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  土壤学报  2021, Vol. 58 Issue (2): 487-494  DOI: 10.11766/trxb201908220433
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引用本文  

王肖君, 王季丰, 侯琼, 等. 西苕溪流域主要经济林土壤磷素流失风险研究. 土壤学报, 2021, 58(2): 487-494.
WANG Xiaojun, WANG Jifeng, HOU Qiong, et al. Potential Risk of Phosphorus Loss from Main Non-Wood Forest Soils in Xitiaoxi Watershed. Acta Pedologica Sinica, 2021, 58(2): 487-494.

基金项目

国家水体污染控制与治理科技重大专项(2014ZX07101-012)资助

通讯作者Corresponding author

倪吾钟, E-mail:wzni@zju.edu.cn

作者简介

王肖君(1994-), 男, 浙江人, 硕士, 主要从事养分资源管理与农业面源污染控制研究。E-mail:wxj0531@qq.com
西苕溪流域主要经济林土壤磷素流失风险研究
王肖君1, 王季丰1, 侯琼1, 冷明珠2, 倪吾钟1    
1. 浙江大学环境与资源学院, 浙江省农业资源与环境重点实验室, 杭州 310058;
2. 浙江省安吉县农业农村局, 浙江安吉 313300
摘要:经济林土壤磷素积累与潜在流失风险的研究对流域内磷素管理和面源污染控制十分必要。通过采样调查和室内分析研究了西苕溪流域主要经济林土壤测试磷的状况及磷素流失的潜在风险,调查采集了西苕溪流域安吉段主要经济林(毛竹、白茶、板栗)土壤样品105个,探讨了土壤理化性质对土壤磷素流失的影响以及土壤有效磷的控制阈值。结果表明,土壤水溶性磷(WEP)与土壤有机碳(SOC)、全磷(TP)呈极显著正相关(P < 0.01),模拟酸雨浸提磷(SARP)也与土壤SOC、TP呈极显著正相关(P < 0.01),土壤WEP、SARP与pH呈极显著负相关(P < 0.01),但决定系数R2分别仅有0.187~0.280,影响相对较小。土壤WEP、SARP与有效磷(Bray 1-P)的关系可用分段线性回归方程描述(P < 0.01),R2分别可达0.992、0.991,估算得出,与WEP、SARP相对应的土壤Bray 1-P的阈值分别为93.63、87.68 mg·kg-1,后者较前者降低了5.95 mg·kg-1。此外,土壤Bray 1-P含量超过40 mg·kg-1、低于5 mg·kg-1的样品占比分别可达17.14%、38.01%,缺磷与磷过度积累现象并存。土壤磷素的流失风险主要受土壤Bray 1-P、TP、SOC、pH等因素的影响,其中Bray 1-P是最重要的影响因子。酸雨会加大土壤磷素流失的潜在风险,作为酸雨频发区域的西苕溪流域,土壤有效磷水平的限制应更为严格。
关键词西苕溪流域    经济林    土壤测试磷    阈值    模拟酸雨    
Potential Risk of Phosphorus Loss from Main Non-Wood Forest Soils in Xitiaoxi Watershed
WANG Xiaojun1, WANG Jifeng1, HOU Qiong1, LENG Mingzhu2, NI Wuzhong1    
1. College of Environmental and Resource Sciences, Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Zhejiang University, Hangzhou 310058, China;
2. Bureau of Agriculture and Rural Affairs of Anji County, Zhejiang Province, Anji, Zhejiang 313300, China
Abstract: 【Objective】 Studies on accumulation and potential loss risk of soil phosphorus in non-wood forest soils are essential to management of soil phosphorus and control of non-point source P pollution in watersheds. So a research project was carried out in the Xitiaoxi watershed.【Method】 In the project, a total of 105 soil samples were collected in the main non-wood forests, such as moso bamboo (Phyllostachys heterocycla (Carr.) Mitford cv. Pubescens Mazel ex H.de leh.), white tea (Camellia sinensis (L.) O. Ktze.), chestnut (Castanea mollissima Bl.) in the watershed for lab analysis of concentrations of water-extractable phosphorus (WEP) and simulated-acid-rain-extractable phosphorus (SARP) and some main soil physico-chemical properties such as total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkalyzable nitrogen (AN), available phosphorus (Bray 1-P), readily available potassium (AK), pH, soil organic carbon (SOC). Acid rain set at 4.75 in pH was simulated and prepared with sulphate acid and nitrate acid. Correlation analysis and regression analysis was performed of the obtained data to determine influences of soil physico-chemical properties on the risk of phosphorus runoff loss and threshold of soil available phosphorus.【Result】 In the survey area, soil TP content varied in the range of 0.22-0.73 g·kg-1 (0.42 g·kg-1 on average) and Bray 1-P content in the range of 0.93-313.2 mg·kg-1 (30.87 mg·kg-1 on average) with coefficient of variation reaching up to 204.7% and the soil samples over 40 mg·kg-1 and below 5 mg·kg-1 in Bray-P content accounted for 17.14% and 38.01% of all the analyzed ones, respectively; soil WEP content varied in the range of 0.03-38.15 mg·kg-1 (2.64 mg·kg-1 on average) with coefficient of variation reaching up to 267.5%; and soil SARP content varied in the range of 0.03-42.91 mg·kg-1 (2.86 mg·kg-1 on average) with coefficient of variation reaching up to 268.6%. It was found that soil WEP and SARP were significantly and positively related to soil organic carbon (SOC) and TP (P < 0.01), and negatively to soil pH, with determination coefficient (R2), however, being only 0.266, 0.251, 0.280, 0.262, 0.187 and 0.190, respectively, which indicates that they are relatively not much affected by these soil properties. The relationship between WEP, SARP and Bray 1-P could be described by the piecewise linear regression equation, which was ${\rm{y}} = \left\{ {\begin{array}{*{20}{l}} {0.0569{\rm{x}} - 0.043, {\rm{x}} < 93.63}\\ {0.1483{\rm{x}} - 8.601, {\rm{x}} > 93.63} \end{array}} \right.$. for WEP with R2 being 0.992(r=0.996), and ${\rm{y}} = \left\{ {\begin{array}{*{20}{l}} {0.0571{\rm{x}} - 0.0216, {\rm{x}} < 87.68}\\ {0.1604{\rm{x}} - 9.079, {\rm{x}} > 87.68} \end{array}} \right.$. for SARP with R2 being 0.991 (r=0.995). Hence, the thresholds of soil Bray 1-P was reckoned to be 93.63 and 87.68 mg·kg-1, respectively, based on WEP and SARP and the latter was 5.95 mg·kg-1 lower than the former.【Conclusion】 All the findings in the study demonstrate that both the phenomena of phosphorus deficiency and excessive accumulation exist in the non-wood forest soils of Xitiaoxi watershed. Soil Bray 1-P, TP, organic matter and pH are the main factors affecting the potential risk of phosphorus runoff loss and Bray 1-P is the most significant one. Acid rain enhances the potential risk of phosphorus runoff loss. As the studied region is one that suffers from frequent acid rain, the content of soil available phosphorus should be more strictly controlled.
Key words: Xitiaoxi watershed    Non-wood forest    Soil test phosphorus    Threshold    Simulated acid rain    

水体富营养化是当今世界面临的最主要的水污染问题,严重影响了人们的正常生活,制约了区域社会经济的可持续发展。西苕溪作为太湖上游的重要支流,入湖水量大,其携入的氮磷等污染物均会对太湖水环境质量产生最直接的影响[1]。据统计,西苕溪流域林地面积占了流域总面积的65%以上[2],每年可产生超过650 t的总氮流失量及270 t的总磷流失量。其中,经济林面积占了林地面积的56%,土壤侵蚀及其产生的养分流失量占比77%[3]

大量研究表明,由于化肥及有机肥的不合理施用,土壤磷素积累现象明显。以钱塘江附近农田为例,超过土壤磷素流失阈值60 mg·kg–1的土样占比可达11.60%[4]。当土壤中磷素积累到一定水平时,其释放潜力会急剧增加,土壤磷释放能力突变点所对应的土壤有效磷含量即土壤磷素流失阈值[5]。综合Hesketh和Brookes[6]、Zhao[7]等的研究结果可以发现,不同类型的土壤磷素流失阈值差异很大,最大值甚至可达最小值的16倍。自从提出土壤磷素流失阈值概念后,土壤磷素流失阈值的研究引起了国内外学者的广泛关注。但是大多数研究集中在农田土壤[8-11]上,对经济林土壤磷素流失阈值的研究相对较少。

相关数据显示,浙江省酸雨覆盖面积可达90%以上,其中重酸雨区约占20%,酸雨污染严重[12]。西苕溪流域位于浙江省西北部的湖州市境内,2012—2017年年均降水pH在4.60~4.98之间,6年pH中位数为4.75,酸雨率超过了90%。刘旭阳等[13]发现,酸雨显著提高了土壤磷的含量。大量研究表明,长期的酸雨作用会导致土壤磷素流失,且土壤磷流失总量与酸雨pH存在显著的非线性关系。随着pH的降低,土壤磷流失总量先增加后降低[14]。Liang等[15]研究发现,pH1.6~6.0范围内,pH越低,胶体态磷流失风险就越高。

综上,土壤磷素流失阈值研究以及酸雨对土壤磷素流失的影响一直是学者们关注的重点。虽然也有少量土壤磷素流失阈值与土壤pH关系的研究[7],但是关于酸雨对土壤磷素流失阈值的影响仍未见报道。因此,本文拟通过模拟酸雨浸提实验,根据土壤水溶性磷、模拟酸雨浸提磷与有效磷之间的相关关系,对西苕溪流域主要经济林土壤磷素流失风险进行研究,旨在为酸雨频发区土壤磷素流失阈值研究提供新思路,对流域内磷素的管理、农业面源污染及水体富营养化治理也具有十分重要的意义。

1 材料与方法 1.1 土样的采集与预处理

浙江省安吉县境内西苕溪流域面积为1 806 km2,约占西苕溪流域总面积的79.42%。根据安吉县主要经济林的分布情况,采集毛竹林、白茶园、板栗林土壤样品(0~20 cm)105个,采样点分布如图 1所示。采集的土样在室温下自然风干后,研磨过筛(20目、100目),保存备用。

图 1 主要经济林土壤采样点分布图 Fig. 1 Map of soil sampling sites in the main non-wood forests
1.2 测定项目与方法

水溶性磷(WEP)采用蒸馏水浸提,水土比为10︰1,振荡时间30 min,0.45 µm滤膜过滤后用磷钼蓝比色法测定[16];模拟酸雨浸提磷(SARP)测定方法参照水溶性磷,其中浸提液换成pH为4.75的模拟酸雨;土壤有效磷含量采用Bray 1法,盐酸-氟化铵溶液提取,钼蓝比色法测定[17],其他土壤理化性质如全氮(TN)、全磷(TP)、全钾(TK)、碱解氮(AN)、速效钾(AK)、pH、有机碳(SOC)等测定方法参照《土壤农业化学分析方法》[17]

模拟酸雨的配制:根据湖州市2012—2017年年均降水pH及酸雨成分资料,设置模拟酸雨的pH为4.75,SO42–与NO3的摩尔浓度比为1:1。模拟酸雨以浓硫酸、浓硝酸为原材料,采用逐步稀释法配制。首先以浓硫酸和浓硝酸配置成pH为1的酸雨母液,再用蒸馏水稀释至pH4.75的模拟酸雨[18]

1.3 数据处理与分析

经济林土壤采样点的分布采用ArcMap 10.2作图。试验数据用Excel 2010软件整理、作图,用SPSS 20.0做相应指标间的相关性分析。土壤活性磷与Bray 1-P之间的定量关系利用分段线性回归模型拟合,拟合方程如下:

${\rm{y}} = \left\{ \begin{array}{l} {\rm{a}} + {\rm{b}}x, \;x < \alpha \\ {\rm{a}} + {\rm{b}}x + {\rm{c}}(x - \alpha ), \;x \geqslant \alpha \\ \end{array} \right.$

式中,y为土壤活性磷,mg·kg–1x为Bray 1-P,mg·kg–1;a为纵坐标上的截距,b、c为拟合回归直线方程的斜率;α为分段线性回归方程转折点所对应的Bray 1-P含量,即阈值,mg·kg–1

2 结果 2.1 西苕溪流域经济林土壤基本理化性质与活性磷含量

调查区域安吉县105个经济林土壤的基本理化性质汇总情况如表 1所示,土壤SOC含量9.00~26.35 g·kg–1,平均为16.59±3.65 g·kg–1;土壤pH3.55~5.92,平均为4.69±0.45;TN、TP、TK含量分别在0.72~2.07、0.22~0.73、3.57~22.80 g·kg–1之间,平均值分别为1.38±0.33、0.42±0.11、9.81± 3.56 g·kg–1;土壤AN、AK含量分别在74.10~265.7、48.00~379.5 mg·kg–1之间,平均值分别为152.2±39.90、138.5±69.02 mg·kg–1。与其他指标相比,Bray 1-P含量变幅较大,范围在0.93~313.2 mg·kg–1 之间,平均为30.87±63.18 mg·kg–1,变异系数可达204.7%。统计数据表明,约17.14%的土壤Bray 1-P含量超过40 mg·kg–1,但也有38.01%的土壤Bray 1-P含量低于5 mg·kg–1

表 1 调查区域105个经济林土壤基本理化性质 Table 1 Basic soil physico-chemical properties of the 105 sampling sites in the main non-wood forests under survey

土壤活性磷的提取分别采用蒸馏水和模拟酸雨浸提,结果如图 2所示:土壤水溶性磷(WEP)含量0.03~38.15 mg·kg–1,平均为2.64±7.06 mg·kg–1,变异系数为267.5%;模拟酸雨浸提磷(SARP)含量0.03~42.91 mg·kg–1,平均为2.86±7.69 mg·kg–1,变异系数为268.6%。SARP含量总体高于WEP,但未达到显著性水平(P>0.05)。

注:箱图中最上方和最下方的线段表示数据的最大值和最小值,箱图中矩形上下两边分别表示第三四分位数和第一四分位数,矩形中间的粗线表示中位数,图中圆圈和星号分别表示离群值和极值。  Note:The line segments at the top and bottom of the box diagram represent the maximum and minimum values of the data; the upper side and the lower side of the rectangle in the box represents the 3rd and 1st quartile, respectively, and the bold in the middle of the rectangle represents the median; and the circle and asterisk in the diagram represents the outlier and extremum, respectively. 图 2 土壤水溶性磷和模拟酸雨浸提磷含量 Fig. 2 Water-extractable phosphorus(WEP)and simulated-acid-rain-extractable phosphorus(SARP)content in the soils
2.2 土壤磷素流失风险与土壤有效磷的关系

分段线性回归分析得出,土壤水溶性磷含量与有效磷含量的回归方程为:

$y = \left\{ \begin{gathered} 0.056\;9{\rm{x}} - 0.043, \;x < 93.63 \\ 0.148\;3{\rm{x}} - 8.601, \;x > 93.63 \\ \end{gathered} \right.\;\;\;\;{R^2} = 0.991\;6$

统计检验结果表明,回归方程的显著性达到极显著水平(P < 0.01)。从图 3可以看出,拟合曲线上有一明显的转折点,相对应的Bray 1-P含量为93.63 mg·kg–1。当Bray 1-P低于93.63 mg·kg–1时,WEP含量随着Bray 1-P变化很小,拟合线段斜率为0.056 9;当Bray 1-P超过93.63 mg·kg–1,WEP含量迅速增加,具体表现为:Bray 1-P每增加10 mg·kg–1,WEP增加1.48 mg·kg–1,拟合线段斜率增加了1.61倍。因此,Bray 1-P含量93.63 mg·kg–1可作为研究区域主要经济林土壤磷素流失阈值。统计数据表明,西苕溪流域主要经济林土壤Bray 1-P超过阈值的样品占比12.38%。

图 3 土壤水溶性磷与有效磷的关系 Fig. 3 Relationship between WEP and Bray 1-P

酸雨会影响土壤磷的溶出,土壤模拟酸雨浸提磷与有效磷含量的关系见图 4,分段线性回归方程为:

$y = \left\{ \begin{gathered} 0.057\;1x - 0.021\;6, \;{\rm{x}} < 87.68 \\ 0.160\;4x - 9.079, \;{\rm{x}} > 87.68 \\ \end{gathered} \right.\;\;\;{R^2} = 0.9912$
图 4 土壤模拟酸雨浸提磷与有效磷的关系 Fig. 4 Relationship between SARP and Bray 1-P

显著性检验结果表明,回归方程达到极显著水平(P < 0.01)。SARP含量普遍高于WEP,且其上限较WEP上限高4.76 mg·kg–1。在模拟酸雨的作用下,拟合方程的两个斜率均有所增加。此外,SARP所对应的土壤磷素流失阈值为87.68 mg·kg–1,较WEP所对应的阈值降低了5.95 mg·kg–1

2.3 土壤测试磷与土壤基本理化性质的关系

本文对土壤全磷、有效磷、活性磷与土壤基本理化性质做了相关性分析,结果如表 2所示:土壤SOC、TN、AN、AK与所有土壤测试磷指标均呈极显著正相关(P < 0.01);土壤pH与所有土壤测试磷指标呈极显著负相关;土壤TK与Bray 1-P、WEP、SARP呈极显著负相关,但决定系数R2较小。

表 2 土壤全磷、有效磷、活性磷与土壤基本理化性质的关系 Table 2 Relationships of total phosphorus, available phosphorus and active phosphorus with basic physico-chemical properties of the soils
3 讨论 3.1 西苕溪流域主要经济林土壤磷素积累状况

土壤全磷和有效磷作为评价土壤肥力、磷素水平的指标,常被用来反映土壤磷素水平及磷素积累情况。西苕溪流域经济林土壤TP含量0.22~0.73 g·kg–1,平均为0.42 g·kg–1。Bray 1-P含量变幅极大,范围在0.93~313.2 mg·kg–1之间,平均为30.87 mg·kg–1,变异系数可达204.7%(表 1)。其中,Bray 1-P含量超过40 mg·kg–1、低于5 mg·kg–1的土壤样品分别达到了17.14%、38.01%,且二者占比超过了55%。可见,本研究地经济林磷缺乏与磷过度积累土壤并存。这可能与山区林农的粗放式管理有关。通常认为,Bray 1-P含量在20~40 mg·kg–1之间即可基本满足作物的需求,过多土壤磷的积累将导致土壤中磷素吸附位点减少,无法继续容纳外源磷素,大大增加土壤磷素的流失风险[19],而Bray 1-P低于5 mg·kg–1又将影响作物的正常生长[17]。因此,有必要对该地经济林土壤磷素水平及其分布进行调查,根据相应的土壤有效磷含量确定适宜的施肥量,同时加强对土壤磷关键源区的识别[20],严格控制磷肥施用。

3.2 土壤基本理化性质与土壤磷素流失风险的关系

水溶性磷(包括文中的模拟酸雨浸提磷)与径流水中磷的浓度密切相关,因此可用来分析土壤磷素随径流及酸雨径流流失的风险。大量研究表明,土壤磷素的流失受土壤有效磷、全磷、pH、有机质等诸多因素的影响。其中,土壤有效磷对土壤磷素流失影响最大,可作为土壤磷的环境指标[21]。这也解释了本文中Bray 1-P的决定系数R2远高于TP、pH、SOC等因素的结果(表 2)。本研究还发现,随着土壤pH下降,土壤Bray 1-P、WEP、SARP在统计学水平上有显著的增加(表 2),与黄敏等[22]的研究结果一致。土壤TN、AN、AK与WEP、SARP均呈极显著正相关(表 2),这可能与农户普遍施用NPK复合肥有关。土壤SOC与WEP、SARP以及Bray 1-P的相关关系均可达到极显著水平(表 2),与Huang等[23]的研究结果相一致。Heredia和Cirelli[24]及Meng等[25]认为,土壤有机质易与磷酸根离子竞争土壤固相表面的专性吸附点位,从而减少了土壤对磷的吸附,且土壤有机质的存在有助于土壤磷向土壤溶液中释放。夏文建等[26]和Yan等[27]的研究发现,土壤有机质含量高的土壤磷吸持饱和度(DPS)较大,土壤吸附磷的能力较弱。因此,土壤有机质含量的增加将导致土壤吸附磷的能力下降,土壤磷更容易向液相中转移,从而使土壤磷素流失阈值降低。Fortune等[28]研究发现,土壤磷素流失阈值与土壤有机碳呈显著负相关,与本文推断结果一致。但是也有学者认为,有机质的存在可以增加土壤团聚体的稳定性[29]。团聚体作为土壤磷素释放与流失的重要载体,对土壤磷素流失具有重大影响,且土壤磷素流失阈值随着土壤有机碳的增加而增大[7]。关于有机质与土壤磷素流失风险的关系有待于进一步的研究。

3.3 模拟酸雨对经济林土壤磷素流失风险的影响

西苕溪流域年均降水pH在4.60~4.98之间,酸雨率超过90%,处于较重酸雨区与重酸雨区之间[30],酸雨污染严重。袁宇志等[31]研究表明,相对于其他类型耕地土壤而言,红壤旱地更易受到酸雨的影响,导致土壤酸化。同时磷素作为水体富营养化的关键限制性因子,酸雨对土壤磷素流失的影响不容忽视。土壤磷素流失阈值的研究一直是国内外学者研究的热点。阈值所对应的有效磷Olsen-P、Mehlich-3 P含量得到了广泛研究,相比之下,Bray-P在土壤磷素流失风险研究中的应用较少。仅有零星报道显示,美国俄亥俄州农业土壤磷素淋失阈值为Bray 1-P 122 mg·kg–1[32]。本研究中,WEP、SARP与Bray 1-P的相关分析结果显示,西苕溪流域经济林土壤磷素流失阈值分别为93.63、87.68 mg·kg–1图 3图 4)。当土壤Bray 1-P含量超过土壤磷素流失阈值时,WEP及SARP急剧增加,土壤磷素流失风险加大。关于酸雨对土壤磷素流失的影响主要体现在以下两个方面。一方面,一定强度的酸雨有助于土壤无机磷组分的溶解,可以促进土壤微生物生物量磷和酸性磷酸酶活性提高,从而提高土壤磷的有效性[33-34]。本研究也发现,土壤SARP含量普遍高于WEP,且分段线性拟合曲线的两段斜率均有了一定程度的提高(图 3图 4)。可见pH4.75的模拟酸雨有助于土壤磷向土壤溶液中释放。另一方面,酸雨的长期作用将导致土壤磷素流失阈值降低。土壤磷素流失阈值越低,土壤磷素流失风险就越大。Zhao等[7]的研究结果显示,当土壤pH < 6.0时,土壤磷素流失阈值随着pH的升高而升高;而当土壤pH > 6.0时,随着pH的升高土壤磷素流失阈值将降低。本研究发现,模拟酸雨作用下土壤磷素流失阈值下降了5.95 mg·kg–1。这表明,相同背景下将会有更多经济林土壤处于土壤磷高流失风险范畴,土壤磷素的潜在流失风险将进一步加大。而常规的根据水溶性磷与土壤有效磷的相关关系得出的磷素流失阈值可能会低估酸雨频发区土壤磷素流失的风险。

4 结论

西苕溪流域安吉段经济林土壤磷素状况变异较大,Bray 1-P含量超过40 mg·kg–1、低于5 mg·kg–1的土壤样品占比分别可达17.14%、38.01%,缺磷和磷过度积累现象并存。土壤磷素积累导致水溶性磷、模拟酸雨浸提磷大幅度升高,存在较大的磷素流失潜在风险。影响土壤磷素流失的因子主要有土壤有效磷、全磷、pH、有机质等,其中有效磷是最重要的影响因子。水溶性磷、模拟酸雨浸提磷与土壤Bray 1-P的分段线性回归分析得出,西苕溪流域经济林土壤磷素流失阈值分别为93.63 mg·kg–1(水溶性磷)、87.68 mg·kg–1(模拟酸雨浸提磷),酸雨会进一步增大磷素的流失风险。鉴于西苕溪流域为酸雨频发区,在土壤有效磷水平的实际限控中应充分考虑酸雨增大磷素流失风险的作用。

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