  We introduce a decoupling method on the Wiener space to define a wide class
of an\-iso\-tro\-pic Besov spaces. The decoupling method is based on a general
distributional approach and not restricted to the Wiener space.
  The class of Besov spaces we introduce contains the traditional isotropic
Besov spaces obtained by the real interpolation method, but also new spaces
that are designed to investigate backwards stochastic differential equations
(BSDEs). As examples we discuss the Besov regularity (in the sense of our
spaces) of forward diffusions and local times. It is shown that among our newly
introduced Besov spaces there are spaces that characterize quantitative
properties of directional derivatives in the Malliavin sense without computing
or accessing these Malliavin derivatives explicitly.
  Regarding BSDEs, we deduce regularity properties of the solution processes
from the Besov regularity of the initial data, in particular upper bounds for
their $L_p$-variation, where the generator might be of quadratic type and where
no structural assumptions, for example in terms of a forward diffusion, are
assumed. As an example we treat sub-quadratic BSDEs with unbounded terminal
conditions.
  Among other tools, we use methods from harmonic analysis. As a by-product, we
improve the asymptotic behaviour of the multiplicative constant in a
generalized Fefferman inequality and verify the optimality of the bound we
established.
