  Complex system stability can be studied via linear stability analysis using
Random Matrix Theory (RMT) or via feasibility (requiring positive equilibrium
abundances). Both approaches highlight the importance of interaction structure.
Here we show, analytically and numerically, how RMT and feasibility approaches
can be complementary. In generalised Lotka-Volterra (GLV) models with random
interaction matrices, feasibility increases when predator-prey interactions
increase; increasing competition/mutualism has the opposite effect. These
changes have crucial impact on the stability of the GLV model.
