  Previous work has shown that species interacting in an ecosystem and actors
transacting in an economic context may have notable similarities in behavior.
However, the specific mechanism that may underlie similarities in nature and
human systems has not been analyzed. Building on stochastic food-web models, we
propose a parsimonious bipartite-cooperation model that reproduces the key
features of mutualistic networks - degree distribution, nestedness and
modularity -- for both ecological networks and socio-economic networks. Our
analysis uses two diverse networks. Mutually-beneficial interactions between
plants and their pollinators, and cooperative economic exchanges between
designers and their contractors. We find that these mutualistic networks share
a key hierarchical ordering of their members, along with an exponential
constraint in the number and type of partners they can cooperate with. We use
our model to show that slight changes in the interaction constraints can
produce either extremely nested or random structures, revealing that these
constraints play a key role in the evolution of mutualistic networks. This
could also encourage a new systematic approach to study the functional and
structural properties of networks. The surprising correspondence across
mutualistic networks suggests their broadly representativeness and their
potential role in the productive organization of exchange systems, both
ecological and social.
