In the last decade, there has been increased interest in measuring and modeling storage in the five forest carbon pools: the aboveground and belowground biomass (living biomass), the deadwood and litter (dead biomass), and the soil (soil organic matter). In this paper, we examined carbon storage in a holm oak coppice stand in the Madonie Mountains in Sicily (Italy), which is a typical case of managed coppice stands. Today, traditional coppice practices are only applied to a small number of forested areas in Sicily, such as the selected site, because of the decline in demand for wood and charcoal. The dendrometric parameters of the stands were recorded, and silvicultural indices were calculated immediately after cutting as well as during and at the end of the rotation period; they showed the trends typical of coppices. The carbon stocks in the five carbon pools were quantified to investigate the effects of coppicing on carbon storage in this Mediterranean area. Results showed that the lowest living biomass values were observed in the first years following coppicing, except for litter carbon. Belowground biomass and the soil carbon stock did not vary significantly with coppicing. During the rotation period, the aboveground biomass was completely restored, and the balance of the carbon stocks indicates that coppicing is a sustainable forest management choice from the point of view of the carbon balance, given that the logged trees are generally used for bioenergy production.
According to Intergovernmental Panel on Climate Change (
Interest in measuring and modeling carbon storage in forests has greatly increased over the last decade, and many studies have adopted a comprehensive approach to investigate the quantification of carbon stocks that accounts for all of the five carbon pools in forest ecosystems (
In recent years, some research has focused on the influences of forest management on carbon storage (
The history of Mediterranean forests encompasses fragmentation, degradation and deforestation, natural expansion (
The objectives of this study were (i) to quantify the carbon stocks in the five carbon pools (above and belowground biomass, deadwood, litter and soil) in a holm oak coppice stand generated by silvicultural felling practices carried out at different times and (ii) to investigate the effects of traditional forest management, in the form of coppicing, on carbon storage in a Mediterranean area by examining a significant example of correctly and timely managed stand in Sicily. The quantification of carbon in forest stands is currently of interest to forest managers since carbon storage can be significantly modified through silvicultural practices (
The study area is located in the Madonie Mountains (Sicily, Italy - 37° 53′ N, 14° 06′ E, elevation ~1000 m a.s.l.) within the B zone of the Madonie National Park, in the meso-Mediterranean vegetation belt. The selected forest stand is mainly composed of holm oak (
In the past, coppicing represented the main silvicultural management system aimed at firewood and charcoal productions in the Madonie Mountains (
Four plots (A1, A2, A3, and A4) were established in the study area on the north-eastern slopes (Tab. S1 in the Supplementary material) that were characterized by coppice stands of different age (
Field surveys were conducted in 2014, and one circular subplot with a 20-m radius was established in each plot. The subplots were as homogeneous as possible in terms of altitude, exposure and stand structure. For the dendrometric characterizations, all trees taller than 1.30 m were individually labeled, and their diameters at breast height (Dbh) ≥ 4 cm and heights (H) were measured in each subplot. Dbh values were measured for all shoots on each stool. Using these basic data, the following parameters were calculated for each plot: stem density (shoots ha-1), stool density (stools ha-1), mean tree diameter (Dm, in cm), mean tree height (Hm, in m) and basal area (G m2), and the whole shoot volume (V, in m3) was calculated using mathematical models developed by
Soil sampling was performed at 10 randomly selected points in each subplot. For a given point, 20 undisturbed soil cores (0.05 m in height by 0.05 m in diameter) were collected following the removal of the litter layer at the depths of 0 to 0.05 m and 0.05 to 0.10 m. In the laboratory, the undisturbed soil cores were used to determine the initial volumetric soil water content, θi (m3 m-3),
To estimate the carbon stocks in the five forest carbon pools, the approach shown in
The biomass equations for holm oak, downy oak and manna ash developed by
where
where
The aboveground biomass per unit area (Mg ha-1) was defined as the sum of the aboveground biomass of the shoots and the aboveground biomass of the cut stools. A 0.5 carbon fraction to dry matter conversion factor (
The belowground biomass was estimated by applying a standard root/shoot ratio (dimensionless) for each forest typology to the aboveground biomass (
Litter carbon,
where
Dead mass in the form of woody debris (WD), standing dead trees (SDT) and stumps (S) was estimated by recording all of the dead material in the subplots. In the case of WD and S, volume (m3) was calculated using the following relationship (
where
In the case of SDT, volume (
where
To estimate the deadwood carbon stock, the volume (in m3) of each subplot was converted to dead mass (Mg) using the appropriate basic density (kg m-3) value for each deadwood category (broadleaves, in our case) and decay class (
The soil carbon stock per unit area,
where SOC (kg Mg-1) is the soil organic carbon content,
Spearman’s correlation analysis was used to individuate the correlation between the species diversity index (SH index) and the stand structure indices (W and VE index). Differences in the carbon pools among plots were analyzed with Kruskal-Wallis one-way analysis of variance on ranks. If any significant differences were detected, a
For each forest plot, the values of all measured and derived stand parameters are reported in
In the recently cut A1 (2013) and A2 (2009) plots, the percentages of natural regeneration with height < 130 cm were 100% (41.322 shoot ha-1) and 67% (21.916 shoot ha-1), respectively, and the corresponding percentages of sprout origin regeneration were 86% (35.447 shoot ha-1) in plot A1 and 90% (29.583 shoot ha-1) in plot A2 (Tab. S3 in the Supplementary material). In plots A3 and A4, the natural regeneration with height < 130 cm was less than in the other plots (A1 and A2) and equal to 90% (5.000 shoot ha-1) and 97% (7.750 shoot ha-1), respectively. In both plots, the natural regeneration was sprout origin (Tab. S3). Considering (i) that manna ash is a light-demanding species and (ii) that there is a higher density of sprout origin regeneration in more recently disturbed plots (A1 and A2), the lower abundance of standards in A3 (63.7 plants ha-1) and A4 (127.3 plants ha-1) suggests a tree-cutting effect; the openness of the canopy and light should have positively influenced seed germination and early seedling development.
The values of all structural indices calculated for each forest plot are reported in Tab. S4 (Supplementary material). Generally, all stands showed low species diversity, but the Shannon index values were higher in plots A1, A2 and A3, as three species (holm oak, downy oak and manna ash) were detected in the tree layers; contrastingly, only two species were found (holm oak and downy oak) in plot A4. Holm oak was dominant in all stands. Forest stands A1 and A2 were characterized by a clumped tree distribution with W index values equal to 0.71 and 0.83, respectively, whereas stands A3 and A4 were characterized by randomly distributed trees with W index values equal to 0.63 and 0.46. The vertical distribution of crowns obtained by TSTRAT consisted of three strata for the A2, A3 and A4 forest stands, which were characterized by VE values greater than 0.8, and two strata for the more recently cut stand (A1) with a VE value of 0.37. Except for the latter stand, the distribution of crowns into the strata was uniform since the crowns of all trees were within the vertical strata. There were no significant correlations (p>0.05) between any pair of indices (SH, W and VE).
The A1, A2, A3 and A4 forest plots were established very close together, no further than 600 meters apart which assured the pedological uniformity of the site; thus, the mean steepness values were very similar, varying from 48% (for A4) to 59% (for A3 -
A coppicing effect was detectable when the less disturbed plots (A3 and A4) were compared with more recently disturbed plots (A1 and A2). The soil in the latter plots was denser and had less organic carbon than in the former, but the effects of coppicing on
The aboveground carbon (Cabv) was higher in the older coppices (109.82 Mg ha-1 in A3 and 245.67 Mg ha-1 in A4) than in the recently cut plots (23.87 Mg ha-1 in A1 and 22.00 Mg ha-1 in A2) with significant differences between the plots, except for A1 and A2 (
Taking into account the relationships between carbon stocks and the five dendrometric parameters (crown cover, number of stools, number of shoots, basal area and volume), the most appropriate parameter to describe the changes in the values of the carbon stocks among the four forest stands was basal area, G (m2 ha-1), since there were statistically significant relationships between this factor and the three carbon pools (aboveground carbon, dead carbon and soil carbon). In particular, Cabv, Cdead and Csoil significantly linearly increased with G (
This study examined managed holm oak stands that had been regularly coppiced under a 40-year rotation in the Madonie Mountains of Sicily. This case study is particularly significant given that, contrary to most Sicilian stands, few holm oak coppices are managed and the reconstruction of historical management in most cases is practically impossible. The trends in the dendrometric parameters and silvicultural indices of the stands immediately after cutting and during and at the end of the rotation period were typical of coppices,
A complete analysis of five carbon pools has been carried out. Living biomass was the main carbon pool, and, on average, no significant differences were found in terms of total carbon stock and soil carbon of each investigated forest stand. However, we observed an effect of coppicing on carbon storage in the living and dead biomass. Except for litter carbon, the lowest living biomass values were observed in the plots in the early stages of development after coppicing. The results of this study revealed that coppicing does not affect the carbon balance, endorsing the sustainability of this kind of management, at least from a four decades perspective, and from the point of view of total carbon stocks and the carbon stored in the soil. The limited number of investigated plot does not allow to draw conclusions of general validity on the relationship between basal area and three carbon pools (aboveground carbon, dead carbon and soil carbon) in the Mediterranean area. However, the data obtained in the present study improve understanding of the effects of coppicing on carbon storage in a Mediterranean holm oak stand. A long-term monitoring of the investigated stands, as well as the characterization of other managed coppices in Sicily and in the Mediterranean area would be useful for the development of an international database on the effects of coppice management on carbon storage.
The following abbreviations have been used throughout the paper:
WD: woody debris
SDT: standing dead trees
S: stumps
SVS: standing visualization system
SH: Shannon index
W: Winkelmass index
VE: vertical evenness
ABV: aboveground biomass
WBD: wood basic density
SOC: soil organic carbon
THSD: Tukey’s honestly significant difference
This work is part of the research project “Development of innovative models for multiscale monitoring of ecosystem services indicators in Mediterranean forests (MiMoSe)” funded by the FIRB2012 program of the Italian Ministry of Universities and Research (Project coordinator: Lombardi F; Grant: RBFR121TWX_004). Thanks to Giovanni Gugliuzza for his availability, as owner of the study area.
SS, FGM and DSLMV performed the forest sampling and data elaboration. MI, GB and VP ivestigated soil characteristics. All authors contributed to the analysis of the results and to paper writing.
This work is dedicated to the memory of Sebastiano Cullotta, who led the Palermo Research Unit with great proficiency and humaneness.
Flowchart describing the approach adopted for estimating forest carbon pools in the investigated stands.
Estimation of carbon stocks in the five carbon pools for each investigated plot.
Relationships between basal area (G, m2 ha-1) and: (a) aboveground carbon (Cabv, Mg ha-1); (b) dead carbon (Cdead, Mg ha-1); and (c) soil carbon (Csoil, Mg ha-1).
Main dendrometric characteristics of the four investigated plots. (Dm): Mean diameter; (Hm): mean tree height; (G): basal area; (V): volume.
Plot | Species | Crowncover (%) | Stools (n ha-1) | Shoots(n ha-1) | Dm(cm) | Hm(m) | G(m2 ha-1) | V(m3 ha-1) |
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A1- Age 1 | Holm oak | - | 1200.0 | 55.7 | 14.9 | 10.2 | 1.0 | 4.9 |
Downy oak | - | 380.0 | 71.6 | 25.7 | 11.7 | 3.7 | 24.5 | |
Manna ash | - | 999.6 | 79.6 | 13.9 | 10.4 | 1.2 | 6.4 | |
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A2- Age 6 | Holm oak | - | 1066.0 | 87.5 | 20.5 | 12.9 | 2.9 | 16.2 |
Downy oak | - | 238.0 | 95.5 | 34.5 | 13.5 | 8.9 | 70.6 | |
Manna ash | - | 999.6 | 39.8 | 15.3 | 12.2 | 0.7 | 4.7 | |
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A3- Age 20 | Holm oak | - | 1209.6 | 3199.0 | 8.6 | 7.5 | 18.6 | 66.5 |
Downy oak | - | 95.5 | 262.6 | 17.0 | 8.2 | 6.0 | 28.6 | |
Manna ash | - | 1050.4 | 1957.6 | 7.1 | 6.8 | 7.7 | 26.3 | |
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A4- Age 40 | Holm oak | - | 1496.1 | 2840.9 | 12.2 | 10.4 | 33.3 | 180.4 |
Downy oak | - | 286.5 | 262.6 | 25.4 | 13.7 | 13.3 | 110.1 | |
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Summary statistics of the basic soil properties for each forest stand. (Ns): sample size; (CV): coefficient of variation; (
Variable | Statistic | A1 | A2 | A3 | A4 |
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Slope (%) | Mean | 56.6 | 55.3 | 59.3 | 48.2 |
Clay (%) | Ns | 10 | 10 | 10 | 10 |
Mean | 17.2 ab | 14.9 a | 22.0 b | 21.2 b | |
CV (%) | 23.0 | 41.9 | 8.2 | 14.2 | |
Silt (%) | Ns | 10 | 10 | 10 | 10 |
Mean | 37.5 a | 35.2 a | 34.5 a | 37.5 a | |
CV (%) | 15.3 | 12.9 | 5.8 | 8.7 | |
Sand (%) | Ns | 10 | 10 | 10 | 10 |
Mean | 45.3 ab | 49.9 a | 43.4 b | 41.2 b | |
CV (%) | 10.7 | 7.2 | 5.1 | 8.9 | |
ρb (Mg m-3) | Ns | 20 | 20 | 20 | 20 |
Mean | 0.914 a | 0.892 a | 0.863 a | 0.785 a | |
CV (%) | 24.5 | 15.8 | 20.0 | 24.4 | |
SOC (kg Mg-1) | Ns | 7 | 7 | 7 | 7 |
Mean | 77.4 a | 76.1 a | 97.8 a | 102.7 a | |
CV (%) | 24.3 | 20.9 | 26.6 | 28.0 |
Carbon stocks in the living and dead biomass of each forest stand. For a given carbon pool, values followed by the same letter are not significantly different (p>0.05) according to Tukey’s Honestly Significant Difference test.
Plot | Living biomass | Dead biomass | ||
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Cabv (Mg ha-1) | Cblw (Mg ha-1) | Clitter (Mg ha-1) | Cdead (Mg ha-1) | |
A1 | 23.87 a | 170.93 | 8.65 a | 1.61 a |
A2 | 22.00 a | 170.93 | 8.71 a | 0.06 a |
A3 | 109.82 b | 170.93 | 6.08 b | 4.89 ab |
A4 | 245.67 c | 170.93 | 2.02 c | 9.56 b |
Soil carbon stocks (Csoil, Mg ha-1) and total carbon stock (Cstock, Mg ha-1) of each forest stand (± standard error). For a given carbon pool, means followed by the same letter are not significantly different (p>0.05) according to Tukey’s Honestly Significant Difference test.
Plot | Csoil (Mg ha-1) | Cstock (Mg ha-1) |
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A1 | 71.83 ± 9.54 * a | 276.89 ± 31.37 * a |
A2 | 67.25 ± 4.86 a | 268.95 ± 31.49 a |
A3 | 85.89 ± 14.56 a | 377.61 ± 31.77 a |
A4 | 87.90 ± 11.66 a | 516.08 ± 46.97 a |
Tab. S1 - Main characteristics of the forest stands.
Tab. S2 - Applied diversity and structure indices with the respective equations and classes.
Tab. S3 - Density of the natural regeneration in the forest stands.
Tab. S4 - Structural indices calculated for each forest stand.