Article(id=1211299025668666161, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1211299024825611053, articleNumber=null, orderNo=null, doi=10.12284/hyxb2023038, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1649520000000, receivedDateStr=2022-04-10, revisedDate=1665504000000, revisedDateStr=2022-10-12, acceptedDate=null, acceptedDateStr=null, onlineDate=1766725792566, onlineDateStr=2025-12-26, pubDate=1677600000000, pubDateStr=2023-03-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1766725792566, onlineIssueDateStr=2025-12-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1766725792566, creator=13701087609, updateTime=1766725792566, updator=13701087609, issue=Issue{id=1211299024825611053, tenantId=1146029695717560320, journalId=1149651085930835976, year='2023', volume='45', issue='3', pageStart='1', pageEnd='158', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1766725792365, creator=13701087609, updateTime=1766924576395, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1212132785515532522, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1211299024825611053, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1212132785515532523, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1211299024825611053, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=76, endPage=83, ext={EN=ArticleExt(id=1211299026880820020, articleId=1211299025668666161, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Study on the population distribution of Acanthaster planci in the reef area of the Xisha Islands based on environmental DNA technology, columnId=1194652705852465724, journalTitle=Haiyang Xuebao, columnName=Article, runingTitle=null, highlight=null, articleAbstract=

Acanthaster planci, one of the predators of reef-building corals, has attracted much attention for its catastrophic damage to coral reef ecosystems. However, the spatial and temporal distribution characteristics of A. planci are still unclear in the coral reef ecosystem of the South China Sea. In this study, using environmental DNA and real-time quantitative PCR techniques, we analyzed the concentration variation of the mitochondrial cytochrome-c-oxidase subunits I (COTS-mtCOI) fragment of A. planci in the surface seawater of the Xisha Islands in September 2020, April 2021 and January 2022, and the correlations between the concentration variation with environmental factors such as seawater temperature, salinity, pH, chlorophyll content, nutrients content and other environmental factors. The results showed that COTS-mtCOI fragment concentration in the Xisha Islands varied from 0 copies/m3 to 4.13×107 copies/m3 during 2020−2022, and there were always higher concentrations in the Yongle Atoll. For Huaguang Reef, Jinqing Islands, Lingyang Reef, Quanfu Island and Zhaoshu Island, the average concentration of COTS-mtCOI fragment in September 2020 was significantly (p<0.05) higher than those in April 2021 and January 2022. In addition, COTS-mtCOI fragment concentration was significantly (p<0.05) positively correlated with surface seawater temperature. These results suggest that the population of A. planci is widely distributed in the seawater of Xisha Islands, and higher density of A. planci could appear in Yongle Atoll. Moreover, ocean warming may accelerate the outbreak of A. planci. This study is helpful to understand the population distribution characteristics of A. planci in the coral reef ecosystems of the South China Sea, and can provide a theoretical basis for the early warning and forecast of the A. planci outbreak.

, correspAuthors=Zhongjie Wu, Zhi Zhou, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2023 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=Zhicong Yan, Jiajie Xing, Wenqi Cai, Kaidian Zhang, Zhongjie Wu, Yuanchao Li, Jia Tang, Zhi Zhou), CN=ArticleExt(id=1211299028113945427, articleId=1211299025668666161, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=基于环境DNA技术的西沙礁区长棘海星种群丰度研究, columnId=1149698756456657529, journalTitle=海洋学报, columnName=论文, runingTitle=null, highlight=null, articleAbstract=

长棘海星(Acanthaster planci)作为珊瑚的天敌之一,因其对珊瑚礁生态系统的灾难性破坏而备受关注。然而,长棘海星在南海珊瑚礁生态系统中的时空分布特征仍不清楚。本研究于2020年9月、2021年4月和2022年1月对西沙群岛礁区表层海水进行取样,借助环境DNA(environmental DNA)和实时荧光定量PCR技术分析了表层海水中长棘海星线粒体细胞色素-c-氧化酶亚基I(COTS-mtCOI)基因片段浓度的时空变化,及其与海水温度、盐度、pH、叶绿素含量和营养盐含量等环境因子的相关性。结果发现,2020−2022年,西沙礁区COTS-mtCOI片段浓度的变化范围为0~4.13×107 拷贝数/m3,且永乐环礁附近一直有较高的COTS-mtCOI片段浓度。对于华光礁、晋卿岛、羚羊礁、全富岛和赵述岛而言,2020年9月表层海水中COTS-mtCOI片段的平均浓度显著高于2021年4月和2022年1月(p<0.05)。此外,COTS-mtCOI片段浓度与表层海水的温度显著正相关(p<0.05)。研究结果表明,当前长棘海星群体广泛分布于我国西沙群岛海域,永乐环礁可能分布着较高密度的长棘海星群体,水温升高可能促进长棘海星的暴发。本研究有助于了解南海珊瑚礁生态系统中长棘海星的种群分布特征,同时也能够对长棘海星暴发的预警预报提供理论依据。

, correspAuthors=吴钟解, 周智, authorNote=null, correspAuthorsNote=
*吴钟解(1981-),男,副研究员,硕士生导师,主要从事珊瑚礁生态学研究。E-mail:;
周智(1983-),男,研究员,博士生导师,主要从事珊瑚礁生物学研究。E-mail:
, copyrightStatement=版权所有©《海洋学报》编辑部 2023, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=BulOUQWGnH8Y4VlhVLqjbg==, magXml=IQT/MnozJZLOODhZYLhfvQ==, pdfUrl=null, pdf=WeVaMXPE70prVGS9gy3rDA==, pdfFileSize=1638371, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=gSZZbzQCzRanD/d8dQEaqg==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=WPjVAxhNtNw43C7WoTu/nQ==, mapNumber=null, authorCompany=null, fund=null, authors=

闫智聪(1999-),男,山西省运城市人,主要从事珊瑚礁保护研究。E-mail:

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闫智聪(1999-),男,山西省运城市人,主要从事珊瑚礁保护研究。E-mail:

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闫智聪(1999-),男,山西省运城市人,主要从事珊瑚礁保护研究。E-mail:

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tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299025668666161, language=EN, label=Fig. 5, caption=Changes of COTS-mtCOI fragment concentration in the surface seawater of Huaguang Reef, Jinqing Island, Lingyang Reef, Quanfu Island and Zhaoshu Island reef areas

a. Mean concentration changes of COTS-mtCOI fragment in the five reef areas over time; b. concentration changes of COTS-mtCOI fragment of individual reef areas over time; * and different letters indicate COTS-mtCOI fragment concentration in the same date and in the different date of the same sampling stations significant differences (p<0.05)

, figureFileSmall=4y6z91lMgj5PVLPYVmV2KA==, figureFileBig=3Lln2LvR7XtJlWgpUADGVg==, tableContent=null), ArticleFig(id=1215304256308040398, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299025668666161, language=CN, label=图5, caption=华光礁、晋卿岛、羚羊礁、全富岛和赵述岛表层海水中COTS-mtCOI片段浓度的变化

a. 5个礁区COTS-mtCOI片段平均浓度随时间的变化;b. 各个礁区COTS-mtCOI片段浓度随时间的变化;*和不同字母分别表示不同日期和相同站点不同日期COTS-mtCOI片段浓度存在显著差异(p<0.05)

, figureFileSmall=4y6z91lMgj5PVLPYVmV2KA==, figureFileBig=3Lln2LvR7XtJlWgpUADGVg==, tableContent=null), ArticleFig(id=1215304256412898001, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299025668666161, language=EN, label=Fig. 6, caption=Correlation between water quality parameters of the surface seawater and COTS-mtCOI fragment concentration of Xisha Islands reef area

* Indicates a significant positive correlation (p<0.05)

, figureFileSmall=eAZMr1a/IluFuTFx6+KrSA==, figureFileBig=CE1yiZFiC74+m4jQ34yy7g==, tableContent=null), ArticleFig(id=1215304256521949910, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299025668666161, language=CN, label=图6, caption=西沙群岛各礁区表层海水水质指标和COTS-mtCOI片段浓度的相关性

*表示存在显著正相关(p<0.05)

, figureFileSmall=eAZMr1a/IluFuTFx6+KrSA==, figureFileBig=CE1yiZFiC74+m4jQ34yy7g==, tableContent=null), ArticleFig(id=1215304256639390425, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299025668666161, language=EN, label=Table 1, caption=

Method for analysis of seawater quality indexes

, figureFileSmall=null, figureFileBig=null, tableContent=
水质指标检测方法
温度表层水温表法
pHpH计法
盐度盐度计法
氨氮含量靛酚蓝分光光度法
亚硝酸盐氮含量盐酸萘乙二胺分光光度法
硝酸盐氮含量锌镉还原法
活性磷酸盐含量磷钼蓝分光光度法
无机磷含量过硫酸钾氧化法
石油含量分析紫外分光光度法
叶绿素含量荧光光度法
悬浮物含量重量法
), ArticleFig(id=1215304256740053725, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1211299025668666161, language=CN, label=表1, caption=

各海水水质指标的检测方法

, figureFileSmall=null, figureFileBig=null, tableContent=
水质指标检测方法
温度表层水温表法
pHpH计法
盐度盐度计法
氨氮含量靛酚蓝分光光度法
亚硝酸盐氮含量盐酸萘乙二胺分光光度法
硝酸盐氮含量锌镉还原法
活性磷酸盐含量磷钼蓝分光光度法
无机磷含量过硫酸钾氧化法
石油含量分析紫外分光光度法
叶绿素含量荧光光度法
悬浮物含量重量法
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基于环境DNA技术的西沙礁区长棘海星种群丰度研究
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闫智聪 1 , 邢家杰 1 , 蔡文启 1, 2 , 张开典 1 , 吴钟解 2, * , 李元超 2 , 唐佳 1 , 周智 1, *
海洋学报 | 论文 2023,45(3): 76-83
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海洋学报 | 论文 2023, 45(3): 76-83
基于环境DNA技术的西沙礁区长棘海星种群丰度研究
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闫智聪1 , 邢家杰1, 蔡文启1, 2, 张开典1, 吴钟解2, * , 李元超2, 唐佳1, 周智1, *
作者信息
  • 1 海南大学 海洋学院,海南 海口 570228
  • 2 海南省海洋与渔业科学研究院,海南 海口 571126
  • 闫智聪(1999-),男,山西省运城市人,主要从事珊瑚礁保护研究。E-mail:

通讯作者:

*吴钟解(1981-),男,副研究员,硕士生导师,主要从事珊瑚礁生态学研究。E-mail:;
周智(1983-),男,研究员,博士生导师,主要从事珊瑚礁生物学研究。E-mail:
Study on the population distribution of Acanthaster planci in the reef area of the Xisha Islands based on environmental DNA technology
Zhicong Yan1 , Jiajie Xing1, Wenqi Cai1, 2, Kaidian Zhang1, Zhongjie Wu2, * , Yuanchao Li2, Jia Tang1, Zhi Zhou1, *
Affiliations
  • 1College of Marine Sciences, Hainan University, Haikou 570228, China
  • 2Hainan Academy of Ocean and Fisheries Sciences, Haikou 571126, China
出版时间: 2023-03-01 doi: 10.12284/hyxb2023038
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长棘海星(Acanthaster planci)作为珊瑚的天敌之一,因其对珊瑚礁生态系统的灾难性破坏而备受关注。然而,长棘海星在南海珊瑚礁生态系统中的时空分布特征仍不清楚。本研究于2020年9月、2021年4月和2022年1月对西沙群岛礁区表层海水进行取样,借助环境DNA(environmental DNA)和实时荧光定量PCR技术分析了表层海水中长棘海星线粒体细胞色素-c-氧化酶亚基I(COTS-mtCOI)基因片段浓度的时空变化,及其与海水温度、盐度、pH、叶绿素含量和营养盐含量等环境因子的相关性。结果发现,2020−2022年,西沙礁区COTS-mtCOI片段浓度的变化范围为0~4.13×107 拷贝数/m3,且永乐环礁附近一直有较高的COTS-mtCOI片段浓度。对于华光礁、晋卿岛、羚羊礁、全富岛和赵述岛而言,2020年9月表层海水中COTS-mtCOI片段的平均浓度显著高于2021年4月和2022年1月(p<0.05)。此外,COTS-mtCOI片段浓度与表层海水的温度显著正相关(p<0.05)。研究结果表明,当前长棘海星群体广泛分布于我国西沙群岛海域,永乐环礁可能分布着较高密度的长棘海星群体,水温升高可能促进长棘海星的暴发。本研究有助于了解南海珊瑚礁生态系统中长棘海星的种群分布特征,同时也能够对长棘海星暴发的预警预报提供理论依据。

珊瑚礁  /  长棘海星  /  环境DNA  /  海水温度

Acanthaster planci, one of the predators of reef-building corals, has attracted much attention for its catastrophic damage to coral reef ecosystems. However, the spatial and temporal distribution characteristics of A. planci are still unclear in the coral reef ecosystem of the South China Sea. In this study, using environmental DNA and real-time quantitative PCR techniques, we analyzed the concentration variation of the mitochondrial cytochrome-c-oxidase subunits I (COTS-mtCOI) fragment of A. planci in the surface seawater of the Xisha Islands in September 2020, April 2021 and January 2022, and the correlations between the concentration variation with environmental factors such as seawater temperature, salinity, pH, chlorophyll content, nutrients content and other environmental factors. The results showed that COTS-mtCOI fragment concentration in the Xisha Islands varied from 0 copies/m3 to 4.13×107 copies/m3 during 2020−2022, and there were always higher concentrations in the Yongle Atoll. For Huaguang Reef, Jinqing Islands, Lingyang Reef, Quanfu Island and Zhaoshu Island, the average concentration of COTS-mtCOI fragment in September 2020 was significantly (p<0.05) higher than those in April 2021 and January 2022. In addition, COTS-mtCOI fragment concentration was significantly (p<0.05) positively correlated with surface seawater temperature. These results suggest that the population of A. planci is widely distributed in the seawater of Xisha Islands, and higher density of A. planci could appear in Yongle Atoll. Moreover, ocean warming may accelerate the outbreak of A. planci. This study is helpful to understand the population distribution characteristics of A. planci in the coral reef ecosystems of the South China Sea, and can provide a theoretical basis for the early warning and forecast of the A. planci outbreak.

coral reef  /  Acanthaster planci  /  environmental DNA  /  seawater temperature
闫智聪, 邢家杰, 蔡文启, 张开典, 吴钟解, 李元超, 唐佳, 周智. 基于环境DNA技术的西沙礁区长棘海星种群丰度研究. 海洋学报, 2023 , 45 (3) : 76 -83 . DOI: 10.12284/hyxb2023038
Zhicong Yan, Jiajie Xing, Wenqi Cai, Kaidian Zhang, Zhongjie Wu, Yuanchao Li, Jia Tang, Zhi Zhou. Study on the population distribution of Acanthaster planci in the reef area of the Xisha Islands based on environmental DNA technology[J]. Haiyang Xuebao, 2023 , 45 (3) : 76 -83 . DOI: 10.12284/hyxb2023038
珊瑚礁生态系统是全球初级生产力最高的生态系统之一,其具有十分显著的生态价值,被称为“海洋中的热带雨林”[1]。近年来,长棘海星(Acanthaster planci)的大规模暴发成为珊瑚礁退化的主要原因之一[2-3]。长棘海星主要分布于印度洋−太平洋区的热带珊瑚礁海域中[4-5],主要捕食造礁石珊瑚,其存在已成为许多地区,尤其是中太平洋和西太平洋的造礁石珊瑚覆盖率持续下降的主要原因之一[6-7]。据统计,1985−2012年期间,澳大利亚大堡礁的珊瑚覆盖率下降了约50%,其中约42%可归因于长棘海星的暴发[8]。2007−2009年,我国西沙群岛的珊瑚礁因长棘海星的大规模暴发而遭到严重的破坏,造礁石珊瑚覆盖率甚至降到1%以下[9-10]。长棘海星的暴发已经成为珊瑚礁生态系统的大灾难,严重阻碍了珊瑚礁生态系统的保护和恢复工作。为有效控制长棘海星暴发,加强对长棘海星的调查监测和预警预报刻不容缓。
长棘海星的传统监测主要通过断面监测和截线样点的人工水下调查[11]。传统监测方法对于隐蔽性好、扩散范围广的长棘海星成体和幼体存在局限性,当发现长棘海星成体大量出现时,珊瑚礁生态系统已经开始遭到严重的破坏。长棘海星的暴发预警也可以通过海水中长棘海星幼虫的监测实现,但对于长棘海星幼虫的形态学鉴定非常困难,需要分子生物学技术的辅助。Suzuki等[12]从浮游生物样品中分离了可能是长棘海星的幼虫,并对这些样品进行了基因验证,证实了日本冲绳的Sekisei澙湖存在高密度的长棘海星幼虫(53.3只/m3),提示该海域可能暴发长棘海星。Doyle等[13]采用荧光定量技术定量了大堡礁周围的长棘海星幼虫,为该海域长棘海星的分布特征提供了基础数据。此外,张颖等[14]设计了针对长棘海星幼体的引物,用于检测是否存在长棘海星幼体,但无法进行准确定量。目前,长棘海星的监测工作无疑耗费了大量的人力物力,亟需一种准确且高效的检测方法,为礁区长棘海星暴发早期阶段提供关键信息。近些年,随着分子生物学技术的不断发展,环境DNA(environmental DNA, eDNA)技术已经成为一种生物和生态多样性监测的新手段[15-16]。eDNA技术是指从环境样品中直接提取DNA,并对该DNA进行定量或者定性分析[17-18]。Kwong等[19]研究表明,长棘海星环境DNA的降解速率较快,因此环境DNA监测结果能够反应近期当地长棘海星群体(包括成体、幼体和幼虫)的分布状况。
西沙群岛珊瑚礁生态系统拥有我国现存珊瑚礁群落中最原始、最典型的珊瑚礁群落,也是我国近海海域保存相对完好的珊瑚礁区域[2]。近年来,我国学者开始关注珊瑚礁区的长棘海星,并进行相关研究。例如,赵思佳等[20]的研究揭示了长棘海星对重金属的富集具有组织差异性,且海星能够通过生物富集和放大效应累积Zn、As和Cd。我国学者在长棘海星幼虫的检测和培养方面也开展了初步研究:张颖等[14]借助分子生物学技术检测到我国西沙七连屿海域存在长棘海星幼体;Tian等[21]在实验室内繁育并培养了长棘海星幼虫。此外,长棘海星暴发的原因和治理也得到国内学者的关注:李元超等[22]对近15年西沙群岛长棘海星的暴发周期及暴发原因进行了分析,并提出了防治措施;Chen等[23]的研究表明营养盐和洋流对于南海长棘海星的遗传结构和幼虫扩散具有重要意义。但是,对西沙群岛礁区长棘海星群体分布的相关了解仍十分有限。本研究于2020年9月、2021年4月和2022年1月采集西沙群岛礁区表层海水样本,并采用环境DNA技术检测了长棘海星线粒体细胞色素-c-氧化酶亚基I(COTS-mtCOI)基因片段浓度的时空分布。采样期间,我们在部分礁区观察到高密度的长棘海星成体。本研究旨在阐明西沙群岛珊瑚礁生态系统中长棘海星的分布特征。研究结果有助于了解西沙群岛长棘海星的物种丰度及其时空变化,对于开展长棘海星的常态化监测和预警具有重要意义。
分别于2020年9月、2021年4月和2022年1月取样西沙群岛不同站点的表层海水。2020年9月设置5个取样站点,包括华光礁、晋卿岛、羚羊礁、全富岛、赵述岛;2021年4月与2022年1月设置相同的26个取样站点,包括华光礁、晋卿岛、羚羊礁、全富岛、赵述岛、永兴岛、北岛、东岛、琛航岛、中建岛、盘石屿、金银岛、甘泉岛、珊瑚岛、鸭公岛、银屿、石屿、南沙洲、浪花礁、西沙洲、筐仔沙洲、玉琢礁、北礁、银砾滩、高尖石、永乐龙洞(图1)。银砾滩、高尖石、筐仔沙洲和永乐龙洞仅有1个取样礁区,其他站点包含至少2个间隔较远的取样礁区,上述所有礁区均取3个生物学重复的水样(取样水深:0.8~40.2 m)。为提高长棘海星环境DNA的检出率,以更加全面评估不同站点附近的长棘海星种群丰度,后续的数据处理以站点为单位进行统计分析。
使用加重型有机玻璃采水器(科析仪器,中国)采集4 L表层海水,用于水质检测分析和COTS-mtCOI片段浓度的定量。具体来说,用孔径为0.2 μm聚碳酸酯膜(Merck Millipore公司,美国)过滤3 L海水,然后将滤膜置于含有DNA lysis buffer(10 mmol/L Tris-HCl pH 8.0,0.5% SDS,100 mmol/L EDTA pH 8.0)的离心管中并于−20℃冰箱保存,用于后续的DNA提取和COTS-mtCOI片段浓度的定量。剩余1 L海水的固定和运输方法具体参照《海洋监测规范第4部分》(GB 17378.4−2007)[24]
严格按照《海洋监测规范第4部分》(GB 17378.4−2007)[24]检测了取样海水的水质指标,包括温度、pH、盐度、无机磷含量、亚硝酸盐氮含量、硝酸盐氮含量、氨氮含量、无机氮含量(硝酸盐氮、亚硝酸盐氮和氨氮含量之和)、叶绿素含量、悬浮物含量、活性磷酸盐含量和石油含量。各海水水质指标的检测方法详见表1
采用DNA Clean & Concentrator试剂盒(Zymo Research,美国)提取和纯化上述过滤海水滤膜中的总DNA[25],接着采用Nanodrop微量紫外分光光度计和琼脂糖凝胶电泳法测定其浓度、纯度及完整性。检测合格的海水环境DNA在−80℃下保存。
采用实时荧光定量技术和绝对定量方法定量环境DNA中的COTS-mtCOI片段浓度。首先提取长棘海星的DNA(该长棘海星于2020年9月份采自西沙礁区,置于−20℃冰箱中运回实验室,解剖获得腕中部的皮下肌肉层并提取DNA),PCR扩增COTS-mtCOI片段并构建含该片段的质粒。扩增引物F:5'-TCCGACTACCCGGACGCCTATAC-3';R:5'-AGTGGTTCGCTGGGAAGTGAAGG-3' [13]。扩增体系:2.5 μL 10×PCR Buffer,2 μL dNTP(2.5 mmol/L),1 μL引物F(10 μmol/L),1 μL引物R(10 μmol/L),1 μL DNA模板,0.15 μL rTaq,17.35 μL DEPC水。扩增条件:95℃ 5 min,35个循环(95℃ 30 s,60℃ 30 s,72℃ 30 s),72℃ 10 min,4℃保存。PCR扩增产物经1%琼脂糖凝胶电泳检测后,用SanPrep柱式DNA胶回收试剂盒(生工生物工程有限公司,中国)将目的片段进行回收纯化,再连接到pMD19-T载体(Takara,中国)后转化至Trans5α感受态细胞(全式金生物技术有限公司,中国)。挑选单克隆菌落并测序验证阳性菌株,过夜培养后采用SanPrep柱式DNA小量抽提试剂盒(生工生物工程有限公司,中国)提取含有COTS-mtCOI片段的质粒,采用Nanodrop微量紫外分光光度计测定抽提质粒的浓度,最后计算COTS-mtCOI片段的浓度。
制备COTS-mtCOI梯度浓度(10~106 拷贝数/μL)的质粒模板后,采用实时荧光定量PCR仪(朗基Q2000B型,中国)扩增质粒模板和海水环境DNA模板中的COTS-mtCOI片段,同时设定3个空白对照。反应体系:10 μL TB Green Premix Ex Taq Ⅱ(Takara,中国),0.8 μL引物F(10 μmol/L,序列同上),0.8 μL引物R(10 μmol/L,序列同上),2 μL DNA模板(总量<100 ng),6.4 μL DEPC水。反应条件:95℃ 30 s,40个循环(95℃ 5 s,65℃ 30 s),熔解曲线的温度从60℃升高至95℃。根据Ct值(每个反应管内的荧光信号到达设定的域值时所经历的循环数,Ct值≤35为阳性)与质粒模板中COTS-mtCOI片段浓度的对数值成反比线性关系,绘制标准曲线(R2>0.99),然后计算海水环境DNA中含有的COTS-mtCOI片段浓度[26]
所有数据均以平均值±标准差表示,统计分析在IBM SPSS Statistics 20软件中完成。通过非参数Kruskal-Wallis检验不同取样点或不同取样时间COTS-mtCOI片段浓度的差异。采用Spearman分析海水中COTS-mtCOI片段浓度和水质参数间的相关性,以p<0.05代表差异具有统计学意义。
2020−2022年各礁区站点表层海水中的COTS-mtCOI片段浓度如图2图4所示。2020年9月,羚羊礁的COTS-mtCOI片段浓度最高(7.58×106 拷贝数/m3),华光礁、晋卿岛、全富岛和赵述岛中的COTS-mtCOI片段浓度相近(2.44×106~2.83×106 拷贝数/m3)(图2)。2021年4月,鸭公岛、琛航岛和东岛礁区表层海水中的COTS-mtCOI片段浓度高于2.00×107 拷贝数/m3,永兴岛、浪花礁、甘泉岛、高尖石和全富岛次之(3.54×106~6.59×106 拷贝数/m3),而在华光礁、永乐龙洞、石屿和中建岛礁区均未检测到COTS-mtCOI片段(图3)。2022年1月,COTS-mtCOI片段的最高浓度(1.89×107 拷贝数/m3)出现在石屿礁区,在其他礁区均低于5×106拷贝数/m3图4)。
连续3年检测了华光礁、晋卿岛、羚羊礁、全富岛和赵述岛礁区表层海水中的COTS-mtCOI片段浓度。2020年9月份上述5个礁区的平均COTS-mtCOI片段平均浓度显著高于2021年4月和2022年1月(p<0.05,图5a)。对于华光礁和晋卿岛而言,2020年9月表层海水中COTS-mtCOI片段浓度显著高于2021年4月(p<0.05),而与2022年1月无显著差异(p>0.05)。对于羚羊礁和赵述岛而言,2020年9月表层海水中COTS-mtCOI片段浓度显著高于2021年4月和2022年1月(p<0.05,图5b)。
西沙群岛各礁区表层海水水质指标和COTS-mtCOI片段浓度的相关性如图6所示,COTS-mtCOI浓度与表层水温显著正相关(ρ=0.348,p<0.05),而与其他指标无显著相关性(p>0.05)。
长棘海星对珊瑚礁生态系统造成的破坏不容小觑,然而南海礁区长棘海星群体相关的监测调查却鲜有报道。本研究调查了西沙礁区中COTS-mtCOI片段浓度的时空分布变化,以及其与海水水质指标的关系。
已有研究表明,西沙群岛的长棘海星暴发周期大约为15年,这15年又可分为两个阶段,依次为5年左右的长棘海星破坏期和10年左右的珊瑚恢复期[11]。西沙群岛珊瑚礁海域长棘海星上一次大规模暴发时间为2006−2010年[11],提示西沙群岛可能正在发生新一轮的长棘海星暴发。本研究检测了2020−2022年西沙群岛不同礁区表层海水中的COTS-mtCOI片段浓度,在大部分礁区均检测到目的片段,浓度范围为0~4.13×107 拷贝数/m3,最高浓度出现在永乐环礁东部的羚羊礁。采用传统方法的现场调查发现,在2020年9月的羚羊礁和赵述岛,2021年4月的西沙洲、东岛、鸭公岛和北礁,以及2022年1月的银屿、珊瑚岛、羚羊礁、金银岛和北礁均监测到多于其他礁区的长棘海星成体。但是,本研究在大部分礁区均检测到COTS-mtCOI片段,传统方法和环境DNA方法存在差异的原因可能是:长棘海星的幼体和幼虫也能够在环境中遗留COTS-mtCOI片段,传统方法仅聚焦于长棘海星成体的调查;长棘海星成体隐蔽性好、扩散范围广,传统方法存在局限性。本研究发现,较高COTS-mtCOI片段浓度均出现在永乐环礁,表明该海域可能具有高密度的长棘海星群体。此外,永乐环礁中长棘海星种群丰度的最高值随时间的变化而出现在不同的岛屿,提示长棘海星种群丰度具有一定的可变性。现有的研究表明影响长棘海星群体分布主要原因包括:对长棘海星幼虫和成体的捕食压力减少[22, 27]、食物增加促进长棘海星幼虫的增加[28]、洋流[14]和人工清理等。由于本研究的局限性,造成永乐环礁存在高密度长棘海星群体的原因,以及长棘海星种群丰度的最高值随时间变化而出现在永乐环礁中不同岛屿的原因还需要进一步探究,未来需要结合多种学科和多种技术手段查明我国长棘海星群体地理分布差异的原因。综上,当前长棘海星群体广泛分布于我国西沙群岛海域,且永乐环礁可能具有高密度的长棘海星群体。
持续3年对华光礁、晋卿岛、羚羊礁、全富岛和赵述岛礁区表层海水中的COTS-mtCOI片段浓度进行检测,发现2020年9月西沙群岛表层海水中的平均COTS-mtCOI片段浓度为3.93×106拷贝数/m3,其数值显著高于2021年4月和2022年1月。这种显著性差异可归因于2020年9月的海水高温,当时调查海域的平均海水温度为30.76℃,最低温度为30.40℃,最高温度为31.15℃,而2021年4月和2022年1月的平均温度为27.00℃,温度范围为25.70~28.25℃。Johnson和Babcock[29]提到了温度升高在长棘海星暴发中的作用,大堡礁中长棘海星的暴发开始于温度较高的北部,而在温度较低的南部海域具有较少频率及较小规模的暴发。温度的季节性变化可能是造成COTS-mtCOI片段浓度存在时间差异的主要原因,相关性分析的结果也证实了该猜想。对于同一季节,温度是否影响长棘海星的种群大小,还需要进行野外和室内模拟实验的充分验证。此外,长棘海星为雌雄异体,海水温度高于28℃时开始繁殖,雌体长棘海星单次产卵量可达300万枚[12, 22]。Tian等[21]的研究表明,中国长棘海星产卵主要发生在8月份,张颖等[14]推测南海长棘海星在9月份和10月份仍能够产卵受精。2022年9月检测到较高的COTS-mtCOI片段浓度也可能与长棘海星繁殖进而造成群体规模增大有关。本研究并未观察到COTS-mtCOI片段浓度和营养盐及叶绿素含量的显著相关性,表明长棘海星可能比之前认为的更能适应低食物水平。类似地,Wolfe等[30]的研究也表明长棘海星种群暴发的开始可能并不需要富营养化条件。然而,Fabricius等[28]的研究表明浮游植物含量可能是造成长棘海星暴发的关键因素,未来需要进一步探究造成该差异的原因。总体而言,我国西沙群岛长棘海星的分布存在明显的时间差异,季节性的水温变化可能是造成该差异的原因之一。
本研究调查了西沙群岛珊瑚礁区表层海水中COTS-mtCOI片段浓度的时空变化,及其与水质指标间的关系。本研究表明当前长棘海星群体广泛分布于我国西沙群岛海域,永乐环礁附近礁区可能有较高密度的长棘海星群体。此外,温度升高可能促进长棘海星的暴发。
  • 海南省自然科学基金(420CXTD432,2019RC067);国家自然科学基金(42076145)。
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文章信息
doi: 10.12284/hyxb2023038
  • 接收时间:2022-04-10
  • 首发时间:2025-12-26
  • 出版时间:2023-03-01
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  • 收稿日期:2022-04-10
  • 修回日期:2022-10-12
基金
海南省自然科学基金(420CXTD432,2019RC067);国家自然科学基金(42076145)。
作者信息
    1 海南大学 海洋学院,海南 海口 570228
    2 海南省海洋与渔业科学研究院,海南 海口 571126

通讯作者:

*吴钟解(1981-),男,副研究员,硕士生导师,主要从事珊瑚礁生态学研究。E-mail:;
周智(1983-),男,研究员,博士生导师,主要从事珊瑚礁生物学研究。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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