  We study the evolution of a particle system whose genealogy is given by a
supercritical continuous time Galton--Watson tree. The particles move
independently according to a Markov process and when a branching event occurs,
the offspring locations depend on the position of the mother and the number of
offspring. We prove a law of large numbers for the empirical measure of
individuals alive at time t. This relies on a probabilistic interpretation of
its intensity by mean of an auxiliary process. The latter has the same
generator as the Markov process along the branches plus additional jumps,
associated with branching events of accelerated rate and biased distribution.
This comes from the fact that choosing an individual uniformly at time t favors
lineages with more branching events and larger offspring number. The central
limit theorem is considered on a special case. Several examples are developed,
including applications to splitting diffusions, cellular aging, branching
L\'{e}vy processes.
