Characterization, structure and genetic dating of an old-growth beech-fir forest in the northern Apennines (Italy)

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Characterization, structure and genetic dating of anold-growth beech-fir forest in the northern Apennines(Italy)D. Travaglini a , D. Paffetti a , L. Bianchi a , A. Bottacci b , F. Bottalico a , G. Giovannini a ,A. Maltoni a , S. Nocentini a , C. Vettori c & G. Calamini aa Dipartimento di Economia, Ingegneria, Scienze e Tecnologie Agrarie e Forestali, Universityof Florence, Via San Bonaventura, 13, 50145, Florence, Italyb Corpo Forestale dello Stato, Ufficio Territoriale per la Biodiversità di Pratovecchio, ViaDante Alighieri, 41, 52015 Pratovecchio, Arezzo, Italyc Istituto di Genetica Vegetale, Consiglio Nazionale delle Ricerche, Via Madonna del Piano,10, 50019, Sesto Fiorentino, Florence, Italy

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To cite this article: D. Travaglini, D. Paffetti, L. Bianchi, A. Bottacci, F. Bottalico, G. Giovannini, A. Maltoni, S. Nocentini, C.Vettori & G. Calamini (2012): Characterization, structure and genetic dating of an old-growth beech-fir forest in the northernApennines (Italy), Plant Biosystems - An International Journal Dealing with all Aspects of Plant Biology: Official Journal of theSocieta Botanica Italiana, 146:1, 175-188

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OLD GROWTH FORESTS

Characterization, structure and genetic dating of an old-growthbeech-fir forest in the northern Apennines (Italy)

D. TRAVAGLINI1, D. PAFFETTI1, L. BIANCHI1, A. BOTTACCI2, F. BOTTALICO1,

G. GIOVANNINI1, A. MALTONI1, S. NOCENTINI1, C. VETTORI3, & G. CALAMINI1

1Dipartimento di Economia, Ingegneria, Scienze e Tecnologie Agrarie e Forestali, University of Florence, Via San

Bonaventura, 13, 50145 Florence, Italy, 2Corpo Forestale dello Stato, Ufficio Territoriale per la Biodiversita di Pratovecchio,

Via Dante Alighieri, 41, 52015 Pratovecchio, Arezzo, Italy, and 3Istituto di Genetica Vegetale, Consiglio Nazionale delle

Ricerche, Via Madonna del Piano, 10, 50019 Sesto Fiorentino, Florence, Italy

AbstractAn old-growth beech forest stand with silver fir within the strict forest reserve of Sasso Fratino has been examined with thefollowing aims: to characterize forest stand on the basis of classic forest parameters and to assess forest stand structure bymeans of spatial functions; to provide genetic dating of the beech population. Total census of size and position of living treesand deadwood was performed on a 9200 m2 permanent plot. Vertical distribution of crowns in the stand was assessed usingthe TSTRAT function, horizontal stand structure using spatial point pattern analysis. Genetic dating was performed on asample of beech trees. DNA was isolated and each individual was genotyped at four chloroplast microsatellite loci.Microsatellite profiles were compared with the profiles of control DNA of known haplotypes. Results show a multi-stratavertical structure, a horizontal structure characterized by small gaps (5160 m2) where silver fir regeneration sets in.Deadwood is present with all the decay classes and with relatively high volumes. Genetic dating ascribes the Sasso Fratinobeech stand to the ancestral haplotype 2: this population can therefore be considered a hot spot of haplotype diversity of theglacial refugia present in central Italy.

Keywords: Old-growth, stand structure, deadwood, genetics, Fagus sylvatica L., Abies alba Mill.

Introduction

Old-growth forests are forest ecosystems which have

developed without human disturbances for many years;

they are usually perceived as complex natural systems

composed of old trees and decaying woody materials

which are important habitat for many species.

According to the Forest Resource Assessment

(FAO-FRA 2010), primary forests (i.e. forest of

native species where there are no clearly visible

indications of human activities and the ecological

processes have not been significantly disturbed)

account for 36% of global forest area; the most part

of these forests are in America (66%), whilst in

Europe, if we exclude the Russian Federation,

primary forest are rare (0.4%).

In Italy, human pressure on forests has a very long

history and today there are no true primary forests in

the Italian peninsula (Motta 2002). However, in

some remote areas of the Alps and Apennines, often

within protected areas, there are forests which have

been left to natural evolution for many years with

potential old-growth features.

A large number of studies have been conducted in

old-growth forests worldwide addressing such di-

verse topics as carbon, nutrient and water cycling,

stand structure, population dynamics, disturbance

regimes and habitat diversity (Wirth et al. 2009).

In Italy, the first studies on the characterization

and monitoring of old-growth forests were initiated

by Pavari in 1954. Nevertheless, only since the end of

the last century the research has been focused on

these complex forest ecosystems (e.g. Paci &

Salbitano 1998; Motta 2002; Piovesan et al. 2005).

The interest on old-growth forest studies has been

recently renewed by national projects aimed to

increase the knowledge on old-growth forest stands

in the Alps and Apennines (Blasi 2010; Chirici &

Correspondence: L. Bianchi, Dipartimento di Economia, Ingegneria, Scienze e Tecnologie Agrarie e Forestali, University of Florence, Via San Bonaventura,

13, 50145 Florence, Italy. Tel: þ39 055 3288650. Fax: þ39 055 319179. Email: [email protected]

Plant Biosystems, Vol. 146, No. 1, March 2012, pp. 175–188

ISSN 1126-3504 print/ISSN 1724-5575 online ª 2012 Societa Botanica Italiana

http://dx.doi.org/10.1080/11263504.2011.650731

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Nocentini 2010; Marchetti & Blasi 2010; Piovesan

et al. 2010). In these projects, the following topics

were addressed: ecology (Marchetti et al. 2010) and

stand structure (Ciancio et al. 2010; Iovino et al.

2010; Manes et al. 2010; Palombo et al. 2010;

Piovesan et al. 2010), deadwood (Burrascano et al.

2008; Lombardi et al. 2010; Motta et al. 2010),

vascular flora (Sabatini et al. 2010), lichens and

bryophytes (Brunialti et al. 2010; Potenza & Fascetti

2010; Ravera et al. 2010), carbon stock (Piovesan

et al. 2010), genetic diversity (Vettori et al. 2010),

monitoring systems (Blasi et al. 2010; Corona et al.

2010; Di Paolo et al. 2010) and, finally, possible

indications from old-growth studies in supporting

forest management and planning in areas with long

standing human impact (Nocentini 2010).

Objectives

The aim of this study is to further develop knowledge

on old-growth beech-fir forests in Apennine environ-

ment. We selected a beech (Fagus sylvatica L.) forest

stand with silver fir (Abies alba Mill.) which has had

very low human impact until 1959 when it was

included in a strict forest reserve and left to natural

evolution. Specific objectives of this paper are: (1) to

characterize forest stand on the basis of classic forest

parameters; (2) to assess forest stand structure by

means of spatial functions and (3) to provide genetic

dating of the population by evaluating the ancestry of

the stand compared to beech glaciation refuges

present in Italy.

Results are discussed in relation to the possibility of

defining reference parameters for the detection of

old-growth forests in the Mediterranean environ-

ment.

Material and methods

Study area

The study has been carried out in the strict nature

reserve of Sasso Fratino within the National Park of

Foreste Casentinesi, Monte Falterona and Cam-

pigna. The reserve was created in 1959. It covers 764

ha going from the Apennine ridge (1520 m a.s.l.) to

an elevation of 650 m a.s.l. in the Romagna region.

Climate is temperate-oceanic; mean annual tem-

perature is 9.08C; annual rainfall is 1750 mm.

Orography is irregular with steep slopes and some

small, almost flat areas; mean slope is usually more

than 65%. The area lies on Miocene sandstone marl

series which originated Inceptisols with acid humus

and high biological activity. The prevalent forest

types are: pure beech forests above 1300 m a.s.l.;

beech and silver fir mixed forests between 800 and

1300 m a.s.l. and mixed deciduous oak forests below

800 m a.s.l. Ground vegetation is composed of mesic

species. Wildlife is abundant; ungulate populations

are large and their pressure on vegetation has been

observed, particularly on tree regeneration (Massei

1981; Paci & Salbitano 1998; Bottacci 2009; Bianchi

et al. 2011).

The forest stand is located in the municipal district

of Bagno di Romagna (FO), within the historical

core of the reserve, close to the resort locally named

‘‘Quota 900’’ (Lat. 43850038.073300; Long.

1184803.181600). The study area lies on a slightly

sloping ground (30%) with an eastern aspect, at an

altitude between 950 and 1000 m a.s.l. The ground

is undulating due to the presence of streams. The

forest stand is composed of beech with silver fir.

Ground vegetation is scarce.

In the core of the reserve silvicultural activities

ended not less than 70 years ago; forest exploitations

were discontinuous in the past and of low intensity

due to difficult access (Sansone 1915; Hofmann

1965, 1985).

Data

Fieldworks were carried out in 2009 within a

quadrangular plot 9200 m2 large.

The geographic coordinates of the plot’s corners

were recorded by a GPS Trimble GeoXT series

2008. In addition, the coordinates of four reference

points located at the corners of a square 1600 m2

large drawn within the plot were recorded by GPS.

The census of living trees and deadwood was

performed. All living trees with a diameter at breast

height (DBH) greater than 2.5 cm were inventoried.

For each tree, the species was noted and the DBH was

measured by a calliper; the total tree height, the height-

to-base of the live crown and the projection of tree

crowns by vertical sighting (four crown radii projec-

tion) were measured by Vertex IV Hypsometer.

Standing and downed dead trees, stumps and coarse

woody debris were also inventoried. Deadwood

measurements were carried out according to the

method described by Lombardi et al. (2010). Dead-

wood decay levels were assessed through Hunter’s

classification system (Hunter 1990).

The position of each living tree and deadwood

piece was recorded by measuring distance from the

nearest plot corner and the angle of this distance and

N. The angle was measured by a Suunto KB-14/360

R compass; the distance was measured using the

Vertex IV.

Mean age of the prevailing species was assessed by

extracting a couple of cores from three living trees

belonging to the most frequent diameter class; the

cores were extracted at a height of 1.3 m above

ground with an angle of 1208 between the two cores.

The rings were counted in the laboratory.

176 D. Travaglini et al.

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For genetic dating of the stand, a sample of wood

was taken at the stem base of 27 beech trees; the trees

were selected considering the distribution of beech

within the plot (Figure 1a); the number of sampled

trees varied between 1 and 3 in each 5 cm diameter

class, starting from class 40 to class 125, including a

sample from 2 trees in the smallest class. In addition,

a sample of plant material was taken both from beech

regeneration and from deadwood; the sample from

regeneration was extracted from six young trees less

than 1.3 m tall. The plant material was conserved in

the laboratory at7208C.

Analysis

Stand structural analysis. To characterize the struc-

ture of the stand, the following parameters were

used: number of stems (N) per hectare, basal area

(BA) per hectare and volume (V) per hectare, mean

diameter ( �D, i.e. the diameter of the mean basal area

tree), mean height (HL, i.e. the height of the mean

basal area tree), dominant height (H100, i.e. the mean

height of the 100 trees per hectare with the largest

diameters), standard deviation of diameters

(SDDBH) and standard deviation of heights (SDH).

For deadwood, the total volume and the decay level

were computed for each surveyed deadwood type.

Volumes of living and dead trees were computed

with a double entry volume equation (Castellani

et al. 1984); the volume of the stumps and the

volume of deadwood in the forest floor were

computed as described by Lombardi et al. (2010).

The following structural features were also ad-

dressed: vertical structure, stand density, canopy gaps,

horizontal structure, spatial interactions between pre-

vailing tree species and between canopy gaps and small

trees. In addition, the spatial pattern of standing and

downed deadwood was assessed. Structural features

were quantified by means of spatial functions.

The vertical distribution of crowns in the stand

was assessed using the TSTRAT function. This

function assigns individual trees to vertical strata or

canopy layers. To do this, TSTRAT defines multiple

vertical height cut-off points based on tree heights

and crown lengths and assigns individual trees to

vertical strata depending on the relative position of

tree crowns to these height cut-off points. The

algorithm considers a tree’s competition zone which

corresponds to the area at the top of the crown where

the majority of photosynthesis occurs (Latham et al.

1998). If the competition zone is equal to b, the

height cut-off point for the ith strata (Hsi) is equal to:

Hsi ¼ ð1� bÞ �CL þHBLC ð1Þ

where b ranges between 0 and 1; CL is the crown

length of the tallest tree (in case of trees of equivalent

height, the tree with the longest crown is considered

first by TSTRAT) and HBLC is the height-to-base

of the live crown of the tallest tree.

The height cut-off point of the upper stratum

(Hs1) is computed first by TSTRAT and all trees

having a total height equal to or greater than Hs1 are

placed in the upper stratum. Then, the cut-off points

of underlying strata are computed using Equation 1,

but excluding from computation the trees already

assigned to the stratum. The process is repeated until

all the trees are accounted for or until some

predefined lower limit for strata definition is reached.

In this study, we set a lower limit for strata at a

height of 5 m on the basis of field observation; all

trees with heights below this lower limit were placed

in the lower stratum. In the examined condition, the

use of b¼ 0.6 (Kutsch et al. 2009) produced a likely

distribution of crowns into vertical strata.

Stand density was measured on the basis of the

percentage canopy cover. For simplicity, the crowns

were shaped as circles with a radius equal to the

mean of the radii measured in the field. Stand

density was computed as the percentage of stand area

covered by crowns. Crown projection area was

assessed excluding crown overlapping and the

portion of the crowns outside the plot.

Canopy gaps were extracted and distinguished

from openings between trees (i.e. areas smaller than

that created by the loss of at least one whole crown).

To do this, the method based on morphological

functions described by Koukoulas and Blackburn

(2004) was applied to the crowns placed in the upper

stratum.

Horizontal stand structure was assessed using the

spatial point pattern analysis. In particular, the

univariate Ripley’s K function (Ripley 1977) was

applied to classify the horizontal structure into

random, regular or clustered (e.g. Kuuluvainen

et al. 1996; Motta & Edouard 2005). The Ripley’s

K function provides statements about changes trends

in the horizontal stand structure around individual

trees as the distance from a standpoint increases. In

practice, the function identifies the extent to which

the tree distribution pattern is more or less dense

than the random Poisson distribution as the distance

d from the tree base increases (Pretzsch 2010). In

case of n trees within a stand having an area equal to

A, the Ripley’s K function for the distance d is equal

to:

K dð Þ ¼ AXn

i¼1

Xn

j¼1

oijðdÞn2

for i 6¼ j ð2Þ

where oij(d) is the distance between the trees i and j.

In this study, the L(d) function, i.e. the transfor-

mation of K(d) developed by Besag (1977), was used

to identifying and testing deviation in the observed

Old-growth beech-fir forest in Italy 177

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Figure 1. (a) Spatial distribution of living trees and deadwood within the plot. (b) Canopy cover and canopy gaps seen from below. The

crowns are coloured according to their distribution into vertical strata. In the lower stratum (stratum 4), the crowns are numbered according

to the cluster distribution of tress in this stratum.

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point pattern from the random distribution. This

transformation linearizes K(d) and stabilizes the

variance; in addition, the results provided by L(d)

are easier to interpret as the function has an expected

value equal to 0 in case of random distribution:

L dð Þ ¼ffiffiffiffiffiffiffiffiffiffiffiKðdÞp

r� d for i 6¼ j ð3Þ

Horizontal spatial pattern was assessed for all trees

of the stand and for groups of trees grouped in

relation to tree species and the distribution of trees

into vertical strata; groups of trees with less than 30

individuals were not considered.

The L(d) function was computed for d ranging

from 1 to 50 m to limit margin effects; at each step,

the distance d was augmented by 1 m. The Monte

Carlo simulations were used to assess the signifi-

cance of deviation from random distribution; 99

randomizations were generated that provided a 95%

confidence envelop (Stoyan & Stoyan 1994). L(d)

greater than the envelop indicates a clustering

pattern; L(d) lower than the envelop indicates a

regular pattern; L(d) within the envelope indicates a

random pattern.

To investigate the spatial interaction between two

species, we used the bivariate K12(d) function which

is a generalization of K(d) function (Lotwick &

Silverman 1982):

K12 dð Þ ¼ n2K12ðdÞ þ n1K21ðdÞn1 þ n2

ð4Þ

where n1 and n2 are the number of trees of species 1

and 2, respectively.

The analysis was made using the L12(d) function

which is the transformation of K12(d) function:

L12 dð Þ ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiK12ðdÞ

p

r� d ð5Þ

The L12(d) function was computed for d ranging

from 1 to 25 m. To test the significance of deviation

from null hypothesis of spatial independence be-

tween tree species, we adopted a 95% confidence

envelop from the toroidal shift null model (Wiagand

& Moloney 2004; Barbeito et al. 2008). In case of

attraction between species 1 and species 2, L12(d) is

greater than the confidence envelope; in case of

repulsion between the two species, L12(d) is lower

than the confidence envelope; in case of spatial

independence between species 1 and species 2,

L12(d) is within the confidence envelope.

In this study, the L12(d) function was used to

investigate spatial interaction between the two

prevailing species in the stand. In addition, the

L12(d) function was used to test the potential

influence of canopy gaps on the regeneration proces-

ses by investigating the spatial relationships between

canopy gaps and trees assigned to the lower stratum

by TSTRAT. To do this, a grid-based approach was

used as proposed by Wiegand et al. (2006). Gaps

were represented as adjacent cells each with a side

0.25 m long. Cells were treated as points located at

the centre of each cell. The L12(d) function was then

used by keeping fix the position of gaps.

The spatial pattern of deadwood was also investi-

gated. In case of standing deadwood (standing dead

trees, snags and stumps), the L(d) function was used.

In case of lying deadwood (downed dead trees and

coarse woody debris), the mean direction of the

pieces of deadwood and the circular variance were

computed. Analogous to a standard deviation

measure, the circular variance tells how well the

directional mean vector represents the set of input

vectors. Circular variance ranges from 0 to 1: if all

the input vectors have very similar directions, the

circular variance is near to 0; when input vector

directions span the entire compass, the circular

variance is near 1. The directional mean vector was

then compared with the direction of the maximum

slope computed on the bases of contour lines

extracted from topographic map.

Genetic analysis. DNA was isolated from plant

material (100 mg as starting material) using the

DNeasy plant kit (QiAgen, Germany) following the

manufacturer specifications.

Each individual was genotyped at the following

four chloroplast microsatellite loci: ccmp4, ccmp7

(Weising and Gardner 1999), DT (Forward: 50-AATTGTTAATAATCCTTTCG-30; Reverse: 50-GTTTCTGATATATTTTTACCG-30) and OA

(Forward: 50-GAAACTGAAAAGATTGAATG-30;Reverse: 50-CCTCTTTCTATCAAAATATCC-30).

Polymerase Chain Reaction (PCR) amplifications

were performed in a Thermal Cycler model 9700

(Applied Biosystem, Foster, CA, USA) in a final

volume of 20 ml, with 4–40 ng of DNA, 5.4 pmoles of

each primer, 250 mM for each dNTPs, 2 ml of reaction

buffer, 2.5 mM MgCl2 and 1 U of Platinum Taq DNA

Table I. Number of stems (N), basal area (BA), volume (V), mean

diameter ( �D) and mean height (HL) of living trees.

Species

N

(n ha71)

BA

(m2 ha71)

V

(m3 ha71)

�D

(cm)

HL

(m)

F. sylvatica L. 97 43.80 984.9 75.8 40.3

A. alba Mill. 78 13.50 204.0 46.9 27.5

T. baccata L. 1 0.05 0.1 25.2 –

S. nigra L. 1 0.05 0.1 25.2 –

Total 177 57.40 1,189.1 – –

Old-growth beech-fir forest in Italy 179

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polymerase (Invitrogen, CA, USA). Amplification

thermal profile was as follows: first denaturation step

at 958C for 5 min, followed by 30 cycles (denaturation

at 948C for 1 min, annealing for 1 min at primer

temperature annealing and extension at 728C for

1 min) and a final elongation at 728C for 30 min.

PCR products were run on an automated sequencer

ABI 310 (Applied Biosystems), and sizing was carried

out with the GeneMapper1

vers. 4.0 (Applied Biosys-

tems).

The microsatellite profiles of the four loci were

compared simultaneously with the profiles of control

DNA of known haplotypes already characterized by

Vettori et al. (2004).

Figure 2. Stem number–diameter distribution for total trees (a), F. sylvatica L. (b) and A. alba Mill. (c), diameter–height curves (d) and

vertical structure (e).

Table II. Height cut-off point (Hs), number of stems, basal area (BA) and percentage canopy cover of vertical strata computed by TSTRAT

(*2 individuals of beech and 11 individuals of silver fir tall less than 5 m were assigned to the stratum 4).

Stratum Hs (m)

F. sylvatica L.

(n ha71)

A. alba Mill.

(n ha71)

T. baccata L.

(n ha71)

S. nigra L.

(n ha71)

BA

(m2 ha71)

Canopy

cover (%)

1 28.84 93 25 0 0 55.4 84.0

2 17.28 2 7 0 0 1.0 3.8

3 9.36 0 14 0 0 0.7 2.9

4 5.00* 2 32 1 1 0.3 3.4

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Results

Stand characteristics

Tree species composition was characterized by

beech and silver fir; European yew (Taxus

baccata L.), European black elderberry (Sambucus

nigra L.) and sycamore maple (Acer pseudoplatanus

L.) were sporadically represented within the

stand; the latter was not inventoried within the

study plot.

Beech is the prevailing species; with 54% of the

total number of trees, it contributes for more than

75% of total basal area and volume. Beech trees are

quite large: HL was equal to 40 m with a maximum

height of 45 m; �D was equal to 76 cm with a

maximum DBH of 126 cm. Silver fir, with approxi-

mately 44% of total number, accounts for less than

25% of basal area and volume. Fir trees are smaller,

HL was equal to 27 m with a maximum height of

44 m; �D was equal to 47 cm with a maximum DBH

of 105 cm (Table I).

Tree distribution in 5 cm diameter classes shows a

bimodal shape with one peak in the 75 cm diameter

class and the other one in the 10 cm class (Figure

2a). For beech, the distribution is unimodal, right-

skewed and rather uniform (Figure 2b); for silver fir,

the distribution was bimodal and more diversified

than for beech (Figure 2c). The higher diameter

differentiation of silver fir is highlighted by SDDBH:

for all the trees in the stand SDDBH is equal to

31.3 cm, for beech it is equal to 21.2 cm and for

silver fir 29.8 cm.

Ring count on cores extracted from beech trees in

the 70 cm diameter class ranges between 130 and

145. However, because the cores were extracted at

breast height, age of beech trees is expected to be

greater than this number; in addition, analysis

revealed that the centre of the stem was never

sampled by the cores.

Vertical structure

For the whole stand H100 was equal to 39 m. The

diameter–height curves for beech and silver fir are

shown in Figure 2d. The vertical distribution of

crowns computed by TSTRAT consisted of four

strata. The upper stratum (1) has a height cut-off

point equal to 29 m; the intermediate strata have a

cut-off points equal to 17 m (2) and 9 m (3),

respectively; for the lower stratum (4) the height

cut-off point was set to 5 m on the basis of field

observation. Table II shows the number of stems and

basal area computed for each stratum.

The distribution of crowns into strata was not

uniform, and the multi-strata profile accounted for

the forest stand was mostly due to silver fir as

shown in Figure 2e. Most of the trees, especially

beech, had their crowns within the upper stratum

whilst only silver fir had crowns within all the

vertical strata. The higher height differentiation of

silver fir is highlighted by SDH: for all the trees in

the stand SDH was equal to 14.0 m, for beech and

silver fir was equal to 6.2 m and 14.3 m, respec-

tively.

Table III shows the size (minimum, maximum and

mean) of diameters and crowns for each vertical

stratum.

Stand density and canopy gaps

The percentage canopy cover of the stand was equal

to 86%. Canopy coverage was rather continuous in

the upper stratum even if locally broken by canopy

gaps; in this stratum the percentage canopy cover

was equal to 84%. In the underlying strata, the

density was sparse: for strata 2, 3 and 4, the canopy

coverage was lower than 4% (Table II).

A total of nine canopy gaps were identified inside

the plot, which covered a total area of 764 m2 (8% of

the plot). Gap size varied between 40 and 60 m2, 80

and 100 m2 and 140 and 160 m2 (Figure 1b).

Horizontal structure and spatial interactions

The spatial point pattern analysis performed by

Besag’s L(d) function for all the trees in the stand

showed that stems have a random distribution at all

distances d from 1 to 50 m, with the exception of

d¼ 3–4 m where repulsion between stems occurred

(Figure 3a). Similar results were obtained for beech,

Table III. Minimum, maximum and mean size of both DBH and tree crowns in each stratum (standard deviation is in brackets).

F. sylvatica L. A. alba Mill.

DBH (cm) Crown area (m2) DBH Crown area (m2)

Stratum Min Max Mean Min Max Mean Min Max Mean Min Max Mean

1 42 126 75 (18) 29 371 157 (78) 38 105 75 (16) 18 107 56 (26)

2 36 51 43 (10) 65 73 69 (6) 12 47 34 (13) 11 56 35 (20)

3 – – – – – – 16 32 23 (5) 7 33 22 (8)

4 5 6 6 (1) 10 17 13 (5) 3 19 11 (4) 1 23 9 (6)

Old-growth beech-fir forest in Italy 181

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silver fir and trees assigned to the upper stratum

(stratum 1): beech had a random distribution with the

exception of d¼ 2–3 m (Figure 3b); silver fir had a

random distribution at all distances (Figure 3c); trees

in the upper stratum had a random distribution with

the exception of d¼ 1–6 m (Figure 3d). Repulsion

Figure 3. L(d) versus distance d for all trees (a), F. sylvatica L. (b), A. alba Mill. (c), trees assigned to the upper stratum (d), trees assigned to

the lower stratum (e), standing deadwood (h). L1,2(d) versus distance d between F. sylvatica L. and A. alba Mill. (f) and between canopy gaps

and group of trees in the lower stratum (g). Grey line is the 95% confidence envelop.

Table IV. Volume of deadwood per deadwood type.

Species

Standing dead

trees (m3 ha71)

Snag

(m3 ha71)

Downed dead

trees (m3 ha71)

Coarse woody

debris (m3 ha71)

Stumps

(m3 ha71)

Total

(m3 ha71)

F. sylvatica L. 0.00 0.03 0.00 21.34 0.00 21.37

A. alba Mill. 0.01 15.58 0.00 27.60 0.61 43.80

Other species 0.00 0.00 0.00 0.06 0.00 0.06

Total 0.01 15.61 0.00 49.00 0.61 65.23

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found at the shorter distances can be explained as an

effect of the competition between trees.

The stems in the lower stratum (stratum 4)

showed a different spatial pattern. In this stratum,

which is mainly composed of silver firs, stems were

significantly clustered at distances between 5 and

17 m; for distances outside this range the stems

had a random distribution (Figure 3e). On the

basis of this result, seven groups of trees were

identified inside stratum 4, one group of beech and

six groups of silver fir; the groups were formed by

individuals located at a distance of 5–17 m each

from the other. The group of beech consists of

only 2 individuals, whilst the group of silver fir

consists of a number of individuals ranging from 2

to 8 (Figure 1b).

The spatial relationships calculated by L12(d)

function between beech and silver fir and between

canopy gaps and groups of trees in the lower stratum

produced the following results: spatial independence

was found between beech and silver fir (Figure 3f);

attraction was found between gaps and groups of

trees in the lower stratum between 1 m and 8 m

(Figure 3g).

Deadwood

The total volume of deadwood was 65 m3 ha71, 2/3

of which was silver fir. The ratio between dead and

living volume is equal to 5.5%.

Most of the deadwood lies on the ground as

branches and stems pieces, equally distributed

between beech and silver fir. In addition, standing

dead trees, snags and silver fir stumps occurred

inside the plot (Table IV).

Standing dead trees and snags were included

within vertical strata 3 and 4 and have a diameter

at the tree base ranging between 6 and 110 cm.

Stump were naturally originated and have a diameter

at the base ranging between 17 and 65 cm. All the

decay classes were found in the study plot. Decay

classes 4 and 5 represent almost 50% of total

deadwood volume (cf. Lombardi et al. 2010).

Standing deadwood (standing dead trees, snags

and stumps) showed a random distribution at

distances lower than 36 m (Figure 3h). Lying dead-

wood (downed dead trees and coarse woody debris)

was uniformly distributed across the study plot

(Figure 1a). The directional mean vector of

lying deadwood was 898N, with a circular variance

of 0.32.

Genetic dating

All the individuals showed the same chloroplast

microsatellite allelic combination (311, 222, 115 and

143) and a single haplotype was identified. The

comparison between microsatellite profiles of the

four loci and control DNA of known haplotypes

(Vettori et al. 2004) showed that the only haplotype

in the Sasso Fratino stand was haplotype 2 (Table

V).

This haplotype corresponds to one of the most

ancestral haplotypes present in the glacial refugia in

Italy. It is distributed in the western Alps, whilst it is

rare along the Apennine chain where it is present

only in two Italian locations: Passo dei Mandrioli –

Bagno di Romangna (FO) and Monte Falterona –

Stia (AR; Figure 4).

Discussion

The Sasso Fratino stand we have studied has

distinctive characteristics with respect to Italian

beech forests. Basal area and standing volume are,

respectively, two times and five times higher than

mean values reported by the National Forest

Inventory (INFC, Inventario Nazionale delle Foreste

e dei Serbatoi Forestali di Carbonio) for beech

forests; deadwood volume is eight times greater than

that reported by INFC (2005).

Some similarities can be found with other old-

growth beech forests along the Italian peninsula. For

instance, in the central Apennines, Piovesan et al.

(2010) found that basal area, standing volume and

deadwood volume range between 41 and 48 m2

ha71, 497 and 715 m3 ha71, 19 and 91 m3 ha71. In

southern Italy, Iovino et al. (2010) found a dead-

wood volume of about 70 m3 ha71, a basal area

ranging between 26 and 70 m2 ha71 and a standing

volume between 390 and 972 m3 ha71. For beech

forest stands, the following data are reported by

Lombardi et al. (2010): living volume between 666

and 1030 m3 ha71 and deadwood volume between

26 and 89 m3 ha71.

Tree size and frequency of large trees are

additional distinctive characteristics of the examined

forest stand. The unusual values of mean diameter

and mean height measured within the plot, denoting

suitable site conditions for beech and silver fir, are

higher than those reported for other old-growth

forests in the Apennines (Iovino et al. 2010; Manetti

et al. 2010). At Sasso Fratino, the number of trees

with a DBH greater than 70 cm is equal to 68 trees

per hectare (50 were beech and 18 silver fir), which

correspond to 38% of the total number of stems. In

the beech stand of Cozzo Ferriero (PZ), Iovino et al.

(2010) found a number of stems with DBH greater

than 60 cm equal to 27%; 25–30 stems per hectare

with a DBH greater than 70 cm are reported by

Piovesan et al. (2010) for old-growth beech forest

stands in the central Apennines. At Sasso Fratino,

the number of trees taller than 40 m is 46 trees per

hectare (36 were beech and 10 silver fir), which

Old-growth beech-fir forest in Italy 183

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correspond to 26% of the total number of stems. It is

worth noting that the maximum beech height

measured at Sasso Fratino (45 m) falls within the

range of maximum heights (44.3–49 m) reported for

this species in central and southern Europe (Holeksa

et al. 2009).

The stand structure analysis revealed additional

distinctive characteristics. Under the examined con-

ditions, tree species composition is dominated by

beech; however, a considerable presence of silver fir

was found which gives the stand a multi-strata profile

and a larger diameter differentiation. This observa-

tion is of some importance if we consider that silver

fir disappeared on large areas of the Apennine chain

due to past forest management of beech forests

(Nocentini 2009; Iovino et al. 2010).

The size of canopy gaps was relatively small having

an area ranging between 40 and 160 m2; the

Figure 4. Comparison between Sasso Fratino and the glacial refugia of F. sylvatica L. in Italy (Vettori et al. 2004).

Table V. Description of the four haplotypes identified by

combining four chloroplast microsatellite loci (the alleles of each

locus is expressed in base pair).

Haplotype

Locus

OA DT ccmp4 ccmp7

3 313 222 115 143

5 314 223 115 142

2 311 222 115 143

8 313 223 115 142

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maximum area measured for canopy gaps corre-

sponds, in the upper stratum, to the mean crown

area of a beech and three times to the mean crown

area of a silver fir. These gap sizes are in line with

those reported by Paci and Ciampelli (1996) for the

Sasso Fratino forest. These authors, on the basis of

studies conducted on forest regeneration in response

to the opening of gaps, found that the regeneration of

shade tolerant species, like beech and silver fir, is

favoured by small and medium size gaps (5400 m2).

The tendency of silver fir to regenerate in the

presence of small gaps (200 m2) has been observed

by Ciancio et al. (1985) in the Calabrian silver fir

forests in southern Apennine and more recently by

Albanesi et al. (2008).

Beech regeneration was scarcely represented with-

in the examined plot, whilst silver fir regeneration

was relatively abundant if we consider as regenera-

tion trees in the lower stratum. The distribution of

regeneration was clustered and clusters were close to

the gaps, usually within 8 m from them. This result

confirms the relationships between silver fir regene-

ration and small canopy gaps.

In the studied area, most of deadwood consists of

branches and stem pieces lying on the ground. A

large range of sizes and decay classes was found for

all deadwood components. However, the occurrence

of large standing and downed trees, which usually

characterizes the last stages of stand development,

was not so high within the stand where we found only

eight pieces of deadwood with a diameter470 cm.

Lying deadwood had a directional mean vector very

similar to the direction of the maximum slope. As

observed in other parts of the Sasso Fratino forest,

slope, together with flowing rainfall and snow

thawing, might affect the layout of lying deadwood

and, especially on steep slopes, it can favour move-

ment and deposition of woody materials towards

creeks and streams.

Old-growth forests are considered to have great

value for species conservation by providing a special

habitat for an array of forest-dependent wildlife.

These older populations may also serve as reservoirs

of genetic diversity and reproductive fitness, impor-

tant for maintaining populations of native trees

under pressure from environmental changes (Mos-

seler et al. 2003). Therefore, it can be supposed that

old-growth forests are ancestral sites for beech, and

genetic analysis of chloroplast DNA can permit the

dating of a population defining its ancestrality.

Previous studies conducted by palaeobotanical

and genetic analyses on Fagus spp. have indicated

that: (i) at the end of Tertiary period the ancestral

Fagus orientalis complex was present in Italy and that

only at the beginning of the Pliocene F. sylvatica

became differentiated from F. orientalis, slowly turn-

ing to a predominant role among the Fagus species in

West Europe (Paffetti et al. 2007); (ii) beech survived

the last glacial period in multiple refuge areas; (iii)

central European refugia were separated from the

Mediterranean refugia (Magri et al. 2006) and (iv)

the Italian peninsula was one of the main European

refugia during the last glaciation for many forest tree

species (Petit et al. 2003).

In particular, the last glacial period has determined

a fragmentation event which had the most important

role in shaping the genetic structure of the present

Italian beech forests. A remarkable geographical

subdivision of chloroplast genetic diversity in Italian

beech was found, and the populations displaying

high divergence were in central–southern Italy

(Vettori et al. 2004).

Therefore, considering that the genetic dating

ascribes the Sasso Fratino beech stand to the

ancestral haplotype 2, this population can be con-

sidered a hot spot of haplotype diversity of the glacial

refugia present in central Italy. This haplotype 2 was

previously detected in the northern Apennines

(Vettori et al. 2004), and therefore, it can be assumed

that during the glacial periods of the Quaternary, this

haplotype remained trapped in these area. In fact, the

beech populations in Italy were mainly restricted to a

few and/or small areas (especially in the centre-south;

Magri 1998). Therefore, it can be supposed that with

the retreat of the glaciers the populations spread to

higher altitudes and to northern latitudes, thereby

coming into contact and mixing haplotypes. Our

results are in agreement with Magri (1998) and

Vettori et al. (2004), who hypothesized, based on

pollen analysis and chloroplast genetic diversity,

respectively, that the northern beech populations

originated from the Apennine region, whilst Slovenia

(the Balkans) might have been the starting point of

the recolonization of the eastern Alps. Therefore, the

actual population of Sasso Fratino is the descendent

of the autochthone ancestral beech population pre-

sent during last glaciation and it can be dated to

15,000 years ago, representing an important ‘‘genetic

diversity reserve’’ which deserves high conservation

priority.

Conclusions

Results obtained within the strict reserve of Sasso

Fratino can provide information on potential attri-

butes characterizing old-growthness of Mediterra-

nean beech forest stands. Tree species composition is

an attribute that must be considered in relation to

site condition and forest history. In the past, species

like silver fir were quite common within beech stands

in the Apennine mountain area, whilst pure and

uniform beech forests are often the results of past

forest management (Burrascano et al. 2008; Nocen-

tini 2009; Vrska et al. 2009).

Old-growth beech-fir forest in Italy 185

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Vertical structure is another important attribute

which is correlated to species composition. At Sasso

Fratino, the stand structure is multi-strata. Under

the examined condition, silver fir plays an important

role in this regard having a higher diameter and

height differentiation than beech.

Concerning deadwood, even though a large range

of sizes and decay classes was found for all deadwood

components, however, the occurrence of large

standing and downed trees, and dead/living volume

ratio, which usually characterizes the last stages of

stand development, was not so high within the stand.

The number of large trees is a parameter used to

characterize old-growthness of forest stands. In

beech dominated forests of central Europe, Nilsson

et al. (2002) found a number of trees with a DBH

greater than 70 cm of about 30 stems per hectare.

This density of large trees has been found in the

Apennine beech forests by Piovesan et al. (2010) and

it is confirmed by our study. However, it is worth

noting that the occurrence of large trees in a stand is

very dependent on site conditions and forest history

and, as such, its use as old-growthness indicator

must be checked.

Forest genetics can play an important role for the

identification and characterization of old-growth

forests. In this study, genetic analysis has demon-

strated that the beech of Sasso Fratino belongs to a

glacial refugia of the northern Apennines and that

this population is the descendent of the rare

autochthonous ancestral beech population which

was present during the last glaciation.

Finally, although the Sasso Fratino beech-fir old-

growth stand cannot be taken as an exact ‘‘model’’

for managing other beech stands, nevertheless it can

provide some indication for forest management.

Specifically, our structural analysis pointed out that

the canopy gaps are relatively small and that there is a

spatial relationship between silver fir regeneration

and canopy gaps. Our findings confirm that forest

management for Apennine beech forest stands with

the object of favouring mixture with silver fir could

be based on a small group selection system opening

gaps5200 m2 in the upper forest canopy. But only

continuous monitoring of stand reaction to this type

of treatment will provide the basis for an adaptive

management approach suited to the evolution and

characters of each individual stand.

Acknowledgements

This work was funded by the Italian Ministry of

Education, University and Research within the

framework of the project PRIN2007 ‘‘Innovative

methods for the identification, characterization and

management of old-growth forests in the Mediterra-

nean environment’’ (National Coordinator: G. Chir-

ici). The authors wish to thank the National Forest

Service (Corpo Forestale dello Stato) for its support

in the fieldworks.

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