Study site

This study was carried out in Chang Riec Historical - Cultural Forest (11°00′30″ to 11°35′13″N and 106°00′00″ to 106°07′10″E), Tayninh Province, Vietnam (Fig. 1). The location has two distinct seasons: the dry season from December to April and the rainy season from May to November. The mean annual temperature is 26.9°C, with the maximum of 35.2°C between April and May and the lowest 21°C from December to February. The mean annual rainfall is 1967 mm with average rainy days of 155. Annual mean humidity is 78.3%, and monthly mean of sunshine is 181-277 hours (IBST, 2009). The terrain in the study area is relatively flat, elevation of 28-53 m a.s.l. with slopes of 3-5°. The soil type is grey brown, developed on ancient alluvium rocks, and soil depth over 100 cm. They are loam in texture with pH (H<sub>2O) of 5.10-5.23. The clay, silt, and sand contents are 12.76, 46.06, and 41.19%, respectively. The predominant planted forests of the area comprise A. mangium Willd., Acacia hybrid (Acacia auriculiformis A. Cunn. ex Benth. × A. mangium Willd.), Hopea sp., Dipterocarpus obtusifolius Teijsm. ex Miq., and Tectona grandis L.f. plantation forests. These plantations accounted for over 39.3% of the total forest area. A. mangium occupied approximately 20% of all plantations in this area and plays a crucial role in pulp and timber production. Our site includes a chronosequence A. mangium stands with ages of 4-, 7-, and 11-year-old. All the stands were the first rotation and no fertilization was applied. They were established in agricultural lands after the clear-harvesting of previous Cassava (Manihot esculenta Crantz). The initial planting density was 4 m × 2.5 m, and thinning operations were done once, twice, and three times for the 4-, 7-, and 11-year-old plantations, respectively. Stand density decreases as the stand age increases due to thinning operation carried out on the plantations. The DBH and H tend to increase with stand age (Table 1). Seed provenance from Dongnai Province was used in raising the seedlings of A. mangium used for the plantations. The diversity and abundance as well as growth of understory vegetation were well developed, especially for the 7- and 11-year-old plantations. The dominant species of shrub and herb layers in these plantations were Mallotus apelta (Lour.) Müll. Arg., Tetracera scandens (L.) Merr., Chromolaena odorata (L.) R.M. King & H. Rob., Saccharum arundinaceum (Retz.), Mimosa pudica var. tetrandra (Willd.) DC., Chrysopogon aciculatus (Retz.) Trin., Maesa perlarius (Lour.) Merr., Lygodium microphyllum (Cav.) R. Br., Dryopteris parasitica (L.) Kuntze, Helicteres angustifolia var. obtusa (Wall. ex Kurz) Pierre, and Cynodon dactylon (L.) Pers.

 

 

Table 1. Basic characteristics of Acacia mangium plantations in Chang Riec Historical - Cultural Forest, Southeastern region, Vietnam

Values shown as mean ± standard deviation (SD). The different lower-case letters in a column indicate significant difference at p<0.05 (one-way ANOVA and LSD test). DBH, diameter at breast height; H, height

 

Biomass estimation and C concentration analysis

During 12th February to 30th March in 2019, four sample plots (40 m × 25 m) were established in each A. mangium stand. All the sampling plots were 500 - 800 m apart (Fig. 1). The DBH (cm) of trees in each plot with DBH ≥5 cm were measured by using a diameter tape accuracy of 1 mm and their heights (H, m) were determined using a Blume-Leiss altimeter. Canopy closure was determined by using a specific smartphone application (Gap Light Analysis Mobile Application software), and 10 points were measured in each plot (Table 1). Three standard trees were chosen based on the mean DBH (Dm) and logged from each sampling plot for biomass determination, using the segmenting method (Hai et al., 2009; Phuong & Hai, 2011; Ngoan & Chung, 2018). A total of 36 trees were harvested (Table 2). The sample trees were divided into four biomass components (stem, branches, leaves, and BGB). The fresh weights of all compartments were measured in situ, and samples of every components in each sample tree were collected for moisture content and C concentration analysis. The root biomass was collected through total excavation, extending radially out from the trunk and downwards to soil layer until no roots were visible. The ratio of different biomass components were computed to analyze changes of relative biomass partitioning with stand age.

In this study, the DBH was used as a predictive variable. The relationships between dry biomass and DBHwere tested using linear and nonlinear functions. According to Parresol (1999), biomass data normally exhibit heteroscedasticity. Consequently, biomass data was log-transformed and fitted as linear models to correct the heteroscedasticity of variance. The White’s test (White, 1980) was also applied to check variance homogeneity of biomass models (Table 3). It is common that a correction factor (CF) would be used to correct for the systematic bias introduced by the anti-log transformation to obtain the expected biomass in original scale when a log-model was fitted to the biomass data (CF = exp (SEE2/2) (Baskerville, 1972). However, other studies found that anti-log transformation tended to overestimate biomass if the CF is applied, and suggested that the CF may be omitted if the bias (B) from anti-log was relatively small compared to the overall variation in the estimate of biomass (B = ((CF–1)/CF)×100) (Madgwick & Satoo, 1975; Zianis et al., 2011). In the present study, the CF values of all biomass equations were less than 1.009. The B values were also rather small ranging from 0.2 to 0.89% (Table 3). Therefore, the CF was not essential for the species in this study. The best biomass equations were selected based on various goodness-of-fit statistics namely the coefficient of determination (R²), the Akaike information criterion (AIC), the root mean squared error (RMSE), and the standard error of estimation (SEE). We also accounted for the significance of the regression (p value) and the significance of parameters. Equations with higher R², smaller AIC, RMSE, SEE, and significant parameters and p value (p<0.05) were selected as the best-fitted biomass allometric equations (Akaike, 1974; Adam & Jusoh, 2018). The RMSE, and AIC were defined as in the following equation:

where: n, number of trees used for model development; yi , observed biomass (kg);𝑦̂𝑖 , predicted biomass (kg); p, number of model parameters to be estimated.

Biomass of shrubs and herbs was estimated by a destructive sampling of five 5 m × 5 m subplots. Shrubs (DBH<5.0 cm) were separated into three components: stem plus branches, leaves and roots, and herbs into aboveground and belowground components. In each plot, the litter contribution was obtained from a set of five quadrats (1 m × 1 m) were separately chosen in each of the four corners and the center of the plot. Litter was separated into two components: leaves plus sexual organs and twigs (<10 mm diameter). All materials were weighed freshly, and approximately 300-500 g of each compartment from each sample (shrubs, herbs, and litter) were taken for moisture and C analysis.

The abovementioned samples were taken to the laboratory of Centre of Forestry Research and Climate Change at the Vietnam National University of Forestry and ovendried at 70°C to a constant weight, then ratios of dry/fresh biomass were calculated and used to convert fresh biomass into dry biomass. The C contents of the components from the tree component samples, understory, and litter were determined by the dichromate oxidation method (Nelson & Sommers, 1982).

 

Table 2. Descriptive statistics (minimum and maximum values) for 36 sampling trees of Acacia mangium tree species

DBH, diameter at breast height; H, height; BGB, belowground tree biomass; TB, total tree biomass

Soil sampling and analysis

Soil samples were taken at fixed depth (0-10, 10-20, 20-30 and 30-50 cm) using a soil corer with four replicates for each age stand. The SBD of the different soil layers was determined by using a soil bulk sampler with a volume of 100 cm3 stainlesssteel cutting ring. The sample was dried to 105°C to constant weigh and weighed to determine SBD (Blake & Hartge, 1986). The SOC was analyzed by using the dichromate oxidation method (Nelson & Sommers, 1982).

 

Carbon stock estimation

Plant biomass C stocks (Cvs) was calculated as following equation:

where: C_vs , plant C stocks (Mg. C ha^-1); B, plant dry bio-mass (Mg. ha^-1); P_c plant biomass C concentration (%).

It should be noted that organic C in soil is usually only calculated as organic C that exists in organic materials with a diameter (<2 mm) (IPCC, 2003; Deng et al., 2017; Thanh & Cuong, 2017), so Cst was calculated following the equation:

where: Cst soil C stocks (Mg. C ha^-1); SOC, soil organic C concentration (g. kg^-1); SBD, soil bulk density (g. cm^-3); and S_d, soil depth (cm).

 

Statistical analysis

One-way analysis of variance (ANOVA) followed by the least significant difference and then the (LSD) test was used to detect the mean difference in biomass and C stocks among different stand ages. In ANOVA, assumptions of normality and homogeneity of variances were tested with significance level at p<0.05 confidence interval. Due to the focus of this study on analyzing allometric relationships between tree component biomass and DBH across stand ages, additivity of the biomass equation was not considered (Zianis & Mencuccini, 2004; Yang et al., 2019). Statistical analysis of data and regression analysis for developing allometric equations were conducted using SPSS 25.0 software package (IBM Corp, 2017).

ResultsTop

Allometric biomass models for biomass of A. magium plantations

The allometric equations using power functions (stem, branches, BGB, and TB) and exponential function (leaves) correlating biomass were established for the various components with DBH (Table 3 and Fig. 2). The allometric equations that were developed interpreted over 92% of the variability for the tree compartments (p<0.001). The equations were most fitted for the AGB and TB among the various tree components (p<0.001). The parameters of the equations varied with tree biomass compartments.

 

Biomass distribution in different components of A. mangium plantation

DiscussionTop

Biomass C of A. mangium stands at different ages

Stand age plays an important role in the distribution of biomass and C (Xie et al., 2016; Justine et al., 2017; Zhang et al., 2019). Results of this study show that the biomass and C of A. mangium in both above-ground and belowground parts increased significantly with increasing stand age. Similar results were reported in previous studies (e.g. Hai et al., 2009; He et al., 2009; Cao et al., 2012; Justine et al., 2015; Zhang et al., 2018). Furthermore, the accumulation rate of TBC was much higher in 4- and 7-year-old plantations than in 11-year-old plantation. The highest accumulation rate of TBC was found in the 4-7-year-old (11.56 Mg. C ha^-1), in line with previous studies for A. mangium forests (Hai et al., 2009; He et al., 2009), demonstrating a fast biomass C accumulation of trees in this stage. The mean TBC of 68.4 Mg. C ha^-1 in this study was much greater than those reported for 4-12-year-old A. mangium plantations (39.8 Mg. C ha^-1) and 2-12-year-old A. auriculiformis forests (21.5 Mg. C ha^-1) in Vietnam conducted by Hai et al. (2009), and Acacia plantations of less than 6 to over 16 years (57.3 Mg. C ha^-1) in the Pearl River Delta region of Southern China (Zhang et al., 2018), slightly lower than that the 71.5 Mg. C ha^-1 in 4-11-year-old A. mangium forests in Guangxi Province of China (He et al., 2009), but within the range of 34.4-85.6 and 44.8-118.2 Mg. C ha^-1 reported for Asian and Global forests (FAO, 2010). The different rate of accumulated biomass C stock could be attributive to the effect of climatic conditions, plant species, stand age, stand density, biomass, soil nutrient, and water availability (Herdiyanti & Sulistyawati, 2009; Lee et al., 2015; Zribi et al., 2016). Our data demonstrated that the A. mangium plantation in Southeastern region can accumulate large amounts of biomass C in both aboveground and belowground parts. Moreover, fertilization was not done in these plantations. This suggests that A. mangium can grow well in soils without fertilization, has great biomass C accumulation potentials in this region.

The present study illustrated changes in biomass and C partitioning with plantation age. We observed an increase in C accumulation in branches along with a decrease in BGB and foliage while relatively stable in ratio of stem biomass C to TBC. This result was in accordance with findings for Acacia auriculiformis (Hai et al., 2009) and Cunninghamia lanceolata (Xie et al., 2016). This allocation pattern may be interpreted by the strategies that trees use to survive during stand development. The fractions of BGB and leaves in early stages of growth are crucial for the survival of young seedlings and the likelihood that they survive to the next developmental stage. With the development, tree foliar biomass productivity no longer increases, resulting in declined demand for water and nutrient supply from BGB (Vanninen et al., 1996). On the contrary, Hai et al. (2009) reported that the fraction of biomass C stored in stem of A. mangium increased during 4-12 years, while the proportion of biomass C stored in branches, leaves, and BGB decreased. He et al. (2009) found an increase in the stem biomass C partitioning along with a decrease in branch and foliar biomass C partitioning for A. mangium stands. The biomass C partitioning into different components can be affected by both biological and environmental conditions. Particularly, in the tree crown, which is characterized spread and lengths of branches, is partly associated with aerial growing space, the branch biomass C proportion might be expected to reflect the stand density. For instance, differences of stand density in the 11-year-old plantation (610 tree.ha^-1) used in the current study and Hai et al.’s 12-year-old plantation (825 tree.ha^-1), and He et al.’s 11-year-old plantation (775 tree.ha^-1) might interpret the different the allocation patterns with age.

In this study, decline in the BGB/AGB ratio with age might be related to root rot and death in the older trees resulting to alleviated BGB and therefore greater BGB/AGB ratio in the younger than in the other stands. The BGB/ AGB ratio average value of 0.28 observed here is within the range of 0.28-0.31 and 0.20-0.33 reported in the Asian and Global forests (FAO, 2010) but higher than the values of 0.23, 0.24, and 0.17 reported for A. mangium plantations by Qin et al. (2007), Ren & Yu (2008), and Hai et al. (2009), respectively. These different values might arise due to the BGB/AGB ratio dependent on forest age (Peichl & Arain, 2006; Xie et al., 2016), tree species (Hai et al., 2009; Ruiz-Peinado et al., 2012), and vegetation category (Mokany et al., 2006). Nevertheless, the BGB accounted for approximately one-quarter of the TB in this chronosequence study, which emphasizes the importance of BGB in the accurate estimation of the biomass and C of A. mangium planted forests.

Understory vegetation plays a crucial role in stabilizing the ecosystem and sequestering CO₂ (Xu et al., 2000), but their biomass C stock account only approximately 1.091.67% (median 1.30%) of the total ecosystem C stock in the A. mangium plantations (Fig. 6), which represents a relatively small proportion in the ecosystem. Gao et al. (2014) demonstrated that absence of the computation for understory vegetation could lead to underestimation of C sequestration capacity. Previous studies found that the biomass C storage in understory vegetation did not show a clear changing trend with stand age (Cheng et al., 2014; Deng et al., 2017; Yue et al., 2018; Zhang et al., 2019). In this study, however, the C stock of the understory vegetation increased with stand age, which was in accordance with the results of He et al. (2009) and Zhang et al. (2018). The distinction in species ecological characteristics, light, and nutrients probably contributed to this difference (Abdallah & Chaieb, 2012). Perhaps in the other previous studies that understory biomass C storage did not clearly increase with stand age was due to the more intense competition for light and nutrients. Our results indicated that the C stock in understory were dependent on stand age.

We found that the biomass C storage of the litter increased with stand age, which was consistent with results from previous studies (Deng et al., 2017; Zhang et al., 2018). In contrast, other investigations found that the litter C stock did not correspond clearly to stand age (Ming et al., 2014; Yue et al., 2018). In general, litter C stock is determined by the balance between litter input and de composition, hence any elements impacting the amount of input and decomposition rate would influence the litter C storage. The lower quantity of C stored in litter in the 4-year-old stand development was due to decreased leaves, branches, and understory biomass standing in the period. In the present study, it was also found that the C stock of the litter in each stand is greater than that of the total understory vegetation, with the largest proportion of 3.8% in the 4-year-old stand, demonstrating that forest litter should be regarded as an important component in plantation ecosystems.

 

Figure 4. Biomass carbon percentage distribution of tree individual components (a) and ecosystem components (b) in the 4-, 7-, and 11-year-old Acacia mangium plantations. BGBC, belowground tree biomass carbon stock; TVC, total understory vegetation biomass carbon stock; TVC, total tree biomass carbon stock..

 

 

Figure 6. Percentage distribution of ecosystem carbon storage in Acacia mangium plantations of three different ages. TVC, total understory vegetation biomass carbon stock; TBC, total tree biomass carbon stock..

 

Carbon concentration

A factor of 50% is commonly used for biomass - C conversion (Brown, 1997; IPCC, 2003). However, it was showed that the C content of different plant compartments might be either above or below 50% (e.g. Thomas & Martin, 2012; Cheng et al., 2014; Zhang et al., 2019). The mean C concentration of total tree of 47.97% in this study is within the range of 40.15-55.87% and 45.54-49.45% reported for the same tree species (Hai et al., 2009; He et al., 2009) but lower than that for A. auriculiformis (49.32%), A. hybrid (51.22%), and Eucalyptus urophylla (53.11%) (Hai et al., 2009). Previous investigations indicated that the C concentrations of planted forests are closely associated with their sample chemical compositions, tree components, wood type, geographical location, climate, and soil conditions (Bert & Danjon, 2006; He et al., 2013). Hence, all of these factors must be taken into account when assessing C contents under different edaphic and climatic conditions. The mean C concentrations of shrubs, herbs, and litter were lower than 45%. Thus, using a coefficient of 50% may result to large errors in up-scaling of C pool. For example, assuming 50% C content for understory in the 7-year-old plantation and for litter in the 11-year-old plantation would result in a difference of 2.62 Mg. ha^-1 (11.75%) and 6.65 Mg. ha^-1 (9.29%), respectively. Therefore, we suggest that a component-specific C content value for individual compartments is suitable for assessing forest C pool among all stands.

 

Soil organic C in A. mangium plantations

Among the three plantation development stages of this study, the soil C concentration was the highest in the surface soil layer (0-10 cm) and indicated a decreasing trend with depth (Fig. 5a). Soil organic matter is the dominant source of soil C and is greater in topsoil (Du et al., 2015). The C concentrations of the top soil layers (0-10 cm, 10-20 cm, and 20-30 cm), and the deep layer (30-50 cm) significantly increased with stand age, probably due to the increasing litter productivity in older stands (Ming et al., 2014; Thanh & Cuong, 2017). This finding contributes to interpret the increase C stocks in belowground as stands age.

Although changes in Cst following afforestation and stand age have been widely reported in previous studies, there still exist great deals of controversies concerning the effects of stand age on Cst level. Some studies reported no significant increase in Cst with stand age (Uri et al., 2012; Yue et al., 2018). Some studies have shown an increasing Cst in the early period after afforestation followed by a gradual decrease with age increment (Noh et al., 2010; Du et al., 2015; Zhang et al., 2019). Some studies indicated a decrease in Cst at the early age and then gradually increased with age (Chen et al., 2013; Wang et al., 2013). These discrepancies may be due in part to how much other influencing factors, such as climate, soil characteristics, forest type, forest management, litter input, root metabolism, and previous land use, which could overshadow the effect of stand age (Jandl et al., 2007; Zeng et al., 2013; Thanh & Cuong, 2017). We found Cst in the mineral soil layer increased with plantation age. Previous studies about Cst with stand age reported same results as our study (Hai et al., 2009; He et al., 2009; Cheng et al., 2015; Deng et al., 2017; Thanh & Cuong, 2017). The increase in Cst with stand age might be due to a larger accumulation of organic matter in older stands (BGB and litter). Additionally, 0-50 cm soil layer Cst accounted for the largest proportion of ecosystem C reservoirs, particularly the Cst in the upper 0-30 cm layer. Approximately 60.37% to 63.33% of Cst in the 0-50 cm range of soil was stored in the 0-30 cm range, where soils can be disturbed by human disturbances. Therefore, this study suggests that protection of organic C in the topsoil from disturbances of planted forests is important for improving C sequestration. The soil C values in the upper 0-30 were much greater than those for the Cst stored in A. mangium and A. auriculiformis planted forests across all age classes described by Hai et al. (2009) for the 0-30 cm upper mineral soil horizon profile.

 

Ecosystem C storage in A. mangium plantations

The results suggested that age plays a crucial role in affecting the overall ecosystem C stock and can provide insight into C sequestration (Cheng et al., 2014; Justine et al., 2015). Total ecosystem C stock in the 11-year-old plantation was twice the amount of the 4-year-old plantation, illustrating a large C sequestration potential during A. mangium development. Fractions of ecosystem C stocks in the three stands were in the order of soil layer > tree layer > litter layer > understory layer. It was observed that soil and tree biomass were the main C pools across all stand ages, accounting for 95.74% of C storage in the ecosystem, which is congruent with previous studies (He et al., 2009; Li et al., 2013; Ming et al., 2014; Du et al., 2015). This highlights the importance of including accurate assess of Cst in ecosystem C accounting.