Soil organic carbon sequestration potential of cropland in China
Post on 23-Dec-2016
Soil organic carbon sequestration potential of cropland in China
Zhangcai Qin,1,2 Yao Huang,1 and Qianlai Zhuang2
Received 21 November 2012; revised 5 May 2013; accepted 13 July 2013; published 12 August 2013.
 Soil organic carbon (SOC) in cropland is of great importance to the global carbon (C)balance and to agricultural productivity, but it is highly sensitive to human activities such asirrigation and crop rotation. It has been observed that under certain improved managementpractices, cropland soils can sequestrate additional C beyond their existing SOC level beforereaching the C saturation state. Here we use data from worldwide, long-term agriculturalexperiments to develop two statistical models to determine the saturated SOC level (SOCS) inupland and paddy agroecosystems, respectively. We then use the models to estimate SOCsequestration potential (SOCP) in Chinese croplands. SOCP is the difference between SOCSand existing SOC level (SOCE). We nd that the models for both the upland and paddyagroecosystems can reproduce the observed SOCS data from long-term experiments. TheSOCE and SOCS stock in Chinese upland and paddy croplands (030 cm soil) are estimated tobe 5.2 and 7.9 Pg C with national average densities of 37.4 and 56.8Mg C ha1,respectively. As a result, the total SOC sequestration potential is estimated to be 2.7 Pg C or19.4Mg C ha1 in Chinese cropland. Paddy has a relatively higher SOCE (45.4Mg C ha1)than upland (34.7Mg C ha1) and also a greater SOCP at 26.1Mg C ha1 compared with17.2Mg C ha1 in the upland. The SOC varies dramatically among different regions.Northeast China has the highest SOCE and SOCS density, while the Loess Plateau has thegreatest SOCP density. The time required to reach SOC saturation in Chinese cropland ishighly dependent onmanagement practices applied. Chinese cropland has relatively low SOCdensity in comparison to the global average but could have great potentials for C sequestrationunder improved agricultural management strategies.
Citation: Qin, Z., Y. Huang, and Q. Zhuang (2013), Soil organic carbon sequestration potential of cropland in China,Global Biogeochem. Cycles, 27, 711722, doi:10.1002/gbc.20068.
 Soil organic carbon (SOC) is a great component of theglobal carbon budget and is important to agricultural produc-tivity [Lal, 2004a; Piao et al., 2009]. It is estimated thataround 2500 Pg carbon (C) is stored in soils globally, whichmeans that the soil C pool is about 3 times the size of theatmospheric C pool and 4 times the biotic C pool [Batjes,1996; Eswaran et al., 1993; Lal, 2004a]. Of the soil C pool,over 60% is SOC that is sensitive to both macroscale envi-ronmental conditions and microscale soil conditions, and40% is soil inorganic carbon, which can be relatively resis-tant to environmental changes. SOC, in this sense, is a keycomponent in determining the carbon budget. Also, SOC is
an important indicator for soil fertility and soil quality, actingas an active sink and source reservoir for plant nutrients, im-proving soil microenvironments through physical, chemical,and biological processes, and thus determining ecosystemproductivity [Bronick and Lal, 2005; Kimetu et al., 2009;Six et al., 2002]. Cropland soils in particular are highly dis-turbed by intensive human activities including variousagricultural management practices [Lal and Bruce, 1999;Lu et al., 2009; Sun et al., 2009]. The cropland SOC pool,especially the top layer (030 cm), is critical to the soil Cstorage and crop yield [Smith et al., 2000; Sun et al., 2010]. Cropland SOC is correlated with both environmental
factors and management practices. For a given cropland,short-term SOC dynamics are strongly affected by manage-ment activities such as fertilization, tillage, and rotation. Forexample, organic carbon input like manure could signicantlyincrease SOC content when preexisting SOC is at a low level[Kimetu et al., 2009; Shen et al., 2007; Stewart et al., 2007],and conservation tillage can prevent soil carbon loss,compared to conventional tillage [Follett, 2001; Lal, 2004a,2004c; Smith, 2004; West and Post, 2002]. Lal [2004a]estimated that by applying conservation tillage, cover crops,manure, and other recommended management practices(RMP; e.g., mulch farming, reduced tillage, integrated nutrientmanagement, integrated pest management, and precisionfarming), global soils could have a C sequestration potential
Additional supporting information may be found in the online version ofthis article.
1State Key Laboratory of Vegetation and Environmental Change,Institute of Botany, Chinese Academy of Sciences, Beijing, China.
2Departments of Earth, Atmospheric and Planetary Sciences andAgronomy, Purdue University, West Lafayette, Indiana, USA.
Corresponding author: Y. Huang, State Key Laboratory of Vegetationand Environmental Change, Institute of Botany, Chinese Academy ofSciences, No. 20 Nanxincun, Xiangshan, Beijing 100093, China.(firstname.lastname@example.org)
2013. American Geophysical Union. All Rights Reserved.0886-6236/13/10.1002/gbc.20068
GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 27, 711722, doi:10.1002/gbc.20068, 2013
of 0.40.8 Pg C yr1 [Lal, 2004a]. For croplands under givenmanagement practices, the environmental factors, such as cli-mate and soil conditions, determine long-term SOC variationsacross space. Experiment-based studies indicate thattemperature has a negative impact on SOC content whileprecipitation has a positive impact [Dai and Huang, 2006;Mller and Hper, 2004], and this relationship tends to benonlinearity [Alvarez and Lavado, 1998; Chapin et al.,2002]. Soil texture, especially ne particle fractions such asclay or silt content, is believed to be positively related toSOC content, especially in soils with high percentage of neparticles [Angers et al., 2011; Liang et al., 2009; Mller andHper, 2004; Zhao et al., 2006]. Soil acidity affects soilphysical and biological properties, e.g., soil microbe activity,and therefore soil carbon decomposition [Chapin et al.,2002; Krug and Frink, 1983; Schmidt et al., 2011].However, the soil acidity effects may only be applied in a verynarrow range of soil pH, since cropland soils are alwaysadjusted to certain acidity for crop growth. It has long been assumed that SOC level is positively
related with C input level in a linear relationship, and mostSOC models employ rst-order kinetics to model decomposi-tion processes; however, recent studies found little or no SOCchange observed in response to varying C input in a number oflong-term agroecosystem experiments, and, to the contrary, aceiling on the capacity of SOC content was observed, whichlimits increases in SOC, even with additional C inputs[Gulde et al., 2008; Six et al., 2002; Stewart et al., 2007].After tens or even hundreds of years of eld experiments, stud-ies in Africa [Kamoni et al., 2007], Asia [Manna et al., 2005;Manna et al., 2007; Shen et al., 2007; Yang et al., 2007],Australia [Coleman et al., 1997; Smith et al., 1997], Europe[Powlson et al., 1998; Schmidt et al., 2000; Smith et al.,1997], North America [Grant et al., 2001; Huggins et al.,1998; Izaurralde et al., 2001; Paul et al., 1997], and SouthAmerica [Bayer et al., 2006, 2000] show that soil can accumu-late a signicant amount of C when the preexisting SOC is stillat a low level, and therefore, SOC at steady state increases withC inputs; however, after SOC content reaches a certain level, itshows little or no signicant change, even with more C inputs.It is believed that soil at the nal SOC stable state reachesits carbon saturation state, and the SOC achieves the SOCsaturation level [Six et al., 2002; Stewart et al., 2007]. Basedon long-term eld experiment observations, Stewart et al. proposed nonlinear carbon saturation models againstthe linear model to test the SOC-C input relationship.Results suggest that the saturation of soil C does occur, andthe highest efciency of C xation is in soils further from Csaturation [Stewart et al., 2007]. In the case that SOC level will reach its ceiling or satu-
ration level, whether in the short or long term, soil carbonsequestration potential could be used to assess the carbonholding capacity in soil. Soil carbon sequestration potentialmeasures the difference between the theoretical SOC satura-tion level and the existing SOC level and corresponds to thesoil saturation decit [Hassink, 1996; Stewart et al., 2007].Soil carbon sequestration potential may represent the potentialfor an additional transfer of C from the atmosphere [Powlsonet al., 2011]. Lal  estimated that by applying RMPs tocropland might enhance SOC sequestration at the rate of200300kgha1yr1, and therefore, a total of 2537 Tg C yr1
can be accumulated in Chinese cropland. By extrapolating
site-level SOC sequestration rates, Lu et al.  suggestedthat the carbon sequestration potentials of Chinese croplandcan reach 34.4 and 4.60 Tg C yr1 using straw return andno-tillage techniques, respectively. Based on several agricul-tural management scenarios of crop residue return and tillage,Yan et al.  simulated the SOC dynamics using a pro-cess-based ecosystem model and predicted an annual soil Csequestration of 32.5 Tg C in China as a result of practicingno-tillage on 50% of the arable lands and returning 50% ofthe crop residue to soils. The soil carbon sequestration ratevaries much among different studies, due to variations fromdata sources, methods, and management scenarios. Even with reliable estimations of soil carbon seques-
tration rates at the site level, large uncertainties still maybe introduced into regional or national extrapolation.Simply applying local management practices into broaderareas ignores the spatial variations in climate, soil, andvegetation conditions, and results in upscaling uncertainty[Lal, 2002; Sun et al., 2010]. Processes-based modeling,by comparison, provides a more reliable theoretical founda-tion by integrating SOC dynamics with spatial environmen-tal factors and quantifying the importance of managementpractices [Smith et al., 1997; Yan et al., 2007]. However,most SOC models do not include the carbon saturation pro-cess and predict linearity between SOC level at steady stateand C input level, which inevitably leads to simulationuncertainty [Stewart et al., 2007]. Moreover, biogeo-chemical and biogeophysical processes are involved in mostprocess-based models, which requires a huge number ofvegetation-specic or soil-specic parameters and generallylots of input data which may not necessarily be available.These extra efforts might make process-based models lessaccessible and more challenging for people to use [Huanget al., 2009; Smith et al., 1997]. In order to incorporate a carbon saturation concept and
spatial environmental variations in estimating SOC sequestra-tion potential, we developed a statistical nonlinear model tosimulate SOC at the saturation level (020 cm soil) in responseto climate and soil conditions [Qin and Huang, 2010]. Thismodel is based on global, long-term agroecosystem experi-ments and is well validated using eld data from nationwideupland experiments in China [Qin and Huang, 2010]. In thisstudy, we further extend this model to 030 cm in upland soilsand develop a similar model for simulating SOC at the satura-tion level in paddy agroecosystems using long-term observa-tional data. Additionally, by applying these models toChinese agroecosystems, we estimate SOC at the saturationlevel and SOC sequestration potential at both regional andnational scales. The SOC sequestration rate and duration arealso discussed in this study in the context of understandingthe importance of management practices in preserving soilC. SOC is estimated and presented for the top 30 cm of thesoils where the great majority of SOC changes occur in crop-land [Smith et al., 2000; Sun et al., 2010].
2. Materials and Methods
2.1. C Saturation and SOC Sequestration Potential
 SOC changes with time. SOC steady state describes adynamic soil condition where carbon input rate equals lossrate. At a given C input level, SOC changes with environ-ment and nally reaches a relatively stable state, the steady
QIN ET AL.: CROPLAND SOC POTENTIAL IN CHINA
state (e.g., SOCE(i) of Figure 1a). However, with additional Cinput, SOC will increase asymptotically with time and achievea new steady state (e.g., SOCE(i) of Figure 1a) in response to Cinput level [Chapin et al., 2002; Johnson et al., 1995].However, the SOC-C input relationship is not positively linearas the dash-dotted line in Figure 1b that SOC increases withcontinuous C input indenitely. Instead, with greater C input,the SOC sequestration efciency declines, and the SOC atsteady state (solid curve in Figure 1b) increases much moreslowly than the linear change; with enough C input, the SOCsequestration rate nally approaches zero, and SOC at steadystate reaches the ceiling (e.g., SOCS(k) in Figure 1b)[Stewart et al., 2007; West and Six, 2007]. Theoretically, the maximum steady state SOC is dened
as saturated SOC (SOCS). SOC sequestration potential(SOCP) is dened as the difference between SOCS and thepreexisting SOC level (SOCE) (Figure 1b). For example,SOCP (k, j) is SOC sequestration potential between the saturateSOC level at state k (SOCS(k)) and the existing SOC level atstate j (SOCE(j)) (Figure 1b). For any given soil type, theoret-ical SOCS is believed to be unique and mainly determined byinherent soil physicochemical properties [Six et al., 2002;Angers et al., 2011]. However, at any given location, changingnvironmental factors such as temperature regime, precipitationor soil moisture, and management practice can all lead to var-iable steady state SOC level and therefore should beconsidered when simulating the SOCS achieved under givenenvironment. The apparent SOCS (referred to as SOCS hereaf-ter, unless otherwise stated) can be modeled as a function of lo-cal climate and soil conditions, nomatter what the existing SOClevel is. The corresponding apparent SOCP (referred to as SOCphereafter, unless otherwise stated) will be determined by thedifference between apparent SOCS and current SOC level.
2.2. Long-Term Experimental Data and Spatial Data
 Over 100 eld experiments that last no less than10 years were selected for model development. For uplandagroecosystems, a total of 95 long-term agricultural ex-periments with high C input level were introduced to developthe model SOCS (U) for estimating saturated SOC (Tables S1
and S2); these experiments are distributed across a vast crop-land area spanning wide ranges of temperate, subtropical,and tropical climates (Figure S1). For paddy agroecosystems,datasets from 36 long-term experiments are included for de-veloping the model of SOCS (P) (Tables S3 and S4). These ex-periments are mostly from Asian countries, such as China,India, and Japan, and cover a majority proportion of theworlds rice planting areas (Statistics Division of the Foodand Agriculture Organization of the United Nations, http:...