Metacommunity modelling, a fundamental approach for marine biodiversity studies


1 - Comprehensive understanding of biological diversity patterns requires quantifying spatial dynamic processes. Mathematical modelling offers an array of techniques to investigate ecosystem processes that cannot be observed directly or tested experimentally.2 - In the 1990’s, a new paradigm for biodiversity studies appeared - called metacommunities - combining ecological and biogeographical concepts of species assemblages. A metacommunity is defined as a set of local communities linked by the exchanges of individuals at the regional scale. This relatively simple definition led to the development of theoretical frameworks (e.g. emphasizing neutrality, patch dynamics, species sorting and mass effects) that generated some controversy about the relative importance of the local ecological niche-based processes and regional dispersal processes. Recent studies have demonstrated that several of these proposed theories can lead to similar results when simulating the dynamics of metacommunity systems.3 - Thus, it does not seem possible to adequately prove whether or not local processes predominate over regional ones from available datasets, even if several evaluation criteria are combined. This is why metacommunity modelling is an important step toward quantifying changes in marine biodiversity. Models can be improved by unifying population dynamics processes and by establishing accurate typologies of parameter estimates. Validation should be performed by carrying out ad hoc experiments, testing dynamic properties; however, the design and implementation of these experiments remain difficult because of the lack of large-scale experimental facilities under controlled conditions.4 - Metacommunity modelling seems however to be promising for a broad range of applications in the domain of conservation of marine biodiversity, and particularly in that it can provide objective criteria to define Marine Protected Areas as a function of regional biodiversity conservation goals.

DOI Code: 10.1285/i1825229Xv6n2p4

Keywords: marine biodiversity; metacommunity; mathematical modelling; conservation

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