Bloom dynamics in a seasonally forced phytoplankton–zooplankton model: Trigger mechanisms and timing effects

Freund, Jan A.; Mieruch, Sebastian; Scholze, Bettina; Wiltshire, Karen Helen; Feudel, Ulrike

doi:10.1016/j.ecocom.2005.11.001

Cited by 61 publications

(39 citation statements)

References 29 publications

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“…The correct alignment is triggered by a cardinal date of the algal bloom which explains the notion of a bloom-triggered averaging. The method was devised (Freund et al 2006a) to reveal small causal components initiating the development of a phytoplankton bloom. As shown by Brüse et al (2011), the onset of a phytoplankton bloom is a better cardinal date than the easier to detect timing of the bloom peak.…”

Section: Bloom-triggered Averagingmentioning

confidence: 99%

Changes in the phytoplankton community at Helgoland, North Sea: lessons from single spot time series analyses

et al. 2012

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In recent regime shift analyses, the phytoplankton compartment of the marine food web was essentially represented by phytoplankton color or chlorophyll concentration. A detection of changes directly at the species level is highly desirable. The Helgoland Roads data series, a collection of high frequency long-term time series comprising biological and physico-chemical components of the southern North Sea, allow such an investigation at the level of single species. Aiming at a detection and characterization of habitat and community changes in the observation period (1962 until the end of 2008), we selected six species as representatives of certain classes, for example, benthic or neritic species, and applied a combination of novel analysis methods-a fitness-based analysis of the realized niche, a bloom-triggered averaging and a Markovian analysis of co-occurrence and succession patterns-to related abundance time series and concurrent environmental parameter time series. We found a general trend toward enlargement of niche size and shifts of the niche position, interesting salinity patterns around bloom events of two species, and statistically highly significant changes of a phytoplankton community segment after 1965 and after 1998. Interpreting our observations in ecological terms leads to the formulation of testable hypotheses.

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Section: Bloom-triggered Averagingmentioning

confidence: 99%

Changes in the phytoplankton community at Helgoland, North Sea: lessons from single spot time series analyses

et al. 2012

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“…This system models the logistic growth of the phytoplankton with an intrinsic rate r and Holling-type III grazing with maximum rate a 2 /b 2 as well as natural mortality of zooplankton with rate m. A small parameter δ reflects a high sensitivity and fast response of the phytoplankton population to environmental changes. Noise-induced phenomena for this stochastic system have been studied by Freund et al (2006) and Sieber et al (2007) using the method of direct numerical simulation of random trajectories. Freund et al (2006) analyzed a trigger mechanism of the noise-induced switching between the bloom and nonbloom modes for TB model under the periodic seasonal forcing.…”

Section: Analysis Of Noise-induced Excitement In Tb Plankton Systemmentioning

confidence: 99%

“…A constructive influence of noise has been observed in many excitable biophysical systems (Pikovsky and Kurths 1997;Lindner et al 2004;Freund et al 2006;Sieber et al 2007;Muratov and Vanden-Eijnden 2008;Li et al 2011). Usually, a noise-induced excitement is connected with the multistability of the corresponding deterministic model.…”

Section: Introductionmentioning

confidence: 99%

“…Noise-induced oscillations with the coherent resonance in this system have been investigated by Sieber et al (2007). Because of the excitability, a stochastic TB model under seasonal forcing behaves as a trigger with a switching between the bloom and nonbloom modes (Freund et al 2006). The phenomenon of the pattern formation ('patchy invasion') in a spatiotemporal TB model has been investigated by Morozov and Petrovskii (2009).…”

Section: Introductionmentioning

confidence: 99%

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Stochastic sensitivity analysis of noise-induced excitement in a prey–predator plankton system

Bashkirtseva

Ryashko

2011

Frontiers in Life Science

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In this paper, the excitable Truscott-Brindley dynamical model of the interacting populations under environmental noise is considered. We study a probabilistic mechanism of the noise-induced outbreaks in a zone of stable deterministic equilibria. The stochastic sensitivity functions technique and method of confidence ellipses are applied for the description of the spatial arrangement of random states near the deterministic attractor. The effectiveness of our method for the constructive analysis of the stochastic excitement in Truscott-Brindley model is demonstrated. A critical value for the intensity of noise-generating noise-induced outbreaks is estimated.

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“…A special focus will be on the appropriate extraction of the bloom start as this information is relevant for many subsequent analyses, e.g. the method of bloom triggered averaging (Freund et al, 2006a), and also important in the context of timing shifts and the afore-mentioned match/mismatch hypothesis.…”

Section: Introductionmentioning

confidence: 99%

A new method of describing phytoplankton blooms: Examples from Helgoland Roads

Mieruch¹,

Freund²,

Feudel³

et al. 2010

Journal of Marine Systems

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Phytoplankton blooms, in their pivotal position in pelagic seasonal succession require precise classification criteria in order to evaluate such parameters as bloom start, bloom timing, bloom maximum and growth rates. Such bloom parameters are linked directly to species and bloom specific features. Currently the phytoplankton bloom concept, though intuitively clear, lacks operational criteria allowing the precise definition of bloom parameters. We present a semi-quantitative method of classification of marine phytoplankton blooms based on an algorithmic estimation of several bloom descriptors computed from densely recorded phytoplankton data, like the Helgoland Roads long-term time series. Combining these descriptors we propose a novel classification scheme which may serve useful in the discussion of species fitness, competition and succession of marine algae. Special emphasis is put on the detection of the bloom start, because of its crucial importance for many current research topics, including trigger mechanisms and climate-induced temporal shifts in the context of the match/mismatch hypothesis. Visual examination of scatter plots of these parameters leads us to propose three types of blooming algae.

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Bloom dynamics in a seasonally forced phytoplankton–zooplankton model: Trigger mechanisms and timing effects

Cited by 61 publications

References 29 publications

Changes in the phytoplankton community at Helgoland, North Sea: lessons from single spot time series analyses

Changes in the phytoplankton community at Helgoland, North Sea: lessons from single spot time series analyses

Stochastic sensitivity analysis of noise-induced excitement in a prey–predator plankton system

A new method of describing phytoplankton blooms: Examples from Helgoland Roads

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