Effects of three cropland afforestation practices on the vertical distribution of soil organic carbon pools and nutrients in eastern China

Effects of three cropland afforestation practices on the vertical distribution of soil organic carbon pools and nutrients in eastern China

Global Ecology and Conservation 22 (2020) e00913 Contents lists available at ScienceDirect Global Ecology and Conservation journal homepage: http://...

2MB Sizes 0 Downloads 54 Views

Global Ecology and Conservation 22 (2020) e00913

Contents lists available at ScienceDirect

Global Ecology and Conservation journal homepage: http://www.elsevier.com/locate/gecco

Original Research Article

Effects of three cropland afforestation practices on the vertical distribution of soil organic carbon pools and nutrients in eastern China Jing Guo 1, Bo Wang 1, Guibin Wang*, Sai Tay Zar Myo, Fuliang Cao Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, 159 Longpan Road, Nanjing, 210037, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 21 November 2019 Received in revised form 6 January 2020 Accepted 7 January 2020

The conversion of croplands to plantations has been broadly implemented to mitigate climate change. This mitigation effect has been achieved mainly via the sequestration of CO2 from the atmosphere and the storage of carbon within tree biomass and the soil, but this effect is not fully understood. To study this mitigation effect, a poplar plantation, a metasequoia plantation, and a poplar and metasequoia agroforestry system converted from croplands were studied. As such, we investigated the soil nutrient contents, soil organic carbon (SOC) fractions and SOC stocks in the three types of plantations to a depth of 100 cm. High total nitrogen, ammonium-nitrogen, and nitrate-nitrogen contents along the soil profile were detected in the poplar-based plantations. After 10 years of development, the poplar plantation had the greatest SOC fraction contents. The SOC stocks of the poplar plantation and poplar and metasequoia agroforestry system reached 90.35 Mg ha1 and 98.12 Mg ha1, respectively. The 0e10, 10e20, and 20e40 cm soil layers accounted for a greater share of the SOC stock in the metasequoia plantation than in the other plantations, and the largest proportion of SOC stock in the poplar and metasequoia system was detected in the subsoil layers. Overall, the different afforestation practices resulted in different SOC accumulation patterns among soil depths, especially in the subsoil. The proportion of the SOC stock in the subsoil layers was greater in the agroforestry plantation than in the pure plantations. © 2020 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Afforestation Soil nutrient Soil organic carbon fraction Soil organic carbon stock Poplar

1. Introduction The structure and function of ecosystems are being disrupted by increased interference from anthropogenic activities via land-use pattern changes, which either decrease or increase the biodiversity and carbon (C) stocks of an ecosystem (Bolstad and Vose, 2005; Guo and Gifford, 2002). Owing to the “Grain for Green” programme, the conversion of croplands to grasslands or forestlands is a common land-use change pattern in China (Fu et al., 2010). Generally, depleted croplands contain low SOC stocks and have a high potential for mitigating climate change after afforestation (Han et al., 2017; Wu et al., 2018). According to Don et al. (2011), the conversion of croplands to forest plantations can increase the soil organic carbon (SOC) stock by 29%. In Europe, the mean SOC stock was estimated to increase by 21 ± 13 Mg ha1 following afforestation (Poeplau

* Corresponding author. E-mail address: [email protected] (G. Wang). 1 These authors contributed equally to this work. https://doi.org/10.1016/j.gecco.2020.e00913 2351-9894/© 2020 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

2

J. Guo et al. / Global Ecology and Conservation 22 (2020) e00913

and Don, 2013). It is generally strongly accepted that increasing SOC stocks via afforestation is beneficial for addressing greenhouse gas emission problems that contribute to global warming as well as for improving soil fertility and productivity (Guo et al., 2016; Lal, 2004; Schlesinger and Andrews, 2000). Therefore, understanding the accumulation of SOC following afforestation is critically important. Although a meta-analysis conducted by Li et al. (2012) found significant C stock increases 30 years after afforestation, the SOC stock increases were only obtained in hardwood plantations (Eucalyptus) and not in softwood plantations (Pinus). On a global scale, nearly half of the terrestrial C is stored in forest soils, which means that forest soil C sequestration is an effective solution for addressing global warming problems (Bonan, 2008; Canadell et al., 2007). The shrinking of natural forest area (3961 M ha to 3721 M ha) contrasted starkly with the expansion of planted forest area (168 M ha to 278 M ha) from 1990 to 2015 (Keenan et al., 2015), confirming that the conversion of croplands forest is increasing in popularity given that it results in the continuous accumulation of C within tree biomass and the soil (Fu et al., 2010; Guedes et al., 2016; Yu et al., 2013). Forest plantations in China contain approximately 7.894 Pg C; 21.4% of this C is temporarily stored as biomass, and 78.6% is securely stored in the soil (Huang et al., 2012). Moreover, for the long-term and healthy growth of forest plantations, relatively low and reasonable densities are commonly required. In this case, the C sequestration potential can still be exploited; alley cropping is the main method applied to plantations, and it does not affect the normal growth or nutrient acquisition of the main tree species (FAO, 2011). The main tree species, understory vegetation, and alley cropping species of different afforestation practices always affect the SOC stocks, dynamics, and forms in the topsoil, but their effects on the subsoil SOC are less understood (Shi et al., 2013). Don et al. (2011) and Gao et al. (2017) indicated that the topsoil (mainly within 0e30 cm) alone is insufficient for estimating soil C stocks, as focusing on the topsoil underestimates the total SOC stock and overestimates the effects of land-use change on SOC stocks. Shi et al. (2013) reported that converting croplands to forest plantations significantly increased the SOC stocks in all surveyed soil layers (0e60 cm). SOC that accumulates in deep soil layers is derived mainly from the decomposition of fine tree roots, the transfer of dissolved organic C, and anthropogenic disturbance (Bounouara et al., 2017). These inputs are closely related to the root structure and root density of plants. Additionally, root exudates from deep root systems can stimulate the decomposition of unstable subsoil SOC (Fontaine et al., 2007). Despite the commonly observed increases in the SOC stocks of shallow soil layers, we are interested in the accumulation of SOC within deep soil layers following afforestation. Therefore, it is necessary to investigate SOC stocks and SOC fractions within deep soil layers following afforestation. Afforestation is a common land-use change strategy that substantially improves the C cycle and increases soil C stocks. However, few studies have analysed the land-use change patterns that affect SOC stocks in reclaimed tidal flats, especially in deep soil layers. In this study, three representative land-use patterns were selected: a poplar (Populus deltoides cv. 35) plantation, a metasequoia (Metasequoia glyptostroboides Hu et Cheng) plantation, and a plantation in which poplar trees were intercropped with metasequoia seedlings. This study was conducted to investigate how these three afforestation practices affect the SOC and labile C fractions within a 0e100 cm soil profile. Thus, the objectives of this study were to (1) investigate the soil physicochemical properties, SOC contents, SOC fractions, and changes in SOC stocks following afforestation and to (2) analyse the interactions between the soil physicochemical properties and SOC fractions. We also evaluated the quantity and quality of SOC in deep soil layers after 10 years of different afforestation practices. 2. Material and methods 2.1. Study site description The study site is located in the Dongtai forest, which lies atop a typical marine deposit plain at an altitude of 5 m above sea level (32 5201800 N, 120 500 4000 E), and is approximately 50 km east of Dongtai County, Jiangsu Province, China (Fig. 1). The site has a subtropical monsoon climate with a mean annual temperature of 15.6  C and a mean annual precipitation of 1044 mm. Both the Yangtze River and the Old Yellow River contribute to sediment deposition in the fields. The fields have been reclaimed for approximately 90 years, and the soil type is classified as a Gleyic Cambisol (Eutric, Siltic) (Zhang et al., 2017).[ Three different land-use patterns, a poplar plantation (P), a metasequoia plantation (M), and a poplar and metasequoia agroforestry system (PM) were selected for comparison. Two poplar plantations with densities of 607 trees ha1 and 312 trees ha1 were established in 2006. In 2010, metasequoia seedlings were intercropped into the low-density poplar plantation at a row spacing of 1.8  1.8 m. A separate metasequoia plantation with a row spacing of 1  1 m was also established in 2010 in an adjacent area. According to interviews with local farmers, a summer maize (JuneeOctober) and winter wheat (October of the previous yeareJune) rotation had been implemented during the decades prior to 2006, at which time the poplar plantations were established. No pesticides or herbicides were applied, and the same amount of fertilizer was applied annually to each plantation. General descriptions of the three plantations before soil sampling are shown in Table 1. 2.2. Soil sampling The soil conditions (topography) and management practices (tending measures) of the three neighbouring plantations were essentially identical. In each plantation, tree height, diameter at breast height (DBH), row and plant spacing, and understorey vegetation were measured (Table 1). Three replicate sample plots (each 10  10 m2) were randomly selected for sampling in each plantation for a total of 9 plots. The soil sampling was conducted in March 2016. Within each plot, soil

J. Guo et al. / Global Ecology and Conservation 22 (2020) e00913

3

Fig. 1. Location of the study site and general view of the three studied plantations.

Table 1 General descriptions of the three plantations. Treatments

Age (years)

Spacing (m)

Mean DBH (cm)

Mean Height (m)

Understorey vegetation

Poplar Poplar and metasequoia

10 10 6 6

35 48 1.8  1.8 11

20.85 ± 4.03 b 27.82 ± 3.52 a 5.80 ± 1.95 c 5.92 ± 2.06 c

18.91 ± 2.99 a 20.63 ± 2.92 a 6.76 ± 1.64 b 7.17 ± 1.87 b

Apocynum venetum L. Rosa multiflora Thunb. Ferns

Metasequoia

Ferns

samples were taken from within the 0e10, 10e20, 20e40, 40e60, and 60e100 cm soil layers via a cutting ring. Five soil cores were collected per layer and mixed into one composite sample per plot, and the litter layer was removed before the soil sampling. Fine roots and detritus were discarded. Moreover, one undisturbed soil core was collected from each plot in each plantation for bulk density (BD) measurements. Common approaches used in our laboratory were also used for the BD, soil pH, water-holding capacity (WHC), SOC, total nitrogen (TN), total phosphorus (TP), ammonium-nitrogen and nitrate-nitrogen measurements (Guo et al., 2018; Lu, 1999; Shibata et al., 2011). Dissolved organic carbon (DOC) was determined by treating fresh soil with distilled water (1:5 g:mL). The soil and water mixtures were shaken for 30 min and then centrifuged for 10 min (3000 rpm). The supernatant was subsequently purified by a membrane filter whose pore size was 0.45 mm. The DOC was ultimately analysed using a total organic carbon (TOC) analyser. The microbial biomass carbon (MBC) was determined via the chloroform fumigation-extraction method (Vance et al., 1987); in breif, 5 g sifted fresh soil sample was placed into a beaker and fumigated with chloroform for 24 h at 25  C, after which the samples and unfumigated soil samples were transferred to a 150 mL wide-mouthed bottle, 20 mL 0.5M K2SO4 was added, and the mixture was shaken for 30 min (180r). MBC was determined using a liquid TOC

4

J. Guo et al. / Global Ecology and Conservation 22 (2020) e00913

analyser (Elementar, Germany). The SOC stocks (Mg C ha1) along the soil profile were estimated via the following equation (Li et al., 2017):

TSOC ¼ SSOCi  BDi  Di  0.1 where SOCi is the SOC content in the ith layer (g kg1 soil), BDi is the bulk density in the ith layer (g cm3), and Di represents the thickness of the ith layer (cm). 2.3. Statistical analyses All the data are presented as the means±standard deviations. Statistical analyses were conducted via SPSS version 20.0 (IBM Inc., Chicago, Illinois, USA), and the figures were drawn by using Origin version 9.1 (OriginLab, Northampton, Massachusetts, USA). One-way analysis of variance (ANOVA) was applied to determine the differences in the soil physicochemical properties, labile C fractions, and C:N ratios between the plantations within the same soil layer. Two-way ANOVA was applied to determine the effects of soil depth and plantation type on the soil physicochemical properties, labile C fractions, and C:N ratios. The Pearson correlation coefficients between the soil physicochemical properties, labile C fractions, and C:N ratios were also calculated. 3. Results 3.1. Soil physical and chemical properties The BD and pH increased with increasing soil depth, while the WHC decreased with increasing soil depth (Fig. 2). Specifically, the pH and BD values were significantly lower in the shallow soil layers (0e10 and 10e20 cm) than in the deep layers (20e100 cm). The pH ranged from 7.91 to 8.67 among the plantations, and the BD ranged from 1.26 to 1.50 g cm3. The WHC

Fig. 2. Soil pH (a), bulk density (b), and water-holding capacity (c) in the three plantations along the soil profile (means±standard deviations). P, poplar plantation; M, metasequoia plantation; and PM, poplar and metasequoia agroforestry system. Different lowercase letters indicate significant differences among soil depth in the same plantation.

J. Guo et al. / Global Ecology and Conservation 22 (2020) e00913

5

ranged from 17.94 to 24.62% among the plantations. The contents of all soil nutrients except ammonium-N differed significantly between the soil layers and plantations, and the interaction effects between the soil layers and plantations were also  significant (P < 0.05, Fig. 3 and Table 2). The highest TN, NHþ 4 -N, and NO3 -N contents were always found in the poplar-based plantations, except for the NHþ -N content in the 10e20 cm layer, and they always decreased dramatically with increasing soil 4  1 1 depth. The TN, NHþ 4 -N, and NO3 -N contents varied within a range of 0.10e1.20 g kg , 1.54e6.02 mg kg , and 0.28e4.91 mg kg1, respectively. The M plantation had slightly higher TP contents than the P and PM plantations, which varied within a range of 0.30e0.46 g kg1. 3.2. SOC fractions and C:N ratios The SOC contents varied significantly between the plantations and soil layers (Fig. 4a, P < 0.01), ranging from 1.17 to 14.54 g kg1. On average, the SOC content in the P and PM plantations was 1.79 and 1.73 times greater than that in the M plantation, respectively. The SOC contents significantly decreased with increasing soil depth and were 3.08-, 1.74-, and 7.00fold greater in the top layer (0e10 cm) than in the bottom layer (60e100 cm) in the P, PM, and M plantations, respectively. The DOC, MBC, and C:N ratios differed significantly between the soil layers (Table 3, P < 0.01), although there were no significant differences between the plantations (P > 0.05). The DOC and MBC contents exhibited different trends along the soil profiles between the plantations, with the greatest values being 320.43 mg kg1 at a depth of 40e60 cm and 303.25 mg kg1 at a depth of 0e10 cm in the P plantation, respectively (Fig. 4b and c). The C:N ratio was significantly greater in the M plantation than in the P and PM plantations at depths of 0e10, 10e20, and 20e40 cm (Fig. 4d). Furthermore, the C:N ratios in the P and PM plantations were relatively stable along the soil profiles. 3.3. Vertical and total SOC stocks The SOC stocks differed significantly between soil layers and plantation types, and there was a significant interaction effect between soil layer and plantation type (Table 2, P < 0.05). Compared with the M plantation, the P and PM plantations had significantly larger total SOC stocks, storing as much as 47.23 and 55.00 Mg C ha1 more SOC than the M plantation, respectively, throughout the 0e100 soil profile (Fig. 5c, P < 0.05). Similar to the results for the SOC stocks, compared with the

Fig. 3. Soil total nitrogen (a), total phosphorus (b), ammonium-N (c), and nitrate-N (d) contents in the three plantations along the soil profile. P, poplar plantation; M, metasequoia plantation; and PM, poplar and metasequoia agroforestry system. Data are presented as the means (±standard deviations), and different lowercase letters indicate significant differences among soil depth in the same plantation.

6

J. Guo et al. / Global Ecology and Conservation 22 (2020) e00913

Table 2 Analysis of variance of soil physicochemical properties, soil organic carbon fractions various stocks and C:N ratios as affected by plantation and soil depth. Plantation

pH BD WHC TN TP AN NN SOC DOC MBC C:N SOC stock

Plantation  Soil depth

Soil depth

F

P

F

P

F

P

16.886 0.606 7.826 54.968 13.479 0.171 35.472 7.820 5.927 8.331 6.088 11.762

0.000012 0.552 0.002 0 0.000067 0.843 0 0.002 0.007 0.001 0.006 0

23.389 18.071 22.246 31.096 46.711 8.049 44.804 18.300 2.298 1.565 1.279 5.793

0 0 0 0 0 0.000156 0 0 0.082 0.209 0.300 0.001

1.763 1.07 1.494 6.107 4.272 0.841 5.490 0.698 2.222 1.962 1.843 2.485

0.124 0.41 0.201 0.00011 0.002 0.574 0.00026 0.691 0.054 0.087 0.108 0.034

Fig. 4. SOC (a), DOC (b), and MBC (c) contents with the C:N ratios (d) in the three plantations along the soil profile.

Table 3 Relationships between the investigated indicators (** represents a significant correlation at P < 0.01, and * represents a significant correlation at P < 0.05).

BD WHC TN TP ammonium-N nitrate-N SOC DOC MBC C:N

pH

BD

WHC

TN

TP

ammonium-N

nitrate-N

SOC

DOC

MBC

0.526** 0.700** 0.25 0.727** 0.503** 0.367* 0.381** 0.106 0.153 0.296*

0.883** 0.474** 0.585** 0.498** 0.477** 0.534** 0.046 0.213 0.092

0.261 0.701** 0.533** 0.298* 0.423** 0.02 0.08 0.314*

0.332* 0.300* 0.715** 0.757** 0.201 0.481** 0.302*

0.578** 0.591** 0.531** 0.052 0.134 0.509**

0.514** 0.578** 0.073 0.312* 0.306*

0.737** 0.123 0.326* 0.016

0.06 0.534** 0.219

0.455** 0.014

0.055

J. Guo et al. / Global Ecology and Conservation 22 (2020) e00913

7

Fig. 5. Stocks (a) and proportional distributions (b) of SOC in the three plantations along the soil depth profile and the total SOC stock in the 0e100 cm soil profile.

M plantation, the P and PM plantations had significantly larger SOC stocks within all soil layers, and the stocks were 1.28e4.15-fold and 1.36e5.63-fold greater in the P and PM plantations than in the M plantation among all soil layers, respectively (P < 0.05). Generally, the P plantation had larger SOC stocks than the PM plantation in the shallow soil layers (0e10 and 10e20 cm), but the results were opposite those in the subsoil layers (Fig. 5a). Additionally, the shallow soil layers (0e10 and 10e20 cm) stored 50.43% of the total SOC stock in the M plantation; however, these layers stored only 41.14% and 30.46% of the total SOC stock in the P and PM plantations, respectively. Furthermore, the cumulative SOC stocks within the 40e60 and 60e100 cm layers accounted for 44.65% and 54.47% of the total stock throughout the investigated soil profile in the P and PM plantations, respectively. The 60e100 cm soil layer stored 31.36%, 39.10%, and 15.82% of the total SOC stock in the P, PM, and M plantations, respectively. The M plantation contained a greater proportion of the SOC stock within the 0e10, 10e20, and 20e40 cm soil layers while the PM plantation contained a greater proportion of the SOC stock in the subsoil layers (Fig. 5b). 3.4. Pearson correlations The Pearson correlations between the soil physical and chemical properties and SOC fractions are presented in Table 3. The soil pH was positively correlated with BD and significantly negatively correlated with all other properties except the TN, DOC, and MBC contents (P < 0.05). BD was negatively correlated with the soil properties and SOC fractions. Significant positive correlations were detected between the WHC, TN, TP, ammonium-N, and nitrate-N contents (P < 0.05). Last, the MBC content was positively correlated with the TN, ammonium-N, nitrate-N, and SOC contents, whereas it was negatively correlated with DOC content (P < 0.05). 4. Discussion The SOC stocks of the poplar plantation and poplar and metasequoia system reached 90.35 Mg ha1 and 98.12 Mg ha1 after the fields had been converted from croplands for 10 years, respectively. SOC stocks always decrease following the re et al., conversion of croplands to forestlands, but they gradually increase following the development of plantations (Laganie 2010; Mao et al., 2010; Nave et al., 2013). This occurs because soil C inputs are low in newly converted plantations (decreased inputs of plant residue biomass) while the soil C output is accelerated (site preparation leads to accelerated SOC decomposition) (Berthrong et al., 2012; Paul et al., 2002). The subsequent accelerated soil C accumulation is mostly attributed to increased tree residue biomass and root exudates, fewer human disturbance, and improved SOC protection mechanisms dominated by high microbial activity and quantity (Liao and Boutton, 2008; Vesterdal et al., 2002). Meanwhile, the SOC stock of the adjacent metasequoia plantation was 43.12 Mg ha1, which is even lower than that of adjacent cropland (46.32 Mg ha1, summer maize-winter wheat rotation system). This difference can be explained by the fact that the plantation is undergoing the early recovery stage after conversion, and the difference is amplified due to the tree species in the plantation. Metasequoia is a coniferous tree species, and its litter contains an abundance of slowly decomposing secondary compounds, such as cellulose, lignin, and tannins (Corbeels et al., 2003). Similarly, some studies have shown that SOC storage decreases by 12% after conifer planting (Guo and Gifford, 2002; Berthrong et al., 2009). The SOC stocks were larger in the poplar plantation than in the poplar and metasequoia system within the 0e10 and 10e20 cm layers despite the relatively low total SOC stock throughout the soil profile. This difference can be explained by the high-density root system of the understorey vegetation and the subsequent large amount of root-driven C input (Schiedung et al., 2019). In this study, a large amount of SOC accumulated at the 60e100 cm depth, accounting for a large proportion (31.36% and 39.10%) of the cumulative SOC stock in the poplar plantation and poplar and metasequoia system, respectively. Similar to our findings, Batjes (1996) reported that the SOC stock at a depth of 50e100 cm accounted for 19e42% of the cumulative SOC stock in the 0e100 cm soil profile in the

8

J. Guo et al. / Global Ecology and Conservation 22 (2020) e00913

global land area. Generally, the main sources of subsoil SOC are dissolved organic C from the topsoil, soil faunal bioturbation, tree roots, and root exudates. Poplars have deeper roots and larger root systems than metasequoias contributing to relatively large amounts of organic matter input in the subsoil (Jobbagy and Jackson, 2000). Significant differences in SOC, DOC, and MBC contents among plantations were obtained. The higher SOC fractions contents in the poplar-based plantations were mostly due to the high understorey vegetation richness and abundance. This is because the litter and roots of the annual understorey vegetation species were the main sources of SOC input and the large amount of metabolites that can be utilized by microorganisms (Ares et al., 2010; Tian et al., 2011). The SOC content decreased significantly with increasing soil depth, which is consistent with the results obtained by Song et al. (2016), whose study was conducted in black locust plantations. In our study, the low SOC fractions contents in the metasequoia plantation may have been due to the poor quality and low quantity of litter input and poor microbial activity, and the importance of organic inputs has been emphasized by Tu et al. (2006). The high soil C:N ratio of the metasequoia plantation also reflects the low soil quality (Brady and Weil, 2002). This high C:N ratio thus provided another confirmation of the decreased N contents in the metasequoia plantation or the rapid depletion of soil N (Berthrong et al., 2009). Additionally, Kirschbaum et al. (2008) reported that the soil C:N ratio responded much more slowly to afforestation practices than the other indicators did. Different land-use patterns had different effects on the physicochemical properties of the plantations. In the present study, the metasequoia plantation had lower pH values than did the other plantations, although the difference between plantations was only 0.07e0.55 pH units along different soil layers. The possible mechanisms explaining this phenomenon primarily involve high organic acid production, high autotrophic respiration rates, and changes in cation ratios in the plantation soils gy and Jackson, 2003; Richter and Markewitz, 1995). Low bulk densities were obtained in the topsoil in each plantation, (Jobba which was attributed mostly to the high organic matter inputs and the high root densities, as well as other related biological processes in the topsoil (Gao et al., 2019; Jiang et al., 2007; Ritter, 2007; Udawatta et al., 2008). Significantly greater nutrient contents were observed in the shallow layers (0e20 cm) than in the deep layers (20e100 cm), which was mostly due to the high organic matter inputs via litter and the high microbial activity. Moreover, deep-rooted trees can absorb nutrients from the subsoil and may return these nutrients to the surface soil via litter and throughfall, a phenomenon known as the “nutrient gy and Jackson, 2004). pumping” effect (Farley and Kelly, 2004; Jobba 5. Conclusions In this study, the afforestation practices were found to be crucial for the nutrient status and C sequestration in the reclaimed tidal flats, especially in deep soil layers. The soil physicochemical properties varied between the plantations and between the soil layers. Greater TN, ammonium-nitrogen, and nitrate-nitrogen contents were detected in the poplar plantation and poplar and metasequoia system than in the metasequoia plantation along the soil profile. The poplar plantation presented the greatest SOC fractions contents, which were mostly attributed to the high richness and abundance of understorey vegetation. After 10 years of development, the SOC stocks of the poplar plantation and poplar and metasequoia system reached 90.35 and 98.12 Mg ha1, respectively, and large SOC stocks accumulated in the subsoil. The SOC stocks in the shallow layers were larger in the poplar plantation than in the poplar and metasequoia system, despite the smaller total SOC stock of the former. The 0e10, 10e20, and 20e40 cm soil layers accounted for a greater share of the SOC stock in the metasequoia plantation than in the other plantations, whereas the proportion of the SOC stock in the subsoil layers was greatest in the poplar and metasequoia system. In conclusion, our results further indicate that afforestation can cause significant SOC accumulation in the soil, especially in the deep layers. This deep SOC cannot be ignored in regional or global C budgets. Declaration of competing interest None. Acknowledgements This study was supported by the Agricultural Science and Technology Independent Innovation Funds of Jiangsu Province (CX(16)1005), the National Key Research and Development Program of China (2017YFD0600700), the Priority Academic Program Development of Jiangsu Higher Education Institution (PAPD), the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX18_0955) and the Doctorate Fellowship Foundation of Nanjing Forestry University. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.gecco.2020.e00913. References Ares, A., Neill, A.R., Puettmann, K.J., 2010. Understory abundance, species diversity and functional attribute response to thinning in coniferous stands. For. Ecol. Manag. 260, 1104e1113. https://doi.org/10.1016/j.foreco.2010.06.023.

J. Guo et al. / Global Ecology and Conservation 22 (2020) e00913

9

Batjes, N.H., 1996. Total carbon and nitrogen in the soils of the world. Eur. J. Soil Sci. 47, 151e163. https://doi.org/10.1111/j.1365-2389.1996.tb01386.x. Berthrong, S.T., Jobb agy, E.G., Jackson, R.B., 2009. A global meta-analysis of soil exchangeable cations, pH, carbon, and nitrogen with afforestation. Ecol. Appl. 19, 2228e2241. https://doi.org/10.1890/08-1730.1. ~ eiro, G., Jobb Berthrong, S.T., Pin agy, E.G., Jackson, R.B., 2012. Soil C and N changes with afforestation of grasslands across gradients of precipitation and plantation age. Ecol. Appl. 22, 76e86. https://doi.org/10.1890/10-2210.1. Bolstad, P.V., Vose, J.M., 2005. Forest and pasture carbon pools and soil respiration in the southern Appalachian mountains. For. Sci. 51, 372e383. Bonan, G.B., 2008. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444e1449. https://doi.org/10.1126/ science.1155121. Bounouara, Z., Chevallier, T., Balesdent, J., Toucet, J., Sbih, M., Bernoux, M., Belaissaoui, N., Bouneb, O., Bensaid, R., 2017. Variation in soil carbon stocks with depth along a toposequence in a sub-humid climate in North Africa (Skikda, Algeria). J. Arid Environ. 141, 25e33. https://doi.org/10.1016/j.jaridenv.2017. 02.001. Brady, N.C., Weil, R.R., 2002. The Nature and Properties of Soils. Prentice Hall, Upper Saddle River, NJ. Canadell, J.G., Kirschbaum, M.U.F., Kurz, W.A., Sanz, M.-J., Schlamadinger, B., Yamagata, Y., 2007. Factoring out natural and indirect human effects on terrestrial carbon sources and sinks. Environ. Sci. Policy 10, 370e384. https://doi.org/10.1016/j.envsci.2007.01.009. Corbeels, M., O’Connell, A.M., Grove, T.S., Mendham, D.S., Rance, S.J., 2003. Nitrogen release from eucalypt leaves and legume residues as influenced by their biochemical quality and degree of contact with soil. Plant Soil 250, 15e28. https://doi.org/10.1023/a:1022899212115. Don, A., Schumacher, J., Freibauer, A., 2011. Impact of tropical land-use change on soil organic carbon stocks-a meta-analysis. Glob. Chang. Biol. 17, 1658e1670. https://doi.org/10.1111/j.1365-2486.2010.02336.x. FAO, 2011. Climate Change, Water and Food Security. FAO Rome, Italy. FAO Water Reports 36. ramo grassland on soil nutrient status. For. Ecol. Manag. 195, 281e290. https://doi.org/10.1016/j. Farley, K.A., Kelly, E.F., 2004. Effects of afforestation of a pa foreco.2003.12.015. , P., Bdioui, N., Mary, B., Rumpel, C., 2007. Stability of organic carbon in deep soil layers controlled by fresh carbon supply. Nature Fontaine, S., Barot, S., Barre 450, 277e280. https://doi.org/10.1038/nature06275. Fu, X., Shao, M., Wei, X., Horton, R., 2010. Soil organic carbon and total nitrogen as affected by vegetation types in Northern Loess Plateau of China. Geoderma 155, 31e35. https://doi.org/10.1016/j.geoderma.2009.11.020. Gao, X., Meng, T., Zhao, X., 2017. Variations of soil organic carbon following land use change on deep-loess hillsopes in China. Land Degrad. Dev. 28, 1902e1912. https://doi.org/10.1002/ldr.2693. Gao, Y., Zhou, J., Wang, L., Guo, J., Feng, J., Wu, H., Lin, G., 2019. Distribution patterns and controlling factors for the soil organic carbon in four mangrove forests of China. Glob. Ecol. Conserv. 17, e00575 https://doi.org/10.1016/j.gecco.2019.e00575. Guedes, B.S., Olsson, B.A., Karltun, E., 2016. Effects of 34-year-old Pinus taeda and Eucalyptus grandis plantations on soil carbon and nutrient status in former miombo forest soils. Glob. Ecol. Conserv. 8, 190e202. https://doi.org/10.1016/j.gecco.2016.09.005. Guo, J., Wang, B., Wang, G., Wu, Y., Cao, F., 2018. Vertical and seasonal variations of soil carbon pools in ginkgo agroforestry systems in eastern China. Catena 171, 450e459. https://doi.org/10.1016/j.catena.2018.07.032. Guo, L.B., Gifford, R.M., 2002. Soil carbon stocks and land use change: a meta analysis. Glob. Chang. Biol. 8, 345e360. https://doi.org/10.1046/j.1354-1013. 2002.00486.x. Guo, X., Meng, M., Zhang, J., Chen, H.Y., 2016. Vegetation change impacts on soil organic carbon chemical composition in subtropical forests. Sci. Rep. 6, 29607. https://doi.org/10.1038/srep29607. Han, X., Zhao, F., Tong, X., Deng, J., Yang, G., Chen, L., Kang, D., 2017. Understanding soil carbon sequestration following the afforestation of former arable land by physical fractionation. Catena 150, 317e327. https://doi.org/10.1016/j.catena.2016.11.027. Huang, L., Liu, J., Shao, Q., Xu, X., 2012. Carbon sequestration by forestation across China: past, present, and future. Renew. Sustain. Energy Rev. 16, 1291e1299. https://doi.org/10.1016/j.rser.2011.10.004. Jiang, P., Anderson, S.H., Kitchen, N.R., Sadler, E.J., Sudduth, K.A., 2007. Landscape and conservation management effects on hydraulic properties of a claypan-soil toposequence. Soil Sci. Soc. Am. J. 71, 803e811. https://doi.org/10.2136/sssaj2006.0236. Jobbagy, E.G., Jackson, R.B., 2000. The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol. Appl. 10, 423e436. https:// doi.org/10.2307/2641104. gy, E.G., Jackson, R.B., 2003. Patterns and mechanisms of soil acidification in the conversion of grasslands to forests. Biogeochemistry 64, 205e229. Jobba https://doi.org/10.1023/a:1024985629259. gy, E.G., Jackson, R.B., 2004. The uplift of soil nutrients by plants: biogeochemical consequences across scales. Ecology 85, 2380e2389. https://doi.org/ Jobba 10.1890/03-0245. Keenan, R.J., Reams, G.A., Achard, F., de Freitas, J.V., Grainger, A., Lindquist, E., 2015. Dynamics of global forest area: results from the FAO global forest resources assessment 2015. For. Ecol. Manag. 352, 9e20. https://doi.org/10.1016/j.foreco.2015.06.014. Kirschbaum, M.U.F., Guo, L.B., Gifford, R.M., 2008. Why does rainfall affect the trend in soil carbon after converting pastures to forests? A possible explanation based on nitrogen dynamics. For. Ecol. Manag. 255, 2990e3000. https://doi.org/10.1016/j.foreco.2008.02.005. re, J., Angers, D.A., Pare , D., 2010. Carbon accumulation in agricultural soils after afforestation: a meta-analysis. Glob. Chang. Biol. 16, 439e453. Laganie https://doi.org/10.1111/j.1365-2486.2009.01930.x. Lal, R., 2004. Soil carbon sequestration impacts on global climate change and food security. Science 304, 1623e1627. https://doi.org/10.1126/science. 1097396. Li, D., Niu, S., Luo, Y., 2012. Global patterns of the dynamics of soil carbon and nitrogen stocks following afforestation: a meta-analysis. New Phytol. 195, 172e181. https://doi.org/10.1111/j.1469-8137.2012.04150.x. Li, Z., Liu, C., Dong, Y., Chang, X., Nie, X., Liu, L., Xiao, H., Lu, Y., Zeng, G., 2017. Response of soil organic carbon and nitrogen stocks to soil erosion and land use types in the Loess hillyegully region of China. Soil Tillage Res. 166, 1e9. https://doi.org/10.1016/j.still.2016.10.004. Liao, J.D., Boutton, T.W., 2008. Soil microbial biomass response to woody plant invasion of grassland. Soil Biol. Biochem. 40, 1207e1216. https://doi.org/10. 1016/j.soilbio.2007.12.018. Lu, R.K., 1999. Analytical Methods for Soil Agrochemistry. Chinese Agricultural Science and Technology Publishing House, Beijing. Mao, R., Zeng, D.-H., Hu, Y.-L., Li, L.-J., Yang, D., 2010. Soil organic carbon and nitrogen stocks in an age-sequence of poplar stands planted on marginal agricultural land in Northeast China. Plant Soil 332, 277e287. https://doi.org/10.1007/s11104-010-0292-7. Nave, L.E., Swanston, C.W., Mishra, U., Nadelhoffer, K.J., 2013. Afforestation effects on soil carbon storage in the United States: a synthesis. Soil Sci. Soc. Am. J. 77, 1035. https://doi.org/10.2136/sssaj2012.0236. Paul, K.I., Polglase, P.J., Nyakuengama, J.G., Khanna, P.K., 2002. Change in soil carbon following afforestation. For. Ecol. Manag. 168, 241e257. https://doi.org/ 10.1016/s0378-1127(01)00740-x. Poeplau, C., Don, A., 2013. Sensitivity of soil organic carbon stocks and fractions to different land-use changes across Europe. Geoderma 192, 189e201. https://doi.org/10.1016/j.geoderma.2012.08.003. Richter, D.D., Markewitz, D., 1995. How deep is soil? Bioscience 45, 600e609. https://doi.org/10.2307/1312764. Ritter, E., 2007. Carbon, nitrogen and phosphorus in volcanic soils following afforestation with native birch (Betula pubescens) and introduced larch (Larix sibirica) in Iceland. Plant Soil 295, 239e251. https://doi.org/10.1007/s11104-007-9279-4. Schiedung, M., Tregurtha, C.S., Beare, M.H., Thomas, S.M., Don, A., 2019. Deep soil flipping increases carbon stocks of New Zealand grasslands. Glob. Chang. Biol. 25, 2296e2309. https://doi.org/10.1111/gcb.14588. Schlesinger, W.H., Andrews, J.A., 2000. Soil respiration and the global carbon cycle. Biogeochemistry 48, 7e20. https://doi.org/10.1023/a:1006247623877.

10

J. Guo et al. / Global Ecology and Conservation 22 (2020) e00913

Shi, S., Zhang, W., Zhang, P., Yu, Y., Ding, F., 2013. A synthesis of change in deep soil organic carbon stores with afforestation of agricultural soils. For. Ecol. Manag. 296, 53e63. https://doi.org/10.1016/j.foreco.2013.01.026. Shibata, H., Urakawa, R., Toda, H., Inagaki, Y., Tateno, R., Koba, K., Nakanishi, A., Fukuzawa, K., Yamasaki, A., 2011. Changes in nitrogen transformation in forest soil representing the climate gradient of the Japanese archipelago. J. For. Res. 16, 374e385. https://doi.org/10.1007/s10310-011-0288-z. Song, B.-L., Yan, M.-J., Hou, H., Guan, J.-H., Shi, W.-Y., Li, G.-Q., Du, S., 2016. Distribution of soil carbon and nitrogen in two typical forests in the semiarid region of the Loess Plateau, China. Catena 143, 159e166. https://doi.org/10.1016/j.catena.2016.04.004. Tian, H., Melillo, J., Lu, C., Kicklighter, D., Liu, M., Ren, W., Xu, X., Chen, G., Zhang, C., Pan, S., Liu, J., Running, S., 2011. China’s terrestrial carbon balance: contributions from multiple global change factors. Glob. Biogeochem. Cycles 25, GB1007. https://doi.org/10.1029/2010gb003838. Tu, C., Ristaino, J.B., Hu, S., 2006. Soil microbial biomass and activity in organic tomato farming systems: effects of organic inputs and straw mulching. Soil Biol. Biochem. 38, 247e255. https://doi.org/10.1016/j.soilbio.2005.05.002. Udawatta, R.P., Anderson, S.H., Gantzer, C.J., Garrett, H.E., 2008. Influence of prairie restoration on CT-measured soil pore characteristics. J. Environ. Qual. 37, 219e228. https://doi.org/10.2134/jeq2007.0227. Vance, E.D., Brookes, P.C., Jenkinson, D.S., 1987. An extraction method for measuring soil microbial biomass C. Soil Biol. Biochem. 19, 703e707. https://doi. org/10.1016/0038-0717(87)90052-6. Vesterdal, L., Ritter, E., Gundersen, P., 2002. Change in soil organic carbon following afforestation of former arable land. For. Ecol. Manag. 169, 137e147. https://doi.org/10.1016/s0378-1127(02)00304-3. Wu, Q., Zhang, C., Yu, Z., Zhang, J., Zhu, C., Zhao, Z., Xiong, J., Chen, J., 2018. Effects of elevated CO2 and nitrogen addition on organic carbon and aggregates in soil planted with different rice cultivars. Plant Soil 432, 245e258. https://doi.org/10.1007/s11104-018-3801-8. Yu, G.-R., Zhu, X.-J., Fu, Y.-L., He, H.-L., Wang, Q.-F., Wen, X.-F., Li, X.-R., Zhang, L.-M., Zhang, L., Su, W., Li, S.-G., Sun, X.-M., Zhang, Y.-P., Zhang, J.-H., Yan, J.-H., Wang, H.-M., Zhou, G.-S., Jia, B.-R., Xiang, W.-H., Li, Y.-N., Zhao, L., Wang, Y.-F., Shi, P.-L., Chen, S.-P., Xin, X.-P., Zhao, F.-H., Wang, Y.-Y., Tong, C.-L., 2013. Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China. Glob. Chang. Biol. 19, 798e810. https://doi.org/10.1111/gcb. 12079. Zhang, H., Wu, P., Yin, A., Yang, X., Zhang, M., Gao, C., 2017. Prediction of soil organic carbon in an intensively managed reclamation zone of eastern China: a comparison of multiple linear regressions and the random forest model. Sci. Total Environ. 592, 704e713. https://doi.org/10.1016/j.scitotenv.2017.02. 146.