The European regional seas ecosystem model, a complex marine ecosystem model

Baretta, J. W.; Ebenhöh, W.; Ruardij, P.

doi:10.1016/0077-7579(95)90047-0

Cited by 491 publications

(274 citation statements)

References 22 publications

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“…The majority of published and applied multispecies models tend to concentrate around fishes or nutrients and in both cases, the history of model development can be 'characterised by the growing intricacy of their internal structure ' (Fransz et al 1991). There have been a number of attempts at producing trophic 'whole ecosystem' models for the marine environment, including the cove model of Patten et al (1975), the multispecies model of Andersen & Ursin (1977), the fjord model of Bax & Eliassen (1990), the ECOPATH with ECOSIM model (Christensen et al 2000); the European regional seas ecosytem (ERSEM I [Baretta et al 1995] and II [Baretta-Bekker & Baretta 1997] (Fulton 2001). Nevertheless, compared with the widespread use of water quality and fisheries multispecies models, the use of ecosystem models remains limited.…”

Section: Sourcementioning

confidence: 99%

“…Species-level detail could mean the complete collapse of many biogeochemical ecosystem models and, for many systems, is beyond what is possible based on empirical data. Nonetheless, without the flexibility inherent in a trophic web rather than a chain, realistic dynamics, especially under changing conditions, may be very difficult to capture (Baretta et al 1995, PahlWostl 1997. Thus, the systematic consideration of the effects of trophic complexity on model behaviour is an important concern.…”

Section: Trophic Complexitymentioning

confidence: 99%

“…However, this approach does not allow the model to adjust to spatial and temporal differences in nutrient availability (Baretta et al 1995). This inability should not present a significant problem and will not (in general) lead to large model divergences if the system state is mesotrophic to eutrophic.…”

Section: Trophic Complexitymentioning

confidence: 99%

“…Such a move would be computationally prohibitive and probably of little assistance. The box-model approach to transport processes is useful as it neglects small-scale gradients but still allows for regional differences and spatial self-structuring which, in turn, lead to the formation of distinct communities and ecological zones (Baretta et al 1995, Fulton 2001. Even when using box-models, large numbers of cells may not be necessary if they are defined such that they resolve hydrographic discontinuities, which have important ecological implications (Nihoul & Djenidi 1998).…”

Section: Physical Scopementioning

confidence: 99%

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Effect of complexity on marine ecosystem models

Fulton¹,

Smith²,

Johnson³

2003

Mar. Ecol. Prog. Ser.

284

174

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Ecosystem rather than species management has become an explicit part of policies that feature in international treaties and national legislation. Many of the tools that will be needed to fulfil the requirements of these policies are still in an early stage of development. One such tool is trophic ecosystem modelling. These models have been put forward to aid system-level understanding and provide insight into the potential impacts of human activities. Despite this, there are many gaps in knowledge of their strengths and weaknesses. In particular, little is known about the effect of the level of detail in a model on its performance. There has been some consideration of the effects of model formulation, as well as the effects of the physical, biological and chemical scope of multispecies and ecosystem models on their performance. A review of existing research indicates that there is a humped relationship between model detail and performance for these models, and that there are some guiding principles to consider during model development. This review gives some insight into which model structures and assumptions are likely to aid understanding and management, and which may be unnecessary. Further, it provides some understanding of whether some models can capture properties of real systems that other models cannot. The main recommendation is that the use of a single 'ultimate' ecosystem model is ill-advised, while the comparative and confirmatory use of multiple 'minimum-realistic' models is strongly recommended.

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Section: Sourcementioning

confidence: 99%

Section: Trophic Complexitymentioning

confidence: 99%

Section: Trophic Complexitymentioning

confidence: 99%

Section: Physical Scopementioning

confidence: 99%

See 2 more Smart Citations

Effect of complexity on marine ecosystem models

Fulton¹,

Smith²,

Johnson³

2003

Mar. Ecol. Prog. Ser.

284

174

View full text Add to dashboard Cite

show abstract

“…Thus, interpretation of biomass distribution by nutrient situation can be difficult when only a snapshot of the situation is available like it is the case on research cruises. This needs time series data where the development of both parameters can be tracked over a longer period, or modeling approaches (e.g., Baretta et al, 1995). Of course, also other parameters like light availability (Loebl et al, 2009), zooplankton grazing (e.g., Calbet and Landry, 2004), or degradation by viruses (Brussaard, 2004;Rhodes et al, 2008) influence phytoplankton biomass development and have to be taken into account.…”

Section: Biomass Distribution and Contribution Of Size Classesmentioning

confidence: 99%

Analysis of phytoplankton distribution and community structure in the German Bight with respect to the different size classes

Wollschläger

Wiltshire

Petersen

et al. 2015

Journal of Sea Research

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Investigation of phytoplankton biodiversity, ecology, and biogeography is crucial for understanding marine ecosystems. Research is often carried out on the basis of microscopic observations, but due to the limitations of this approach regarding detection and identification of picophytoplankton (0.2-2 μm) and nanophytoplankton (2-20 μm), these investigations are mainly focused on the microphytoplankton (20-200 μm). In the last decades, various methods based on optical and molecular biological approaches have evolved which enable a more rapid and convenient analysis of phytoplankton samples and a more detailed assessment of small phytoplankton. In this study, a selection of these methods (in situ fluorescence, flow cytometry, genetic fingerprinting, and DNA microarray) was placed in complement to light microscopy and HPLC-based pigment analysis to investigate both biomass distribution and community structure of phytoplankton. As far as possible, the size classes were analyzed separately. Investigations were carried out on six cruises in the German Bight in 2010 and 2011 to analyze both spatial and seasonal variability. Microphytoplankton was identified as the major contributor to biomass in all seasons, followed by the nanophytoplankton. Generally, biomass distribution was patchy, but the overall contribution of small phytoplankton was higher in offshore areas and also in areas exhibiting higher turbidity. Regarding temporal development of the community, differences between the small phytoplankton community and the microphytoplankton were found. The latter exhibited a seasonal pattern regarding number of taxa present, alphaand beta-diversity, and community structure, while for the nano-and especially the picophytoplankton, a general shift in the community between both years was observable without seasonality. Although the reason for this shift remains unclear, the results imply a different response of large and small phytoplankton to environmental influences.

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Exploring the Red Sea seasonal ecosystem functioning using a three-dimensional biophysical model

Triantafyllou

Yao

Petihakis

et al. 2014

J. Geophys. Res. Oceans

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The Red Sea exhibits complex hydrodynamic and biogeochemical dynamics, which vary both in time and space. These dynamics have been explored through the development and application of a 3-D ecosystem model. The simulation system comprises two off-line coupled submodels: the MIT General Circulation Model (MITgcm) and the European Regional Seas Ecosystem Model (ERSEM), both adapted for the Red Sea. The results from an annual simulation under climatological forcing are presented. Simulation results are in good agreement with satellite and in situ data illustrating the role of the physical processes in determining the evolution and variability of the Red Sea ecosystem. The model was able to reproduce the main features of the Red Sea ecosystem functioning, including the exchange with the Gulf of Aden, which is a major driving mechanism for the whole Red Sea ecosystem and the winter overturning taking place in the north. Some model limitations, mainly related to the dynamics of the extended reef system located in the southern part of the Red Sea, which is not currently represented in the model, still need to be addressed.

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The European regional seas ecosystem model, a complex marine ecosystem model

Cited by 491 publications

References 22 publications

Effect of complexity on marine ecosystem models

Effect of complexity on marine ecosystem models

Analysis of phytoplankton distribution and community structure in the German Bight with respect to the different size classes

Exploring the Red Sea seasonal ecosystem functioning using a three-dimensional biophysical model

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