2023 Vol. 42, No. 2-3
Article Contents

AN Yonglon, YIN Xiulan, JIN Aifang, LI Wenjuan, LU Qingyuan. 2023. Ecological stoichiometry and spatial variation characteristics of soil nutrients in a cultivation area of Zhangjiakou City, Hebei Province. Geological Bulletin of China, 42(2-3): 443-459. doi: 10.12097/j.issn.1671-2552.2023.2-3.021
Citation: AN Yonglon, YIN Xiulan, JIN Aifang, LI Wenjuan, LU Qingyuan. 2023. Ecological stoichiometry and spatial variation characteristics of soil nutrients in a cultivation area of Zhangjiakou City, Hebei Province. Geological Bulletin of China, 42(2-3): 443-459. doi: 10.12097/j.issn.1671-2552.2023.2-3.021

Ecological stoichiometry and spatial variation characteristics of soil nutrients in a cultivation area of Zhangjiakou City, Hebei Province

More Information
  • By applying geostatistics, ecological chemometrics and GIS techniques, the characteristics of the content, trend distribution, spatial variability and distribution of biogenic elements of N, P, K2O, CaO, MgO, S, Mo, Mn, Fe2O3, B, Corg, pH and other parameters in the surface soil of a planting area in Wanquan District, Zhangjiakou City, Hebei Province were studied.The results showed that Corg belonged to the strongly differentiated variation type with a coefficient of variation of 71.54%, while the rest of the elements belonged to the weak or uniform differentiation type.N, P, K2O and pH were in the very abundant and abundant classes, while S, Mo, Mn, Fe2O3, B and Corg were in the deficient and extremely deficient classes.By comparing the errors in different trend orders superimposed on the block gold coefficient analysis, it was tentatively determined that the study area could be classified into three prediction types, namely, no trend prediction, first-order trend prediction and second-order trend prediction, with K2O, CaO, MgO, S, Mn and Corg mainly influenced by the structural type, and N, P, Mo, Fe2O3, B and pH mainly influenced by a mixture of structural and stochastic properties, among which S and Mo variance functions surface with weak directionality.Ecological chemometrics showed that the average content of biogenic elements K2O > Corg > N > P > S.Soil CNR and NPR were mainly controlled by soil Corg and N, and the vertical direction showed a predominantly epistatic and smooth distribution, supplemented by mutational and sawtooth distribution.Finally, ordinary kriging interpolation clearly shows that N, P, K2O, CaO, MgO, and Mn all show obvious anomalous areas in the watershed range from northeast to southwest, mainly controlled by river migration and transport, with N and P in the key area being of the trapezoidal type, K2O, CaO, and pH of the inner concave type, S and Mo of the outer convex type, and MgO, Fe2O3, Mn, B, and Corg belong to the jump type.

  • 加载中
  • [1] An Y L, Huang Y, Yin Z Q, et al. Spatial distribution patterns and sources for potential toxic elements in soil in the Daxing District, Beijing, China[J]. Arabian Journal of Geosciences, 2022, 15(8) : 1-21.

    Google Scholar

    [2] Bekele A, Hudnall W H. Spatial variability of soil chemical properties of a prairie-forest transition in Louisiana[J]. Plant and Soil, 2006, 280: 7-21. doi: 10.1007/s11104-005-4983-4

    CrossRef Google Scholar

    [3] Burgess T M, Webster R. Optimal interpolation and isarithmic mapping of soil properties: Ⅱ. BlockKriging[J]. Journal of Soil Science, 1980, 31: 333-341. doi: 10.1111/j.1365-2389.1980.tb02085.x

    CrossRef Google Scholar

    [4] Cambardella C A, Moorman T B, Novak J M, et al. Field-scale variability of soil properties in Central IOWA soils[J]. Soil Sci. Soc. Am. J., 1994, 58: 1501-1511. doi: 10.2136/sssaj1994.03615995005800050033x

    CrossRef Google Scholar

    [5] Cleveland C C, Liptzin D. C: N: P stoichiometry in soil: is there a "Redfield ratio" for the microbial biomass[J]. Biogeochemistry, 2007, 85(3) : 235-252. doi: 10.1007/s10533-007-9132-0

    CrossRef Google Scholar

    [6] Cole C V. Mechanisms of phosphate adsorption by calciumcarbonate[J]. Soil. Sci. Soc. Amer. Proc., 1953, 17: 352-35. doi: 10.2136/sssaj1953.03615995001700040013x

    CrossRef Google Scholar

    [7] Dayani M, Mohammadi J. Geostatistical assessment of Pb, Zn and Cd contamination in near-surface; soils of the urban-mining transitional region of Isfahan, Iran[J]. Pedosphere, 2010, 20(5) : 568-577. doi: 10.1016/S1002-0160(10)60046-X

    CrossRef Google Scholar

    [8] Deluigne J, Bisdom E, Sleeman J, et al. Olivines, their pseudomorphs and secondary products[J]. Pedologie, 1979, 29(3) : 247-300.

    Google Scholar

    [9] Elser J J, Acquisti C, Kumar S. Stoichiogenomics: theevolutionary ecology of macromolecular elemental composition [J]. Trends in Ecology & Evolution, 2011, 26(1) : 38-44.

    Google Scholar

    [10] Elser J J, Fagan W F, Kerkhoff A J, et al. Biological stoichiometry of plant production: metabolism, scaling and ecological response to global change[J]. New Phytologist, 2010, 186(3) : 593-608. doi: 10.1111/j.1469-8137.2010.03214.x

    CrossRef Google Scholar

    [11] Facchinelli A, Sacchi E, Mallen L. Multivariate statistical and GIS-based approach to identify heavymetal sources in soils[J]. Environmental Pollution, 2001, 114(3) : 313-324. doi: 10.1016/S0269-7491(00)00243-8

    CrossRef Google Scholar

    [12] Huang B, Sun W, Zhao Y, et al. Temporal and spatial variability of soil organic matter and total nitrogen in an agricultural ecosystem as affected by farming practices[J]. Geoderma, 2007, 139(3/4) : 336-345.

    Google Scholar

    [13] Jordan T E, Cornwell J C, Boynton W R, et al. Changes in phosphorus biogcochemistry along an estuarine salinity gradient: The iron conveyer belt[J]. Limnology and Oceanography, 2008, 53(1) : 172-184. doi: 10.4319/lo.2008.53.1.0172

    CrossRef Google Scholar

    [14] LiuR, Wang M, Chen W P, et al. Spatial pattern of heavy metals accumulation risk in urban soils of Beijing and its influencing factors[J]. Environmental Pollution, 2016, 210: 174-181. doi: 10.1016/j.envpol.2015.11.044

    CrossRef Google Scholar

    [15] Negrin V L, Spetter C V, Asteasuain R O, et al, Influence of flooding and vegetation oncarbon, nitrogen, and phosphorus dynamics in the pore water of a Spartina alterniflora salt marsh[J]. Journal of Environmental Sciences, 2011, 23(2) : 212-221. doi: 10.1016/S1001-0742(10)60395-6

    CrossRef Google Scholar

    [16] Oliver M A, Webster R. Kriging: a method of interpolation for geographical informationsystems[J]. Int. J. Geogr. Inf. Syst., 1990, 4: 313-332. doi: 10.1080/02693799008941549

    CrossRef Google Scholar

    [17] Sah R N, Mikkelsen D S. Effects of anaerobic decomposition of organic matter on sorption and transformations of phosphate in drained soils: Ⅰ[J]. Effects on Phosphate Sorption Soil Science, 1986, 142(5) : 267-274.

    Google Scholar

    [18] Sardans J, Rivasubach A, Penuelas J. The C: N: P stoichiometry of organisms and ecosystems in a changing world: A review and perspectives[J]. Perspectives in Plant Ecology Evolution & Systematics, 2012, 14(1) : 33-47.

    Google Scholar

    [19] Zhang Z M, Zhou Y C, Huang X F, et al. Applicability of GIS-based spatial interpolation and simulation for estimating the soil organic carbon storage in karst regions[J]. Global Ecology and Conservation, 2020, 21: e00849. doi: 10.1016/j.gecco.2019.e00849

    CrossRef Google Scholar

    [20] 安永龙, 杜子图, 黄勇. 基于地统计学和GIS技术的北京市大兴区礼贤镇土壤养分空间变异性研究[J]. 现代地质, 2018, 32(6) : 1311-1321. doi: 10.19657/j.geoscience.1000-8527.2018.06.19

    CrossRef Google Scholar

    [21] 安永龙, 万利勤, 李霞, 等. 承德市土壤重金属空间结构与分布特征[J]. 水文地质工程地质, 2020, 47(6) : 119-131.

    Google Scholar

    [22] 常妮. 汉诺坝碱性玄武岩巨量地幔岩石堆积机制研究[D]. 中国地质大学(北京) 硕士学位论文, 2020.

    Google Scholar

    [23] 陈绪钰, 王东辉, 倪化勇, 等. 长江经济带上游地区丘陵城市工程建设适宜性评价——以泸州市规划中心城区为例[J]. 吉林大学学报(地球科学版), 2020, 50(1) : 194-207. doi: 10.13278/j.cnki.jjuese.20180303

    CrossRef Google Scholar

    [24] 董正武, 玉米提· 哈力克, 李生宇, 等. 古尔班通古特沙漠西南缘柽柳沙包的土壤化学计量特征[J]. 生态学报, 2020, 40(20) : 7389-7400.

    Google Scholar

    [25] 付海曼, 贾黎明. 土壤对氮、磷吸附/解吸附特性研究进展[J]. 中国农学通报, 2009, 25(21) : 198-203.

    Google Scholar

    [26] 贾恒义. 黄土高原主要土壤成壤过程与矿物元素再分配[J]. 水土保持研究, 1995, (4) : 56-60, 68.

    Google Scholar

    [27] 姜华, 唐晓华, 杨利亚, 等. 基于土地资源的市县级多要素国土空间开发适宜性评价研究——以湖北省宜昌市为例[J]. 中国地质, 2020, 47(6) : 1776-1792.

    Google Scholar

    [28] 李启权, 岳天祥, 范泽孟, 等. 中国表层土壤有机质空间分布模拟分析方法研究[J]. 自然资源学报, 2010, 25(8) : 1385-1399.

    Google Scholar

    [29] 林燕, 白秀佳, 叶泽宇, 等. 基于ArcGIS的南通市农业生产适宜性评价[J]. 地质通报, 2021, 40(6) : 968-977.

    Google Scholar

    [30] 刘雪松, 刘金巍, 魏建朋, 等. 赣江梅江河河流作用对土壤元素分配的影响[J]. 人民长江, 2019, 50(10) : 69-72, 76.

    Google Scholar

    [31] 刘永生, 杨楠, 王轶, 等. 保定—沧州地区基于空间自相关分析的土壤区域监测点网络密度研究[J]. 水文地质工程地质, 2012, 39(5) : 126-131.

    Google Scholar

    [32] 刘源, 李晓晶, 段玉玺, 等. 库布齐沙漠东部植被恢复对土壤生态化学计量的影响[J]. 干旱区研究, 2022, 39(3) : 924-932.

    Google Scholar

    [33] 卢建男, 刘凯军, 王瑞雄, 等. 中国荒漠植物-土壤系统生态化学计量学研究进展[J]. 中国沙漠, 2022, 42(2) : 173-182.

    Google Scholar

    [34] 罗艳, 贡璐, 朱美玲, 等. 塔里木河上游荒漠区4种灌木植物叶片与土壤生态化学计量特征[J]. 生态学报, 2017, 37(24) : 8326-8335.

    Google Scholar

    [35] 骆珊, 张德明, 卢定彪, 等. 乌蒙山区毕节市耕地土壤微量元素丰缺评价及其影响因素[J]. 地质通报, 2021, 40(9) : 1570-1583.

    Google Scholar

    [36] 秦王念, 颜雄, 李文昭, 等. 基于CNKI数据库的生态化学计量文献计量分析[J]. 现代农业科技, 2021, (24) : 228-230.

    Google Scholar

    [37] 曲林雨. 汉诺坝玄武岩结构和化学特征多样性的联系[D]. 中国地质大学(北京) 硕士学位论文, 2020.

    Google Scholar

    [38] 石建省, 马荣, 马震. 区域地球多圈层交互带调查探索研究[J]. 地球学报, 2019, 40(6) : 767-780.

    Google Scholar

    [39] 孙厚云, 卫晓锋, 贾凤超, 等. 冀北承德地区土壤生源要素生态化学计量与空间分异特征[J]. 生态学报, 2022, 42(5) : 1750-1765.

    Google Scholar

    [40] 孙厚云, 卫晓锋, 张晓敏, 等. 河北承德中部伊逊河红旗地区土壤生源要素空间分布格局及其影响因素[J]. 矿产勘查, 2021, 12(4) : 1008-1018.

    Google Scholar

    [41] 田静, 盛茂银, 汪攀, 等. 西南喀斯特土地利用变化对植物凋落物-土壤C、N、P化学计量特征和土壤酶活性的影响[J]. 环境科学, 2019, 40(9) : 4278-4286.

    Google Scholar

    [42] 汪璇, 王成秋, 唐将, 等. 基于地统计学和GIS的三峡库区土壤微量营养元素空间变异性研究[J]. 土壤通报, 2009, 40(2) : 359-365.

    Google Scholar

    [43] 王学求, 周建, 徐善法, 等. 全国地球化学基准网建立与土壤地球化学基准值特征[J]. 中国地质, 2016, 43(5) : 1469-1480.

    Google Scholar

    [44] 卫晓锋, 孙厚云, 张竞, 等. 承德特色林果资源的生态地球化学过程及其品质提升意义[J]. 水文地质工程地质, 2020, 47(6) : 99-108.

    Google Scholar

    [45] 魏卓群, 白军红, 张玲, 等. 黄河口潮间带芦苇湿地土壤生源要素的时空动态变化特征[J]. 北京师范大学学报(自然科学版), 2021, 57(1) : 43-50.

    Google Scholar

    [46] 吴美玲, 田晋文. 基于GIS和地统计学的黔西北农业园区土壤养分空间变异特征研究[J]. 中国农学通报, 2019, 35(17) : 48-53.

    Google Scholar

    [47] 吴云霞, 蔡奎, 吕凤军, 等. 冀西北农牧交错带表层土壤营养元素特征研究——以河北省康保县为例[J]. 干旱区资源与环境, 2019, 33(1) : 84-89.

    Google Scholar

    [48] 奚小环. 自然资源时期: 大数据与地球系统科学——再论全面发展时期的勘查地球化学[J]. 物探与化探, 2019, 43(3) : 449-460.

    Google Scholar

    [49] 夏汉平, 高子勤. 磷酸盐在白浆土中的吸附与解吸特性[J]. 土壤通报, 1992, 23: 283-287.

    Google Scholar

    [50] 熊杏, 熊清华, 郭熙, 等. 南方典型丘陵区耕地土壤全氮、有机碳和碳氮比空间变异特征及其影响因素[J]. 植物营养与肥料学报, 2020, 26(9) : 1656-1668.

    Google Scholar

    [51] 杨社锋, 方维萱, 胡瑞忠, 等. 老挝南部波罗芬高原玄武岩砖红壤风化壳微量元素地球化学特征[J]. 矿产与地质, 2005, (6) : 723-727.

    Google Scholar

    [52] 杨之江, 陈效民, 景峰, 等. 基于GIS和地统计学的稻田土壤养分与重金属空间变异[J]. 应用生态学报, 2018, 29(6) : 1893-1901.

    Google Scholar

    [53] 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

    [54] 中国环境监测总站. 中国土壤元素背景[M]. 北京: 中国环境科学出版社, 1990: 1-501.

    Google Scholar

    [55] 中华人民共和国国资源部. 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.

    Google Scholar

    [56] 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∶250000) [S]. 北京: 地质出版社, 2014.

    Google Scholar

    [57] 朱礼学. 土壤pH值及CaCO3在多目标地球化学调查中的研究意义[J]. 四川地质学报, 2001, (4) : 226-228.

    Google Scholar

    [58] 朱秋莲, 邢肖毅, 张宏, 等. 黄土丘陵沟壑区不同植被区土壤生态化学计量特征[J]. 生态学报, 2013, 33(15) : 4674-4682.

    Google Scholar

  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(10)

Tables(4)

Article Metrics

Article views(1728) PDF downloads(94) Cited by(0)

Access History

Other Articles By Authors

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint