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Carbon stock changes in successive rotations of Chinese fir (Cunninghamia lanceolata (lamb) hook) plantations
Forest Ecology and Management 202 (2004) 131–147 www.elsevier.com/locate/foreco
Carbon stock changes in successive rotations of Chinese fir (Cunninghamia lanceolata (lamb) hook) plantations Xiao-Quan Zhanga,*, Miko U.F. Kirschbaumb,1, Zhenhong Houa, Zhihua Guoa a
Institute of Forest Ecology and Environment, The Chinese Academy of Forestry, Wan Shou Shan, Beijing 100091, China b CSIRO Forestry and Forest Products, PO Box E4008, Kingston, ACT 2604, Australia Received 11 February 2004; received in revised form 18 April 2004; accepted 4 July 2004
Abstract Chinese fir is an important timber species in Southern China. Millions of hectares of Chinese fir plantations have been established during the past decades, and increasing areas are re-planted as second or later rotations. Since the 1980s, scientists and forest managers have reported apparent yield decline and soil fertility degradation over successive rotations. If this yield decline is accompanied by a reduction in carbon stocks, and if it is caused by management, it has to be considered as a form of forest degradation and will become important from a carbon-accounting point of view. In this paper we have collected and compiled published data relevant to growth and soil properties over successive rotations of Chinese fir, calculated the stocks of stand biomass and soil organic carbon and nitrogen, and have analyzed the impact on carbon stocks of growing Chinese fir over successive rotations. We found that on an average, stand biomass increments were reduced by 24% from the first to the second rotation, and by a further 40% from the second to the third rotation. Soil organic carbon was reduced by 10% and 15% between the first and second, and second and third rotations, respectively. Soil carbon losses were usually accompanied by nitrogen losses but carbon losses were generally larger than nitrogen losses. The reduction of carbon stocks in successive rotations appears to be related to increases in soil bulk density and nutrient losses caused by burning of residues during site preparation. Potential afforestation/reforestation projects under the clean development mechanism (CDM) of the Kyoto Protocol may also need to consider the possible yield decline and soil degradation over successive rotations of plantations. # 2004 Elsevier B.V. All rights reserved. Keywords: Chinese fir; Successive rotation; Carbon stock change; Bulk density; Kyoto Protocol
1. Introduction * Corresponding author. Tel.: +86 10 6288 9512; fax: +86 10 6288 8840. E-mail address: [email protected] (X.-Q. Zhang), [email protected] (Miko U.F. Kirschbaum). 1 Tel.: +61 2 6281 8252; fax: +61 2 6281 8312.
Chinese fir (Cunninghamia lanceolata (lamb) hook) is one of the most important timber species in Southern China due to its fast growth and good timber quality (Wu, 1984). The earliest plantings of
0378-1127/$ – see front matter # 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2004.07.032
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Fig. 1. Changes in area (A) and standing volume (B) of Chinese fir stands in southern China (Data sources: CMOF, 1983, 1989, 1994, 1995; SFA, 2000).
Chinese fir can be dated back to 1000 years ago (Yu, 1997). With the large scale of afforestation/reforestation activities, the land area under Chinese fir stands has expanded rapidly since the 1950s, and, in particular, since the 1980s, with both the area and standing volume having more than doubled (Fig. 1). Most of the expanded areas are plantations. Chinese fir plantations are usually established for industrial timber production with a short rotation time of around 25 years. Land used for plantations was mostly covered by broadleaf forests that had been cleared, and residues were slashed and burned before planting Chinese fir. In addition to planting new areas with Chinese fir, more and more plantations are being established with successive rotations of Chinese fir. Once planted with fir, sites are usually retained under fir for several rotations. Since the 1980s, scientists have increasingly recognized that yield of fir tends to decline over successive rotations (Ma et al., 2000a, 2002, 2003; Tian et al., 2002). For example, Chen (1983) reported that the standing wood volume of the second and third rotations of Chinese fir plantation decreased by 30% and
47%, respectively, compared to the first rotation. Fang (1987) found that, compared to the first rotation, the dominant tree height of the second and third rotation of Chinese fir was reduced by 7% and 23%, respectively. Degradation in soil physical, chemical, biological and biochemical properties under successive rotations of Chinese fir have also been widely reported (Fang, 1987; Yu and Zhang, 1989; Lin et al., 1992; Shao, 1992; Zhou et al., 1992; Yang et al., 1996; Ying, 1997; Ma et al., 2000b; Yu et al., 2000; Sun et al., 2003). However, the extent to which successive rotations of Chinese fir influence the carbon stocks on a site is not known. Especially for soil organic carbon, many investigations (Fang, 1987; Lin et al., 1992; Shao, 1992; Zhou et al., 1992; Ma et al., 2000b; Yu et al., 2000; Sun et al., 2003) have reported a reduction in soil organic matter concentration (percentage of soil mass) and an increase in soil bulk density, both of which are closely associated with stocks of soil organic carbon, but no report specifically assessed changes in stocks of soil carbon.
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Therefore, the objectives of our studies were to calculate carbon-stock changes over successive rotations of Chinese fir plantations with particular emphasis on changes in soil organic carbon and nitrogen, and to assess possible causes and implications of any observed changes.
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10.0 for Windows, using the equation: Bs ¼ Bmax ½1 expðrAÞn
(4)
where Bmax is the estimated maximum standing biomass of a mature stand, and r and n are fitted parameters (Cooper, 1983). 2.3. Bulk density
2. Data and methods 2.1. Data collection Published data on growth, standing volume, stand biomass, soil organic matter and nitrogen content, and soil bulk density for different rotations of Chinese fir plantations were used. Only data available from paired sites were used for analysis. The selected data set consisted of 34 paired sites from 21 studies. Data for most paired sites were given as mean values of replicate plots, with varying number of replicates ranging from 1 to 23 replicates per site. Raw data are listed in Appendix A. 2.2. Biomass Not all studies provided stand biomass data. For those reporting standing volume data, total stand biomass, including stems, roots, foliage and branches, Bs, in tDW ha1 was calculated through a biomass expansion factor simplified from Fang et al. (2001) as: Bs ¼ 22:5 þ 0:40Vs
(1)
where Vs represents standing volume (m3 ha1) of a whole stand. For those sites where only mean height and DBH were available, we used the following binary equation (CMOF, 1978) to estimate the standing volume of single trees, Vt Vt ¼ 0:0000581D1:96 H 0:894 ðJiangxi and Fujian provincesÞ 1:97
Vt ¼ 0:0000588D
H
0:896
ðother provincesÞ
(2) (3)
where D and H represent DBH (cm) and tree height (m). Standing volume per unit area, Vs, in m3 ha1 was then calculated by multiplying Vt by the number of trees per hectare. Stand biomass was calculated by using Eq. (1). Stand biomass, Bs, was then regressed against stand age, A, for each rotation by using SPSS
Assessment of soil bulk density is required if soil carbon and nitrogen are to be expressed on a volume or area basis and if original data are only available as concentrations of carbon and nitrogen. This is particularly important if bulk density changes in parallel with possible changes in soil carbon and nitrogen. Studies that provided only contents of soil organic matter and nitrogen to specified depths but lacked bulk density measurements (He and Yu, 1992; Yang et al., 1996; Ying, 1997; Ma et al., 2000b) were, therefore, excluded from the analysis. As highlighted by Murty et al. (2002), changes in bulk density could create difficulties in the estimation of soil carbon changes. If the soil is sampled to a fixed depth, changes in bulk density could lead to an apparent increase or decrease of estimated soil carbon depending on the way the data are expressed (Murty et al., 2002). If data are expressed as mass of carbon per unit area to a constant depth, an increase in bulk density would lead to an apparent increase in soil carbon because more soil mass would be sampled from more compacted soil, whereas for data expressed as percentage of carbon per unit of soil mass, an increase in bulk density could lead to an apparent reduction of soil carbon because soil from deeper layers within the profile would be included with its typically lower carbon concentration than for soil nearer the soil surface as shown in Fig. 2. This suggests that the bulk density effect on measurements of soil organic carbon and nitrogen contents must be corrected before a stock change can be estimated. The method that we used to make this correction was to take the mass of the most compacted soil within each paired observation as the reference soil mass and adding small notional soil layers to the less compacted soils in such a way that the notional soil mass in all cases became the same. The task of the correction was basically to add a small further layer at the bottom of those that had been measured to emulate
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density (State Criteria Administration, 1987) as: Pn SOMi Di BDi (6) SOC ¼ i¼1 1:724
Fig. 2. Changes in soil organic matter concentration with increasing depth for Chinese fir plantation (n = 170). Data from those collected in Section 2.1. For each data set, data were normalized to 1 by a linear or exponential fit to each data set, and then dividing each measured value by the extrapolated value at 0 cm.
the expected finding if the same mass of soil had been sampled in all instances. Hence, it was necessary to estimate the properties of that additional layer from the information contained in the measurements that have been carried out on layers higher in the soil. The procedure of making the correction is described in Appendix B. Those studies that provided bulk density for only one layer of soil depth and that recorded large changes in bulk density (Fang, 1987; Sun et al., 2003) were also excluded from our analysis because it was not feasible to correct bulk density effects for those data. In order to understand to what extent the change of bulk density could be related to changes in growth, we calculated a site growth potential by inverting Eq. (4). Hence, Bmax was calculated as: Bmax ¼
Bs 1 expðrAÞn
(5)
where Bs is observed biomass, A is stand age, and r and n represent the same parameters as given in Eq. (4). 2.4. Soil organic carbon and nitrogen Stocks of soil organic carbon were calculated based on the organic matter content, sampled depth and bulk
where i is a sampled layer, SOC is the total stock of soil organic carbon (tC ha1), SOM represents the weight percentage of soil organic matter [g (100 g)1], Di is the depth of the ith layer (cm), BDi is the bulk density of that layer (in g cm3) and 1.724 is a factor for converting organic matter to organic carbon. Soil nitrogen was calculated with an equivalent equation but without the conversion factor. Since the inherent soil-carbon amounts in different soils, the depth to which soil samples were taken and the sampling protocol varied between studies; it was difficult to compare absolute stock changes between studies. Changes were therefore calculated as a percentage difference between sites, which minimized some of these problems. The adopted procedure allowed us to calculate and collate percentage changes of stocks between rotations from each study.
3. Results 3.1. Changes in biomass Compared with the previous rotation, biomass stocks decreased considerably in the second rotation, and further declined in the third rotation of Chinese fir (Fig. 3). The largest reductions were 72% in a 6-yearold second rotation (Zhang et al., 2001) and 68% in a 12-year-old third rotation (Ma et al., 2002), and the smallest biomass reductions were 1% and 16% in 31year-old second and third rotations (Ma et al., 2002). Mean biomass reductions between first and second, and second and third rotation stands of the same ages were 24 3% (n = 28) and 40 4% (n = 15), respectively. 3.2. Changes in soil organic carbon and nitrogen Changes in soil carbon in successive rotations of Chinese fir are shown in Fig. 4. Eight out of nine observations showed SOC stock reductions from the first to the second rotation, with a mean change of
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Fig. 3. Biomass comparisons for the first, second and third rotations of Chinese fir. The curves are given by: Bs = 243 (1 exp(0.0904A))1.87 (first rotation, R2 = 0.63, n = 28); Bs = 183 (1 exp(0.0937A))1.91 (second rotation, R2 = 0.68, n = 28); Bs = 142 (1 exp(0.0892A))1.90 (third rotation, R2 = 0.67, n = 15).
9.5 5.1% (n = 9). From the second to the third rotation, SOC stocks decreased further for six out of seven observations, with a mean change of 15.3 4.8% (n = 8).
All studies that reported soil C described above also reported soil N. There were generally losses in both soil C and N, but C losses were generally larger than N losses. The mean changes in soil N were 6.2 3.8% (n = 9) and 12.4 2.2% (n = 7) from the first to the second, and from the second to the third rotations, respectively. Due to the larger changes in soil C compared to that in soil N, C:N ratios decreased when soil carbon was lost (Fig. 5). 3.3. Changes in bulk density and its relationship to growth Observed soil bulk density in the first, second and third rotations are shown in Fig. 6. Compared with the
Fig. 4. Comparisons of soil organic carbon (SOC) under the different rotations of Chinese fir (tC ha1).
Fig. 5. Changes in soil C:N ratios in relation to soil C changes under different rotations.
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4. Discussion 4.1. Yield decline, soil degradation and attributable factors
Fig. 6. Comparison of soil bulk density over successive rotations of Chinese fir plantations.
first rotation, bulk density generally increased in the second rotation and increased further in the third rotation although there was a decrease in a few sites. The average increase in bulk density was 6.4 2.9% (n = 19) and 8.8 3.0% (n = 12) from the first to the second, and from the second to the third rotations, respectively. Increases in soil bulk density probably affected stand growth, leading to reduced litter input and ultimately causing a loss of soil carbon. Our results indicate that the growth potential on individual sites was well correlated with soil bulk density, in particular, for the first rotation (Fig. 7).
Our results show that biomass, soil carbon and nitrogen stock were reduced while soil bulk density increased in the successive rotations of Chinese fir (Table 1). The strong correlation between bulk density and growth potential (Fig. 7) suggests that the increase in bulk density could be a primary factor responsible for the observed yield decline. Soil nitrogen was also reduced over successive rotations (Fig. 4), but the C:N ratio decreased with reductions in soil carbon (Fig. 5). A decreasing C:N ratio normally indicates that nitrogen availability is improving. The observations on Chinese fir were similar to earlier studies that also showed yield declines of successive Pinus radiata and coppiced Eucalyptus plantation (Keeves, 1966; Evans, 1992). Harvesting and site preparation practices, e.g., windrowing and inadequate weed control, were believed to be the major cause of the yield decline of P. radiata in South Australia, and counter-measures such as organic matter conservation, careful site preparation and adequate weed control, could greatly improved productivity of second rotations and largely overcome the problem of declining yields (Woods, 1990).
Fig. 7. Growth potential in relation to soil bulk density.
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Table 1 Summary of biomass reduction in relation to soil properties in successive rotations of Chinese fir From first to second rotation
Biomass Soil carbon Bulk density Nitrogen
From second to third rotation
Change (%)
Observed number
Change (%)
Observed number
24.1 9.5 6.4 6.2
28 9 19 9
39.7 15.3 8.8 12.4
15 8 12 7
3.0 5.1 2.9 3.8
The yield decline and soil degradation in successive Chinese fir plantation are probably attributable to poor site preparation practices. Traditional practice for preparing sites for fir production is to slash harvesting residues and burn them. All slash (branches, leaves and other non-timber part of trees), forest floor litter, undergrowth vegetation and even excavated coarse roots are generally burnt on site. This is then usually followed by ploughing the site before replanting. During the following rainy season, the partly burnt materials and surface soil are subject to erosion, resulting in rapid and large loss of soil organic matter and nutrients as well as leading to increased bulk density. This is probably a more important cause for increasing bulk density than the physical compaction during tree felling and pulling of felled logs. Based on 6 years of observations in Fujian, Ma et al. (1997a) found that the rate of soil erosion on a ‘slash and burn’ site of Chinese fir was 88 times that of a control site in the first year following the slash and burn treatment. Although soil erosion decreased exponentially in subsequent years, 38.0 t ha1 of soil eroded in the first 6 years compared to 1.9 t ha1 for a control site. This resulted in losses of 1056 kg ha1 organic matter, 30.3 kg N ha1, 10.4 kg P ha1 and 483 kg K ha1 from burnt sites, compared to 153 kg organic matter ha1, 6.1 kg N ha1, 1.7 kg P ha1 and 78 kg K ha1 from a control site. Zhang (1986) and Ye et al. (1992) also found that slash and burn of residues and site preparation methods had significant impacts on soil organic matter, nutrients and soil biochemical activities. Experiments by Soto et al. (1995) indicated that soil losses by surface runoff from two slash and burnt sites were 46 and 57 t ha1 compared to 1.4 t ha1 from a control site. A recent experiment in Fujian province is studying the effect of establishment technique on subsequent stand growth and soil properties. While the experi-
4.4 4.8 3.0 2.2
ment is still in its early phases, indications are that productivity up to age 6 may be positively related to the amount of slash retention, but, in contrast to other studies, little effect on soil properties has been found (Fan et al., 1998, 1999; Fan, 2004, Personal communication). Some studies have suggested that toxic substances may accumulate over successive rotations of Chinese fir and inhibit tree growth (He, 1992, 1995; Ma et al., 2000b,c). However, while it is well established that conifers produce phenolic substances in their litter that are inhibitory to many organisms, it is less clear whether those phenolics are also inhibitory for the trees themselves, and in particular, whether it could affect the growth of established trees. Evans (1998) pointed out that the effect of allelopathy on productivity remains unsolved. There may be factors other than changes in bulk density that led to reduced tree growth, such as loss of potassium, phosphorus, magnesium and/or microelements, etc. Fertilization experiments showed that potassium and phosphorus can be important for tree growth on some sites (Li et al., 1992a,b,c), and Ma et al. (1997a) observed significant erosion on some burnt site leading to losses of potassium and phosphorus. Some SOC may be lost to the atmosphere especially during regeneration burning. Carbon lost through erosion will flow into rivers, lakes or even the ocean and may not initially add to the CO2 load of the atmosphere. Ma et al. (1997a), for example, found 6.6% of total soil organic matter to be lost during slash and burn, and 10.1% to be lost with erosion over the next 4 years after burning. 4.2. Implications for carbon accounting Based on the analysis described above, we can construct a temporal pattern of carbon stock changes
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Fig. 8. Conceived carbon stock changes for successive rotations of Chinese fir plantations, showing a notional sustainably managed plantation (A) and a plantation according to actual observations as summarized in the present work (B).
over successive rotations of Chinese fir plantations. Under sustainable management practice, we could assume biomass increments in the second and third rotations to be the same as during the first rotation, and soil organic carbon to remain unchanged (Fig. 8A). However, our analysis indicates that under actual traditional practice, both biomass increments and soil carbon stocks tend to decrease. Biomass and soil carbon stocks by the end of the second rotation are only about 76% and 90% of those in the first rotation, and they continue to decrease to 60% and 75% by the end of the third rotation (Fig. 8B). Article 3.4 of the Kyoto Protocol allows parties to include forest management as one of activities that could be used to offset some of their greenhouse gas emissions to meet their commitments. The definition of forest management in the Marrakesh Accord explicitly states that forest land eligible for such activity must be managed sustainably (UNFCCC, 2001a), which is a more stringent requirement than that stipulated for managed forests defined by the IPCC (1997).
Therefore there is the concern that inclusion of forest management activities could give rise to unbalanced accounting if the area under forest management under Article 3.4 could exclude areas subject to forest degradation. This is similar to the treatment of fire, where carbon losses due to forest fires are not included under the IPCC default methodology, yet carbon gains from subsequent forest regrowth are allowed to be counted (Kirschbaum, 2000). In such a case, greenhouse gas emissions from human-induced forest degradation should be accounted to achieve balanced accounting. In response to the decision on land use, land-use change and forestry (LULUCF) adopted by COP7 in Marrakesh (UNFCCC, 2001b), IPCC has initiated a program to develop definitions for direct humaninduced forest degradation and methodological options for emissions resulting from such activity. Although there could be many factors causing the observed carbon-stock reduction over successive rotations of Chinese fir, it is indeed a human-induced forest degradation from a carbon-accounting point of view. Accounting and reporting of carbon stock changes under such activities are important for long-term sustainability and management of atmospheric CO2 concentration. It also has special implication for government and forest managers to make special efforts to reverse these stock reductions as a potential action for the mitigation of carbon dioxide emission from managed forests. The Kyoto Protocol also allows Annex I countries to use carbon credits under the clean development mechanism (CDM) through afforestation and reforestation (AR) to offset some of their greenhouse gas emissions. Although the duration of CDM AR project is still subject to negotiations, sustainable management of AR plantations needs to be guaranteed over the long term to ensure the permanence of stored carbon.
5. Conclusions Our literature review and analysis found a significant reduction in growth or biomass stocks, and losses of soil C and N stock over successive rotations of Chinese fir. The growth reduction appears to be attri-
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
butable to an increase of bulk density, but the limited amount of available data suggest that they may not be related to losses of soil nitrogen. Soil nutrients are often also lost in erosion after site preparation which may link to those losses to subsequent stand productivity in the later development stages. Increases in bulk density and losses of soil C and nutrients are probably largely related to ‘slash and burn’ site preparation. All of these results have important implications for carbon accounting and mitigation through managed forests because Chinese fir plantations cannot be considered as a sustainable production system under
139
the silvicultural management regime used over the past decades.
Acknowledgements We would like to give our appreciation to the China Ministry of Science and Technology for its financial support under the project no. 2002CB412508 and Nature Science Foundation of China under project no. 40271109. We would also like to thank Jacqui England and Partap Khanna for many useful suggestions on the manuscript.
140
Appendix A. Sources of data and site description for different rotation of Chinese fir plantation. References
Nitrogen Bulk Locations Age Number Sampling SOM Notes Number Mean Mean Standing biomass density (years) of depth content content of trees height DBH volume (tDW ha1) (%) (g cm3) (tree ha1) (m) rotations (cm) (%) (cm) (m3 ha1)
He and Yu (1992), Fujian Yu and Zhang (1989)
I
14
II
17
I
17
II
0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40
3.22 2.08 3.15 1.68 8.84 3.72 2.94 2.08
0.088 0.077 0.084 0.077 0.117 0.080 0.084 0.072
78.1 65.1 139.3 75.8
Fang (1987)
Hunan
15 15 15
I II III
62 58 51
1.92 1.51 1.75
0.130 0.100 0.100
1.13 1.15 1.16
Zhou et al. (1992)
Fujian
23
I
21
II
19
III
16
I
16
II
0–20 20–60 0–15 16–35 0–10 10–32 0–18 19–40 0–15 16–38
4.28 0.99 5.30 1.07 5.21 1.10 6.38 2.43 7.24 1.81
0.185 0.062 0.212 0.049 0.214 0.051 0.299 0.102 0.272 0.084
0.95 1.32 1.03 0.98 1.07 1.15 0.73 1.23 0.83 1.22
20
I
20
II
20
III
20
I
20
II
0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50
5.92 2.64 2.56 4.68 2.56 2.34 4.30 2.57 2.18 5.20 2.77 1.33 3.50 2.70 2.72
0.20 0.11 0.09 0.15 0.13 0.06 0.09 0.10 0.06 0.24 0.14 0.09 0.16 0.13 0.08
0.82 1.08 1.33 0.97 1.15 1.32 1.17 1.27 1.36 0.82 1.08 1.33 0.97 1.15 1.32
Shao (1992)
Fujian
Average for 23 plots Average for 20 plots Average for 22 plots 1905
16.2
18.9
1995
14.4
15.7
2295
10.1
12.9
1800
17.0
18.8
1995
13.2
16.8
749.3
334.6
128.0
419.6
330.3
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
12
Yang et al. (1996)
Zhejiang
Zhejiang
III
2.85 2.07 1.77 6.62 2.48 2.86 5.01 2.80 1.72 3.95 3.00 1.72 6.28 3.57 2.13 4.09 2.88 2.10 2.78 1.44 1.45
0.10 0.10 0.07 0.19 0.16 0.07 0.18 0.12 0.13 0.11 0.09 0.05 0.12 0.10 0.05 0.10 0.09 0.06 0.10 0.07 0.05
1.17 1.27 1.36 0.82 1.08 1.33 0.97 1.15 1.32 1.17 1.27 1.36 0.82 1.08 1.33 0.97 1.15 1.32 1.17 1.27 1.36
20
I
20
II
20
III
20
I
20
II
20
III
20
I
0–40 40–60 0–40 40–60
1.91 0.70 1.60 0.71
0.048 0.015 0.044 0.019
1.04 1.13 1.06 1.13
20
II
14
I II I II
0–45 0–45 0–45 0–45
4.11 2.56 3.33 2.60
6
I
0–20
3.40
0.096
1.05
6
II
6
I
4
II
6
I
5
II
20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40
1.25 3.23 1.73 2.67 1.74 3.46 1.99 3.44 1.86 4.44 2.18
0.072 0.120 0.048 0.079 0.064 0.107 0.072 0.105 0.059 0.141 0.085
1.23 1.21 1.37 1.14 1.22 1.16 1.29 0.98 1.13 1.12 1.34
14
Sun et al. (2003); Zhang et al. (2001)
Jiangxi
84.1
417.9
274.1
111.3
408.0
347.6
137.5
3925 3175 2500 3525
8.4 7.3 8.2 6.7
10.9 11.2 12.4 9.7
345.3
Average for 13 plots
270.1
Average for 13 plots
171.9 129.4 138.9 99.9
4600
32.8
Average for 3 plots
1725
9.2
Average for 3 plots
3267
34.3
Average for 3 plots
2300
9.8
Average for 3 plots
2500
55.4
Average for 3 plots
3867
32.7
Average for 3 plots 141
0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Lin et al. (1992)
20
142
Appendix A. (Continued ) References
Ma et al. (2000a,b, 2003)
Zhejiang
Fujian
Notes
Age (years)
Number of rotations
Sampling depth (cm)
SOM content (%)
Nitrogen content (%)
Bulk density (g cm3)
Number of trees (tree ha1)
12
I
3900
89.9
Average for 3 plots
I
2600
86.0
Average for 3 plots
12
II
3850
95.9
Average for 3 plots
12
I
2067
81.3
Average for 3 plots
12
II
1.03 1.22 1.30 1.50 0.99 1.14 1.24 1.40 1.11 1.25 1.14 1.30
Average for 3 plots
12
0.106 0.078 0.086 0.054 0.119 0.072 0.094 0.055 0.113 0.086 0.112 0.063
57.4
II
3.70 1.72 3.23 1.14 3.16 1.52 3.15 1.45 4.32 2.69 4.23 2.42
1800
12
0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40
2233
54.1
Average for 3 plots
21
I
21
II
0–20 20–40 0–20 20–40
3.79 2.53 3.36 1.91
0.122 0.096 0.110 0.080
1.16 1.16 1.19 1.19
5
I
0–20
3.81
0.174
0.98
3340
5.5
8.0
95.9
68.2
Average for 5 plots
6
II
5.9
8.9
75.0
53.5
Average for 5 plots
1.18
3350
5.3
8.1
58.0
39.6
Average for 5 plots
8
I
1.02
2300
7.6
10.0
109.9
95.9
Average for 5 plots
9
II
1.11
2174
7.5
9.9
74.1
73.2
Average for 5 plots
9
III
0.105 0.156 0.103 0.138 0.095 0.149 0.096 0.139 0.091 0.131 0.082 0.171 0.125 0.133 0.104 0.124 0.079 0.156 0.106 0.134 0.088
3320
III
1.73 3.49 1.63 2.95 1.51 3.42 1.56 3.11 1.51 2.64 1.28 3.61 1.95 3.12 1.88 2.69 1.19 3.81 1.80 3.59 1.65
1.07
6
20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40
1.20
2195
6.6
9.0
55.3
54.6
Average for 5 plots
1.02
1550
13.0
16.3
215.1
121.5
Average for 5 plots
1.21
1575
11.6
14.7
163.5
105.8
Average for 5 plots
1.25
1650
11.2
13.7
121.9
78.4
Average for 5 plots
1.09
1566
14.4
17.6
315.1
149.9
Average for 5 plots
1.20
1550
13.0
15.9
235.9
118.8
Average for 5 plots
15
I
15
II
16
III
19
I
19
II
Mean height (m)
Mean DBH (cm)
Standing volume (m3 ha1)
biomass (tDW ha1)
345.3 270.1
Average for 13 plots Average for 13 plots
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Du et al. (2001)
Locations
22
III
0–20 20–40
3.03 1.62
0.122 0.085
1.25
1800
13.6
16.5
206.1
92.2
Average for 5 plots
20 20 20 20 20 20
I II I II I II
20–40 20–40 20–40 20–40 20–40 20–40
4.62 2.57 4.38 2.44 4.25 2.29
3250 3342 3316 3406 3161 3273
12.3 8.9 11.7 8.3 11.3 7.9
13.1 10.9 12.9 10.5 12.7 10.0
309.1 122.1 223.8 118.9 207.1 110.0
Yang et al. (1997)
Fujian
29
I
19.9
21.3
648.8
327.1
Average for 5 plots
II
2005
18.2
17.7
500.7
239.6
Average for 5 plots
29
III
3.06 1.45 2.88 1.24 2.58 1.13
1845
29
0–20 20–40 0–20 20–40 0–20 20–40
2084
15.7
16.5
346.6
190.0
Average for 5 plots
0–20
0.81
0.078
1.41
3225
5.3
9.0
64.5
44.4
Average for 3 plots
20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60
0.47 0.17 1.62 0.98 0.77 2.12 0.85 0.47 0.87 0.59 0.20 0.92 0.37 0.17 3.23 1.88 0.89 2.04 1.16 0.90 2.03 0.90 0.86 3.36 1.11 1.00
0.152 0.032 0.118 0.084 0.076 0.106 0.031 0.031 0.083 0.059 0.039 0.079 0.061 0.011 0.140 0.077 0.042 0.128 0.089 0.078 0.147 0.082 0.088 0.147 0.046 0.033
1.54 1.34 1.08 1.06 1.01 1.21 1.16 1.15 0.99 1.33 1.43 1.27 1.25 1.35 1.11 1.41 1.38 1.14 1.19 1.24 0.82 0.92 0.95 1.17 1.25 1.16
3200
5.1
7.6
44.8
38.3
Average for 3 plots
3050
4.9
6.8
32.6
20.3
Average for 3 plots
2850
40.5
13.6
234.3
112.1
Average for 3 plots
2950
9.6
12.7
196.8
101.7
Average for 3 plots
2530
9.2
9.5
91.6
32.6
Average for 3 plots
1095
15.8
23.7
390.3
183.4
Average for 3 plots
1550
15.1
19.9
377.9
170.3
Average for 3 plots
1620
14.6
18.1
315.9
127.7
Average for 3 plots
Ma et al. (2002)
Fujian
6
I
Yu et al. (2000) 6
II
6
III
12
I
12
II
12
III
31
I
31
II
31
III
143
Fujian
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Ying (1997)
144
Appendix A. (Continued ) References
Locations
Age (years)
Sampling depth (cm)
SOM content (%)
Nitrogen content (%)
Bulk density (g cm3)
Number of trees (tree ha1)
6
I
6
II
6
III
0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60
1.13 0.46 0.27 1.69 0.81 0.84 2.18 2.17 1.89 1.82 1.01 0.45 1.02 0.56 0.29 2.02 1.05 0.21 1.41 0.95 0.61 2.84 1.54 0.79 2.80 0.70 0.87
0.112 0.060 0.049 0.139 0.107 0.084 0.173 0.044 0.043 0.108 0.080 0.079 0.092 0.058 0.046 0.097 0.046 0.025 0.114 0.162 0.076 0.168 0.120 0.075 0.130 0.079 0.073
1.08 1.21 1.38 1.08 1.07 1.18 0.86 1.05 1.36 0.92 1.09 1.3 1.32 1.34 1.36 1.4 1.18 1.54 1.1 1.28 1.22 1.06 1.04 1.04 1.26 1.44 1.18
12
I
12
II
12
III
31
I
31
II
31
III
Mean height (m)
Mean DBH (cm)
3150
6.3
9.4
78.8
49.6
Average for 3 plots
3090
5.7
8.4
56.9
46.7
Average for 3 plots
3150
5.4
7.4
43.2
25.1
Average for 3 plots
2760
11.8
14.5
287.3
123.1
Average for 3 plots
2940
10.3
13.1
221.7
108.8
Average for 3 plots
2625
9.9
10.6
126.0
48.6
Average for 3 plots
1200
18.8
24.4
529.3
216.5
Average for 3 plots
1650
18.0
20.1
477.8
213.4
Average for 3 plots
1620
17.2
19.8
437.2
178.8
Average for 3 plots
87.9 76.0
Average for 3 plots Average for 3 plots
Hu and Xu (1994)
Anhui
9 9
I II
3600 3600
7.9 7.1
10.3 9.1
Tian et al. (2002)
Hunan
11 11
I II
2280 2080
10.5 9.8
12.7 11.7
Standing volume (m3 ha1)
biomass (tDW ha1)
Notes
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Number of rotations
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Appendix B. The basic notion of the correction for measurements using constant depth but different soil mass is to modify calculations to estimate the likely measurements that would have been expected had samples been taken to a common mass of mineral soil. Some studies have taken appropriate measurements so that soil organic carbon amounts could be compared for the same mass of soil. In other studies, corrections were not made at the time when measurements were taken, but sufficient additional measurements were taken and reported to allow subsequent corrections to be made. The aim of the correction is to estimate the amount of carbon that would be contained to a depth that corresponds to an identical mass of soil in different samples. As the first step, we assumed that bulk density (BD) changed linearly with soil depth (L) and make the regression with BD ¼ a þ bL
(B.1)
Where a and b are the intercept and slope parameters. Secondly, we need to calculate the soil mass of the additional layer, W, given as: W ¼ W2 W1
(B.2)
Where W1 and W2 represent sampled soil mass for less compacted soil and most compacted soil, respectively. Thirdly, we calculated the required thickness of the additional layer, t, given as: t ¼ Wða þ bdÞ
(B.3)
where d is the mean depth of the new layer which is given as: t (B.4) 2 where ds is the depth to which the soil had already been sampled. Combining Eqs. (B.3) and (B.4) leads to a quadratic equation with only one sensible solution which is given by: qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ða þ bds Þ þ ða þ bds Þ2 þ 2bW t¼ (B.5) b The bulk density of the extra layer was calculated using Eqs. (B.1) and (B.4). The soil organic carbon d ¼ ds þ
145
and nitrogen contents of the additional layer were estimated assuming they changed exponentially with soil depth if the number of sampled layers was three, and linearly if only two layers had been sampled. Data were excluded where only one soil layer was sampled or where too large an extrapolation from observed properties was required.
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Fang, J., Chen, A., Peng, C., Zhao, S., Ci, L., 2001. Changes in forest biomass carbon storage in China between 1949 and 1998 292, 2320–2322. He, G., 1992. Physiological mechanism for plant poisoning caused by phenolic substance. J. Zhejiang Coll. Forestry 9 (3), 339–344. He, G., 1995. Decomposition of phenolic substance in the successive rotation land of Chinese fir. J. Zhejiang Coll. Forestry 12 (4), 434–439. He, Z., Yu, X., 1992. Study on problems of soil degradation in continuous cropping Chinese fir plantation. In: Sheng, W., Chen, B., Xu, H., Xu, X. (Eds.), Research on Site Degradation of Timber Plantation. Chinese Science & Technology Press, Beijing, (in Chinese), pp. 243–250. Hu, F., Xu, X., 1994. The growth analysis of Chinese fir plantation in young age in the Huangshan Hill area. J. Anhui Agri. Univ. (Suppl.) 43–45, 43–45 (in Chinese). Intergovernmental Panel on Climate Change (IPCC), 1997. In: Houghton JT et al. (Eds.), Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. IPCC/OECD/IEA, Paris, France. Keeves, A., 1966. Some evidence of loss of productivity with successive rotations of Pinus radiata in the southeast of South Australia. Austr. Forestry 30, 51–63. Kirschbaum, M.U.F., 2000. How should fire be treated in the National Greenhouse Gas Inventory? Austr. Forestry 63, 136–141. Li, Y., Chen, D., Ji, J., 1992a. Growth responses of young Chinese fir stand to fertilizer application. In: Sheng, W., Chen, B., Xu, H., Xu, X. (Eds.), Research on Site Degradation of Timber Plantation. Chinese Science & Technology Press, Beijing, (in Chinese), pp. 198–211. Li, Y., Chen, D., Yao, M., Ji, J., 1992b. Growth responses of middleaged Chinese fir plantation to fertilizer application. In: Sheng, W., Chen, B., Xu, H., Xu, X. (Eds.), Research on Site Degradation of Timber Plantation. Chinese Science & Technology Press, Beijing, (in Chinese), pp. 212–222. Li, Y., Chen, D., Shen, G., Liu, B., 1992c. Growth responses of prematured Chinese fir plantation to fertilizer application. In: Sheng, W., Chen, B., Xu, H., Xu, X. (Eds.), Research on Site Degradation of Timber Plantation. Chinese Science & Technology Press, Beijing, (in Chinese), pp. 223–241. Lin, X., Hong, L., Du, G., 1992. Preliminary study on soil quality evaluation on continuous cropping Chinese fir plantation. In: Sheng, W., Chen, B., Xu, H., Xu, X. (Eds.), Research on Site Degradation of Timber Plantation. Chinese Science & Technology Press, Beijing, (in Chinese), pp. 267–275. Ma, X., Yang, Y., Lin, K., Liu, A., He, Z., 1997a. Effect of different ground clearance on Chinese fir plantation ecosystems. Acta Ecologica Sinica 17 (2), 176–183. Ma, X., Liu, A., Ma, Z., Fan, S., 2000a. A comparative study on nutrient accumulation and distribution of different generations of Chinese Fir plantation. Chinese J. Appl. Ecol. 11 (4), 501–506 (in Chinese). Ma, X., Fan, S., Liu, A., Chen, S., Lin, S., 2000b. A comparison on soil fertilities of Chinese fir plantations of different generations. Forest Res. 13 (6), 577–582 (in Chinese).
Ma, X., Liu, A., Huang, B., 2000c. Studies on the self-poison of Chinese fir. J. Nanjing Forestry Univ. 24 (1), 12–16 (in Chinese). Ma, X., Kang, S., Huang, Y., Lin, K., Fan, S., 2002. Effects of multirotation of Chinese fir plantations on granite sites. J. Fujian Col. Forestry 22 (4), 289–294 (in Chinese). Ma, X., Fan, S., Chen, S., Lin, S., 2003. Study on biomass productivity of Chinese fir plantations after successive planting. Scientia Silvae Sinicae 39 (2), 78–83. Murty, D., Kirschbaum, M.U.F., McMurtrie, R.E., McGilvray, H., 2002. Does conversion of forest to agricultural land change soil carbon and nitrogen? A review of the literature. Global Change Biol. 8, 105–123. Shao, J., 1992. Influences of continuous cropping on soil fertility and stand growth in Chinese fir plantation in Fujian Province. In: Sheng, W., Chen, B., Xu, H., Xu, X. (Eds.), Research on Site Degradation of Timber Plantation. Chinese Science & Technology Press, Beijing, (in Chinese), pp. 87–92. Soto, B., Basanta, R., Perez, R., Diaz-Fierros, F., 1995. An experimental study of the influence of traditional slash and burn practices on soil erosion. Catena 24, 13–23. State Criteria Administration, 1987. National Criteria for Forest Soil Analysis Methods (III). GB 7848-7858-87., China Criteria Publishing House (in Chinese). State Forestry Administration (SFA), 2000. Statistics of Forest Resource in China (1994–1998), Department of Forest Resource and Management, SFA, Beijing, China (in Chinese). Sun, Q., Yang, C., Jiao, R., 2003. The changes of soil properties of the successive Chinese fir plantation in Dagang Mountain of Jiangxi Province. Scientia Silvae Sinicae 39 (3), 1–5. Tian, D., Xiang, W., Yan, W., Kang, W., 2002. Effect of successive rotation on productivity and biomass of Chinese fir plantation at fast growing stage. Scientia Silvae Sinicae 38 (4), 14–18 (in Chinese). UNFCCC, 2001a. Decision 11/CP. 7: Land Use, Land-use Change and Forestry. UNFCCC/CP/2001/13/Add.1, pp. 54–63. UNFCCC, 2001b. Draft Decision CP. 6: Land Use, Land-use Change and Forestry. UNFCCC/CP/2001/L.11, pp. 1–10. Woods, R.V., 1990. Second rotation decline in Pinus radiata plantations in South Australia has been corrected. Water Air Soil Pollut. 54, 607–619. Wu, Z., 1984. Chinese Fir, Chinese Forestry Publishing House, Beijing, China. Yang, C., Zhang, X-Q., Jiao, R., 1996. Variations of chemical properties, biochemical, microoganism activities and function in soil of successive rotation of Chinese fir and their influences on growing. Scientia Silvae Sinicae 32 (2), 175–181 (in Chinese). Yang, Y., Zhang, R., He, Z., 1997. Change on the stand productivity of 29-year-old Chinese fir plantation in different rotations. J. Fujian Col. Forestry 18, 202–206 (in Chinese). Ye, J., Shao, J., Wang, G., Li, X., 1992. Impacts of slash and burn on soil physical and chemical properties. In: Sheng, W., Chen, B., Xu, H., Xu, X. (Eds.), Research on Site Degradation of Timber Plantation. (in Chinese), pp. 130–134.
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147 Ying, J., 1997. Comparative study on the growth and soil properties under different successive rotation of Chinese fir. J. Jiangsu Forestry Sci. Technol. 24 (1), 31–34 (in Chinese). Yu, X., 1997. Silviculture of Chinese Fir, Fujian Science & Technology Press, Fuzhou, China (in Chinese). Yu, X., Zhang, Q., 1989. Influences of continuous cropping on soil biochemical properties and soil fertility in Chinese fir plantation. J. Fujian Col. Forestry 9 (3), 263–271 (in Chinese). Yu, Y., Deng, X., Sheng, W., Fan, S., Lin, Q., Lei, L., 2000. Effects of continuous plantation of Chinese fir on soil physical properties. J. Nanjing Forestry Univ. 24 (6), 36–40 (in Chinese).
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Zhang, X., 1986. Influences of site preparations on soil conservation and the growth of young Chinese fir stand. Scientia Silvae Sinicae 22 (3), 225–230 (in Chinese). Zhang, J., Sheng, W., Nie, D., Bai, X., 2001. Comparison and study on the productivity and biomass component proportions of different rotation of Chinese fir plantations in Fenyi, Jiangxi Province. Forest Res. 14 (2), 160–167 (in Chinese). Zhou, X., Luo, R., Ye, J., 1992. Influences of continuous cropping on soil nutrients and their feedback effects. In: Sheng, W., Chen, B., Xu, H., Xu, X. (Eds.), Research on Site Degradation of Timber Plantation. (in Chinese), pp. 100–107.
Carbon stock changes in successive rotations of Chinese fir (Cunninghamia lanceolata (lamb) hook) plantations Xiao-Quan Zhanga,*, Miko U.F. Kirschbaumb,1, Zhenhong Houa, Zhihua Guoa a
Institute of Forest Ecology and Environment, The Chinese Academy of Forestry, Wan Shou Shan, Beijing 100091, China b CSIRO Forestry and Forest Products, PO Box E4008, Kingston, ACT 2604, Australia Received 11 February 2004; received in revised form 18 April 2004; accepted 4 July 2004
Abstract Chinese fir is an important timber species in Southern China. Millions of hectares of Chinese fir plantations have been established during the past decades, and increasing areas are re-planted as second or later rotations. Since the 1980s, scientists and forest managers have reported apparent yield decline and soil fertility degradation over successive rotations. If this yield decline is accompanied by a reduction in carbon stocks, and if it is caused by management, it has to be considered as a form of forest degradation and will become important from a carbon-accounting point of view. In this paper we have collected and compiled published data relevant to growth and soil properties over successive rotations of Chinese fir, calculated the stocks of stand biomass and soil organic carbon and nitrogen, and have analyzed the impact on carbon stocks of growing Chinese fir over successive rotations. We found that on an average, stand biomass increments were reduced by 24% from the first to the second rotation, and by a further 40% from the second to the third rotation. Soil organic carbon was reduced by 10% and 15% between the first and second, and second and third rotations, respectively. Soil carbon losses were usually accompanied by nitrogen losses but carbon losses were generally larger than nitrogen losses. The reduction of carbon stocks in successive rotations appears to be related to increases in soil bulk density and nutrient losses caused by burning of residues during site preparation. Potential afforestation/reforestation projects under the clean development mechanism (CDM) of the Kyoto Protocol may also need to consider the possible yield decline and soil degradation over successive rotations of plantations. # 2004 Elsevier B.V. All rights reserved. Keywords: Chinese fir; Successive rotation; Carbon stock change; Bulk density; Kyoto Protocol
1. Introduction * Corresponding author. Tel.: +86 10 6288 9512; fax: +86 10 6288 8840. E-mail address: [email protected] (X.-Q. Zhang), [email protected] (Miko U.F. Kirschbaum). 1 Tel.: +61 2 6281 8252; fax: +61 2 6281 8312.
Chinese fir (Cunninghamia lanceolata (lamb) hook) is one of the most important timber species in Southern China due to its fast growth and good timber quality (Wu, 1984). The earliest plantings of
0378-1127/$ – see front matter # 2004 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2004.07.032
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Fig. 1. Changes in area (A) and standing volume (B) of Chinese fir stands in southern China (Data sources: CMOF, 1983, 1989, 1994, 1995; SFA, 2000).
Chinese fir can be dated back to 1000 years ago (Yu, 1997). With the large scale of afforestation/reforestation activities, the land area under Chinese fir stands has expanded rapidly since the 1950s, and, in particular, since the 1980s, with both the area and standing volume having more than doubled (Fig. 1). Most of the expanded areas are plantations. Chinese fir plantations are usually established for industrial timber production with a short rotation time of around 25 years. Land used for plantations was mostly covered by broadleaf forests that had been cleared, and residues were slashed and burned before planting Chinese fir. In addition to planting new areas with Chinese fir, more and more plantations are being established with successive rotations of Chinese fir. Once planted with fir, sites are usually retained under fir for several rotations. Since the 1980s, scientists have increasingly recognized that yield of fir tends to decline over successive rotations (Ma et al., 2000a, 2002, 2003; Tian et al., 2002). For example, Chen (1983) reported that the standing wood volume of the second and third rotations of Chinese fir plantation decreased by 30% and
47%, respectively, compared to the first rotation. Fang (1987) found that, compared to the first rotation, the dominant tree height of the second and third rotation of Chinese fir was reduced by 7% and 23%, respectively. Degradation in soil physical, chemical, biological and biochemical properties under successive rotations of Chinese fir have also been widely reported (Fang, 1987; Yu and Zhang, 1989; Lin et al., 1992; Shao, 1992; Zhou et al., 1992; Yang et al., 1996; Ying, 1997; Ma et al., 2000b; Yu et al., 2000; Sun et al., 2003). However, the extent to which successive rotations of Chinese fir influence the carbon stocks on a site is not known. Especially for soil organic carbon, many investigations (Fang, 1987; Lin et al., 1992; Shao, 1992; Zhou et al., 1992; Ma et al., 2000b; Yu et al., 2000; Sun et al., 2003) have reported a reduction in soil organic matter concentration (percentage of soil mass) and an increase in soil bulk density, both of which are closely associated with stocks of soil organic carbon, but no report specifically assessed changes in stocks of soil carbon.
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Therefore, the objectives of our studies were to calculate carbon-stock changes over successive rotations of Chinese fir plantations with particular emphasis on changes in soil organic carbon and nitrogen, and to assess possible causes and implications of any observed changes.
133
10.0 for Windows, using the equation: Bs ¼ Bmax ½1 expðrAÞn
(4)
where Bmax is the estimated maximum standing biomass of a mature stand, and r and n are fitted parameters (Cooper, 1983). 2.3. Bulk density
2. Data and methods 2.1. Data collection Published data on growth, standing volume, stand biomass, soil organic matter and nitrogen content, and soil bulk density for different rotations of Chinese fir plantations were used. Only data available from paired sites were used for analysis. The selected data set consisted of 34 paired sites from 21 studies. Data for most paired sites were given as mean values of replicate plots, with varying number of replicates ranging from 1 to 23 replicates per site. Raw data are listed in Appendix A. 2.2. Biomass Not all studies provided stand biomass data. For those reporting standing volume data, total stand biomass, including stems, roots, foliage and branches, Bs, in tDW ha1 was calculated through a biomass expansion factor simplified from Fang et al. (2001) as: Bs ¼ 22:5 þ 0:40Vs
(1)
where Vs represents standing volume (m3 ha1) of a whole stand. For those sites where only mean height and DBH were available, we used the following binary equation (CMOF, 1978) to estimate the standing volume of single trees, Vt Vt ¼ 0:0000581D1:96 H 0:894 ðJiangxi and Fujian provincesÞ 1:97
Vt ¼ 0:0000588D
H
0:896
ðother provincesÞ
(2) (3)
where D and H represent DBH (cm) and tree height (m). Standing volume per unit area, Vs, in m3 ha1 was then calculated by multiplying Vt by the number of trees per hectare. Stand biomass was calculated by using Eq. (1). Stand biomass, Bs, was then regressed against stand age, A, for each rotation by using SPSS
Assessment of soil bulk density is required if soil carbon and nitrogen are to be expressed on a volume or area basis and if original data are only available as concentrations of carbon and nitrogen. This is particularly important if bulk density changes in parallel with possible changes in soil carbon and nitrogen. Studies that provided only contents of soil organic matter and nitrogen to specified depths but lacked bulk density measurements (He and Yu, 1992; Yang et al., 1996; Ying, 1997; Ma et al., 2000b) were, therefore, excluded from the analysis. As highlighted by Murty et al. (2002), changes in bulk density could create difficulties in the estimation of soil carbon changes. If the soil is sampled to a fixed depth, changes in bulk density could lead to an apparent increase or decrease of estimated soil carbon depending on the way the data are expressed (Murty et al., 2002). If data are expressed as mass of carbon per unit area to a constant depth, an increase in bulk density would lead to an apparent increase in soil carbon because more soil mass would be sampled from more compacted soil, whereas for data expressed as percentage of carbon per unit of soil mass, an increase in bulk density could lead to an apparent reduction of soil carbon because soil from deeper layers within the profile would be included with its typically lower carbon concentration than for soil nearer the soil surface as shown in Fig. 2. This suggests that the bulk density effect on measurements of soil organic carbon and nitrogen contents must be corrected before a stock change can be estimated. The method that we used to make this correction was to take the mass of the most compacted soil within each paired observation as the reference soil mass and adding small notional soil layers to the less compacted soils in such a way that the notional soil mass in all cases became the same. The task of the correction was basically to add a small further layer at the bottom of those that had been measured to emulate
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density (State Criteria Administration, 1987) as: Pn SOMi Di BDi (6) SOC ¼ i¼1 1:724
Fig. 2. Changes in soil organic matter concentration with increasing depth for Chinese fir plantation (n = 170). Data from those collected in Section 2.1. For each data set, data were normalized to 1 by a linear or exponential fit to each data set, and then dividing each measured value by the extrapolated value at 0 cm.
the expected finding if the same mass of soil had been sampled in all instances. Hence, it was necessary to estimate the properties of that additional layer from the information contained in the measurements that have been carried out on layers higher in the soil. The procedure of making the correction is described in Appendix B. Those studies that provided bulk density for only one layer of soil depth and that recorded large changes in bulk density (Fang, 1987; Sun et al., 2003) were also excluded from our analysis because it was not feasible to correct bulk density effects for those data. In order to understand to what extent the change of bulk density could be related to changes in growth, we calculated a site growth potential by inverting Eq. (4). Hence, Bmax was calculated as: Bmax ¼
Bs 1 expðrAÞn
(5)
where Bs is observed biomass, A is stand age, and r and n represent the same parameters as given in Eq. (4). 2.4. Soil organic carbon and nitrogen Stocks of soil organic carbon were calculated based on the organic matter content, sampled depth and bulk
where i is a sampled layer, SOC is the total stock of soil organic carbon (tC ha1), SOM represents the weight percentage of soil organic matter [g (100 g)1], Di is the depth of the ith layer (cm), BDi is the bulk density of that layer (in g cm3) and 1.724 is a factor for converting organic matter to organic carbon. Soil nitrogen was calculated with an equivalent equation but without the conversion factor. Since the inherent soil-carbon amounts in different soils, the depth to which soil samples were taken and the sampling protocol varied between studies; it was difficult to compare absolute stock changes between studies. Changes were therefore calculated as a percentage difference between sites, which minimized some of these problems. The adopted procedure allowed us to calculate and collate percentage changes of stocks between rotations from each study.
3. Results 3.1. Changes in biomass Compared with the previous rotation, biomass stocks decreased considerably in the second rotation, and further declined in the third rotation of Chinese fir (Fig. 3). The largest reductions were 72% in a 6-yearold second rotation (Zhang et al., 2001) and 68% in a 12-year-old third rotation (Ma et al., 2002), and the smallest biomass reductions were 1% and 16% in 31year-old second and third rotations (Ma et al., 2002). Mean biomass reductions between first and second, and second and third rotation stands of the same ages were 24 3% (n = 28) and 40 4% (n = 15), respectively. 3.2. Changes in soil organic carbon and nitrogen Changes in soil carbon in successive rotations of Chinese fir are shown in Fig. 4. Eight out of nine observations showed SOC stock reductions from the first to the second rotation, with a mean change of
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
135
Fig. 3. Biomass comparisons for the first, second and third rotations of Chinese fir. The curves are given by: Bs = 243 (1 exp(0.0904A))1.87 (first rotation, R2 = 0.63, n = 28); Bs = 183 (1 exp(0.0937A))1.91 (second rotation, R2 = 0.68, n = 28); Bs = 142 (1 exp(0.0892A))1.90 (third rotation, R2 = 0.67, n = 15).
9.5 5.1% (n = 9). From the second to the third rotation, SOC stocks decreased further for six out of seven observations, with a mean change of 15.3 4.8% (n = 8).
All studies that reported soil C described above also reported soil N. There were generally losses in both soil C and N, but C losses were generally larger than N losses. The mean changes in soil N were 6.2 3.8% (n = 9) and 12.4 2.2% (n = 7) from the first to the second, and from the second to the third rotations, respectively. Due to the larger changes in soil C compared to that in soil N, C:N ratios decreased when soil carbon was lost (Fig. 5). 3.3. Changes in bulk density and its relationship to growth Observed soil bulk density in the first, second and third rotations are shown in Fig. 6. Compared with the
Fig. 4. Comparisons of soil organic carbon (SOC) under the different rotations of Chinese fir (tC ha1).
Fig. 5. Changes in soil C:N ratios in relation to soil C changes under different rotations.
136
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
4. Discussion 4.1. Yield decline, soil degradation and attributable factors
Fig. 6. Comparison of soil bulk density over successive rotations of Chinese fir plantations.
first rotation, bulk density generally increased in the second rotation and increased further in the third rotation although there was a decrease in a few sites. The average increase in bulk density was 6.4 2.9% (n = 19) and 8.8 3.0% (n = 12) from the first to the second, and from the second to the third rotations, respectively. Increases in soil bulk density probably affected stand growth, leading to reduced litter input and ultimately causing a loss of soil carbon. Our results indicate that the growth potential on individual sites was well correlated with soil bulk density, in particular, for the first rotation (Fig. 7).
Our results show that biomass, soil carbon and nitrogen stock were reduced while soil bulk density increased in the successive rotations of Chinese fir (Table 1). The strong correlation between bulk density and growth potential (Fig. 7) suggests that the increase in bulk density could be a primary factor responsible for the observed yield decline. Soil nitrogen was also reduced over successive rotations (Fig. 4), but the C:N ratio decreased with reductions in soil carbon (Fig. 5). A decreasing C:N ratio normally indicates that nitrogen availability is improving. The observations on Chinese fir were similar to earlier studies that also showed yield declines of successive Pinus radiata and coppiced Eucalyptus plantation (Keeves, 1966; Evans, 1992). Harvesting and site preparation practices, e.g., windrowing and inadequate weed control, were believed to be the major cause of the yield decline of P. radiata in South Australia, and counter-measures such as organic matter conservation, careful site preparation and adequate weed control, could greatly improved productivity of second rotations and largely overcome the problem of declining yields (Woods, 1990).
Fig. 7. Growth potential in relation to soil bulk density.
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
137
Table 1 Summary of biomass reduction in relation to soil properties in successive rotations of Chinese fir From first to second rotation
Biomass Soil carbon Bulk density Nitrogen
From second to third rotation
Change (%)
Observed number
Change (%)
Observed number
24.1 9.5 6.4 6.2
28 9 19 9
39.7 15.3 8.8 12.4
15 8 12 7
3.0 5.1 2.9 3.8
The yield decline and soil degradation in successive Chinese fir plantation are probably attributable to poor site preparation practices. Traditional practice for preparing sites for fir production is to slash harvesting residues and burn them. All slash (branches, leaves and other non-timber part of trees), forest floor litter, undergrowth vegetation and even excavated coarse roots are generally burnt on site. This is then usually followed by ploughing the site before replanting. During the following rainy season, the partly burnt materials and surface soil are subject to erosion, resulting in rapid and large loss of soil organic matter and nutrients as well as leading to increased bulk density. This is probably a more important cause for increasing bulk density than the physical compaction during tree felling and pulling of felled logs. Based on 6 years of observations in Fujian, Ma et al. (1997a) found that the rate of soil erosion on a ‘slash and burn’ site of Chinese fir was 88 times that of a control site in the first year following the slash and burn treatment. Although soil erosion decreased exponentially in subsequent years, 38.0 t ha1 of soil eroded in the first 6 years compared to 1.9 t ha1 for a control site. This resulted in losses of 1056 kg ha1 organic matter, 30.3 kg N ha1, 10.4 kg P ha1 and 483 kg K ha1 from burnt sites, compared to 153 kg organic matter ha1, 6.1 kg N ha1, 1.7 kg P ha1 and 78 kg K ha1 from a control site. Zhang (1986) and Ye et al. (1992) also found that slash and burn of residues and site preparation methods had significant impacts on soil organic matter, nutrients and soil biochemical activities. Experiments by Soto et al. (1995) indicated that soil losses by surface runoff from two slash and burnt sites were 46 and 57 t ha1 compared to 1.4 t ha1 from a control site. A recent experiment in Fujian province is studying the effect of establishment technique on subsequent stand growth and soil properties. While the experi-
4.4 4.8 3.0 2.2
ment is still in its early phases, indications are that productivity up to age 6 may be positively related to the amount of slash retention, but, in contrast to other studies, little effect on soil properties has been found (Fan et al., 1998, 1999; Fan, 2004, Personal communication). Some studies have suggested that toxic substances may accumulate over successive rotations of Chinese fir and inhibit tree growth (He, 1992, 1995; Ma et al., 2000b,c). However, while it is well established that conifers produce phenolic substances in their litter that are inhibitory to many organisms, it is less clear whether those phenolics are also inhibitory for the trees themselves, and in particular, whether it could affect the growth of established trees. Evans (1998) pointed out that the effect of allelopathy on productivity remains unsolved. There may be factors other than changes in bulk density that led to reduced tree growth, such as loss of potassium, phosphorus, magnesium and/or microelements, etc. Fertilization experiments showed that potassium and phosphorus can be important for tree growth on some sites (Li et al., 1992a,b,c), and Ma et al. (1997a) observed significant erosion on some burnt site leading to losses of potassium and phosphorus. Some SOC may be lost to the atmosphere especially during regeneration burning. Carbon lost through erosion will flow into rivers, lakes or even the ocean and may not initially add to the CO2 load of the atmosphere. Ma et al. (1997a), for example, found 6.6% of total soil organic matter to be lost during slash and burn, and 10.1% to be lost with erosion over the next 4 years after burning. 4.2. Implications for carbon accounting Based on the analysis described above, we can construct a temporal pattern of carbon stock changes
138
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Fig. 8. Conceived carbon stock changes for successive rotations of Chinese fir plantations, showing a notional sustainably managed plantation (A) and a plantation according to actual observations as summarized in the present work (B).
over successive rotations of Chinese fir plantations. Under sustainable management practice, we could assume biomass increments in the second and third rotations to be the same as during the first rotation, and soil organic carbon to remain unchanged (Fig. 8A). However, our analysis indicates that under actual traditional practice, both biomass increments and soil carbon stocks tend to decrease. Biomass and soil carbon stocks by the end of the second rotation are only about 76% and 90% of those in the first rotation, and they continue to decrease to 60% and 75% by the end of the third rotation (Fig. 8B). Article 3.4 of the Kyoto Protocol allows parties to include forest management as one of activities that could be used to offset some of their greenhouse gas emissions to meet their commitments. The definition of forest management in the Marrakesh Accord explicitly states that forest land eligible for such activity must be managed sustainably (UNFCCC, 2001a), which is a more stringent requirement than that stipulated for managed forests defined by the IPCC (1997).
Therefore there is the concern that inclusion of forest management activities could give rise to unbalanced accounting if the area under forest management under Article 3.4 could exclude areas subject to forest degradation. This is similar to the treatment of fire, where carbon losses due to forest fires are not included under the IPCC default methodology, yet carbon gains from subsequent forest regrowth are allowed to be counted (Kirschbaum, 2000). In such a case, greenhouse gas emissions from human-induced forest degradation should be accounted to achieve balanced accounting. In response to the decision on land use, land-use change and forestry (LULUCF) adopted by COP7 in Marrakesh (UNFCCC, 2001b), IPCC has initiated a program to develop definitions for direct humaninduced forest degradation and methodological options for emissions resulting from such activity. Although there could be many factors causing the observed carbon-stock reduction over successive rotations of Chinese fir, it is indeed a human-induced forest degradation from a carbon-accounting point of view. Accounting and reporting of carbon stock changes under such activities are important for long-term sustainability and management of atmospheric CO2 concentration. It also has special implication for government and forest managers to make special efforts to reverse these stock reductions as a potential action for the mitigation of carbon dioxide emission from managed forests. The Kyoto Protocol also allows Annex I countries to use carbon credits under the clean development mechanism (CDM) through afforestation and reforestation (AR) to offset some of their greenhouse gas emissions. Although the duration of CDM AR project is still subject to negotiations, sustainable management of AR plantations needs to be guaranteed over the long term to ensure the permanence of stored carbon.
5. Conclusions Our literature review and analysis found a significant reduction in growth or biomass stocks, and losses of soil C and N stock over successive rotations of Chinese fir. The growth reduction appears to be attri-
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
butable to an increase of bulk density, but the limited amount of available data suggest that they may not be related to losses of soil nitrogen. Soil nutrients are often also lost in erosion after site preparation which may link to those losses to subsequent stand productivity in the later development stages. Increases in bulk density and losses of soil C and nutrients are probably largely related to ‘slash and burn’ site preparation. All of these results have important implications for carbon accounting and mitigation through managed forests because Chinese fir plantations cannot be considered as a sustainable production system under
139
the silvicultural management regime used over the past decades.
Acknowledgements We would like to give our appreciation to the China Ministry of Science and Technology for its financial support under the project no. 2002CB412508 and Nature Science Foundation of China under project no. 40271109. We would also like to thank Jacqui England and Partap Khanna for many useful suggestions on the manuscript.
140
Appendix A. Sources of data and site description for different rotation of Chinese fir plantation. References
Nitrogen Bulk Locations Age Number Sampling SOM Notes Number Mean Mean Standing biomass density (years) of depth content content of trees height DBH volume (tDW ha1) (%) (g cm3) (tree ha1) (m) rotations (cm) (%) (cm) (m3 ha1)
He and Yu (1992), Fujian Yu and Zhang (1989)
I
14
II
17
I
17
II
0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40
3.22 2.08 3.15 1.68 8.84 3.72 2.94 2.08
0.088 0.077 0.084 0.077 0.117 0.080 0.084 0.072
78.1 65.1 139.3 75.8
Fang (1987)
Hunan
15 15 15
I II III
62 58 51
1.92 1.51 1.75
0.130 0.100 0.100
1.13 1.15 1.16
Zhou et al. (1992)
Fujian
23
I
21
II
19
III
16
I
16
II
0–20 20–60 0–15 16–35 0–10 10–32 0–18 19–40 0–15 16–38
4.28 0.99 5.30 1.07 5.21 1.10 6.38 2.43 7.24 1.81
0.185 0.062 0.212 0.049 0.214 0.051 0.299 0.102 0.272 0.084
0.95 1.32 1.03 0.98 1.07 1.15 0.73 1.23 0.83 1.22
20
I
20
II
20
III
20
I
20
II
0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50
5.92 2.64 2.56 4.68 2.56 2.34 4.30 2.57 2.18 5.20 2.77 1.33 3.50 2.70 2.72
0.20 0.11 0.09 0.15 0.13 0.06 0.09 0.10 0.06 0.24 0.14 0.09 0.16 0.13 0.08
0.82 1.08 1.33 0.97 1.15 1.32 1.17 1.27 1.36 0.82 1.08 1.33 0.97 1.15 1.32
Shao (1992)
Fujian
Average for 23 plots Average for 20 plots Average for 22 plots 1905
16.2
18.9
1995
14.4
15.7
2295
10.1
12.9
1800
17.0
18.8
1995
13.2
16.8
749.3
334.6
128.0
419.6
330.3
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
12
Yang et al. (1996)
Zhejiang
Zhejiang
III
2.85 2.07 1.77 6.62 2.48 2.86 5.01 2.80 1.72 3.95 3.00 1.72 6.28 3.57 2.13 4.09 2.88 2.10 2.78 1.44 1.45
0.10 0.10 0.07 0.19 0.16 0.07 0.18 0.12 0.13 0.11 0.09 0.05 0.12 0.10 0.05 0.10 0.09 0.06 0.10 0.07 0.05
1.17 1.27 1.36 0.82 1.08 1.33 0.97 1.15 1.32 1.17 1.27 1.36 0.82 1.08 1.33 0.97 1.15 1.32 1.17 1.27 1.36
20
I
20
II
20
III
20
I
20
II
20
III
20
I
0–40 40–60 0–40 40–60
1.91 0.70 1.60 0.71
0.048 0.015 0.044 0.019
1.04 1.13 1.06 1.13
20
II
14
I II I II
0–45 0–45 0–45 0–45
4.11 2.56 3.33 2.60
6
I
0–20
3.40
0.096
1.05
6
II
6
I
4
II
6
I
5
II
20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40
1.25 3.23 1.73 2.67 1.74 3.46 1.99 3.44 1.86 4.44 2.18
0.072 0.120 0.048 0.079 0.064 0.107 0.072 0.105 0.059 0.141 0.085
1.23 1.21 1.37 1.14 1.22 1.16 1.29 0.98 1.13 1.12 1.34
14
Sun et al. (2003); Zhang et al. (2001)
Jiangxi
84.1
417.9
274.1
111.3
408.0
347.6
137.5
3925 3175 2500 3525
8.4 7.3 8.2 6.7
10.9 11.2 12.4 9.7
345.3
Average for 13 plots
270.1
Average for 13 plots
171.9 129.4 138.9 99.9
4600
32.8
Average for 3 plots
1725
9.2
Average for 3 plots
3267
34.3
Average for 3 plots
2300
9.8
Average for 3 plots
2500
55.4
Average for 3 plots
3867
32.7
Average for 3 plots 141
0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50 0–10 10–30 30–50
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Lin et al. (1992)
20
142
Appendix A. (Continued ) References
Ma et al. (2000a,b, 2003)
Zhejiang
Fujian
Notes
Age (years)
Number of rotations
Sampling depth (cm)
SOM content (%)
Nitrogen content (%)
Bulk density (g cm3)
Number of trees (tree ha1)
12
I
3900
89.9
Average for 3 plots
I
2600
86.0
Average for 3 plots
12
II
3850
95.9
Average for 3 plots
12
I
2067
81.3
Average for 3 plots
12
II
1.03 1.22 1.30 1.50 0.99 1.14 1.24 1.40 1.11 1.25 1.14 1.30
Average for 3 plots
12
0.106 0.078 0.086 0.054 0.119 0.072 0.094 0.055 0.113 0.086 0.112 0.063
57.4
II
3.70 1.72 3.23 1.14 3.16 1.52 3.15 1.45 4.32 2.69 4.23 2.42
1800
12
0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40
2233
54.1
Average for 3 plots
21
I
21
II
0–20 20–40 0–20 20–40
3.79 2.53 3.36 1.91
0.122 0.096 0.110 0.080
1.16 1.16 1.19 1.19
5
I
0–20
3.81
0.174
0.98
3340
5.5
8.0
95.9
68.2
Average for 5 plots
6
II
5.9
8.9
75.0
53.5
Average for 5 plots
1.18
3350
5.3
8.1
58.0
39.6
Average for 5 plots
8
I
1.02
2300
7.6
10.0
109.9
95.9
Average for 5 plots
9
II
1.11
2174
7.5
9.9
74.1
73.2
Average for 5 plots
9
III
0.105 0.156 0.103 0.138 0.095 0.149 0.096 0.139 0.091 0.131 0.082 0.171 0.125 0.133 0.104 0.124 0.079 0.156 0.106 0.134 0.088
3320
III
1.73 3.49 1.63 2.95 1.51 3.42 1.56 3.11 1.51 2.64 1.28 3.61 1.95 3.12 1.88 2.69 1.19 3.81 1.80 3.59 1.65
1.07
6
20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40 0–20 20–40
1.20
2195
6.6
9.0
55.3
54.6
Average for 5 plots
1.02
1550
13.0
16.3
215.1
121.5
Average for 5 plots
1.21
1575
11.6
14.7
163.5
105.8
Average for 5 plots
1.25
1650
11.2
13.7
121.9
78.4
Average for 5 plots
1.09
1566
14.4
17.6
315.1
149.9
Average for 5 plots
1.20
1550
13.0
15.9
235.9
118.8
Average for 5 plots
15
I
15
II
16
III
19
I
19
II
Mean height (m)
Mean DBH (cm)
Standing volume (m3 ha1)
biomass (tDW ha1)
345.3 270.1
Average for 13 plots Average for 13 plots
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Du et al. (2001)
Locations
22
III
0–20 20–40
3.03 1.62
0.122 0.085
1.25
1800
13.6
16.5
206.1
92.2
Average for 5 plots
20 20 20 20 20 20
I II I II I II
20–40 20–40 20–40 20–40 20–40 20–40
4.62 2.57 4.38 2.44 4.25 2.29
3250 3342 3316 3406 3161 3273
12.3 8.9 11.7 8.3 11.3 7.9
13.1 10.9 12.9 10.5 12.7 10.0
309.1 122.1 223.8 118.9 207.1 110.0
Yang et al. (1997)
Fujian
29
I
19.9
21.3
648.8
327.1
Average for 5 plots
II
2005
18.2
17.7
500.7
239.6
Average for 5 plots
29
III
3.06 1.45 2.88 1.24 2.58 1.13
1845
29
0–20 20–40 0–20 20–40 0–20 20–40
2084
15.7
16.5
346.6
190.0
Average for 5 plots
0–20
0.81
0.078
1.41
3225
5.3
9.0
64.5
44.4
Average for 3 plots
20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60
0.47 0.17 1.62 0.98 0.77 2.12 0.85 0.47 0.87 0.59 0.20 0.92 0.37 0.17 3.23 1.88 0.89 2.04 1.16 0.90 2.03 0.90 0.86 3.36 1.11 1.00
0.152 0.032 0.118 0.084 0.076 0.106 0.031 0.031 0.083 0.059 0.039 0.079 0.061 0.011 0.140 0.077 0.042 0.128 0.089 0.078 0.147 0.082 0.088 0.147 0.046 0.033
1.54 1.34 1.08 1.06 1.01 1.21 1.16 1.15 0.99 1.33 1.43 1.27 1.25 1.35 1.11 1.41 1.38 1.14 1.19 1.24 0.82 0.92 0.95 1.17 1.25 1.16
3200
5.1
7.6
44.8
38.3
Average for 3 plots
3050
4.9
6.8
32.6
20.3
Average for 3 plots
2850
40.5
13.6
234.3
112.1
Average for 3 plots
2950
9.6
12.7
196.8
101.7
Average for 3 plots
2530
9.2
9.5
91.6
32.6
Average for 3 plots
1095
15.8
23.7
390.3
183.4
Average for 3 plots
1550
15.1
19.9
377.9
170.3
Average for 3 plots
1620
14.6
18.1
315.9
127.7
Average for 3 plots
Ma et al. (2002)
Fujian
6
I
Yu et al. (2000) 6
II
6
III
12
I
12
II
12
III
31
I
31
II
31
III
143
Fujian
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Ying (1997)
144
Appendix A. (Continued ) References
Locations
Age (years)
Sampling depth (cm)
SOM content (%)
Nitrogen content (%)
Bulk density (g cm3)
Number of trees (tree ha1)
6
I
6
II
6
III
0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60 0–20 20–40 40–60
1.13 0.46 0.27 1.69 0.81 0.84 2.18 2.17 1.89 1.82 1.01 0.45 1.02 0.56 0.29 2.02 1.05 0.21 1.41 0.95 0.61 2.84 1.54 0.79 2.80 0.70 0.87
0.112 0.060 0.049 0.139 0.107 0.084 0.173 0.044 0.043 0.108 0.080 0.079 0.092 0.058 0.046 0.097 0.046 0.025 0.114 0.162 0.076 0.168 0.120 0.075 0.130 0.079 0.073
1.08 1.21 1.38 1.08 1.07 1.18 0.86 1.05 1.36 0.92 1.09 1.3 1.32 1.34 1.36 1.4 1.18 1.54 1.1 1.28 1.22 1.06 1.04 1.04 1.26 1.44 1.18
12
I
12
II
12
III
31
I
31
II
31
III
Mean height (m)
Mean DBH (cm)
3150
6.3
9.4
78.8
49.6
Average for 3 plots
3090
5.7
8.4
56.9
46.7
Average for 3 plots
3150
5.4
7.4
43.2
25.1
Average for 3 plots
2760
11.8
14.5
287.3
123.1
Average for 3 plots
2940
10.3
13.1
221.7
108.8
Average for 3 plots
2625
9.9
10.6
126.0
48.6
Average for 3 plots
1200
18.8
24.4
529.3
216.5
Average for 3 plots
1650
18.0
20.1
477.8
213.4
Average for 3 plots
1620
17.2
19.8
437.2
178.8
Average for 3 plots
87.9 76.0
Average for 3 plots Average for 3 plots
Hu and Xu (1994)
Anhui
9 9
I II
3600 3600
7.9 7.1
10.3 9.1
Tian et al. (2002)
Hunan
11 11
I II
2280 2080
10.5 9.8
12.7 11.7
Standing volume (m3 ha1)
biomass (tDW ha1)
Notes
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Number of rotations
X.-Q. Zhang et al. / Forest Ecology and Management 202 (2004) 131–147
Appendix B. The basic notion of the correction for measurements using constant depth but different soil mass is to modify calculations to estimate the likely measurements that would have been expected had samples been taken to a common mass of mineral soil. Some studies have taken appropriate measurements so that soil organic carbon amounts could be compared for the same mass of soil. In other studies, corrections were not made at the time when measurements were taken, but sufficient additional measurements were taken and reported to allow subsequent corrections to be made. The aim of the correction is to estimate the amount of carbon that would be contained to a depth that corresponds to an identical mass of soil in different samples. As the first step, we assumed that bulk density (BD) changed linearly with soil depth (L) and make the regression with BD ¼ a þ bL
(B.1)
Where a and b are the intercept and slope parameters. Secondly, we need to calculate the soil mass of the additional layer, W, given as: W ¼ W2 W1
(B.2)
Where W1 and W2 represent sampled soil mass for less compacted soil and most compacted soil, respectively. Thirdly, we calculated the required thickness of the additional layer, t, given as: t ¼ Wða þ bdÞ
(B.3)
where d is the mean depth of the new layer which is given as: t (B.4) 2 where ds is the depth to which the soil had already been sampled. Combining Eqs. (B.3) and (B.4) leads to a quadratic equation with only one sensible solution which is given by: qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ða þ bds Þ þ ða þ bds Þ2 þ 2bW t¼ (B.5) b The bulk density of the extra layer was calculated using Eqs. (B.1) and (B.4). The soil organic carbon d ¼ ds þ
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and nitrogen contents of the additional layer were estimated assuming they changed exponentially with soil depth if the number of sampled layers was three, and linearly if only two layers had been sampled. Data were excluded where only one soil layer was sampled or where too large an extrapolation from observed properties was required.
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