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Distribution and influencing factors of selenium content in soil in karst areas in Mashan County, Guangxi, China |
ZHANG Chun-Lai1( ), YANG Hui1, Huang Fen1, CAO Jian-Hua1,2 |
1. Institute of Karst Geology, Chinese Academy of Geological Sciences Key Laboratory of Karst Dynamics, Ministry of Nature Resources and Science and Guangxi, Guilin 541004, China 2. International Research Center on Karst under the Auspices of UNESCO, Guilin 541004, China |
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Abstract This study aims to investigate the distribution characteristics of the total selenium content in soil in karst areas in Mashan County, Guangxi and to explore the effects of different soil parent materials, land uses, and soil types on the selenium content in soil. To this end, 492 samples of surface soil (0~20 cm) were collected from the northern part of Mashan County and the distribution of the total selenium content in the samples were studied by statistical methods. The results are as follows. The total selenium content in the soil varies from 0.20×10-6 to 3.54×10-6, with an average value of 0.76×10-6. Meanwhile, the selenium-rich area accounts for 98.29% and the coefficient of variation is 34.49%. The soil in the Permian Heshan formation bearing black shales and coal-measure strata has the highest selenium content, with an average of 1.17×10-6, while the Carboniferous Maping formation has the lowest selenium content, with an average of 0.64×10-6. In terms of different soil types, the lateritic red soil has the highest selenium content, with an average value of 1.04×10-6, while the fluvo-aquic soilhas the lowest selenium content, with an average value of 0.56×10-6. In terms of land use types,the forestland and orchard have a high selenium content in soil, while the paddy field, grassland, and arid land have a low selenium content. Therefore, the selenium content in soil in the study area is mainly affected by soil parent materials, with the selenium enrichmentin soil being affected by the organic matter content to a certain extent.
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Received: 30 December 2020
Published: 21 December 2021
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The study location(a) and the main land use types(b)
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模型 | 块金值 | 基台值 | 块金效应 | 变程/km | 拟合系数 | 残差 | 球状模型 | 0.0188 | 0.0727 | 74.10% | 2.37 | 0.981 | 4.63×10-5 | 高斯模型 | 0.0264 | 0.0726 | 63.60% | 1.96 | 0.98 | 4.89×10-5 | 指数模型 | 0.0087 | 0.0733 | 88.10% | 2.46 | 0.968 | 7.81×10-5 | 线性模型 | 0.0515 | 0.0800 | 35.60% | 6.82 | 0.447 | 1.32×10-3 |
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Semi-variogram function model for soil selenium and its corresponding parameters
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Gradingchart of soil Se in study area
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Box diagram of soil selenium content in different types of samples
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样品类型 | 样品数量 | Hg | Mn | K2O | 有机质 | pH | 整体 | 492 | 0.102* | -0.246** | -0.191** | 0.216** | 0.003 | 水田 | 98 | -0.043 | -0.206* | -0.192 | 0.307** | -0.022 | 旱地 | 255 | 0.162** | -0.219** | -0.334** | 0.505** | 0.038 | 果园 | 26 | 0.25 | -0.386 | -0.602** | 0.097 | -0.245 | 有林地 | 62 | 0.325* | -0.237 | -0.389** | 0.054 | 0.075 | 灌木林地 | 43 | -0.045 | -0.466** | -0.320* | -0.017 | 0.07 | 草地 | 8 | 0.051 | -0.175 | -0.509 | 0.598 | 0.074 | 碳酸盐岩 | 151 | 0.192* | -0.184* | -0.182* | 0.213** | 0.238** | 砂页岩 | 264 | 0.140* | -0.270** | -0.160** | 0.138* | -0.07 | 冲积物 | 77 | 0.603** | -0.135 | -0.369** | 0.417** | 0.311** | 水稻土 | 118 | -0.127 | -0.286** | -0.166 | 0.185* | -0.163 | 红壤 | 65 | 0.257* | -0.106 | 0.140 | 0.298* | 0.296* | 赤红壤 | 138 | 0.051 | -0.411** | -0.212* | 0.351** | -0.077 | 石灰土 | 111 | 0.216* | -0.182 | -0.252** | 0.240* | 0.224* | 潮土 | 60 | 0.533** | -0.371** | -0.212 | 0.387** | -0.229 |
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Pearson correlation coefficient analysis of soil Seand other elements under different soil types
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