Accumulated temperature dictates the regional structural variation of prokaryotic periphyton at soil-water interface in paddy fields

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2024-08-13 DOI:10.1016/j.watres.2024.122259
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Abstract

As a pervasive microbial aggregate found at the water-soil interface in paddy fields, periphyton plays crucial roles in modulating nutrient biogeochemical cycling. Consequently, it effectively mitigates non-point source pollution due to its diverse composition. Despite its significance, the mechanisms governing periphyton diversity across different rice planting regions remain poorly understood. To bridge this gap, we investigated periphyton grown in 200 paddy fields spanning 25° of latitude. Initially, we analyzed local diversity and latitudinal variations in prokaryotic communities within paddy field periphyton, identifying 7 abundant taxa, 42 moderate taxa, and 39 rare taxa as the fundamental prokaryotic framework. Subsequently, to elucidate the mechanisms governing periphyton diversity across large scales, we constructed interaction models illustrating triangular relationships among local richness, assembly, and regional variation of prokaryotic subcommunities. Our findings suggest that accumulated temperature-driven environmental filtering partially influences the assembly process of prokaryotes, thereby impacting local species richness and ultimately governing regional structural variations in periphyton. Furthermore, we determined that a latitude of 39° represents the critical threshold maximizing local species richness of periphyton in paddy fields. This study advances our understanding of the factors shaping periphyton geo-imprints and provides valuable insights into predicting their responses to environmental changes, potentially influencing rice production outcomes.

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积温决定了水稻田水土界面原核栖息生物的区域结构变化
作为水稻田水土界面上的一种普遍微生物集合体,浮游生物在调节养分的生物地球化学循环方面发挥着至关重要的作用。因此,浮游生物因其组成的多样性而有效缓解了非点源污染。尽管浮游生物具有重要意义,但人们对不同水稻种植区浮游生物多样性的调节机制仍然知之甚少。为了弥补这一差距,我们对纬度跨度为 25° 的 200 块稻田中生长的浮游生物进行了调查。首先,我们分析了稻田浮游生物中原核生物群落的地方多样性和纬度差异,确定了 7 个丰富类群、42 个中等类群和 39 个稀有类群作为基本的原核生物框架。随后,为了阐明大尺度浮游生物多样性的支配机制,我们构建了相互作用模型,说明了原核生物亚群落的局部丰富度、集合度和区域变化之间的三角关系。我们的研究结果表明,累积的温度驱动的环境过滤部分影响了原核生物的组装过程,从而影响了当地物种的丰富度,并最终控制了浮游生物的区域结构变化。此外,我们还确定,39°的纬度是最大限度地提高稻田围岩局部物种丰富度的临界阈值。这项研究加深了我们对形成浮游生物地理印迹的因素的理解,并为预测浮游生物对环境变化的反应提供了有价值的见解,从而对水稻生产结果产生潜在影响。
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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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