A biogeographic network reveals evolutionary links between deep-sea hydrothermal vent and methane seep faunas

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Abstract

Deep-sea hydrothermal vents and methane seeps are inhabited by members of the same higher taxa but share few species, thus scientists have long sought habitats or regions of intermediate character that would facilitate connectivity among these habitats. Here, a network analysis of 79 vent, seep, and whale-fall communities with 121 genus-level taxa identified sedimented vents as a main intermediate link between the two types of ecosystems. Sedimented vents share hot, metal-rich fluids with mid-ocean ridge-type vents and soft sediment with seeps. Such sites are common along the active continental margins of the Pacific Ocean, facilitating connectivity among vent/seep faunas in this region. By contrast, sedimented vents are rare in the Atlantic Ocean, offering an explanation for the greater distinction between its vent and seep faunas compared with those of the Pacific Ocean. The distribution of subduction zones and associated back-arc basins, where sedimented vents are common, likely plays a major role in the evolutionary and biogeographic connectivity of vent and seep faunas. The hypothesis that decaying whale carcasses are dispersal stepping stones linking these environments is not supported.

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Functional cartography of complex metabolic networks

, (2005)

High-throughput techniques are leading to an explosive growth in the size of biological databases and creating the opportunity to revolutionize our understanding of life and disease. Interpretation of these data remains, however, a major scientific challenge. Here, we propose a methodology that enables us to extract and display information contained in complex networks. Specifically, we demonstrate that one can (i) find functional modules in complex networks, and (ii) classify nodes into universal roles according to their pattern of intra- and inter-module connections. The method thus yields a ``cartographic representation'' of complex networks. Metabolic networks are among the most challenging biological networks and, arguably, the ones with more potential for immediate applicability. We use our method to analyze the metabolic networks of twelve organisms from three different super-kingdoms. We find that, typically, 80% of the nodes are only connected to other nodes within their respective modules, and that nodes with different roles are affected by different evolutionary constraints and pressures. Remarkably, we find that low-degree metabolites that connect different modules are more conserved than hubs whose links are mostly within a single module.

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Plant-Animal Mutualistic Networks: The Architecture of Biodiversity

Jordi Bascompte, Pedro Jordano (2007)

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Compartments revealed in food-web structure.

Ann Krause, Kenneth A. Frank, Doran Mason … (2003)

Compartments in food webs are subgroups of taxa in which many strong interactions occur within the subgroups and few weak interactions occur between the subgroups. Theoretically, compartments increase the stability in networks, such as food webs. Compartments have been difficult to detect in empirical food webs because of incompatible approaches or insufficient methodological rigour. Here we show that a method for detecting compartments from the social networking science identified significant compartments in three of five complex, empirical food webs. Detection of compartments was influenced by food web resolution, such as interactions with weights. Because the method identifies compartmental boundaries in which interactions are concentrated, it is compatible with the definition of compartments. The method is rigorous because it maximizes an explicit function, identifies the number of non-overlapping compartments, assigns membership to compartments, and tests the statistical significance of the results. A graphical presentation reveals systemic relationships and taxa-specific positions as structured by compartments. From this graphic, we explore two scenarios of disturbance to develop a hypothesis for testing how compartmentalized interactions increase stability in food webs.