Microbial co-occurrence networks as a biomonitoring tool for aquatic environments: a review

被引:9
|
作者
Codello, Annachiara [1 ]
Hose, Grant C. [1 ]
Chariton, Anthony [1 ]
机构
[1] Macquarie Univ, Environm DNA & Biomonitoring Lab, Sch Nat Sci, Wallumattagal North Ryde Campus, Darug Nation, NSW 2113, Australia
关键词
BACTERIAL COMMUNITY COMPOSITION; ECOLOGICAL NETWORKS; BACTERIOPLANKTON COMMUNITIES; SENSITIVE INDICATORS; GRAPH-THEORY; PATTERNS; BIODIVERSITY; COMPETITION; EVOLUTION; DYNAMICS;
D O I
10.1071/MF22045
中图分类号
S9 [水产、渔业];
学科分类号
0908 ;
摘要
Aquatic microbial ecosystems are increasingly under threat from human activities, highlighting the need to for the development and application of biomonitoring tools that can identify anthropogenically induced stress across a wide range of environments. To date, microbial biomonitoring has generally focussed on community composition and univariate endpoints, which do not provide discrete information about how species both interact with each other and as a collective. To address this, co-occurrence networks are being increasingly used to complement traditional community metrics. Co-occurrence network analysis is a quantitative analytical tool that examines the interactions between nodes (e.g. taxa) and their strengths. This information can be integrated and visualised as a network, whose characteristics and topological structures can be quantified. To date, co-occurrence network analysis has rarely been applied to aquatic systems. Here we explore the potential of co-occurrence networks as a biomonitoring tool in aquatic environments, demonstrating its capacity to provide a more comprehensive view of how microbial, notably bacterial, communities may be altered by human activities. We examine the key attributes of networks and providence evidence of how these may change as a response to disturbances while also highlighting some of the challenges associated with making the approach routine.
引用
收藏
页码:409 / 422
页数:14
相关论文
共 50 条
  • [21] Evolutionary cores of domain co-occurrence networks
    Stefan Wuchty
    Eivind Almaas
    BMC Evolutionary Biology, 5
  • [22] Evolutionary cores of domain co-occurrence networks
    Wuchty, S
    Almaas, E
    BMC EVOLUTIONARY BIOLOGY, 2005, 5 (1)
  • [23] Identification and Analysis of Co-Occurrence Networks with NetCutter
    Muller, Heiko
    Mancuso, Francesco
    PLOS ONE, 2008, 3 (09):
  • [24] Exploring the random genesis of co-occurrence networks
    Gustedt, Jens
    Raghavan, Hari K.
    Schimit, Pedro
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2011, 390 (09) : 1516 - 1528
  • [25] A theory for species co-occurrence in interaction networks
    Cazelles, Kevin
    Araujo, Miguel B.
    Mouquet, Nicolas
    Gravel, Dominique
    THEORETICAL ECOLOGY, 2016, 9 (01) : 39 - 48
  • [26] Analyzing Co-occurrence Networks of Emojis on Twitter
    Alsaif, Hasan
    Roesch, Phil
    Othman, Salem
    INTELLIGENT COMPUTING, VOL 2, 2021, 284 : 80 - 96
  • [27] A theory for species co-occurrence in interaction networks
    Kévin Cazelles
    Miguel B. Araújo
    Nicolas Mouquet
    Dominique Gravel
    Theoretical Ecology, 2016, 9 : 39 - 48
  • [28] CoNet: Co-occurrence neural networks for recommendation
    Chen, Ming
    Li, Yunhao
    Zhou, Xiuze
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2021, 124 : 308 - 314
  • [29] Co-occurrence Networks for Word Sense Induction
    Humonen, Innokentiy S.
    Makarov, Ilya
    2023 IEEE 21ST WORLD SYMPOSIUM ON APPLIED MACHINE INTELLIGENCE AND INFORMATICS, SAMI, 2023, : 97 - 102
  • [30] Conceptual grouping in word co-occurrence networks
    Veling, A
    van der Weerd, P
    IJCAI-99: PROCEEDINGS OF THE SIXTEENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOLS 1 & 2, 1999, : 694 - 699