Qualitative modelling of functional relationships in marine benthic communities

Nikolaos Alexandridis, Jeffrey M. Dambacher, Fred Jean, Nicolas Desroy, Cédric Bacher

Research output: Contribution to journalArticlepeer-review


In order to better understand and predict the dynamics of benthic macroinvertebrate communities, we need to first define the functional components of benthic biodiversity and then provide a mechanistic description of how they interact with their abiotic environment, their basic resources and each other. These interactions should be largely controlled by readily available biological traits, making trait-based modelling an ideal framework for the synthesis of relevant hypotheses from ecological theory and expert knowledge. With the help of benthic species traits, we derived a set of first principles regarding the role of organisms in processes of environmental filtering, consumption of algae/detritus, predation, use of space, biogenic habitat modification and trade-offs in the utilization and allocation of resources. These principles were incorporated into qualitative models in the form of functional relationships linking groups of benthic organisms in the Rance estuary (Brittany, France). The general stability of these models illustrates their potential to persist in time and to constitute a plausible representation of the natural world. Their structure provides insight into the role of various community assembly mechanisms and the direction that the system might take in response to perturbations. The results are expected to inform the development of quantitative models reproducing the spatial and temporal dynamics of marine benthic biodiversity in the Rance estuary.

Original languageEnglish
Pages (from-to)300-312
Number of pages13
JournalEcological Modelling
Publication statusPublished - 2017 Sept 24
Externally publishedYes

Subject classification (UKÄ)

  • Ecology

Free keywords

  • Benthic macroinvertebrates
  • Biological traits
  • Biotic interactions
  • Community assembly
  • Functional groups
  • Qualitative modelling


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