Comparison of depth- and mass-based approaches for estimating changes in forest soil carbon stocks: A case study in young plantations and secondary forests in West Java, Indonesia

Forest Ecology and Management 262 (2011) 1659–1667

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Comparison of depth- and mass-based approaches for estimating changes in forest soil carbon stocks: A case study in young plantations and secondary forests in West Java, Indonesia Jumpei Toriyama a,⇑, Tsuyoshi Kato b, Chairil Anwar Siregar c, Harris Herman Siringoringo c, Seiichi Ohta d, Yoshiyuki Kiyono a a

Bureau of Climate Change, Forestry and Forest Products Research Institute (FFPRI), 1 Matsunosato Tsukuba, Ibaraki 305-8687, Japan Former expert of Japan International Cooperation Agency (JICA), Nibancho Center Building 5-25, Niban-cho, Chiyoda-ku, Tokyo 102-8012, Japan c Forestry Research and Development Agency (FORDA), Jalan Gunung Batu 5, Bogor 16610, Indonesia d Graduate School of Agriculture, Kyoto University, Kyoto City 606-8502, Japan b

a r t i c l e

i n f o

Article history: Received 31 May 2011 Received in revised form 20 July 2011 Accepted 23 July 2011 Available online 25 August 2011 Keywords: Soil carbon stock Mass-based approach Kyoto Protocol Acacia mangium Shorea leprosula

a b s t r a c t Soil carbon (C) stocks in forest ecosystems have been widely estimated to a fixed soil depth (i.e., 0–30 cm) to clarify temporal changes in the C pool. However, surface elevations change as a result of compaction or expansion of the soil under forest management and land use. On the other hand, the calculation of soil C stocks based on ‘‘equivalent soil mass’’ is not affected by compaction or expansion of forest soil. To contribute to the development of a forest C accounting methodology, we compared changes in soil C stocks over 4 years between depth- and mass-based approaches using original soil data collected at 0–30 cm depths in young plantations and secondary forests in West Java, Indonesia. Our methodology expanded on the mass-based approach; rather than using one representative value for the mass-based calculation of soil C stocks, we adjusted individual values, maintaining the coefficient of variance in soil mass. We also considered the effect of an increase or decrease in soil organic matter on equivalent soil mass. Both increasing and decreasing trends in soil C stocks became clearer when the mass-based approach was used rather than the depth-based approach. The trends in soil C stocks based on equivalent soil mass were particularly evident in the surface soil layers (0–5 cm) and in plantation sites, compared with those for soil profiles including subsurface soil layers (0–30 cm) and in secondary forests. These trends in soil C stocks corresponded with temporal trends in litter stocks. We suggest that equivalent mass-basis soil C stock for the upper 30 cm of soil be calculated based on multiple soil layers to reduce estimation errors. Changes in soil organic matter mass had little effect on the estimation of soil C stock on an equivalent mass basis. For the development of a forest C accounting system, the mass-based approach should be used to characterize temporal trends in soil C stocks and to improve C cycle models, rather than simpler methods of calculating soil C stocks. These improvements will help to increase the tier level of country-specific forest C accounting systems. Ó 2011 Elsevier B.V. All rights reserved.

1. Introduction Forest soil is an important component of the greenhouse gas balance at both national and global levels (Intergovernmental Panel on Climate Change (IPCC, 2006). Globally, more than 1500 Pg of soil carbon (C) is stored in the top 1 m of terrestrial ecosystems and approximately half of this is distributed in forested regions (Jobbágy and Jackson, 2000). The forest soil C pool is affected by changes in aboveground biomass, such as deforestation and afforestation. Afforestation of abandoned land often enhances soil C storage especially when long-term rotation, nitrogen-fixing ⇑ Corresponding author. Tel.: +81 29 829 8330; fax: +81 29 874 3720. E-mail address: [email protected] (J. Toriyama). 0378-1127/$ - see front matter Ó 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.foreco.2011.07.027

species, or fertilizer is applied (Jandl et al., 2007; Johnson, 1992; Lal, 2005; Paul et al., 2002). Thus, over the last decade, soil C stocks have been measured under Afforestation/Reforestation (A/R) projects associated with the Clean Development Mechanism (CDM) (García-Oliva and Masera, 2004; Jandl et al., 2007; Ringius, 2002), one of the C sequestration strategies specified in the Kyoto Protocol, to determine whether soil C is eligible for credit under the CDM. In developing countries in tropical regions, the development of a C accounting system for Reducing Emissions from Deforestation and Degradation (REDD) is also an important goal at present (GOFC-GOLD, 2010). To develop scientifically sound schemes for A/R CDM or REDD, the methodology used during the First Commitment Period of the Kyoto Protocol (2008–2012) should be reexamined in the transition to the Second Commitment Period

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J. Toriyama et al. / Forest Ecology and Management 262 (2011) 1659–1667

A erage treee heig Ave h ghtt (m m)

10

Plantation

Secondaryy forest f

8 Maribaya

6

Ngasuh 4 Maribaya 2

g Ngasuh

0 0

300

600

900

1200

1500

0

300

Time (days)

600

900

1200

1500

Time (days)

Fig. 1. Tree height over time at the study sites. Time = days elapsed from July 1, 2001. Average tree height = mean height of trees taller than 1.5 m (secondary forest) and height of all trees (plantation).

(2013–2018), considering difficulties experienced during the First Commitment Period. The ‘‘stock-change’’ method is commonly used to estimate changes in soil C storage with time (IPCC, 2003). This method is based on comparison of soil C stocks per unit area between two different time points, and involves two approaches to expressing soil C stocks per unit area (Mg ha1 of C): depth- and mass-based approaches (Ellert and Bettanym, 1995; Gifford and Roderick, 2003; IPCC, 2003; McKenzie et al., 2000). The depth-based approach has been widely used and recommended and requires the measurement of soil C pools to a fixed depth (e.g., 0–30 cm; GOFC-GOLD, 2010; IPCC, 2003; Paul et al., 2002). However, surface elevation of soil changes because of erosion or deposition, and compaction or expansion of the soil (Ellert and Bettanym, 1995; Gifford and Roderick, 2003). Changes in surface elevation caused by erosion or deposition cannot be managed by either the depthor the mass-based approaches, and are not the subject of this paper. Soil compaction and expansion, however, usually occur with land use changes, especially near the soil surface. Projects designed to enhance soil organic C likely cause decreases in soil bulk density (Huong et al., 2008; IPCC, 2003); thus, sampling to a fixed depth from the surface in such situations means that a different mass of soil material is sampled (Ellert and Bettanym, 1995; Gifford and Roderick, 2003). This problem with the depth-based approach may obscure actual trends in soil C stock with time. On the other hand, the mass-based approach using ‘‘equivalent soil mass’’ avoids errors associated with compaction or expansion of the soil (Ellert and Bettanym, 1995; Gifford and Roderick, 2003), although it is less common than the depth-based approach. The mass-based approach with the specified sampling technique requires the additional step of obtaining information about changes in soil bulk density ahead of sampling so that adjustments can be made to collect soil sample of equivalent soil mass (Gifford and Roderick, 2003; IPCC, 2003). Thus, an alternative method has been proposed in which soil C data for a fixed soil depth can be adjusted as part of the calculations of equivalent soil mass basis (Ellert and Bettanym, 1995; McKenzie et al., 2000). This approach has been effective at estimating C, water, and nutrient stocks in agricultural land under tillage and in pastures following deforestation where soil bulk density changes (Ellert and Bettanym, 1995; Fearnside and Barbosa, 1998; Wuest, 2009). Another advantage of the mass-based calculation of soil C stocks is that it can efficiently use archived depth-based data. However, the mass-based approach has only been applied in a few afforestation sites, where temporal changes in bulk density are likely to be small compared with those in cultivated agricultural lands. In this study, we calculated soil C stocks using both soil depthand mass-based approaches using original soil C data collected at

0–30 cm depth in young plantations and secondary forests in Indonesia. The objectives of this study were to compare the changes in soil C stocks for two land use types between the soil depth- and mass-based approaches and to propose a methodology for detecting relatively small changes in soil C stocks in forest ecosystems.

2. Materials and methods 2.1. Study site We established two experimental sites, Maribaya and Ngasuh, in West Java Province, Indonesia (6.4–6°S, 106.4–5°E). The annual precipitation in this area is 3000 mm. The two sites are 15 km apart; both areas are flat and surrounded by undulating land of Tertiary sedimentary rocks. The study sites were selected on level-to-slightly-sloped ground with little erosion. We created different scenarios for the two sites; at Maribaya, a fast-growing species was planted after cutting of a forest with relatively low biomass, and at Ngasuh, a slow-growing species was planted after cutting of a forest with biomass typical of an average forest in this region. Maribaya was characterized by secondary forest, dominated by Schima wallichii. This secondary forest had been used for shifting cultivation and was fallow during the study. At the beginning of the study in July 2001, the secondary forest had a low average tree height (Fig. 1). The soils in Maribaya were Haplic Acrisols, characterized generally by a clayey texture and a high exchangeable Al content (Table 1); the topsoil was dark brown in color (7.5YR 3/4 in the Munsell color system) with a strong, coarse, and subangular blocky structure. The original vegetation in Ngasuh was a secondary forest of Maesopsis emini and S. wallichii. Shifting cultivation had not been conducted in the study area. At the start of the study, this secondary forest had a higher average tree height than that in Maribaya (Fig. 1). The soils in Ngasuh were Haplic Ferralsols with a high clay content and low exchangeable base content (Table 1). The topsoil had a brownish-black color (10YR 3/2) and a very weak, medium, and granular structure. Both sites included 5 ha of plantation in a total experimental area of 15 ha. After clear-cutting the secondary forests, Acacia mangium and Shorea leprosula were planted in Maribaya and Ngasuh, respectively. Trees were planted in 30-cm deep holes with a 2  3 m spacing. During the study, the A. mangium plantation in Maribaya showed a rapid increase in tree biomass and reached an average tree height of 10.0 m in 2005 (Fig. 1). Meanwhile, the average tree height of S. leprosula in Ngasuh was 2.5 m in 2005 (Fig. 1).

J. Toriyama et al. / Forest Ecology and Management 262 (2011) 1659–1667 Table 1 Soil chemical properties in representative soil profiles of the secondary forests at Maribaya and Ngasuh. Site

Depth (cm)

Horizon

Clay (%)

Ex. bases (cmol kg1)

Ex. Al (cmol kg1)

Ca

Mg

K

Maribaya

0–10 10–20 20–39 39–58 58–79 79–100+

Ah A BA1 BA2 Bt1 Bt2

64 67 75 77 82 80

7.9 3.3 2.5 2.7 2.5 2.8

5.1 2.4 1.8 1.5 1.4 1.7

0.2 0.1 0.1 0.1 0.1 0.1

3.0 10.5 13.6 14.3 15.3 15.7

Ngasuh

0–7 7–21 21–36 36–59 59–80 80–100+

Ah A AB Bo1 Bo2 Bo3

77 80 73 81 80 80

2.5 0.5 0.4 0.4 0.4 0.4

1.7 0.3 0.1 0.2 0.1 0.1

0.5 0.1 0.1 0.0 0.0 0.0

2.7 4.4 4.1 3.9 3.8 3.5

Ex. bases and Al = exchangeable bases and aluminum, respectively.

2.2. Sampling methodology We prepared 40 sampling subunits within each plantation and secondary forest area. In each plantation area, four blocks (20  30 m) were randomly arranged, with 10 subunits inside each block. In each secondary forest area, 10 points were randomly selected and four subunits were arranged around each point. Over 4 years, soil samples were collected twice from two different sections within each sampling subunit. The first sampling was conducted in October (Maribaya) and November (Ngasuh) 2001 before planting, and the second sampling occurred in August and September 2005, respectively, 46 months after the first sampling. We collected soil samples from four soil layers (0–5, 5–10, 10–20, and 20–30 cm in depth) in each sampling subunit using four 100-cm3 (20 cm2  5 cm) sampling cylinders in each layer. The four cylinder samples in each layer were composited. Thus, soil samples of 1280 layers were prepared in total. We also collected litter samples four times from four different sections within the sampling subunits. All the litter within a 0.25-m2 frame was collected. Litter sampling was conducted from October and November 2001 until 34 months after the first sampling. 2.3. Sample treatment and analysis Soil samples were air-dried, weighed, and sieved to separate fine soil material (<2 mm) and coarse roots and gravel. Coarse roots and gravel were removed, oven-dried, and weighed. A portion of the fine soil material was extracted and pulverized for measuring moisture factor and total C concentration (TC; Sumigraph NC analyzer NC-800). Bulk density (BD) was calculated using the air-dried weight of fine soil material per volume and the moisture factor. Litter samples were oven-dried at 70 °C for 72 h and weighed. 2.4. Calculation of soil C stock 2.4.1. Depth-based approach For the depth-based approach, soil C stocks were calculated in a same way as for previous soil C inventories (Ellert and Bettanym, 1995), as shown in Eq. (1). Because the studied soil was highly weathered and no boulders were observed at 0–30 cm depth, corrections of soil C stocks for stoniness were not conducted.

Cstockdepth ðnÞ ¼

n X

TCðiÞ  BDðiÞ  THðiÞ

Mg C ha1), TC(i) the total soil C concentration in the ith layer (g C kg1), BD(i) the bulk density in the ith layer (Mg m3, and TH(i) is the thickness of the ith layer (m). 2.4.2. Mass-based approach The concept and methodology for calculating soil C stocks based on equivalent soil mass were presented by Ellert and Bettanym (1995). Given the spatial variability of soil properties, equivalent soil mass should be calculated for each sampling point (Gifford and Roderick, 2003). Thus, rather than using one representative value for the mass-based calculation of soil C stocks as has been done previously (Ellert and Bettanym, 1995), in this study we adjusted individual values. Additionally, we used the mineral soil mass for the calculation of equivalent soil mass, rather than bulk soil mass (Ellert and Bettanym, 1995), to eliminate the effects of changes in soil organic matter on the equivalent soil mass. Soil C stocks in the first survey (reference year; 2001 in this paper) were calculated in the same manner as in the depth-based approach. In the second survey, (year 2005 in this paper), soil C stocks were adjusted according to the difference in the mean cumulative mass of the soil mineral fraction between the first and the second surveys. A series of calculations was conducted; first, the cumulative mass of the soil mineral fraction was calculated using soil data from the first survey to determine equivalent soil mass.

BDmf ¼ BD  BDsom n X MFmassðnÞ ¼ BDmf ðiÞ  THðiÞ

ð2Þ ð3Þ

i¼1

where BDmf is the mass of soil mineral fraction per volume (Mg m3), BDsom the mass of soil organic matter (Mg m3), BD  TC  1.724  103, MFmass(n) the cumulative mass of soil mineral fraction to the bottom of the nth layer (Mg ha1), and BDmf(i) is the BDmf in the ith layer (Mg m3). The soil layers at 0–5, 5–10, 10–20, and 20–30 cm depth in this study correspond to layers 1–4 in the equations, respectively. The validity of the conversion factor (1.724; Pribyl, 2010), the mass ratio of soil organic C to soil organic matter, is examined in the Discussion. There are several ways to calculate the equivalent soil mass in each sampling subunit (Fig. 2). While a representative value can be used for the determination of equivalent soil mass (Fig. 2c; Diekow et al., 2005; Russell et al., 2007), we used the ratio of mean values of cumulative soil mass in the first and second survey to moderate the coefficient of variance in cumulative soil mass (Fig. 2e), considering the spatial variability in cumulative soil mass within the study sites.

MFmassequiv ¼ MFmass2nd  M1st  M 1 2nd

ð4Þ

where MFmassequiv is the equivalent mass of soil mineral fraction in each sampling subunit (Mg ha1; Fig. 2e), MFmass2nd the cumulative mass of soil mineral fraction in the second survey in each sampling subunit (Mg ha1; Fig. 2b), and M1st and M2nd is the mean MFmass for the subunit (n = 40) in the first and second survey, respectively. The soil C stock, originally calculated for a fixed soil depth, was adjusted to an equivalent soil mass basis according to the difference between MFmassequiv and MFmass2nd.

Cstockmass ðnÞ ¼ Cstockdepth ðnÞ þ TCmf ðiÞ  ðMFmassequiv ðnÞ  MFmass2nd ðnÞÞ

ð1Þ

i¼1

where is the Cstockdepth(n) is the cumulative soil C stock at a fixed soil depth to the bottom of the nth layer (kg C m2  10 =

1661

TCmf ðiÞ ¼



TCmf ðn þ 1Þ ðMFmassequiv ðnÞ > MFmass2nd ðnÞÞ TCmf ðnÞ

ðMFmassequiv ðnÞ < MFmass2nd ðnÞÞ

ð5Þ

ð6Þ

J. Toriyama et al. / Forest Ecology and Management 262 (2011) 1659–1667

Cumu Cu ulattivee so oil maass (M Mg ha--1)

1662

(ANOVA) was conducted for each site and land use type. The factor of block or point in the soil sampling design was incorporated as a random effect. All statistical tests were conducted using the ‘R’ software (ver. 2.11; R Development Core Team, 2005).

2600

3. Results

2200

3.1. Soil C content, bulk density, and soil C density

1800

((a))

((b))

((c))

((d))

((e))

Fig. 2. Calculation of equivalent soil mass using sample data for 0–30 cm depth. n = 10. (a) Cumulative soil mass in the first survey (mean = 2297 Mg ha1, standard deviation (SD) = 263, coefficient of variance (CV) = 11.4%). (b) Cumulative soil mass in the second survey (mean = 2135 Mg ha1, SD = 201, CV = 9.4%). (c) Equivalent soil mass adjusted by average soil mass (mean = 2297 Mg ha1, SD = 0, CV = 0%). (d) Equivalent soil mass adjusted by the difference in the mean of (a) and (b) (mean = 2297 Mg ha1, SD = 201, CV = 8.8%). (e) Equivalent soil mass adjusted by the ratio of the mean of (a) and (b) (mean = 2297 Mg ha1, SD = 217, CV = 9.4%).

where Cstockmass(n) is the cumulative soil C stock adjusted to the equivalent soil mass up to the nth layer (Mg C ha1), and TCmf(i) is the concentration of total soil C per mass of soil mineral fraction 3 in the ith layer, TC  BD  BD1 mf  10 . When n = 4 in Eq. (6), TCmf(4) is uniformly assigned to TCmf(i). Briefly, we assumed that the C concentration (TCmf) in the 20–30 ± x cm soil layer was equal to that sampled from the 20–30 cm layer. In this study, we did not apply the mass-based approach to compare the soil C stocks of different land use types (plantation vs. secondary forest). The use of the mass-based approach for a chronosequential study assumes equivalent soil mass for two adjacent sites with different land use. However, soil bulk density may not be equal between the two sites, even for the original soil conditions. Thus, in this study we only examined within-site temporal changes in soil C stocks. 2.5. Statistical analysis To compare the soil properties in each layer and the soil C stocks between 2001 (YR1) and 2005 (YR5), analysis of variance

During the four year study, TC in Maribaya and Ngasuh exhibited different trends. In Maribaya, TC in the plantation clearly increased at 0–30 cm depth (p < 0.001), especially at 0–5 cm depth, whereas in the secondary forest, a significant increase (p < 0.001) in TC was observed only in the surface soil layers (Table 2). TC in Ngasuh decreased with time, except at 10–30 cm depth in the secondary forest. The decrease in TC in Ngasuh was significant (p < 0.001) at 0–5 cm depth in both the plantation and the secondary forest (Table 2). Generally, BD decreased in Maribaya and increased in Ngasuh during the 4 years. The ratio of BD in the second and first surveys (YR5/YR1; Table 3) in Maribaya ranged from 0.85 to 0.96, and had the lowest value in the plantation at 0–5 cm depth. In contrast, the YR5/YR1 value for BD in Ngasuh ranged from 1.01 to 1.17 and was highest at 0–5 cm depth in the plantation. In the sample treatment process, nine missing values of BD occurred in the secondary forest in Maribaya, and the mean value from the same layer was assigned to calculate the soil C stock of each subunit. Soil C density, the product of TC and BD, increased slightly with time in some subsurface soil layers. Soil C density was relatively unchanged with time at 0–10 cm depth in Maribaya and Ngasuh, increased at 10–20 cm depth, except in the secondary forest in Maribaya, and increased at 20–30 cm depth in the Maribaya plantation and the Ngasuh secondary forest (Table 4).

3.2. Density and cumulative mass of the soil mineral fraction The density of the soil mineral fraction at the same depth differed between the first and second soil surveys. The density of the soil mineral fraction in Maribaya was higher in YR1 than in YR5, whereas that at Ngasuh in YR1 was similar to or lower than that in YR5 (Table 5).

Table 2 Total soil C concentrations in 2001 and 2005. Site

Maribaya

Ngasuh

Landuse

Depth (cm)

Total soil C (g kg1), mean ± SD YR1

YR5

YR5/YR1

ANOVA F-value

Plantation

0–5 5–10 10–20 20–30

40.3 ± 8.4 31.5 ± 6.0 24.5 ± 5.4 20.4 ± 4.3

47.9 ± 8.8 36.7 ± 6.7 28.6 ± 6.0 23.0 ± 4.9

1.19 1.17 1.16 1.13

22.2*** 21.8*** 19.3*** 14.7***

Secondary forest

0–5 5–10 10–20 20–30

33.7 ± 5.5 26.5 ± 4.4 21.6 ± 4.4 17.5 ± 2.7

38.1 ± 4.8 27.7 ± 3.4 22.2 ± 2.8 17.9 ± 2.0

1.13 1.05 1.03 1.03

14.5*** 2.4 0.8 1.4

Plantation

0–5 5–10 10–20 20–30

58.5 ± 8.2 43.0 ± 6.8 35.8 ± 5.8 28.2 ± 4.8

48.3 ± 8.7 41.4 ± 6.8 34.8 ± 5.2 27.2 ± 4.7

0.82 0.96 0.97 0.97

27.4*** 1.3 0.8 0.8

Secondary forest

0–5 5–10 10–20 20–30

60.7 ± 8.4 46.0 ± 7.8 35.4 ± 5.4 27.0 ± 4.1

54.7 ± 8.1 44.4 ± 7.1 38.1 ± 8.1 31.3 ± 8.2

0.90 0.97 1.08 1.16

12.7*** 1.3 4.0 9.7**

n = 40; SD = standard deviation; YR1 and YR5 = year 2001 and 2005, respectively. ** p < 0.01. *** p < 0.001.

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J. Toriyama et al. / Forest Ecology and Management 262 (2011) 1659–1667 Table 3 Soil bulk density in 2001 and 2005. Bulk density (Mg m3), mean ± SD

Site

Landuse

Depth (cm)

YR1

YR5

Maribaya

Plantation

0–5 5–10 10–20 20–30

0.728 ± 0.091 0.830 ± 0.078 0.860 ± 0.098 0.888 ± 0.100

0.620 ± 0.108 0.749 ± 0.106 0.826 ± 0.107 0.847 ± 0.102

0.85 0.90 0.96 0.95

35.0*** 25.6*** 7.5** 9.0**

Secondary forest

0–5 5–10 10–20 20–30

0.861 ± 0.085 0.902 ± 0.092 0.940 ± 0.073 0.945 ± 0.057

0.759 ± 0.089 0.868 ± 0.099 0.892 ± 0.116 0.892 ± 0.085

0.88 0.96 0.95 0.94

n/a n/a n/a n/a

Plantation

0–5 5–10 10–20 20–30

0.574 ± 0.089 0.666 ± 0.081 0.694 ± 0.069 0.733 ± 0.060

0.669 ± 0.113 0.699 ± 0.077 0.764 ± 0.107 0.776 ± 0.096

1.17 1.05 1.10 1.06

21.9*** 6.6* 14.2*** 7.4**

Secondary forest

0–5 5–10 10–20 20–30

0.527 ± 0.062 0.641 ± 0.054 0.680 ± 0.050 0.720 ± 0.048

0.584 ± 0.075 0.662 ± 0.083 0.683 ± 0.088 0.734 ± 0.106

1.11 1.03 1.01 1.02

11.8** 2.1 0.1 0.7

Ngasuh

YR5/YR1

ANOVA F-value

(n = 39 (n = 36 (n = 38 (n = 39

in in in in

YR1) YR1) YR1) YR1)

n = 40, except for secondary forest in Maribaya; SD = standard deviation; YR1 and YR5 = year 2001 and 2005, respectively; n/a = not applicable. p < 0.05. p < 0.01. *** p < 0.001. *

**

Table 4 Soil carbon density in 2001 and 2005. Site

Maribaya

Ngasuh

Landuse

Depth (cm)

Soil C density (Mg C ha1 cm1), mean ± SD YR1

YR5

YR5/YR1

ANOVA F-value

Plantation

0–5 5–10 10–20 20–30

2.88 ± 0.46 2.59 ± 0.41 2.08 ± 0.39 1.79 ± 0.33

2.91 ± 0.50 2.71 ± 0.41 2.33 ± 0.46 1.93 ± 0.37

1.01 1.05 1.12 1.08

<0.1 1.4 7.9** 5.9*

Secondary forest

0–5 5–10 10–20 20–30

2.88 ± 0.42 2.37 ± 0.37 2.02 ± 0.38 1.64 ± 0.19

2.87 ± 0.36 2.39 ± 0.29 1.97 ± 0.30 1.59 ± 0.16

1.00 1.01 0.98 0.97

<0.1 <0.1 0.4 1.5

Plantation

0–5 5–10 10–20 20–30

3.30 ± 0.29 2.82 ± 0.31 2.46 ± 0.34 2.04 ± 0.27

3.21 ± 0.71 2.88 ± 0.48 2.65 ± 0.46 2.10 ± 0.37

0.97 1.02 1.08 1.03

0.6 0.4 4.5* 0.5

Secondary forest

0–5 5–10 10–20 20–30

3.16 ± 0.31 2.94 ± 0.47 2.39 ± 0.33 1.93 ± 0.24

3.17 ± 0.51 2.92 ± 0.44 2.58 ± 0.54 2.26 ± 0.51

1.00 0.99 1.08 1.17

<0.1 <0.1 4.8* 13.2***

n = 40; SD = standard deviation; YR1 and YR5 = year 2001 and 2005, respectively. * p < 0.05. ** p < 0.01. *** p < 0.001.

The YR5/YR1 value for the cumulative mass of the soil mineral fraction ranged from 0.84 to 0.94 in Maribaya and was lowest at 0–5 cm depth, whereas that in Ngasuh ranged from 1.03 to 1.19 and was highest at 0–5 cm depth (Table 5). The cumulative mass of the soil mineral fraction obtained from the upper 30 cm in YR5 was comparable to those from 27.9 and 28.2 cm thicknesses in YR1 for the plantation and secondary forest in Maribaya, respectively, and 32.5 and 30.7 cm in Ngasuh, respectively (Table 5). 3.3. Soil C stock Changes in soil C stocks between the first and second soil surveys were more apparent under the mass-based approach than the depth-based approach. When the depth-based approach was

used, the soil C stock of the surface soil layers did not differ between YR1 and YR5 within each site or by land use type (Table 6); at 0–30 cm depth, the soil C stock increased by 4.6 and 5.0 Mg ha1 of C (p < 0.05) over 4 years in the Maribaya plantation and the Ngasuh secondary forest, respectively, and was relatively unchanged in the secondary forest of Maribaya and the Ngasuh plantation (Table 6). In contrast, the mass-based approach clearly showed temporal changes in soil C stock for each site and land use type, especially in the surface soil layers. A significant increase and decrease in soil C stock with time was found in soil at 0–10 cm depth in Maribaya and Ngasuh, respectively (Table 6). These changes were more prominent in the plantation than the secondary forest in both Maribaya and Ngasuh. The temporal change in soil C stock at

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Table 5 Density and cumulative mass of soil mineral fraction in 2001 and 2005. Site

Maribaya

Ngasuh

Landuse

Soil MF density, mean

Soil MF mass, mean

Equivalent thickness of YR5 to YR1 (cm)

Depth (cm)

YR1 (Mg ha1 cm1)

YR5 (Mg ha1 cm1)

Depth (cm)

YR1 (Mg ha1)

YR5 (Mg ha1)

YR5/ YR1

Plantation

0–5 5–10 10–20 20–30

68 79 82 86

57 70 79 81

0–5 0–10 0–20 0–30

339 732 1556 2413

285 636 1421 2235

0.84 0.87 0.91 0.93

4.2 8.8 18.4 27.9

Secondary forest

0–5 5–10 10–20 20–30

81 86 90 92

71 83 86 86

0–5 0–10 0–20 0–30

406 836 1741 2658

355 768 1626 2491

0.87 0.92 0.93 0.94

4.4 9.2 18.7 28.2

Plantation

0–5 5–10 10–20 20–30

52 62 65 70

61 65 72 74

0–5 0–10 0–20 0–30

259 567 1219 1917

307 632 1350 2090

1.19 1.11 1.11 1.09

5.8 11.0 21.9 32.5

Secondary forest

0–5 5–10 10–20 20–30

47 59 64 69

53 61 64 70

0–5 0–10 0–20 0–30

236 532 1170 1857

265 570 1209 1904

1.12 1.07 1.03 1.03

5.5 10.6 20.6 30.7

n = 40; YR1 and YR5 = year 2001 and 2005, respectively; soil MF = soil mineral fraction.

Table 6 Soil carbon stock on a depth- and mass-basis in 2001 and 2005. Site

Maribaya

Ngasuh

Landuse

Depth (cm) 

Soil C stock (Mg C ha1), mean ± SD

YR5/YR1

ANOVA, F-value

YR1

YR5-depth

YR5-mass

Depth

Mass

Depth

Mass

Plantation

0–5 0–10 0–20 0–30

14.4 ± 2.3 27.3 ± 3.7 48.2 ± 6.9 66.1 ± 9.4

14.6 ± 2.5 28.1 ± 3.5 51.4 ± 6.1 70.7 ± 8.0

16.6 ± 2.6 30.9 ± 3.7 54.6 ± 6.3 74.9 ± 8.5

1.01 1.03 1.07 1.07

1.16 1.13 1.13 1.13

<0.1 0.7 4.4* 6.3*

13.6*** 14.1*** 17.1*** 21.9***

Secondary forest

0–5 0–10 0–20 0–30

14.4 ± 2.1 26.3 ± 3.6 46.4 ± 6.4 62.8 ± 7.5

14.4 ± 1.8 26.3 ± 2.7 46.1 ± 4.7 62.0 ± 5.7

15.9 ± 2.0 27.9 ± 2.8 48.2 ± 4.8 65.1 ± 5.9

1.00 1.00 0.99 0.99

1.10 1.06 1.04 1.04

<0.1 <0.1 0.1 0.4

10.0** 5.7 * 2.2 2.3

Plantation

0–5 0–10 0–20 0–30

16.5 ± 1.4 30.6 ± 2.4 55.2 ± 5.0 75.7 ± 6.8

16.0 ± 3.5 30.4 ± 5.3 56.9 ± 8.6 77.9 ± 11.2

13.5 ± 3.0 27.6 ± 4.9 52.0 ± 7.9 72.9 ± 10.5

0.97 0.99 1.03 1.03

0.82 0.90 0.94 0.96

0.6 <0.1 1.2 1.1

33.8*** 14.1*** 5.0* 1.9

Secondary forest

0–5 0–10 0–20 0–30

15.8 ± 1.6 30.5 ± 3.1 54.4 ± 5.7 73.8 ± 7.2

15.9 ± 2.5 30.4 ± 4.3 56.2 ± 8.7 78.8 ± 12.4

14.2 ± 2.3 28.6 ± 4.1 54.7 ± 8.4 77.3 ± 12.0

1.00 1.00 1.03 1.07

0.90 0.94 1.00 1.05

<0.1 <0.1 1.7 6.1*

17.8*** 7.2* <0.1 3.1

n = 40; SD = standard deviation; YR1 and YR5 = year 2001 and 2005, respectively. p < 0.05. ** p < 0.01. *** p < 0.001.   Soil C stock in YR5-mass is based on the equivalent mass of soil mineral fraction in the corresponding depth of YR1. *

0–30 cm depth ranged from 0.7 (=1.0% year1 in weightedaverage; Ngasuh plantation) to 2.3 Mg ha1 year1 of C (=3.3% year1; Maribaya plantation; Table 6).

experienced more change than those of the secondary forest, at both the Maribaya and Ngasuh. 4. Discussion

3.4. Litter stock The litter stock increased in Maribaya and decreased in Ngasuh, in general, during the 3 years. In Maribaya, the litter stock increased from 3.6 to 8.4 Mg ha1 in the plantation, primarily later in the study period, and from 3.5 to 6.7 Mg ha1 in the secondary forest (Fig. 3). The litter stock in Ngasuh decreased from 7.5 to 1.9 Mg ha1 in the plantation and from 4.5 to 3.0 Mg ha1 in the secondary forest (Fig. 3). Accordingly, the plantation litter stocks

4.1. Changes in soil C stock calculated using the depth- and massbased approaches Trends in soil C stock were better clarified by the mass-based approach, especially in the surface soil layers. As the soil C pool is affected by C input from both litter and fine roots (Russell et al., 2004, 2007; Turner and Lambert, 2000), it was reasonable that the change in soil C stock was prominent in the surface soil

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Littterr sttockk (ddry y matt m ter, M Mg ha h -1)

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10 0 10.0

Ngasuh g

Maribaya y 8.0 6.0 4 .0 0 2 .0 0

Pl Plantation i

Plantation

Secondary forest

Secondary forest

0 0

300

600

900

1200

0

300

Time (days)

600

900

1200

Time (days)

Fig. 3. Litter stock over time at the study sites. n = 40. Time = days elapsed from September 1, 2001. Error bar = standard error.

1.3

YR55/YR1 1 foor BD B

10-20 10 20 cm 20 30 cm 20-30

0 5 cm 0-5 5-10 cm

1.2 11 1.1 10 1.0 09 0.9 0.8 0.6

0.8

1.0

1.2

1.4

YR5/YR1 for TC

1.6

0.6

0.8

1.0

1.2

1.4

1.6

YR5/YR1 for TC

Fig. 4. Relationship between the change in total soil C concentration and bulk density. 0–5 cm, y = 0.687x + 1.701, R2 = 0.734; 5–10 cm, y = 0.363x + 1.365, R2 = 0.343; 10– 20 cm, y = 0.212x + 1.218, R2 = 0.160; 20–30 cm, y = 0.1364x + 1.1372, R2 = 0.091. Each circle represents the mean value of a sampling block or point.

layers (0–5 cm depth), which were covered by a litter layer and where fine roots concentrated, in comparison with the soil profile including subsurface soil layers (0–30 cm depth). On the other hand, no trend in soil C in the surface soil layer was suggested by the depth-based approach (Table 6). This result was accounted for by the opposing temporal changes in TC and BD in surface soil layers (Fig. 4). The change in mass of the soil mineral fraction suggested that expansion and compaction of surface soil occurred in Maribaya and Ngasuh, respectively (Table 5), and that these changes offset changes in soil C stocks for a fixed soil depth in the surface layers. These results suggest that compared with the depth-based approach, the mass-based approach was effective at detecting temporal trends, not only in soil C stocks, but also in soil nutrient stocks in tropical plantations where soil nutrients are concentrated in the surface soil layers (Yamashita et al., 2008). The mass-based approach also detected clearer trends in soil C stock in the plantation sites than in the secondary forest sites. The increase in soil C in Maribaya plantation (3.3% year1, 0–30 cm in corresponding depth) was large compared with that of young (0.6% year1; <5 years) or tropical (1.6% year1) plantations, or high clay soil sites (1.1% year1) (Paul et al., 2002). This may be due in part to the enhanced soil C accumulation in Maribaya as a result of planting A. mangium, a nitrogen-fixing species (Huang et al., 2011; Johnson, 1992; Paul et al., 2002; Resh et al., 2002). Additionally, the Maribaya site was originally a fallow forest in a cycle of shifting cultivation; thus, the initial soil C stock may have been reduced to levels similar to those of agricultural land. Thus, the establishment of a plantation at Maribaya may have had a

positive effect on soil C enhancement, similar to that previously reported for former agricultural land (Lal, 2005; Paul et al., 2002). The mass-based approach revealed a decrease in the soil C stock (1.0% year1) in the S. leprosula plantation in Ngasuh, in contrast to the increase found by the depth-based approach, but neither trend was significant. This decreasing trend in soil C in Ngasuh followed the general trend reported for early stages of afforestation (Jandl et al., 2007; Paul et al., 2002; Turner and Lambert, 2000; Zinn et al., 2002). Because the difference in litter production between tree species affects the soil C pool (Russell et al., 2004), the soil C stock in Ngasuh may have decreased with decreasing litter supply from S. leprosula, compared with the A. mangium site (Fig. 3). The relationship between changes in litter stock and soil C stock during the study period is illustrated in Fig. 5, and the positive correlation between the two increased under the massbased approach in comparison with the depth-based approach. In summary, the mass-based approach was better able to detect both increasing and decreasing trends in soil C stocks than the depth-based approach. Re-assessment of archived soil C data in future studies using the mass-based approach rather than simple estimations of soil C stocks will improve C models (Nabuurs et al., 2008; Paul et al., 2003), which will help to raise the tier level of country-specific forest C accounting systems (IPCC, 2003). 4.2. Considerations in using the mass-based approach Although the mass-based approach was shown to have advantages in the analysis of temporal trends in forest soil C stocks, care

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60 6.0

3.0

0 -10.0 10 0

-5.0 50

60 6.0

b

0

5.0 50

10.0 10 0

-3.0

Δso Δ oil C stoc s ck (M Mg ha h -11)

Δsooil C stoc Δ s ck (M Mg ha h -11)

a

3.0

0 -10.0 10 0

-5.0 50

0

5.0 50

10.0 10 0

-3.0

60 -6.0

-6.0 60

g Δlitter stock ((Mg

g ha-1) Δlitter stock ((Mg

ha-1)

Fig. 5. Relationship between the change in litter stock and the change in soil C stock. Dlitter stock = change in litter stock during the research period (Fig. 3); Dsoil C stock = change in soil C stock between 2001 and 2005; (a) Dsoil C stock calculated using the mass-based approach (equivalent mass in 0–5 cm depth), y = 0.458x  0.402, R2 = 0.582; (b) Dsoil C stock calculated using the depth-based approach (0–5 cm depth), y = 0.049x  0.065, R2 = 0.018. Each circle represents the mean value of a sampling block or point.

Table 7 Soil carbon stock on a mass-basis in plantation sites based on various assumptions. Site

Depth (cm)

Soil C stock (Mg C ha1), mean (difference, %) One layer

cf = 0

cf = 1.4

cf = 2.5

Maribaya

0–5 0–10 0–20 0–30

17.3 32.3 56.3 76.3

(4.0) (4.5) (3.1) (1.9)

16.5 30.8 54.3 74.6

(0.9) (0.6) (0.5) (0.5)

16.6 30.9 54.5 74.9

(0.2) (0.1) (0.1) (0.1)

16.7 31.0 54.7 75.1

(0.4) (0.3) (0.2) (0.2)

Ngasuh

0–5 0–10 0–20 0–30

13.5 27.3 51.3 71.4

(0.0) (0.9) (1.3) (2.1)

13.8 27.8 52.2 73.1

(1.8) (0.8) (0.4) (0.2)

13.6 27.6 52.1 73.0

(0.4) (0.2) (0.1) (0.0)

13.4 27.5 51.9 72.9

(0.9) (0.4) (0.2) (0.1)

n = 40; one layer = soil C stock calculated assuming one soil layer for the entire soil profile; cf = conversion factor of soil organic carbon to soil organic matter. Numbers in parentheses show the difference from the soil C stock on a mass basis in YR5 (Table 6).

must be taken when applying this approach in future studies. First, the mass-based approach involves linear interpolation and extrapolation of soil C stocks per soil mass to calculate cumulative soil C stocks (Ellert and Bettanym, 1995; Gifford and Roderick, 2003). To obtain a smooth curve in the relationship between cumulative soil C stock and soil mass, the total soil profile from the soil core sample should be divided into several segments (Gifford and Roderick, 2003). When only one soil layer was assumed for 0–30 cm depth, the soil C stocks on a mass basis of the plantation sites had errors, ranging from 2.1% to 1.9% (Table 7) of that with four soil layers. Thus, the calculation of soil C on a mass basis should be conducted using soil data for two or more layers for the upper 0–30 cm of soil to reduce errors in linear interpolation and extrapolation. The use of the equivalent mass of the soil mineral fraction and the conversion factor of 1.724 was not so influential on the soil C stock under the mass-based approach. Pribyl (2010) pointed out that 1.724 is too low a value for most soils and presented a range of factor values between 1.4 and 2.5, depending on organic matter composition. In the present study, the mass-based soil C stock changed little with variation in conversion factor from 0 to 2.5 (Table 7). A conversion factor of zero means the calculation of equivalent soil mass based on bulk soil, as presented in previous studies (Ellert and Bettanym, 1995). Thus, the conversion factor of 1.724 may be appropriate for future studies where larger changes in soil C concentration are expected than observed in this study.

5. Conclusions Both increasing and decreasing trends in forest soil C stocks became clearer when the mass-based approach was used rather than the depth-based approach. The trends in soil C stock on an equivalent soil mass basis were particularly improved for surface soil layers and plantation sites, compared with soil profiles that included subsurface soil layers and secondary forest sites. These trends in soil C stocks corresponded to trends in litter stock during the research period. Given the error associated with assuming one soil layer in a soil profile, soil C stocks on should be calculated on a mass-basis using multiple soil layers for the upper 0–30 cm of soil. Meanwhile, changes in soil organic matter mass had little effect on the estimation of soil C stocks on a mass basis. To improve the tier level of country-specific forest C accounting systems, the massbased approach should be used to characterize temporal trends in soil C stocks and to improve C cycle models, rather than using simpler methods of calculating soil C stocks.

Acknowledgments This study was conducted as part of the ‘‘Demonstration Study on Carbon Fixing Forest Management’’ by the Japan International Cooperation Agency (JICA) and the Forestry Research and Development Agency (FORDA). This study was funded by the Japanese Ministry of Education, Culture, Sports, Science, and Technology

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