Article(id=1259824977327547206, tenantId=1146029695717560320, journalId=1259198853740773394, issueId=1259824976404800325, articleNumber=null, orderNo=null, doi=10.3724/1000-3207.2025.2025.0372, pmid=null, cstr=32229.14.SSSWXB.2025.0372, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1761148800000, receivedDateStr=2025-10-23, revisedDate=1766678400000, revisedDateStr=2025-12-26, acceptedDate=null, acceptedDateStr=null, onlineDate=1778295281010, onlineDateStr=2026-05-09, pubDate=1778774400000, pubDateStr=2026-05-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1778295281010, onlineIssueDateStr=2026-05-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1778295281010, creator=13701087609, updateTime=1778295281010, updator=13701087609, issue=Issue{id=1259824976404800325, tenantId=1146029695717560320, journalId=1259198853740773394, year='2026', volume='50', issue='5', pageStart='052601-1', pageEnd='052618-200', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1778295280791, creator=13701087609, updateTime=1778295467894, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1259825761310073651, tenantId=1146029695717560320, journalId=1259198853740773394, issueId=1259824976404800325, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1259825761310073652, tenantId=1146029695717560320, journalId=1259198853740773394, issueId=1259824976404800325, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=052612-114, endPage=052612-125, ext={EN=ArticleExt(id=1259824977805697869, articleId=1259824977327547206, tenantId=1146029695717560320, journalId=1259198853740773394, language=EN, title=THE IMPACT OF NUTRIENT SOURCES ON THE BETA DIVERSITY PATTERNS OF MACROZOOBENTHOS IN PLATEAU LAKES: A CASE STUDY OF THE ZHALING LAKE AND ELING LAKE BASINS, columnId=1259824977629537099, journalTitle=Acta Hydrobiologica Sinica, columnName=Water Ecology and Environment, runingTitle=null, highlight=null, articleAbstract=

To explore the influence of nutrient sources on the beta diversity patterns of macrozoobenthic communities in plateau lakes, a quantitative survey of macrozoobenthos and their nutrient sources was conducted in the Zhaling Lake and Eling Lake basins from 2022 to 2024 in the dry and wet seasons. A total of 108 taxa belonging to 8 orders, 39 families were collected. Overall, the lake, habitat, season, and their interactions showed no significant effects on zoobenthos species richness (P>0.05). However, total beta-diversity was relatively high and primarily driven by turnover component. We used parameters in water (chlorophyll a, phytoplankton, total nitrogen, total phosphorus) and catchment characteristics (vegetation coverage, altitude differences, precipitation) to quantify allochthonous inputs and autochthonous nutrients. The Chl.a was significantly higher in the wet season than that in the dry season (P<0.001), and the allochthonous input in the littoral zone of Eling Lake was significantly higher than that in the river region (P<0.01). The Random Forest model indicated that allochthonous nutrient had a stronger correlation with the beta-diversity of the macrozoobenthic community. Allochthonous inputs outweighed autochthonous nutrients in both river and littoral zones during the wet season. In contrast, during the dry season in littoral zone, the importance of autochthonous nutrients such as chlorophyll a and total phosphorus increased significantly, revealing a co-dominant pattern driven by internal and external sources. The total beta diversity and its turnover component exhibited greater sensitivity to allochthonous input, while nestedness in river zone during the wet season also showed certain responsiveness to autochthonous nutrient. These findings provide fundamental scientific support for the ecological management of plateau lake ecosystems.

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为探究营养来源对高原湖泊大型底栖动物群落β多样性格局的影响, 在2022—2024年间干季和湿季对扎陵湖、鄂陵湖流域开展了大型底栖动物及其营养来源的定量调查。共鉴定大型底栖动物8纲39科108属种, 总体来看, 湖泊类型、生境类型、季节单独及交互作用对底栖动物种类数的影响均不显著(P>0.05)。群落整体β多样性较高, 且主要由周转组分驱动。通过水体指标(叶绿素a、浮游植物、营养盐)与集水区特征(植被覆盖率、海拔高差、降水)量化内外源营养, 其中叶绿素a浓度湿季显著高于干季(P<0.001), 湖滨带植被覆盖率显著高于河流区(P<0.01)。随机森林分析表明, 营养源对底栖动物的影响具有生境与季节特异性, 外源输入在湿季河流区及湖滨带的重要性高于内源因子; 而干季湖滨带中, 叶绿素a和总磷等内源因子重要性显著上升, 呈现内外源共同驱动格局。总β多样性及周转组分对外源因子响应更为敏感, 湿季河流区嵌套组分也对内源因子表现出一定响应。研究成果为高原湖泊的生态管理提供基础科学支撑。

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和雅静(1990—), 女, 研究方向为淡水生态、监测及多样性保护。E-mail:
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何滢池(2001—), 女, 硕士研究生; 研究方向为青藏高原生物多样性与进化生态学。E-mail:

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a. distributions of sampling sites; b. habitat types (from top to bottom): littoral zone, intermittent surface water, river zone

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a. Zhaling Lake basin; b. Eling Lake basin

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a. Autochthonous nutrient: TN. Total nitrogen; TP. Total phosphorus; Chl.a. Chlorophyll a; Bphy. Phytoplankton biomass; b. Allochthonous input: Prec. Precipitation; Height. Altitude difference; Vegetation. the Proportion of vegetation cover; ***P<0.001

, figureFileSmall=I4oPa0zjv992nH8PcyY/Qw==, figureFileBig=AnY8iQkVS9TLmUQ1yyn3Iw==, tableContent=null), ArticleFig(id=1259825020180750627, tenantId=1146029695717560320, journalId=1259198853740773394, articleId=1259824977327547206, language=EN, label=Fig.5, caption=Variable importance of the nutrient sources on zoobenthos β-diversity across different seasons and regions based on %IncMSE (Blue bar plot indicates autochthonous nutrient; green bar plot indicates allochthonous input), figureFileSmall=OlBR/BaIQBC83BQNSr2UYg==, figureFileBig=epHVxLM40vNRQRjqbUrSpg==, tableContent=null), ArticleFig(id=1259825020637929774, tenantId=1146029695717560320, journalId=1259198853740773394, articleId=1259824977327547206, language=CN, label=图5, caption=基于%IncMSE的不同季节和区域营养来源对底栖动物β多样性的变量重要性(蓝色条形图代表内源; 绿色条形图代表外源)

TN. Total nitrogen; TP. Total phosphorus; Chl.a. Chlorophyll a; Bphy. Phytoplankton biomass; Prec. Precipitation; Height. Altitude difference; Vegetation. Proportion of vegetation cover

, figureFileSmall=OlBR/BaIQBC83BQNSr2UYg==, figureFileBig=epHVxLM40vNRQRjqbUrSpg==, tableContent=null), ArticleFig(id=1259825021803946295, tenantId=1146029695717560320, journalId=1259198853740773394, articleId=1259824977327547206, language=EN, label=Tab.1, caption=

Results of the chi-square test on the effects of habitat, season and their interaction on zoobenthos species richness

, figureFileSmall=null, figureFileBig=null, tableContent=
湖泊
Lake
因子/交互作用
Factor/Interaction
卡方值
Chisq
自由度
df
P
P value
扎陵湖
Zhaling Lake
生境(湖滨带/河流区) Habitat (lake/river)0.0910.76
季节(湿季/干季) Season (wet/dry)3.2610.07
生境: 季节Habitat: Season0.8110.37
鄂陵湖
Eling Lake
生境Habitat3.7410.05†
季节Season0.0710.79
生境: 季节Habitat: Season0.1410.70
总体
Total
湖泊Lake0.0510.82
生境Habitat3.3910.06
季节Season0.0910.76
湖泊: 生境Lake: Habitat0.9610.33
湖泊: 季节Lake: Season2.1610.14
生境: 季节Habitat: Season0.0110.92
湖泊: 生境: 季节Lake: Habitat: Season0.5410.46
), ArticleFig(id=1259825022240153917, tenantId=1146029695717560320, journalId=1259198853740773394, articleId=1259824977327547206, language=CN, label=表1, caption=

生境、季节及其交互作用对底栖动物种类数影响的卡方检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
湖泊
Lake
因子/交互作用
Factor/Interaction
卡方值
Chisq
自由度
df
P
P value
扎陵湖
Zhaling Lake
生境(湖滨带/河流区) Habitat (lake/river)0.0910.76
季节(湿季/干季) Season (wet/dry)3.2610.07
生境: 季节Habitat: Season0.8110.37
鄂陵湖
Eling Lake
生境Habitat3.7410.05†
季节Season0.0710.79
生境: 季节Habitat: Season0.1410.70
总体
Total
湖泊Lake0.0510.82
生境Habitat3.3910.06
季节Season0.0910.76
湖泊: 生境Lake: Habitat0.9610.33
湖泊: 季节Lake: Season2.1610.14
生境: 季节Habitat: Season0.0110.92
湖泊: 生境: 季节Lake: Habitat: Season0.5410.46
), ArticleFig(id=1259825022760247626, tenantId=1146029695717560320, journalId=1259198853740773394, articleId=1259824977327547206, language=EN, label=Tab.2, caption=

Wilcoxon rank-sum test for the effects of region and seasonal variation on beta diversity and its components

, figureFileSmall=null, figureFileBig=null, tableContent=
湖泊
Lake
因子
Factor
β多样性组分
β-diversity components
统计量WP value
扎陵湖
Zhaling Lake
生境
Habitat
Sørensen8460.63
Turnover9010.32
Nestedness7160.49
季节
Season
Sørensen11220.38
Turnover11990.13
Nestedness8210.12
鄂陵湖
Eling Lake
生境
Habitat
Sørensen6240.13
Turnover6790.31
Nestedness9150.26
季节
Season
Sørensen10340.87
Turnover9050.39
Nestedness14260.001***
), ArticleFig(id=1259825023133540683, tenantId=1146029695717560320, journalId=1259198853740773394, articleId=1259824977327547206, language=CN, label=表2, caption=

生境与季节变化对β多样性及其组分影响的Wilcoxon秩和检验

, figureFileSmall=null, figureFileBig=null, tableContent=
湖泊
Lake
因子
Factor
β多样性组分
β-diversity components
统计量WP value
扎陵湖
Zhaling Lake
生境
Habitat
Sørensen8460.63
Turnover9010.32
Nestedness7160.49
季节
Season
Sørensen11220.38
Turnover11990.13
Nestedness8210.12
鄂陵湖
Eling Lake
生境
Habitat
Sørensen6240.13
Turnover6790.31
Nestedness9150.26
季节
Season
Sørensen10340.87
Turnover9050.39
Nestedness14260.001***
), ArticleFig(id=1259825025037754707, tenantId=1146029695717560320, journalId=1259198853740773394, articleId=1259824977327547206, language=EN, label=Tab.3, caption=

Wilcoxon rank-sum test for the effects of the zoobenthos nutritional sources parameters

, figureFileSmall=null, figureFileBig=null, tableContent=
湖泊
Lake
因子
Factor
营养来源指标
Nutritional source
统计量WP value湖泊
Lake
因子
Factor
营养来源指标
Nutritional source
统计量WP value
扎陵湖
Zhaling lake
生境
Habitat
TN9150.26鄂陵湖
Eling lake
生境
Habitat
TN7830.93
TP8220.79TP5830.06
Chl.a9340.20Chl.a6750.29
Bphy7330.59Bphy7760.89
Prec6590.22Prec8160.834
Height15840.001***Height7921
Vegetation7200.46Vegetation11880.01**
季节
Season
TN11670.21季节
Season
TN7680.048*
TP8940.34TP10620.692
Chl.a2400.001***Chl.a2110.001***
Bphy12220.09Bphy11730.197
Prec6870.009**Prec7470.032*
Height10131Height10131
Vegetation10131Vegetation10131
), ArticleFig(id=1259825025574625629, tenantId=1146029695717560320, journalId=1259198853740773394, articleId=1259824977327547206, language=CN, label=表3, caption=

生境与季节变化对底栖动物营养来源指标影响的Wilcoxon秩和检验

, figureFileSmall=null, figureFileBig=null, tableContent=
湖泊
Lake
因子
Factor
营养来源指标
Nutritional source
统计量WP value湖泊
Lake
因子
Factor
营养来源指标
Nutritional source
统计量WP value
扎陵湖
Zhaling lake
生境
Habitat
TN9150.26鄂陵湖
Eling lake
生境
Habitat
TN7830.93
TP8220.79TP5830.06
Chl.a9340.20Chl.a6750.29
Bphy7330.59Bphy7760.89
Prec6590.22Prec8160.834
Height15840.001***Height7921
Vegetation7200.46Vegetation11880.01**
季节
Season
TN11670.21季节
Season
TN7680.048*
TP8940.34TP10620.692
Chl.a2400.001***Chl.a2110.001***
Bphy12220.09Bphy11730.197
Prec6870.009**Prec7470.032*
Height10131Height10131
Vegetation10131Vegetation10131
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高原湖泊营养来源对大型底栖动物β多样性的影响——以扎陵湖、鄂陵湖流域为例
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何滢池 1, 2 , 和雅静 2 , 吴俊燕 2 , 赵永晶 2 , 徐东坡 3 , 匡箴 3 , 王洪铸 2 , 崔永德 2
水生生物学报 | 水生态与环境 2026,50(5): 052612-114-052612-125
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水生生物学报 | 水生态与环境 2026, 50(5): 052612-114-052612-125
高原湖泊营养来源对大型底栖动物β多样性的影响——以扎陵湖、鄂陵湖流域为例
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何滢池1, 2 , 和雅静2 , 吴俊燕2, 赵永晶2, 徐东坡3, 匡箴3, 王洪铸2, 崔永德2
作者信息
  • 1西藏大学生态环境学院, 拉萨 850000
  • 2中国科学院水生生物研究所, 武汉 430072
  • 3中国水产科学研究院淡水渔业研究中心, 农业农村部淡水渔业和种质资源利用重点实验室, 无锡 214081
  • 何滢池(2001—), 女, 硕士研究生; 研究方向为青藏高原生物多样性与进化生态学。E-mail:

通讯作者:

和雅静(1990—), 女, 研究方向为淡水生态、监测及多样性保护。E-mail:
THE IMPACT OF NUTRIENT SOURCES ON THE BETA DIVERSITY PATTERNS OF MACROZOOBENTHOS IN PLATEAU LAKES: A CASE STUDY OF THE ZHALING LAKE AND ELING LAKE BASINS
Ying-Chi HE1, 2 , Ya-Jing HE2 , Jun-Yan WU2, Yong-Jing ZHAO2, Dong-Po XU3, Zhen KUANG3, Hong-Zhu WANG2, Yong-De CUI2
Affiliations
  • 1School of Ecology and Environment, Xizang University, Lhasa 850000, China
  • 2Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China
  • 3Key Laboratory of Freshwater Fisheries and Germplasm Resources Utilization, Ministry of Agriculture and Rural Affairs, Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Wuxi 214081, China
出版时间: 2026-05-15 doi: 10.3724/1000-3207.2025.2025.0372
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为探究营养来源对高原湖泊大型底栖动物群落β多样性格局的影响, 在2022—2024年间干季和湿季对扎陵湖、鄂陵湖流域开展了大型底栖动物及其营养来源的定量调查。共鉴定大型底栖动物8纲39科108属种, 总体来看, 湖泊类型、生境类型、季节单独及交互作用对底栖动物种类数的影响均不显著(P>0.05)。群落整体β多样性较高, 且主要由周转组分驱动。通过水体指标(叶绿素a、浮游植物、营养盐)与集水区特征(植被覆盖率、海拔高差、降水)量化内外源营养, 其中叶绿素a浓度湿季显著高于干季(P<0.001), 湖滨带植被覆盖率显著高于河流区(P<0.01)。随机森林分析表明, 营养源对底栖动物的影响具有生境与季节特异性, 外源输入在湿季河流区及湖滨带的重要性高于内源因子; 而干季湖滨带中, 叶绿素a和总磷等内源因子重要性显著上升, 呈现内外源共同驱动格局。总β多样性及周转组分对外源因子响应更为敏感, 湿季河流区嵌套组分也对内源因子表现出一定响应。研究成果为高原湖泊的生态管理提供基础科学支撑。

黄河源  /  β多样性  /  内源营养  /  外源输入  /  大型底栖动物

To explore the influence of nutrient sources on the beta diversity patterns of macrozoobenthic communities in plateau lakes, a quantitative survey of macrozoobenthos and their nutrient sources was conducted in the Zhaling Lake and Eling Lake basins from 2022 to 2024 in the dry and wet seasons. A total of 108 taxa belonging to 8 orders, 39 families were collected. Overall, the lake, habitat, season, and their interactions showed no significant effects on zoobenthos species richness (P>0.05). However, total beta-diversity was relatively high and primarily driven by turnover component. We used parameters in water (chlorophyll a, phytoplankton, total nitrogen, total phosphorus) and catchment characteristics (vegetation coverage, altitude differences, precipitation) to quantify allochthonous inputs and autochthonous nutrients. The Chl.a was significantly higher in the wet season than that in the dry season (P<0.001), and the allochthonous input in the littoral zone of Eling Lake was significantly higher than that in the river region (P<0.01). The Random Forest model indicated that allochthonous nutrient had a stronger correlation with the beta-diversity of the macrozoobenthic community. Allochthonous inputs outweighed autochthonous nutrients in both river and littoral zones during the wet season. In contrast, during the dry season in littoral zone, the importance of autochthonous nutrients such as chlorophyll a and total phosphorus increased significantly, revealing a co-dominant pattern driven by internal and external sources. The total beta diversity and its turnover component exhibited greater sensitivity to allochthonous input, while nestedness in river zone during the wet season also showed certain responsiveness to autochthonous nutrient. These findings provide fundamental scientific support for the ecological management of plateau lake ecosystems.

Source region of the Yellow River  /  Beta diversity  /  Autochthonous nutrient  /  Allochthonous input  /  Macrozoobenthos
何滢池, 和雅静, 吴俊燕, 赵永晶, 徐东坡, 匡箴, 王洪铸, 崔永德. 高原湖泊营养来源对大型底栖动物β多样性的影响——以扎陵湖、鄂陵湖流域为例. 水生生物学报, 2026 , 50 (5) : 052612-114 -052612-125 . DOI: 10.3724/1000-3207.2025.2025.0372
Ying-Chi HE, Ya-Jing HE, Jun-Yan WU, Yong-Jing ZHAO, Dong-Po XU, Zhen KUANG, Hong-Zhu WANG, Yong-De CUI. THE IMPACT OF NUTRIENT SOURCES ON THE BETA DIVERSITY PATTERNS OF MACROZOOBENTHOS IN PLATEAU LAKES: A CASE STUDY OF THE ZHALING LAKE AND ELING LAKE BASINS[J]. Acta Hydrobiologica Sinica, 2026 , 50 (5) : 052612-114 -052612-125 . DOI: 10.3724/1000-3207.2025.2025.0372
大型底栖动物在水生态系统的能量流动、物质循环中发挥着重要作用[1], 它们因具备对环境变化敏感、扩散能力弱、生活史相对较长等特点[2], 常用于指示生态系统的稳定性。湖泊大型底栖动物群落结构受到多种因素的综合影响, 包括海拔、水文、底质、水体理化、生物作用、人类干扰等[36]。例如, 大型底栖动物多样性随着海拔升高单调递减[7]; 在中度水文干扰下, 底栖动物不仅物种多样性最高, 生物量和生产量也达到最大[8]; 下降的温度通过改变底栖动物生存环境, 直接或间接地影响底栖动物生物量与多样性, 尤其是软体动物与水生昆虫[9]; 水体氨氮是影响底栖动物分布的重要因子, 且与现存量呈负相关关系[10]。这些环境差异不仅直接塑造了底栖动物的栖息条件, 还通过改变营养来源影响群落的物种组成和多样性格局。
大型底栖动物的营养来源主要包括内源性[11, 12](如浮游植物、附着藻类、水生维管植物等)和外源性[13](如陆源有机物输入)两类。现有相关研究多针对平原湖泊, 随着海拔的上升, 气温下降, 太阳辐射与地理隔离作用增强[14], 以及部分区域雨雪的变化, 使得高原湖泊有着与平原湖泊截然不同的环境条件。高原湖泊(如青藏高原上的湖泊)的主要水源来自冰川融化和雨雪[15], 湖泊理化条件发生了相应的变化, 表现为叶绿素水平变低[16], 浮游植物个体趋向小型化[17]等特征。此外, 陆地土地利用类型的改变会影响进入湖泊内部有机质的类型及含量, 这些环境差异会通过调节营养来源的可获得性和组成, 进而影响底栖动物群落结构。如水温会影响浮游植物的丰度及多样性, 进而与底栖动物群落呈正相关关系[18]; 水生植物不仅能稳定底质, 维持水生态系统结构的复杂性, 还能直接为底栖动物提供营养[19]; 陆地通过地表径流带入水体的有机物则可能改变沉积物特征, 从而驱动底栖动物群落结构的差异[20]; 土地利用类型变化影响输入湖泊的有机质, 导致营养来源和结构的变化, 从而造成底栖动物群落变化[21]
β多样性是衡量不同群落之间物种组成差异或更替程度的指标, 用来反映群落间的异质性。可分为周转和嵌套两个组分, 周转表示样点间物种的替代, 而嵌套反映了物种的包含关系, 即某样点的物种完全存在另一样点之中, 成为其子集[22]β多样性主要受环境过滤与扩散限制两方面的影响, 环境因子与空间差异能解释大部分的β多样性变化[23], 在小尺度研究区域中, β多样性的变化主要由环境因素而非空间因素驱动[24, 25]。近年来, 其作为衡量不同区域或样点间物种组成差异的指标, 已成为理解群落结构构建过程与生态过程的重要工具。但关于营养来源如何塑造底栖动物群落β多样性格局的研究几为空白。一方面, 传统的底栖动物生态学研究多关注物理化学因子的影响, 如温度[9]、沉积物[26]、海拔[27]等, 而对底栖动物营养来源的直接作用缺乏深入探讨。另一方面, 已有研究大多集中于α多样性分析, 对β多样性及其组分的驱动机制研究较少, 尤其高寒地区。在高原湖泊生态系统中, 底栖动物营养内外源输入如何变化, 及其如何通过不同的生态系统过程影响底栖动物群落的β多样性格局, 仍需进一步研究。
扎陵湖、鄂陵湖位于青藏高原东北部, 是黄河源最大的两个淡水湖泊, 也是典型的高原湖泊。为揭示营养来源对高原湖泊底栖动物群落β多样性格局的影响, 本研究以扎陵湖、鄂陵湖两湖泊流域为研究区域, 在2022—2024年对两湖生物和环境进行调查, 分析干季与湿季不同时期、湖滨带(含湖边间歇性水体)与出入湖河段(河流区)不同生境中底栖动物群落的β多样性格局, 量化营养内源(叶绿素a、浮游植物生物量、营养盐)和外源(流域植被覆盖、地形、降水)影响因子对β多样性及其周转、嵌套组分的相对贡献, 旨在揭示高原湖泊营养来源驱动底栖动物群落空间格局的生态机制, 为高原湖泊生态系统的保护和管理提供科学依据。
扎陵湖与鄂陵湖位于黄河源头, 该区域典型的高原季风气候导致年内水量分布不均, 每年70%以上的降雨集中在5—9月, 最大降水在7月, 干湿季分明[28]。鄂陵湖位于青海省果洛藏族自治州玛多县, 扎陵湖位于玛多县和玉树藏族自治州曲麻莱县之间, 海拔在4200 m以上, 都是由地壳运动所形成的高原淡水构造湖, 底质大多为岩石。流域内土地利用类型以高寒草甸、高寒草原为主体, 零星分布有高寒沼泽及裸岩、砾石滩, 无大规模农业开发或城镇建设用地, 人为干扰程度较低[29]。流域植被以典型高寒植物为优势类群, 植被覆盖率约为65%—75%。扎陵湖面积526 km2, 平均水深8.9 m, 鄂陵湖面积610.7 km2, 平均水深17 m, 冰封期从每年11月开始到次年4月下旬结束, 达半年之久[30], 在此期间采样较为困难, 因此本研究的采样时间仅在无冰期, 在此基础上根据降雨量将其分为干季(4—5月)与湿季(6—8月)两个时期进行调查。
本研究在2022—2024年的干季和湿季各进行了3次采样。每个湖泊流域设置点位15个(图 1), 各有11个位于湖滨带(扎陵湖1#—5#、10#—15#; 鄂陵湖3#—10#、13#—15#), 4个位于黄河出入湖河段(扎陵湖6#—9#; 鄂陵湖1#、2#、11#、12#)。本研究中湖滨带点位包括了主体湖沿岸带点位和与湖泊有水文联系的间歇性水体点位(扎陵湖3#、10#; 鄂陵湖5#), 这些间歇性水体是与湖滨带邻近的非持续性地表水体, 可视为湖滨带的季节性延伸。因调查开展于无冰期, 在调查期间该水体始终存在。而由于两湖位于黄河源保护区, 湖内不允许船只进入, 采样点均设在沿岸带, 受地理条件影响, 湖泊部分区域较难抵达, 采样点只设在便于到达的区域。
采集的生物类群包括大型底栖动物和浮游植物, 大型底栖动物采用D形网(边长0.25 m)采集, 每个样点采集不同生境共3 m, 采样面积为0.75 m2。先将大石块和凋落物等在水桶内清洗干净后丢弃, 剩余物倒入水桶并加水搅拌, 随后经60目筛网过滤洗净, 在白瓷盘内挑拣后装入样品瓶, 带回实验室鉴定。在显微镜和解剖镜下进行标本鉴定[3134]。依据相关参考书籍, 寡毛纲和软体动物鉴定到属或者种, 水生昆虫鉴定到科或属, 其他类群(如蛭纲、多毛纲、甲壳类等)至少鉴定到科。
整理各采样点位底栖动物的present/absence (0/1)数据矩阵。基于此矩阵采用Sørensen相异性指数计算各点位群落总β多样性(βsor), 并按照Baselga[22]的方法将总β多样性分解为物种周转(βsim)和嵌套(βnes)两个组分, 用于比较扎陵湖与鄂陵湖底栖动物的空间结构差异。公式:
$ \beta_{{\mathrm{sor}}}=(b+c)/(2a+b+c) \qquad$
$ \beta_{{\mathrm{sim}}}=\min (b,c)/[a+\min (b,c)] $
$ \beta_{{\mathrm{nes}}}=\beta_{{\mathrm{sor}}}-\beta_{{\mathrm{sim}}} \qquad\qquad\qquad$
式中, βsor为Sørensen相异性指数, 代表群落总β多样性; a为两个位点共有的物种数; bc分别为两个位点所特有的物种数; βsim为Simpson相异性指数, 代表β多样性中的周转组分; min(b, c)为b、c中较小的数值; βnes为嵌套性相异性指数, 代表β多样性中的嵌套组分。
本研究将湖泊底栖动物的营养来源分为内源与外源两部分。内源指湖泊内自己生产的供底栖动物生存的有机物来源, 包括藻类、水生植物等, 因扎陵湖鄂陵湖属于构造湖, 底质多为岩石, 湖内几乎没有水生植物, 故主要用浮游植物生物量(Phytoplankton biomass, 下文简写为Bphy)、叶绿素a (Chlorophyll a, 下文简写为Chl.a)、总氮(Total nitrogen, 下文简写为TN)和总磷(Total phosphorus, 下文简写为TP)来表征; 外源指从湖外流入湖内的有机质, 主要用集水区内植被覆盖率(Proportion of vegetation cover, 下文简写为Vegetation)、海拔高差(Altitude difference, 下文简写为Height)和降雨量(Precipitation, 下文简写为Prec)来表征。
内源方面, 浮游植物通过在水体中层采集1 L水样, 随后立即用10 mL鲁哥试液固定, 静置24h充分沉淀后用虹吸管缓慢吸去上清液, 留下含沉淀物的水样30—50 mL装入样品瓶带回实验室进行鉴定。根据浮游植物的细胞形态, 按接近的几何形状测量长度、高度及直径等, 每一种类随机测定30—50个个体, 计算体积平均值, 因浮游植物密度接近1 g/cm3, 所以体积平均值乘以1 L水样中该浮游植物的数量, 便可得到其生物量。叶绿素a采用90%丙酮提取, 使用分光光度法测定, 总氮采用碱性过硫酸钾消解紫外分光光度法进行测定, 总磷采用钼酸铵分光光度法测定, 为了减小系统误差, 样品均重复测定3次。
在外源方面, 首先使用ArcGIS10.8中的Arc Hydro Tools拓展模块, 基于ASTER GDEM 30M分辨率数字高程数据进行水文单元细分, 该过程通过分析流量累积、流向等水文数据, 提取河网结构、划分流域等级并识别汇水单元, 进而确定各采样点位对应的集水区。植被覆盖率通过土地覆盖数据计算可得, 数据来自2022年中国土地覆盖数据集[35](https://zenodo.org/records/12779975), 空间分辨率为30 m。通过统计各集水区内森林和草地的植被覆盖占比, 将其作为外源营养输入的指标。考虑到外源有机质进入湖泊的过程受地形和气候因素影响[36], 本研究进一步纳入海拔高差和降水量作为外源输入强度的调节因子。其中海拔高差基于ASTER GDEM 30 M分辨率数字高程数据计算, 方法为提取集水区河流线段的最高与最低海拔差值, 数据来源于中国科学院计算机网络信息中心地理空间数据云平台(http://www.gscloud.cn)。降雨量来自世界气候数据库[37](https://worldclim.org), 空间分辨率为1 km, 提取采样月份的降雨数据至相应的集水区。
本研究使用负二项广义线性混合模型(Generalized Linear Mixed Model, GLMM)分析扎陵湖和鄂陵湖不同生境类型(湖滨带/河流区)及季节(湿季/干季)对底栖动物种类数的影响。模型中, 生境、季节及其交互作用为固定效应, 湖泊、年份和采样点的嵌套关系为随机效应。对于不同条件下各β多样性组分之间及各营养指标间显著性差异, 均使用Wilcoxon秩和检验进行两两比对。使用随机森林(Random Forest)探究大型底栖动物β多样性与营养来源之间的潜在关系。在模型中, β多样性、周转组分和嵌套组分作为响应变量, 营养来源及环境变量作为解释变量。随机森林模型通过Bootstrap重抽样生成多棵决策树, 并在每棵树的节点分裂时随机选取部分解释变量, 最终以所有决策树的预测结果集成作为模型输出, 以此降低过拟合风险并提升预测稳健性。模型中通过均方误差增加百分比(%IncMSE)评估各变量的重要性, 该指标通过对变量进行随机置换后模型预测误差的变化来评估变量贡献, 数值越大表示该变量对预测贡献越显著, 说明其在解释β多样性变化中的作用越大, 数值较低或接近零表示该变量对模型贡献有限, 数值为负代表其对结果的预测性较低, 去掉该项对结果影响不大甚至更好。
本研究使用ArcGIS10.8对采样图及点位物种组成图进行绘制。使用R.4.4.3软件的lme4 包构建负二项广义线性混合模型(GLMM); 通过betapart包进行β多样性的计算; 各季节、区域β多样性及其组分箱线图和各季节、区域内外源参数箱线图均使用ggplot2包绘制, 同时使用ggsignif包进行Wilcoxon秩和检验并绘图; 使用randomForest包构建随机森林模型以评估环境因子的重要性。
六次调查共采集到大型底栖动物108属种, 隶属于8纲39科。扎陵湖流域共采集到88属种, 其中在主体湖的沿岸带采集到70属种, 周边的间歇性水体中采集到40属种, 河流区采集到45属种; 鄂陵湖流域共采集到77属种, 其中在主体湖的沿岸带采集到63属种, 在周边的间歇性水体中采集到20属种, 河流区采集到52属种。扎陵湖流域底栖动物平均密度为136 ind./m2, 平均生物量为0.73 g/m2; 鄂陵湖流域底栖动物的平均密度为213 ind./m2, 平均生物量为0.44 g/m2。两湖泊密度最高的种类都为水生昆虫, 生物量最高的为其他类群, 主要是钩虾属的种类。
从物种组成空间格局上看(图 2), 综合3年调查结果, 两湖泊流域均以水生昆虫为主, 其中摇蚊科种类在扎陵湖和鄂陵湖分别占水生昆虫种类数的58.6%和61.5%, 湖滨带寡毛类物种数大于河流区, 如在扎陵湖湖滨带记录寡毛类18种, 河流区为10种。扎陵湖最高物种数出现在3# (37属种), 最低物种数出现在5#和9# (均为13属种), 鄂陵湖最高物种数出现在5# (28属种), 最低物种数出现在14# (5属种)。尽管存在局部差异, 但整体物种数的空间变异并不大。
对两湖泊流域底栖动物种类数进行广义线性混合模型负二项检验, 结果显示(表 1), 总体来看, 湖泊类型、生境类型、季节单独及交互作用对底栖动物种类数的影响均不显著(P>0.05)。生境因子的效应(P=0.06)表明, 湖滨带与河流区的研究对象可能存在潜在差异趋势。分湖泊分析结果表明, 除鄂陵湖的生境因子效应边际显著(P=0.05), 其他作用均不明显。
各点位β多样性结果显示(图 3), 扎陵湖、鄂陵湖流域底栖动物群落的Sørensen相异性指数分别为0.75±0.10和0.74±0.11, 总β多样性均处于较高水平, 表明两湖不同点位间底栖动物群落在物种组成上存在明显差异。两湖泊流域周转组分分别占45%—98%和31%—98%, 表明点位之间大型底栖动物群落的β多样性差异主要是由周转作用(物种替换)驱动, 反映各位点间底栖动物种类组成存在显著差异。季节分析显示, 干季与湿季间的底栖动物群落β多样性未呈现显著性差异(P>0.05), 表明季节变化对两湖流域大型底栖动物群落的整体影响较小。
对两湖流域不同生境及季节条件下β多样性及其组分进行Wilcoxon秩和检验, 结果表明(表 2), 在扎陵湖流域, 不论生境还是季节的变化, 对底栖动物β多样性及其组分都不呈现显著性的影响; 而在鄂陵湖流域, 仅有嵌套组分(Nestedness)在季节上呈现极显著的差异, 差异方向为干季>湿季。
对扎陵湖、鄂陵湖底栖动物营养来源调查结果显示(图 4), 在内源方面, 扎陵湖流域叶绿素a (Chl.a)浓度为(1.70±0.12) μg/L, 鄂陵湖流域为(1.82±0.13) μg/L, 且二者湿季含量都显著高于干季(P<0.001; 表 3), 这反映了两湖流域叶绿素含量高低受到季节的影响, 呈现明显的季节分异。扎陵湖浮游植物生物量(Bphy)为(4.04±0.27) mg/L, TN为(0.51±0.04) mg/L, TP为(0.08±0.01) mg/L, 以上3个指标在季节和生境之间并没有明显的差异。鄂陵湖TN为(0.71±0.06) mg/L, 其在季节上有显著差异(P<0.05; 表 3), 差异方向为湿季>干季; 浮游植物生物量(Bphy)为(4.29±0.31) mg/L; TP为(0.08±0.01) mg/L, 二者在季节和生境之间并没有明显的差异。在外源上, 扎陵湖、鄂陵湖流域各集水区的植被覆盖率(Vegetation)分别为(84.5±2.1)%和(79.0±2.1)%, 其中鄂陵湖湖滨带的植被覆盖率显著高于河流区(P<0.01); 扎陵湖、鄂陵湖流域各集水区的海拔高差(Height)分别为(218.2±10.9)和(225.1±9.6) m, 其中扎陵湖两生境地形差异较大, 湖滨带的海拔高差极显著大于河流区(P<0.001)。
随机森林模型基于%IncMSE的变量重要性分析显示(图 5), 底栖动物β多样性及其组分在不同生境类型和季节下主要受外源环境因子驱动, 而内源营养因子的相对重要性整体较低。在所有生境–季节组合中, 植被覆盖率始终表现出最高的变量重要性, 表明其对底栖动物群落空间格局具有重要的塑造作用。从地形因子来看, 海拔高差在湖滨带中的重要性显著高于河流区(图 5), 这反映了地形对外源物质向湖泊输送效率的调节作用。相比之下, 内源营养因子的重要性相对较低且在不同情境下变化较小。从β多样性组分来看, 总β多样性和周转组分对外源因子的响应更为敏感, 而嵌套组分中各因子的影响差异相对较小。季节差异分析表明, 干季时各环境因子的重要性分化更为明显, 内源因子的重要性显著增加, 湿季时因子间的重要性差异相对减小。总的来说, 外源营养输入是塑造扎陵湖、鄂陵湖流域底栖动物群落空间异质性的主导因素, 且其影响程度受生境区域类型和季节变化的调节。
高原湖泊具有高海拔、低水温、湖内营养物质较低且有机碎屑分解较慢等特点[17], 独特的地理环境形成了特有的物种库。从生态习性上来看, 冷水性、耐低氧及广适应性的种类占比较高, 如哑口仙女虫、拟突摇蚊属、毛突摇蚊属、单寡角摇蚊属等适应于低温低氧环境的物种[33, 38]。从摄食方式上看, 高原湖泊受到低温低氧等环境因素的影响, 有机碎屑分解较慢[39]。而钩虾属作为广适应性撕食者, 能够较好利用进入湖泊的粗颗粒有机物, 更容易利用高原湖泊中的营养物质[40], 因此该类群在扎陵湖与鄂陵湖流域中占据较为重要的生态位。相较之下, 滤食性和刮食性的软体动物在此环境中分布较少。从繁殖策略上看, 高原湖泊短暂的无冰期要求底栖动物具备快速繁殖能力或延长发育周期的适应性。多数种类采用r策略, 如摇蚊科中更适应冷水的类群(直突摇蚊亚科和寡角摇蚊亚科)能在短时间内大量繁殖, 其中部分种类可以通过延长幼虫期以适应严酷环境[41], 而寡毛类中适应高原的种类可通过出芽、断裂等无性繁殖方式在底泥中快速扩散以获得更多个体。因此, 这些类群在高原湖泊底栖动物群落中占据更大的比重。
作为典型的高原湖泊, 其底栖动物群落的营养来源结构显著区别于平原湖泊。相比平原湖泊普遍具有较高的初级生产力、营养来源主要由内源过程驱动, 高原湖泊受低温、强风混合和生长季短等限制, 湖内整体自生有机物产量较低。虽然从高原湖泊的生态特性来看, 底栖动物及大多水生生物主要集中分布在浅水及湖滨带, 但深水区水深大、光照穿透有限、生境结构简单, 这也导致内源性碳输入不足且空间异质性较弱[42]。在这种背景下, 外源输入便成为维持底栖动物营养供给的主要来源。高原流域陆地植被虽然类型相对单一, 但因地处青藏高原, 人类干扰较平原地区大幅降低, 其通过地表径流等方式进入湖泊的碳源则会成为更优质的营养来源, 而水生生物的摄食具有选择性, 因此相较于内部营养, 底栖动物更倾向于从外部获取优质营养来源以供自身生长需要[43, 44]。这一点也在本研究结果中得到体现, 即外源营养在几乎所有生境–季节组合中均显示出较高的变量重要性, 反映了外源碳源对群落结构的关键作用, 并与Hershey等[45]的研究结论一致(图 5)。
在高海拔湖泊中, 底栖动物群落常表现出较大的异质性[46], 这是由底质、环境及营养物质等条件不同所导致的。周转组分在β多样性中的主导地位表明, 不同生境间底栖动物群落差异主要源于物种的空间替代而非简单的嵌套丢失(图 3)。在高海拔、低温低氧等环境条件下, 能够存活的物种本身就是经过环境过滤, 因此不同生境间的群落差异更多表现为生态位特化导致的物种替换, 而非基于定殖能力差异的渐进性种类丢失。值得注意的是, 不同β多样性组分对生境类型的响应存在明显交互效应: 虽然本研究湖滨带区域包括了间歇性水体, 但其与湖滨带相邻近且均属于流速较缓的静水水体, 周转组分在湖滨带的外源敏感性远高于河流区, 而嵌套组分在两种生境间的差异相对较小(图 5), 该模式表明, 静水环境的营养梯度对大型底栖动物的物种更替有着显著的影响, 更有利于促进生态位分化[47], 而在流水环境, 均化作用使营养条件差异变小, 因此基于营养条件的群落分化程度降低。
河流区与湖滨带底栖动物β多样性的驱动机制存在显著差异。在河流区, 外源输入的重要性相对较低, 而内源因子(如叶绿素a、浮游植物)的影响相对均衡, 且在干季有占主导的趋势, 这可能是因为河流区和湖滨带在水文、地形及生态过程等方面存在一定差异, 导致了底栖动物群落β多样性驱动机制的不同[48]。河流区水流通常较为湍急, 水体交换频繁, 外源性输入的影响相对较小, 因此内源性因子对底栖动物群落的影响相对重要。相比之下, 湖滨带的水流较为缓慢, 水体交换较少, 因此外源输入和海拔高差的重要性显著增强, 反映了静水环境中地形对营养物质汇聚和沉积过程的调节作用更为突出, 形成了更强的空间异质性格局。季节差异进一步揭示了环境过滤的时间动态。干季时各因子重要性分化明显, 特别是外源输入的主导作用更为突出, 这可能与干季降水减少、外源输入成为限制性资源有关。湿季时, 整个水生态系统可能更多地依赖于内部的物质循环和能量流动, 使得内源性因子对底栖动物群落的影响的重要性增加, 从而反映了充沛降水对于水生态系统营养限制的缓解作用。
本研究证实了在高原湖泊中外源营养输入在驱动群落组装过程中的重要作用。这种以外源输入为主导的营养供给模式对高原湖泊的保护管理具有重要启示: 维护流域植被完整性和合理的土地利用格局对湖泊生态系统健康至关重要。在全球气候变化背景下, 降水格局的改变可能影响外源物质的输送过程, 进而改变底栖动物群落结构, 这为高原湖泊生态系统的长期监测和适应性管理提供了科学依据。
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doi: 10.3724/1000-3207.2025.2025.0372
  • 接收时间:2025-10-23
  • 首发时间:2026-05-09
  • 出版时间:2026-05-15
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  • 收稿日期:2025-10-23
  • 修回日期:2025-12-26
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    1西藏大学生态环境学院, 拉萨 850000
    2中国科学院水生生物研究所, 武汉 430072
    3中国水产科学研究院淡水渔业研究中心, 农业农村部淡水渔业和种质资源利用重点实验室, 无锡 214081

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和雅静(1990—), 女, 研究方向为淡水生态、监测及多样性保护。E-mail:
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2种不同金属材料的力学参数

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

Genus
种数
Number of
species
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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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