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近30年中国主要农田土壤pH时空演变及其驱动因素

花匠小妙招
2024-12-13 01:43

摘要:

目的

研究中国农田土壤pH时空变化特征及其主要的驱动因素，为土壤酸化阻控、土壤质量提升和土地可持续利用提供理论基础。

方法

基于农业农村部布置在全国主要农田区域的耕地质量监测点数据 (950个)，分析旱地、水旱轮作、水田等不同土地利用类型下土壤pH时空变化特征，并利用提升回归树模型探究影响土壤pH变化的主要驱动因素。

结果

就全国而言，土壤pH及其变异系数表现为旱地 (6.74 ± 1.19和17.63%) > 水旱轮作 (6.54 ± 0.93和14.26%) > 水田 (5.80 ± 0.81和13.95%)，其中华南地区农田土壤pH表现为水田 (5.74 ± 0.79) 大于水旱轮作 (5.47 ± 0.56) 和旱地 (5.45 ± 0.91)。从监测初期 (Ⅰ阶段，1988—2000) 到监测中期 (Ⅱ阶段，2001—2010)，旱地和水田土壤pH整体上随时间呈降低趋势，下降速率分别为0.065和0.054/年 (P < 0.01)，而水旱轮作土壤pH无显著变化；从Ⅱ到Ⅲ阶段 (2001—2018)，旱地和水旱轮作土壤pH整体上随时间呈上升趋势，上升速率分别为0.022和0.016/年 (P < 0.05)，而水田土壤pH无显著变化。东北、华北、西南、长江中下游地区的旱地土壤pH随时间均呈线性下降趋势 (P < 0.05)，而华南地区从Ⅱ到Ⅲ阶段呈线性上升趋势 (P < 0.01)；西南、长江中游和华南地区水田土壤pH从Ⅰ到Ⅲ阶段呈线性下降趋势 (P < 0.01)，而东北、西南和长江下游地区pH从Ⅱ到Ⅲ阶段呈上升趋势 (P < 0.01)；西南地区水旱轮作土壤pH从Ⅰ到Ⅲ阶段呈线性下降趋势 (P < 0.01)，而华北、长江下游和华南地区pH从Ⅱ到Ⅲ阶段呈上升趋势 (P < 0.05)。通过Pearson和提升回归树分析发现，年均降雨量是造成土壤pH空间尺度上差异的最主要因素，其次是土壤质地、容重和有机质含量。此外，在旱地土壤上长期的氮肥投入和在水田和水旱轮作土壤上钾肥的投入对pH变化的影响较大。

结论

整体而言，我国旱地和水田土壤pH从监测初期到中期呈快速下降趋势，而旱地和水旱轮作土壤pH从监测中期到2018年呈缓慢增加趋势。东北地区的旱地土壤pH呈持续下降趋势，需要引起重视。氮肥在旱地和钾肥在水田上的施用导致土壤pH的降低，今后应优化水肥运筹，通过改善土壤容重和有机质进而有效调控土壤pH。

Abstract:

Objectives

Exploration of the temporal and spatial changes of soil pH in Chinese farmland and the main driving factors are of great significance in alleviating acidification, soil quality improvement and sustainable land use.

Methods

Based on the national long-term farmland fertilization monitoring data from the Ministry of Agricultural and Rural Affairs (950 experiments), we analyzed the temporal and spatial variations of soil pH in upland field, paddy field and paddy-upland rotation field. The main factors affecting the change of soil pH were analyzed using boosted regression tree model.

Results

The soil pH value and coefficient of variation in China followed the sequence of upland (6.74 ± 1.19 and 17.63%) > upland-paddy rotation field (6.54 ± 0.93 and 14.26%) > paddy field (5.80 ± 0.81 and 13.95%). While

the paddy soil pH (5.74 ± 0.79) was higher than that of upland-paddy field and upland field in South China. From the initial stage of monitoring (I, 1988–2000) to the middle stage (II, 2001–2010), the pH of upland and paddy soils showed a decreasing trend, and the decreasing rates were 0.065 and 0.054 units per year, respectively (P < 0.05).

From stage II to III (2001–2018), pH of upland and upland-paddy soil increased with time, and the rising rates were 0.022 and 0.016 units per year, respectively (P < 0.05), but there was no significant change in paddy soils. The soil pH of uplands in Northeast, North China, Southwest, Middle and Lower Reaches of Yangtze River decreased linearly with time (P < 0.05), while opposite trend was found in South China from stage II to III (P < 0.01). The pH of paddy soils in Southwest, Middle Reaches of Yangtze River and South China decreased linearly from stage I to III (P < 0.01), but increased linearly from stage II to III (P < 0.01) in Northeast, Southwest and Lower Reaches of Yangtze River. The pH of upland-paddy soil in Southwest China decreased linearly from stage I to III (P < 0.01), while opposite result was observed in North China, Lower Reaches of Yangtze River and South China from stage II to III (P < 0.05). Pearson’s correlation and boosted regression tree model revealed that mean annual precipitation was the most important factor driving regional soil pH change, followed by soil texture, bulk density and organic matter content. Moreover, the long-term inputs of nitrogen fertilizer in upland and the input of potassium fertilizer in paddy and upland-paddy fields also played key roles in soil pH change.

Conclusions

Overall, soil pH shows a trend of decreasing from the initial stage to the middle stage in upland and paddy soil, then slow increasing from the middle stage to 2018 in upland and upland-paddy soils, except that the pH in upland soil of Northeast China shows durative decrease. The application of nitrogen fertilizer in upland and potash in paddy field has caused soil pH decrease, so reasonable nutrient management, and the soil bulk density and organic matter amelioration should be considered to alleviate the decrease of soil pH in Chinese farmlands.

图 1 三个监测阶段全国及各种植区域旱作土壤pH

[注（Note）：Ⅰ, 1988—2000; Ⅱ, 2001—2010; Ⅲ, 2011—2018; MYR—Middle Reaches of the Yangtze River; LYR—Lower Reaches of the Yangtze River；图中箱体上下框分别代表全部数据的75%和25%，箱体上下两条线分别代表全部数据的95%和5%，箱内实线和星号分别表示中位数和平均数，括号里的数字为样品数；柱上不同小写字母表示同一区域不同阶段间差异显著 (P < 0.05) The upper and lower frames of the box represent 75% and 25% of total data, the upper and lower short lines outside the box represent 95% and 5% of total data, the solid line and asterisks inside the box represent the median and average values, and the digitals inside brackets are sample number. Different small letters above the bars indicate significant difference among the monitoring periods in same region (P < 0.05).]

Figure 1. pH of upland soils in each planting area and whole country during the three monitoring periods

图 2 全国和各种植区域3个监测阶段水田土壤的pH

[注（Note）：Ⅰ, 1988—2000; Ⅱ, 2001—2010; Ⅲ, 2011—2018; MYR—Middle Reaches of the Yangtze River; LYR—Lower Reaches of the Yangtze River；图中箱体上下框分别代表全部数据的75%和25%，箱体上下两条线分别代表全部数据的95%和5%，箱内实线和星号分别表示中位数和平均数，括号里的数字为样品数；不同小写字母表示同一区域不同阶段间差异显著 (P < 0.05) The upper and lower frames of the box represent 75% and 25% of total data, the upper and lower short lines outside the box represent 95% and 5% of total data, the solid line and asterisks inside the box represent the median and average values, and the digitals inside brackets are sample number. Different small letters above the bars indicate significant difference among the monitoring periods in same region (P < 0.05).]

Figure 2. pH of paddy soils in each planting areas and whole county during the three monitoring periodss

图 3 不同种植区域水旱轮作下土壤pH随时间的变化特征

[注（Note）：Ⅰ, 1988—2000; Ⅱ, 2001—2010; Ⅲ, 2011—2018; MYR—Middle Reaches of the Yangtze River; LYR—Lower Reaches of the Yangtze River；图中箱体上下框分别代表全部数据的75%和25%，箱体上下两条线分别代表全部数据的95%和5%，箱内实线和星号分别表示中位数和平均数，括号里的数字为样品数；柱上不同小写字母表示同一区域不同阶段间差异显著 (P < 0.05) The upper and lower frames of the box represent 75% and 25% of total data, the upper and lower short lines outside the box represent 95% and 5% of total data, the solid line and asterisks inside the box represent the median and average values, and the digitals inside brackets are sample number; Different small letters above the bars indicate significant difference among the monitoring periods in same region (P < 0.05).]

Figure 3. Variation characteristics of soil pH with time in upland-paddy soil in different planting areas

图 4 各因素影响土壤pH变化的相对重要性

[注（Note）：MAP—年均降雨量 Mean annual precipitation；AP—有效磷 Available phosphorus；BD—容重 Bulk density；Texture—质地；MAT—年均气温 Mean annual temperature；SOM—土壤有机质 Soil organic matter；SAK—缓效钾 Slowly available potassium；AK—速效钾 Available potassium；NF—氮肥 Nitrogen fertilizer；PF—磷肥 Phosphorus fertilizer；TN—全氮 Total nitrogen；KF—钾肥 Potassium fertilizer.]

Figure 4. Relative importance of factors affecting soil pH change

表 1 不同区域土壤pH统计分析 (1988—2018)

Table 1 Statistical analysis of soil pH in different regions from 1988 to 2018

区域
Region土地利用
Land use统计量
n均值
Mean标准差
SD偏度
Skewness峰度
Kurtosis变异系数 (%)
CVP 值
P value 东北地区 Northeast China旱地 Upland7846.430.840.520.0813.110.3127水田 Paddy1286.070.620.371.5210.130.2851华北地区 North China旱地 Upland6687.830.79–2.084.2310.080.5728水旱轮作 U-P816.560.750.420.0111.500.5367西南地区 Southwest China旱地 Upland4016.611.23–0.03–1.1118.550.8132水田 Paddy2076.171.000.42–0.7816.180.6928水旱轮作 U-P2476.780.94–0.10–1.1613.880.7781长江中游 MYR旱地 Upland3886.051.09–0.06–0.7717.980.0948水田 Paddy6545.710.781.181.2213.680.2329水旱轮作 U-P3476.390.840.00–0.4213.140.9800长江下游 LYR旱地 Upland3136.821.05–0.20–0.8715.460.3391水田 Paddy1015.690.570.430.119.950.2356水旱轮作 U-P7596.660.920.18–0.9713.850.9394华南地区 South China旱地 Upland1545.450.910.850.4416.720.3813水田 Paddy5985.740.790.960.5713.830.6059水旱轮作 U-P995.470.560.020.0610.290.2214全国 Total旱地 Upland27086.741.19–0.18–0.9917.630.1527水田 Paddy16885.800.810.940.5513.950.1723水旱轮作 U-P15336.540.930.15–0.7814.260.8509 注（Note）：MYR—Middle Reaches of the Yangtze River; LYR—Lower Reaches of the Yangtze River; U-P—Upland-paddy rotation; P > 0.05 表明数据符合正态分布 P > 0.05 shows that the data conform to normal distribution.

表 2 不同种植区域旱作土壤pH (y) 与试验持续时间 (x) 的拟合方程

Table 2 The fitting equations of soil pH (y) and duration time (x) in upland soil in different planting areas

区域 Region监测阶段 Monitoring period方程 EquationR2P 东北地区 Northeast China1998—2010y = –0.0456x + 97.7350.76542.02E-062001—2018y = –0.0192x + 45.0780.65574.48E-04华北地区 North China1988—2018y = –0.0149x + 8.23810.71260.0169西南地区 Southwest China1988—2018y = –0.0256x + 58.0890.45296.34E-05长江中游 MYR1998—2018y = –0.0134x + 33.0510.32730.0259长江下游 LYR1988—2010y = –0.1232x + 253.6600.86752.60E-042001—2018y = –0.0328x + 72.4810.55080.0057华南地区 South China2001—2018y = 0.0354x – 65.7290.47158.27E-04全国 Total1988—2010y = –0.0646x + 136.0200.80624.30E-072001—2018y = 0.0215x – 52.7240.43980.0135 注（Note）：MYR—Middle Reaches of the Yangtze River; LYR—Lower Reaches of the Yangtze River; 方程中，各监测阶段内以相应的起始年份开始每隔 3 年获取一个平均值作为 y, 持续时间 x 从该监测期的第二年开始计算 In each equation, y is the average pH value of every three years since the starting of the monitoring, and duration (x) is counted from the second year of the monitoring period.

表 3 不同种植区域水田土壤pH (y) 与试验持续时间 (x) 的拟合方程

Table 3 The fitting equations of soil pH (y) and duration time (x) in paddy soil in different planting areas

区域 Region监测阶段 Monitoring period方程 EquationR2P 东北地区 NortheastChina2001—2018y = 0.0260x – 46.1560.54030.0018西南地区 SouthwestChina1988—2010y = –0.0873x + 180.3700.61921.07E-042001—2018y = 0.0815x – 157.8800.70263.45E-04长江中游 MYR1988—2010y = –0.0392x + 84.6170.71834.99E-042001—2018y = –0.0233x + 52.5660.38400.0239长江下游 LYR2001—2018y = 0.0206x – 35.6610.47250.0066华南地区 South China1988—2010y = –0.0557x + 117.1000.56613.15E-042001—2018y = 0.0022x + 1.3330.00450.8206全国 Total1988—2010y = –0.0535x + 112.8100.63896.90E-052001—2018y = 0.0009x + 4.00240.00280.8578 注（Note）：MYR—Middle Reaches of the Yangtze River; LYR—Lower Reaches of the Yangtze River; 方程中，各监测阶段内以相应的起始年份开始每隔 3 年获取一个平均值作为 y, 持续时间 x 从该监测期的第二年开始计算 In each equation, y is the average pH value of every three years since the starting of the monitoring, and duration (x) is counted from the second year of the monitoring period.

表 4 不同种植区域水旱轮作下土壤pH (y) 与试验持续时间 (x) 的拟合方程

Table 4 Fitting equations of soil pH (y) and duration time (x) in upland-paddy soil in different planting areas

区域 Region监测阶段 Monitoring period方程 EquationR2P 华北地区 Northeast China2001—2018y = 0.0403x – 74.6030.65268.36E-04西南地区 Southwest China1988—2010y = –0.0494x + 105.6600.59361.83E-042001—2018y = –0.0076x + 6.8010.03630.93444长江中游 MYR1988—2018y = 0.0104x – 14.3810.14530.0661长江下游 LYR1988—2010y = –0.0087x + 24.0010.11370.21912001—2018y = 0.0201x – 33.9120.34030.0465华南地区 South China2001—2018y = 0.0256x – 46.1250.33550.0300全国 Total1988—2010y = –0.0107x + 28.0640.11590.14172001—2018y = 0.0160x – 25.7430.48280.0177 注（Note）：MYR—Middle Reaches of the Yangtze River; LYR—Lower Reaches of the Yangtze River; 方程中，各监测阶段内以相应的起始年份开始每隔 3 年获取一个平均值作为 y, 持续时间 x 从该监测期的第二年开始计算 In each equation, y is the average pH value of every three years since the starting of the monitoring, and duration (x) is counted from the second year of the monitoring period.

表 5 各因素与土壤pH之间的Pearson相关性分析

Table 5 Pearson correlation analysis between soil pH and each factor

项目 Item旱地 Upland soil水田 Paddy soil水旱轮作 Upland-paddy soilrPnrPnrPn 氮肥 N fertilizer–0.277 < 0.0012593–0.0720.0031648–0.160 < 0.0011502磷肥 P fertilizer0.0160.07925930.0270.2651648–0.0050.8391502钾肥 K fertilizer–0.131 < 0.0012593–0.125 < 0.0011648–0.196 < 0.0011502土壤有机质SOM–0.312 < 0.00127070.219 < 0.0011668–0.108 < 0.0011510全氮 Total N0.296 < 0.00127000.252 < 0.0011646–0.0710.0061504有效磷 Available P–0.34 < 0.0012685–0.050.0431656–0.0780.0021524有效钾 Available K0.116 < 0.00126730.187 < 0.00116560.207 < 0.0011520缓效钾 SAK0.465 < 0.00121000.102 < 0.00112270.411 < 0.0011187容重 Bulk density–0.292 < 0.00127070.179 < 0.0011668–0.118 < 0.0011510年均气温 MAT–0.071 < 0.0012708–0.133 < 0.0011674–0.347 < 0.0011533年均降雨量 MAP–0.485 < 0.0012708–0.286 < 0.0011674–0.378 < 0.0011533 注（Note）：n—样本数 Sample number; SOM—Soil organic matter; SAK—Slowly available potassium; MAT—Mean annual temperature; MAP—Mean annual precipitation. [1]

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