Article(id=1246833312753406963, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246833307606995898, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-4193.2019.08.001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1541692800000, receivedDateStr=2018-11-09, revisedDate=1549814400000, revisedDateStr=2019-02-11, acceptedDate=null, acceptedDateStr=null, onlineDate=1775197826803, onlineDateStr=2026-04-03, pubDate=1566662400000, pubDateStr=2019-08-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1775197826803, onlineIssueDateStr=2026-04-03, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1775197826803, creator=13701087609, updateTime=1775197826803, updator=13701087609, issue=Issue{id=1246833307606995898, tenantId=1146029695717560320, journalId=1149651085930835976, year='2019', volume='41', issue='8', 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=1775197825576, creator=13701087609, updateTime=1775200503343, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1246844539051332282, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246833307606995898, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1246844539051332283, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1246833307606995898, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1, endPage=12, ext={EN=ArticleExt(id=1246833313177030659, articleId=1246833312753406963, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=The distribution characteristics of hydrothermal plume in mid-ocean ridge and its indicative role in polymetallic sulfide prospecting, columnId=1200807624443818795, journalTitle=Haiyang Xuebao, columnName=Review, runingTitle=null, highlight=null, articleAbstract=

Hydrothermal plume is an important symbol of hydrothermal activity. Seafloor polymetallic sulfide deposits are products of hydrothermal activity. At the present stage, seafloor polymetallic sulfide prospection and exploration in the mid-ocean ridges are mainly based on the detection of hydrothermal plume and combined with the comprehensive anomaly detection information to realize the breakthrough from the discovery of hydrothermal vents to the discovery of mineral deposits. Based on the hydrothermal plume as the research object, from the three aspects of near-bottom observations, dispersion mechanism and distribution characteristics, this paper summarizes the latest progress and aspects need to be improved of hydrothermal plume, and emphasizes the hydrothermal mapping as a prospective tool for seafloor polymetallic sulfide deposits in the mid-ocean ridges. Finally, this paper points out in conclusion that the spatial and temporal continuity, parameter diversification will be the development trend of hydrothermal detection, which will help promote understanding of hydrothermal plume distribution characteristics and will provide more detailed data to the study on the model of the hydrothermal fields.

, correspAuthors=Chunhui Tao, authorNote=null, correspAuthorsNote=null, copyrightStatement=Haiyang Xuebao, 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=Sheng Chen, Chunhui Tao, Jianping Zhou, Guoyin Zhang, Huawei Qin, Yuan Wang, Dong Chen), CN=ArticleExt(id=1246833314531790932, articleId=1246833312753406963, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=洋中脊热液羽状流的分布特征及其在多金属硫化物找矿中的指示作用, columnId=1189609213333594548, journalTitle=海洋学报, columnName=综述, runingTitle=null, highlight=null, articleAbstract=

热液羽状流是海底热液活动的重要标志,海底多金属硫化物是热液活动的产物。现阶段洋中脊多金属硫化物勘探工作的第一步是开展热液羽状流的近底探测;综合各类异常信息,实现从发现热液活动喷口到发现矿床的突破。本文以热液羽状流为研究对象,从羽状流的近底探测、扩散机制和分布特征3个方面,概述了最新的研究进展和有待完善的方面,阐述了羽状流在洋中脊多金属硫化物找矿中的指示作用,最后总结性地指出时空连续性、参数多元化将是热液探测的发展趋势,有助于提升对热液羽状流分布特征的认识,将为热液区分布模式的研究提供更加精细的探测资料。

, correspAuthors=陶春辉, authorNote=null, correspAuthorsNote=
*陶春辉,研究员,主要从事海洋地球物理研究。E-mail:
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陈升(1988—),女,浙江省武义县人,讲师,主要从事海底热液探测研究。E-mail:

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Journal of Geophysical Research: Solid Earth, 1996, 101(B8): 17995−18010., articleTitle=null, refAbstract=null)], funds=[Fund(id=1254506153216500617, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, awardId=null, language=CN, fundingSource=浙江省自然科学青年基金(LQ19D060008,LQ16D060008);国家重点研发计划课题(2018YFC0309901);国际海域资源调查与开发“十三五”项目(DY135-S1-01)及课题“硫化物合同区羽状流特征与找矿应用”(DY135-S1-1-09);国家海洋局海底科学重点实验室开放基金(KLSG1803);国家海洋局第二海洋研究所科研基金(JG1609)。, fundOrder=null, country=null)], companyList=[AuthorCompany(id=1254506128990200500, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, xref=1, ext=[AuthorCompanyExt(id=1254506129006977718, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, companyId=1254506128990200500, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 Institute of Marine Engineering and Technology, School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China), AuthorCompanyExt(id=1254506129036337847, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, companyId=1254506128990200500, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 杭州电子科技大学 机械工程学院 海洋工程技术研究所,浙江 杭州 310018)]), AuthorCompany(id=1254506131137684157, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, xref=2, ext=[AuthorCompanyExt(id=1254506131150267070, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, companyId=1254506131137684157, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 State Oceanic Administration of Key Laboratory of Submarine Geoscience, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China), AuthorCompanyExt(id=1254506131183821503, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, companyId=1254506131137684157, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2 自然资源部第二海洋研究所 国家海洋局海底科学重点实验室,浙江 杭州 310012)]), AuthorCompany(id=1254506131422896835, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, xref=3, ext=[AuthorCompanyExt(id=1254506131506782918, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, companyId=1254506131422896835, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3 College of Oceanography, Hohai University, Nanjing 210098, China), AuthorCompanyExt(id=1254506131557114568, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, companyId=1254506131422896835, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3 河海大学 海洋学院,江苏 南京 210098)])], figs=[ArticleFig(id=1254506148296581985, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=EN, label=Fig. 1, caption=Stacked bar histogram of known and predicted number of active vent fields as functions of spreading rate for mid-ocean ridges, distinguishing those discovered since year 2000[5]

Entire column height represents the predicted number of vent fields

, figureFileSmall=hci30idko1KPPbdKoqgcsQ==, figureFileBig=065Tu8AjeFtBIrh5mmvMwQ==, tableContent=null), ArticleFig(id=1254506148648903524, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=CN, label=图1, caption=洋中脊上已知的和未发现的热液区的数目与扩张速率的分布关系[5]

整个柱高代表预测的热液区数目

, figureFileSmall=hci30idko1KPPbdKoqgcsQ==, figureFileBig=065Tu8AjeFtBIrh5mmvMwQ==, tableContent=null), ArticleFig(id=1254506148917338984, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=EN, label=Fig. 2, caption=The representation of interdisciplinary lithosphere to hydrosphere of the Endeavour Segment[38] , figureFileSmall=WP6YPKwtiGg9P74xAsR6Jw==, figureFileBig=11OGPuAMa9kHa0jgdYIZgg==, tableContent=null), ArticleFig(id=1254506149194163051, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=CN, label=图2, caption=从岩石圈到水圈多学科交叉研究的典型代表—Endeavour洋脊段[38] , figureFileSmall=WP6YPKwtiGg9P74xAsR6Jw==, figureFileBig=11OGPuAMa9kHa0jgdYIZgg==, tableContent=null), ArticleFig(id=1254506149445821294, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=EN, label=Fig. 3, caption=Interpolated concentrations and station map along the US GEOTRACES GP16 eastern Pacific zonal transect[45]

The 3Hexs presents the total concentration of 3He deducts the background values of sea water and air

, figureFileSmall=qZbChlU8RL6O2fJlimp2Jw==, figureFileBig=G/QixRhrDYzCTNS5YNMEpw==, tableContent=null), ArticleFig(id=1254506151144514416, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=CN, label=图3, caption=国际海洋痕量元素及同位素生物地球化学循环研究计划(GEOTRACES)项目GP16航次在东太平洋南部15°S海域的调查站位分布和浓度等值线[45]

3Hexs表示减去背景海水和空气中的3He浓度所得的异常值

, figureFileSmall=qZbChlU8RL6O2fJlimp2Jw==, figureFileBig=G/QixRhrDYzCTNS5YNMEpw==, tableContent=null), ArticleFig(id=1254506151446504308, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=EN, label=Fig. 4, caption=An idealized comparison of how detectable plume chemistry can change over distance[41] , figureFileSmall=TIJTjDUeweQYzks1H70g9w==, figureFileBig=mGZHkcsF1FcKzNzzq7TuBA==, tableContent=null), ArticleFig(id=1254506151903683449, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=CN, label=图4, caption=在可探测的羽状流中,羽流示踪元素的浓度随距离变化的对比示意图[41] , figureFileSmall=TIJTjDUeweQYzks1H70g9w==, figureFileBig=mGZHkcsF1FcKzNzzq7TuBA==, tableContent=null), ArticleFig(id=1254506152084038523, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=EN, label=Fig. 5, caption=Hydrothermal frequency vs. spreading rate, spacing vs. spreading rate

27 ridge sections using data from the InterRidge database (small red dots). Inverted triangle(eastern Galapagos Spreading Center, eGSC), large circle (center Galapagos Spreading Center, cGSC), diamond (Eastern Lau Spreading Center, ELSC) and square (northern East Pacific Ridge, nEPR) represent 4 segments of spreading ridge studied in Baker et al[3]. Results for these sections are from InterRidge Database (large red symbol), Baker et al[3] (green), and results from visual seafloor observations (purple). nEPR and sEPR (southern East Pacific Rise, skewed triangles) carried out detailed visual seafloor observations

, figureFileSmall=/vhZdybL/1bJic7cdcpmVg==, figureFileBig=Tg9yptwFccXpXoNbd6zoIw==, tableContent=null), ArticleFig(id=1254506152310530943, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=CN, label=图5, caption=热液区发生率、热液区分布间距与洋脊扩张速率间的分布规律

红色小圈表示InterRidge数据库中统计的27段不同扩张速率的洋脊。倒三角(加拉帕格斯扩张中心的东部,eastern Galapagos Spreading Center,eGSC)、大圆圈(加拉帕格斯扩张中心的中部,center Galapagos Spreading Center,cGSC)、菱形(劳扩张中心,Eastern Lau Spreading Center,ELSC)、正方形(东太平洋海隆的北部,northern East Pacific Ridge,nEPR)分别表示Baker等[3]重新开展热液探测的4段快速、中速扩张洋脊;红色表示通过InterRidge数据库计算的热液区发生率和热液区分布间距,绿色表示通过最新热液探测资料计算的结果,紫色表示通过详细的海底摄像观测资料计算的热液区发生率和热液区分布间距;只有nEPR和sEPR(东太平洋海隆的南部,southern East Pacific Ridge,斜三角形) 开展了 详细的海底摄像观测

, figureFileSmall=/vhZdybL/1bJic7cdcpmVg==, figureFileBig=Tg9yptwFccXpXoNbd6zoIw==, tableContent=null), ArticleFig(id=1254506152490886017, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=EN, label=Table 1, caption=

Distribution characteristics of hydrothermal plume and types of hydrothermal fields

, figureFileSmall=null, figureFileBig=null, tableContent=
序号 羽状流的异常分布特征 热液流体类型 热液区发育类型
温度 示踪指标含量 浊度及是否伴随“黑烟” 典型热液区
1 >350℃ 高Fe,H2S;高CH4、Mn 伴随“黑烟”,明显浊度异常 Rainbow 高温热液流体 高温离散热液区
2 >350℃ 高Fe,H2S;低CH4、Mn 伴随“黑烟”,明显浊度异常 Snake Pit 高温热液流体 高温离散热液区
3 100~300℃ 高CH4;低Fe、H2S 无“黑烟”,上升流:高温清澈中性浮力层:热液微生物 Lost City 高温清澈热液流体 高温离散热液区
4 100~300℃ 高Fe;低H2S 无“黑烟”,上升流:高温清澈中性浮力层:Fe氢氧化物 EPR 9°30′N 高温清澈热液流体 高温离散热液区
5 <35℃,有时达100℃ CH4、H2S、Fe、Mn等 无“黑烟”,无明显浊度异常 Endeavour 洋脊 低温弥散热液流体 低温弥散热液区
), ArticleFig(id=1254506152750932868, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1246833312753406963, language=CN, label=表1, caption=

羽状流的异常分布特征及热液区发育类型

, figureFileSmall=null, figureFileBig=null, tableContent=
序号 羽状流的异常分布特征 热液流体类型 热液区发育类型
温度 示踪指标含量 浊度及是否伴随“黑烟” 典型热液区
1 >350℃ 高Fe,H2S;高CH4、Mn 伴随“黑烟”,明显浊度异常 Rainbow 高温热液流体 高温离散热液区
2 >350℃ 高Fe,H2S;低CH4、Mn 伴随“黑烟”,明显浊度异常 Snake Pit 高温热液流体 高温离散热液区
3 100~300℃ 高CH4;低Fe、H2S 无“黑烟”,上升流:高温清澈中性浮力层:热液微生物 Lost City 高温清澈热液流体 高温离散热液区
4 100~300℃ 高Fe;低H2S 无“黑烟”,上升流:高温清澈中性浮力层:Fe氢氧化物 EPR 9°30′N 高温清澈热液流体 高温离散热液区
5 <35℃,有时达100℃ CH4、H2S、Fe、Mn等 无“黑烟”,无明显浊度异常 Endeavour 洋脊 低温弥散热液流体 低温弥散热液区
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洋中脊热液羽状流的分布特征及其在多金属硫化物找矿中的指示作用
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陈升 1 , 陶春辉 2, * , 周建平 2 , 张国堙 2 , 秦华伟 1 , 王渊 2 , 陈栋 2, 3
海洋学报 | 综述 2019,41(8): 1-12
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海洋学报 | 综述 2019, 41(8): 1-12
洋中脊热液羽状流的分布特征及其在多金属硫化物找矿中的指示作用
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陈升1 , 陶春辉2, * , 周建平2, 张国堙2, 秦华伟1, 王渊2, 陈栋2, 3
作者信息
  • 1 杭州电子科技大学 机械工程学院 海洋工程技术研究所,浙江 杭州 310018
  • 2 自然资源部第二海洋研究所 国家海洋局海底科学重点实验室,浙江 杭州 310012
  • 3 河海大学 海洋学院,江苏 南京 210098
  • 陈升(1988—),女,浙江省武义县人,讲师,主要从事海底热液探测研究。E-mail:

通讯作者:

*陶春辉,研究员,主要从事海洋地球物理研究。E-mail:
The distribution characteristics of hydrothermal plume in mid-ocean ridge and its indicative role in polymetallic sulfide prospecting
Sheng Chen1 , Chunhui Tao2, * , Jianping Zhou2, Guoyin Zhang2, Huawei Qin1, Yuan Wang2, Dong Chen2, 3
Affiliations
  • 1 Institute of Marine Engineering and Technology, School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
  • 2 State Oceanic Administration of Key Laboratory of Submarine Geoscience, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
  • 3 College of Oceanography, Hohai University, Nanjing 210098, China
出版时间: 2019-08-25 doi: 10.3969/j.issn.0253-4193.2019.08.001
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热液羽状流是海底热液活动的重要标志,海底多金属硫化物是热液活动的产物。现阶段洋中脊多金属硫化物勘探工作的第一步是开展热液羽状流的近底探测;综合各类异常信息,实现从发现热液活动喷口到发现矿床的突破。本文以热液羽状流为研究对象,从羽状流的近底探测、扩散机制和分布特征3个方面,概述了最新的研究进展和有待完善的方面,阐述了羽状流在洋中脊多金属硫化物找矿中的指示作用,最后总结性地指出时空连续性、参数多元化将是热液探测的发展趋势,有助于提升对热液羽状流分布特征的认识,将为热液区分布模式的研究提供更加精细的探测资料。

热液羽状流  /  分布特征  /  洋中脊  /  多金属硫化物

Hydrothermal plume is an important symbol of hydrothermal activity. Seafloor polymetallic sulfide deposits are products of hydrothermal activity. At the present stage, seafloor polymetallic sulfide prospection and exploration in the mid-ocean ridges are mainly based on the detection of hydrothermal plume and combined with the comprehensive anomaly detection information to realize the breakthrough from the discovery of hydrothermal vents to the discovery of mineral deposits. Based on the hydrothermal plume as the research object, from the three aspects of near-bottom observations, dispersion mechanism and distribution characteristics, this paper summarizes the latest progress and aspects need to be improved of hydrothermal plume, and emphasizes the hydrothermal mapping as a prospective tool for seafloor polymetallic sulfide deposits in the mid-ocean ridges. Finally, this paper points out in conclusion that the spatial and temporal continuity, parameter diversification will be the development trend of hydrothermal detection, which will help promote understanding of hydrothermal plume distribution characteristics and will provide more detailed data to the study on the model of the hydrothermal fields.

hydrothermal plume  /  distribution characteristics  /  mid-ocean ridges  /  polymetallic sulfide
陈升, 陶春辉, 周建平, 张国堙, 秦华伟, 王渊, 陈栋. 洋中脊热液羽状流的分布特征及其在多金属硫化物找矿中的指示作用. 海洋学报, 2019 , 41 (8) : 1 -12 . DOI: 10.3969/j.issn.0253-4193.2019.08.001
Sheng Chen, Chunhui Tao, Jianping Zhou, Guoyin Zhang, Huawei Qin, Yuan Wang, Dong Chen. The distribution characteristics of hydrothermal plume in mid-ocean ridge and its indicative role in polymetallic sulfide prospecting[J]. Haiyang Xuebao, 2019 , 41 (8) : 1 -12 . DOI: 10.3969/j.issn.0253-4193.2019.08.001
海底热液活动是海洋与地球深部物质与能量循环的重要方式[1-2],存在于不同地质构造环境中[3-5],对认识整个地球内部岩浆活动、火山活动和构造运动都具有指示意义,在当前深海科学研究中已占据重要地位,目前已发现的海底热液区超过700个[6]。随着对热液活动认识的提高和探测技术诸如自治水下机器人(Autonomous Underwater Vehicle,AUV)及载人潜水器(Human Occupied Vehicle,HOV)的发展,更多的热液区及热液喷口也将被逐步发现[4]。洋中脊热液活动集中发生在洋中脊及邻近海域,是最大规模的海底热液活动[7]。由于洋中脊具有独特的板块构造背景和活动形式、圈层结构和岩石类型,形成了独特的热液系统。根据热液羽状流发生率与扩张速率之间的经验公式,预测在全球海底扩张中心具有1 305个活动热液区,其中洋中脊孕育1 100个热液活动区[5]图1)。迄今为止,通过热液调查活动已在超快速、快速、中速、慢速和超慢速扩张洋脊上发现了399个海底热液区,其中包含362个活动热液区[6]
热液羽状流,是由海底热液喷口喷出的流体与周围冷海水相遇后迅速混合形成的[8],其物理化学组成和性质与海水有很大的区别。具体地说,喷口流体的密度与海水密度相比偏小,压力偏大,因此可使喷口流体脱离喷口,同时被不断卷入的周围海水所稀释,以羽状体的形式上浮,在距离海底几十米至几百米的高度,与环境达到平衡,形成中性浮力层。热液羽状流可在中性浮力层横向运移几千米至几十千米[9]。此外,热液羽状流在上升的同时,会在喷口附近沉淀出富含金属元素的硫化物和氧化物颗粒[10-11]
海底热液多金属硫化物富含Cu、Zn、Au、Ag等多种金属元素,极具资源潜力和经济价值[12-17],主要分布在大洋中脊和弧后盆地扩张中心,水深在数百米到数千米之间,以大于2 000 m水深为主,其中65%分布在洋中脊[18]。作为一种重要的战略资源,海底多金属硫化物资源的调查一直备受关注。美国、法国、日本、德国、加拿大和俄罗斯等国家主导了早期海底多金属硫化物的调查研究,并取得了一批重要成果[19-23]。近年来,中国大洋协会也在全球洋中脊开展了一系列的硫化物勘探活动,并于2011年率先与国际海底管理局正式签署了《国际海底多金属硫化物矿区勘探合同》,获批了1万km2的勘探区域,使我国在海底多金属硫化物的勘探工作方面走在了世界前列[24]。此后,俄罗斯、韩国、法国、日本、德国、印度、波兰等国家先后申请并获批了硫化物矿区(www.isa.org.jm)。可以看出,各国对海底多金属硫化物资源的争先调查,抢占有利靶区的竞争已全面展开。
热液羽状流是地球深部向海洋进行物质与能量输送的关键节点[25],有助于深刻认识海洋中岩石圈与水圈的相互作用。羽状流空间分布特征的研究是推算热液活动中物质和能量贡献的不可缺少的环节,有助于进一步认识热液活动的规模、研究热液系统的物质和能量通量。
洋中脊海底多金属硫化物勘探是一项复杂的长期工程,全球洋中脊总长约6万km,目前还有70%的洋脊未开展详细的热液探测[5]。虽然海底热液活动及多金属硫化物在近40年前就已被发现,但因其身处大洋深处,外加洋中脊热液成因硫化物矿床具有分布面积小、立体分布的特点(瞬变电磁和AUV近底磁法探测的异常分布结果仅有几百米甚至几十米[26]),因此洋中脊多金属硫化物的勘探工作严重依赖于多金属矿床的勘查方法及技术水平。
伴随热液活动过程产生的热液羽状流,尽管其各组分浓度在流体喷发过程中迅速稀释至原有的10–5~10–4[27],同时随着距离热液喷口位置的增加逐渐减弱,但受热液羽状流影响的水体在物理、化学和光学性质上与周围海水存在明显的差别,可在远离热液喷口几千米之外被探测,因此在以往的热液调查中,通过探测分布较广、较为稳定的(3He和温度)[2, 28-29]或者类似稳定的(浊度、颗粒态铁(pFe)、溶解态锰(dMn)、甲烷(CH4)等)[9, 30-32]示踪指标来勾勒羽状流的空间分布,从而初步圈定海底热液区所在的位置。相比其他地球物理探测手段,热液羽状流的探测大大地提高了热液探测的效率。通过对热液羽状流的分布模式开展深入分析和研究,能为洋中脊海底多金属硫化物找矿工作提供重要科学支撑[33]
在验证“岩浆供给”假说的过程中,存在3方面困难:第一,缺乏热通量或者化学物质通量定量化的知识;第二,缺少岩浆循环与热液喷发在不同时间尺度上的统计数据,即全球洋中脊上每一个热液区积累出的时间跨度还不够长;第三,热液循环与热源、渗透率之间的关系未知。为克服以上3点困难,通常使用热液羽状流发生率或者热液区发生频率作为热液活动的定量指标,用空间的取样来代替时间上的取样。同时,通过对具有相同扩张速率但不同构造背景的洋脊段开展热液调查,为洋脊段的扩张速率和热液活动特征提供具有统计学意义的信息。将渗透率理解成扩张速率的函数,其对热液循环的影响可以简化为岩浆供给与热液活动之间的关系,有助于研究洋中脊三维地幔和熔融流体、海洋地壳的热状态、脊轴下伏岩浆供给与热液循环之间的关系[34],同时也助于研究热液循环在浅层洋壳中的模式[1]
热液羽状流分布在不同扩张速率、不同构造背景的洋中脊。在全球尺度范围内对热液区的空间分布进行研究,表明热液区数目与洋中脊扩张速率(表征岩浆供给)存在强烈的相关性[5],验证了岩浆供给假说;同时受局部环境的影响,热液区的发育和分布情况表现出不同特征。通过探讨热液羽状流的物理化学过程及扩散机制,研究其与周围环境的化学、动力学的相互作用[35],可进一步阐述热液系统与洋中脊的岩浆作用、地质构造的关系[36-38]图2)。
对热液羽状流开展近底探测是目前海底热液活动调查应用最为广泛的技术手段[4]。几乎所有的热液探测都是基于扩散的中性浮力羽状流,通过温盐深传感器(Conductivity Temperature Depth,CTD)、浊度探测器(Miniature Autonomous Plume Recorders,MAPR)、甲烷传感器(Methane Sensor,Mets)、化学传感器等轻便型传感器,搭载在深拖测线或CTD站位的光缆上,对水体进行实时探测;同时,CTD采水器可获取距离海底一定高度的海水样品,并在实验室中开展化学成分的测定与分析,在此基础上解译羽状流特征。羽状流近底探测的内容甚广,物理参数包括温度、流体的运动特征(羽状流的上升高度及中性浮力层的对流)等[39],光学参数主要包括浊度,化学参数包括氧化还原电位异常(Oxidation Reduction Potential,ORP)、3He、H2、CO2、CH4、H2S等气体组分含量和Fe、Mn等金属元素含量。
位温、浊度和ORP是最主要的3种探测指标。热液羽状流的位温异常通常是指同一地区等密度层位处热液羽状流温度与正常海水温度之间的差值,是最明确的海底热液活动指示标志[40-42]。浊度异常是应用最为广泛的海底热液活动指示标志,几乎所有的高温热液区都伴随着水体颗粒物浓度增大的现象,因此利用水体光学性质对水体浊度值进行探测是极为高效的热液活动探查方法[7]。另外,热液流体中还富含硫化氢(H2S)和氢气(H2),它们的存在使得受到热液羽状流影响的水体呈现酸性和还原性,因此海水的pH值和ORP值也是衡量和探测热液流体及其扩散羽状流的重要标志[43-44]
利用热液中的元素及同位素探测海底热液羽状流,其中Fe、Mn金属元素及3He、CH4是最为常用的指标。美国GEOTRACE EPZT航次对东太平洋南部15°S西侧4 500 km洋脊进行调查,通过近20个CTD站位的采样,基于位温、浊度、ORP、3He、溶解态铁(dFe)、dMn、pFe和颗粒态锰(pMn)浓度勾勒出东太平洋南部15°S热液羽状流的形态(图3),其羽状流水体异常可达数千千米[45]3He元素是最敏感的热液示踪指标,表现出很强的惰性,只会随着羽状流的扩散而稀释,浓度变化逐渐变小,可用来判断热液喷口是否活动;然而海上无法现场分析3He元素,限制了3He元素作为热液羽状流示踪指标被广泛使用的可能性。洋脊尺度上更加有效的示踪元素是Mn离子和Fe离子,这些元素可以通过形成化合物的方式在羽状流中稳定存在[45-46],可在羽状流中保持几千千米,时间可达数年[9];目前还没有实时又精确的探测铁锰氧化物颗粒的手段,所以需要离散的采样。在小范围尺度,一般是10 km范围内,CH4是重要的示踪元素,CH4可在羽状流中存在数月或数天[47],但并不是所有的羽状流中都能探测到CH4;一些低温热液区产生的羽状流中会探测到CH4,但探测不到浊度或金属元素异常[48];虽然CH4可以通过水样进行测量,但是目前没有传感器可以准确实时地测量羽状流的CH4含量。
现有条件下,热液羽状流示踪指标的实时连续探测主要局限在温度、浊度和ORP(包括H2S)3方面(图4)。浊度异常可沿着洋中脊主轴追踪几百千米,验证了细小颗粒物含铁的氧化物颗粒可以在羽状流中停留很长的时间[7]。一些特定的化学示踪元素,如:不同的硫离子(诸如HS)、Fe2+和H2,会发生氧化还原反应,引起显著的ORP变化[49-51],而这些氧化还原反应发生很迅速,因此只能在喷口附近的地方探测到异常。Baker[4]通过4个不同洋脊段的拖曳调查,探测到290个ORP异常,通过计算异常的路径长度来量化这些异常的空间分布尺度。平均路径长度在(0.57±0.72)km,表明初步的定位喷口位置的精度小于1 km。
羽状流示踪元素的停留时间和定位精度不同,使得我们可以有一套更宽泛的热液羽状流示踪指标来有效地定位热液喷口位置以及相关联的硫化物沉积。图4每一条曲线定性地展示了特定示踪元素从喷口(0 m)到50 km的相对浓度变化,意味着羽状流在与周围水体交换过程中会有明显的梯度变化,随着与热液喷口位置的距离增加,各参数的异常梯度值迅速降低,不同示踪元素的异常分布对海底热液活动有不同的指示意义。图中除了硫化亚铁颗粒(pFeS)和含铁氧化物颗粒(pFeoxy),所有示踪元素都是指溶解态元素。几乎一半的微粒状铁物质在靠近喷口的地方以硫化物的形式沉淀下来,而另一半则慢慢地以细小颗粒的含铁氧化物形式进行沉降。dMn的沉降速度和含铁氧化物一样都比较慢。只有3He和热量(Q)是真正保守的,但在喷口附近几千米内热量会被稀释,不容易探测到热量异常。
通过总结已公开发表的羽状流异常分布特征,可将热液流体的类型大致分成3类:高温热液流体、高温清澈热液流体、低温弥散热液流体(表1)。高温热液流体(High-temperature flow with black smoke)是指传统认识上的由高温(>350℃)热液喷口喷发形成的伴随“黑烟”的流体。高温清澈热液流体(High-temperature,clear flow without black smoke)是指温度在100~300℃的高温热液喷口释放的流体,因其上升流中含有很少的颗粒物而呈白色,随着含铁物质的氧化或热液微生物的作用,在中性浮力层可探测到浊度异常。低温弥散热液流体(Low-temperature,diffuse flow)是指低温(<35℃有时达100℃)热液喷口喷发的流体,通常不能形成一定规模的上升流和中性浮力层,其示踪元素的含量变化因热液区不同而呈现不同的组合情况。
在上述传统的热液探测过程中,存在3个方面有待改进和完善。第一方面,这些示踪元素可有效探测温度大于100℃且富含颗粒物的“黑烟”,但很难辨别羽状流集合体(由多个集中分布的热液喷口释放所形成的流体),对于含有极少颗粒物或溶解态金属的高温清澈热液流体(Lost City热液区[52]),或是不能形成上升羽状流的低温弥散热液流体的探测更是成问题。第二方面,截至目前,拖曳式的传感器调查只是占了全球洋中脊总长的20%,而且在绝大多数洋脊段上开展的热液探测并不具有空间连续性,测线间隔在几千米至几十千米之间[53]。离散的调查方式会错失分布规模较小、温度异常比较微弱、通常没有“黑烟”伴随的低温弥散热液区。然而,已有研究表明,低温弥散热液区在热液与海洋的物质和能量循环中占据主导地位[10],为深海提供绝大部分的铁元素,物质通量远超高温热液喷口的通量,其热通量是洋中脊主轴热量散失总值的90%。第三方面,受限于热液系统本身的复杂性和热液探测技术的局限性,全球范围内不同扩张速率洋脊的热液探测程度相差很大。洋中脊热液羽状流的探测和研究多集中在快速、中速和部分慢速扩张洋脊上,并在这些洋脊段取得了丰硕的成果[3]。慢速扩张洋脊占据全球洋脊总长度的60%,然而由于在慢速及超慢速扩张洋脊进行热液调查的难度(地理和气候方面的因素),其目前的调查程度是最低的。通过InterRidge热液区共享数据库估算洋中脊上还有3/4的热液区有待被发现,其中将近一半的热液区(约400个)有待在慢速和超慢速扩张的洋脊(扩张速度小于60 mm/a)发现;具有较慢的平均扩散速率的洋脊,即南大西洋洋脊、北大西洋洋脊、西南印度洋脊等,有可能孕育有绝大部分未被发现的热液区[5]
因此,在洋中脊尺度开展连续且高分辨率的热液探测是全面认识洋中脊热液区分布特征的关键。一系列用于探测ORP、H2S、CH4等的新型传感器应运而生[22-25]。ORP是指溶解态的还原性物质(诸如H2、H2S和Fe2+)在喷口附近迅速发生的氧化还原电位变化。而CH4是小范围尺度(10 km范围内)重要的示踪元素。目前最先进的热液羽状流探测方式是利用各类新型潜水器搭载各类传感器,在局部区域内进行自动、连续探测,开展多源同步观测数据综合分析判断,提高了探测数据的空间密度、获取率和多样性,增加了热液异常判断的可靠性。可对集中分布的热液流体进行分辨,有助于更加准确判别热液流体的类型。此外,原位传感器的研制使得监测热液区的空间和瞬时连续变化成为可能。
随着声学探测技术的发展,已有学者进行了相关研究,利用多波束声呐对热液羽状流进行长期观测,基于Simrad SM2000和Reson Seabat 7125多波束声呐,应用热液羽状流的声学反向散射参数,开展了热液羽状流的三维分布结构的声学图像研究,表现出声学探测方法的巨大潜力[54-56]
从定性、定量两个角度对羽状流扩散机制进行研究,将有助于更快、更准确地探测热液区和热液喷口位置,同时还有助于计算羽状流对深海热量传输和物质交换的贡献量。
对热液羽状流扩散机制的定性研究,主要是基于对洋中脊热液区的近底探测,总结了一系列影响热液羽状流分布扩散的因素。影响海底热液羽状流扩散的因素很多,在距离热液喷口水平或垂直方向几百米的范围内,对流与湍流夹卷为水动力学的主要特征,因此影响羽状流扩散的最主要的因素有:热液喷出速度[57]、热液羽状流上升高度[58]、海底地形[59]以及深海流[60-62]等。这些因素控制着热液喷口的各种化学物质的初始传输,与周围海水的混合,以及相关的化学反应。水动力学的这些特征同时还控制着夹卷周围海水、有机质和微生物进入上升热液羽状流的复杂过程。在实际情况中,还可能受到其他因素的影响,如岩浆的供给[7]、局部构造[63]、海洋层结[64]、地球自转[65]以及热液喷口的尺寸等。
鉴于目前海底现场观测取样的技术还不是很成熟,沿着洋脊上方进行热通量和物质通量的测量需要先进的科学技术和昂贵的人力和物力,而对具有连续性和事件性的热源来说,其测量更是只能根据对热液流体的采样和观测来推算,因此国内外学者对热液羽状流扩散机制的定量研究相对有限,针对热液羽状流的扩散机制进行了一系列实验分析和模拟研究。
在实验室模拟方面,早期学者已经进行了大量的工作,包括烟囱体的形成和发育过程、烟囱体内部流体的压力分布和演化过程[58]、不同模式下热液的成矿过程及沉淀顺序的研究[66]。张巍等[67]采用线性层结盐水发生装置以及喷嘴向下以重盐水注入盐水层结的方法,模拟线性层结盐水中羽状流的发展过程;应用时间分辨粒子图像测速技术,研究线性层结盐水中羽状流内部的流场结构。实验结果显示:羽状流流速从中心区域向边缘逐步递减;羽状流下沉到最大深度后回升到中性浮力层,并向四周扩散;在羽状流内部及边界存在大量复杂的涡旋结构,说明在羽状流发展过程中,始终伴随着羽状流与周围环境水体之间的掺混作用。
对热液羽状流进行“数值模拟”是研究当前取样观测技术还不能触及的深部过程和定量研究热液循环系统的有效手段。从20世纪70年代至今,针对热液流体的性质、烟囱体的演化、热液的大规模输送、硫化物的沉积过程、热液对大洋的热输送、热液循环系统的发育过程以及巨型羽状流的形成机制等设计了多种模型来进行模拟、分析并探讨其影响因素。Jiang和Breier[68]基于数值求解耦合的Navier-Stockes方程和热传导方程,开发了一种热液羽状流的计算流体力学模型;使用κ-ω湍流闭合模型来描述湍流及其引起的夹卷和混合过程,并且采用高温高压海水非线性状态方程来统一描述热液与周围海水的特性;通过现有理论模型,验证了新的模拟方法,将详细的水动力学模型结合到相似尺度下的地球生物化学模型来研究与热液羽状流相关的地球化学、微生物及其他过程。
自从在加拉帕格斯扩张中心发现首个热液活动区以来,已经对热液活动以及羽状流的分布特征展开了很多讨论。洋中脊系统的热液区分布受多种地质作用的影响,解释岩浆供给作用与热液羽状流分布特征之间的关系,通常会因为其他过程的同时影响而变得困难[69]。随着热液探测程度的提高,对热液活动区分布特征的认识不断深入[4]
Francheteau和Ballard[70]最早明确提出“岩浆供给”假说,预测岩浆供给的变化是大尺度上控制洋中脊热液区分布模式的主要因素。之后的10年中,由于缺乏以洋脊段为尺度的热液活动调查资料,无法验证“岩浆供给”假说。Baker等[71]基于快速、中速扩张洋脊的研究,提出一个简单但具有挑战性的假说:热液活动随着岩浆供给的增加(扩张速率线性增加)而线性增加。German和Parson[72]将这种关系延伸到慢速扩张的大西洋中脊,尽管结论支持了这个假说,但是岩浆过程与构造过程的相互作用可以导致这种线性趋势有显著的偏差。
为了验证“岩浆供给”假说,Baker和German[7]总结了1995–2004年的大量热液调查资料,包括已经确认的(海底观测)以及推断的(水柱测试)活动热液区的分布,对比分析热液区在快速以及慢速扩张洋脊的分布情况,通过洋壳的厚度推算相应的岩浆供给,发现在快速、中速扩张洋脊的热液区频率或热液羽状流发生率与岩浆供给之间存在强烈的线性关系,这种线性关系强烈地支持了“岩浆供给”假说,并提出了全球模式,其主要内容为:洋中脊主要分布于高温离散热液区(伴随“黑烟”),热液区发生率与洋脊扩张速率之间存在一定的规律,热液区发生率是指通过连续探测在100 km范围内所发现的热液区数目,而洋脊扩张速率是控制洋中脊地幔熔融和构造活动的一级因素。此外,还提到次级的控制因素包括渗透率和深大断裂所提供的额外热量,以及在超慢速洋脊及受热点影响的热液活动分布情况,最终验证了“岩浆供给”假说[73]
通过对西南印度洋77°~99°E洋脊段开展研究,Baker等[69]进一步检验了热液喷口的空间分布密度与岩浆供给两方面在区域和洋脊段尺度的变化。在区域尺度上,受热点影响的岩浆较厚的洋脊段,其羽状流发生率受抑制。相反地,所有其他洋脊段的羽状流发生率遵循全球模型。远离三联点的地方,符合全球羽状流发生率模型的洋脊段也符合区域性主轴深度的趋势,发生率高的地方,主轴深度高,发生率低的地方主轴深度低。在单独的洋脊尺度,羽状流发生率与洋脊段的主轴抬升之间的强烈关系表明不同的岩浆供给可以通过不同的热液空间分布水平来体现[69]
在洋壳与海洋的相互作用过程中,热液释放过程对其具有重要的贡献。在评价热液释放的影响力时,热液区的分布间距是重要的变量;同时,该变量对于理解化能合成生物的分布、海底采矿后生态系统的恢复以及海底喷发等都具有关键意义[3]
海底观测以及对洋壳的测量等直接证据表明,年轻洋壳的最上层,具有裂隙结构,渗透性高达10–10 m2 [74],为发育热液区提供了充足的条件。然而,Hannington等[18]通过计算洋中脊上70个块状硫化物沉积的分布间距(研究区涵盖了全球扩张速率的范围),推测洋中脊上热液区的分布间距在10~330 km之间;并且块状硫化物沉积之间的距离,随着扩张速率的降低而增加。Beaulieu等[5]通过当时已有的数据预测在扩张速率大于55 mm/a的洋中脊上,海底热液区的平均分布间距是12~220 km,在超快速扩张洋脊(150 mm/a)上热液区的平均分布间距是25 km,而在超慢速扩张洋脊(10 mm/a)上热液区的平均分布间距是90 km[5]。显然,钻孔资料表明的孔隙度似乎与上述估算出的热液区分布间距不太一致,热液区的分布更加稀疏,尤其是在那些下伏岩浆房的洋脊段,热液区的分布数量并没有明显增多。究其原因主要是:在前期的海底观测中缺少大规模系统的调查,尤其是缺乏在洋脊尺度上开展的连续、一定规模的(长度在10~100 km之间)海底观测,因此统计的数据还不够全面。此外,调查数据显示,比起全球统计数据,那些已开展连续的且具有一定规模的热液探测的洋脊段热液区分布更加密集[75-76],正是说明了在洋脊段上开展系统、连续、大规模的热液调查的必要性。
因此,Baker等[3]通过拖曳方式对4个快速和中速扩张(>55 mm/a)的东太平洋海隆(EPR)开展了精密探测。结果表明,EPR的热液区平均分布间距为3~20 km,远低于全球模式的统计值;EPR的热液区发生率与扩张速率间依然呈现相关性,但EPR的热液区发生率远超全球模式对EPR的预测结果;结合海底摄像观测资料,预测扩张速率大于55 mm/a的洋脊的热液区分布总量至少是目前已发现热液区数量的3~6倍(图5)。
较小的热液分布间距说明了传感器探测能力的提高,可对孤立热液区释放的颗粒物浓度较低的羽状流进行探测,以及对集群的离散的热液区(1 km以内)的辨别能力有了提升。热液区数目的增加给海底扩张的模式提供了大量的约束条件,诸如海底和洋壳化能合成生物的分布模式、弥散热液区对生物地球化学的影响、热液区的分布模式等。
海底多金属硫化物沉积的勘探工作,相比陆地上的硫化物勘探工作难很多。因为海水层的覆盖,难以对海底的硫化物直接观察与取样,需要借助大量的深海高新装备来获取各类勘查信息,包括船舶、水下机器人(Remote Operated Vehicle,ROV)、HOV等平台以及各类勘查设备。这些设备在陆地勘查工作中几乎没有涉及,为了适应海洋及深海极端工作环境,通常是研发与应用并进,因此尚未达到成熟应用的阶段。海洋地球物理勘查的手段主要是电法、磁力、地震、多波束测深、侧扫声呐、重力等,但由于海水层的阻隔及海水对电磁场的屏蔽和干扰,调查结果精度不高且数据解释具有多解性,因此其可靠性和合理性都需进一步验证。从地球化学的角度来看,洋中脊工作程度低,常规地质填图、地球化学勘查等工作难以实施。而在洋中脊开始热液羽状流的异常探测可以达到“迅速掌握全局、逐步缩小靶区”的目的,为海底多金属硫化物勘探提供了有效的指示作用,可借助羽状流的分布特征研究,帮助我们更快更有效地定位热液喷口的位置,进而指导洋中脊海底多金属硫化物的找矿工作。
前期的热液羽状流探测主要通过探测富含矿物颗粒的热液羽状流,发现了一系列高温热液活动区,但是低温的颗粒物含量较少的热液区仍有待发现。在快速和中速扩张洋脊上进行的热液调查结果显示,存在很多孤立的且只有ORP异常的热液点,占据了洋脊段上全部热液点统计值的1/4。这些异常的点有可能是仅仅代表低温的热液流体。在对弥散型热液区的羽状流进行数值模拟过程中,湍流对流模型的结果表明,即使从一个很小的弥散流源区喷发的羽状流,也可以上升到100~200 m。目前我们无法区分低温流体以及高温但颗粒物浓度低的流体,因此如果用分辨率更高的化学传感器进行采样和探测,将会促进对弥散型热液区的研究。热液示踪元素在灵敏度、探测范围、存在周期和数据可利用性方面有显著的差异,因此有效的调查将需要扩大示踪元素的探测范围,对羽状流末梢开展探测,同时在小范围内开展更加精细化的探测,来确定热液区的喷口。
连续实时地探测温度、浊度和氧化还原电位数据,是目前最精确的海底热液羽状流调查方式。此前的热液调查中极其缺少对那些长度在10~100 km之间的洋脊段的羽状流开展近底探测。尤其是在超慢速和慢速扩张洋脊,进行热液调查的难度更大,期待在未来可以通过AUV搭载化学传感器增加这些区域的调查。ROV/AUV的混合使用也将增加采样的可能性。现有的技术已经能够让AUV调查达到一级洋脊段的尺度(约100 km)。展望未来,更长更系统的AUV调查(约1 000 km)将帮助我们填补一些区域的空白。
热液系统普遍发育在海底扩张中心,其热液产物具有很大的资源潜力,因此需对海底热液活动区域进行高效探测和精确定位。洋中脊热液羽状流的分布特征研究有助于更快更有效地定位海底热液喷口,有助于定量研究热液系统的物质通量和能量通量,有助于深入探讨热液活动与岩浆供给、构造活动的关系。
热液羽状流的示踪元素主要包括物理参数、光学参数、化学参数三大类。其中温度、浊度和氧化还原电位是目前最主要的,也是应用最广的探测参数。根据示踪元素的停留时间和定位精度,建立一套宽泛的羽状流示踪指标来指导热液喷口及其相关联的多金属硫化物沉积的定位工作。
受限于热液系统本身的复杂性、热液探测技术的局限性及全球范围内热液探测程度的差异性,目前对全球海底的热液区分布模式以及热液羽状流分布特征的认识还很不深入,热液区发育类型、热液区发生率、热液区分布间距以及影响热液区分布的主要因素等方面将继续是热液区分布模式研究的重点。尤其是在超慢速扩张西南印度洋脊,因其轴部岩浆总体不足且不连续,表现出特殊的分段性,外加其热液调查程度普遍偏低,如何准确判别热液区发育类型、评估岩浆供给对热液区分布的影响,更加全面深入认识西南印度洋脊热液区分布模式是超慢速扩张洋脊热液区分布模式研究和热液循环系统研究有待解决的课题之一。
随着热液探测技术的发展和调查策略的完善,热液探测具有时空连续性、参数多元化的发展趋势,将为热液系统的研究提供更加精细的探测资料,有助于提高对慢速及超慢速扩张洋脊的探测程度,同时也将提升对低温弥散热液区的认识。
  • 浙江省自然科学青年基金(LQ19D060008,LQ16D060008);国家重点研发计划课题(2018YFC0309901);国际海域资源调查与开发“十三五”项目(DY135-S1-01)及课题“硫化物合同区羽状流特征与找矿应用”(DY135-S1-1-09);国家海洋局海底科学重点实验室开放基金(KLSG1803);国家海洋局第二海洋研究所科研基金(JG1609)。
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2019年第41卷第8期
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doi: 10.3969/j.issn.0253-4193.2019.08.001
  • 接收时间:2018-11-09
  • 首发时间:2026-04-03
  • 出版时间:2019-08-25
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  • 收稿日期:2018-11-09
  • 修回日期:2019-02-11
基金
浙江省自然科学青年基金(LQ19D060008,LQ16D060008);国家重点研发计划课题(2018YFC0309901);国际海域资源调查与开发“十三五”项目(DY135-S1-01)及课题“硫化物合同区羽状流特征与找矿应用”(DY135-S1-1-09);国家海洋局海底科学重点实验室开放基金(KLSG1803);国家海洋局第二海洋研究所科研基金(JG1609)。
作者信息
    1 杭州电子科技大学 机械工程学院 海洋工程技术研究所,浙江 杭州 310018
    2 自然资源部第二海洋研究所 国家海洋局海底科学重点实验室,浙江 杭州 310012
    3 河海大学 海洋学院,江苏 南京 210098

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*陶春辉,研究员,主要从事海洋地球物理研究。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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