  It is a classical result of Stein and Waterman that the asymptotic number of
RNA secondary structures is $1.104366 \cdot n^{-3/2} \cdot 2.618034^n$.
Motivated by the kinetics of RNA secondary structure formation, we are
interested in determining the asymptotic number of secondary structures that
are locally optimal, with respect to a particular energy model. In the Nussinov
energy model, where each base pair contributes -1 towards the energy of the
structure, locally optimal structures are exactly the saturated structures, for
which we have previously shown that asymptotically, there are $1.07427\cdot
n^{-3/2} \cdot 2.35467^n$ many saturated structures for a sequence of length
$n$. In this paper, we consider the base stacking energy model, a mild variant
of the Nussinov model, where each stacked base pair contributes -1 toward the
energy of the structure. Locally optimal structures with respect to the base
stacking energy model are exactly those secondary structures, whose stems
cannot be extended. Such structures were first considered by Evers and
Giegerich, who described a dynamic programming algorithm to enumerate all
locally optimal structures. In this paper, we apply methods from enumerative
combinatorics to compute the asymptotic number of such structures.
Additionally, we consider analogous combinatorial problems for secondary
structures with annotated single-stranded, stacking nucleotides (dangles).
