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2022 Vol. 46, No. 5
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YANG Ze, ZHANG Yi-He, DAI Hui-Min, LIU Guo-Dong, LIU Kai, XU Jiang. 2022. Control factor of the spatial variations in the soil organic carbon content in the topsoil of the Xingkai Lake Plain. Geophysical and Geochemical Exploration, 46(5): 1076-1086. doi: 10.11720/wtyht.2022.0186
Citation: YANG Ze, ZHANG Yi-He, DAI Hui-Min, LIU Guo-Dong, LIU Kai, XU Jiang. 2022. Control factor of the spatial variations in the soil organic carbon content in the topsoil of the Xingkai Lake Plain. Geophysical and Geochemical Exploration, 46(5): 1076-1086. doi: 10.11720/wtyht.2022.0186

Control factor of the spatial variations in the soil organic carbon content in the topsoil of the Xingkai Lake Plain

  • Obtaining accurate soil organic carbon (SOC) content in the Xingkai Lake Plain and the main factor controlling its spatial variation is greatly significant for controlling and restoring the SOC content and achieving sustainable agricultural development. This study investigated the spatial distribution characteristics of the SOC content in the Xingkai Lake Plain and their control factor based on 4,151 topsoil samples collected at a depth of 0~20 cm in the field. Moreover, it compared the effects of soil parent materials, soil texture, soil type, land use type, and land reclamation duration (year) on the spatial distribution of the SOC content in the plain through geostatistical and regression analyses. The results are as follows. The SOC content in the topsoil of the study area is 0.35%~14.49% (average: 2.80%). It has a coefficient of variation of 0.44, indicating moderate spatial variations. It has a nugget-to-sill ratio of 47.06%, indicating that its spatial distributions are affected by both structural and random factors. It is low in the middle and west and is high in the east and north overall. All these five factors have significant effects on the SOC content (P<0.01). Among them, soil parent materials, soil type, land use type, and land reclamation duration can independently account for 6.8%, 3.8%, 9.2%, and 3.3% of the spatial variations in the SOC content, respectively. By contrast, soil texture can independently account for 30.1% of the spatial variations of the SOC content, which is far greater than that of the other four factors. Therefore, soil texture is the main control factor in the spatial distribution of the SOC content in the study area.
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  • [1] 方华军, 杨学明, 张晓平. 东北黑土有机碳储量及其对大气CO2的贡献[J]. 水土保持学报, 2003, 17(3):9-12.

    Google Scholar

    [2] Fang H J, Yang X M, Zhang X P. Organic carbon stock of black soils in northeast China and it’s contribution to atmospheric CO2[J]. Journal of Soil and Water Conservation, 2003, 17(3): 9-12.

    Google Scholar

    [3] Batjes N H. Total carbon and nitrogen in the soils of the world[J]. European Journal of Soil Science, 1996, 7(2): 151-163.

    Google Scholar

    [4] 赵其国. 提升对土壤认识,创新现代土壤学[J]. 土壤学报, 2008, 45(5): 771-777.

    Google Scholar

    [5] Zhao Q G. Improving knowledge of soil, innovating modern pedology[J]. Acta Pedologica Sinica, 2008, 45(5): 771-777.

    Google Scholar

    [6] Pan G X, Smith P, Pan W N. The role of soil organic matter in maintaining the productivity and yield stability of cereals in China[J]. Agriculture,Ecosystems and Environment, 2009, 129(1/3): 344-348.

    Google Scholar

    [7] Lal R. Soil carbon sequestration impacts on global climate change and food security[J]. Science, 2004, 304(5677): 1623-1627.

    Google Scholar

    [8] 江叶枫, 饶磊, 郭熙, 等. 江西省耕地土壤有机碳空间变异的主控因素研究[J]. 土壤, 2018, 50(4):778-786.

    Google Scholar

    [9] Jiang Y F, Rao L, Guo X, et al. Study on main controlling factors of spatial variability of farmland SOC in Jiangxi Province[J]. Soils, 2018, 50(4):778-786.

    Google Scholar

    [10] 罗由林, 李启权, 王昌全, 等. 四川省仁寿县土壤有机碳空间分布特征及其主控因素[J]. 中国生态农业学报, 2015, 23(1):34-42.

    Google Scholar

    [11] Luo Y L, Li Q Q, Wang C Q, et al. Spatial variability of soil organic carbon and related controlling factors in Renshou County, Sichuan Province[J]. Chinese Journal of Eco-Agriculture, 2015, 23(1):34-42.

    Google Scholar

    [12] 李启权, 王昌全, 岳天祥, 等. 基于RBF神经网络的土壤有机质空间变异研究方法[J]. 农业工程学报, 2010, 26(1):87-93.

    Google Scholar

    [13] Li Q Q, Wang C Q, Yue T X, et al. Method for spatial variety of soil organic matter based on radial basis function neural network[J]. Transactions of the Chinese Society of Agricultural Engineering, 2010, 26(1):87-93.

    Google Scholar

    [14] 潘成忠, 上官周平. 土壤空间变异性研究评述[J]. 生态环境, 2003, 12(3):371-375.

    Google Scholar

    [15] Pan C Z, Shangguan Z P. Review of the research on soil spatial variability[J]. Ecology and Environment Sciences, 2003, 12(3):371-375.

    Google Scholar

    [16] 赵明松, 张甘霖, 王德彩, 等. 徐淮黄泛平原土壤有机质空间变异特征及主控因素分析[J]. 土壤学报, 2013, 50(1):1-11.

    Google Scholar

    [17] Zhao M S, Zhang G L, Wang D C, et al. Spatial variability of soil organic matter and its dominating factors in Xu-Huai alluvial plain[J]. Acta Pedologica Sinica, 2013, 50(1):1-11.

    Google Scholar

    [18] 顾成军, 史学正, 于东升, 等. 省域土壤有机碳空间分布的主控因子——土壤类型与土地利用比较[J]. 土壤学报, 2013, 50(3):425-432.

    Google Scholar

    [19] Gu C J, Shi X Z, Yu D S, et al. Main factor controlling soc spatial distribution at the province scale as affected by soil type and land us[J]. Acta Pedologica Sinica, 2013, 50(3):425-432.

    Google Scholar

    [20] 胡玉福, 邓良基, 张世熔, 等. 川中丘陵区典型小流域土壤氮素空间变异特征及影响因素研究[J]. 水土保持学报, 2008, 22(3):70-75.

    Google Scholar

    [21] Hu Y F, Deng L J, Zhang S R, et al. Study on spatial variability and its influential factors of soils nitrogen in typical small watershed in the hilly region of the middle Sichuan[J]. Journal of Soil and Water Conservation, 2008, 22(3):70-75.

    Google Scholar

    [22] 李婷, 张世熔, 刘浔, 等. 沱江流域中游土壤有机质的空间变异特点及其影响因素[J]. 土壤学报, 2011, 48(4):863-868.

    Google Scholar

    [23] Li T, Zhang S R, Liu X, et al. Spatial variation of soil organic matter and its influence factors in the middle reaches ofTuojiang river basin[J]. Acta Pedologica Sinica, 2011, 48(4):863-868.

    Google Scholar

    [24] Zhang S W, Huang Y F, Shen C Y, et al. Spatial prediction of soil organic matter using terrain indices and categorical variables as auxiliary information[J]. Geoderma, 2012, 171/172: 35-43.

    Google Scholar

    [25] 房飞, 唐海萍, 李滨勇. 不同土地利用方式对土壤有机碳及其组分影响研究[J]. 生态环境学报, 2013, 22(11): 1774-1779.

    Google Scholar

    [26] Fang F, Tang H P, Li B Y. Effects of land use type on soil organic carbon and its fractions[J]. Ecology and Environment Sciences, 2013, 22(11): 1774-1779.

    Google Scholar

    [27] 王晓丽, 王嫒, 石洪华, 等. 南长山岛不同土地利用方式下的土壤有机碳密度[J]. 环境科学学报, 2014, 34(4): 1009-1015.

    Google Scholar

    [28] Wang X L, Wang A, Shi H H, et al. Soil organic carbon density under different land use types on the Nanchangshan Island of Miaodao Archipelago[J]. Acta Scientiae Circumstantiae, 2014, 34(4): 1009-1015.

    Google Scholar

    [29] Rasmussen C, Torn M S, Southard R J. Mineral assemblage and aggregates control carbon dynamics in a California conifer forest[J]. Soil Science Society of America Journal, 2005, 69(6): 1711-1721

    Google Scholar

    [30] 赵明松, 张甘霖, 李德成, 等. 江苏省土壤有机质变异及其主要影响因素[J]. 生态学报, 2013, 33(16):5058-5066.

    Google Scholar

    [31] Zhao M S, Zhang G L, Li D C, et al. Variability of soil organic matter and its main factors in Jiangsu Province[J]. Acta Ecologica Sinica, 2013, 33(16):5058-5066.

    Google Scholar

    [32] 范胜龙, 黄炎和, 林金石. 表征土壤有机碳区域分布的优化空间插值模型研究——以福建省龙海市为例[J]. 水土保持研究, 2011, 18(6):1-5.

    Google Scholar

    [33] Fan S L, Huang Y H, Lin J S. The optimized interpolation models and its relationship with soil sampling density on detecting spatial variability of farmland soil organic carbon:A case study in Longhai City,Fujian Province[J]. Research of Soil and Water Conservation, 2011, 18(6):1-5.

    Google Scholar

    [34] 中华人民共和国国土资源部. DZ/T 0258-2014多目标区域地球化学调查规范(1:250 000)[S]. 北京: 中国标准出版社, 2015.[20] Ministry of Land and Resources of the People's Republic of China. DZ/T 0258-2014 Specification of multi-purpose regional geochemical survey[S]. Beijing: Geological Publishing House, 2015.

    Google Scholar

    [35] 中华人民共和国国土资源部. DZ/T 0295-2016土地质量地球化学评价规范[S]. 北京: 地质出版社, 2016.[21] Ministry of Land and Resources of the People's Republic of China. DZ/T 0295-2016 Specification of land quality geochemical assessment[S]. Beijing: Geological Publishing House, 2016.

    Google Scholar

    [36] 綦魏, 付建飞, 王恩德, 等. 基于化学蚀变指数(CIA)的辽河流域土壤风化程度研究[J]. 东北大学学报:自然科学版, 2012, 33(3):444-447.

    Google Scholar

    [37] Qi W, Fu J F, Wang E D, et al. Study of the soil weathering degree of the Liao River basin Based on CIA index[J]. Journal of Northeastern University:Natural Science, 2012, 33(3):444-447.

    Google Scholar

    [38] Mclennan S M. Weathering and global denudation[J]. Journal of Geology, 1993, 101(2):295-303.

    Google Scholar

    [39] 王攀, 宁凯, 石迎春, 等. 吴起全新世土壤剖面常量元素地球化学特征[J]. 土壤通报, 2019, 50(6):1261-1268.

    Google Scholar

    [40] Wang P, Ning K, Shi Y C, et al. Geochemical characteristics of major elements of holocene soil from Wuqi, Shaanxi Province[J]. Chinese Journal of Soil Science, 2019, 50(6):1261-1268.

    Google Scholar

    [41] 孙厚云, 孙晓明, 贾凤超, 等. 河北承德锗元素生态地球化学特征及其与道地药材黄芩适生关系[J]. 中国地质, 2020, 47(6):1646-1667.

    Google Scholar

    [42] Sun H Y, Sun X M, Jia F C, et al. The eco-geochemical characteristics of germanium and its relationship with the genuine medicinal material Scutellariabaicalensis in Chengde, Hebei Province[J]. Geology in China, 2020, 47(6):1646-1667.

    Google Scholar

    [43] 徐树建, 倪志超, 丁新潮. 山东平阴黄土剖面常量元素地球化学特征[J]. 矿物岩石地球化学通报, 2016, 35(2):353-359.

    Google Scholar

    [44] Xu S J, Ni Z C, Ding X C. Geochemical characteristics of major elements of the Pingyin loess in Shandong Province[J]. Bulletin of Mineralogy, Petrology and Geochemistry, 2016, 35(2): 353-359.

    Google Scholar

    [45] 李绪龙, 张霞, 林春明, 等. 常用化学风化指标综述:应用与展望[J]. 高校地质学报, 2022, 28(1):51-63.

    Google Scholar

    [46] Li X L, Zhang X, Lin C M, et al. Overview of the application and prospect of common chemical weathering indices[J]. Geological Journal of China Universities, 2022, 28(1):51-63.

    Google Scholar

    [47] 黑龙江省土地管理局, 黑龙江省土壤普查办公室. 黑龙江土壤[M]. 北京: 农业出版社,1994.

    Google Scholar

    [48] Heilongjiang Land Management Bureau, Heilongjiang Province Soil Census Office. Heilongjiang soil[M]. Beijing: China agricultural machinery press,1994.

    Google Scholar

    [49] 解宏图, 郑立臣, 何红波, 等. 东北黑土有机碳、全氮空间分布特征[J]. 土壤通报, 2006, 37(6):1058-1061.

    Google Scholar

    [50] Xie H T, Zheng L C, He H B, et al. Spatial distribution of soil organic carbon and total nitrogen in mollisols in the Northeast of China[J]. Chinese Journal of Soil Science, 2006, 37(6):1058-1061.

    Google Scholar

    [51] 戴慧敏, 刘国栋. 东北黑土地1:25万土地质量地球化学调查报告[R]. 中国地质调查局沈阳地质调查中心, 2019.

    Google Scholar

    [52] Dai H M, Liu G D. Land quality geochemical survey report of black soil in northeast China on scale 1:250 000[R]. Shenyang Geological Survey Center,CGS, 2019.

    Google Scholar

    [53] 罗梅, 郭龙, 张海涛. 基于环境变量的中国土壤有机碳空间分布特征[J]. 土壤学报, 2020, 57(1):48-59.

    Google Scholar

    [54] Luo M, Guo L, Zhang H T, et al. Characterization of spatial distribution of soil organic carbon in China[J]. Acta Pedologica Sinica, 2020, 57(1):48-59.

    Google Scholar

    [55] Anderson D W, Paul E A. Organo-mineral complexes and their study by radiocarbon dating[J]. Journal of the Soil Science Society of America, 1984, 48(2):298-301.

    Google Scholar

    [56] 王茹, 张凤荣, 王军艳, 等. 潮土区不同质地土壤的养分动态变化研究[J]. 土壤通报, 2001, 32(6):255-257.

    Google Scholar

    [57] Wang R, Zhang F R, Wang J Y. Temporal changing of plant nutrients in different texture soils in the North China Plain[J]. Chinese Journal of Soil Science, 2001(6):255-257.

    Google Scholar

    [58] Schimel D S, Braswell B H, Holland E A, et al. Climatic,edaphic,and biotic controls over storage and turnover of carbon in soils[J]. Global Biogeochemical Cycles, 1994, 8(3):279-294.

    Google Scholar

    [59] 张秀芝, 赵相雷, 李波, 等. 基于区域土壤元素地球化学的河北平原土壤质地类型划分[J]. 第四纪地质研究, 2017, 37(1):25-35.

    Google Scholar

    [60] Zhang X Z, Zhao X L, Li B, et al. The classifying of soil texture types based on the regional soil geochemical elements in Hebei plain[J]. Quaternary Sciences, 2017, 37(1):25-35.

    Google Scholar

    [61] Hook P B, Burke I C. Biogeochemistry in a shortgrass landscape:Control by topography,soil texture and microclimate[J]. Ecology, 2000, 81(10):2686-2703.

    Google Scholar

    [62] Parton W J, Schimel D S, Cole C V O N, et al. Analysis of factors controlling soil organic matter levels in great plains grasslands[J]. Soil Science society of america journal, 1987, 51(5):1173-1179.

    Google Scholar

    [63] 刘驰, 刘希瑶, 刘澎. 松辽平原典型黑土区有机质的变化及影响因素分析[J]. 地质与资源, 2020, 29(6):550-555.

    Google Scholar

    [64] Liu C, Liu X Y, Liu P. Analysis on the changes of organic matters and their influencing factors of typical black soil areas in Songliao plain[J]. Geology and Resources, 2020, 29(6):550-555.

    Google Scholar

    [65] Bell M J, Worrall F. Estimating a region's SOC baseline:The undervalued role of land-management[J]. Geoderma, 2009, 152(1-2):74-84.

    Google Scholar

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