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生态学杂志 ›› 2020, Vol. 39 ›› Issue (10): 3350-3362.doi: 10.13292/j.1000-4890.202010.010

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云南中部和南部湖泊夏季浮游植物空间分布及其影响因子

张涛1,陈丽1*,刘晓曦1,尚丽1,刘园园1,王纯波2,赵帅营1,陈光杰1   

  1. 1云南省高原地理过程与环境变化重点实验室, 云南师范大学地理学部, 昆明 650500;2中国科学院水生生物研究所, 武汉 430072)
  • 出版日期:2020-10-10 发布日期:2021-04-09

Spatial pattern and influencing factors of phytoplankton in lakes of central and southern Yunnan in summer.

ZHANG Tao1, CHEN Li1*, LIU Xiao-xi1, SHANG Li1, LIU Yuan-yuan1, WANG Chun-bo2, ZHAO Shuai-ying1, CHEN Guang-jie1#br#   

  1. (1Provincial Key Laboratory of Plateau Geographical Processes and Environmental Change, Faculty of  Geography, Yunnan Normal University, Kunming 650500, China; 2Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan 430072, China).
  • Online:2020-10-10 Published:2021-04-09

摘要: 高原湖泊是云南地区重要的淡水资源储库,目前面临富营养化、重金属污染等环境问题,持续的流域开发明显改变水生生物群落的结构特征与分布模式。浮游植物作为初级生产者,是湖泊食物网的重要基础。本研究以云南中部(8个)和南部(5个)的13个湖泊为对象,于2016年夏季进行浮游植物采样,结合水质数据和湖泊基础资料,对区域尺度上浮游植物的空间分布特征及其影响因子进行识别。结果表明:13个湖泊中浮游植物共有7门72属161种;浮游植物群落结构除抚仙湖、差黑海和石林长湖外,其他湖泊均以蓝藻门为主;Jaccard相异性指数显示,滇池浮游植物群落组成与差黑海、长湖、月湖、阳宗海、长桥海和杞麓湖差异性最大(0.98),长桥海和大屯海浮游植物群落组成最相似(0.19);ANOSIM分析显示,云南中部和南部湖泊浮游植物群落结构差异性显著(R=0.27, P<0.05);南部湖泊生物量总体高于中部湖泊(南部和北部平均生物量分别为105.87和29.27 mg·L-1;t检验: P<0.05);Pearson相关分析表明,浮游植物生物量与温度、总磷(TP)、总氮(TN)、砷和电导率呈显著正相关,与海拔和透明度显著负相关(P<0.05, n=13)。典型对应分析(CCA)结果显示,总磷、氮磷比、锰、钙和空间变量(PCNM1)是影响云南中部和南部湖泊夏季浮游植物空间分布的主要因子;方差分解显示,营养水平(TN、TP)、空间变量(PCNM5)和湖泊类型(水体面积)共同影响了云南中部和南部湖泊夏季浮游植物的空间分布,分别单独解释了群落变化的30.35%、4.90%和3.44%,人类活动与空间变量和湖泊类型分别共同解释了群落变化的6.52%和4.27%;在流域开发日益加强的背景下,水体富营养化已经成为影响该地区浮游植物群落构建的主控因子,而湖泊类型、空间分布等自然环境特征的驱动作用明显降低。因此,养分控制是云南富营养化湖泊环境治理和生态修复的关键内容,是高原湖泊藻类爆发防控和生物多样性保护的重要基础。

关键词: 浮游植物, 群落结构, 空间分布, 环境因子

Abstract: As an important storage of freshwater resources, plateau lakes in Yunnan are facing multiple environmental stresses, such as eutrophication and heavy metal pollution. The structure and distribution pattern of aquatic communities have been changed with the intensification of catchment development. Phytoplankton, an important group of primary producer, are the basis of lake food webs. In this study, we identified the spatial pattern of algal communities and their driving factors during the summer of 2016, in eight and five lakes from the central and south of Yunnan, respectively. The results showed that 161 species of algae were identified, belonging to seven phyla and 73 genera. Cyanophyta was dominant in all the lakes except for lakes of Fuxian, Chaheihai and Changhu. Phytoplankton community of Dianchi Lake was significantly dissimilar with those in lakes of Chaheihai, Changhu, Yuehu, Yangzong, Changqiao and Qilu, with a Jaccard’s dissimilarity value of 0.98. Changqiao Lake was most similar to Datun Lake (0.19). Furthermore, phytoplankton community structure were dissimilar between lakes from the central and southern Yunnan (ANOSIM, R=0.27, P<0.05). The total biomass in lakes of south Yunnan was significantly higher than that of central Yunnan (ttest, P<0.05), with a mean biomass of 105.87 and 29.27 mg·L-1, respectively. The results of Pearson correlation analysis showed that phytoplankton biomass was positively correlated with temperature, total phosphorus (TP), total nitrogen (TN), arsenic and electrical conductivity, and negatively related to elevation and transparency (P<0.05,n=13). The results of Canonical Correspondence Analysis (CCA) showed that TP, N:P ratio, Mn (magnesium), Ca (calcium), and spatial variable (PCNM1) wereamong the significant factors in driving phytoplankton distribution. The analyses of variation partitioning also displayed that the trophic level (TN, TP), spatial variable (PCNM5) and lake type (lake size) independently explained 30.35%, 4.90%, and 3.44% of the total variation in phytoplankton communities, respectively. Meanwhile, the interaction of human activities with spatial variable and lake type accounted for 6.52% and 4.27% of community variation, respectively. With the intensification of catchment development, lake eutrophication was the major driver in structuring phytoplankton communities, with both lake type and spatial distribution having relatively minor impacts on algal community structure. Our results highlight the importance of nutrient control for lake protection and ecological restoration, and thus provide basis for preventing algal blooms and biodiversity conservation in plateau lakes of Yunnan.

Key words: phytoplankton, community structure, spatial distribution, environmental factor.