Small-scale nutrient patches in tidally mixed coastal waters

Seuront, Laurent; Gentilhomme, Valérie; Lagadeuc, Yvan

doi:10.3354/meps232029

Cited by 52 publications

(48 citation statements)

References 60 publications

(56 reference statements)

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“…For example, temporal variability in temperature, nitrite, and fluorescence has been documented at scales of seconds to hours in coastal waters (15,16,19). These studies found that parameter variability, or "patchiness", is not confined to a set of frequencies, nor did they find that the variability is random (i.e., white noise).…”

Section: Introductionmentioning

confidence: 99%

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Enterococci Concentrations in Diverse Coastal Environments Exhibit Extreme Variability

Boehm

2007

Environ. Sci. Technol.

112

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Fecal indicator bacteria (FIB) concentrations in a single grab sample of water are used to notify the public about the safety of swimming in coastal waters. If concentrations are over a single-sample standard, waters are closed or placed under an advisory. Previous work has shown that notification errors occur often because FIB vary more quickly than monitoring results can be obtained (typically 24 h). Rapid detection technologies (such as quantitative polymerase chain reaction) that allow FIB quantification in hours have been suggested as a solution to notification errors. In the present study, I explore variability of enterococci (ENT) over time scales less than a day that might affect interpretation of FIB concentrations from a single grab sample, even if obtained rapidly. Five new data sets of ENT collected at 10 and 1 min periodicities for 24 and 1 h, respectively, are presented. Data sets are collected in diverse marine environments from a turbulent surf zone to a quiescent bay. ENT vary with solar and tidal cycles, as has been observed in previous studies. Over short time scales, ENT are extremely variable in each environment even the quiescent bay. Changes in ENT concentrations between consecutive samples (1 or 10 min apart) greater than the single-sample standard (104 most probable number per 100 mL) are not unusual. Variability, defined as the change in concentration between consecutive samples, is not distinct between environments. ENT change by 60% on average between consecutive samples, and by as much as 700%. Spectral analyses reveal no spectral peaks, but power-law decline of spectral density with frequency. Power-law exponents are close to 1 suggesting ENT time series share properties with 1/f noise and are fractal in nature. Since fractal time series have no characteristic time scale associated with them, it is not obvious how the fractal nature of ENT can be exploited for adaptive sampling or management. Policy makers, as well as scientists designing field campaigns for microbial source tracking and epidemiology studies, are cautioned that a single sample of water reveals little about the true water quality at a beach. Multiple samples must be taken to gain a snapshot into the patchy structure of microbial water quality and associated human health risk.

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Section: Introductionmentioning

confidence: 99%

“…Fractal time series are identified from a power-law decay in spectral density (E) with frequency (f) (16 (16). D and are useful for describing how energy in a time series varies from one time scale to the next.…”

Section: Introductionmentioning

confidence: 99%

Enterococci Concentrations in Diverse Coastal Environments Exhibit Extreme Variability

Boehm

2007

Environ. Sci. Technol.

112

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“…of plankton distributions [3][4][5][6][7][10][11][12]. Instead, turbulence intermittency has recurrently been considered as irrelevant to marine life.…”

Section: Intermittency In Marine Sciencesmentioning

confidence: 99%

“…This intermittency may correspond to a basic property of aquatic ecosystems, as sharp, local fluctuations are ubiquitously observed in space-time distributions of turbulent dissipation rates, temperature, salinity, nutrient and plankton concentration [3][4][5][6][7][10][11][12] and the motion behaviour of both benthic and pelagic organisms [13][14][15]. Practically, the occurrence of high density peaks positively skews a given probability distribution, causing it to deviate from Gaussianity (in which case the skewness is nil, and the probability distribution symmetric).…”

Section: Introductionmentioning

confidence: 99%

“…Numerous experimental data analyses done in different frameworks and geographical regions have shown that physical and biological patterns and processes in marine sciences display high intermittency [1][2][3][4][5][6][7][8][9][10][11]. This intermittency may correspond to a basic property of aquatic ecosystems, as sharp, local fluctuations are ubiquitously observed in space-time distributions of turbulent dissipation rates, temperature, salinity, nutrient and plankton concentration [3][4][5][6][7][10][11][12] and the motion behaviour of both benthic and pelagic organisms [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

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Microscale Complexity in the Ocean: Turbulence, Intermittency and Plankton Life

Seuront

2008

Math. Model. Nat. Phenom.

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Abstract. This contribution reviews the nonlinear stochastic properties of turbulent velocity and passive scalar intermittent fluctuations in Eulerian and Lagrangian turbulence. These properties are illustrated with original data sets of (i) velocity fluctuations collected in the field and in the laboratory, and (ii) temperature, salinity and in vivo fluorescence (a proxy of phytoplankton biomass, i.e. unicelled vegetals passively advected by turbulence) sampled from highly turbulent coastal waters. The strength of three of the most popular models describing intermittent fluctuations (the lognormal, log-Lévy and log-Poisson models) to fit the distribution of in vivo fluorescence has subsequently been critically assessed. A theoretical formulation for the stochastic properties of biologically active scalars is also provided and validated. Finally, the potential effect of the intermittent properties of turbulent velocity fluctuations on processes relevant to the life of plankton organisms are theoretically investigated. It is shown that the intermittent nature of microscale turbulence may result in (i) a decrease in the rate of nutrient fluxes towards non-motile phytoplankton cells (6-62 %), (ii) a decrease in the physical coagulation of phytoplankton cells (25-48 %) and in the subsequent phytoplankton aggregate volumes (22-41 %), and (iii) a decrease of the turbulence contribution to predator-prey encounter rates (25-50 %).

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