Temporal shifts in the phytoplankton network in a large eutrophic shallow freshwater lake subjected to major environmental changes due to human interventions

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2024-07-05 DOI:10.1016/j.watres.2024.122054
Guojun Cai , Yili Ge , Zheng Dong , Yu Liao , Yaoqi Chen , Aiping Wu , Youzhi Li , Huanyao Liu , Guixiang Yuan , Jianming Deng , Hui Fu , Erik Jeppesen
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Abstract

Phytoplankton communities are crucial components of aquatic ecosystems, and since they are highly interactive, they always form complex networks. Yet, our understanding of how interactive phytoplankton networks vary through time under changing environmental conditions is limited. Using a 29-year (339 months) long-term dataset on Lake Taihu, China, we constructed a temporal network comprising monthly sub-networks using “extended Local Similarity Analysis” and assessed how eutrophication, climate change, and restoration efforts influenced the temporal dynamics of network complexity and stability. The network architecture of phytoplankton showed strong dynamic changes with varying environments. Our results revealed cascading effects of eutrophication and climate change on phytoplankton network stability via changes in network complexity. The network stability of phytoplankton increased with average degree, modularity, and nestedness and decreased with connectance. Eutrophication (increasing nitrogen) stabilized the phytoplankton network, mainly by increasing its average degree, while climate change, i.e., warming and decreasing wind speed enhanced its stability by increasing the cohesion of phytoplankton communities directly and by decreasing the connectance of network indirectly. A remarkable shift and a major decrease in the temporal dynamics of phytoplankton network complexity (average degree, nestedness) and stability (robustness, persistence) were detected after 2007 when numerous eutrophication mitigation efforts (not all successful) were implemented, leading to simplified phytoplankton networks and reduced stability. Our findings provide new insights into the organization of phytoplankton networks under eutrophication (or re-oligotrophication) and climate change in subtropical shallow lakes.

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一个大型富营养化浅层淡水湖中浮游植物网络的时间变化,该湖泊因人类干预而发生了重大环境变化
浮游植物群落是水生生态系统的重要组成部分,由于它们具有高度互动性,因此总是形成复杂的网络。然而,我们对浮游植物网络在不断变化的环境条件下如何随时间而变化的了解还很有限。利用中国太湖 29 年(339 个月)的长期数据集,我们使用 "扩展局部相似性分析 "构建了一个由月度子网络组成的时间网络,并评估了富营养化、气候变化和修复工作如何影响网络复杂性和稳定性的时间动态变化。浮游植物的网络结构随着环境的变化呈现出强烈的动态变化。我们的研究结果揭示了富营养化和气候变化通过网络复杂性的变化对浮游植物网络稳定性产生的级联效应。浮游植物网络的稳定性随平均度、模块化和嵌套度的增加而增加,随连接度的增加而减少。富营养化(氮的增加)主要通过增加浮游植物网络的平均度来稳定浮游植物网络,而气候变化,即气候变暖和风速减小,则通过直接增加浮游植物群落的凝聚力和间接减少网络的连通性来增强浮游植物网络的稳定性。在 2007 年之后,浮游植物网络的复杂性(平均度、嵌套度)和稳定性(稳健性、持久性)的时间动态发生了明显的变化和显著下降,当时实施了大量富营养化减缓措施(并非全部成功),导致浮游植物网络简化和稳定性降低。我们的研究结果为亚热带浅水湖泊在富营养化(或再富营养化)和气候变化条件下浮游植物网络的组织提供了新的见解。
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来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
期刊介绍: Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.
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