).
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Cryptogams and Mediterranean old forests
223
Sampling design
This project is part of a long-term program to moni-
tor the impacts of forest management practices on
organisms and ecosystem attributes in Cilento
National Park.
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 36 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 verte-
brates (see Blasi et al. 2010).
In this study, to reduce environmental variability
biases, we limited the analyses on 28 plots represent-
ing two forest types (17 beech woods and 11 Turkey
oak woods), including both OG and non-OG stands
(17 OG stands and 11 non-OG stands; Figure 1).
The multi-taxon field survey was carried out in
spring and summer 2008.
Vascular plant samplin
g
.
In each plot, a complete list
of the vascular plants was performed and a cover value
was assigned to each species according to the Braun-
Blanquet scale (Braun-Blanquet 1932). The data
were then treated, distinguishing tree species (indi-
cating overstory species) from understory species.
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
center of three circular 14-m diameter subplots,
diameter breast height – DBH > 16 cm, bole incli-
nation < 30
°
) was surveyed. A total of 84 trees were
sampled. An abundance score was assigned to each
species in relation to its frequency on the three trees
per plot: 0 = absent; 1 = rare (1–3 individuals per
plot); 2 = uncommon (4–10 individuals per plot); 3
= common (>10 individuals per plot but less than
half of the appropriate substrates bearing the
species); 4 = very abundant (more than half of the
appropriate substrates bearing the species). Species
difficult to identify in field were collected for identi-
fication in lab. The nomenclature, ecology, and
distribution of lichen species followed the online
checklist of Italian lichens (Nimis & Martellos
2008). Nationally “very rare” and “extremely rare”
species (
sensu
Nimis & Martellos 2008) were
grouped into a single category, labeled “rare
species.”
Bryophyte sampling.
In each plot, epiphytic,
epilithic, epixilic, and terricolous bryophytes
(including mosses and hepatics) had been collected
on all substrates (tree, deadwood, soil, and rocks).
An abundance score was assigned to each species in
relation to its frequency per plot (see lichen
sampling). The nomenclature and distribution
Figure 1. Study area: Cilento and Vallo di Diano National Park (south Italy).
Downloaded by [Universita Studi la Sapienza], [S. Ravera] at 06:58 17 June 2014
224
G. Brunialti et al.
followed Aleffi et al. (2008), while for ecology and
autoecology we referred to Ellenberg et al. (1991),
Düll (1991), and Dier
β
en (2001). Also in this case,
nationally “very rare” and “extremely rare” species
(
sensu
Aleffi et al. 2008) were merged into a single
category named, “rare species.”
Selection of old-growth characteristics.
The 28 plots
were classified as OG vs. non-OG according to their
structural attributes, following the definitions
reported in the literature (for a review, see
Humphrey 2005). OG stands were considered to be
structurally more heterogeneous than younger ones
in relation to the following criteria: (1) the presence
of OG individual trees (individuals with DBH > 50
cm); (2) weak or no human disturbance; (3) multi-
layered canopy; (4) large volumes of standing and
fallen deadwood; (5) decaying ancient and veteran
trees (standing dead trees).
Data analysis
Both structural variables and vascular plant species
richness have been used as predictors, while lichen
and bryophyte species richness were adopted as
response variables. We tested first the response of
cryptogams as a whole and then we considered
separately the subsets of lichens and bryophytes
(Table I).
Due to the unbalanced dataset, the comparison
between OG and non-OG stands might just reflect
the relationship between beech forests and Turkey
oak forests, more specifically OG beech forests and
non-OG Turkey oak forests. This bias was taken
into account by the use of permutational multivari-
ate analysis of variance (PERMANOVA; Anderson
2001), testing the simultaneous response of lichen
and bryophyte species composition to factors in an
ANOVA experimental design, using permutation
methods. The factors were forest continuity (OG vs.
non-OG) and forest type (beech vs. Turkey oak
forests); we also considered the interaction between
forest continuity and forest type. Analyses were
conducted using Bray–Curtis measure on abun-
dance data. The statistical significance of multivari-
ate variance components was tested using 999
unrestricted permutations of raw data using correct
permutable units, as implemented in Primer-E
(Clarke & Gorley 2006).
Non-metric multidimensional scaling (NMS,
Kruskal 1964), as implemented in the program PC-
Ord (McCune & Mefford 1999), was adopted as an
ordination method in order to study the influence of
the main predictors on cryptogamic species compo-
sition. This is an iterative ordination method based
on ranked distances between sample units in the
data matrix. NMS does not require multivariate
normality of data and is considered as a reliable ordi-
nation method giving a high degree of explanation
for the underlying data structure (McCune & Grace
2002). Species frequencies (main matrix, both
lichen and bryophyte species
×
28 plot, 198 species;
only lichens, 127 species; only bryophytes, 71
species) were tested against the environmental vari-
ables (second matrix, see Table I). The categorical
variables “forest types” (two categories: beech stands
and Turkey oak stands) and “forest continuity” (two
categories: OG and non-OG) were included in the
Table I. Predictive and response variables included in NMS ordination (mean
±
SD).
Forest type Forest continuity
Predictors Turkey oak stands Beech stands OG stands Non-OG stands
Structural variables
Basal area (m
2
ha
−
1
) 18.6
±
11.1 30.3
±
10.7 28.4
±
10.8 23.9
±
12.9
Number of old trees 3.09
±
5.58 9.12
±
8.08 11.4
±
8.4 3.76
±
5.64
Diameter classes number 7.18
±
3.19 10.7
±
3.2 10.8
±
3.8 8.35
±
3.18
Deadwood
Standing deadwood (vol ha
−
1
) 0.11
±
0.26 1.74
±
3.28 0.32
±
0.32 1.61
±
3.34
Fallen deadwood (vol ha
−
1
) 1.02
±
1.52 0.98
±
1.35 1.67
±
1.58 0.56
±
1.10
Vascular plants biodiversity
Tree species richness 6.18
±
1.78 1.82
±
0.73 3.27
±
2.49 3.71
±
2.54
Understory species richness 66.3
±
14.9 41.8
±
23.0 46.3
±
22.7 54.7
±
23.8
Response variables
Total lichen species richness 31.9
±
10.1 26.7
±
7.2 29.8
±
12.3 28.1
±
5.7
Rare lichen species richness
a
1.91
±
2.02 3.94
±
1.85 3.64
±
2.54 2.82
±
1.85
Total bryophyte species richness 25.0
±
8.6 36.6
±
11.5 34.2
±
12.5 30.7
±
11.5
Rare bryophyte species richness
b
1.73
±
1.01 2.41
±
1.97 2.45
±
1.63 1.94
±
1.71
a
Rare lichen species: include “very rare” and “extremely rare” Italian species (Nimis & Martellos 2008);
b
rare bryophyte species: include
“very rare” and “extremely rare” Italian species (Aleffi et al. 2008).
Note: OG, old-growth stands; non-OG, non old-growth stands.
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Cryptogams and Mediterranean old forests
225
second matrix with dummy figures (0/1). The final
ordination was done with the “slow and thorough”
autopilot mode using the quantitative version of
Sørensen distance measure. This procedure
performed 40 runs with real data compared with 50
randomized data with 400 iterations each. Stress
levels differed significantly (
p
< 0.05). Correlations
between the ordination axes and the variables and
species were calculated with Pearson correlation in
PC-Ord, as well as the cumulative correlations
between distances in the original
n
-dimensional
space and distances on the ordination axes.
Mantel test, as implemented in the program PC-
Ord (McCune & Mefford 1999), was performed to
evaluate the congruence between the community
structure of the two groups of organisms from the
same 28 plots (lichens: 127 species; bryophytes: 71
species). This test evaluates the null hypothesis of no
relationship between two dissimilarity (distance) and
similarity matrices. Since the cells of distances matri-
ces are not independent of each other, we cannot
accept the
p
-values from standard techniques that
assume independence of the observations (for exam-
ple, Pearson correlation). Nevertheless, the Pearson
correlation can be used as a measure of the strength
of relationship between two distance matrices. In
this context, this is called as the standardized Mantel
statistic (
r
) (Sokal & Rohlf 1995) and
r ranges from
−1 to 1. The Mantel method tests the significance of
the correlation by a permutation method: the rows
and columns of one of the two matrices are
permuted simultaneously, so that for each i, the ith
row and ith column will correspond to the same case
(Monte Carlo randomization test). The diagonal
elements always remain in the diagonal (but in
different positions), but non-diagonal elements
appear with equal probability in each of the n(n–1)
non-diagonal positions. After each permutation, the
Z statistic is calculated and the resulting values
provide an empirical distribution that is used for the
significance test. The Z statistic is simply the sum of
the products of the corresponding off-diagonal
elements of the two matrices, also known as the
Hadamard product of the matrices. A positive asso-
ciation between matrices is indicated by observed Z
greater than average Z from randomized runs.
Results
A total of 127 infrageneric taxa of lichens and 71 of
bryophytes were sampled across the two forest types.
Of these, 17 lichens (13%) and six bryophytes (8%)
occurred in more than half of the plots, 17 (13%)
and 33 (26%) lichens and six (8%) and 28 (39%)
bryophytes occurred in only two and only one plot,
respectively.
The sample includes 34 (27%) and 10 (14%) rare
and very rare lichens and bryophytes, respectively.
The predictors and the response variables
included in NMS ordination are given in Table I.
Mantel test shows a strong positive correspon-
dence between the two groups of organisms
(observed Z: 0.31E + 03 > average Z from random-
ized runs: 0.29E + 03, r = 0.62, p < 0.01).
The PERMANOVA on lichen and bryophyte
species composition showed that the factors (forest
continuity and forest type) and their interaction term
(forest continuity × forest type) have a significant
effect on species composition (p < 0.05; Table II).
The pair-wise tests of factor “forest type,” within the
level “OG” of factor “forest continuity” showed that
the species composition of beech and Turkey oak
stands differ significantly in OG forests (p < 0.05;
Table II), while in the managed stands, no differ-
ences between different forest types (beech vs.
Turkey oak) emerged (p > 0.05). Hence, the results
regarding the management effect on species compo-
sition were not strongly influenced by the unbal-
anced dataset.
Considering cryptogamic species richness as a
whole, the three axes of the NMS ordination
(Figure 2) explain 93.4% of total variability in their
community structure (43.7% for Axis 1, 28.7% for
Axis 2, and 20.9% for Axis 3).
Figure 2. NMS ordinations (Sørensen distance measure) of 28 plots in species space (198 species). The NMS suggested a three-dimensional final solution, with a final stress of 8.5 in 40 runs of real data, statistically significant ( p < 0.05, mean stress = 19.7) when compared with 50
randomized runs of the Monte Carlo test. Plots are categorized by forest type (a and b) and forest continuity (c and d). Length of overlaid vectors is proportional to Pearson R2 of variables with axis (only variables with R2 > 0.2 are displayed). Abbreviations of variable names are asfollows (Table II): OT, old trees; BA, basal area; DCN, diameter classes number; TSRich, tree species richness; USRich, understory species richness; LSRich, total lichen species richness; BrSRich, total bryophyte species richness.
Table III shows the correlations of the predictors
with the axes, while Table IV reports the list of 53
Table II. Results of PERMANOVA and associated pair-wise comparison for lichen and bryophyte species composition variability among
the levels of the factors: forest continuity (OG vs. non-OG), forest type (beech vs. Turkey oak forests), and their interaction term.
Source of variation – factors Pseudo-F statistic Significance Pair-wise test
Forest type F1,24 = 2.1076 <0.01 Beech vs. Turkey oak; p < 0.05
Forest continuity F1,24 = 4.3591 <0.05 OG vs. non-OG; p < 0.001
Forest type × forest continuity F1,24 = 2.0202 <0.05 Within OG forests
Beech vs. Turkey oak; p < 0.05
Within non-OG forests
Beech vs. Turkey oak; p > 0.05
Within beech forests
OG vs. non-OG; p < 0.001
Within Turkey oak forests
OG vs. non-OG; p < 0.05
Downloaded by [Universita Studi la Sapienza], [S. Ravera] at 06:58 17 June 2014
226 G. Brunialti et al.
species showing R2 ≥ 0.2 for at least one axis. The
two forest types are clearly separated along Axis 1
(Figure 2a and 2b), showing an increasing gradient
of tree (R2 = 0.580) and understory species richness
(R2 = 0.217) in correspondence to Turkey oak
stands. Fourteen species are preferentially distrib-
uted in this latter forest type (R2 ≥ 0.2), including
mainly common species such as the lichens
Figure 2. NMS ordinations (Sørensen distance measure) of 28 plots in species space (198 species). The NMS suggested a three-
dimensional final solution, with a final stress of 8.5 in 40 runs of real data, statistically significant (p < 0.05, mean stress = 19.7) when
compared with 50 randomized runs of the Monte Carlo test. Plots are categorized by forest type (a and b) and forest continuity (c and
d). Length of overlaid vectors is proportional to Pearson R2 of variables with axis (only variables with R2 > 0.2 are displayed). Abbrevia-
tions of variable names are as follows (Table II): OT, old trees; BA, basal area; DCN, diameter classes number; TSRich, tree species
richness; USRich, understory species richness; LSRich, total lichen species richness; BrSRich, total bryophyte species richness.
Table III. Correlation coefficients of the nine predictors with NMS ordination axes.
Axis 1 Axis 2 Axis 3
Predictors Abbreviations rR
2rR
2rR
2
Deadwood Standing deadwood SDW −0.233 0.054 −0.012 0.000 0.137 0.019
Fallen deadwood FDW 0.082 0.007 0.246 0.060 0.197 0.039
Stuctural variables Old trees OT −0.328 0.108 0.527 0.277 0.425 0.181
Basal area BA −0.514 0.264 0.526 0.277 0.551 0.303
Diameter classes number DCN −0.450 0.203 0.646 0.417 0.636 0.405
Biodiversity Tree species richness TSRich 0.762 0.580 −0.234 0.055 −0.129 0.017
Understory species richness USRich 0.466 0.217 −0.163 0.027 0.467 0.218
Total lichen species richness LSRich 0.170 0.029 0.244 0.060 0.591 0.350
Total bryophyte species
richness
BrSRich −0.438 0.192 0.390 0.152 0.581 0.338
R2 ≥ 0.2 are reported in bold.
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Cryptogams and Mediterranean old forests 227
Table IV. Correlations of epiphytic lichen (42) and bryophyte (11) species with the three ordination axes (see Figure 2).
Axis 1 Axis 2 Axis 3
Rarity P% r R2rR
2rR
2
Lichens
Arthonia radiata (Pers.) Ach. c54 −0.464 0.215 0.39 0.152 −0.057 0.003
Arthonia spadicea Leight. vr 4 0.298 0.089 0.534 0.285 −0.003 0
Caloplaca cerina (Hedw.) Th.Fr. v. cerina c 18 −0.302 0.091 −0.447 0.199 −0.528 0.279
Caloplaca pyracea (Ach.) Th.Fr. vc 29 0.645 0.416 −0.237 0.056 −0.455 0.207
Candelariella faginea Nimis, Poelt & Puntillo vr 14 −0.362 0.131 −0.451 0.203 −0.454 0.206
Chrysothrix candelaris (L.) J.R.Laundon c7 0.331 0.11 0.562 0.316 0.006 0
Cladonia fimbriata (L.) Fr. vc 39 0.497 0.247 0.169 0.029 −0.031 0.001
Dimerella pineti (Ach.) V[ecaron] zda r4 0.298 0.089 0.534 0.285 −0.003 0
Evernia prunastri (L.) Ach. c54 −0.041 0.002 −0.031 0.001 0.638 0.408
Flavoparmelia caperata (L.) Hale vc 14 0.48 0.23 −0.047 0.002 −0.166 0.028
Flavoparmelia soredians (Nyl.) Hale r14 0.552 0.304 −0.49 0.24 −0.53 0.281
Fuscidea stiriaca (A.Massal.) Hafellner vr 50 −0.652 0.425 0.053 0.003 0.095 0.009
Graphis scripta (L.) Ach. r14 0.469 0.22 0.127 0.016 −0.199 0.04
Hyperphyscia adglutinata (Flörke) H.Mayrhofer & Poelt vc 14 0.474 0.225 −0.454 0.206 −0.328 0.108
Lecanora argentata (Ach.) Malme r46 −0.465 0.216 −0.088 0.008 0.159 0.025
Lecanora expallens Ach. vc 21 0.625 0.391 −0.114 0.013 −0.149 0.022
Lecanora hagenii (Ach.) Ach. vc 36 0.502 0.252 −0.601 0.362 −0.643 0.413
Lecanora intumescens (Rebent.) Rabenh. vr 61 −0.682 0.465 0.293 0.086 0.067 0.004
Lecidella elaeochroma (Ach.) M.Choisy vc 96 −0.033 0.001 −0.216 0.047 −0.643 0.413
Lepraria sp.c54 −0.111 0.012 0.4 0.16 0.677 0.458
Lobaria pulmonaria (L.) Hoffm. vr 32 −0.137 0.019 −0.098 0.01 0.65 0.423
Melanelixia subaurifera (Nyl.) O. Blanco, A. Crespo, Divakar, Essl.,
D. Hawksw. & Lumbsch
vc 50 0.536 0.287 −0.287 0.083 −0.157 0.025
Melanohalea elegantula (Zahlbr.) O.Blanco, A.Crespo, Divakar, Essl.,
D.Hawksw. & Lumbsch
r43 −0.24 0.058 0.143 0.02 0.618 0.382
Normandina pulchella (Borrer) Nyl. c7 0.481 0.232 −0.248 0.062 −0.546 0.298
Opegrapha vulgata Ach. r4 0.298 0.089 0.534 0.285 −0.003 0
Parmelia saxatilis (L.) Ach. r71 −0.418 0.175 0.156 0.024 0.81 0.656
Parmelia sulcata Taylor vc 89 −0.154 0.024 −0.06 0.004 0.566 0.32
Parmotrema perlatum (Huds.) M.Choisy vc 18 0.548 0.301 −0.225 0.051 −0.136 0.018
Pertusaria albescens (Huds.) M.Choisy & Werner c79 −0.392 0.154 0.259 0.067 0.604 0.365
Pertusaria amara (Ach.) Nyl. vc 64 −0.093 0.009 0.126 0.016 0.695 0.484
Pertusaria coccodes (Ach.) Nyl. r36 −0.154 0.024 0.165 0.027 0.454 0.206
Pertusaria flavida (DC.) J.R.Laundon c43 −0.086 0.007 −0.064 0.004 0.619 0.384
Pertusaria pertusa (Weigel) Tuck. c61 −0.203 0.041 0.202 0.041 0.748 0.559
Pertusaria slesvicensis Erichsen vr 36 −0.245 0.06 0.225 0.051 0.555 0.308
Phlyctis agelaea (Ach.) Flot. c39 −0.048 0.002 0.501 0.251 0.32 0.102
Phlyctis argena (Spreng.) Flot. vc 93 −0.251 0.063 0.515 0.266 0.879 0.773
Physcia adscendens (Fr.) H.Olivier vc 46 0.753 0.567 −0.477 0.227 −0.54 0.292
Physconia servitii (Nádv.) Poelt r11 0.491 0.241 −0.407 0.166 −0.251 0.063
Physconia venusta (Ach.) Poelt c25 −0.005 0 −0.211 0.044 0.506 0.256
Platismatia glauca (L.) W. L. Culb. & C. F. Culb. vr 21 −0.047 0.002 −0.112 0.013 0.489 0.239
Ramalina fastigiata (Pers.) Ach. c21 −0.095 0.009 −0.146 0.021 0.483 0.233
Tephromela atra v. torulosa (Flot.) Hafellner r57 −0.515 0.265 0.185 0.034 −0.091 0.008
Bryophytes
Antitrichia curtipendula (Hedw.) Brid. r39 −0.208 0.043 0.125 0.016 0.661 0.437
Ctenidium molluscum (Hedw.) Mitt. c50 −0.45 0.203 0.387 0.15 0.473 0.223
Fissidens crispus Mont. r4 0.298 0.089 0.534 0.285 −0.003 0
Fissidens taxifolius Hedw. c11 0.327 0.107 0.539 0.29 0.092 0.009
Grimmia trichophylla Grev. c54 −0.233 0.054 0.043 0.002 0.516 0.266
Homalothecium sericeum (Hedw.) Schimp. r79 −0.535 0.286 0.141 0.02 0.641 0.41
Hypnum cupressiforme Hedw. vc 82 0.377 0.142 −0.73 0.532 −0.208 0.043
Isothecium alopecuroides (Lam. ex Dubois) Isov. c64 −0.384 0.147 0.738 0.545 0.373 0.139
Kindbergia praelonga (Hedw.) Ochyra c4 0.298 0.089 0.534 0.285 −0.003 0
Plasteurhynchium striatulum (Spruce) M. Fleisch. c11 0.473 0.223 0.285 0.081 −0.22 0.048
Pterigynandrum filiforme Hedw. c50 −0.653 0.427 0.247 0.061 0.354 0.125
Note: Only 53 species out of the 198 are reported, showing R2 ≥ 0.2 for at least one axis (evidenced in bold). Rarity status: vc, very
common; c, common; r, rare; vr, very rare.
e
ˇ
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228 G. Brunialti et al.
Caloplaca pyracea, Flavoparmelia caperata, Lecanora
expallens, Parmotrema perlatum, Physcia adscendens,
and the bryophyte Plasteurhynchium striatulum
(Table IV). Negative values of the first axis are
related to beech stands with an increasing gradient
of basal area (R2 = 0.264), diameter classes number
(DCN; R2 = 0.203), and old trees (R2 = 0.108). Five
lichens (Arthonia radiata, Fuscidea stiriaca, Lecanora
argentata, L. intumescens, Tephromela atra v. torulosa)
and three bryophytes (Ctenidium molluscum, Homal-
othecium sericeum, Pterigynandrum filiforme) are corre-
lated with these stands.
OG stands have positive values of the second axis
(Figure 2c and 2d) in relation to higher values of
basal area (R2 = 0.277), old trees (R2 = 0.277), and
a gradient of heterogeneity of the stands in terms of
forest structure (DCN: R2 = 0.417). Along this
gradient, six lichens (Arthonia spadicea, Chrysothrix
candelaris, Dimella pineti, Opegrapha vulgata, Phlyctis
agelaea, P. argena) and four bryophytes (Fissidens
crispus, F. taxifolius, Isothecium alopecuroides, Kindber-
gia praelonga) are mainly distributed (Table IV). On
the contrary, non-OG stands have negative values of
the second axis. Only Candelariella faginea,
Flavoparmelia soredians, Hyperphyscia adglutinata,
Lecanora hagenii, and P. adscendens among lichens
and Hypnum cupressiforme among bryophytes (Table
IV) are related to these stands.
Bryophyte (R2 = 0.338) and lichen (R2 = 0.350)
species richness are positively related to Axis 3
(Figure 2b and 2d). In particular, the higher crypto-
gamic diversity is related to OG stands showing an
increasing gradient of basal area (R2 = 0.303), old
trees (R2 = 0.181), DCN (R2 = 0.405), underwood
species richness (R2 = 0.218).
Along this gradient, 16 lichen species (in particu-
lar Evernia prunastri, Lobaria pulmonaria, Melano-
halea elegantula, Parmelia saxatilis, P. sulcata,
Pertusaria albescens, P. amara, P. flavida, P. pertusa,
P. slesvicensis, Phlyctis argena) and four bryophytes
(Antitrichia curtipendula, C. molluscum, Grimmia
trichophylla, H. sericeum) were mainly distributed
(Table IV), while only eight lichens were related to
negative values of the axis (mainly L. hagenii,
Lecidella elaeochroma). The majority of rare and very
rare lichens and bryophytes (16 out of 20 species,
Table IV) are related to OG beech stands (positive
values of Axes 2 and 3 and negative values of Axis 1)
and to increasing gradients of DCN, basal area, and
old trees.
Considering the two groups of organisms sepa-
rately, both for lichens (Table V) and bryophytes
(Table VI) a final NMS ordination with two-dimen-
sional solution was obtained (Figure 3). In both
ordinations, Axis 1 shows a gradient of vascular
plant species richness (tree species richness and
underwood species richness), corresponding to
Turkey oak stands (Figure 3a and 3c). Rare lichen
species are related to negative values of this axis
(Table V; Figure 3c and 3d) in relation to OG beech
forests characterized by higher structural heteroge-
neity (increasing gradient of DCN). On the
contrary, rare bryophyte species are not significantly
correlated with any gradient, while total bryophyte
species richness is mainly related to OG beech
stands (Table VI; Figure 3a and 3b).
Figure 3. NMS ordinations (Sørensen distance measure). Response variables: lichens (a, b) and bryophytes (c, d). (a) and (b) ordination of 28 plots in lichen species space (127 species): two-dimensional final solution, final stress of 13 in 40 runs of real data, p < 0.05 (mean stress =19.5) when compared with 50 randomized runs of the Monte Carlo test. (c) and (d) ordination of 28 plots in bryophyte species space (71 species): two-dimensional final solution, final stress of 18.7 in 40 runs of real data, p < 0.05 (mean stress = 19.7) when compared with 50 randomizedruns of the Monte Carlo test. Plots are categorized by forest continuity (b and d) and forest type (a and c). The length of overlaid vectors is proportional to Pearson R2 of variables with axis (only variables with R2 ≥ 0.2 are displayed). Abbreviations of variable names are as follows(Tables IV and V): OT, old trees; BA, basal area; DCN, diameter classes number; TSRich, tree species richness; USRich, understory species richness; BrSRich, total bryophyte species richness; RL%, percentage of rare lichen species.
Discussion
The selected predictor variables explained a signifi-
cant part of the variation in species richness and
composition of lichen and bryophyte communities,
confirming the important influence of forest struc-
ture and continuity on these organisms (see e.g.,
Rose 1992; Neitlich & McCune 1997; Ohlson et al.
1997; Gustafsson et al. 2004; Fritz et al. 2008).
In particular, higher species richness of bryophytes
and lichens was mostly related to OG stands charac-
terized by old trees, high levels of basal area, a broad
range of diameter classes, and high understory diver-
sity. In addition, these stands tended to harbor most
species of conservation importance with respect to
younger, structurally more homogeneous stands.
Similar results have been obtained by several
Table V. Lichens: correlation coefficients of the seven predictors with NMS ordination axes.
Predictors Abbreviations Axis 1 Axis 2
rR
2rR
2
Old trees OT −0.028 0.001 −0.467 0.218
Basal area BA −0.247 0.061 −0.651 0.423
Diameter classes number DCN −0.069 0.005 −0.710 0.504
Tree species richness TSRich 0.625 0.390 0.268 0.072
Understory species richness USRich 0.561 0.314 −0.295 0.087
Total bryophyte species richness BrSRich −0.190 0.036 −0.559 0.312
Percentage of rare bryophyte species RB% 0.185 0.034 −0.238 0.057
R2 ≥ 0.2 are reported in bold.
Note: The two axes represented 87.6% of the total variation in species composition (Axis 1: 35.2%; Axis 2: 52.3%).
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Cryptogams and Mediterranean old forests 229
authors, both in coniferous and in deciduous broad-
leaved forests (e.g., Hyvärinen et al. 1992; Gustafs-
son et al. 2004; Nordén et al. 2007; Fritz et al.
2008). As regards these latter forests, epiphyte rich-
ness was strongly linked to a combination of
substrate quantity, high stand age, and forest conti-
nuity (Lõhmus et al. 2007; Fritz et al. 2008). In
particular, Fritz et al. (2008) found that substrate
availability (i.e., old trees, large trees, deadwood) is
the most important variable correlated with red-
listed and indicator lichens and bryophytes.
As far as only the forest type is concerned, lichen
and bryophyte communities found in relation to
beech and oak stands were clearly separated. This
was mostly due to the structural differences between
the two forest types. Indeed, Turkey oak stands host
a higher vascular plant richness (both overstory and
understory), but they are very homogeneous with
regard to the age of trees (even-aged stands). For
this reason, despite the presence of a large number of
colonizing substrates, their homogeneous structure
leads to colonization by common species, which are
also better suited to live in the drier habitats of these
woods. In contrast, beech stands display a lower
vascular plant diversity, but a greater variability in
the distribution of diameter classes (multi-layered
tree stands). The presence of old trees provides a
very rich supply in microhabitats (OG qualities),
representing an important refuge for lichens and
mosses. Furthermore, beech stands are a well-lit and
very moist habitat, resulting in a light and humidity
conditions more suitable for the growth of species of
conservation concern (Rose 1992; Neitlich &
McCune 1997; Hilmo & Sastad 2001).
Another point to consider is the relationship
between the two forest types and the altitude in the
Mediterranean mountains. In general, beech stands
are mainly distributed at higher elevations with
respect to oak stands, and they are also less easily
reached due to the geomorphology of the territory.
Thus, a historical reason could explain the fewer
observations of red-listed species at lower altitudes:
these stands most likely were more affected by
logging due to a closer proximity to roads and
Figure 3. NMS ordinations (Sørensen distance measure). Response variables: lichens (a, b) and bryophytes (c, d). (a) and (b) ordination
of 28 plots in lichen species space (127 species): two-dimensional final solution, final stress of 13 in 40 runs of real data, p < 0.05 (mean
stress = 19.5) when compared with 50 randomized runs of the Monte Carlo test. (c) and (d) ordination of 28 plots in bryophyte species
space (71 species): two-dimensional final solution, final stress of 18.7 in 40 runs of real data, p < 0.05 (mean stress = 19.7) when com-
pared with 50 randomized runs of the Monte Carlo test. Plots are categorized by forest continuity (b and d) and forest type (a and c).
The length of overlaid vectors is proportional to Pearson R2 of variables with axis (only variables with R2 ≥ 0.2 are displayed). Abbrevia-
tions of variable names are as follows (Tables IV and V): OT, old trees; BA, basal area; DCN, diameter classes number; TSRich, tree
species richness; USRich, understory species richness; BrSRich, total bryophyte species richness; RL%, percentage of rare lichen species.
Downloaded by [Universita Studi la Sapienza], [S. Ravera] at 06:58 17 June 2014
230 G. Brunialti et al.
settlements. For this reason, oak woods may have
suffered more from forestry activities such as thin-
ning, by retaining even-aged trees, resulting in a
lower colonization probability for species of conser-
vation concern. This might be confirmed by the
evidence that considering managed forests, the
differences in species composition of lichens and
bryophytes between beech and Turkey oak forests
disappeared.
A qualitative (species composition) rather than a
quantitative (species richness) difference between
the two forest types has been found. This is
confirmed by the fact that only few species are
common to many plots while others are locally rare,
with little turnover between the lists of species of
both forest types. Thus, substrate and habitats are
important not only for biodiversity, but also espe-
cially for species composition, as firstly suggested by
Barkman (1958) and already shown in other situa-
tions (see e.g., Ohlson et al. 1997; Peck et al. 2004;
Ravera et al. 2006; Lõhmus et al. 2007). However,
the “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 also affect our results,
since the plots are small, while the survey area is very
large. Probably, a higher sampling density may lead
to a more homogeneous distribution of the species
that were sporadic in this survey.
The OG forests of our study are mainly character-
ized by higher basal area, many old trees, and a gradi-
ent of diameter classes (uneven-aged stands). For the
first two parameters, there is a large agreement on
their positive correlation with lichens and mosses
diversity and on their importance for endangered
species conservation (e.g., Peck & McCune 1997;
Gustafsson et al. 2004). On the other hand, to our
knowledge, this is the first time that the number of
diameter classes was used effectively as a parameter
explaining cryptogams communities variation. This
is one of the most important findings of this study,
since this variable well represents the uneven-aged
features of the stands and is also a good proxy of
maturity and complexity of forest ecosystems. Such
a prominent role of this structural variable has impor-
tant implications for several aspects of conservation
planning and forest management. In fact, most of the
rare species of bryophytes and lichens were related to
OG characteristics, represented by the gradients of
structural complexity of the forest.
Time of continuous forests is probably the main
factor enhancing colonization probability of rare
forest-dwelling species (Rose 1992; Humphrey
2002; Fritz et al. 2008). This, however, is strictly
related to the presence of highly stable habitats, such
as old trees (Nilsson et al. 1995; Boudreault et al.
2000; Fritz et al. 2008). Consequently, we cannot
effectively separate effects of continuity per se and
habitat quality factors of the variable “forest conti-
nuity.” Once again, there is the problem that the
concept of continuity is mainly based on correlative
assumptions, that is, we consider OG stands as all
the stands with OG characteristics (Ohlson et al.
1997). For this reason, it is difficult to understand
which factor is more important especially in the
selection of indicator species (Nordén & Appelqvist
2001; Rolstad et al. 2002; Burrascano et al. 2008).
Interestingly, some species regarded as indicators
of forest continuity, such as L. pulmonaria, A.
curtipendula, and H. sericeum (Rose 1992; Nilsson
et al. 1995; Campbell & Fredeen 2004; Fritz et al.
2008) are associated with OG forests in this study,
independently from forest type. The fact that these
species are quite common in the plots suggests that
they are not particularly site-specific and may thus
be regarded as suitable indicators of OG features
also in the Mediterranean forests.
Another interesting finding is that we found no
relationship between deadwood and lichen and
bryophyte communities (standing and fallen dead-
wood, the number of standing dead trees was also
excluded as not significant, along with other
structural variables, in the preparation of the
dataset). Contrastingly, deadwood is considered as a
Table VI. Bryophytes: correlation coefficients of the seven predictors with NMS ordination axes.
Predictors Abbreviations Axis 1 Axis 2
rR
2rR
2
Old trees OT −0.434 0.188 0.484 0.234
Basal area BA −0.361 0.130 0.596 0.355
Diameter classes number DCN −0.460 0.212 0.658 0.433
Tree species richness TSRich 0.480 0.230 −0.317 0.100
Understory species richness USRich 0.462 0.213 0.034 0.001
Total lichen species richness LSRich 0.141 0.020 0.417 0.174
Percentage of rare lichen species RL% −0.451 0.203 0.405 0.164
R2 ≥ 0.2 are reported in bold.
Note: The two axes represented 80.7% of the total variation in species composition (Axis 1: 41.0%; Axis 2: 39.6%).
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Cryptogams and Mediterranean old forests 231
fundamental structural component of OG forests
and several studies carried out in temperate and
boreal forests showed the importance of decaying
wood for biodiversity (see Humphrey 2005), also for
cryptogams (see Nordén et al. 2007), and even in
the Alps (Nascimbene et al. 2008). However, we
must critically analyze our findings in the light of the
adopted sampling design to obtain an exhaustive
explanation: only bryophytes were always collected
on deadwood, while we sampled only epiphytic
lichens growing on live trees. Moreover, our
outcomes are similar to those of Ohlson et al. (1997)
who found that the amount of deadwood was the
most important variable in determining species rich-
ness only for wood-inhabiting fungi and hepatics,
while no correlations were found for the other
bryophytes and for lichens. In our opinion, this is
particularly true in the Mediterranean forests where
the biodegradation of woods is probably faster
than in Northern Europe because of a higher
temperature.
Finally, we found a strong congruence in the
general structure of communities of the two groups
of organisms, showing a good relationship between
lichens and bryophytes. This is in contrast with the
findings of Pharo et al. (2000). However, if we
consider separately their response, we get slightly
different and more detailed information. In this
study, the main difference lies in the behavior of rare
species: lichens are more sensitive than bryophytes.
Indeed, although the total bryophyte richness is
positively related to OG stands, our results reflect
the general pattern that rare lichens were more
closely linked than rare bryophytes to stands with a
greater ecological continuity, due to a natural small-
scale disturbance (Nordén et al. 2007; Fritz et al.
2008). This is mostly in relation to the fact that
lichens have relatively narrower ecological require-
ments (e.g., for a long substrate continuity) than
bryophytes, which to a large extent may grow also on
other substrates (Nordén et al. 2007).
Conclusion
Our results suggest that lichen and mosses diversity
was deeply influenced by both the forest types and
the variables related to forest disturbance regime and
the deriving structure, making it often difficult to
discern the effect of each factor and confirming the
complexity of this topic.
The main differences between the two forest types
were qualitative and rare species were found mainly
in beech woods. At the same time, higher biodiver-
sity and the presence of rare species were related to
OG features potentially associated with forest conti-
nuity. The main predictors were related to structural
features and floristic diversity of vascular plants,
while deadwood failed to explain the variability of
lichen and bryophyte communities.
Substrate continuity rather than forest continuity
per se had a considerable importance. In particular,
the number of diameter classes has proved an excel-
lent predictor. Indeed, it can be considered a good
indicator of the complexity and maturity of the
forest, since it well represents the uneven-aged
stands.
Although the two groups of taxa are related to
each other, lichens seem to be more selective in
respect of stands with OG features. On the contrary,
bryophytes may be more easily dispersed and/or
have wider ecological amplitudes.
We can conclude that in the Mediterranean
forests, OG features and site-specific microhabitats
were in all probability more important than forest
temporal continuity per se. For this reason, in order
to develop long-term monitoring, we believe that it
is unwise to consider a priori a list of indicator
species of continuity, thus avoiding circular reason-
ing.
Our approach, on the other hand, may allow to
study in time and space the overall species richness
of cryptogams in relation to changes in the structure
and floristic diversity of the forest. Consequently, we
may obtain information of conservation concern
extrapolating from this finding outcome related to
the ecology of rare species.
Acknowledgments
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 are grateful to
Valerio Genovesi for his help in the field. We are also
grateful to the anonymous referees for improving the
manuscript with their important suggestions.
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