Size-specific growth and grazing rates for picophytoplankton in coastal and oceanic regions of the eastern Pacific

Taniguchi, Daa; Landry,; Franks, P. J. S.; Selph, Karen E.

doi:10.3354/meps10895

Cited by 17 publications

(16 citation statements)

References 86 publications

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“…The average growth rate of Synechococcus is nearly 60% higher than that of Prochlorococcus for the data examined here (pairwise Wilcox test, p < 0.03) (Figure 2). This difference has been frequently observed in previous studies comparing rates sample by sample in a single oceanic region (Guo et al 2014, Liu et al 1995, Taniguchi et al 2014. Also, the maximum growth rate of isolated strains of Synechococcus is greater than that of Prochlorococcus strains (Biller et al 2015, Moore et al 1995.…”

Section: Growth Rates Of Cyanobacteria: Relationship With Cell Sizesupporting

confidence: 57%

“…Even when the rate-size relationship is statistically significant, growth rates for a single cell size vary greatly, by more than tenfold. A recent Landry-Hassett study in the North Pacific did not see any size effects on rates for cells between 0.45 and 4.0 μm (Taniguchi et al 2014). In short, size is important, but it is hardly the only property of cells connected to growth rates.…”

Section: Growth Rates Of Cyanobacteria: Relationship With Cell Sizementioning

confidence: 84%

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Growth Rates of Microbes in the Oceans

Kirchman

2016

Annu. Rev. Mar. Sci.

216

203

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A microbe's growth rate helps to set its ecological success and its contribution to food web dynamics and biogeochemical processes. Growth rates at the community level are constrained by biomass and trophic interactions among bacteria, phytoplankton, and their grazers. Phytoplankton growth rates are approximately 1 d(-1), whereas most heterotrophic bacteria grow slowly, close to 0.1 d(-1); only a few taxa can grow ten times as fast. Data from 16S rRNA and other approaches are used to speculate about the growth rate and the life history strategy of SAR11, the most abundant clade of heterotrophic bacteria in the oceans. These strategies are also explored using genomic data. Although the methods and data are imperfect, the available data can be used to set limits on growth rates and thus on the timescale for changes in the composition and structure of microbial communities.

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Section: Growth Rates Of Cyanobacteria: Relationship With Cell Sizesupporting

confidence: 57%

Section: Growth Rates Of Cyanobacteria: Relationship With Cell Sizementioning

confidence: 84%

Growth Rates of Microbes in the Oceans

Kirchman

2016

Annu. Rev. Mar. Sci.

216

203

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“…S2). Here the smallest grazers do not have a clear dif-ference in grazing related to size (following the data compilation of Taniguchi et al, 2014). Mixotrophic dinoflagellates also graze on plankton with the same predator-prey ratios as the zooplankton and have size-dependent maximum grazing rates.…”

Section: Numerical Modelmentioning

confidence: 62%

Dimensions of marine phytoplankton diversity

et al. 2020

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Abstract. Biodiversity of phytoplankton is important for ecosystem stability and marine biogeochemistry. However, the large-scale patterns of diversity are not well understood and are often poorly characterized in terms of statistical relationships with factors such as latitude, temperature and productivity. Here we use ecological theory and a global trait-based ecosystem model to provide mechanistic understanding of patterns of phytoplankton diversity. Our study suggests that phytoplankton diversity across three dimensions of trait space (size, biogeochemical function and thermal tolerance) is controlled by disparate combinations of drivers: the supply rate of the limiting resource, the imbalance in different resource supplies relative to competing phytoplankton demands, size-selective grazing and transport by the moving ocean. Using sensitivity studies we show that each dimension of diversity is controlled by different drivers. Models including only one (or two) of the trait dimensions will have different patterns of diversity than one which incorporates another trait dimension. We use the results of our model exploration to infer the controls on the diversity patterns derived from field observations along meridional transects in the Atlantic and to explain why different taxa and size classes have differing patterns.

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“…Field measurements show that there may be an opposite size related trend in maximum growth rates for picophytoplankton in oligotrophic ocean regions with picoprokaryotes having higher growth rates than picoeukaryotes (Taniguchi et al ; Zubkov ). We show that even though the affinity to light is higher for picoprokaryotes, growth rates (Fig.…”

Section: Discussionmentioning

confidence: 99%

The physiological response of seven strains of picophytoplankton to light, and its representation in a dynamic photosynthesis model

Stawiarski

Buitenhuis

Fallens

2017

Limnology & Oceanography

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Picophytoplankton dominate the phytoplankton community in wide ocean areas and are considered efficient in the acquisition of light compared to other phytoplankton groups. To quantify their photophysiological parameters we use three strains of picoprokaryotes and four strains of picoeukaryotes. We measure the acclimated response of the exponential growth rates and chlorophyll a (Chl a) to carbon ratios, as well as the instantaneous response of photosynthesis rates at 5-7 light intensities. We then use a dynamic photosynthesis model (Geider et al. 1997) and extend it with a photoinhibition term. We derive five photophysiological parameters: the maximum rate of photosynthesis (P C m ), the affinity to light (a chl ), the photoinhibition term (b chl ), the respiration rate (resp), and the maximum Chl a to carbon ratio (h max ). We show that P C m is significantly lower for picoprokaryotes than for picoeukaryotes and increases significantly with increasing cell size. In turn, a chl decreases significantly with increasing maximum growth rate (l max ). The latter finding is contrary to a previously reported relationship for phytoplankton, but agrees with theoretical assumptions based on size. The higher efficiency in light acquisition gives picoprokaryotes an advantage in light limited environments at the expense of their maximum growth rate. In addition, our results indicate that the accumulation of long-term damage through photoinhibition during acclimation is not well represented by the dynamic photosynthesis model. Hence, we would recommend to distinguish between the effects of irreversible damage (on a time scale of days) on growth rates and of reversible damage (on a time scale of minutes) on photosynthesis rates.

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Size-specific growth and grazing rates for picophytoplankton in coastal and oceanic regions of the eastern Pacific

Cited by 17 publications

References 86 publications

Growth Rates of Microbes in the Oceans

Growth Rates of Microbes in the Oceans

Dimensions of marine phytoplankton diversity

The physiological response of seven strains of picophytoplankton to light, and its representation in a dynamic photosynthesis model

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