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| Titel |
Modeling dissolved oxygen dynamics and hypoxia |
| VerfasserIn |
M. A. Peña, S. Katsev, T. Oguz, D. Gilbert |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 7, no. 3 ; Nr. 7, no. 3 (2010-03-09), S.933-957 |
| Datensatznummer |
250004586
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| Publikation (Nr.) |
 copernicus.org/bg-7-933-2010.pdf |
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| Zusammenfassung |
| Hypoxia conditions are increasing throughout the world, influencing
biogeochemical cycles of elements and marine life. Hypoxia results from
complex interactions between physical and biogeochemical processes, which
can not be understood by observations alone. Models are invaluable tools at
studying system dynamics, generalizing discrete observations and predicting
future states. They are also useful as management tools for evaluating
site-specific responses to management scenarios. Here we review oxygen
dynamics models that have significantly contributed to a better
understanding of the effects of natural processes and human perturbations on
the development of hypoxia, factors controlling the extent and temporal
variability of coastal hypoxia, and the effects of oxygen depletion on
biogeochemical cycles. Because hypoxia occurs in a variety of environments
and can be persistent, periodic or episodic, models differ significantly in
their complexity and temporal and spatial resolution. We discuss the
progress in developing hypoxia models for benthic and pelagic systems that
range from simple box models to three dimensional circulation models.
Applications of these models in five major hypoxia regions are presented. In
the last decades, substantial progress has been made towards the
parameterization of biogeochemical processes in both hypoxic water columns
and sediments. In coastal regions, semi-empirical models have been used more
frequently than mechanistic models to study nutrient enrichment and hypoxia
relationships. Recent advances in three-dimensional coupled
physical-ecological-biogeochemical models have allowed a better
representation of physical-biological interactions in these systems. We
discuss the remaining gaps in process descriptions and suggest directions
for improvement. Better process representations in models will help us
answer several important questions, such as those about the causes of the
observed worldwide increase in hypoxic conditions, and future changes in the
intensity and spread of coastal hypoxia. At the same time, quantitative
model intercomparison studies suggest that the predictive ability of our
models may be adversely affected by their increasing complexity, unless the
models are properly constrained by observations. |
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