It is becoming widely accepted that very early in the origin of life, even
before the emergence of genetic encoding, reaction networks of diverse small
chemicals might have manifested key properties of life, namely self-propagation
and adaptive evolution. To explore this possibility, we formalize the dynamics
of chemical reaction networks within the framework of chemical ecosystem
ecology. To capture the idea that life-like chemical systems are maintained out
of equilibrium by fluxes of energy-rich food chemicals, we model chemical
ecosystems in well-mixed containers that are subject to constant dilution by a
solution with a fixed concentration of food chemicals. Modelling all chemical
reactions as fully reversible, we show that seeding an autocatalytic cycle (AC)
with tiny amounts of one or more of its member chemicals results in logistic
growth of all member chemicals in the cycle. This finding justifies drawing an
instructive analogy between an AC and the population of a biological species.
We extend this finding to show that pairs of ACs can show competitive,
predator-prey, or mutualistic associations just like biological species.
Furthermore, when there is stochasticity in the environment, particularly in
the seeding of ACs, chemical ecosystems can show complex dynamics that can
resemble evolution. The evolutionary character is especially clear when the
network architecture results in ecological precedence (survival of the first),
which makes the path of succession historically contingent on the order in
which cycles are seeded. For all its simplicity, the framework developed here
is helpful for visualizing how autocatalysis in prebiotic chemical reaction
networks can yield life-like properties. Furthermore, chemical ecosystem
ecology could provide a useful foundation for exploring the emergence of
adaptive dynamics and the origins of polymer-based genetic systems