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引用本文:宋子豪,邹伟,桂智凡,许海,蔡永久.我国常用湖泊营养状态指数研究进展与展望.湖泊科学,2024,36(4):987-1000. DOI:10.18307/2024.0401
Song Zihao,Zou Wei,Gui Zhifan,Xu Hai,Cai Yongjiu.Common-used trophic level index in Chinese lakes: Progress and prospects. J. Lake Sci.2024,36(4):987-1000. DOI:10.18307/2024.0401
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我国常用湖泊营养状态指数研究进展与展望
宋子豪1,2, 邹伟1, 桂智凡2, 许海1, 蔡永久1
1.中国科学院南京地理与湖泊研究所, 湖泊与环境国家重点实验室, 南京 210008;2.湖北师范大学城市与环境学院, 黄石 435002
摘要:
湖泊(包括自然湖泊和人工水库)富营养化已成为世界性的环境问题,营养状态指数是目前最流行的富营养化水平量化方法。然而,不同营养状态指数的基本逻辑和适用水体等方面存在明显差异,不当选取可能会造成营养水平和相关水华风险的错误估计,并引发湖泊保护和修复措施的错位。鉴于此,本文对我国常用营养状态指数的构建思路、共性和差异以及不确定性来源等进行了综述。总体来看,营养状态指数基本构建思路分3种:1) Carlson指数型(如TSI),以透明度(SD)为核心参数,使用SD的2倍变化对应指数的10分差值,假定SD 为64 m时记为指数值0分;2)改良TSI指数型(如TSIm),以叶绿素a(Chl.a)为核心参数,使用Chl.a的2.5倍变化对应指数的10分差值,假定Chl.a 1000 μg/L对应该指数100分;3)营养足迹指数型(如TFI),该指数亦使用Chl.a指示藻类生物量,Chl.a的e倍关系对应藻类生物量的二倍变化和指数10分差值,假定Chl.a为10 μg/L时对应该指数50分。根据上述假设得出对应的基础参数评估方程,然后均以基础参数(SD或Chl.a)与衍生参数间的经验方程 “直接替换”获得衍生参数的评估方程。如上可知,营养状态指数均体现了数值增大表征藻类初级生产力和伴随的水华风险提高的共性,同时本文也从:1)数据集属性和基础指标评估方程获取的方法;2)衍生指标评估方程获取的统计原理;3)分项指标的权重设置方式3个方面分析营养状态指数之间的差异性。未来展望方面,首先,鉴于当前营养状态指数均属于通用性指数,因而建议未来基于上述3种基本类型开发因地制宜的营养状态指数,实现湖泊藻类生产力和水华风险的精准指示;其次,营养状态指数的生态学依据是藻类限制因子理论,营养状态指数各分项指标(即基于总氮、总磷、SD和Chl.a)的差异可以指示初级生产力的限制因子,建议未来开展营养状态指数分项指标差异机制研究,以指导藻类水华防控措施精准施策;再次,除富营养化外,湖泊生态健康受损往往也与其它压力有关,建议未来开展湖泊生态健康对富营养化和其他压力的综合响应机制研究,制定服务于湖泊生态系统健康提升的精准调控路径。本文目的并非将营养状态指数的通用属性“复杂化”,而是旨在阐明营养状态指数的“前世今生”,进而为广大湖泊富营养化相关人员使用指数时提供参考,也希望为我国湖泊营养状态精准量化、后续保护和修复措施的精准实施提供科学依据。
关键词:  营养盐  藻类水华  富营养化  生态修复  湖泊生态系统健康
DOI:10.18307/2024.0401
分类号:
基金项目:国家重点研发计划项目(2022YFC3204100)、国家自然科学基金项目(42107078,42271126)、江苏省双创博士项目(JSSCBS20211399)和中国科学院南京地理与湖泊研究所自主部署项目(NIGLAS2022GS03)联合资助。
Common-used trophic level index in Chinese lakes: Progress and prospects
Song Zihao1,2, Zou Wei1, Gui Zhifan2, Xu Hai1, Cai Yongjiu1
1.State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China;2.College of Urban and Environmental Sciences, Hubei Normal University, Huangshi 435002, P. R. China
Abstract:
The eutrophication of lakes (including natural lakes and artificial reservoirs) and the associated algal blooms are global environmental problems, and the trophic state index is the most popular tool for quantifying eutrophication levels. However, there are obvious differences in ecological principle, applicability, etc. between the commonly used trophic state indices, and improper use may lead to misestimation of eutrophication levels and the associated risk of algal blooms, resulting in misalignment of lake protection and restoration measures. Here, the ecological principle, commonalities, differences and sources of uncertainty of commonly used trophic state indices in China were reviewed in the current study. In general, the ecological principle of trophic level index includes three types: 1) Carlson type (e.g. trophic state index, TSI), secchi depth (SD) was considered as the key variable in Carlson type index, and doubled SD corresponds to the 10 points difference of the index, which hypothetically indicates doubled phytoplankton biomass changes. In addition, it is assumed that when SD reaches 64 m, it is recorded as an index value of 0; 2) modified TSI type (e.g. modified trophic state index, TSIm), chlorophyll-a (Chl.a) is considered as the key variable in modified TSI type, and 2.5-fold change in Chl.a corresponds to the 10-score difference that hypothetically indicated doubled phytoplankton biomass changes. Meanwhile, it is assumed that when Chl.a reaches 1000 μg/L, the corresponding index score is 100; 3) Trophic Footprint Index type (e.g. trophic footprint index, TFI), which also uses Chl.a as an indicator of algal biomass, with the e-fold of Chl.a corresponding to 10-score difference in the index, which hypothetically indicated doubled phytoplankton biomass changes. It was also assumed that 50 points of the index corresponded to a Chl.a of 10 μg/L. The corresponding base equations of the ‘key variable’ (i.e. SD or Chl.a) were derived based on the above assumptions, and then both were ‘directly replaced’ with empirical equation models between the key variable (SD or Chl.a) and the remaining variables to obtain the assessment equations for the derived parameter. According to the extension above, the commonality of the trophic level index is that the values of these indices increased with phytoplankton primary productivity and the associated algal risk. On the other hand, the differences between the Trophic Level Index were discussed from the perspective of 1) the dataset attributes and the method of obtaining the evaluation equation for the key variable, 2) the statistical principle of obtaining the evaluation equation for the non-key variables, and 3) the way of setting the weights for the sub-indices. In terms of prospects, firstly, in order to improve the accuracy of evaluation, it is proposed to develop localised trophic state indices based on the three basic types mentioned above-as the current commonly used indices are characterised by a "one-size-fits-all" approach. Second, the ecological principle of the trophic level index is the theory of phytoplankton limiting factors. The differences in the trophic state index sub-indices (i.e. based on total nitrogen, TP, SD and Chl.a) can be used to identify the limiting factors of phytoplankton. It is suggested that research should be carried out on the mechanism of the differences in the sub-indices, as these studies could guide cost-effective algal control efforts. Finally, since lake ecosystems are often degraded by other pressures in addition to eutrophication, it is recommended that studies be conducted on the mechanism of the integrated response of lake ecological health to eutrophication and other pressures, which can be used to formulate targeted restoration efforts to improve lake ecosystem health. The purpose of this review is not to complicate the use of the trophic level index, but to clarify its ecological principle and applicability, so as to provide a reference for the relevant personnel of lake eutrophication in using the index, and also to provide a scientific basis for the accurate quantification of trophic status and the accurate implementation of subsequent protection and restoration measures of lakes in China.
Key words:  Nutrients  algal bloom  eutrophication  ecological restoration  lake ecosystem health
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