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A seasonal analysis of the southern North Sea ecosystem
Hannon, B.; Joiris, C. (1989). A seasonal analysis of the southern North Sea ecosystem. Ecology 70(6): 1916-1934
In: Ecology. Ecological Society of America: Brooklyn, NY. ISSN 0012-9658; e-ISSN 1939-9170, meer
Peer reviewed article  

Beschikbaar in  Auteurs 

Trefwoorden
    Cycles > Chemical cycles > Geochemical cycle > Biogeochemical cycle > Nutrient cycles > Carbon cycle
    Ecosystems
    Energy
    Modelling
    ANE, Noordzee [Marine Regions]
    Marien/Kust

Auteurs  Top 
  • Hannon, B.
  • Joiris, C., meer

Abstract
    We developed an input-output model of the Southern North Sea ecosystem in order to determine the relationships between 10 biotic and abiotic stock levels and to investigate how their direct and indirect dependency changed through the typical year. Ecologists now examine stomach contents of top carnivores, for example, to evaluate theirdirect connection to the food source. Our method allows ecologists to extend their understanding of connection in an ecosystem. The method captures not only the food source connection but also those species that contribute to the food source, those at the next level that contribute to those sources, and so on, until all the exchanges have been assigned without ambiguity. The method even captures the indirect connection that a species may have to itself. A small change in the activity level of any species in an ecosystem affects all the rest; we can show the effect of that change on each species in the system. We followed the fate of absorbed solar energy to trace the connections between the elements of this ecosystem, although any external input (e.g., phosphorus, nitrogen) could have been used, depending on the objectives of the analysis. We traced only physical exchanges in the sample ecosystem, but measurable nonphysical exchanges, such as pollinator time in a terrestrial ecosystem, could be included. A sensitivity analysis showed which of the direct and indirect interconnecting flows is most affected by the rate of fish removal. We also used the model to show where specific management intervention (e.g., "fertilization") would be the most efficient in allowing stable system responses to fishing rate increases.

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