Purgar Marija, Kapetanović Damir, Geček Sunčana, Marn Nina, Haberle Ines, Hackenberger Branimir K, Gavrilović Ana, Pečar Ilić Jadranka, Hackenberger Domagoj K, Djerdj Tamara, Ćaleta Bruno, Klanjscek Tin
Ruđer Bošković Institute, 10000 Zagreb, Croatia.
School of Biological Sciences, The University of Western Australia, Crawley, WA 6009, Australia.
Microorganisms. 2022 Aug 31;10(9):1765. doi: 10.3390/microorganisms10091765.
spp. have an important role in biogeochemical cycles; some species are disease agents for aquatic animals and/or humans. Predicting population dynamics of spp. in natural environments is crucial to predicting how the future conditions will affect the dynamics of these bacteria. The majority of existing 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 spp. abundance using two new and five already published longitudinal datasets on abundance in four different habitat types. Results demonstrate that, while the models were able to predict 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.
某些物种在生物地球化学循环中发挥着重要作用；一些物种是水生动物和/或人类的病原体。预测自然环境中某些物种的种群动态对于预测未来环境条件将如何影响这些细菌的动态至关重要。大多数现有的某些物种种群增长模型是在受控环境中开发的，其在自然环境中的适用性尚不清楚。我们从文献中收集了所有可用的功能模型，并使用统一的命名法将它们提炼成28个变体。接下来，我们使用关于四种不同栖息地类型中某些物种丰度的两个新的和五个已发表的纵向数据集，评估了它们预测某些物种丰度的能力。结果表明，虽然这些模型在一定程度上能够预测某些物种的丰度，但预测并不可靠。模型往往表现不佳，尤其是在受到重大人为影响的环境中，如水产养殖和城市沿海栖息地。我们讨论了分析的意义和局限性，并提出了研究重点；特别是，我们主张对有机物质进行测量和建模。
