Social science and ecology. Networking tips for social scientists and ecologists

Keystone species and food webs

Different species are of different importance in maintaining ecosystem functions in natural communities. Quantitative approaches are needed to identify unusually important or influential, 'keystone' species particularly for conservation purposes. Since the importance of some species may largely be the consequence of their rich interaction structure, one possible quantitative approach to identify the most influential species is to study their position in the network of interspecific interactions. In this paper, I discuss the role of network analysis (and centrality indices in particular) in this process and present a new and simple approach to characterizing the interaction structures of each species in a complex network. Understanding the linkage between structure and dynamics is a condition to test the results of topological studies, I briefly overview our current knowledge on this issue. The study of key nodes in networks has become an increasingly general interest in several disciplines: I will discuss some parallels. Finally, I will argue that conservation biology needs to devote more attention to identify and conserve keystone species and relatively less attention to rarity.

Compartments revealed in food-web structure

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.

New methods to investigate infectious disease transmission and pathogenesis--Staphylococcus aureus disease in drug users

Staphylococcus aureus is the single most important bacterial pathogen in infections among drug users. It is responsible for several diseases, ranging from superficial cutaneous abscesses to life-threatening intravascular infections. Although the nature of these infections is well described in published work, there is limited understanding of their epidemiology and pathogenesis. This limitation is in part due to the difficulty of studying disease transmission among drug users in the community, and the limitations of the investigative tools that have so far been used. We review the current understanding of the pathogenesis of staphylococcal disease in drug users and argue for the integration of molecular epidemiological techniques and social network methodology to increase our understanding of the basis for the persistence, distribution, and transmission dynamics of S aureus among drug users. Finally, we propose a framework for investigating the transmission of pathogens in community-based settings.