Analysis of the Influence of Seasonal Water Column Dynamics on the Relationship between Marine Viruses and Microbial Food Web Components Using an Artificial Neural Network

Artificial neural network analysis (ANN) is used to study the seasonal distribution of viruses and microbial food web (MFW) components in the open Adriatic Sea. The effect of viruses within the MFW is often overlooked, although viruses play an important role in microbial community dynamics. The resu...
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Autor*in:	Marin Ordulj [verfasserIn] Danijela Šantić [verfasserIn] Frano Matić [verfasserIn] Slaven Jozić [verfasserIn] Stefanija Šestanović [verfasserIn] Mladen Šolić [verfasserIn] Jere Veža [verfasserIn] Živana Ninčević Gladan [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	viruses heterotrophic bacteria autotrophic picoplankton heterotrophic nanoflagellates oligotrophic environment P-limitation

Übergeordnetes Werk:	In: Journal of Marine Science and Engineering - MDPI AG, 2014, 11(2023), 3, p 639
Übergeordnetes Werk:	volume:11 ; year:2023 ; number:3, p 639

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/jmse11030639

Katalog-ID:	DOAJ087323915

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allfieldsSound	10.3390/jmse11030639 doi (DE-627)DOAJ087323915 (DE-599)DOAJaa2e90d3578d4011815e46665b7e4d8b DE-627 ger DE-627 rakwb eng VM1-989 GC1-1581 Marin Ordulj verfasserin aut Analysis of the Influence of Seasonal Water Column Dynamics on the Relationship between Marine Viruses and Microbial Food Web Components Using an Artificial Neural Network 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Artificial neural network analysis (ANN) is used to study the seasonal distribution of viruses and microbial food web (MFW) components in the open Adriatic Sea. The effect of viruses within the MFW is often overlooked, although viruses play an important role in microbial community dynamics. The results showed that the strongest influence is found in the nonlinear relationship between viruses and temperature. In addition, the algorithm showed that the number of viral populations in the P-limited open sea varies by season and according to the abundance of their main hosts, HB. A strong positive relationship between viruses and HB was found in more than 50% of the observed data. Moreover, this algorithm confirmed the association of the virus with the autotrophic part of the picoplankton and with heterotrophic nanoflagellates. The dynamics of the four resulting clusters, characterized by biological and environmental parameters, is described as a cyclic pattern in the water layer above the thermocline. Neural gas network analysis has been shown to be an excellent tool for describing changes in MFW components in the open Adriatic. viruses heterotrophic bacteria autotrophic picoplankton heterotrophic nanoflagellates oligotrophic environment P-limitation Naval architecture. Shipbuilding. Marine engineering Oceanography Danijela Šantić verfasserin aut Frano Matić verfasserin aut Slaven Jozić verfasserin aut Stefanija Šestanović verfasserin aut Mladen Šolić verfasserin aut Jere Veža verfasserin aut Živana Ninčević Gladan verfasserin aut In Journal of Marine Science and Engineering MDPI AG, 2014 11(2023), 3, p 639 (DE-627)771274181 (DE-600)2738390-8 20771312 nnns volume:11 year:2023 number:3, p 639 https://doi.org/10.3390/jmse11030639 kostenfrei https://doaj.org/article/aa2e90d3578d4011815e46665b7e4d8b kostenfrei https://www.mdpi.com/2077-1312/11/3/639 kostenfrei https://doaj.org/toc/2077-1312 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2023 3, p 639
language	English
source	In Journal of Marine Science and Engineering 11(2023), 3, p 639 volume:11 year:2023 number:3, p 639
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topic_facet	viruses heterotrophic bacteria autotrophic picoplankton heterotrophic nanoflagellates oligotrophic environment P-limitation Naval architecture. Shipbuilding. Marine engineering Oceanography
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callnumber-first	V - Naval Science
author	Marin Ordulj
spellingShingle	Marin Ordulj misc VM1-989 misc GC1-1581 misc viruses misc heterotrophic bacteria misc autotrophic picoplankton misc heterotrophic nanoflagellates misc oligotrophic environment misc P-limitation misc Naval architecture. Shipbuilding. Marine engineering misc Oceanography Analysis of the Influence of Seasonal Water Column Dynamics on the Relationship between Marine Viruses and Microbial Food Web Components Using an Artificial Neural Network
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topic_title	VM1-989 GC1-1581 Analysis of the Influence of Seasonal Water Column Dynamics on the Relationship between Marine Viruses and Microbial Food Web Components Using an Artificial Neural Network viruses heterotrophic bacteria autotrophic picoplankton heterotrophic nanoflagellates oligotrophic environment P-limitation
topic	misc VM1-989 misc GC1-1581 misc viruses misc heterotrophic bacteria misc autotrophic picoplankton misc heterotrophic nanoflagellates misc oligotrophic environment misc P-limitation misc Naval architecture. Shipbuilding. Marine engineering misc Oceanography
topic_unstemmed	misc VM1-989 misc GC1-1581 misc viruses misc heterotrophic bacteria misc autotrophic picoplankton misc heterotrophic nanoflagellates misc oligotrophic environment misc P-limitation misc Naval architecture. Shipbuilding. Marine engineering misc Oceanography
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title	Analysis of the Influence of Seasonal Water Column Dynamics on the Relationship between Marine Viruses and Microbial Food Web Components Using an Artificial Neural Network
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title_full	Analysis of the Influence of Seasonal Water Column Dynamics on the Relationship between Marine Viruses and Microbial Food Web Components Using an Artificial Neural Network
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author_browse	Marin Ordulj Danijela Šantić Frano Matić Slaven Jozić Stefanija Šestanović Mladen Šolić Jere Veža Živana Ninčević Gladan
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title_sort	analysis of the influence of seasonal water column dynamics on the relationship between marine viruses and microbial food web components using an artificial neural network
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title_auth	Analysis of the Influence of Seasonal Water Column Dynamics on the Relationship between Marine Viruses and Microbial Food Web Components Using an Artificial Neural Network
abstract	Artificial neural network analysis (ANN) is used to study the seasonal distribution of viruses and microbial food web (MFW) components in the open Adriatic Sea. The effect of viruses within the MFW is often overlooked, although viruses play an important role in microbial community dynamics. The results showed that the strongest influence is found in the nonlinear relationship between viruses and temperature. In addition, the algorithm showed that the number of viral populations in the P-limited open sea varies by season and according to the abundance of their main hosts, HB. A strong positive relationship between viruses and HB was found in more than 50% of the observed data. Moreover, this algorithm confirmed the association of the virus with the autotrophic part of the picoplankton and with heterotrophic nanoflagellates. The dynamics of the four resulting clusters, characterized by biological and environmental parameters, is described as a cyclic pattern in the water layer above the thermocline. Neural gas network analysis has been shown to be an excellent tool for describing changes in MFW components in the open Adriatic.
abstractGer	Artificial neural network analysis (ANN) is used to study the seasonal distribution of viruses and microbial food web (MFW) components in the open Adriatic Sea. The effect of viruses within the MFW is often overlooked, although viruses play an important role in microbial community dynamics. The results showed that the strongest influence is found in the nonlinear relationship between viruses and temperature. In addition, the algorithm showed that the number of viral populations in the P-limited open sea varies by season and according to the abundance of their main hosts, HB. A strong positive relationship between viruses and HB was found in more than 50% of the observed data. Moreover, this algorithm confirmed the association of the virus with the autotrophic part of the picoplankton and with heterotrophic nanoflagellates. The dynamics of the four resulting clusters, characterized by biological and environmental parameters, is described as a cyclic pattern in the water layer above the thermocline. Neural gas network analysis has been shown to be an excellent tool for describing changes in MFW components in the open Adriatic.
abstract_unstemmed	Artificial neural network analysis (ANN) is used to study the seasonal distribution of viruses and microbial food web (MFW) components in the open Adriatic Sea. The effect of viruses within the MFW is often overlooked, although viruses play an important role in microbial community dynamics. The results showed that the strongest influence is found in the nonlinear relationship between viruses and temperature. In addition, the algorithm showed that the number of viral populations in the P-limited open sea varies by season and according to the abundance of their main hosts, HB. A strong positive relationship between viruses and HB was found in more than 50% of the observed data. Moreover, this algorithm confirmed the association of the virus with the autotrophic part of the picoplankton and with heterotrophic nanoflagellates. The dynamics of the four resulting clusters, characterized by biological and environmental parameters, is described as a cyclic pattern in the water layer above the thermocline. Neural gas network analysis has been shown to be an excellent tool for describing changes in MFW components in the open Adriatic.
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container_issue	3, p 639
title_short	Analysis of the Influence of Seasonal Water Column Dynamics on the Relationship between Marine Viruses and Microbial Food Web Components Using an Artificial Neural Network
url	https://doi.org/10.3390/jmse11030639 https://doaj.org/article/aa2e90d3578d4011815e46665b7e4d8b https://www.mdpi.com/2077-1312/11/3/639 https://doaj.org/toc/2077-1312
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author2	Danijela Šantić Frano Matić Slaven Jozić Stefanija Šestanović Mladen Šolić Jere Veža Živana Ninčević Gladan
author2Str	Danijela Šantić Frano Matić Slaven Jozić Stefanija Šestanović Mladen Šolić Jere Veža Živana Ninčević Gladan
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up_date	2024-07-04T01:12:11.875Z
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Analysis of the Influence of Seasonal Water Column Dynamics on the Relationship between Marine Viruses and Microbial Food Web Components Using an Artificial Neural Network

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