  Mutualistic networks are formed when the interactions between two classes of
species are mutually beneficial. They are important examples of cooperation
shaped by evolution. Mutualism between animals and plants plays a key role in
the organization of ecological communities. Such networks in ecology have
generically evolved a nested architecture independent of species composition
and latitude - specialists interact with proper subsets of the nodes with whom
generalists interact. Despite sustained efforts to explain observed network
structure on the basis of community-level stability or persistence, such
correlative studies have reached minimal consensus. Here we demonstrate that
nested interaction networks could emerge as a consequence of an optimization
principle aimed at maximizing the species abundance in mutualistic communities.
Using analytical and numerical approaches, we show that because of the
mutualistic interactions, an increase in abundance of a given species results
in a corresponding increase in the total number of individuals in the
community, as also the nestedness of the interaction matrix. Indeed, the
species abundances and the nestedness of the interaction matrix are correlated
by an amount that depends on the strength of the mutualistic interactions.
Nestedness and the observed spontaneous emergence of generalist and specialist
species occur for several dynamical implementations of the variational
principle under stationary conditions. Optimized networks, while remaining
stable, tend to be less resilient than their counterparts with randomly
assigned interactions. In particular, we analytically show that the abundance
of the rarest species is directly linked to the resilience of the community.
Our work provides a unifying framework for studying the emergent structural and
dynamical properties of ecological mutualistic networks.
