Phytoplankton motility and the competition for nutrients in the thermocline

Ross, Oliver N.; Sharples, Jonathan

doi:10.3354/meps06999

Cited by 62 publications

(54 citation statements)

References 56 publications

(76 reference statements)

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“…Sharples et al 2001) and modelling results (e.g. Ross & Sharples 2007) of a turbulent SML, which fulfils all necessary requirements for use with the random walk in terms of differentiability, steadiness, and reflecting boundary conditions (cf. Ross & Sharples 2004).…”

Section: Methodsmentioning

confidence: 99%

“…4) rather than obtaining the values from a k-ε model that calculates the diffusivity dynamically from the external forcing and ambient water column stability (e.g. Ross & Sharples 2007). As a result, our diffusivity profiles are fairly constant throughout the SML (Fig.…”

Section: Turbulence Parameterisationmentioning

confidence: 99%

“…3c of Ross & Sharples 2007), and (2) a scenario where the intermittency was largely due to changes in the surface wind forcing and where the diffusivity varied randomly between K m and 1% of K m . In both cases the impact on the errors was minimal and did not warrant the inclusion of such effects in our analysis.…”

Section: Turbulence Parameterisationmentioning

confidence: 99%

“…The model consists of 2 components: (1) a Lagrangian turbulence module, which provides the individual particle tracks and associated light histories in response to turbulence mixing, and (2) a biological module, which calculates the growth rates based on the individual light histories, taking into account photoacclimation and photoinhibition. The Lagrangian technique (Woods & Onken 1982, Wolf & Woods 1988, Lizon et al 1998, Broekhuizen 1999, Ross & Sharples 2007) seems a natural choice to approach this problem, as its Eulerian counterpart cannot provide the necessary information on the individual light histories. We simulate shallow and deep, turbid and clear, turbulent and quiescent water columns in order to quantify the differences between the growth rates for a range of natural environments.…”

Section: Introductionmentioning

confidence: 99%

“…Particularly in coastal areas or estuaries, where strong turbulent mixing in combination with high light attenuation coefficients may subject the cells to large and rapid changes in light intensity (e.g. Lizon et al 1998, Sharples et al 2001, Moore et al 2006, Ross & Sharples 2007, or during deep mixing events in the open ocean in winter and spring (e.g. Fig.…”

Section: Introductionmentioning

confidence: 99%

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Modelling the effect of vertical mixing on bottle incubations for determining in situ phytoplankton dynamics. I. Growth rates

Ross¹,

Geider²,

Berdalet³

et al. 2011

Mar. Ecol. Prog. Ser.

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Reliable estimates of in situ phytoplankton growth rates are central to understanding the dynamics of aquatic ecosystems. A common approach for estimating in situ growth rates is to incubate natural phytoplankton assemblages in clear bottles at fixed depths or irradiance levels and measure the change in chlorophyll a (Chl) over the incubation period (typically 24 h). Using a modelling approach, we investigate the accuracy of these Chl-based methods focussing on 2 aspects: (1) in a freely mixing surface layer, the cells are typically not in balanced growth, and with photoacclimation, changes in Chl may yield different growth rates than changes in carbon; and (2) the in vitro methods neglect any vertical movement due to turbulence and its effect on the cells' light history. The growth rates thus strongly depend on the incubation depth and are not necessarily representative of the depth-integrated in situ growth rate in the freely mixing surface layer. We employ an individual based turbulence and photosynthesis model, which also accounts for photoacclimation and photoinhibition, to show that the in vitro Chl-based growth rate can differ both from its carbon-based in vitro equivalent and from the in situ value by up to 100%, depending on turbulence intensity, optical depth of the mixing layer, and incubation depth within the layer. We make recommendations for choosing the best depth for single-depth incubations. Furthermore we demonstrate that, if incubation bottles are being oscillated up and down through the water column, these systematic errors can be significantly reduced. In the present study, we focus on Chl-based methods only, while productivity measurements using carbon-based techniques (e.g. 14 C) are discussed in Ross et al. (2011; Mar Ecol Prog Ser 435:33-45).

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Section: Methodsmentioning

confidence: 99%

Section: Turbulence Parameterisationmentioning

confidence: 99%

Section: Turbulence Parameterisationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Modelling the effect of vertical mixing on bottle incubations for determining in situ phytoplankton dynamics. I. Growth rates

Ross¹,

Geider²,

Berdalet³

et al. 2011

Mar. Ecol. Prog. Ser.

Self Cite

View full text Add to dashboard Cite

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Turbulence and Mixing in a Shallow Shelf Sea From Underwater Gliders

2017

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The seasonal thermocline in shallow shelf seas acts as a natural barrier for boundary‐generated turbulence, damping scalar transport to the upper regions of the water column and controlling primary production to a certain extent. To better understand turbulence and mixing conditions within the thermocline, two unique 12 and 17 day data sets with continuous measurements of the dissipation rate of turbulent kinetic energy (ɛ) collected by autonomous underwater gliders under stratified to well‐mixed conditions are presented. A highly intermittent ɛ signal was observed in the stratified thermocline region, which was mainly characterized by quiescent flow (turbulent activity index below 7). The rate of diapycnal mixing remained relatively constant for the majority of the time with peaks of higher fluxes that were responsible for much of the increase in bottom mixed layer temperature. The water column stayed predominantly strongly stratified, with a bulk Richardson number across the thermocline well above 2. A positive relationship between the intensity of turbulence, shear, and stratification was found. The trend between turbulence levels and the bulk Richardson number was relatively weak but suggests that ɛ increases as the bulk Richardson number approaches 1. The results also highlight the interpretation difficulties in both quantifying turbulent thermocline fluxes as well as the responsible mechanisms.

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Biodiversity of Phytoplankton: Responses to Environmental Changes in Coastal Zones

Monaco¹,

Prouzet²

2015

Marine Ecosystems

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Phytoplankton motility and the competition for nutrients in the thermocline

Cited by 62 publications

References 56 publications

Modelling the effect of vertical mixing on bottle incubations for determining in situ phytoplankton dynamics. I. Growth rates

Modelling the effect of vertical mixing on bottle incubations for determining in situ phytoplankton dynamics. I. Growth rates

Turbulence and Mixing in a Shallow Shelf Sea From Underwater Gliders

Biodiversity of Phytoplankton: Responses to Environmental Changes in Coastal Zones

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