Pregled bibliografske jedinice broj: 1215255
Investigating the Ability of Growth Models to Predict In Situ Vibrio spp. Abundances
Investigating the Ability of Growth Models to Predict In Situ Vibrio spp. Abundances // Microorganisms, 10 (2022), 9; 1765, 22 doi:10.3390/microorganisms10091765 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1215255 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Investigating the Ability of Growth Models to
Predict In Situ Vibrio spp. Abundances
Autori
Purgar, Marija ; Kapetanović, Damir ; Geček, Sunčana ; Marn, Nina ; Haberle, Ines ; Hackenberger Kutuzović, Branimir ; Gavrilović, Ana ; Pečar Ilić, Jadranka ; Hackenberger Kutuzović, Domagoj ; Đerđ, Tamara ; Ćaleta, Bruno ; Klanjscek, Tin
Izvornik
Microorganisms (2076-2607) 10
(2022), 9;
1765, 22
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
mechanistic modeling ; primary and secondary growth models overview ; comprehensive datasets ; bacterial growth
Sažetak
Vibrio spp. have an important role in biogeochemical cycles ; some species are disease agents for aquatic animals and/or humans. Predicting population dynamics of Vibrio spp. in natural environments is crucial to predicting how the future conditions will affect the dynamics of these bacteria. The majority of existing Vibrio spp. population growth models were developed in controlled environments, and their applicability to natural environments is unknown. We collected all available functional models from the literature, and distilled them into 28 variants using unified nomenclature. Next, we assessed their ability to predict Vibrio spp. abundance using two new and five already published longitudinal datasets on Vibrio abundance in four different habitat types. Results demonstrate that, while the models were able to predict Vibrio spp. abundance to an extent, the predictions were not reliable. Models often underperformed, especially in environments under significant anthropogenic influence such as aquaculture and urban coastal habitats. We discuss implications and limitations of our analysis, and suggest research priorities ; in particular, we advocate for measuring and modeling organic matter.
Izvorni jezik
Engleski
Znanstvena područja
Matematika, Biologija, Interdisciplinarne prirodne znanosti
POVEZANOST RADA
Projekti:
HRZZ-IP-2018-01-3150 - Prilagodba uzgoja bijele ribe klimatskim promjenama (AqADAPT) (Klanjšček, Tin, HRZZ - 2018-01) ( CroRIS)
Ustanove:
Institut "Ruđer Bošković", Zagreb,
Agronomski fakultet, Zagreb,
Sveučilište u Osijeku - Odjel za biologiju
Profili:
Marija Purgar
(autor)
Ines Haberle
(autor)
Nina Marn
(autor)
Ana Gavrilović
(autor)
Jadranka Pečar Ilić
(autor)
Domagoj Hackenberger
(autor)
Branimir Hackenberger Kutuzović
(autor)
Tin Klanjšček
(autor)
Sunčana Geček
(autor)
Damir Kapetanović
(autor)
Tamara Đerđ
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus