浮游细菌组成作为环境状况的指标:利用河口群落指标值分析的原理证明

IF 1.6 4区 环境科学与生态学 Q3 ECOLOGY
Cecilia Alonso, Emiliano Pereira, Florencia Bertoglio, Miquel De Cáceres, Rudolf Amann
{"title":"浮游细菌组成作为环境状况的指标:利用河口群落指标值分析的原理证明","authors":"Cecilia Alonso, Emiliano Pereira, Florencia Bertoglio, Miquel De Cáceres, Rudolf Amann","doi":"10.3354/ame01979","DOIUrl":null,"url":null,"abstract":"ABSTRACT: Increasing awareness of environmental impacts caused by anthropogenic activities highlights the need to determine indicators of environmental status that can be routinely assessed at large spatial and temporal scales. Microbial communities comprise the greatest share of biological diversity on Earth and can rapidly reflect recent environmental changes while providing a record of past events. However, they have rarely been targeted in the search for ecological indicators of habitat types, environmental conditions, or environmental changes. Here, as a proof of principle, we analysed the bacterioplankton community composition of 4 estuaries in North and South America, Europe, and Asia, and looked for indicators of groups of samples defined using partition techniques, according to primary physicochemical variables typically monitored to infer water quality. Indicator value analysis (<i>IndVal</i>) was conducted to identify indicator operational taxonomic units (OTUs; analogous to species in other fields of ecology) in each group. These bacterioplankton-based indicators exhibited a high capacity to predict the group membership of the samples within each estuary and to correctly assign the samples to the appropriate estuary in a combined data set, employing different machine learning techniques. The indicators were composed of OTUs belonging to several bacterial phyla, which responded significantly and differentially to the environmental variables used to define the groups of samples. Moreover, the predictive values of these bacterial indicators were generally higher than those of other biological assemblages commonly used for environmental monitoring. Therefore, this approach appears to be a promising tool to complement existing strategies for monitoring and conservation of aquatic systems worldwide.","PeriodicalId":8112,"journal":{"name":"Aquatic Microbial Ecology","volume":"125 s1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2022-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bacterioplankton composition as an indicator of environmental status: proof of principle using indicator value analysis of estuarine communities\",\"authors\":\"Cecilia Alonso, Emiliano Pereira, Florencia Bertoglio, Miquel De Cáceres, Rudolf Amann\",\"doi\":\"10.3354/ame01979\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT: Increasing awareness of environmental impacts caused by anthropogenic activities highlights the need to determine indicators of environmental status that can be routinely assessed at large spatial and temporal scales. Microbial communities comprise the greatest share of biological diversity on Earth and can rapidly reflect recent environmental changes while providing a record of past events. However, they have rarely been targeted in the search for ecological indicators of habitat types, environmental conditions, or environmental changes. Here, as a proof of principle, we analysed the bacterioplankton community composition of 4 estuaries in North and South America, Europe, and Asia, and looked for indicators of groups of samples defined using partition techniques, according to primary physicochemical variables typically monitored to infer water quality. Indicator value analysis (<i>IndVal</i>) was conducted to identify indicator operational taxonomic units (OTUs; analogous to species in other fields of ecology) in each group. These bacterioplankton-based indicators exhibited a high capacity to predict the group membership of the samples within each estuary and to correctly assign the samples to the appropriate estuary in a combined data set, employing different machine learning techniques. The indicators were composed of OTUs belonging to several bacterial phyla, which responded significantly and differentially to the environmental variables used to define the groups of samples. Moreover, the predictive values of these bacterial indicators were generally higher than those of other biological assemblages commonly used for environmental monitoring. Therefore, this approach appears to be a promising tool to complement existing strategies for monitoring and conservation of aquatic systems worldwide.\",\"PeriodicalId\":8112,\"journal\":{\"name\":\"Aquatic Microbial Ecology\",\"volume\":\"125 s1\",\"pages\":\"\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2022-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Aquatic Microbial Ecology\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.3354/ame01979\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Aquatic Microbial Ecology","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.3354/ame01979","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

摘要:人类活动对环境影响的认识日益增强,表明需要确定可在大时空尺度上常规评估的环境状况指标。微生物群落构成了地球上生物多样性的最大份额,可以迅速反映最近的环境变化,同时提供过去事件的记录。然而,在寻找生境类型、环境条件或环境变化的生态指标方面,它们很少成为目标。在这里,作为原理证明,我们分析了北美、南美、欧洲和亚洲4个河口的浮游细菌群落组成,并根据通常监测的主要物理化学变量来推断水质,寻找使用分区技术定义的样品组的指标。采用指标值分析(IndVal)确定指标操作分类单位(otu);(类似于其他生态学领域中的物种)。这些基于浮游细菌的指标显示出很高的能力,可以预测每个河口内样本的群体成员,并使用不同的机器学习技术在组合数据集中正确地将样本分配到适当的河口。这些指标由属于几个细菌门的otu组成,它们对用于定义样品群的环境变量有显著且差异的响应。此外,这些细菌指标的预测值普遍高于其他常用的环境监测生物组合。因此,这种方法似乎是一种很有前途的工具,可以补充世界范围内监测和保护水生系统的现有战略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bacterioplankton composition as an indicator of environmental status: proof of principle using indicator value analysis of estuarine communities
ABSTRACT: Increasing awareness of environmental impacts caused by anthropogenic activities highlights the need to determine indicators of environmental status that can be routinely assessed at large spatial and temporal scales. Microbial communities comprise the greatest share of biological diversity on Earth and can rapidly reflect recent environmental changes while providing a record of past events. However, they have rarely been targeted in the search for ecological indicators of habitat types, environmental conditions, or environmental changes. Here, as a proof of principle, we analysed the bacterioplankton community composition of 4 estuaries in North and South America, Europe, and Asia, and looked for indicators of groups of samples defined using partition techniques, according to primary physicochemical variables typically monitored to infer water quality. Indicator value analysis (IndVal) was conducted to identify indicator operational taxonomic units (OTUs; analogous to species in other fields of ecology) in each group. These bacterioplankton-based indicators exhibited a high capacity to predict the group membership of the samples within each estuary and to correctly assign the samples to the appropriate estuary in a combined data set, employing different machine learning techniques. The indicators were composed of OTUs belonging to several bacterial phyla, which responded significantly and differentially to the environmental variables used to define the groups of samples. Moreover, the predictive values of these bacterial indicators were generally higher than those of other biological assemblages commonly used for environmental monitoring. Therefore, this approach appears to be a promising tool to complement existing strategies for monitoring and conservation of aquatic systems worldwide.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Aquatic Microbial Ecology
Aquatic Microbial Ecology 环境科学-海洋与淡水生物学
CiteScore
3.30
自引率
0.00%
发文量
8
审稿时长
3.0 months
期刊介绍: AME is international and interdisciplinary. It presents rigorously refereed and carefully selected Research Articles, Reviews and Notes, as well as Comments/Reply Comments (for details see AME 27:209), Opinion Pieces (previously called ''As I See It'') and AME Specials. For details consult the Guidelines for Authors. Papers may be concerned with: Tolerances and responses of microorganisms to variations in abiotic and biotic components of their environment; microbial life under extreme environmental conditions (climate, temperature, pressure, osmolarity, redox, etc.). Role of aquatic microorganisms in the production, transformation and decomposition of organic matter; flow patterns of energy and matter as these pass through microorganisms; population dynamics; trophic interrelationships; modelling, both theoretical and via computer simulation, of individual microorganisms and microbial populations; biodiversity. Absorption and transformation of inorganic material; synthesis and transformation of organic material (autotrophic and heterotrophic); non-genetic and genetic adaptation; behaviour; molecular microbial ecology; symbioses.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信