Article(id=1233737682808001388, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1233737680710849370, articleNumber=null, orderNo=null, doi=10.12284/hyxb2021034, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1592582400000, receivedDateStr=2020-06-20, revisedDate=1602259200000, revisedDateStr=2020-10-10, acceptedDate=null, acceptedDateStr=null, onlineDate=1772075585319, onlineDateStr=2026-02-26, pubDate=1619280000000, pubDateStr=2021-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1772075585319, onlineIssueDateStr=2026-02-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1772075585319, creator=13701087609, updateTime=1772075585319, updator=13701087609, issue=Issue{id=1233737680710849370, tenantId=1146029695717560320, journalId=1149651085930835976, year='2021', volume='43', issue='4', pageStart='1', pageEnd='140', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1772075584819, creator=13701087609, updateTime=1772075584819, updator=13701087609, preIssue=null, nextIssue=null, ext=null, issueFiles=null}, startPage=55, endPage=64, ext={EN=ArticleExt(id=1233737683126768497, articleId=1233737682808001388, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=The design of the stations of marine environmental monitoring buoys in the Chinese sturgeon nature reserve in the Changjiang River Estuary, columnId=1194652705852465724, journalTitle=Haiyang Xuebao, columnName=Article, runingTitle=null, highlight=null, articleAbstract=

The Changjiang River Estuary is an important habitat for many migratory fishes, and its complex environmental conditions affect the growth and reproduction of aquatic organisms in this area. Marine environmental monitoring buoys are capable of long-term, continuous, real-time and large-scale monitoring of many environmental factors, and are an important part of the modern marine environmental automatic observation system. To establish a reasonable and effective buoy monitoring network for the Chinese sturgeon nature reserve and its adjacent waters in the Changjiang River Estuary , this study used Ordinary Kriging (OK) method to simulate the spatial distribution of various environmental factors, and then compared the effects of different strata design and sample size of Stratified Random Sampling (StRS) on the monitoring results. The results showed that: (1) the sampling accuracy of salinity was better when the stratum of StRS was 3, and water temperature, dissolved oxygen and chemical oxygen demand (COD) was better when the stratum was 2; (2) the relative estimation errors became more concentrated and tended to 0 value with the increase of sample size, and when the sample size was larger than 30, the accuracy tended to be stable gradually; (3) the sampling accuracy of salinity in autumn was different to the other three seasons, and the sampling effect of COD in winter was worst. In the future, when setting up an environmental monitoring buoy network in the Chinese sturgeons nature reserve in the Changjiang River Estuary, it is suggest to adopt three stratum stratified random sampling for salinity monitoring, and the number of stations should be more than 50. When taking various hydrological environments as the monitoring target, it is recommended to use two stratified standard, and the number of stations should be more than 30.

, correspAuthors=Siquan Tian, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2021 Pratacultural Science. All rights reserved., 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=Shaoyuan Pan, Xuefang Wang, Siquan Tian, Jianfeng Tong, Chunxia Gao, Jing Zhao, Dongyan Han), CN=ArticleExt(id=1233737686670955515, articleId=1233737682808001388, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=长江口中华鲟保护区海洋环境监测浮标站点的优化设计, columnId=1149698756456657529, journalTitle=海洋学报, columnName=论文, runingTitle=null, highlight=null, articleAbstract=

长江口是众多洄游性鱼类重要的栖息场所,其复杂的环境条件影响着该水域水生生物的生长和繁殖过程。海洋环境监测浮标能够对诸多环境要素进行长期、连续、实时和大范围的监测,是现代海洋环境自动观测系统中的重要组成部分。为在长江口中华鲟自然保护区及其邻近水域组建合理有效的浮标监测网络,本研究基于海上实测调查数据,使用普通克里金法模拟了多种环境要素的空间分布,在此基础上比较了分层随机采样设计中不同分层方案和站点数量变化对监测效果的影响,结果显示:(1)盐度要素在层数为3的分层随机采样方法中采样精度更高,水温、溶解氧和化学需氧量要素在层数为2的采样设计中采样效果更好;(2)站点数越多,相对误差越集中并趋向于0,并当站点数多于30时,采样估测准确性逐渐趋于稳定;(3)各季节中,秋季盐度要素中层数为2的采样准确性更高;与其他3季以及总体相对误差结果相比,冬季化学需氧量要素的采样效果比其他3个季节要差。在今后长江口中华鲟自然保护区水域组建环境监测浮标网络时,建议采用3层的分层随机采样作为盐度监测的分层标准,且站点数量要大于50个;使用2层的分层随机采样作为其他多种水文环境要素监测的分层标准,且站点数量要大于30个。

, correspAuthors=田思泉, authorNote=null, correspAuthorsNote=
田思泉(1978-),男,安徽省无为市人,教授,研究方向为海洋渔业资源调查监测等。E-mail:
, copyrightStatement=版权所有©《海洋学报》编辑部 2021, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=LNeIumqLMCzw8FNZ9DewTA==, magXml=p3Iewyq/ogK0D7KxOSD/EQ==, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=knk/xnt1EHsIfpHiPBkanA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=X4IxPC+8NWddw/yysu5kCw==, mapNumber=null, authorCompany=null, fund=null, authors=

潘邵媛(1995-),女,江苏省扬州市人,研究方向为海洋生态学。E-mail:

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潘邵媛(1995-),女,江苏省扬州市人,研究方向为海洋生态学。E-mail:

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潘邵媛(1995-),女,江苏省扬州市人,研究方向为海洋生态学。E-mail:

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4Key Laboratory of Oceanic Fisheries Exploitation, Ministry of Agriculture, Shanghai 201306, China
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3大洋渔业资源可持续开发教育部重点实验室,上海 201306
4农业部大洋渔业开发重点实验室,上海 201306
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2National Distant-water Fisheries Engineering Research Center, Shanghai 201306, China
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figureFileBig=DlE45iremCYXDAHuM8WxCA==, tableContent=null), ArticleFig(id=1233805856551268838, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233737682808001388, language=CN, label=图1, caption=长江口中华鲟自然保护区及其邻近水域综合监测调查站点, figureFileSmall=u1NYeCKa3qqvH6Zm9kktog==, figureFileBig=DlE45iremCYXDAHuM8WxCA==, tableContent=null), ArticleFig(id=1233805856706458092, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233737682808001388, language=EN, label=Fig. 2, caption=Stratified design of stratified random sampling in the Chinese sturgeon nature reserve and its adjacent waters in the ChangjiangRiver Estuary

a. Two stratum stratified random sampling; b. three stratum stratified random sampling

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a. 2层分层随机采样方法;b. 3层分层随机采样方法

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Stratified design and sample size distribution of stratified random sampling

, figureFileSmall=null, figureFileBig=null, tableContent=
区域分层盐度范围$ {{N_h}}$$ {{w_h}}$$ {{S_h}}$$ {{n_{h10}}}$$ {{n_{h{\rm{14}}}}}$$ {{n_{h20}}}$$ {{n_{h{\rm{30}}}}}$$ {{n_{h{\rm{40}}}}}$$ {{n_{h{\rm{5}}0}}}$
A>10610.385.80458121619
B≤10990.625.576912182431
C>15440.281.922357911
D5~15290.187.776811172328
E≤5870.540.982346811
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分层随机采样的分层设计及站点数分布

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区域分层盐度范围$ {{N_h}}$$ {{w_h}}$$ {{S_h}}$$ {{n_{h10}}}$$ {{n_{h{\rm{14}}}}}$$ {{n_{h20}}}$$ {{n_{h{\rm{30}}}}}$$ {{n_{h{\rm{40}}}}}$$ {{n_{h{\rm{5}}0}}}$
A>10610.385.80458121619
B≤10990.625.576912182431
C>15440.281.922357911
D5~15290.187.776811172328
E≤5870.540.982346811
), ArticleFig(id=1233805859667636767, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233737682808001388, language=EN, label=Table 2, caption=

The average relative estimation error of different sampling design results of various environmental factors

, figureFileSmall=null, figureFileBig=null, tableContent=
站点数水温盐度溶解氧COD
2层3层2层3层2层3层2层3层
101.0121.23713.41812.7520.5350.6815.5007.664
140.8401.00811.45510.3850.4470.5534.5746.232
200.6930.8489.1938.3150.3650.4643.7695.250
300.5440.6787.1906.6610.2870.3712.9824.201
400.4530.5826.0015.6070.2400.3182.4703.600
500.3870.4865.1884.7970.2060.2662.1053.016
), ArticleFig(id=1233805859747328545, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233737682808001388, language=CN, label=表2, caption=

各环境要素不同采样设计结果的平均相对误差

, figureFileSmall=null, figureFileBig=null, tableContent=
站点数水温盐度溶解氧COD
2层3层2层3层2层3层2层3层
101.0121.23713.41812.7520.5350.6815.5007.664
140.8401.00811.45510.3850.4470.5534.5746.232
200.6930.8489.1938.3150.3650.4643.7695.250
300.5440.6787.1906.6610.2870.3712.9824.201
400.4530.5826.0015.6070.2400.3182.4703.600
500.3870.4865.1884.7970.2060.2662.1053.016
), ArticleFig(id=1233805859864769063, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233737682808001388, language=EN, label=Table 3, caption=

The average relative bias of different sampling design results of various environmental factors

, figureFileSmall=null, figureFileBig=null, tableContent=
站点数水温盐度溶解氧COD
2层3层2层3层2层3层2层3层
10 0.000−0.009−0.099 0.119 0.003−0.003 0.012 0.009
14−0.006 0.003 0.037−0.071 0.005−0.001 0.009 0.003
20−0.002 0.000 0.053−0.031 0.000 0.001−0.013 0.016
30 0.000−0.003−0.027−0.017−0.001 0.001 0.012 0.004
40−0.001−0.001 0.044 0.040 0.001 0.000 0.000 0.003
50−0.001 0.003−0.006−0.005 0.001−0.003 0.000−0.004
), ArticleFig(id=1233805859965432363, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1233737682808001388, language=CN, label=表3, caption=

各环境要素不同采样设计结果的平均相对偏差

, figureFileSmall=null, figureFileBig=null, tableContent=
站点数水温盐度溶解氧COD
2层3层2层3层2层3层2层3层
10 0.000−0.009−0.099 0.119 0.003−0.003 0.012 0.009
14−0.006 0.003 0.037−0.071 0.005−0.001 0.009 0.003
20−0.002 0.000 0.053−0.031 0.000 0.001−0.013 0.016
30 0.000−0.003−0.027−0.017−0.001 0.001 0.012 0.004
40−0.001−0.001 0.044 0.040 0.001 0.000 0.000 0.003
50−0.001 0.003−0.006−0.005 0.001−0.003 0.000−0.004
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长江口中华鲟保护区海洋环境监测浮标站点的优化设计
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潘邵媛 1 , 王学昉 1, 2, 3, 4, 5 , 田思泉 1, 2, 3, 4, 5, * , 童剑锋 1, 2, 3, 4, 5 , 高春霞 1, 2, 3, 4, 5 , 赵静 1, 2, 3, 4, 5 , 韩东燕 1, 2, 3, 4, 5
海洋学报 | 论文 2021,43(4): 55-64
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海洋学报 | 论文 2021, 43(4): 55-64
长江口中华鲟保护区海洋环境监测浮标站点的优化设计
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潘邵媛1 , 王学昉1, 2, 3, 4, 5, 田思泉1, 2, 3, 4, 5, * , 童剑锋1, 2, 3, 4, 5, 高春霞1, 2, 3, 4, 5, 赵静1, 2, 3, 4, 5, 韩东燕1, 2, 3, 4, 5
作者信息
  • 1上海海洋大学 海洋科学学院,上海 201306
  • 2国家远洋渔业工程技术研究中心,上海 201306
  • 3大洋渔业资源可持续开发教育部重点实验室,上海 201306
  • 4农业部大洋渔业开发重点实验室,上海 201306
  • 5农业部大洋渔业资源环境科学观测实验站,上海 201306
  • 潘邵媛(1995-),女,江苏省扬州市人,研究方向为海洋生态学。E-mail:

通讯作者:

田思泉(1978-),男,安徽省无为市人,教授,研究方向为海洋渔业资源调查监测等。E-mail:
The design of the stations of marine environmental monitoring buoys in the Chinese sturgeon nature reserve in the Changjiang River Estuary
Shaoyuan Pan1 , Xuefang Wang1, 2, 3, 4, 5, Siquan Tian1, 2, 3, 4, 5, * , Jianfeng Tong1, 2, 3, 4, 5, Chunxia Gao1, 2, 3, 4, 5, Jing Zhao1, 2, 3, 4, 5, Dongyan Han1, 2, 3, 4, 5
Affiliations
  • 1College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
  • 2National Distant-water Fisheries Engineering Research Center, Shanghai 201306, China
  • 3Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China
  • 4Key Laboratory of Oceanic Fisheries Exploitation, Ministry of Agriculture, Shanghai 201306, China
  • 5Scientific Observing and Experimental Station of Oceanic Fishery Resources, Ministry of Agriculture, Shanghai 201306, China
出版时间: 2021-04-25 doi: 10.12284/hyxb2021034
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长江口是众多洄游性鱼类重要的栖息场所,其复杂的环境条件影响着该水域水生生物的生长和繁殖过程。海洋环境监测浮标能够对诸多环境要素进行长期、连续、实时和大范围的监测,是现代海洋环境自动观测系统中的重要组成部分。为在长江口中华鲟自然保护区及其邻近水域组建合理有效的浮标监测网络,本研究基于海上实测调查数据,使用普通克里金法模拟了多种环境要素的空间分布,在此基础上比较了分层随机采样设计中不同分层方案和站点数量变化对监测效果的影响,结果显示:(1)盐度要素在层数为3的分层随机采样方法中采样精度更高,水温、溶解氧和化学需氧量要素在层数为2的采样设计中采样效果更好;(2)站点数越多,相对误差越集中并趋向于0,并当站点数多于30时,采样估测准确性逐渐趋于稳定;(3)各季节中,秋季盐度要素中层数为2的采样准确性更高;与其他3季以及总体相对误差结果相比,冬季化学需氧量要素的采样效果比其他3个季节要差。在今后长江口中华鲟自然保护区水域组建环境监测浮标网络时,建议采用3层的分层随机采样作为盐度监测的分层标准,且站点数量要大于50个;使用2层的分层随机采样作为其他多种水文环境要素监测的分层标准,且站点数量要大于30个。

长江口  /  环境监测  /  分层随机采样  /  站点数量  /  采样设计

The Changjiang River Estuary is an important habitat for many migratory fishes, and its complex environmental conditions affect the growth and reproduction of aquatic organisms in this area. Marine environmental monitoring buoys are capable of long-term, continuous, real-time and large-scale monitoring of many environmental factors, and are an important part of the modern marine environmental automatic observation system. To establish a reasonable and effective buoy monitoring network for the Chinese sturgeon nature reserve and its adjacent waters in the Changjiang River Estuary , this study used Ordinary Kriging (OK) method to simulate the spatial distribution of various environmental factors, and then compared the effects of different strata design and sample size of Stratified Random Sampling (StRS) on the monitoring results. The results showed that: (1) the sampling accuracy of salinity was better when the stratum of StRS was 3, and water temperature, dissolved oxygen and chemical oxygen demand (COD) was better when the stratum was 2; (2) the relative estimation errors became more concentrated and tended to 0 value with the increase of sample size, and when the sample size was larger than 30, the accuracy tended to be stable gradually; (3) the sampling accuracy of salinity in autumn was different to the other three seasons, and the sampling effect of COD in winter was worst. In the future, when setting up an environmental monitoring buoy network in the Chinese sturgeons nature reserve in the Changjiang River Estuary, it is suggest to adopt three stratum stratified random sampling for salinity monitoring, and the number of stations should be more than 50. When taking various hydrological environments as the monitoring target, it is recommended to use two stratified standard, and the number of stations should be more than 30.

Changjiang River Estuary  /  environmental monitoring  /  stratified random sampling  /  sample size  /  sampling design
潘邵媛, 王学昉, 田思泉, 童剑锋, 高春霞, 赵静, 韩东燕. 长江口中华鲟保护区海洋环境监测浮标站点的优化设计. 海洋学报, 2021 , 43 (4) : 55 -64 . DOI: 10.12284/hyxb2021034
Shaoyuan Pan, Xuefang Wang, Siquan Tian, Jianfeng Tong, Chunxia Gao, Jing Zhao, Dongyan Han. The design of the stations of marine environmental monitoring buoys in the Chinese sturgeon nature reserve in the Changjiang River Estuary[J]. Haiyang Xuebao, 2021 , 43 (4) : 55 -64 . DOI: 10.12284/hyxb2021034
河口生态系统是地球上极为重要的生态过渡区域,河口地区环境变化大,营养物质和饵料生物丰富,其生境变化对河口水生生物的栖息地研究十分重要[1-2]。随着全球气候变化和大量涉水工程的建设,长江口生物多样性和生态系统稳定性受到严重影响[3-6],其特殊的升温降盐变化过程也影响着该水域水生生物的生长和繁殖过程[7]。因此,为更好地对河口生态系统进行研究,需要准确监测长江口水文要素的变化。
海洋环境自动监测技术的发展提高了人类对海洋环境的监测、预测和预报能力,海洋监测浮标具有长期、连续、实时和范围大等优点,是现代海洋水文要素信息观测系统中的主要方式之一[8-10]。在组建以海洋监测浮标为站点的监测网络时,需要考虑不同的监测目标以及站点空间布局的合理性等因素[11-12]。因此,对浮标监测站点进行布局设计和数量优化是构建科学高效的监测网络的必要过程。
分层随机采样(Stratified Random Sampling,StRS)是渔业资源和生态调查中常见的调查设计之一[13],根据资源状况和水文环境的分布将研究区域划分为若干层,各层内的采样相互独立,从各层中随机挑选采样站点能够提高采样结果的精度和准确性[14-18]。因此,该采样设计中层数和站点数的确定是常见的优化内容,如韩青鹏等[19]比较了不同调查站位数量对定点采样与分层随机采样分析结果的影响,并对渤海多目标渔业资源调查的设计方案进行了优化;赵静等[20]比较了不同采样站点数下的分层采样设计对鱼类群落丰富度指数采样精度的影响。
目前,长江口中华鲟自然保护区及其邻近水域的海洋环境浮标监测站点的设计缺少样本量优化的过程[3],监测布局不够完善、功能不够齐全[4]。本研究通过普通克里金法(Ordinary Kriging,OK)模拟了该水域各项环境要素的空间分布,在此基础上比较了分层随机采样设计中的不同分层方案和站点数量变化对多种环境要素监测效果的影响,旨在为该水域海洋环境监测浮标组成的监测网络的发展改进提供参考依据。
环境监测数据源于长江口中华鲟自然保护区执行的综合性常规监测。调查水域为长江口中华鲟自然保护区及其邻近水域,在2015−2018年调查期间,每年春季(5月)、夏季(8月)、秋季(11月)和冬季(2月)进行4次定点调查。目前的监测调查共设置14个固定站点,按照地理位置将调查水域划分为北港 (Z1、Z3)、东滩 (Z6、Z9、Z14、Z16、Z17、Z18、Z19) 和北支 (Z4、Z5、Z7、Z13、Z15) 区域(图1)。监测内容包括多项水文物理环境要素和水化学环境要素,调查时使用WTW Multi 3430水质测试仪现场同步测定水温、盐度和溶解氧,以及通过采集水样带回实验室分析获取站点的化学需氧量(COD)要素。
在评估采样效果时,基于模型的方法充分考虑了调查目标的总体结构,能够将由模型获得的研究区域内调查目标的总体分布情况作为重采样的“真实值”(即潜在采样站点)[21-22]。在获取连续分布的环境要素时,空间插值方法能够用已知点的值来估算未知点的值,如普通克里金法就是常用于模拟研究的空间插值方法之一[23-26]
本研究中,将研究区域按照2′×2′的空间分辨率进行划分,去除不能进行的调查站点后,共产生160个潜在采样站点。使用基于高斯模型的普通克里金法获得整个研究区域内的水温、盐度、溶解氧和COD数据,为避免不同采样时间潮汐情况的差别,在模型分析时使用的全部为涨潮时的数据。交叉验证通过分别计算诊断统计量预测误差的算数平均值(Mean Error,ME)和均方根误差(Root Mean Square Error,RMSE),来评价插值结果的有效性[27-28]。ME和RMSE用于评价插值方法的精度,在结果中RMSE应首先被比较[29]。ME反映了插值方法的总体估计偏差[30],ME越接近于0,预测值越是无偏;RMSE可以量化观测密度和拟合密度之间的差异,RMSE越接近0值,表明插值方法的拟合更好[31]。各统计量计算公式分别为
${\rm{ME}} = \frac{{\rm{1}}}{n}\sum\limits_{i = 1}^n {\left[ {z\left( {{x_i}} \right) - {z^*}\left( {{x_i}} \right)} \right]}, $
${\rm{RMSE}} = \sqrt {\frac{1}{n}\sum\limits_{i = 1}^n {{{\left[ {z\left( {{x_i}} \right) - {z^*}({x_i})} \right]}^2}} } ,$
式中,$z\left( {{x_i}} \right)$${z^*}\left( {{x_i}} \right)$分别为${x_i}$点的观测值和预测值;n为样本数。
考虑长江口水域盐度的空间分布受潮汐和径流量影响,盐水入侵导致北支盐度始终高于南支,且北支盐度变化幅度也大于南支[32],因此根据盐度数据的插值结果对研究区域进行分层。研究中,依照2015−2018年平均盐度值空间分布将监测水域划分为2~3层,并采用最优分配法确定各层站点数(图2表1)。最优分配法中各层站点数量与该层的误差呈正比,可以求出方差最小时的站点数量[33],计算公式为
${n_h} = n\frac{{{w_h}{S_h}}}{{\displaystyle\sum\limits_{h = 1}^H {{w_h}{S_h}} }},$
${w_h} = \frac{{{N_h}}}{N},$
式中,${n_h}$为分配到h层中的站点数量;n为总站点数量;${w_h}$h层的权重;${S_h}$h层的样本方差;H为全部层数;${N_h}$h层可被采样的站点数量;N为全部潜在站点数。
分层随机采样的采样过程在R软件中进行模拟,对采样过程重复进行100次以获取平均效应。计算相对误差(Relative Estimation Error,REE)和相对偏差(Relative Bias,RB)比较采样设计的结果,REE反映了估算值的估测准确性,RB反映了估算值的偏差。两个统计值越接近0表示采样效果越好[34],计算公式为
${\rm{REE}} = \frac{{\sqrt {\dfrac{{\displaystyle\sum\limits_{i = 1}^N {{{\left( {V_i^{{\rm{estimated}}} - {V^{{\rm{true}}}}} \right)}^2}} }}{N}} }}{{{V^{{\rm{true}}}}}} \times 100{\text %}, $
${\rm{RB}} = \frac{{\dfrac{{\displaystyle\sum\limits_{i = 1}^N {\left( {V_i^{{\rm{estimated}}} - {V^{{\rm{true}}}}} \right)} }}{N}}}{{{V^{{\rm{true}}}}}} \times 100{\text %}, $
式中,${V^{{\rm{estimated}}}}$为某一采样方法的模拟估算平均值;${V^{{\rm{true}}}}$为对应的真实平均值;N为模拟次数 (N=100)。
交叉验证结果显示,基于高斯模型的普通克里金法获得的水温、溶解氧和COD要素插值结果ME和RMSE值都接近于0,模型较好地估测了调查区域内海洋环境数据的分布值,而盐度数据插值效果则相对较差(图3)。水温和溶解氧要素在全部调查中均获得了精度较高的插值结果,并且插值结果几乎无偏;COD要素的插值结果也几乎无偏,但2017年8月结果误差较大,产生了较大的RMSE值;盐度要素模型拟合的结果略差,产生了相对较大的误差和偏差。
两种分层方案中,随着样本数量的增加,各环境要素平均相对误差(REE)值越小,采样估测准确性越高(表2)。溶解氧数据的REE值最小,两种分层方案的采样设计效果均为最好;盐度数据的REE值最大,两种分层方案的采样设计效果相对较差。除盐度数据外,水温、溶解氧和COD要素中划分为两层的分层随机采样估测准确性更高,而盐度数据中则是划分为3层的估测准确性更高。随着站点数的增加,各环境要素在不同采样设计中的采样结果REE值集中趋势也越高(图4)。水温、溶解氧和COD要素中,REE值的下降趋势在站点数为10~30的区间内较为明显,当站点数增加到30个时,REE随站点下降的幅度开始明显变小。盐度数据中,当站点数增加到50个时,REE值下降幅度仍然很明显。
不同季节各环境要素采样结果的平均相对误差与总体REE值变化趋势一致,随着站点数的增加,采样效果越好,并当样本量大于30个时,采样估测准确性逐渐趋于稳定(图5)。水温数据在四季中的REE值都较小,但秋季REE值略高。虽然盐度数据的总体REE值显示层数为3的采样设计效果更好,但在秋季,层数为2的采样准确性则更高。溶解氧数据在各季节不同采样设计效果相近,REE值最小,采样效果最优。COD数据在冬季的REE值最高,其中层数为3的分层随机采样在该季节所有采样设计中表现最差。
随着站点数的增加,各环境要素采样结果的平均相对偏差(RB)未表现出一致的变化趋势,当样本量增加到50个时,所有采样设计估计值都几乎无偏(表3)。水温和溶解氧要素的采样偏差最小,并且当站点数大于20个时,采样结果几乎无偏;盐度要素的平均RB值较大,层数为3且站点数为10的采样结果偏差最大,层数为3且站点数为50个的采样结果偏差最小;COD数据中,在分层数为2且站点数大于30个和分层数为3且站点数大于20个时,采样结果RB值均接近0。不同设计方案的分层随机采样效果几乎无偏,并且站点数量越多,数据集中趋势也越高(图6)。水温、溶解氧和COD的采样结果RB值均集中在0值附近,盐度数据的采样结果偏差离散程度则相对较大。
除盐度数据外,不同季节各环境要素采样结果的平均RB值均接近0,采样效果无偏,但随着站点数的增加,RB值无一致性变化趋势(图7)。盐度数据中,春季和夏季站点数小于20个时的采样偏差较大,秋季和冬季则相对较小。
本研究基于模型的方法,比较了分层随机采样中不同分层方案和站点数量的变化对长江口水温、盐度、溶解氧和COD等要素监测效果的影响。基于模型的方法可以获取这些要素的总体结构,但模型中的不同假设会影响模型的预测精度和准确性。因此,在评价不同采样设计的有效性时,还需要考虑影响模型预测性能的各种因素,通过比较以确定在某一具体研究中所需的最合适的方法。譬如,克里金法提供了最好的线性无偏估计[35],充分考虑了测量点之间的空间关系和空间相关性,但它在数据量较小时的预测可能会出现较大的偏差[36]。本研究中,对于空间分布变化趋势小的水温、溶解氧和COD要素,基于高斯模型的普通克里金法较好地估测了整个调查区域内的空间分布状况。但在空间分布变化大的盐度数据中,由于目前监测调查中站点的布局及数量等问题,导致插值效果较差。
通常认为,分层随机采样根据资源和环境的分布特征,可以将采样区域划分为不同的层次,能够提高采样结果的精度和准确性[15-16]。但针对不同的监测目标,如果分层方案不合适,估测的数据质量可能比简单随机采样调查更差[37]。本研究考虑了长江口区域盐度受潮汐和径流量的影响造成的显著空间分布差异[38],将研究区域根据盐度要素的空间分布状况分为2层和3层。在将研究区域划分为3层时,尽管盐度要素的采样精度提高,但水温、溶解氧和COD要素的采样效果反而比划分为2层时的更差。根据盐度要素空间分布作为分层随机采样中的分层依据,可能影响了其他环境要素监测站点的空间布局合理性,导致采样效果变差。
此外,环境要素的季节性变化也可能会造成采样效果的差异。比较各季度的平均相对误差发现,秋季盐度要素中层数为2的采样准确性更高,与其他3季以及总体相对误差结果存在区别;冬季COD要素的采样效果比其他3个季节要差。径流大小、汊道分流比、潮汐强弱和地形条件是导致环境要素出现时空变化的重要因素,长江口径流的洪(5−10月)、枯(11月至翌年4月)期变化显著,这可能造成一些与径流量有关的因素出现了季节性的变化[38-39]
在海洋环境监测中,不同的监测目标可能导致站点数量的选择存在差别,因此需要对采样设计的有效性和数据质量进行评估[40-44]。随机采样的过程是无偏的,当站点数增加到50个时,所有采样设计估计值都几乎无偏。随着站点数的增加,两种分层方案采样结果的相对偏差值分布更集中,相对误差都逐渐减小。当站点数大于30个时,水温、溶解氧和COD要素采样结果的相对误差逐渐趋于稳定,盐度要素相对误差值仍存在明显的下降趋势。
海洋监测浮标技术具较好的精度和时效性,能够实现对海洋水文环境要素信息实时和自动化地观测,是现在及未来我国海洋水文自动化监测调查的重要技术手段之一[10]。另一方面,监测成本是任何监测项目都需要考虑的因素,达到站点数量和更高观测精度的平衡,也是监测网络优化设计的一个重要内容。本研究为长江口中华鲟自然保护区及其邻近水域的海洋环境浮标监测网络的布局设计和优化提供了一种参考依据,同时也为保护区内国家级海洋牧场示范区的自动化监测设计提供了方法。我们建议采用3层的分层随机采样作为盐度监测的分层标准,且站点数量要大于50个;使用2层的分层随机采样作为其他多种水文环境要素监测的分层标准,且站点数量要大于30个。
  • 上海市科委地方能力建设项目(18050502000);上海市长江口海域国家级海洋牧场建设项目(NY2017002);上海市长江口中华鲟资源调查和保护项目(NY2018001)。
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2021年第43卷第4期
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doi: 10.12284/hyxb2021034
  • 接收时间:2020-06-20
  • 首发时间:2026-02-26
  • 出版时间:2021-04-25
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  • 收稿日期:2020-06-20
  • 修回日期:2020-10-10
基金
上海市科委地方能力建设项目(18050502000);上海市长江口海域国家级海洋牧场建设项目(NY2017002);上海市长江口中华鲟资源调查和保护项目(NY2018001)。
作者信息
    1上海海洋大学 海洋科学学院,上海 201306
    2国家远洋渔业工程技术研究中心,上海 201306
    3大洋渔业资源可持续开发教育部重点实验室,上海 201306
    4农业部大洋渔业开发重点实验室,上海 201306
    5农业部大洋渔业资源环境科学观测实验站,上海 201306

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田思泉(1978-),男,安徽省无为市人,教授,研究方向为海洋渔业资源调查监测等。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
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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