  In the last years, a remarkable theoretical effort has been made in order to
understand stability and complexity in ecological communities. The non-random
structures of real ecological interaction networks has been recognized as one
key ingredient contributing to the coexistence between high complexity and
stability in real ecosystems. However most of the theoretical studies have
considered communities with only one interaction type (either antagonistic,
competitive, or mutualistic). Recently it has been proposed a theoretical
analysis on multiple interaction types in ecological systems, concluding that:
a) Mixture of antagonistic and mutualistic interactions stabilize the system
with respect to the less realistic case of only one interaction type; b)
Complexity, measured in terms of the number of interactions and the number of
species, increases stability in systems with different types of interactions.
By introducing new theoretical investigations and analyzing 21 empirical data
sets representing mutualistic plant-pollinator networks, we show that that
conclusions are incorrect. We will prove that the positive complexity-stability
effect observed in systems with different kind of interactions is a mere
consequence of a rescaling of the interaction strengths, and thus unrelated to
the mixing of interaction types.
