Effects of nutrient and inorganic carbon on single cell formation of &lt;i&gt;Pediastrum duplex&lt;/i&gt;

Cho, Jae-Hyung; Noh, Kyung-Ho; Park, Kyu Hyun; Jang, Jung-Seok; Nam, Gui-Sook; Hwang, Sun‐Jin

doi:10.11001/jksww.2018.32.2.153

Cited by 1 publication

(1 citation statement)

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“…The six species studied by Lewington‐Pearce et al (2019) belonged to three groups: cyanobacteria ( Microcystis and Synechococcus ), diatoms ( Cyclotella ), and chlorophytes ( Pediastrum , Raphidocelis , and Scenedesmus ). Accordingly, we searched for available papers on the temperature‐ and phosphorus‐dependent growth of six species either identical to those used in the case of nitrogen or belonging to the same genus (Mastala et al 1996; Amano et al 2010; Takeya et al 2012; Thomas and Litchman 2016; Bestion et al 2018; Cho et al 2018), and used those data for parameter estimation. Model parameterization was performed with a maximum likelihood estimation method using the R package bbmle (Bolker and R Development Core Team 2021).…”

Section: Methodsmentioning

confidence: 99%

Combined effect of warming, nutrients, and species pool size on the seasonal variability of phytoplankton composition: A modeling perspective

Pálffy,

Smeti

2024

Limnology & Oceanography

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The anticipated long‐term rise in temperature can have numerous effects on freshwater phytoplankton, however, there is a great deal of uncertainty about how biogeochemical processes modify community functioning under a warming climate. Previous works regarding a large shallow lake and a mesocosm study showed a positive relationship between the temporal variability of phytoplankton composition and mean temperature, which might be a sign of warming‐stimulated instability in ecosystem processes. To elucidate whether these observations are part of a more general phenomenon, we combined a numerical model describing the dependence of algal growth on temperature and nutrient concentration with a multispecies, multi‐nutrient model. We ran simulations representative of changes in phytoplankton communities with randomized initial species composition under different temperature scenarios (current annual temperature pattern increased with 1°C, 2°C, or 3°C), various levels of nitrogen and phosphorus supply and different degrees of temporal variability in those supplies. The model outputs showed that seasonal variability in composition can be enhanced by warming through the mechanistic links between nutrient availability, temperature, and species‐specific growth rates, but the rate of increase is also dependent on nutrient ratios and the size of the species pool. Moreover, temporal variability in nutrient loads also enhanced compositional variability, but the rate of increase also depended on the level of nutrient supply. The results of our study hint that the impact of climate change and eutrophication on phytoplankton dynamics can be more intricate than spatiotemporally limited field or experimental observations would suggest.

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