The concept of limiting step gives the limit simplification: the wholenetwork behaves as a single step. However, in its simplest form this idea isapplicable only to the simplest linear cycles in steady states. For such thesimplest cycles the nonstationary behaviour is also limited by a single step,but not the same step that limits the stationary rate. We develop a generaltheory of static and dynamic limitation for all linear multiscale networks. Newestimates of eigenvectors for diagonally dominant matrices are used. Multiscale ensembles of reaction networks with well separated constants areintroduced and typical properties of such systems are studied. For any givenordering of reaction rate constants the explicit approximation of steady state,relaxation spectrum and related eigenvectors ("modes") is presented. Theobtained multiscale approximations that we call "dominant systems" arecomputationally cheap and robust. These dominant systems can be used for directcomputation of steady states and relaxation dynamics, especially when kineticinformation is incomplete, for design of experiments and mining of experimentaldata, and could serve as a robust first approximation in perturbation theory orfor preconditioning.