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Based on field data from 2019 to 2022 in the South Tiaoxi River Watershed in the upper reaches of the Taihu Lake Basin, redundancy analysis (RDA) and non-parametric breakpoint analysis (nCPA) were employed to analyze the relationships between riverine nitrogen (N) concentrations and landscape pattern indices at different buffer scales, and identity the critical landscape threshold ranges affecting the river nitrate (NO3--N) concentration. The results showed that the total nitrogen (TN) concentration in the South Tiaoxi River exceeded the Class V surface water quality standard, with NO3--N as the predominant N pollutant. During the wet season, the concentrations of TN, dissolved total nitrogen (DTN), NO3--N, and dissolved organic nitrogen (DON) were significantly higher than those in the dry season, whereas ammonium nitrogen (NH4+-N) concentrations were lower. N concentrations were lower in the upstream compared to downstream. The landscape pattern indices in the buffer zones of 400m and 200m explained the largest variance in river N concentrations during the wet and dry seasons, respectively (89.49% and 90.97%). Based on the identified key thresholds of landscape pattern indices for significantly reducing the risk of NO3--N pollution in the watershed, the following suggestions are provided: the proportion of farmland, construction land, and Shannon diversity index (SDHI)in the buffer zone of 400m should be controlled within 0.25%, 1.75%, and 0.77, respectively; and the proportion of farmland and edge density (ED) in the buffer zone of 200m should be kept within 0.5% and 39m/hm2, simultaneously with the proportion of forest area exceeding 91.0%.

, correspAuthors=Lin-lin TIAN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Xue-bing CHEN, Shuo WANG, Fu-ping LIU, Xiao-xue MA, Lin-lin TIAN, Jian CHEN, Yan LI, Yan-jiang CAI), CN=ArticleExt(id=1241408729195794542, articleId=1241408722556211624, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=南苕溪河岸带景观格局对水体氮素浓度的影响, columnId=1234106386565624579, journalTitle=中国环境科学, columnName=水污染与控制, runingTitle=null, highlight=null, articleAbstract=

基于2019~2022年太湖流域上游南苕溪流域的实测数据,分别利用冗余分析(RDA)和非参数变点分析(nCPA)确定流域氮(N)素浓度与不同尺度河岸带景观格局指数的关系和影响水体硝态氮(NO3--N)浓度变化的关键景观阈值区间(景观格局指数阈值).结果显示:南苕溪流域总氮(TN)浓度超过地表水Ⅴ类标准,NO3--N是主要N污染物赋存形态.湿季水体TN、溶解性总氮(DTN)、NO3--N和溶解性有机氮(DON)浓度均显著高于干季,而铵态氮(NH4+-N)浓度则相反;上游河段N素浓度低于下游河段.400和200m河岸带缓冲区内景观格局指数分别对湿季和干季水体N素浓度解释度最高(89.49%和90.97%).在确定降低流域水体NO3--N污染风险的关键景观格局指数阈值分析的基础上,建议在400m河岸带缓冲区内调控耕地、建设用地面积占比及香农多样性指数(SDHI)分别低于0.25%、1.75%和0.77;在200m河岸带缓冲区内调控耕地面积占比和边缘密度(ED)分别应低于0.5%和39m/hm2,且林地面积占比应高于91.0%.

, correspAuthors=田琳琳, authorNote=null, correspAuthorsNote=
* 责任作者,副教授,
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陈学兵(1996-),男,安徽安庆人,博士研究生,主要研究方向为农业面源污染与生态治理.发表论文1篇..

, authorsList=陈学兵, 王烁, 刘富平, 马小雪, 田琳琳, 陈健, 李彦, 蔡延江)}, authors=[Author(id=1241408730844156175, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408722556211624, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=XuebingChen@stu.zafu.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1241408730999345437, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408722556211624, authorId=1241408730844156175, language=EN, stringName=Xue-bing CHEN, firstName=Xue-bing, middleName=null, lastName=CHEN, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1.National Key Laboratory for Development and Utilization of Forest Food Resources, Zhejiang A&F University, Hangzhou 311300, China
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2.浙江农林大学环境与资源学院、碳中和学院,浙江 杭州 311300, bio={"content":"

陈学兵(1996-),男,安徽安庆人,博士研究生,主要研究方向为农业面源污染与生态治理.发表论文1篇..

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陈学兵(1996-),男,安徽安庆人,博士研究生,主要研究方向为农业面源污染与生态治理.发表论文1篇..

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3.College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou 311300, China
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*和**分别表示在0.05和0.01水平上有显著差异,ns表示无显著差异

, figureFileSmall=QyCBTNYNtV49ihLRuXnofw==, figureFileBig=49JQE/lP/vroFVwJ+nSXmg==, tableContent=null), ArticleFig(id=1241408738121274183, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408722556211624, language=EN, label=Fig.5, caption=Spatial variations of nitrogen concentrations in dry and wet seasons in the South Tiaoxi River Watershed, figureFileSmall=WbAJviDgRHiFFV79i/3uKQ==, figureFileBig=HA+XAA7ba7exM8+m7P8MJA==, tableContent=null), ArticleFig(id=1241408738247103317, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408722556211624, language=CN, label=图5, caption=南苕溪流域水体干湿季中氮素浓度的空间变化

P<0.001表示在0.001水平上有显著差异

, figureFileSmall=WbAJviDgRHiFFV79i/3uKQ==, figureFileBig=HA+XAA7ba7exM8+m7P8MJA==, tableContent=null), ArticleFig(id=1241408738360349538, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408722556211624, language=EN, label=Fig.6, caption=Relationships between nitrogen concentrations in wet and dry seasons and landscape pattern indices of riparian buffer at different scales based on the redundancy analysis (RDA), figureFileSmall=3m11M57E/HiK2w7eXDxfLw==, figureFileBig=Dg2rDngAEVGiIJw5BgXJWw==, tableContent=null), ArticleFig(id=1241408738469401453, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408722556211624, language=CN, label=图6, caption=基于RDA的干湿季流域水体氮素浓度与不同尺度河岸缓冲区景观格局指数的关系

虚线箭头为环境变量;实线箭头为响应变量;样本量n=15

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样本量n=15,*和**分别表示在0.05和0.01水平上有显著关系

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频数和累积概率分别反映了景观格局指数分布的特征和相应条件下NO3--N浓度变化发生的概率

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Landscape pattern indices and their ecological significances

, figureFileSmall=null, figureFileBig=null, tableContent=
类型名称生态含义
景观组成林地林地面积占比
耕地耕地面积占比
草地草地面积占比
建设用地建设用地面积占比
景观配置斑块密度(PD)单位面积的斑块数量
边缘密度(ED)景观的破碎化程度
最大斑块指数(LPI)最大斑块占景观总面积的百分比
景观形状指数(LSI)对应土地利用类型的周长面积比
蔓延度指数(CONTAG)土地利用类型集聚趋势
香农多样性指数(SHDI)群落生态多样性的一种度量,代表景观中斑块的多样性
), ArticleFig(id=1241408739140490144, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408722556211624, language=CN, label=表1, caption=

景观格局指数及其生态意义

, figureFileSmall=null, figureFileBig=null, tableContent=
类型名称生态含义
景观组成林地林地面积占比
耕地耕地面积占比
草地草地面积占比
建设用地建设用地面积占比
景观配置斑块密度(PD)单位面积的斑块数量
边缘密度(ED)景观的破碎化程度
最大斑块指数(LPI)最大斑块占景观总面积的百分比
景观形状指数(LSI)对应土地利用类型的周长面积比
蔓延度指数(CONTAG)土地利用类型集聚趋势
香农多样性指数(SHDI)群落生态多样性的一种度量,代表景观中斑块的多样性
), ArticleFig(id=1241408739304068009, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408722556211624, language=EN, label=Table 2, caption=

Interpretation of landscape pattern indices of riparian buffer at different scales on nitrogen concentrations in wet and dry seasons based on the redundancy analysis (RDA)

, figureFileSmall=null, figureFileBig=null, tableContent=
季节空间范围(m)解释度变化(%)景观格局指数对水体N素浓度的总解释度(%)主要景观格局指数及其解释度(%)
第一轴第二轴第三轴第四轴
湿季10066.3412.186.972.3787.86耕地(38.1)、草地(10.7)、林地(10.6)
20065.1911.945.362.2384.72耕地(37.7)、PD(11.0)、林地(8.0)
30066.3012.617.393.0089.30耕地(43..4)、建设用地(10.6)、草地(8.9)
40067.2312.787.012.4789.49耕地(46.7)、建设用地(10.6)、SHDI(6.2)
50066.1813.446.522.4188.55耕地(48.5)、建设用地(10.6)、ED(7.8)
100059.2213.683.302.7778.97PD(53.8)、建设用地(8.0)、林地(7.6)
干季10050.2624.4212.882.7990.35耕地(28.4)、林地(15.9)、CONTAG(12.8)
20051.5224.4612.302.6990.97耕地(29.7)、林地(12.5)、ED(11.0)
30053.1524.8710.002.7390.75耕地(34.7)、CONTAG(12.6)、建设用地(11.9)
40053.4724.686.112.7587.01耕地(36.7)、草地(11.7)、建设用地(10.7)
50054.0324.496.362.6987.57耕地(39.1)、建设用地(10.5)、SHDI(10.4)
100051.7822.7211.372.4288.29SHDI(44.4)、草地(13.9)、LPI(9.7)
), ArticleFig(id=1241408739417314229, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408722556211624, language=CN, label=表2, caption=

基于冗余(RDA)分析的不同尺度河岸缓冲区景观格局指数对干湿季水体氮素浓度的解释度

, figureFileSmall=null, figureFileBig=null, tableContent=
季节空间范围(m)解释度变化(%)景观格局指数对水体N素浓度的总解释度(%)主要景观格局指数及其解释度(%)
第一轴第二轴第三轴第四轴
湿季10066.3412.186.972.3787.86耕地(38.1)、草地(10.7)、林地(10.6)
20065.1911.945.362.2384.72耕地(37.7)、PD(11.0)、林地(8.0)
30066.3012.617.393.0089.30耕地(43..4)、建设用地(10.6)、草地(8.9)
40067.2312.787.012.4789.49耕地(46.7)、建设用地(10.6)、SHDI(6.2)
50066.1813.446.522.4188.55耕地(48.5)、建设用地(10.6)、ED(7.8)
100059.2213.683.302.7778.97PD(53.8)、建设用地(8.0)、林地(7.6)
干季10050.2624.4212.882.7990.35耕地(28.4)、林地(15.9)、CONTAG(12.8)
20051.5224.4612.302.6990.97耕地(29.7)、林地(12.5)、ED(11.0)
30053.1524.8710.002.7390.75耕地(34.7)、CONTAG(12.6)、建设用地(11.9)
40053.4724.686.112.7587.01耕地(36.7)、草地(11.7)、建设用地(10.7)
50054.0324.496.362.6987.57耕地(39.1)、建设用地(10.5)、SHDI(10.4)
100051.7822.7211.372.4288.29SHDI(44.4)、草地(13.9)、LPI(9.7)
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南苕溪河岸带景观格局对水体氮素浓度的影响
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陈学兵 1, 2 , 王烁 3, 4 , 刘富平 1, 3 , 马小雪 5, 6 , 田琳琳 1, 3, 7, * , 陈健 1, 3, 7 , 李彦 1, 3 , 蔡延江 1, 2
中国环境科学 | 水污染与控制 2025,45(4): 1925-1938
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中国环境科学 | 水污染与控制 2025, 45(4): 1925-1938
南苕溪河岸带景观格局对水体氮素浓度的影响
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陈学兵1, 2 , 王烁3, 4, 刘富平1, 3, 马小雪5, 6, 田琳琳1, 3, 7, * , 陈健1, 3, 7, 李彦1, 3, 蔡延江1, 2
作者信息
  • 1.浙江农林大学,森林食物资源挖掘与利用全国重点实验室,浙江 杭州 311300
  • 2.浙江农林大学环境与资源学院、碳中和学院,浙江 杭州 311300
  • 3.浙江农林大学林业与生物技术学院,浙江 杭州 311300
  • 4.中国科学院武汉植物园,中国科学院水生植物与流域生态重点实验室,湖北 武汉 430074
  • 5.江苏第二师范学院地理科学学院,江苏 南京 210013
  • 6.中国科学院南京地理与湖泊研究所,江苏 南京 211135
  • 7.浙江天目山森林生态系统国家定位观测研究站,浙江 杭州 311300
  • 陈学兵(1996-),男,安徽安庆人,博士研究生,主要研究方向为农业面源污染与生态治理.发表论文1篇..

通讯作者:

* 责任作者,副教授,
Effects of landscape pattern in riparian buffer on water nitrogen concentrations in the South Tiaoxi River
Xue-bing CHEN1, 2 , Shuo WANG3, 4, Fu-ping LIU1, 3, Xiao-xue MA5, 6, Lin-lin TIAN1, 3, 7, * , Jian CHEN1, 3, 7, Yan LI1, 3, Yan-jiang CAI1, 2
Affiliations
  • 1.National Key Laboratory for Development and Utilization of Forest Food Resources, Zhejiang A&F University, Hangzhou 311300, China
  • 2.College of Environmental and Resource Sciences, Zhejiang A&F University, Hangzhou 311300, China
  • 3.College of Forestry and Biotechnology, Zhejiang A&F University, Hangzhou 311300, China
  • 4.CAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China
  • 5.College of Geosciences, Jiangsu Second Normal University, Nanjing 210013, China
  • 6.Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 211135, China
  • 7.Tianmushan Forest Ecosystem National Orientation Observation and Research Station of Zhejiang Province, Hangzhou 311300, China
出版时间: 2025-04-20
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基于2019~2022年太湖流域上游南苕溪流域的实测数据,分别利用冗余分析(RDA)和非参数变点分析(nCPA)确定流域氮(N)素浓度与不同尺度河岸带景观格局指数的关系和影响水体硝态氮(NO3--N)浓度变化的关键景观阈值区间(景观格局指数阈值).结果显示:南苕溪流域总氮(TN)浓度超过地表水Ⅴ类标准,NO3--N是主要N污染物赋存形态.湿季水体TN、溶解性总氮(DTN)、NO3--N和溶解性有机氮(DON)浓度均显著高于干季,而铵态氮(NH4+-N)浓度则相反;上游河段N素浓度低于下游河段.400和200m河岸带缓冲区内景观格局指数分别对湿季和干季水体N素浓度解释度最高(89.49%和90.97%).在确定降低流域水体NO3--N污染风险的关键景观格局指数阈值分析的基础上,建议在400m河岸带缓冲区内调控耕地、建设用地面积占比及香农多样性指数(SDHI)分别低于0.25%、1.75%和0.77;在200m河岸带缓冲区内调控耕地面积占比和边缘密度(ED)分别应低于0.5%和39m/hm2,且林地面积占比应高于91.0%.

硝态氮(NO3--N)  /  河岸缓冲带  /  景观组成  /  景观配置  /  景观格局指数阈值  /  尺度效应

Based on field data from 2019 to 2022 in the South Tiaoxi River Watershed in the upper reaches of the Taihu Lake Basin, redundancy analysis (RDA) and non-parametric breakpoint analysis (nCPA) were employed to analyze the relationships between riverine nitrogen (N) concentrations and landscape pattern indices at different buffer scales, and identity the critical landscape threshold ranges affecting the river nitrate (NO3--N) concentration. The results showed that the total nitrogen (TN) concentration in the South Tiaoxi River exceeded the Class V surface water quality standard, with NO3--N as the predominant N pollutant. During the wet season, the concentrations of TN, dissolved total nitrogen (DTN), NO3--N, and dissolved organic nitrogen (DON) were significantly higher than those in the dry season, whereas ammonium nitrogen (NH4+-N) concentrations were lower. N concentrations were lower in the upstream compared to downstream. The landscape pattern indices in the buffer zones of 400m and 200m explained the largest variance in river N concentrations during the wet and dry seasons, respectively (89.49% and 90.97%). Based on the identified key thresholds of landscape pattern indices for significantly reducing the risk of NO3--N pollution in the watershed, the following suggestions are provided: the proportion of farmland, construction land, and Shannon diversity index (SDHI)in the buffer zone of 400m should be controlled within 0.25%, 1.75%, and 0.77, respectively; and the proportion of farmland and edge density (ED) in the buffer zone of 200m should be kept within 0.5% and 39m/hm2, simultaneously with the proportion of forest area exceeding 91.0%.

nitrate nitrogen (NO3--N)  /  riparian buffer  /  landscape composition  /  landscape configuration  /  threshold of landscape pattern index  /  scaling effect
陈学兵, 王烁, 刘富平, 马小雪, 田琳琳, 陈健, 李彦, 蔡延江. 南苕溪河岸带景观格局对水体氮素浓度的影响. 中国环境科学, 2025 , 45 (4) : 1925 -1938 .
Xue-bing CHEN, Shuo WANG, Fu-ping LIU, Xiao-xue MA, Lin-lin TIAN, Jian CHEN, Yan LI, Yan-jiang CAI. Effects of landscape pattern in riparian buffer on water nitrogen concentrations in the South Tiaoxi River[J]. China Environmental Science, 2025 , 45 (4) : 1925 -1938 .
河流氮(N)污染已成为全球性环境问题,据报道全球每年由陆地生态系统向河流生态系统输送的N量约为184.3Tg[1].大量的N负荷将加剧水体富营养化、温室气体排放等风险,并威胁水生生态系统安全和人体健康[2-4].城市化发展和农业集约化扩张引起的流域水体N污染亦不容忽视[5-6],这类问题既可威胁到流域上游源头溪流及部分水源地的水环境质量[7-8],对下游湖库水体环境承载力也造成一定影响[9-10].因此,源头溪流水体N素的监管和阻控对于流域水体N污染治理具有重要意义[9].以往的研究指出,通过减少和控制农业氮肥的施用和城镇生活污水直排等方式可以从源头上有效控制河流中的N输入[11-12].然而,河流水体N素浓度特征亦受流域内土地利用类型和结构空间异质性的影响较大,这可能增加了流域N素管理的难度[13].因此,阐明流域内N污染物浓度对土地利用方式的响应规律对于源头溪流及流域N污染的管控和水安全的保障具有重要意义.
土地利用景观格局包括景观组成(即土地利用类型的面积比例)和景观配置两个方面[14-15].景观组成指标主要体现在土地利用斑块的多样性和丰富度,而景观配置指标包含斑块的空间分布和组合信息[16].流域内景观格局会影响其向河流水体迁移的水文过程和N污染物负荷量大小[17-18].研究表明流域景观格局与河流水体N素浓度的关系具有典型的尺度依赖性和空间差异性[19].河岸缓冲区是连接陆地和河流的关键区域,对于N污染物的截留及水体污染阻控等方面有重要生态服务功能[20].2020年浙江省发布的《浙江省河流生态缓冲带划定与生态修复技术指南(试行)》中强调了对河岸生态缓冲区的保护和合理划定的重要性[21].然而,以往研究对于如何界定合适的河岸缓冲区尺度仍没有达成共识[22-23].以往研究对于不同宽度河岸缓冲区的景观格局与水质(含N污染物)间的关系存在最佳解释尺度[22-23].因此,有必要深入分析多空间尺度的景观格局与水体N素浓度的关系及其产生原因,这将有利于优化流域土地利用结构进而有助于控制流域面源污染.
河岸缓冲区景观格局对水体N素浓度的影响也表现出一定的季节差异[19,24],这主要是因为降水的季节差异会影响陆地与河流间的水文过程[25].龙川江流域雨季末期(9月)土地利用结构与景观格局对TN的影响大于雨季初期(5月)[26].丹江口库区胡家山流域枯水期景观格局指数能够更好地解释河流TN变化,而丰水期对氨氮(NH3-N)的解释度优于枯水期[27].此外,也有研究表明不同形态N污染物在流域内随水迁移转化的能力差异较大[28],也可能加剧景观格局与水体N浓度关系季节差异的异质性.施肥等农业活动常发生在生长季,在季节性降雨叠加下,可能会增加外源N的输入[29-30],上述人为和自然因素的叠加可加剧景观格局与水环境间关系的复杂性[4,31].因此,需明确河岸缓冲区景观格局对水体N素浓度影响效应的季节差异,更有助于因地制宜、科学合理地制定对应的调控措施.
河流水体N素浓度与流域景观格局指数梯度通常呈现非线性和非正态的关系[32].而这种典型的关系会导致景观指标出现一些关键阈值效应,体现出N素浓度对景观格局的变化尤为敏感[33].这种阈值通常被定义为景观阈值或突变点,即水体污染物能够对景观指标值的变化快速作出反应的特定点或区域[22,34].因此,确定不同空间尺度的景观阈值对于优化流域土地利用方式和结构、提升流域水质净化功能具有重要的科学意义.
南苕溪是太湖流域的源头支流,也是下游杭嘉湖地区重要的水源涵养区[9].本世纪以来,南苕溪流域的杭州市临安区处于城镇化高速发展期,土地利用类型和结构的转换伴随着农业面源污染的加剧,导致南苕溪流域水体存在较为严重的N污染负荷[7,35].然而,该区源头溪流水体N素浓度与流域景观格局的多尺度空间分析及其特征仍不甚明了.因此,本文以太湖流域源头溪流南苕溪为研究对象,探究河岸缓冲区景观格局对水体N素浓度影响效应及其时空分异规律,从而明确影响南苕溪流域水体N素浓度的关键景观格局指数,并确定河岸缓冲区景观阈值及其关键控制范围.本研究有助于为源头小流域土地利用规划的调整及管理优化提供科学指导,并最终为改善太湖流域水体N污染提供数据支撑和理论基础.
南苕溪流域位于浙江省杭州市临安区(30°13′49.07″~30°23′35.52″N,119°32′52.44″~119°44′21.96″E),是太湖流域的源头支流,也是杭嘉湖地区优质的饮用水源地[35].该流域全长63km,流域面积为720km2,平均比降1.23%[36].研究区属于北亚热带季风气候,多年平均气温15.8℃,年相对高温月出现在7~9月[7],四季分明,年平均降水量1500mm,降水相对集中于5~9月(约占全年降水量的57%),雨热同期.因此,本研究中将全年划分为湿季(5~9月)和干季(10~次年4月)[24].流域内主要自然植被类型为常绿阔叶林,上游区域主要分布森林,中游主要分布农田、果园、竹林和村镇;下游则主要分布城镇,土地开发程度高[36].
根据子流域划分方法选取了15个流域出口作为采样点进行定期采样观测(图1).在2019年7月~2022年6月(因新冠疫情2020年2~6月暂停采样),每月至少进行1次野外采样观测,研究期间共完成37次采样.每次采集各采样点的表层0~20cm水样贮存于250mL聚乙烯塑料瓶中,并放入装有冰袋的保温箱中,采样结束(每次采样均在当天完成)运回实验室后迅速保存于4℃冰箱,并于2d内完成样品所有N素指标的测定.
测定指标包括TN、溶解性总氮(DTN)、铵态氮(NH4+-N)和硝态氮(NO3--N).参照《水和废水监测分析方法》[37],分别采用靛酚蓝比色法和双波长比色法测定NH4+-N和NO3--N浓度,分别将水样原液和经0.45μm滤膜过滤的水样用碱性过硫酸钾消解-紫外分光光度法测定TN和DTN浓度.经过前期多次测定实验发现,亚硝态氮(NO2--N)浓度基本上低于所测定方法的检测下限[37],故忽略不计.因此,溶解性有机氮(DON)和颗粒态氮(PN)分别利用公式(1)和(2)计算得出[35]:
根据前人研究[38-39]以及南苕溪流域边界特征,分别划分各采样点上游至源头河段的多个河岸带尺度的带状范围(100,200,300,400,500和1000m)作为缓冲区宽度,划分情况详见图1.
土地利用数据源自于2022年欧洲航天局(ESA;https://worldcover2021.esa.int/)发布的全球土地覆盖图,作者数据分析后发现研究期间研究区内的土地利用年变化幅度<0.2%,故选择2021年的土地利用数据(基于Sentinel-1和Sentinel-2数据,分辨率为10m,精度为76.7%)[40].通过ArcGIS10.2软件(美国Esri公司)人工目视解译提取到南苕溪流域林地、草地、耕地、建设用地、水域和未利用地6种土地利用类型(图1),其中水域和未利用地面积占比不足1%,根据相关文献[1624],后续所有数据统计分析中予以忽略.根据前人的研究中较为常用的几种景观配置指标[24,26,41],选择能够反映景观破碎度、聚集度、优势性和多样性等的景观格局指数.因此,本文从景观水平上选取了斑块密度(PD)、边缘密度(ED)、最大斑块指数(LPI)、景观形状指数(LSI)、蔓延度指数(CONTAG)和香农多样性指数(SHDI)这6种景观配置指标(表1).基于ArcGIS10.2和FRAGSTATS4.2软件计算上述6个河岸带尺度的景观指数.
非参数变点分析(nCPA)通常用于确定引发水质显著变化的景观度量阈值[14,42].由于实际测得样本数据有限,通常采用自举例法来估计变点频率分布[22].使用非参数偏差减少方法计算变化阈值.本研究中nCPA的计算方法如下:第一步,将景观指标(x1x2,…,xn)和N素浓度(y1y2,…,yn)从小到大排序.第二步,在分割点i处将N素浓度分为两组:(y1y2,…,yi)和(yi+1yi+2,…,yn).每组偏差使用公式(1.3)进行计算:
式中:D表示第i个变点的偏差;m为样本数;µm个观测值yk的平均值.
由于两个子组的偏差之和总是小于整体数据的偏差,因此可以对每个点i计算偏差的减少Δi.具体由公式(4)进行计算:
式中:D为整体数据的偏差;DiD>i分别为(y1y2,…,yi)和(yi+1yi+2,…,yn)的偏差.
为了提高变化点频率分布估计的准确性,采用自举例法从N素浓度和景观指标数据集中提取1000个样本.使用R4.4.1中的boot包进行突变点分析.
利用Kolmogorov-Smirnov检验N素浓度的正态性,对于非正态分布的数据进行了对数log(x+1)转换.采用独立样本T检验比较N素浓度的季节差异,采用ANOVA单因素方差分析及Duncan检验确定不同季节采样点间N素浓度的空间差异.利用观测期间各个采样点N素浓度的3a平均值(n=15),采用Pearson相关分析和冗余分析(RDA)来探究N素浓度与景观格局指数的关系.为了明确线性模型或单峰模型的可靠性与准确性,本文首先进行去趋势对应分析(DCA),发现4个轴的最长梯度小于3,同时也参考相关的研究[41],最终使用RDA来探索河岸缓冲带景观格局指数对水体N素浓度的影响程度.RDA分析使用Canoco5.0软件进行.
在景观组成方面,各观测点位上游不同尺度上河岸缓冲区土地利用类型均以林地为主,林地面积占比均已超过60%(图2).从S1~S5到S6~S15河段,河岸缓冲带林地面积由96.45%降低至80.97%,而耕地和建设用地面积占比则分别由0.25%和1.83%增加至8.90%和7.26%.S1~S5河段缓冲带中耕地和建设用地面积占比较小,表明农业和城镇开发利用程度较低.南苕溪流域随着河岸缓冲区尺度的增加,林地面积占比均值逐渐升高,由78.57%(100m宽缓冲区内)逐步上升到90.50%(1000m宽缓冲区内);而建设用地和草地面积占比均值逐渐降低,分别由10.20%和8.35%(100m宽缓冲区内)降至3.64%和3.19%(1000m宽缓冲区内).耕地面积平均占比随缓冲区尺度的增加而先降低后增加(图2).
在景观配置上,南苕溪流域内河岸带的PD、ED、LSI和SHDI均随着河岸缓冲区尺度的增加而增加;LPI和CONTAG随缓冲区尺度的增加而降低(图3).相同缓冲区尺度下不同河段采样点之间的LSI差异较大.
研究期间南苕溪水体TN,DTN,NO3--N,NH4+-N,DON和PN浓度均值分别为3.96,3.64,3.37,0.10,0.37和0.31mg/L,其中NO3--N/TN值最高(均值77.45%),表明南苕溪流域水体中NO3--N是N污染物的最主要赋存形态.该流域TN浓度超出了地表水环境质量标准(GB3838-2002)中规定的V类水体的浓度范围,NO3--N浓度也超出标准限值,而NH4+-N浓度低于地表水Ⅰ类标准范围.因此,南苕溪流域亟需首要管控的N污染物为NO3--N.鉴于NO3--N具有长距离迁移的特性,源头溪流NO3--N迁移的尺度效应可能导致下游水体N污染的负荷加剧[43].因此,该流域内NO3--N对缓冲区景观格局的空间响应将是后续研究的重点.
研究期间全流域水体湿季中TN,DTN,NO3--N,NH4+-N,DON和PN浓度均值分别为4.23,3.92,3.44,0.08,0.40和0.32mg/L;干季水体TN,DTN,NO3--N,NH4+-N,DON和DON浓度均值分别为3.69,3.38,2.91,0.12,0.35和0.31mg/L(图4);湿季水体TN、DTN、NO3--N和DON浓度均显著高于干季,而湿季水体NH4+-N浓度显著低于干季,PN浓度则无显著干湿季差异(图4).
空间上,除DON和PN外,S1~S5河段的N素浓度均小于S6~S15河段的(图5).这主要是因为S1~S5河段处在森林覆盖率高的区域,受人类活动影响较小,而S6~S15河段河岸带主要分布农业区和城镇居民点区(图1).
南苕溪流域河岸带不同宽度缓冲区景观格局指数对N素浓度的总解释度为78.97%~90.97%,100,200,300和1000m缓冲区内的景观格局指数对流域水体N素的总解释度在干季高于湿季(表2).
河岸带景观格局指数对河流N素浓度的影响随河岸带空间尺度的增加先增后降.200和400m缓冲区内的景观格局指数对湿季和干季中流域水体N素浓度的总解释度最大.100~500m的缓冲带中耕地面积占比是影响该流域水体N素浓度的最佳解释变量,且其对N素浓度的解释度随缓冲区尺度的增大而增加,但其对湿季中水体N素的解释度(37.7%~48.5%)高于干季(28.4%~39.1%).
各形态N素浓度均与缓冲带内林地面积占比和CONTAG负相关,而与耕地、草地和建设用地面积占比以及PD、ED和SHDI正相关(图67).水体N素浓度主要与100~300m缓冲区草地、耕地和建设用地面积占比显著正相关,而与该区域内林地面积占比显著负相关;在400~1000m缓冲区与上述的土地利用类型占比显著相关,也与PD、ED和SHDI显著正相关,与CONTAG显著负相关(图7).干季水体DON浓度仅与1000m缓冲带的LPI显著相关,可能是因为以森林为主的河岸带缓冲区域,河流中DON最主要来源于水体浮游植物的内源生产,而受到陆源输入的影响较小[35].
鉴于NO3--N是南苕溪水体主要的N污染物,且其浓度已超出地表水V类标准范围(图4).因此,本研究分别选择对湿季和干季水体NO3--N浓度解释度最高的河岸缓冲区尺度(400和200m),在二种缓冲区范围内对主要影响干湿季水体NO3--N浓度突变的景观格局指数阈值予以分析,最终确定影响水体NO3--N浓度变化的景观格局指数的关键阈值区间(图8).
河岸带400m缓冲区内耕地和建设用地面积占比对湿季水体NO3--N浓度变化影响的关键阈值区间分别为0%~0.25%和1.25%~1.75%,而SHDI的关键阈值区间为0.75~0.77[图8(a)]. 当缓冲区内耕地和建设用地面积占比分别>0.25%和>1.75%,河流NO3--N浓度增加的突变概率则分别可达到91.3%和97.4%.当SHDI>0.77时,NO3--N浓度突变概率可达到93.5%.
河岸带200m缓冲区内耕地和林地面积占比对干季水体NO3--N浓度变化影响的关键阈值区间分别为8.5%~9.5%和89.0%~91.0%,该缓冲区ED的关键阈值区域为37~39m/hm2[图8(b)]. 当缓冲带中耕地面积占比>9.5%时,河流NO3--N浓度增加的突变概率则会达到96.3%;当耕地面积占比>0.5%时,突变概率也会达到61.2%.干季河流NO3--N浓度突变的累积概率可随缓冲带内林地面积占比增加而增加,当其占比>91.0%,NO3--N浓度降低的突变概率达到100%,表明提高研究区河岸缓冲区内林地面积占比(如>91.0%)显著有利于提高对陆源NO3--N的阻控拦截效率[图8(b)]. 当缓冲带中ED>39m/hm2,河流NO3--N浓度增加的突变概率可达92.0%.
河流N素浓度的变化与土地利用方式密切相关[19,44].森林具有涵养水源、水土保持等功能,对地表径流和壤中流中N素污染物有截留、转化和吸收等作用,从而可显著降低输入河流的N污染物[15,45].本研究中100~1000m河岸缓冲带中林地面积占比的增加对水体NO3--N、NH4+-N、DON和PN浓度升高均有抑制效应(图6),且全流域森林覆盖率高达85%(图1),这表明保障河岸缓冲带中林地的高覆盖度,同时降低景观破碎化程度能够有效阻控流域内水体N污染物[46].农业化肥大量施用使土壤N素随地表径流和淋溶迁入河流[47].本研究发现100~1000m河岸缓冲带中耕地面积占比增加会导致水体NO3--N、NH4+-N、DON和PN浓度升高(图6),在河岸缓冲带中耕地面积占比较高的区域(S6~S13),河流水体N素浓度也相对较高(图25),这与杨莎莎等[38]在苏子河流域研究结果一致.因此,农业非点源N污染是南苕溪流域水体中N污染物的重要来源之一[7,35].此外,该区(S6~S13)河岸缓冲带中耕地面积占比与河流NO3--N和PN浓度相关系数更高(图7),这可能是因为农耕活动影响了土壤结构,导致NO3--N和PN更容易迁入河流[47].居民点和建设用地也是流域N污染物的主要来源,建设用地不透水层面积占比较高以及生活废弃物未经处理后直接排放,会减少地表下渗并增加河流N污染负荷[15].本研究发现河岸带缓冲区内建设用地面积占比与NH4+-N浓度的相关系数显著较高,表明居民点区生活污水是该流域水体NH4+-N主要来源[48-49].本研究还发现,河岸缓冲带内草地面积占比升高可在一定程度上促进河流N素浓度增加(图6图7),其原因可能是草地土壤中仍含有一定农业源N素[41];同时,草地面积占比高的河段缓冲区内(如S8河段)ED也较高(图2图3),表明草地的单位面积小且分布较为零散,增加了河岸带景观的破碎化程度,从而弱化了对地表径流N污染物的截留效应[50].
景观配置指数反映了土地利用的大小、密度、聚集性和多样性,合理的景观配置在调节水质方面具有重要作用[17].CONTAG是衡量土地利用类型聚集程度的指标,该值越大表明景观连通性越高[51].本研究河岸缓冲区CONTAG与河流N素浓度负相关(图6图7),表明提高和保障缓冲带内林地占比和景观连通性可增加对N污染物的截留能力,最终减少河流陆源N污染物的输入[34].PD、ED和SHDI分别可反映景观丰富度、破碎化程度和多样性[4,41,52].本研究水体N素浓度均与河岸缓冲带PD、ED和SHDI负相关(图6图7),表明河岸缓冲带中耕地和建设用地占比过高可能会引起景观斑块密度和边缘密度的增加,进而导致河流N污染物浓度的增加[53].因此,该流域内应加强对河岸缓冲带的监管,推广使其景观破碎化程度降低(如退耕还林、防护林建设等)的措施[6,34],从而有助于增强对该区河流N污染的阻控效果.
南苕溪流域河岸缓冲区景观格局指数对湿季和干季中河流N素浓度解释度的高低随着空间尺度的变化有所差异.当缓冲区尺度≤300m和1000m时,景观格局指数对干季N素浓度的解释度高于湿季,该发现也与吕乐婷等[15]研究结果一致.其原因可能是湿季降雨量大对河流N污染物产生较强的稀释效应,而干季降雨量小对河流N素浓度的影响较小[15].湿季水体N素浓度对400和500m河岸缓冲区景观格局的敏感性比干季高(图7),这与徐明珠等[41]研究结果一致.上述原因主要为:该区域景观破碎化较为严重、连通性较差(图3);同时,湿季农业施肥耕作活动频繁,增加了缓冲区土壤的N输入[35],而干季较低的降水量会减少陆地N素向河流输入,最终使得耕地面积占比对干季NO3--N浓度负荷的威胁较湿季有所减缓[1],从而表现出耕地面积占比对水体N素浓度的解释度最大(表2).
研究表明,河流较普遍存在一个临界河岸缓冲区(即景观格局对水质的解释度最大的河岸缓冲区)[54].本研究发现南苕溪流域不同空间尺度河岸缓冲区景观格局指数对河流N素浓度的解释度在湿季和干季中均有类似的空间变化规律,即对N素浓度的解释度随空间尺度的增加先升后降,400和200m河岸缓冲区景观格局分别对湿季和干季水体N素浓度的解释度最高(表2).表明这些河岸缓冲区是对水环境变化反应最为迅速和直接的区域[39].因此,上述结果均表明科学合理的划分南苕溪流域河岸缓冲区管理范围是十分必要和亟需的[5].
河岸缓冲区景观格局指数阈值的确定对于土地利用结构的优化与河流N污染的阻控不可或缺[34].由于NO3--N是南苕溪流域N污染物的主要赋存形态,鉴于NO3--N具有可长距离迁移的特性,源头溪流NO3--N迁移的尺度效应可能导致下游水体N污染的负荷加剧[43].本研究地属太湖流域源头的山溪性河流,建设用地和耕地主要分布在沿河岸200m缓冲区范围内[图2(a)和2(b)],导致河岸带缓冲区景观格局指数的空间变化不够均一且有一定差异(图3);同时,200和400m河岸带缓冲区内影响N素浓度变化的景观格局指数及其解释度均不同(表2)、景观配置指数SDHI和ED均不同(图3),因此在400和200m河岸带缓冲区的景观格局指数阈值指标有所差异(图8).进一步研究发现,当400m河岸缓冲区内耕地和建设用地面积占比及SHDI分别大于0.25%、1.75%及0.77时[图8(a)],湿季河流面临NO3--N负荷风险会显著增加.这与闵家河流域100m河岸缓冲区尺度对TN浓度的影响效应类似[4].当200m河岸缓冲区耕地面积占比和ED分别大于9.5%和39m/hm2,干季河流NO3--N浓度会显著升高;而林地面积占比大于91.0%时,对干季迁入河流的NO3--N的阻控效应显著[图8(b)]. 上述景观格局指数阈值分析表明,即使200m缓冲带中耕地占比对干季中水体NO3--N浓度影响的敏感性降低[图8(b)],仍需要严格控制河岸缓冲带耕地面积占比[如低于0.5%,图8(b)],从而避免其景观破碎化程度增加,可能有助于降低河流NO3--N负荷风险.因此,建议加强该区域土地利用规划的优化管理及农业集约化经营,减少河岸缓冲带景观破碎化程度,以促进生活废弃物的集中处置和提升土壤N肥利用率,进而减少人为活动对河流水质的威胁[51,55].同时,在河岸缓冲带内坚持以退耕还林、生态育林为主的林业生态修复(如生态公益林)措施则是对太湖流域上游及源头河流N污染阻控的有效途径[6,41].
4.1 南苕溪流域水体N素浓度有明显的时空变化,湿季中水体TN、DTN、NO3--N和DON浓度均显著高于干季,湿季水体NH4+-N浓度显著较低,上游河段N素浓度低于下游河段.100~1000m河岸缓冲带内林地面积占比以及PD、ED、LSI和SHDI均随缓冲带尺度的增加逐渐升高,而建设用地和草地面积占比以及LPI和CONTAG则反之,耕地面积占比先降低后增加.
4.2 南苕溪100~1000m河岸缓冲带内林地占比越高、CONTAG越大,对河流N污染物的阻控效应越强,而耕地、草地和建设用地面积占比升高及PD、ED和SHDI增大均可能会导致河流中N素浓度升高.
4.3 在流域N素管理时,应确保在湿季和干季河岸缓冲区保护的范围分别在400和200m以上,同时,在400m河岸缓冲区的耕地和建设用地面积占比以及SHDI分别应低于0.25%、1.75%和0.77;在200m河岸缓冲区耕地面积占比和ED分别应低于0.5%和39m/hm2,且林地面积占比应高于91.0%.同步实施上述管理措施,将会有更为有效地保障促进对南苕溪流域及其下游NO3--N负荷的削减和污染风险的调控作用.
  • 国家自然科学基金资助项目(41907268; 42406234)
  • 浙江省领雁研发攻关计划项目(2022C02019)
  • 浙江农林大学校科研发展基金资助项目(2018FR005; 2018FR006; 2018FR061)
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2025年第45卷第4期
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  • 接收时间:2024-09-27
  • 首发时间:2026-03-19
  • 出版时间:2025-04-20
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  • 收稿日期:2024-09-27
基金
国家自然科学基金资助项目(41907268; 42406234)
浙江省领雁研发攻关计划项目(2022C02019)
浙江农林大学校科研发展基金资助项目(2018FR005; 2018FR006; 2018FR061)
作者信息
    1.浙江农林大学,森林食物资源挖掘与利用全国重点实验室,浙江 杭州 311300
    2.浙江农林大学环境与资源学院、碳中和学院,浙江 杭州 311300
    3.浙江农林大学林业与生物技术学院,浙江 杭州 311300
    4.中国科学院武汉植物园,中国科学院水生植物与流域生态重点实验室,湖北 武汉 430074
    5.江苏第二师范学院地理科学学院,江苏 南京 210013
    6.中国科学院南京地理与湖泊研究所,江苏 南京 211135
    7.浙江天目山森林生态系统国家定位观测研究站,浙江 杭州 311300

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2种不同金属材料的力学参数

Family
属数
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genus
种数
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species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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