Forest ecosystem carbon
accumulation during a secondary
succession in the Eastern Prealps
of Italy
GIORGIO ALBERTI1*, ALESSANDRO PERESSOTTI1, PIETRO PIUSSI2
and GIUSEPPE ZERBI2
1 Department
of Agriculture and Environmental Sciences, University of Udine, Udine, Italy
of Agriculture and Forest Sciences and Technologies, University of Firenze, Firenze, Italy
*Corresponding author. E-mail: [email protected]
2 Department
Summary
Land use changes represent one of the most important components of global environmental change.
In most European countries, the transformed economies and social conditions of previous decades
have had consequences in terms of agriculture intensification, industrialization and migration of
people from the rural areas. As a consequence, areas of marginal agriculture were abandoned
leading to secondary successions.
This research studied the effects of the natural recovery of abandoned lands on carbon pools using a
chronosequence approach of mixed ash (Fraxinus excelsior L.) and sycamore (Acer pseudoplatanus L.)
stands in the Eastern Italian Prealps. A series of five formerly cultivated sites spanning a range of
40–75 years since agricultural abandonment and a meadow were selected. The dominant sink for the
atmospheric CO2 within these secondary forests seems to be live wood while the soil played a much
smaller role. The ecosystem carbon stock increased at a mean rate of 1.18 Mg C ha−1 y−1 during the
chronosequence. However, a difference in the carbon accumulation in the different pools was detected.
Introduction
Since the origin of agriculture, the human population and their consumption of resources have
both increased and forest and other natural areas
have been gradually transformed into farmland
and pastureland. Although FAO (2001) reports
that between 1990 and 2000 the global annual
forest area decreased by about 9391 103 ha, during the last century, in the mid-latitudes of the
Northern hemisphere, the major changes in the
economic and social conditions resulted in agriculture intensification, industrialization and the
© Institute of Chartered Foresters, 2008. All rights reserved.
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migration of rural population away from agricultural areas. As a consequence, areas of marginal
agriculture were abandoned leading to secondary successions. According to the Global Forest
Resources Assessment (FAO, 2001), a secondary
forest can be defined as ‘forest regenerated largely
through natural processes after significant human
or natural disturbance of the original forest vegetation’. The disturbance may have occurred
at a single point in time or over an extended
period. In the present research, we consider
secondary forests as all the regenerated stands on
abandoned meadows. Natural forest expansion
Forestry, Vol. 81, No. 1, 2008. doi:10.1093/forestry/cpm026
Advance Access publication date 29 February 2008
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FORESTRY
on abandoned crops, pastures or meadows is taking place in Europe (Mather, 1992; Piussi, 2000)
and in North America (Houghton and Hackler,
2000; Knops and Tilman, 2000). In Italy, according to the National Statistics Bureau, during the
last 50 years the total forest area increased by
14.9 per cent and this increase due to secondary
successions took place both in the Alps and the
Appenines (Piussi, 2002; Corona et al., 2005).
Land use changes play an important role in CO2
exchange between the terrestrial biosphere and
the atmosphere. Globally, ~156 Pg C was emitted
as CO2 into the atmosphere by land use change
(deforestation) from 1850 to 2000 (Houghton,
2003). However, during the last two decades, terrestrial ecosystems represent net sinks of carbon
as a result of different activities: land use practices; stands derived from secondary successions
in middle and high latitudes; N deposition and
climate change (IPCC, 2001). The complex nature of the interactions among land use changes,
anthropogenic activities and the environment on
the carbon cycle is just beginning to be explained
and critical gaps remain in our knowledge (i.e.
influence of past land use; equilibrium between
C input and C output). Furthermore, a key uncertainty is the role that land use change and forest
management practices can play in carbon cycling
and carbon sequestration (Schulze et al., 1999)
and how to calculate the changes in carbon stocks
associated with land use changes during the commitment period of the Kyoto Protocol (Valentini
et al., 2000).
This research studied the effects of natural forest recovery of abandoned lands on carbon pools.
The following questions were addressed:
1
How does total ecosystem C storage change
over time?
2 Which pool (soil or vegetation) is the dominant C sink?
To address the above questions and to evaluate carbon stock changes since the beginning of
colonization, a chronosequence approach was
used (Thuille et al., 2000; Hooker and Compton, 2003). A chronosequence stand of mixed
ash (Fraxinus excelsior L.) and sycamore (Acer
pseudoplatanus L.) in the Eastern Prealps was considered. A series of five formerly cultivated sites
spanning a range of 40–75 years since agricultural abandonment and a meadow were selected.
All the forest sites have similar climate and soil
and land use history.
Methods
Study area
The study area is located on the Eastern Prealps
of Friuli Venezia Giulia (Italy) (46° 12′ N, 12°
20′ E). The elevation is ~600 m a.s.l. and the
mean annual temperature is 10°C with a mean
temperature of ~0°C during winter and an annual rainfall of about 2500–3000 mm. Soil can
be classified as Cambisols. Land abandonment in
these formerly agricultural lands occurred during
the last century because of social and economic
changes, leaving large areas of the landscape unmanaged (Salbitano, 1987).
Site selection
Within the study area, the land use history was
analysed using digital orthophoto images and
the 1823 land ownership register and its following modification. Using the results of this analysis, a chronosequence consisting of six phases
was chosen (i.e. a managed meadow and five
secondary forest stands) that met all the following criteria:
1
2
3
4
evidence of historical agricultural use before
1957;
dominance of ash and sycamore;
minimum anthropogenic disturbance;
accessibility.
Four random replicate plots of 25 × 10 m within
each stand were located. The age of each tree
within the plots was determined using an increment core taken downslope at ~25 cm above the
ground. As secondary succession generally takes
place during several years, it is difficult to determine a precise average age for each stand. Using
data from sample trees, a non-linear relationship
between time and tree density was established for
each plot using a modified Richards logistic function; the annual increment in tree number (n yr−1)
at each year was then calculated (Figure 1). Because some trees could have been present before
the abandonment, stand age was estimated as the
4.3 ± 0.5
2.3 ± 1.1
5.7 ± 2.8
2.9 ± 0.9
5.9 ± 1.1
173 ± 26
128 ± 7
183 ± 11
122 ± 22
325 ± 31
Aboveground biomass
3.0 ± 0.5
1.9 ± 1.1
4.0 ± 2.7
2.3 ± 0.9
5.0 ± 1.1
33 ± 6
25 ± 2
35 ± 3
23 ± 5
62 ± 7
0.8 ± 0.1
0.5 ± 0.3
1.1 ± 0.7
0.6 ± 0.2
1.1 ± 0.2
Within each plot, live and dead standing trees,
stems and stumps were identified, labelled and
mapped. Stem origin (i.e. seed or coppice) was
registered; diameter at breast height (1.30 m;
d.b.h.) and total height were measured. Aboveground total biomass (stem, branches and foliage)
was calculated using species-specific allometric
equations (Ter-Mikaelian and Korzukhin, 1997;
Alberti et al., 2005) or the method proposed by
Ketterings et al. (2001) for the species lacking an
allometric equation in literature. Shrubs (mainly
Corylus avellana L.) volume was estimated using
the following equation:
V = 0.5 p/4 Dm2 H mn
(1)
where Dm is the average d.b.h. of the stems for
each stump, Hm is the average height and n is the
number of stem. Shrub volume was converted to
biomass by using a wood density of 520 kg m−3
(IPCC, 2003).
Root biomass was estimated using a root : shoot
biomass ratio of 0.24 (Cairns et al., 1997; Brown,
2002).
Leaf area index (LAI; m2 m−2) in each stand
was measured using a LiCor-2000 plant canopy
analyzer (LiCor Biosciences, Lincoln, NE, USA).
LAI was partitioned among species following the
corresponding percentages of wood basal area
(Alberti et al., 2005). Three branches for each
species were collected at the end of July from
the upper part of the crown and the ratio between dry weight and leaf area (measured using
a LiCor-3000 leaf area metre) was calculated
(specific leaf mass, SLM in g cm−2). Foliage mass
was obtained using the following equation:
SE = Standard error.
Grassland 1308 ± 273 100 ± 35
Grassland
970 ± 87 220 ± 182
Grassland 1130 ± 181 210 ± 77
Grassland 1950 ± 426 760 ± 258
Grassland
980 ± 207 120 ± 20
40
50
55
55
75
600
660
660
700
580
Cambisols
Cambisols
Cambisols
Cambisols
Cambisols
139 ± 25
103 ± 25
147 ± 11
98 ± 21
261 ± 30
fd1
Previous
land use
Age
(years) Elevation (m)
3
10th percentile of the annual tree number increment distribution (Alberti et al., in preparation).
Plot characteristics are reported in Table 1.
Soil type
Stem biomass
Root biomass
Total biomass
No. of
living trees Living trees Dead trees Living trees Dead trees Living trees Dead trees
(n ha−1)
(Mg ha−1) (Mg ha−1) (Mg ha−1) (Mg ha−1) (Mg ha−1) (Mg ha−1)
No. of
living trees
(n ha−1)
Table 1: General features of the five stands (averages ± 1 SE; n = 4)
SECONDARY SUCCESSION ON EASTERN PREALPS
Bf = 10 ´ SLM ´ LAI s ,
(2)
where Bf is foliage biomass (kg m−2), SLM
(g cm−2) is the specific leaf mass and LAIs (m2 m−2)
is the LAI for the considered species.
Leaf dry material was then ground to a fine
powder and analysed for total C and N in a CHN
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Figure 1. Five idealized stages in stand development can be recognized during a secondary succession.
At initiation (I), seedlings are rarely affected by competition with other trees. At canopy closure, stem
exclusion begins. As the overstorey trees approach maximum height, the canopy opens and an understorey
is re-initiated. Solid line represents number of trees sampled vs year, dashed line represents annual increment
in tree number. Stand age was estimated as the 10th percentile of the annual tree number increment
distribution (initiation stage; from Alberti et al., 2007).
Elemental Analyzer (NA1500 Series 2, Carlo Erba
Instruments, Rodano, Italy).
Subtracting leaf biomass from aboveground
biomass, wood biomass (stem + branches) was
obtained and converted to carbon stock using a
coefficient of 0.50 gC g−1 dry mass.
To determine the meadow biomass, a plot
of 50 × 20 m was located at the centre of the
meadow at the end of July. Within four 1 m2
square sub-plots, aboveground biomass and roots
were collected and their fresh weight determined
separately. Samples were then dried at 70°C and
sub-samples analysed for C and N content using
the CHN Elemental Analyzer.
Woody debris
Standing dead trees were labelled during stand
survey; d.b.h. and total height were recorded.
Volume was calculated using the equation:
2
V = 0.5 π/4 D1.30
H
(3)
where D1.30 is the d.b.h. in cm and H is total
height in m.
The volume was then converted to biomass
using the density values determined for the first
woody debris decay class (see below). C and N
concentrations (per cent) were also assumed to be
the same of this decay class.
SECONDARY SUCCESSION ON EASTERN PREALPS
Deadwood on forest floor was separated into
fine wood debris (FWD; <2 cm diameter) and
coarse woody debris (CWD; >2 cm diameter).
For CWD, the transect method used by Harmon
and Sexton (1996) was applied. Within each
plot, a 25-m length linear transect was set up.
The decay class and diameter of each deadwood
fragment crossing the line were labelled. Three
decay classes were established: (1) wood hard
but not stained, visible rings, bark intact; (2)
wood hard but not stained, rings visible, bark
sloughed off; (3) advanced wood decay with loss
of original form, wood friable. The formula to
calculate the CWD volume (VCWD in m3 ha−1) for
each transect is (Harmon and Sexton, 1996):
VCWD
 d2 
= 9.869 × ∑ 
,
 8L 
(4)
where d is the fragment diameter (m) and L is
transect length (L = 25 m). To convert volume to
biomass, basic density (dry weight/fresh volume)
was determined for each decay class collecting
three sample for each class and transect. Fresh
volume of the materials was measured by immersion in water before drying them at 102°C for 48
hours to measure dry weight. Samples were then
reduced to sawdust and sub-samples were collected for C and N analysis using a CHN Elemental Analyzer. C and N concentrations were then
multiplied for dry biomass to obtain total carbon
and nitrogen stocks in this compartment.
FWD was included in measurements of the forest
floor; litter was defined as the L horizon according
to Green et al. (1993). FWD and litter were collected from a 1 × 1 m sub-plot randomly located
within each plot. Material was stored at 4°C and
total fresh weight was recorded after arrival in
the laboratory. Fresh weight of four sub-samples
was also recorded; these samples were then dried
at 70°C until constant weight was attained and
dry weight was determined. Using the average
ratio between dry and fresh weight of these subsamples, total fresh weight was converted in dry
biomass. Sub-samples were then reduced to fine
powder and prepared for C and N analysis.
Soil
Soil samples were collected from the centre of
each plot. In each selected point, after measuring
5
organic horizon thickness, eight soil cores were
collected after removal of the litter layer (0–30
cm). Prior to processing, samples were kept at
4°C. Once in the lab, each sample was mixed and
sieved through a 2-mm sieve. Dried material was
ground to a fine powder, treated with HCl 2 : 1
to remove carbonates and then analyzed for organic C and N by the CHN-Elemental Analyzer.
Average soil bulk density to a depth of 30 cm
was estimated in the centre of each plot following the excavation method (Elliott et al., 1999).
Calculations and statistical analysis
Changes in C pool sizes during the chronosequence were analysed by simple linear regression
using time since abandonment as the independent variable: rates of change were estimated
using the slope derived from linear regression of
pool C content vs stand age. The rates calculated
using this approach are net rates (Hooker and
Compton, 2003). The level of significance for all
the analysis was P < 0.05. When data for a given
component (i.e. volume or total carbon) appeared
to depart from the linear model, non-linear curve
fitting was used to describe the shape of the relationship. Non-linear analysis was performed
using a modified Gauss–Newton procedure of
least squares estimation. Biomass–time relationship was described using a modification of the
Richards logistic function (Cooper, 1983):
β
y = Bmin + Bmax 1 − e(−α age)  ,
(5)
where Bmin equals the minimum pool size, Bmax
the maximum increase in pool size and α and β
are coefficients controlling the rate and the inflection point of the sinusoidal curve.
Results
Plant biomass and carbon
Total leaf biomass ranged between 2.0 and 2.8
Mg ha−1, total C between 0.9 and 1.2 Mg ha−1
and total N between 0.02 and 0.03 Mg ha−1
(Table 2).
Stem carbon stock increased during the chronosequence at a mean rate of 1.69 Mg ha−1 yr−1
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(R2 = 0.76, P < 0.05) and most of the C was sequestered in the bole wood (77 per cent). Richard’s model fitted the data well (Figure 2) with
the exception of site T2 because of the presence
of large trees pre-existing the abandonment.
Therefore, the model was estimated excluding
this site. The maximum rate of C annual increment according to this model occurs at 55 year
after colonization (5.31 Mg ha−1 yr−1). As far
as pre-existing trees are concerned, Rackham
(1995), in similar situations, reports that ash and
other hardwood species, which were useful for
timber or fodder production, were often maintained within the edges and small woodlands.
Furthermore, Piussi (1998) reports that over a
large part of the territory it was common practice
to plant alder in meadows in order to improve
grass production.
Woody debris
The number of dead trees ranged from 100 ha−1 in
the 40 years old stand to 760 ha−1 in the 55 years
old stand. Total biomass of dead trees ranged
from 1.9 to 4.8 Mg ha−1. No significant relationships (P > 0.05) between volume, biomass, total
C and N vs age were found while the C : N ratio
increased with stand age at a mean rate of 1.75 g
C (g N)−1 yr−1 (R2 = 0.77, P < 0.01).
CWD volume, biomass and C : N ratio slightly
increased with time (Table 3) while N remained
constant. CWD was 2.7 Mg C ha−1 in the
40-year-old stand and 7.5 Mg C ha−1 in the oldest
stand and increased with stand age (C: slope 0.08
Mg C ha−1 yr−1, R2 = 0.62, P < 0.05). In the oldest
stand, the large amount of CWD (32.8 m3 ha−1)
was due to a previous wind throw: the stability
of plants was compromised because of the high
Table 2: Total leaf biomass, C and N in the five stands (±1 SE) (original biomass data in grams both for C and N)
Age
Biomass (Mg ha−1)
C (Mg ha−1)
N (Mg ha−1)
C:N
40
50
55
55
75
2.0 ± 0.1
2.7 ± 0.1
2.4 ± 0.1
2.0 ± 0.1
2.8 ± 0.2
0.9 ± 0.1
1.2 ± 0.1
1.1 ± 0.1
0.9 ± 0.1
1.2 ± 0.1
0.02 ± 0.003
0.03 ± 0.003
0.03 ± 0.02
0.02 ± 0.002
0.03 ± 0.004
43.6 ± 12.4
42.2 ± 9.6
41.5 ± 7.3
46.1 ± 10.8
44.0 ± 13.8
Above ground C (Mg C ha-1)
200.0
180.0
160.0
140.0
120.0
100.0
80.0
60.0
40.0
20.0
0.0
0
10
20
30
40
50
60
70
80
90
100
Age
Figure 2. Total carbon stock in living trees vs stand age estimated with linear regression (dashed line:
R2 = 0.76, P < 0.05, slope = 1.69 Mg ha−1yr−1) and with the Richards function model (solid line: C = 32 + 169
[1 − e(−0.072 × age)]47.3, R2 = 0.94, P < 0.01). While T2 (open symbol) was considered for the linear regression,
it was not considered for Richards model estimation.
SECONDARY SUCCESSION ON EASTERN PREALPS
density (plants have an high height : d.b.h. ratio).
In this stand, most of the CWD was partially
decomposed (54 per cent of the volume is in the
second decay class) while in the youngest stand
the first decay class was more important (33 per
cent) (data not reported).
No significant relationship either between
FWD and litter C stock and stand age or between
C : N ratio and stand age was detected (Table 4;
P > 0.05).
The total C stock in the dead compartment increases significantly at a mean annual rate of 0.17
Mg ha−1 yr−1 (R2 = 0.91, P < 0.01).
7
Ecosystem carbon
Total ecosystem C increased linearly with stand
age at a mean rate of 1.18 Mg C ha−1 yr−1 (R2 =
0.42, P > 0.05; Figure 4a. In the meadow, most of
the carbon was contained in the mineral soil with
only 4–5 per cent held within the biomass. Over
the course of forest development, the aboveground biomass increased: in the oldest stand
about 60 per cent of the C was contained in the
plant biomass (Figure 4b).
Discussion
Plant biomass and CWD
Soil
Soil showed a decrease in carbon sequestration
from colonization (Table 5 and Figure 3). The
thickness of the organic horizon (O) increased
linearly with forest age probably because of the
increasing input of litter during stand development (slope = 0.09 cm yr−1; R2 = 0.77; P < 0.05).
After 40 years of forest succession, organic horizon thickness was 4.0 cm compared with 7.1 cm
thick in the 75 years old stand. No significant
correlation between soil bulk density and age
since succession was found (P > 0.05).
Total carbon (0–30 cm) showed a linear decrease during the chronosequence (slope C: −0.69
Mg C ha−1 yr−1, R2 = 0.54, P > 0.05, Figure 3a)
and nitrogen also decreased with age (N (t ha−1) =
88.20 exp (−0.04 age), R2 = 0.92, P < 0.001,
Figure 3b).
In the meadow, total C stock reaches 153 Mg
C ha−1 compared with 107 Mg C ha−1 in the
75-year-old forest stand.
Carbon accumulated in secondary forest biomass
at a significant rate during the first 75 years after
agricultural abandonment (1.69 Mg ha−1 yr−1) and
most of the carbon was sequestered in the bole
wood (77 per cent). This rate of increment is close
to the value reported by Hooker and Compton
(2003) for a Pinus strobus secondary succession in
Northeast United States (1.53 Mg C ha−1 yr−1).
Carbon stored in woody debris and litter accounted for only 20 per cent of total ecosystem
accumulation (0.24 Mg C ha−1 yr−1); similar
values were reported by Hamburg (1984) in a 65
years old hardwood chronosequence in New
Hampshire. In all the stands, detritus (dead trees,
CWD, FWD and litter) represented 7–13 per cent
of the total aboveground carbon stocks.
Soil
Guo and Gifford (2002) reported that when pasture changes to a secondary broadleaf forest, soil
Table 3: Coarse woody debris volume, density for each decay class, total biomass, C and N (±1 SE, n = 4) and
C : N ratio
Wood density
Age
Volume
(m3 ha−1)
0
40
50
55
55
75
–
16 ± 5
8±2
19 ± 7
11 ± 2
33 ± 3
Decay class Decay class
1 (kg m−3) 2 (kg m−3)
–
500 ± 21
356 ± 37
356 ± 56
625 ± 121
543 ± 42
–
380 ± 29
358 ± 35
409 ± 55
527 ± 20
441 ± 50
Decay class
3 (kg m−3)
Total
biomass
(Mg ha−1)
C (Mg ha−1)
N (Mg ha−1)
C:N
(Mg ha−1)
–
240 ± 44
231 ± 42
285 ± 83
303 ± 77
334 ± 69
–
6±2
2±1
6±2
5±1
14 ± 3
–
3±1
1±0
3±1
2±1
7±2
–
0.04 ± 0.02
0.02 ± 0.01
0.04 ± 0.02
0.03 ± 0.01
0.05 ± 0.02
–
63 ± 11
60 ± 15
70 ± 22
76 ± 22
133 ± 49
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carbon stock is not affected while when arable
land is converted to forest an increase in soil C is
usually apparent.
Hooker and Compton (2003) reported an annual increase in soil C of 0.52 Mg C ha−1 yr−1 and a
annual decrease in soil N of −12.4 kg N ha−1 yr−1 in
a coniferous secondary succession (P. strobus L.).
Similar results are reported by Thuille et al. (2000)
in a chronosequence of Norway spruce (Picea abies
K.) stand regenerating on abandoned meadows in
Table 4: Fine woody debris and litter biomass, C and
N stocks and C : N ratios (±1 SE, n = 4)
Table 5: Soil bulk density (g cm−3), C and N content
(%) between 0 and 30 cm.
Age Density (g cm−3) C content (%) N content (%)
Biomass
C
N
Age
Mg ha−1
Mg ha−1
Mg ha−1
C:N
0
40
50
55
55
75
–
6.3 ± 0.2
10.3 ± 0.6
7.0 ± 0.4
7.8 ± 0.4
7.0 ± 0.2
–
2.8 ± 0.1
5.1 ± 0.3
3.2 ± 0.2
3.5 ± 0.2
3.7 ± 0.1
–
0.2 ± 0.01
0.2 ± 0.01
0.2 ± 0.01
0.1 ± 0.01
0.1 ± 0.01
–
14 ± 1.7
26 ± 3.4
16 ± 3.2
35 ± 4.4
38 ± 3.0
A
0
40
50
55
55
75
0.84 ± 0.10
0.75 ± 0.06
0.82 ± 0.06
0.78 ± 0.05
0.93 ± 0.04
0.68 ± 0.13
6.1 ± 0.8
7.4 ± 0.8
4.9 ± 0.3
4.9 ± 0.5
4.2 ± 0.4
5.3 ± 0.8
3.2 ± 0.4
0.6 ± 0.03
0.4 ± 0.1
0.5 ± 0.04
0.5 ± 0.03
0.4 ± 0.2
Values are means ± 1 SE (n = 4).
200.0
Soil carbon (Mg C ha-1)
180.0
160.0
140.0
120.0
100.0
80.0
60.0
40.0
20.0
0.0
Soil nitrogen (Mg N ha-1)
B
160.0
140.0
120.0
100.0
80.0
60.0
40.0
20.0
0.0
0
10
20
30
40
50
60
70
80
Age
Figure 3. (a) Total carbon in soil during the chronosequence: R2 = 0.57, P > 0.05; slope: −0.71 Mg C
ha−1yr−1. Bars indicate standard error (SE) (n = 4). (b) Total nitrogen in soil during the chronosequence:
R2 = 0.92, P < 0.001;. N (t ha−1) = 88.20 exp (–0.04 year). Bars indicate SE (n = 4).
SECONDARY SUCCESSION ON EASTERN PREALPS
9
Figure 4. (a) Total ecosystem carbon vs site age (slope = 1.18 Mg C ha−1 yr−1, R2 = 0.42, P > 0.05). Bars are
SE (n = 4). (b) Carbon in the different pools vs age. Bars are SE (n = 4).
the Southern Alps. On the other hand, Paul et al.
(2002) and Davis and Condron (2002) reported a
decrease in soil C following afforestation.
The high precipitation in our study area
(3000 mm yr−1) (Jackson et al., 2002; Paul
et al., 2002), the vegetation type (mixed broadleaf
forest), the previous land use (Piussi, 2000) and
the long time lags for changes in litter inputs to
affect soil organic carbon storage could explain
the decrease in total soil organic C stocks during
the chronosequence (−0.71 Mg C ha−1yr−1). After
abandonment, grassland organic matter continued its decomposition while young trees did not
begin to contribute to soil organic carbon pools
through the production of litter and woody products. Therefore, 40–70 years may be a too short
period to observe an increase in soil carbon after
colonization even though litter is still accumulating
in the 70 years old stand. Post and Kwon (2000)
also reported a decrease in soil organic matter
after woody plants invasion because woody plants
produce more recalcitrant materials. Typically,
regenerating forests produce litter that is more
resistant to decomposition compared to the residues produced by previous agricultural crops and
tree roots are less important as a source of organic
matter than grass roots because a large fraction of
tree roots survive intact for many years.
However, the decrease we measured in soil carbon may be also related to an inadequate sample
size and under-sampling (Smith and Johnson,
10
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2001). Therefore, probably more samples and
sites are needed to confirm the observed trend.
Long-term accumulation of carbon in forest
ecosystem after agricultural abandonment
The rate of total ecosystem sequestration during
the chronosequence (1.18 Mg C ha−1 yr−1) is less
than the value reported for pine chronosequence by
Hooker and Compton (2003) (2.10 Mg C ha−1 yr−1)
but is greater than the value reported by Davis et al.
(2003) for a Nothofagus chronosequence (0.55 Mg
C ha−1 yr−1). The dominant sink for atmospheric
CO2 within these secondary forests seems to be
live wood (Schlesinger and Lichter, 2001; Hooker
and Compton, 2003) with the soil playing a much
smaller role (Post and Kwon, 2000).
Funding
European commission Interreg IIIB CADSES CarbonPro
(5D038), Italian Government FISR Project CarboItaly
Acknowledgements
We would like to thank Diego Chiabà for the help during the field campaigns, Giacomo Blasone and Sara Berra
for the help during lab analyses and Sheera Turco and
Rossella Napolitano for LI-Cor 2000 measurements. We
also thank Francesca Cotrufo for useful suggestions.
Conflict of Interest Statement
None declared.
References
Conclusions
The wood production of these secondary stands
is quite high and it could represent an important
economic resource for the local communities even
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their possible management. The dominant sink
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Received 2 February 2007