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PhD ceremony Mr. Q. Liu: The emergent properties of spatial self-organization: a study of patterned mussel beds

When:Fr 15-11-2013 at 14:30
Where:Academiegebouw, Broerstraat 5, Groningen

PhD ceremony: Mr. Q. Liu

Dissertation: The emergent properties of spatial self-organization: a study of patterned mussel beds

Promotor(s): prof. J. van de Koppel, prof. P.M.J. Herman, prof. H. Olff

Faculty: Mathematics and Natural Sciences

Quan-Xing Liu examined what the dominant processes are that explain self-organized pattern formation in mussel beds. Moreover, he studied how these processes affect ecosystem functioning, in term of productivity, resilience, and whether the patterns can be used as indicator for imminent collapse of mussel beds. Although these studies are based on a specific ecosystem - mussel beds - the conclusions have abroad implication that, in principles, should apply to different ecosystems.

Firstly, Liu proposed an alternative mechanism - sediment accumulation feedback - to explain the large-scale mussel beds formation, where he compares the predictions of ecosystem functioning with early decreased losses feedback. His results indicate that the predictions of the implications and emergent properties of spatial self-organization strikingly depend on the granted mechanisms.

Next, Liu proposed a phase separation principle to explain the self-organization pattern in mussel beds at a small-scale level. Using laboratory experiments, he demonstrated that this principle corresponds to the well-known Cahn-Hilliard equation for phase separation in physics. Liu proposed a model integrated the interplay of ecological processes and behavioral processes to understanding the complex mussel beds that reveal two spatial-scale levels interaction and patterns. His model demonstrates that complex self-organization patterns have less vulnerability and larger resilience. Finally, Liu studied the effect of spatial heterogeneity, resulting from large-scale effects of mussels on their environment, on ecosystem functioning. His results suggest that realistic environmental settings are an important aspect when assessing the emergent properties of self-organization ecosystems.

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