Article(id=1292187196623183907, tenantId=1146029695717560320, journalId=1291416733694918677, issueId=1292187163098112845, articleNumber=null, orderNo=null, doi=10.11693/hyhz20260100013, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1768406400000, receivedDateStr=2026-01-15, revisedDate=1771948800000, revisedDateStr=2026-02-25, acceptedDate=null, acceptedDateStr=null, onlineDate=1786011035352, onlineDateStr=2026-08-06, pubDate=1780070400000, pubDateStr=2026-05-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1786011035352, onlineIssueDateStr=2026-08-06, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1786011035352, creator=13701087609, updateTime=1786011035352, updator=13701087609, issue=Issue{id=1292187163098112845, tenantId=1146029695717560320, journalId=1291416733694918677, year='2026', volume='57', issue='3', pageStart='579', pageEnd='830', issueExtLink='null', onlineDate='null', pubDate='1780070400000', pubDateStr='2026-05-30', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1786011027358, creator='13701087609', updateTime=1786013993148, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1292199602611056777, tenantId=1146029695717560320, journalId=1291416733694918677, issueId=1292187163098112845, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1292199602611056778, tenantId=1146029695717560320, journalId=1291416733694918677, issueId=1292187163098112845, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=660, endPage=672, ext={EN=ArticleExt(id=1292187198183464997, articleId=1292187196623183907, tenantId=1146029695717560320, journalId=1291416733694918677, language=EN, title=STAGE-SPECIFIC CHANGES IN THE SEASONAL CYCLE OF PHYTOPLANKTON BIOMASS IN JIAOZHOU BAY (2005~2020) AND THEIR ENVIRONMENTAL DRIVERS, columnId=1292187198095384612, journalTitle=Oceanologia et Limnologia Sinica, columnName=ARTICLES, runingTitle=null, highlight=null, articleAbstract=

Changes in the seasonal cycle of phytoplankton are important indicators of coastal ecosystem responses to climate change and human activities. Based on historical observations from Jiaozhou Bay in 2005, 2010, 2015, and 2020, this study examined long-term variations in the seasonal cycle of phytoplankton biomass and their environmental drivers. The results showed that the seasonal distribution pattern of phytoplankton biomass in Jiaozhou Bay changed markedly during 2005~2020, shifting from a bimodal pattern with winter and summer peaks to a predominantly unimodal pattern with a summer-autumn peak. Winter peak values of net-collected phytoplankton abundance and chlorophyll a concentration decreased substantially, from 103.62×106 cells/m3 and 15.29 μg/L in 2005 to 12.81×106 cells/m3 and 1.13 μg/L in 2020, respectively. Community structure analysis indicated that diatoms consistently dominated the phytoplankton assemblage and that variation in diatom abundance was the primary driver of the observed shift in the seasonal cycle of phytoplankton biomass. In contrast, dinoflagellate abundance declined markedly after peaking in 2010. Correlation analyses suggested that increasing winter water temperature and decreasing phosphate concentration were the main factors underlying the attenuation and eventual disappearance of the winter phytoplankton biomass peak. These findings reveal the long-term evolution of phytoplankton seasonal structure in Jiaozhou Bay under the combined influence of climate change and nutrient adjustment, and offer scientific support for coastal ecosystem management.

, authors=Xiao-Xia SUN1, 2, 3, 4, Ming LIU1, 4, Shu-Jin GUO1, 2, 3, , authorsList=Xiao-Xia SUN, Ming LIU, Shu-Jin GUO, authorCompany=null, correspAuthors=Shu-Jin GUO, 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, fund=null), CN=ArticleExt(id=1292187200226091063, articleId=1292187196623183907, tenantId=1146029695717560320, journalId=1291416733694918677, language=CN, title=2005~2020年胶州湾浮游植物生物量季节周期的阶段性变化特征及其原因解析, columnId=1292187198254768166, journalTitle=海洋与湖沼, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

浮游植物季节周期的变化是近海生态系统响应气候变化和人类活动的重要表征, 但当前针对中国近海浮游植物季节周期变化及其驱动机制的研究仍然较少。基于胶州湾2005、2010、2015和2020年的历史观测数据, 分析了该区域浮游植物生物量季节周期的长期变化特征及其环境驱动机制。结果表明, 2005~2020年间, 胶州湾浮游植物生物量的季节分布格局发生了显著变化, 由以冬季和夏季双峰为特征转变为以夏、秋季单峰为主。浮游植物丰度和叶绿素a浓度的冬季峰值明显下降, 分别由2005年的103.62×106 cells/m3和15.29 μg/L降至2020年的12.81×106 cells/m3和1.13 μg/L。群落结构分析表明, 硅藻始终占据优势地位, 其丰度变化是驱动浮游植物生物量季节周期转变的主要原因; 甲藻丰度在2010年达到峰值后显著下降。相关性分析表明, 冬季水温升高及磷酸盐浓度降低, 可能是导致浮游植物冬季生物量峰值衰减的主要原因。研究结果揭示了气候变化和营养盐调整共同作用下胶州湾浮游植物季节结构的长期演变特征, 可为近海生态系统管理提供科学依据。

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孙晓霞, 研究员, E-mail:

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郭术津, 副研究员, E-mail:
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Continental Shelf Research, 231: 104602., articleTitle=Seasonal dynamics of phytoplankton phosphorus stress in temperate Jiaozhou Bay, North China, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1292187200494526521, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, xref=1, ext=[AuthorCompanyExt(id=1292187200502915130, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, companyId=1292187200494526521, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Jiaozhou Bay Marine Ecosystem Research Station, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China), AuthorCompanyExt(id=1292187200519692347, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, companyId=1292187200494526521, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1中国科学院海洋研究所 山东胶州湾海洋生态系统国家野外科学观测研究站 山东青岛 266071)]), AuthorCompany(id=1292187200611967036, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, xref=2, ext=[AuthorCompanyExt(id=1292187200762961981, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, companyId=1292187200611967036, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2Key Laboratory of Marine Ecology and Environmental Sciences, Shandong Province Key Laboratory of Marine Biodiversity and Bio-resource Sustainable Utilization, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China), AuthorCompanyExt(id=1292187200775544894, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, companyId=1292187200611967036, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2中国科学院海洋研究所海洋生态与环境科学重点实验室 山东省海洋生物多样性与资源可持续利用重点实验室 山东青岛 266071)]), AuthorCompany(id=1292187202381963327, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, xref=3, ext=[AuthorCompanyExt(id=1292187202394546240, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, companyId=1292187202381963327, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao 266237, China), AuthorCompanyExt(id=1292187202402934849, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, companyId=1292187202381963327, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3青岛海洋科技中心海洋生态与环境科学功能实验室 山东青岛 266237)]), AuthorCompany(id=1292187202478432322, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, xref=4, ext=[AuthorCompanyExt(id=1292187202486820931, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, companyId=1292187202478432322, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4University of Chinese Academy of Sciences, Beijing 100049, China), AuthorCompanyExt(id=1292187202495209540, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, companyId=1292187202478432322, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4中国科学院大学 北京 100049)])], figs=[ArticleFig(id=1292187204533641320, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=EN, label=Fig.1, caption=Sampling stations in Jiaozhou Bay, figureFileSmall=GaK9qjnzR8PZazgPoPJ4wQ==, figureFileBig=F9m+9F0ikrI6UdKe8O3idg==, tableContent=null), ArticleFig(id=1292187204621721705, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=CN, label=图1, caption=胶州湾采样站点图, figureFileSmall=GaK9qjnzR8PZazgPoPJ4wQ==, figureFileBig=F9m+9F0ikrI6UdKe8O3idg==, tableContent=null), ArticleFig(id=1292187205078900842, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=EN, label=Fig.2, caption=Seasonal variations in sea surface temperature (℃) and salinity, figureFileSmall=uzlAzdmthHwBOXjS/whV6g==, figureFileBig=NJYMqKwVk28tGdJfCzE7IQ==, tableContent=null), ArticleFig(id=1292187205162786923, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=CN, label=图2, caption=海表温度(℃)和盐度的季节变化特征

注: a、c、e和g分别表示2005、2010、2015和2020年海表温度的月变化特征; b、d、f和h分别表示2005、2010、2015和2020年海表盐度的月变化特征。箱体上下边缘分别表示第75%和25%分位数, 箱体中横线表示中位数; 竖线表示非异常值的最大值和最小值(即1.5倍四分位距范围内); 散点表示异常值

, figureFileSmall=uzlAzdmthHwBOXjS/whV6g==, figureFileBig=NJYMqKwVk28tGdJfCzE7IQ==, tableContent=null), ArticleFig(id=1292187205234090092, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=EN, label=Fig.3, caption=Seasonal variations in nutrient concentrations, figureFileSmall=Ta2KzSNg4y2VDZdmcYJKqw==, figureFileBig=1PFPWf5YJOyxEokP6cHGDg==, tableContent=null), ArticleFig(id=1292187206886645869, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=CN, label=图3, caption=营养盐的季节变化特征

注: a、d、g和j分别表示2005、2010、2015和2020年溶解无机氮(DIN)的月变化特征; 图b、e、h和k分别表示2005、2010、2015和2020年磷酸盐(PO43-)的月变化特征; 图c、f、i和l分别表示2005、2010、2015和2020年硅酸盐(SiO32-)的月变化特征。箱体上下边缘分别表示第75%和25%分位数, 箱体中横线表示中位数; 竖线表示非异常值的最大值和最小值; 散点表示异常值

, figureFileSmall=Ta2KzSNg4y2VDZdmcYJKqw==, figureFileBig=1PFPWf5YJOyxEokP6cHGDg==, tableContent=null), ArticleFig(id=1292187206970531950, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=EN, label=Fig.4, caption=Interannual variations in temperature, salinity, and nutrients across different months, figureFileSmall=o80ADM2S8D4Nl47w1aG9hg==, figureFileBig=764To+xDcMW1wF1OhFAm3Q==, tableContent=null), ArticleFig(id=1292187207029252207, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=CN, label=图4, caption=温度、盐度及营养盐在不同月份的年际变化特征

注: a~e、f~j、k~o和p~t分别表示2、5、8和11月的变化情况; 每一行中, 各子图依次表示海表温度、盐度、溶解无机氮(DIN)、磷酸盐(PO43-)和硅酸盐(SiO32-)在不同年份的变化。符号表示平均值, 误差线表示标准差。由于部分年份冬季缺乏连续3个月的完整观测数据, 为保证不同年份之间数据的可比性, 本文采用季度代表月份(2、5、8和11月)表征四季环境状况

, figureFileSmall=o80ADM2S8D4Nl47w1aG9hg==, figureFileBig=764To+xDcMW1wF1OhFAm3Q==, tableContent=null), ArticleFig(id=1292187207134109808, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=EN, label=Fig.5, caption=Monthly variations in chl a concentration across different years, figureFileSmall=n65QDK3VlGxBRvP9KU3MLA==, figureFileBig=kNMFqVRyR29a2vn7H1/Mjg==, tableContent=null), ArticleFig(id=1292187207217995889, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=CN, label=图5, caption=不同年份叶绿素a浓度的月变化趋势

注: a~d分别表示2005、2010、2015和2020年叶绿素a浓度的月变化特征。图中黑色散点表示各采样站位的叶绿素a浓度值, 红色曲线表示所有站位叶绿素a浓度的月平均变化趋势

, figureFileSmall=n65QDK3VlGxBRvP9KU3MLA==, figureFileBig=kNMFqVRyR29a2vn7H1/Mjg==, tableContent=null), ArticleFig(id=1292187207289299058, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=EN, label=Fig.6, caption=Monthly variations in the abundance of phytoplankton, diatoms, and dinoflagellates across different years, figureFileSmall=d/A4V1cDwsqHptxshlqMgQ==, figureFileBig=NzlZAmpecKxse/vG8qTQDg==, tableContent=null), ArticleFig(id=1292187207368990835, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=CN, label=图6, caption=不同年份浮游植物、硅藻和甲藻丰度的月变化特征

注: a~l分别表示2005、2010、2015和2020年浮游植物总丰度、硅藻丰度和甲藻丰度的月变化情况。黑色散点为各站位观测值, 红色曲线为月平均变化趋势

, figureFileSmall=d/A4V1cDwsqHptxshlqMgQ==, figureFileBig=NzlZAmpecKxse/vG8qTQDg==, tableContent=null), ArticleFig(id=1292187207440294004, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=EN, label=Fig.7, caption=Importance ranking of environmental factors affecting phytoplankton and major taxonomic groups identified by the random forest model, figureFileSmall=M9NDa0VXAnz+fT3AN1iSFw==, figureFileBig=JXZzfEpLfFuReqXKTbRLPw==, tableContent=null), ArticleFig(id=1292187207503208565, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=CN, label=图7, caption=随机森林模型识别的浮游植物及主要类群丰度影响因子的重要性排序

注: 图中展示了基于随机森林模型得到的不同环境因子对浮游植物丰度(a)、叶绿素a浓度(b)、硅藻丰度(c)和甲藻丰度(d)的相对重要性排序。横轴表示环境因子, 纵轴表示变量重要性(以%IncMSE表示)。柱状高度表示各因子对模型预测误差增加的贡献程度, 星号表示变量重要性达到统计显著水平(*P<0.05, **P<0.01, ***P<0.001)

, figureFileSmall=M9NDa0VXAnz+fT3AN1iSFw==, figureFileBig=JXZzfEpLfFuReqXKTbRLPw==, tableContent=null), ArticleFig(id=1292187207566123126, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=EN, label=Fig.8, caption=Correlations between phytoplankton abundance, chl a concentration, and environmental factors in different months, figureFileSmall=t1g/B64pEbUsIbxZl2WG6g==, figureFileBig=C6F1SbsP3T2lS5GdLSZzAw==, tableContent=null), ArticleFig(id=1292187207633231991, tenantId=1146029695717560320, journalId=1291416733694918677, articleId=1292187196623183907, language=CN, label=图8, caption=不同月份浮游植物丰度和叶绿素a浓度与环境因子的相关性分析

注: a~d分别表示2、5、8和11月浮游植物丰度和叶绿素a浓度与环境因子之间的相关性热图。相关性采用Pearson相关系数表示, 圆点颜色和大小分别表示相关性的方向和强度, 数值为对应的相关系数

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2005~2020年胶州湾浮游植物生物量季节周期的阶段性变化特征及其原因解析
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孙晓霞 1, 2, 3, 4 , 刘铭 1, 4 , 郭术津 1, 2, 3,
海洋与湖沼 | 研究论文 2026,57(3): 660-672
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海洋与湖沼 |研究论文 2026 , 57 (3) : 660 -672
2005~2020年胶州湾浮游植物生物量季节周期的阶段性变化特征及其原因解析
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孙晓霞1, 2, 3, 4 , 刘铭1, 4, 郭术津1, 2, 3,
作者信息
  • 1中国科学院海洋研究所 山东胶州湾海洋生态系统国家野外科学观测研究站 山东青岛 266071
  • 2中国科学院海洋研究所海洋生态与环境科学重点实验室 山东省海洋生物多样性与资源可持续利用重点实验室 山东青岛 266071
  • 3青岛海洋科技中心海洋生态与环境科学功能实验室 山东青岛 266237
  • 4中国科学院大学 北京 100049
通讯作者:
郭术津, 副研究员, E-mail:
作者简介:

孙晓霞, 研究员, E-mail:

STAGE-SPECIFIC CHANGES IN THE SEASONAL CYCLE OF PHYTOPLANKTON BIOMASS IN JIAOZHOU BAY (2005~2020) AND THEIR ENVIRONMENTAL DRIVERS
Xiao-Xia SUN1, 2, 3, 4 , Ming LIU1, 4, Shu-Jin GUO1, 2, 3,
Affiliations
  • 1Jiaozhou Bay Marine Ecosystem Research Station, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
  • 2Key Laboratory of Marine Ecology and Environmental Sciences, Shandong Province Key Laboratory of Marine Biodiversity and Bio-resource Sustainable Utilization, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
  • 3Laboratory for Marine Ecology and Environmental Science, Qingdao Marine Science and Technology Center, Qingdao 266237, China
  • 4University of Chinese Academy of Sciences, Beijing 100049, China
出版时间: 2026-05-30 doi: 10.11693/hyhz20260100013
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浮游植物季节周期的变化是近海生态系统响应气候变化和人类活动的重要表征, 但当前针对中国近海浮游植物季节周期变化及其驱动机制的研究仍然较少。基于胶州湾2005、2010、2015和2020年的历史观测数据, 分析了该区域浮游植物生物量季节周期的长期变化特征及其环境驱动机制。结果表明, 2005~2020年间, 胶州湾浮游植物生物量的季节分布格局发生了显著变化, 由以冬季和夏季双峰为特征转变为以夏、秋季单峰为主。浮游植物丰度和叶绿素a浓度的冬季峰值明显下降, 分别由2005年的103.62×106 cells/m3和15.29 μg/L降至2020年的12.81×106 cells/m3和1.13 μg/L。群落结构分析表明, 硅藻始终占据优势地位, 其丰度变化是驱动浮游植物生物量季节周期转变的主要原因; 甲藻丰度在2010年达到峰值后显著下降。相关性分析表明, 冬季水温升高及磷酸盐浓度降低, 可能是导致浮游植物冬季生物量峰值衰减的主要原因。研究结果揭示了气候变化和营养盐调整共同作用下胶州湾浮游植物季节结构的长期演变特征, 可为近海生态系统管理提供科学依据。

胶州湾  /  浮游植物  /  生物量  /  季节周期  /  气候变化  /  营养盐

Changes in the seasonal cycle of phytoplankton are important indicators of coastal ecosystem responses to climate change and human activities. Based on historical observations from Jiaozhou Bay in 2005, 2010, 2015, and 2020, this study examined long-term variations in the seasonal cycle of phytoplankton biomass and their environmental drivers. The results showed that the seasonal distribution pattern of phytoplankton biomass in Jiaozhou Bay changed markedly during 2005~2020, shifting from a bimodal pattern with winter and summer peaks to a predominantly unimodal pattern with a summer-autumn peak. Winter peak values of net-collected phytoplankton abundance and chlorophyll a concentration decreased substantially, from 103.62×106 cells/m3 and 15.29 μg/L in 2005 to 12.81×106 cells/m3 and 1.13 μg/L in 2020, respectively. Community structure analysis indicated that diatoms consistently dominated the phytoplankton assemblage and that variation in diatom abundance was the primary driver of the observed shift in the seasonal cycle of phytoplankton biomass. In contrast, dinoflagellate abundance declined markedly after peaking in 2010. Correlation analyses suggested that increasing winter water temperature and decreasing phosphate concentration were the main factors underlying the attenuation and eventual disappearance of the winter phytoplankton biomass peak. These findings reveal the long-term evolution of phytoplankton seasonal structure in Jiaozhou Bay under the combined influence of climate change and nutrient adjustment, and offer scientific support for coastal ecosystem management.

Jiaozhou Bay  /  phytoplankton  /  biomass  /  seasonal cycle  /  climate change  /  nutrients
孙晓霞, 刘铭, 郭术津. 2005~2020年胶州湾浮游植物生物量季节周期的阶段性变化特征及其原因解析. 海洋与湖沼, 2026 , 57 (3) : 660 -672 . DOI: 10.11693/hyhz20260100013
Xiao-Xia SUN, Ming LIU, Shu-Jin GUO. STAGE-SPECIFIC CHANGES IN THE SEASONAL CYCLE OF PHYTOPLANKTON BIOMASS IN JIAOZHOU BAY (2005~2020) AND THEIR ENVIRONMENTAL DRIVERS[J]. Oceanologia et Limnologia Sinica, 2026 , 57 (3) : 660 -672 . DOI: 10.11693/hyhz20260100013
海洋浮游植物是海洋生态系统中最重要的初级生产者, 是海洋食物网的基础, 其初级生产力贡献了全球海洋超过50%的有机物生产(沈国英等, 2010)。浮游植物通过被浮游动物、鱼类等摄食, 将物质和能量向更高营养级传递, 在维持海洋生态系统结构与功能稳定、调控物质循环和能量流动等方面发挥着关键作用(Reynolds, 2006)。因此, 浮游植物群落的时空变化特征被广泛认为是反映海洋生态系统状态和演变的重要指标。
在海洋环境因子季节性变化的作用下, 浮游植物通常表现出显著的季节周期特征, 其具体形态受纬度、区域水文条件及环境因素的综合调控。在高纬度海域, 浮游植物季节周期往往表现为单一而强烈的春季或夏季峰值(Tian et al, 2001); 而在温带海域, 由于光照、温度和营养盐条件的相对缓和, 浮游植物除主要生长峰外, 常在秋季出现幅度较弱的次高峰(Cebrián et al, 1999; Winder et al, 2010)。由于浮游植物对环境变化高度敏感, 其季节周期易受到气候变化和人类活动的扰动而发生改变, 这种改变不仅反映了生态系统的物理和化学环境变化, 还可能通过食物网途径对整个生态系统产生深远影响。已有研究表明, 许多海洋生物的产卵、发育和生长过程与浮游植物季节周期密切耦合(Hirst et al, 2003)。当浮游植物季节周期发生改变时, 可能导致食物资源供给的时间窗口与高营养级生物关键生命阶段不同步, 进而引发捕食者需求与资源可利用性之间的不匹配, 影响浮游动物的存活率以及幼鱼的生长和补充成功(Scheffer et al, 2000)。因此, 浮游植物季节周期的变化不仅是海洋生态系统对外界驱动因素的响应结果, 也是影响生态系统稳定性和生物资源可持续利用的重要过程。
胶州湾位于山东半岛南部、青岛市近岸, 是典型的半封闭城市化海湾。受长期城市扩张、人口增长及陆源输入增强等因素影响, 胶州湾曾经历比较明显的富营养化过程, 并伴随赤潮等海洋生态灾害的频发(姚云等, 2007)。近年来, 随着流域治理和污染减排措施的实施, 胶州湾营养盐水平和结构发生了明显变化, 但营养盐结构失衡所带来的生态压力仍然持续存在(孙晓霞等, 2011b)。除人类活动影响外, 区域气候变化同样对胶州湾生态环境产生了重要影响, 近几十年海表温度升高及水文条件变化逐渐显现(孙松等, 2011)。胶州湾区域的浮游植物生态学调查研究已经开展了不少。已有研究围绕胶州湾浮游植物群落结构开展了大量工作(杨世民等, 2014; 石晓勇等, 2015; Guo et al, 2019; Liu et al, 2022), 为认识该区域浮游植物群落组成和空间分布奠定了良好基础。此外, 也有少量研究探讨胶州湾浮游植物群落的长期演变趋势(吴玉霖等, 2005; 孙晓霞等, 2011a; Yang et al, 2025)。然而, 目前关于胶州湾浮游植物季节周期长期演变的研究相对不足, 特别是在气候变暖和人类活动持续调整的背景下, 浮游植物季节周期是否发生了系统性重构, 其主导因子是什么, 仍缺乏深入分析。
基于此, 本研究利用胶州湾2005、2010、2015和2020年的历史观测数据, 对浮游植物生物量及其季节周期的长期变化特征进行了系统分析, 并探讨了环境因子的变化规律。进一步结合随机森林模型和Pearson相关性分析, 识别了影响浮游植物季节周期变化的关键环境驱动因素。本研究旨在揭示气候变化和人类活动共同作用下胶州湾浮游植物季节周期的演变特征, 为认识温带型海湾生态系统的动态变化及其可持续管理提供科学依据。
本研究依托国家胶州湾生态系统研究站, 在胶州湾内设置11个固定采样站位(图1)。调查分别于2005、2010、2015和2020年开展, 每个年份均进行为期12个月的连续调查, 每月采样一次。每次调查持续2~3 d, 采样时间主要集中在当月9~13日。所有航次均由“创新号”科考船执行。
水体温度、盐度和pH的垂向剖面采用YSI6600多参数水质仪现场测定。水体透明度使用塞氏盘进行测量。各站位表层(0.5 m)海水采用10 L采水桶采集, 用于叶绿素a (chl a)及溶解无机营养盐样品的分析。
chl a样品经25 mm GF/F玻璃纤维滤膜(WhatmanTM)过滤后, 避光保存于-20 ℃条件下。实验室中, 采用90%丙酮在4 ℃、避光条件下提取24 h后, 使用Turner Designs TrilogyTM荧光计进行测定。溶解无机营养盐样品经酸洗的醋酸纤维素滤膜(孔径0.45 μm)过滤, 滤液在0~4 ℃、避光条件下保存, 并加入HgCl2溶液进行抑制处理。实验室分析采用连续流动分析仪(Skalar SAN+, Skalar Analysis, 荷兰)测定硝酸盐(NO3-)、亚硝酸盐(NO2-)、磷酸盐(PO43-)、硅酸盐(SiO32-)和铵盐(NH4+)浓度。溶解无机氮(DIN)定义为NO3-、NO2-和NH4+浓度之和(Liu et al, 2005)。
浮游植物样品采用浮游植物网进行垂直拖网采集, 自近底层至表层进行一次完整拖网。所用浮游植物网网目尺寸为76 μm, 网口内径为37 cm, 网长为140 cm。采集后的样品用5%福尔马林固定, 置于500 mL塑料样品瓶中避光保存。实验室内在Olympus BX51显微镜下, 于200×或400×放大倍数下对浮游植物进行分类鉴定和计数, 计数采用0.5 mL计数板完成。
数据整理、统计分析及绘图在R软件环境(R version4.5.2)中完成。浮游植物丰度、叶绿素a浓度及环境因子数据在分析前进行质量控制, 对缺失值和异常值进行检查。为识别影响浮游植物季节周期变化的主要环境驱动因子, 采用随机森林(random forest)模型对浮游植物生物量与环境因子之间的关系进行分析。随机森林分析基于R包“rfPermute”实现, 该方法通过多次随机抽样和变量置换评估自变量的重要性, 并能够有效处理非线性关系及多重共线性问题。模型中环境因子作为自变量, 浮游植物丰度或叶绿素a浓度作为响应变量, 通过变量重要性排序识别对浮游植物变化贡献较大的环境因子。同时, 为进一步分析环境因子与浮游植物生物量及主要类群丰度之间的相关关系, 采用Pearson相关性分析。相关系数的显著性水平通过双侧检验进行评估。环境因子与生物变量之间的相关性结果以相关性热图形式展示, 热图绘制使用R包“corrplot”, 以直观反映不同变量之间相关性的方向和强度。所有统计分析均在显著性水平P<0.05下进行。
2005、2010、2015和2020年胶州湾海表温度均表现出明显的季节变化特征(图2a, 2c, 2e, 2g)。海表温度变化范围为–1.57~29.35 ℃, 各年份海表温度在冬季处于全年最低水平, 随后自春季开始逐渐升高, 并在夏季达到峰值, 入秋后逐步下降。不同年份之间, 海表温度的季节变化趋势基本一致。盐度的变化范围为13.13~35.20, 具有明显的季节规律, 低盐度时期集中于夏季, 其余月份盐度基本保持稳定(图2b, 2d, 2f, 2h)。2005年海表盐度在不同月份间波动较为明显, 部分月份(8月)盐度分布范围较大; 2010年盐度整体水平较为集中, 仅在8月出现明显波动。2015年海表盐度全年变化幅度较小; 2020年盐度在全年范围内保持相对稳定, 但在8、9月出现一定程度的下降。
胶州湾溶解无机氮(DIN)变化范围为2.57~ 200.33 μmol/L, 磷酸盐浓度变化范围为0.00~8.61 μmol/L, 硅酸盐浓度变化范围为0.12~64.80 μmol/L (图3)。2005年和2010年, DIN在夏季月份普遍处于较高水平, 而在其他月份相对较低。磷酸盐(PO43-)和硅酸盐(SiO32-)的季节变化特征与DIN基本一致, 均在夏季月份出现较高浓度。除夏季高值外, 2005年和2010年的冬季(1月), DIN、磷酸盐和硅酸盐浓度亦表现出一定程度的升高。相比之下, 2015年和2020年营养盐的季节变化幅度明显减小。同时, 2015年和2020年冬季营养盐浓度整体处于较低水平, 冬季高值现象不明显。
季度月环境因子的年际变化特征如图4所示。在2月, 海表温度在2005~2020年间呈现出持续升高的特征, 从2005年的(2.48±0.64) ℃升高到2020年的(5.55±0.71) ℃ (图4a)。8月和11月温度的年际变化幅度较小(图4k, 4p)。DIN在2月的年际变化幅度相对较小, 4个年份之间差异不明显(图4c)。而在8月和11月, DIN浓度随年份总体呈现降低特征(图4m, 4r)。磷酸盐(PO43-)在不同月份均表现出随年份降低的变化特征。尤其在2月, 2005年为(0.58±0.20) μmol/L, 2015年和2020年已降至0.2 μmol/L以下, 明显低于早期年份(图4d)。在其他月份, 磷酸盐浓度亦整体呈下降特征。硅酸盐(SiO32-)在2月的年际变化幅度较大, 调查期间总体呈现轻微升高的变化特征(图4e); 而在5月、8月和11月, 浓度随年份整体呈降低趋势(图4j, 4o, 4t)。
胶州湾的叶绿素a浓度变化范围为0.01~45.14 μg/L (图5)。2005年呈现明显的双峰型分布(图5a), 最高值分别在2月和8月, 分别为(13.52±10.81) μg/L和(9.08±13.08) μg/L。2010年季节峰值特征不明显(图5b), 全年浓度整体较低, 最高值出现在8月, 平均浓度为(1.60±1.78) μg/L; 此外, 在2月出现轻微升高, 平均浓度为(0.48±0.58) μg/L。2015年浓度高值主要出现在夏末至秋初(图5c), 最高值出现在9月, 为(3.59±1.68) μg/L。2020年浓度最高值出现在8月, 为(10.01±10.16) μg/L, 此外在11月出现次高值, 为(2.34±1.73) μg/L (图5d)。总体来看, 2015年和2020年冬季月份的叶绿素a浓度均维持在较低水平。
浮游植物细胞丰度的季节变化特征与叶绿素a表现出较好的一致性(图6)。2005年细胞丰度呈现明显的季节峰值(图6a), 最高峰出现在2月, 为(85.95±79.21)×106 cells/m3; 此外, 在9月出现一个轻微高值, 为(7.66±5.98)×106 cells/m3。2010年浮游植物细胞丰度的最高峰仍出现在2月, 但峰值降低, 为(36.50±73.20)×106 cells/m3 (图6d)。同时, 在6月和10月也可观察到轻微的高值。2015年浮游植物细胞丰度的高峰出现在9月, 为(96.62±137.34)×106 cells/m3 (图6g), 其余月份丰度整体处于较低水平。2020年浮游植物细胞丰度的最高值出现在8月, 为(113.91±248.42)×106 cells/m3 (图6j)。总体来看, 冬季浮游植物细胞丰度的高峰在调查期间明显减弱, 而夏季的高峰在各年份中持续存在在类群组成方面, 硅藻始终占据浮游植物细胞丰度的绝大部分, 其季节变化趋势与浮游植物总丰度基本一致(图6b, 6e, 6h, 6k)。甲藻的丰度高值主要集中在夏季和秋季(图6c, 6f, 6i, 6l)。
随机森林模型结果显示, 不同环境因子对浮游植物丰度、叶绿素a浓度以及主要类群丰度的影响程度存在差异(图7)。对于浮游植物丰度(图7a), 温度和盐度在变量重要性排序中位居前列, 其次为硝酸盐、硅酸盐和磷酸盐等。在叶绿素a浓度的随机森林结果中(图7b), 温度和盐度同样表现出较高的变量重要性, 营养盐次之。对于硅藻丰度(图7c), 温度和盐度仍为重要性较高的环境因子, 硝酸盐及硅酸盐等在变量重要性排序中占据相对靠前的位置。在甲藻丰度的随机森林结果中(图7d), 浮游动物在所有环境因子中表现出最高的重要性, 其次为温度及部分营养盐因子。
Pearson相关性分析表明, 冬季浮游植物丰度与温度和透明度呈显著负相关(P<0.01), 与亚硝酸盐和磷酸盐呈极显著正相关(P<0.001) (图8)。春季浮游植物丰度仅与硝酸盐呈显著正相关(P<0.01)。在夏季, 浮游植物丰度与氮磷比和硅磷比均呈显著正相关(P<0.01)。相比之下, 秋季浮游植物丰度与各环境因子之间的相关性均未达到显著水平。硅藻丰度与环境因子的相关性特征与浮游植物总丰度基本一致。甲藻丰度在冬季与盐度呈显著负相关, 而在冬、春和夏季均与浮游动物丰度呈显著正相关。
本研究发现, 2005~2020年间胶州湾水温整体呈升高特征, 其中冬季升温最为显著, 由2005年的(2.48±0.64) ℃升高至2020年的(5.55±0.71) ℃ (图4a)。相比之下, 夏季和秋季水温的升高幅度相对较小。这种“冬季升温强于夏季升温”的现象, 已在多个中高纬近岸海域的观测研究中被报道(Graham et al, 2017; Clark et al, 2020; Azarian et al, 2024)。自20世纪后期以来, 中国近海海表温度持续升高, 且冬季升温幅度普遍大于其他季节, 这一冬季升温增强的现象, 通常被认为与区域气候变暖背景下的大气–海洋相互作用变化密切相关(Wang et al, 2023)。在冬季, 中高纬近海水体原本处于强烈冷却和混合状态, 对大气热通量变化高度敏感。随着近几十年来冬季气温升高, 海气之间的感热和潜热通量差异减小, 海洋向大气释放的热量减少, 从而导致冬季海水冷却过程减弱, 表现为冬季平均水温的显著抬升(Clark et al, 2020)。对于半封闭海湾而言, 这种变化往往更为敏感和显著。相较之下, 夏季和秋季水温的变化幅度较小, 可能与夏季海气热通量接近饱和以及强太阳辐射背景下水温对进一步增温的响应受限有关。此外, 夏秋季节风、降水和径流变化等因素对近岸水温的调节作用增强, 也可能在一定程度上削弱年际尺度上水温升高信号的表现(Wang et al, 2023)。总体来看, 胶州湾在2005~2020年间表现出的水温升高特征, 尤其是冬季升温的显著增强, 反映了该区域对气候变暖信号的敏感响应。
除水温升高外, 本研究还观测到胶州湾磷酸盐浓度在2005~2020年间呈现出先升高后显著降低的特征(图4d, i, n, s)。磷酸盐在2、5和8月均表现出随年份先升高后下降的变化趋势, 其中冬季(2月)变化尤为明显: 磷酸盐浓度由2005年的(0.58±0.20) μmol/L降低至2015年和2020年的0.2 μmol/L以下, 明显低于早期年份(图4d)。这表明磷酸盐的长期下降并非局限于某一季节, 而是一种具有普遍性的环境变化特征。类似的结果也在其他研究中被发现。Zhang等(2021a)发现胶州湾磷酸盐在2013年前总体升高, 但在2014~2016年出现了显著下降, 与本研究观测到的2015年和2020年磷酸盐明显降低的结果在时间上是一致的。已有研究指出, 0.2 μmol/L是胶州湾浮游植物由磷相对充足向明显磷胁迫转变的重要阈值, 该阈值以下往往伴随磷利用方式和生态过程的显著调整(Zhang et al, 2021b)。因此, 2015年和2020年的胶州湾冬季环境可以认为处于磷胁迫的状态。磷酸盐浓度的持续降低, 与近20年来胶州湾及其流域陆源输入结构的变化密切相关。近年来在流域污染治理和人为排放控制背景下, 胶州湾陆源营养盐输入发生了明显调整, 水体营养盐水平整体呈下降趋势。尤其是随着污水处理能力提升和排放管理措施的加强, 营养盐通量受到有效控制(Chen et al, 2023)。相比氮素, 磷素更容易通过污水处理和面源控制得到有效削减, 因此磷酸盐浓度往往呈现出更为明显的下降趋势。这一特征也在其他半封闭海湾中得到报道。例如, 基于2004~2018年长期监测数据, Jiang等(2024)发现莱州湾溶解无机磷浓度在整个研究期间呈持续下降趋势。总体而言, 胶州湾磷酸盐浓度在2005~2020 年间表现出的先升高后下降的趋势, 反映了人类活动调控与区域环境变化共同作用下近岸营养盐背景的长期演变。
除磷酸盐外, 胶州湾DIN和硅酸盐在研究期间亦总体呈现下降趋势, 但其变化幅度稍弱于磷酸盐(图4)。这主要反映了不同营养盐来源及调控机制的差别。氮素除点源排放外, 还受到农业面源输入、大气沉降及水体内部再生过程的共同影响, 使其对外源削减措施的响应相对缓慢(Liu et al, 2005)。硅酸盐则主要受河流径流和流域地质背景控制, 其输入过程相对稳定, 对人为排放控制的直接响应有限(Yuan et al, 2018)。尽管不同营养盐的变化幅度存在差异, 但DIN和硅酸盐与磷酸盐在变化方向上的一致性表明, 胶州湾营养盐环境正经历整体性的长期调整, 而非单一要素或个别季节的短期波动。
本研究表明, 2005~2020年间, 胶州湾浮游植物生物量的季节分布格局发生了显著改变。2005年, 浮游植物生物量呈现典型的双峰型季节周期特征, 冬季(2月)和夏季(8~9月)分别形成明显高值, 其中冬季峰为全年最高(图5a)。这一季节格局与以往对胶州湾及邻近海域的观测结果一致。孙晓霞等(2012)研究发现, 2010年以前胶州湾小型和微型浮游植物表现出明显的双峰型季节变化, 小型浮游植物的高峰值通常出现在冬季, 而微型浮游植物则出现在夏季(孙晓霞等, 2012)。孙松等(2002)早期研究也报道胶州湾叶绿素a浓度呈现双周期型的季节变化规律。基于网采浮游植物的长期观测亦显示, 冬季和夏季均为浮游植物丰度的重要高值期(孙晓霞等, 2011a)。随时间推移, 胶州湾浮游植物季节周期结构逐渐发生调整。2010年浮游植物生物量在全年出现多个相对高值, 季节周期的稳定性明显减弱(图5b)。至2015年及2020年, 季节周期进一步简化, 表现为以夏末秋初为主的单一生物量高峰, 而冬季生物量高值显著衰减甚至消失(图5c, 5d)。与此同时, 夏季峰值强度明显增强, 成为主导全年浮游植物生物量变化的核心特征。这一变化表明, 胶州湾浮游植物季节周期不仅在峰值数量上由“双峰”向“单峰”转变, 而且生物量分配的季节重心发生了系统性偏移, 即由冬、夏并重转变为以夏秋季为主导。
尽管浮游植物季节周期结构发生了显著变化, 但群落组成的基本特征在研究期间保持相对稳定。硅藻在2005~2020年间始终占据浮游植物群落的优势地位, 是决定总生物量季节变化的主要类群(图6)。这表明, 胶州湾浮游植物季节周期的演变并非由优势类群的根本性替代所驱动, 而是在硅藻持续占优的背景下, 其季节性生产节律发生了调整。相比之下, 甲藻在不同年份和季节的相对贡献存在一定波动, 尤其在夏秋季更为明显(图6c, 6f, 6i, 6l)。但总体来看, 甲藻并未取代硅藻成为优势类群。因此, 胶州湾浮游植物季节周期由双峰向单峰演变的核心特征, 主要反映了硅藻季节性生产格局的变化。
硅藻的季节性生产为何会发生改变?这需要从控制硅藻生长和季节分布的关键环境因子分析。随机森林分析表明, 温度是影响浮游植物和硅藻细胞丰度的首要重要因子(图7a, 7c)。2005~2020年间, 胶州湾水温整体升高, 其中冬季升温最为显著(图4a), 而相关性分析结果表明冬季浮游植物和硅藻生物量与水温呈显著负相关关系(图8a)。硅藻多为冷水型或宽温型浮游植物, 其最适生长温度通常低于甲藻等类群, 在低温条件下可以保持较高的光合作用效率和生长速率(Wei et al, 2024; Sheng et al, 2025)。冬季水温升高会使水体温度偏离硅藻的最适生理区间, 从而降低其细胞分裂速率和群体增长潜力。已有研究表明, 在温度升高背景下, 硅藻的光系统效率和营养盐利用能力可能受到抑制(Fan et al, 2023), 尤其是在低光照的冬季环境中, 这种不利影响会被放大。另外, 冬季升温可能改变不同浮游植物类群之间的竞争关系。相较于硅藻, 部分非硅藻类群如甲藻在较高温度条件下具有更强的代谢优势。本研究中在2015年冬季发现甲藻的细胞丰度有一个次高峰, 也验证了这一点(图6i)。冬季温度的抬升可能削弱硅藻在低温环境下形成的竞争优势, 使其在群落中难以维持高生物量水平。升温导致的硅藻生长受抑的现象, 在其他海域的研究中也有报道(Xiao et al, 2018; Mutshinda et al, 2025)。
除温度外, 营养盐的长期调整也会对浮游植物季节周期变化产生重要影响。研究期间, 胶州湾磷酸盐浓度显著降低, 尤其在冬季已降至浮游植物磷限制阈值水平以下(图4d)。相关性分析显示, 冬季浮游植物生物量和细胞丰度与磷酸盐浓度呈显著正相关(图8a), 这表明磷可能成为限制胶州湾浮游植物生物量的重要因子。相比之下, DIN和硅酸盐虽然也呈总体下降趋势, 但其变化幅度较小, 且与浮游植物生物量的直接相关性不显著(图8a), 说明这两种营养盐浓度并非决定季节周期变化的直接驱动因素。冬季原本是胶州湾硅藻形成高生物量的重要时期, 其生长依赖于低温条件下较强的垂向混合和相对稳定的营养盐供给。作为“快速生长策略”类群, 在这一阶段, 硅藻通过快速的细胞分裂形成短时间内的高生物量积累, 而磷作为细胞核酸合成、能量代谢和光合作用关键过程中的必需元素, 对硅藻的生长具有不可替代的作用(Brembu et al, 2017)。当磷酸盐浓度下降至限制阈值以下时, 即使氮和硅仍处于相对充足水平, 硅藻的细胞分裂速率和群体增长能力也会受到显著抑制, 从而难以形成以往的冬季生物量高峰。而部分甲藻由于具备利用有机磷或混合营养等生理优势, 对无机磷降低的耐受性相对较高(Huang et al, 2005)。因此, 在磷酸盐显著降低的背景下, 硅藻主导的冬季生物量高峰更易发生衰减。需要指出的是, 尽管夏、秋季营养盐浓度总体呈下降趋势, 浮游植物生物量高峰仍得以维持甚至增强, 说明营养盐供给并非夏、秋季高峰变化的主导因素。近些年胶州湾部分水产养殖区域的撤销, 可能在一定程度上降低了滤食性养殖生物对浮游植物的摄食压力, 从而导致浮游植物在营养盐降低背景下维持较高生物量。该过程仍需结合生物摄食压力和养殖活动变化数据进一步验证。另外, 除水温和营养盐外, 光照条件、水体混合强度及水动力过程等也可能对浮游植物季节变化产生影响。受限于历史数据条件, 本文未对上述过程进行分析, 相关作用有待在未来结合更系统的物理和光学观测资料进一步探讨。
综上, 在冬季升温与磷酸盐持续降低的共同作用下, 浮游植物(主要是硅藻)的冬季生产受到限制, 导致冬季生物量高峰难以维持; 而在夏秋季, 较高的温度条件和相对充足的营养盐供应有利于浮游植物生物量的集中暴发, 从而强化了夏季单峰型季节结构。综合来看, 2005~2020年间胶州湾浮游植物季节周期由双峰型向单峰型的转变, 是在气候变暖背景下, 冬季升温与营养盐结构调整共同作用的结果。这一变化并未伴随优势类群的根本性替代, 而主要表现为硅藻类群季节性生产节律的重新分配。作为典型的半封闭城市化海湾, 胶州湾浮游植物季节周期的显著转变, 反映了海湾生态系统在气候变化与人类活动双重影响下的快速响应特征。
基于胶州湾2005、2010、2015和2020年的观测数据, 研究发现近20年来浮游植物生物量季节周期发生了显著变化, 由早期以冬季和夏季为特征的双峰型结构, 逐渐转变为以夏末秋初为主的单峰型分布, 冬季生物量高峰明显衰减甚至消失。2005~2020年间胶州湾水温整体升高, 冬季升温尤为显著, 同时磷酸盐浓度降低并在冬季降至磷胁迫水平, 二者共同削弱了以硅藻为主的浮游植物在冬季形成高生物量的条件, 推动浮游植物季节周期由双峰型向以夏末秋初为主的单峰型结构转变。本研究揭示了气候变暖背景下冬季升温与营养盐结构调整对近岸海湾浮游植物季节周期的影响, 为理解温带型海湾生态系统的长期演变提供了重要依据, 也为近岸生态环境评估与管理提供了科学参考。

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2026年第57卷第3期
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doi: 10.11693/hyhz20260100013
  • 接收时间:2026-01-15
  • 首发时间:2026-08-06
  • 出版时间:2026-05-30
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  • 收稿日期:2026-01-15
  • 修回日期:2026-02-25
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    1中国科学院海洋研究所 山东胶州湾海洋生态系统国家野外科学观测研究站 山东青岛 266071
    2中国科学院海洋研究所海洋生态与环境科学重点实验室 山东省海洋生物多样性与资源可持续利用重点实验室 山东青岛 266071
    3青岛海洋科技中心海洋生态与环境科学功能实验室 山东青岛 266237
    4中国科学院大学 北京 100049

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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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