Simulations and interpretations of cumulative trophic theory
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Simulations and interpretations of cumulative trophic theory

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  • Journal Title:
    Ecological Modelling
  • Personal Author:
  • NOAA Program & Office:
    NMFS (National Marine Fisheries Service)
  • Description:
    Examining marine ecosystems in a distinct way can produce new ecological, theoretical and applied insights. The common "S" and "hockey stick" -shaped curves, which result from examining the cumulative biomass and trophic level and the cumulative production and cumulative biomass curves of marine ecosystems, have strong potential to elucidate the mechanisms of marine food webs. These curves are based on the cumulative trophic theory, which can be summarized as the integration of biomass and production across trophic level that results from the relatively simple trophic transfer equation. Here we test the behavior of this theory via modeled simulations of the transfer equation under a variety of common mechanisms that can influence marine ecosystems. The simulated scenarios we present and evaluate here explore bottom-up driven changes (production, growth), internal dynamics (transfer efficiency) or top-down driven changes (mortality, selectivity), as well as multi-mechanism scenarios (overfishing and eutrophication) that are commonly experienced in marine ecosystems. We explore these scenarios at high, medium or low levels of change for each feature to ascertain how they can result in major changes to the realized trophodynamics of a marine ecosystem. Our results lend credence to the generality of the cumulative trophic theory by predicting the empirically observed "S" and "hockey stick" -shaped curves under a wide range of possible mechanisms. Given that common, repeatable and predictable dynamics is a key hallmark of increasingly robust theories, the application of cumulative trophic theory in managing marine ecosystems enables more repeatable and predictable responses across a wide range of conditions.
  • Keywords:
  • Source:
    Ecological Modelling, 463, 109800
  • DOI:
  • ISSN:
    0304-3800
  • Format:
    PDF
  • Publisher:
    Elsevier BV
  • Document Type:
    Journal Article
  • License:
  • Rights Information:
    CC BY-NC-ND
  • Compliance:
    Library
  • Main Document Checksum:
  • Download URL:
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