不同采样间距下农田土壤镉含量空间自相关分析的研究

doi:10.16178/j.issn.0528-9017.20221280

摘要/Abstract

摘要：

本文以舟山市定海区某水稻田土壤为研究对象,采用全局空间自相关和局部空间自相关相结合的方法,在仅改变采样间距的基础上,全面探讨40 m、20 m这两种采样间距下农田土壤镉(Cd)的空间自相关特征。结果表明,两种采样间距下均具有明显的尺度效应,短采样间距(20 m)更易于揭示Cd元素的空间分布状况;对于Cd污染农田土壤的安全利用及治理,虽然40 m采样间距能减少前期调查成本,但无法准确识别Cd含量较高值所在的具体位置,增加后期安全利用及治理的不确定性,而20 m采样间距则能够准确地进行异常值识别,有助于对Cd含量较高值所在位置的土壤采取针对性的污染防控措施以及摸排切断污染源头,为Cd污染农田土壤的安全利用及治理提供参考依据。

关键词: 空间自相关, 采样间距, 镉, 尺度效应

Abstract:

Taking a paddy field soil in Dinghai District, Zhoushan City as the research object, the spatial autocorrelation characteristics of cadmium (Cd) in farmland soil under 40 m and 20 m sampling intervals were comprehensively discussed by using the combined method of global spatial autocorrelation and local spatial autocorrelation. The results showed that there was an obvious scale effect at both sampling intervals, and the short sampling interval (20 m) was easier to reveal the spatial distribution of Cd element. For the safe use and treatment of CD-contaminated farmland soil, although the sampling interval of 40 m can reduce the investigation cost in the early stage, the specific location of the higher Cd content could not be accurately identified, which increased the uncertainty of safe use and treatment in the later stage, while the sampling interval of 20 m could accurately identify outliers. It is helpful to take targeted pollution prevention and control measures for the soil with high Cd content and cut off the pollution source, which provides a reference for the safe utilization and treatment of Cd-polluted farmland soil.

Key words: spatial autocorrelation, sampling interval, Cd, scale effect

中图分类号:

陈胤再, 陈柏成, 梅皓天, 夏枫, 柳丹. 不同采样间距下农田土壤镉含量空间自相关分析的研究[J]. 浙江农业科学, 2024, 65(1): 224-229.

CHEN Yinzai, CHEN Baicheng, MEI Haotian, XIA Feng, LIU Dan. Study on spatial autocorrelation analysis of cadmium content in farmland soil at different sampling intervals[J]. Journal of Zhejiang Agricultural Sciences, 2024, 65(1): 224-229.

图/表 5

图1 不同采样间距下采样点位图

Fig.1 Bitmap of sampling points with different sampling spacing

表1 不同置信度下临界Z值和临界P值

Table 1 Critical Z and critical P values at different confidence levels

置信度/%	Z得分(标准差)	P值(概率)
90	<-1.65或>1.65	<0.10
95	<-1.96或>1.96	<0.05
99	<-2.58或>2.58	<0.01

表2 Descriptive statistics of Cd content at different sampling intervals单位:mg·kg-1

Table 2

间距/ m	最大值	最小值	平均值	变异系数/	偏度	峰度
40	0.220	0.020	0.067	74.785	1.721	2.491
20	0.250	0.020	0.063	71.246	2.031	0.653

表3 不同采样间距下Cd含量全局Moran's/指数及其显著性检验

Table 3 Global Moran's/index of Cd content and its significance test at different sampling intervals

间距/m	Moran's I	Z得分	P值	全局分布	全局自相关性
40	-0.106 0	-0.758 4	0.214	空间孤立	不显著空间负相关
20	0.163 6	2.897 5	0.009	空间聚集	显著空间正相关

图2 不同采样间距下Cd含量空间聚类和异常值分析

Fig.2 Spatial clustering and outlier analysis of Cd content at different sampling intervals

参考文献 32

[1]	黄卫, 庄荣浩, 刘辉, 等. 农田土壤镉污染现状与治理方法研究进展[J]. 湖南师范大学自然科学学报, 2022, 45(1): 49-56.
[2]	生态环境部. 2019年全国生态环境质量简况[J]. 环境保护, 2020, 48(10): 8-10.
[3]	LI S, CHEN J R, ISLAM E, et al. Cadmium-induced oxidative stress, response of antioxidants and detection of intracellular cadmium in organs of moso bamboo (Phyllostachys pubescens) seedlings[J]. Chemosphere, 2016, 153: 107-114.
[4]	LI S, ISLAM E, PENG D L, et al. Accumulation and localization of cadmium in moso bamboo (Phyllostachys pubescens) grown hydroponically[J]. Acta Physiologiae Plantarum, 2015, 37(3): 1-7.
[5]	李婧, 周艳文, 陈森, 等. 我国土壤镉污染现状、危害及其治理方法综述[J]. 安徽农学通报, 2015, 21(24): 104-107.
[6]	李湘凌, 张颖慧, 杨善谋, 等. 合肥大兴地区土壤重金属含量的空间分布特征[J]. 土壤通报, 2011, 42(1): 179-184.
[7]	邢旭光, 赵文刚, 柳烨, 等. 猕猴桃果园不同采样密度下土壤含水率空间变异性研究[J]. 农业机械学报, 2015, 46(8): 138-145.
[8]	张少良, 张海军, 肖梓良, 等. 东北典型黑土区农田景观多尺度土壤养分时空分异研究进展[J]. 东北农业大学学报, 2020, 51(7): 86-96.
[9]	SYLLA M, STEIN A, VAN BREEMEN N, et al. Spatial variability of soil salinity at different scales in the mangrove rice agro-ecosystem in West Africa[J]. Agriculture, Ecosystems & Environment, 1995, 54(1/2): 1-15.
[10]	RODRÍGUEZ J A, NANOS N, GRAU J M, et al. Multiscale analysis of heavy metal contents in Spanish agricultural topsoils[J]. Chemosphere, 2008, 70(6): 1085-1096.
[11]	王永东, 冯娜娜, 李廷轩, 等. 不同尺度下低山茶园土壤阳离子交换量空间变异性研究[J]. 中国农业科学, 2007, 40(9): 1980-1988.
[12]	段秋亚. 对GIS中尺度和尺度转换的理解与分析[J]. 四川水泥, 2017(2): 296.
[13]	MALLARINO A P. 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.
[14]	WANG R Y, SHAFI M, MA J W, et al. Effect of amendments on contaminated soil of multiple heavy metals and accumulation of heavy metals in plants[J]. Environmental Science and Pollution Research International, 2018, 25(28): 28695-28704.
[15]	王金云, 李小娜, 吴忠忠. 石墨炉原子吸收光谱法测定土壤中镉[J]. 理化检验-化学分册, 2020, 56(9): 965-969.
[16]	陶吉兴, 傅伟军, 姜培坤, 等. 基于Moran's I和地统计学的浙江森林土壤有机碳空间分布研究[J]. 南京林业大学学报(自然科学版), 2014, 38(5): 97-101.
[17]	戴巍, 赵科理, 高智群, 等. 典型亚热带森林生态系统碳密度及储量空间变异特征[J]. 生态学报, 2017, 37(22): 7528-7538.
[18]	ZHAO K L, ZHANG L Y, DONG J Q, et al. Risk assessment, spatial patterns and source apportionment of soil heavy metals in a typical Chinese hickory plantation region of southeastern China[J]. Geoderma, 2020, 360: 114011.
[19]	李丹丹. 基于GIS与地统计学的不同尺度下土壤重金属空间变异研究: 以湖南石门雄黄矿区为例[D]. 成都: 成都理工大学, 2020.
[20]	杨冕, 王银. 长江经济带PM_2.5时空特征及影响因素研究[J]. 中国人口·资源与环境, 2017, 27(1): 91-100.
[21]	NIELSON D R, BOUMA J J. Soil spatial variability:proceedings of a workshop of the ISSS and the SSSA Las Vegas, USA, 30 November-1 December, 1984[M]. Wageningen, The Netherlands: PUDOC, 1985.
[22]	杜平, 赵欢欢, 王世杰, 等. 大冶市农田土壤中镉的空间分布特征及污染评价[J]. 土壤, 2013, 45(6): 1028-1035.
[23]	王劲峰, 姜成晟, 李连发. 空间抽样与统计推断[M]. 北京: 科学出版社, 2009: 17.
[24]	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.
[25]	黄银华. 广州市农业表层土壤重金属污染及其与景观格局的多尺度关系[D]. 广州: 广州大学, 2015.
[26]	LI X H, ZHAO L, TENG Y, et al. spatial distribution and risk assessment of combined mercury and cadmium pollution in farmland soils surrounding mercury mining areas in Guizhou[J]. Ecology and Environmental Sciences, 2022, 31(8): 1629-1636.
[27]	杨奇勇, 杨劲松, 余世鹏, 等. 不同尺度下耕地土壤Cr含量的空间自相关性分析[J]. 应用与环境生物学报, 2011, 17(3): 393-397.
[28]	王幼奇, 白一茹, 展秀丽. 在不同尺度下宁夏引黄灌区农田土壤养分空间变异分析[J]. 干旱区研究, 2014, 31(2): 209-215.
[29]	王鹏, 赵君, 刘拓, 等. 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): 988-997.
[30]	王小艳, 冯跃华, 李云, 等. 黔中喀斯特山区村域稻田土壤理化特性的空间变异特征及空间自相关性[J]. 生态学报, 2015, 35(9): 2926-2936.
[31]	阙泽胜, 吴星根, 李冠超, 等. 基于GIS的土壤氡浓度空间分布规律探析[J]. 地理信息世界, 2022, 29(4): 42-47.
[32]	沈惠雅, 李晓岚, 潘瑜春, 等. 土壤重金属数据异常识别方法: 以北京农田区样点数据为例[J]. 江苏农业科学, 2021, 49(8): 219-226.