Abstract: Ecological systems are exposed and are influenced by
various natural and anthropogenic disturbances. They produce
various effects and states seeking response symmetry to a state of
global phase coherence or stability and balance of their food webs.
This research project addresses the development of a computational
methodology for modeling plankton food webs. The use of
algorithms to establish connections, the generation of representative
fuzzy multigraphs and application of technical analysis of complex
networks provide a set of tools for defining, analyzing and evaluating
community structure of coastal aquatic ecosystems, beyond the
estimate of possible external impacts to the networks. Thus, this
study aims to develop computational systems and data models to
assess how these ecological networks are structurally and
functionally organized, to analyze the types and degree of
compartmentalization and synchronization between oscillatory and
interconnected elements network and the influence of disturbances on
the overall pattern of rhythmicity of the system.
Abstract: The objective of this work is to explicit knowledge on the interactions between the chlorophyll-a and nine meroplankton larvae of epibenthonic fauna. The studied case is the Arraial do Cabo upwelling system, Southeastern of Brazil, which provides different environmental conditions. To assess this information a network approach based in probability estimative was used. Comparisons among the generated graphs are made in the light of different water masses, application of Shannon biodiversity index, and the closeness and betweenness centralities measurements. Our results show the main pattern among different water masses and how the core organisms belonging to the network skeleton are correlated to the main environmental variable. We conclude that the approach of complex networks is a promising tool for environmental diagnostic.