Please wait a minute...
E-mail Alert Rss
 
物探与化探  2022, Vol. 46 Issue (4): 1011-1020    DOI: 10.11720/wtyht.2022.1404
  生态地质调查 本期目录 | 过刊浏览 | 高级检索 |
半干旱区有机质与全氮空间变异的尺度效应特征——以延安市为例
王鹏1(), 赵君1(), 刘拓1, 周一凡2, 魏锦萍1, 王磊1
1.中国地质调查局 西安地质调查中心西北地质科技创新中心,陕西 西安 710054
2.西安市勘察测绘院,陕西 西安 710059
Scale effects of spatial variations in SOM and STN in semi-arid regions: A case study of Yan'an
WANG Peng1(), ZHAO Jun1(), LIU Tuo1, ZHOU Yi-Fan2, WEI Jin-Ping1, WANG Lei1
1. Xi'an Center of China Geological Survey Northwest China Center for Geoscience Innovation,Xi'an 710054,China
2. Xi'an Institute of Prespecting and Mapping,Xi'an 710059,China
全文: PDF(5421 KB)   HTML
输出: BibTeX | EndNote (RIS)      
摘要 

以高密度采样数据为数据集,经重采样分析,模拟不同尺度的采样空间分布场景,采用莫兰指数、半方差函数值和分形维数 F D等空间分析方法,探讨土壤有机质和全氮空间变异的尺度效应特征,并分析其影响因素的尺度间转换关系。结果表明:随着尺度增大,空间集聚性降低,有机质和全氮含量空间总变异先增大后趋于稳定,但随机性变异逐渐减少,结构性变异先增大后减少。小尺度产生的空间变异中的随机变异占比较多,结构变异占比较少,而大尺度则相反。不同的影响因素对有机质和全氮空间变异具有不同的区分度,高程的区分度最小;土壤类型、植被指数、年均气温、湿度等影响因素的区分度次之;降水量的区分度最大。有机质和全氮空间变异影响因素具有尺度特征,随着尺度增大,小尺度因素引起的随机变异逐渐减少,而大尺度因素引起的结构性变异先增大后减弱,直至转换为相对的小尺度因素;各影响因素对土壤有机质和全氮含量的影响协同机制在尺度间差异较大,引起随机变异和结构变异出现尺度间消长,导致空间变异呈现出先减少后趋于平稳的变化规律。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
王鹏
赵君
刘拓
周一凡
魏锦萍
王磊
关键词 采样尺度空间变异分形维数半方差函数有机质全氮半干旱区    
Abstract

Taking high-density sampling data as a dataset, the sampling spatial distribution scenarios on different scales were simulated through resampling analysis. Spatial analysis methods, such as Moran's I index, semi-variance function value, and fractal dimension FD, were used to explore the scale effects of spatial variations in soil organic matter (SOM) and soil total nitrogen (STN) and to analyze the conversion of influencing factors between different scales. The results are as follows. With an increase in scale, the spatial agglomeration decreased, and the spatial variation of SOM and STN in general increased first and then tended to be stable. By contrast, the random variation decreased gradually and the structural variation increased first and then decreased as the scales increased. The spatial variation generated on small scales consisted of a large proportion of random variation and a small proportion of structural variation, while the opposite is true on large scales. Different influencing factors had different distinguishing degrees for the spatial variations in SOM and STN. Their distinguishing degrees were in the order of height<factors such as soil type, vegetation index, annual average temperature, and humidity<precipitation. The influencing factors of the spatial variations in SOM and STN had scale effects. Specifically, with an increase in scale, the random variation caused by small-scale factors decreased gradually, while the structural variation caused by large-scale factors increased first and then weakened until the large-scale factors were transformed into relatively small-scale factors. The coordination mechanism of the effects of each factor on the SOM and STN contents was quite different between different scales, causing the random and structural variations to fluctuate between different scales. As a result, the spatial variations showed the law of decreasing first and then tending to stabilize.

Key wordssampling scale    spatial variation    fractal dimension    semi-variance function    SOM    STN    semi-arid regions
收稿日期: 2021-07-20      修回日期: 2021-09-29      出版日期: 2022-08-20
ZTFLH:  P632  
基金资助:中国地质调查局基础地质调查项目“西北地区自然资源动态监测与风险评估”(DD20211393);“新疆耕地区土地质量地球化学调查”(DD20190521)
通讯作者: 赵君
作者简介: 王鹏(1986-),男,河南杞县人,高级工程师,主要从事土地质量地球化学调查方面的研究工作。Email: 331559202@qq.com
引用本文:   
王鹏, 赵君, 刘拓, 周一凡, 魏锦萍, 王磊. 半干旱区有机质与全氮空间变异的尺度效应特征——以延安市为例[J]. 物探与化探, 2022, 46(4): 1011-1020.
WANG Peng, ZHAO Jun, LIU Tuo, ZHOU Yi-Fan, WEI Jin-Ping, WANG Lei. Scale effects of spatial variations in SOM and STN in semi-arid regions: A case study of Yan'an. Geophysical and Geochemical Exploration, 2022, 46(4): 1011-1020.
链接本文:  
https://www.wutanyuhuatan.com/CN/10.11720/wtyht.2022.1404      或      https://www.wutanyuhuatan.com/CN/Y2022/V46/I4/1011
Fig.1  研究区域位置
尺度 S-0 S-1 S-2 S-3 S-4 S-5 S-6 S-7 S-8 S-9 S-10
指定距离/m 500 1000 1500 2000 2500 3000 3500 4000 4500 5000
样点数 8462 8037 4062 2301 1463 936 666 486 380 302 249
Table 1  重采样后不同间距尺度对应关系
Fig.2  不同尺度采样分布
Fig.3  不同采样尺度均值(a)、变异系数(b)与尺度的散点分布
Fig.4  不同采样尺度Moran’s I指数与尺度的散点分布
指标 采样距离/m 方向/(°) 拟合模型 C0 C0+C [C0/(C0+C)]/%
有机质 0 0 G 0.0368 0.1286 0.2862
45 G 0.0366 0.1287 0.2845
90 G 0.0368 0.1287 0.2859
135 G 0.0365 0.1286 0.2839
5000 0 G 0.0254 0.1178 0.2156
45 G 0.0253 0.1177 0.2149
90 G 0.0255 0.1178 0.2164
135 G 0.0256 0.1183 0.2164
全氮 0 0 G 0.0197 0.0698 0.2822
45 G 0.0196 0.0696 0.2816
90 G 0.0198 0.0698 0.2837
135 G 0.0199 0.0699 0.2847
5000 0 G 0.0125 0.0768 0.1628
45 G 0.0126 0.0769 0.1640
90 G 0.0126 0.0769 0.1642
135 G 0.0126 0.0769 0.1633
Table 2  有机质和全氮半方差结构异质性分析
项目 采样
距离/m
拟合
模型
C0 C0+C [C0/(C0+
C)]/%
变程/m 决定
系数R2
残差
RSS
分形
维数FD
有机质 0 G 0.0337 0.1114 30.25 45400 0.975 1.52×10-4 1.759
500 G 0.0338 0.1116 30.29 45000 0.977 1.18×10-3 1.758
1000 G 0.0321 0.1242 25.85 46900 0.981 1.49×10-4 1.730
1500 G 0.0301 0.1362 22.10 49400 0.985 1.49×10-4 1.705
2000 G 0.0277 0.1314 21.08 47500 0.986 1.42×10-4 1.690
2500 G 0.0271 0.1342 20.19 47700 0.987 1.32×10-4 1.676
3000 G 0.025 0.1250 20.00 47200 0.985 1.38×10-4 1.673
3500 G 0.026 0.1410 18.44 50300 0.991 9.64×10-5 1.669
4000 G 0.0218 0.1106 19.71 44400 0.988 9.80×10-5 1.649
4500 G 0.0236 0.1112 21.22 46000 0.992 6.39×10-5 1.677
5000 G 0.0254 0.1178 21.56 49900 0.989 8.25×10-5 1.660
全氮 0 G 0.0197 0.0698 28.22 46100 0.98 4.64×10-5 1.747
500 G 0.0196 0.0701 27.96 45800 0.982 4.44×10-5 1.744
1000 G 0.019 0.0767 24.77 46200 0.985 4.66×10-5 1.721
1500 G 0.0175 0.0825 21.21 48400 0.994 9.30×10-5 1.694
2000 G 0.0164 0.0800 20.50 45900 0.986 8.36×10-5 1.683
2500 G 0.0157 0.0832 18.87 47000 0.990 4.34×10-5 1.660
3000 G 0.0141 0.0775 18.19 47100 0.989 4.10×10-5 1.653
3500 G 0.0146 0.0877 16.65 48900 0.991 1.46×10-5 1.637
4000 G 0.0121 0.0726 16.67 44700 0.992 2.79×10-5 1.620
4500 G 0.0137 0.0738 18.56 47100 0.992 2.56×10-5 1.650
5000 G 0.0125 0.0768 16.28 50900 0.990 3.38×10-5 1.623
Table 3  不同尺度有机质和全氮的半方差函数及分形维数
Fig.5  不同采样尺度下有机质和全氮的块基比(a)、分形维数(b)散点分布
Fig.6  有机质和全氮的含量在S-0、S-5、S-10尺度的空间分布
Fig.7  各影响因素对有机质和全氮含量的区分度
影响因素 指标 S-0 S-1 S-2 S-3 S-4 S-5 S-6 S-7 S-8 S-9 S-10
土壤类型 有机质 13/21 12/21 10/21 9/21 5/21 3/21 1/21 0/21 0/21 0/21 0/21
全氮 8/21 8/21 7/21 6/21 5/21 2/21* 2/21 0/21* 0/21 0/21 0/21
植被指数 有机质 6/6** 6/6** 6/6*** 5/6*** 5/6*** 4/6*** 4/6*** 4/6*** 3/6*** 3/6*** 3/6***
全氮 5/6** 5/6** 5/6** 5/6** 5/6*** 5/6*** 5/6*** 5/6*** 3/6*** 4/6*** 3/6***
年均气温 有机质 5/6 5/6 5/6 4/6 4/6 3/6 2/6 3/6 1/6 1/6 1/6
全氮 3/6 3/6 3/6 2/6 3/6 2/6 0/6 0/6 0/6 0/6 0/6
降水量 有机质 6/6** 6/6** 6/6** 6/6** 5/6** 5/6** 5/6*** 5/6** 4/6*** 4/6*** 4/6***
全氮 6/6** 6/6** 6/6** 6/6** 6/6** 5/6** 5/6** 4/6*** 4/6** 4/6** 3/6***
湿度 有机质 6/6** 6/6** 6/6** 6/6** 6/6** 6/6** 5/6** 5/6** 5/6** 4/6** 4/6**
全氮 6/6** 6/6** 6/6** 6/6** 6/6** 5/6** 5/6** 4/6** 5/6** 4/6** 4/6**
海拔 有机质 6/6 6/6 6/6 4/6 4/6 3/6 3/6 2/6 2/6 2/6 1/6
全氮 5/6 5/6 3/6 3/6 2/6 2/6 1/6 1/6 0/6 1/6 0/6
Table 4  不同尺度间的SOM、STN在不同影响因素下的显著性差异统计
[1] 齐雁冰, 常庆瑞, 刘梦云, 等. 县域农田土壤养分空间变异及合理样点数确定[J]. 土壤通报, 2014, 45(3):556-561.
[1] Qi Y B, Chang Q R, Liu M Y, et al. County-scale spatial variability of soil nutrient distribution and determination of reasonable sampling density[J]. Chinese Journal of Soil Science, 2014, 45(3):556-561.
[2] 张法升, 刘作新. 分形理论及其在土壤空间变异研究中的应用[J]. 应用生态学报, 2011, 22(5):1351-1358.
[2] Zhang F S, Liu Z X. Fractal theory and its application in the analysis of soil spatial variability:A review[J]. Chinese Journal of Applied Ecology, 2011, 22(5): 1351-1358.
[3] Heuvelink GBM, Webster R. Modelling soil variation:Past, present and future[J]. Geoderma, 2001, 100: 269-301.
doi: 10.1016/S0016-7061(01)00025-8
[4] Jenny H. Factors of soil formation:A system of quantitative pedology[M]. New York: Dover Publications, 1994.
[5] 姜秋香, 付强, 王子龙. 空间变异理论在土壤特性分析中的应用研究进展[J]. 水土保持研究, 2007, 14(4): 413-415.
[5] Jiang Q X, Fu Q, Wang Z L. Research progress of the spatial variability theory in application to soil characteristic analysis[J]. Research of Soil and Water Conservation, 2007, 14(4): 413-415.
[6] 霍霄妮, 李红, 张微微, 等. 北京耕作土壤重金属多尺度空间结构[J]. 农业工程学报, 2009, 25(3):223-229.
[6] Huo X N, Li H, Zhang W W, et al. Multi-S spatial structure of heavy metals in Beijing cultivated soils[J]. Transactions of the CSAE, 2009, 25(3): 223-229.
[7] 潘瑜春, 刘巧芹, 阎波杰, 等. 采样尺度对土壤养分空间变异分析的影响[J]. 土壤通报, 2010, 41(2):257-262.
[7] Pan Y C, Liu Q Q, Yan B J, et al. Effects of sampling S on soil nutrition spatial variability analysis[J]. Chinese Journal of Soil Science, 2010, 41(2): 257-262.
[8] 雷咏雯, 危常州, 李俊华, 等. 不同尺度下土壤养分空间变异特征的研究[J]. 土壤, 2004, 36(4):376-381.
[8] Lei Y W, Wei C Z, Li J H, et al. Characters of soil nutrient spatial variability in different S[J]. Soil, 2004, 36(4): 376-381.
[9] 刘伟, 郜允兵, 周艳兵, 等. 农田土壤重金属空间变异多尺度分析——以北京顺义土壤Cd为例[J]. 农业环境科学学报, 2019, 38(1):87-94.
[9] Liu W, Gao Y B, Zhou Y B, et al. Multi-S analysis of spatial variability of heavy metals in farmland soils: Case study of soil Cd in Shunyi District of Beijing,China[J]. Journal of Agro-Environment Science, 2019, 38(1): 87-94.
[10] 郑袁明, 陈煌, 陈同斌, 等. 北京市土壤中Cr、Ni含量的空间结构与分布特征[J]. 第四纪研究, 2003, 23(4):436-445.
[10] Zheng Y M, Chen H, Chen T B, et al. Spatialdistribution patterns of Cr and Ni in soils of beijing[J]. Quaternary Sciences, 2003, 23(4): 436-445.
[11] 陈涛, 常庆瑞, 刘钊, 等. 耕地土壤有机质与全氮空间变异性对粒度的响应研究[J]. 农业机械学报, 2013, 44(10):122-129.
[11] Chen T, Chang Q R, Liu Z, et al. Spatial variablility response of farmland soil organic matter and total nitrogen to sampling grain size[J]. Transactions of the Chinese Society for Agricultural Machinery, 2013, 44(10):122-129.
[12] 王鹏, 刘拓, 邱德明. 基于局部惩罚型变权的建设用地生态适宜性空间模糊评价——以陕西延安宝塔区为例[J]. 西北地质, 2021, 54(1):232-241.
[12] Wang P, Liu T, Qiu D M. Spatial fuzzy assessment of ecological suitability for urban land based on local penalty variable weights:A case study of Baota district[J]. Northwestern Geogloy, 2021, 54(1):232-241.
[13] 杨奇勇, 杨劲松, 刘广明. 土壤速效养分空间变异的尺度效应[J]. 应用生态学报, 2011, 22(2):431-436.
[13] Yang Q Y, Yang J S, Liu G M. S-dependency of spatial variability of soil available nutrients[J]. Chinese Journal of Applied Ecology, 2011, 22(2): 431-436.
[14] Antonio P M. Spatial variability patterns of phosphorus and potassium in no-tilled soils for two sampling scales[J]. Soil Science Society of America Journal, 1996, 60(5): 1473-1481.
doi: 10.2136/sssaj1996.03615995006000050027x
[15] 李小昱, 雷廷武, 王为. 农田土壤特性的空间变异性及分形特征[J]. 干旱地区农业研究, 2000, 18(4): 61-65.
[15] Li X Y, Lei T W, Wang W. Spatial variablelity and fractal dimension of soil property in field[J]. Agricultural Research in the Arid Areas, 2000, 18(4): 61-65.
[16] 沈思源. 土壤空间变异研究中地统计学的应用及其展望[J]. 土壤学进展, 1989, 17(3):11-25.
[16] Shen S Y. Application and prospect of geostatistics in soil spatial variability research[J]. Advances in Soil Science, 1989, 17(3): 11-25.
[17] 盛建东, 肖华, 武红旗, 等. 不同取样间距农田土壤全量养分空间变异特征研究[J]. 土壤通报, 2006, 37(6):1062-1065.
[17] Sheng J D, Xiao H, Wu H Q, et al. Spatial variability of total nutrients in arable soil as affected by different sampling distances[J]. Chinese Journal of Soil Science, 2006, 37(6) : 1062-1065.
[18] 李雅琦, 田均良, 刘普灵. 黄土高原土壤元素含量地域分异规律[J]. 西北农业学报, 2000, 9(3):63-66.
[18] Li Y Q, Tian J L, Liu P L. A Study on laws of regional variance of soil element in loess plateau through trend surface analysis method[J]. Acta Agriculturae Boreali-occidentalis Sinica, 2000, 9(3):63-66.
[19] 王鹏, 段星星, 赵禹, 等. 治沟造地新增耕地的土壤质量评价——延安宝塔区为例[J]. 土地开发工程研究, 2019, 4(1):41-45.
[19] Wang P, Duan X X, Zhao Y, et al. The evaluation of soil nutrient status in newly reclaimed land from trench construction:Taking Baota district of Yan'an city as example[J]. Land Development and Engineering Research, 2019, 4(1):41-45.
[20] 陈云坪, 王秀, 马伟, 等. 小麦多年产量空间变异与空间关联分析[J]. 农业机械学报, 2010, 41(10):180-184.
[20] Chen Y P, Wang X, Ma W, et al. Spatial autocorrelation analysis of wheat yield over five years[J]. Transactions of the Chinese Society for Agricultural Machinery, 2010, 41(10): 180-184.
[21] Burrough P A. Multiscale sources of spatial variation in soil. I. The application of fractal concepts to nested levelsof soil variation[J]. European Journal of Soil Science, 1983, 34: 577-597.
[22] 张忠启. 采样点布设与区域土壤有机碳变异性研究[M]. 北京: 科学出版社, 2019:110-128.
[22] Zhang Z Q. Sampling site arrangement and regional soil organic carbon variability[M]. Beijing: Science Press, 2019:110-128.
[23] Lei G, Shao M A. The interpolation accuracy for seven soil properties at various sampling Ss on the Loess Plateau, China[J]. Journal of Soils and Sediments, 2012, 12(2): 128-142.
doi: 10.1007/s11368-011-0438-0
[24] Daniels, Lee W. The Nature and Properties of Soils, 15th Edition[J]. Soil Science Society of America Journal, 2016, 80(5):1428.
doi: 10.2136/sssaj2016.0005br
[25] 李元年. 基于熵理论的指标体系区分度测算与权重设计[D]. 南京: 南京航空航天大学, 2008.
[25] Li Y N. Evaluation and weight design of index system based on entropy theory[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2008.
[26] 王鹏, 刘拓, 段星星, 等. 基于熵权的土壤养分地球化学多级模糊综合评判——以陕西省关中地区为例[J]. 水土保持通报, 2019, 39(6):136-141.
[26] Wang P, Liu T, Duan X X, et al. Multi-stage fuzzy comprehensive evaluation of soil nutrient geochemistry based on entropy weight:Take Guanzhong region for example[J]. Bulletin of Soil and Water Conservation, 2019, 39(6):136-141.
[27] 金继运, 白山路. 精准农业与土壤养分管理[M]. 北京: 中国大地出版社, 2001:5l-57.
[27] Jin J Y, Bai S L. Precision agriculture and soil nutrient management[M]. Beijing: China Dadi Publishing House, 2001:5l-57.
[28] 王鹏, 刘拓. 延安市宝塔区土壤养分地球化学评价中的变权效果[J]. 物探与化探, 2020, 44(4):847-854.
[28] Wang P, Liu T. Variational weight effect in the geochemical evaluation of soil nutrients in Baota District of Yan'an City[J]. Geophysical and Geochemical Exploration, 2020, 44(4):847-854.
[1] 张一鹤, 杨泽, 戴慧敏, 刘国栋, 韩晓萌, 李秋燕. 穆棱河—兴凯湖平原土壤有机碳、全氮的时空变异特征[J]. 物探与化探, 2022, 46(5): 1050-1055.
[2] 杨泽, 张一鹤, 戴慧敏, 刘国栋, 刘凯, 许江. 兴凯湖平原表层土壤有机碳空间变异的主控因素[J]. 物探与化探, 2022, 46(5): 1076-1086.
[3] 陈超群, 戴慧敏, 冯雨林, 杨泽, 杨佳佳. 基于Sentinel-2A的孙吴地区土壤有机质反演研究[J]. 物探与化探, 2022, 46(5): 1141-1148.
[4] 殷启春, 王元俊, 周道容, 张丽, 孙桐. 复电阻率法在安徽南陵盆地海相页岩气勘探中的应用[J]. 物探与化探, 2022, 46(3): 668-677.
[5] 严明书, 吴春梅, 蒙丽, 丁相伦, 董攀, 邓海, 雷家立, 龚媛媛, 鲍丽然. 重庆市黔江猕猴桃果园土壤养分状况分析[J]. 物探与化探, 2019, 43(5): 1123-1130.
[6] 唐世新, 李建军, 马生明, 胡树起. 运积物覆盖区地球化学找矿方法——土壤热磁组分测量[J]. 物探与化探, 2019, 43(4): 749-757.
[7] 彭敏, 李括, 刘飞, 唐世琪, 马宏宏, 杨柯, 杨峥, 郭飞, 成杭新. 东北平原区地块尺度土地质量地球化学评价合理采样密度研究[J]. 物探与化探, 2019, 43(2): 338-350.
[8] 李春鹏, 隋桂梅, 刘志国, 杨松岭, 闫青华, 尹川. 成熟—过成熟烃源岩有机质类型识别[J]. 物探与化探, 2017, 41(2): 219-223.
[9] 段晓梦, 陈培元, 吕栋, 孔令武, 蒋百召. 增生楔盆地烃源岩特征综合评价——以缅甸某区块为例[J]. 物探与化探, 2016, 40(2): 257-263.
[10] 周印明, 刘雪军, 张春贺, 朱永山. 快速识别页岩气“甜点”目标的时频电磁勘探技术及应用[J]. 物探与化探, 2015, 39(1): 60-63,83.
[11] 李广之, 陈银节, 尹红军, 宣海波. 近地表土壤中可溶态阴离子的石油地质意义[J]. 物探与化探, 2011, 35(2): 198-202.
[12] 宋明义, 周涛发, 蔡子华, 冯雪外, 简中华, 黄春雷. 浙江典型癌症高发区地质环境[J]. 物探与化探, 2010, 34(3): 382-385.
[13] 孔牧, 杨少平. 森林沼泽景观区有机质 对元素表生地球化学特征的影响机制[J]. 物探与化探, 2008, 32(1): 31-32,74.
[14] 白显清, 单久库, 那晓红, 贾宏. 佳木斯隆起带乌拉嘎断裂西缘 1:5万水系沉积物测量方法研究[J]. 物探与化探, 2007, 31(5): 469-472.
[15] 程志中, 王学求, 胡忠贤, 杨兆武. 森林沼泽区富含有机质样品中金的存在形式及对分析的影响[J]. 物探与化探, 2004, 28(3): 206-208.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-3
版权所有 © 2021《物探与化探》编辑部
通讯地址:北京市学院路29号航遥中心 邮编:100083
电话:010-62060192;62060193 E-mail:whtbjb@sina.com