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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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/11/3/639 |
| _version_ | 1827749266629591040 |
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| author | Marin Ordulj Danijela Šantić Frano Matić Slaven Jozić Stefanija Šestanović Mladen Šolić Jere Veža Živana Ninčević Gladan |
| author_facet | Marin Ordulj Danijela Šantić Frano Matić Slaven Jozić Stefanija Šestanović Mladen Šolić Jere Veža Živana Ninčević Gladan |
| author_sort | Marin Ordulj |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T06:20:24Z |
| format | Article |
| id | doaj.art-aa2e90d3578d4011815e46665b7e4d8b |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-11T06:20:24Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-aa2e90d3578d4011815e46665b7e4d8b2023-11-17T11:58:24ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-03-0111363910.3390/jmse11030639Analysis of the Influence of Seasonal Water Column Dynamics on the Relationship between Marine Viruses and Microbial Food Web Components Using an Artificial Neural NetworkMarin Ordulj0Danijela Šantić1Frano Matić2Slaven Jozić3Stefanija Šestanović4Mladen Šolić5Jere Veža6Živana Ninčević Gladan7Department of Marine Studies, University of Split, Ruđera Boškovića 37, 21000 Split, CroatiaInstitute of Oceanography and Fisheries, Šetalište I. Meštrovića 63, 21000 Split, CroatiaDepartment of Marine Studies, University of Split, Ruđera Boškovića 37, 21000 Split, CroatiaInstitute of Oceanography and Fisheries, Šetalište I. Meštrovića 63, 21000 Split, CroatiaInstitute of Oceanography and Fisheries, Šetalište I. Meštrovića 63, 21000 Split, CroatiaInstitute of Oceanography and Fisheries, Šetalište I. Meštrovića 63, 21000 Split, CroatiaInstitute of Oceanography and Fisheries, Šetalište I. Meštrovića 63, 21000 Split, CroatiaInstitute of Oceanography and Fisheries, Šetalište I. Meštrovića 63, 21000 Split, CroatiaArtificial 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.https://www.mdpi.com/2077-1312/11/3/639virusesheterotrophic bacteriaautotrophic picoplanktonheterotrophic nanoflagellatesoligotrophic environmentP-limitation |
| spellingShingle | Marin Ordulj Danijela Šantić Frano Matić Slaven Jozić Stefanija Šestanović Mladen Šolić Jere Veža Živana Ninčević Gladan 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 Journal of Marine Science and Engineering viruses heterotrophic bacteria autotrophic picoplankton heterotrophic nanoflagellates oligotrophic environment P-limitation |
| 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 |
| 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| 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 |
| 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 |
| topic | viruses heterotrophic bacteria autotrophic picoplankton heterotrophic nanoflagellates oligotrophic environment P-limitation |
| url | https://www.mdpi.com/2077-1312/11/3/639 |
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