In these lectures, we give an account of certain recent developments of
the theory of spatial branching processes. These developments lead to
several fas- cinating probabilistic objects, which combine spatial
motion with a continuous branching phenomenon and are closely related to
certain semilinear partial dif- ferential equations. Our first objective
is to give a short self-contained presentation of the measure- valued
branching processes called superprocesses, which have been studied
extensively in the last twelve years. We then want to specialize to the
important class of superprocesses with quadratic branching mechanism and
to explain how a concrete and powerful representation of these processes
can be given in terms of the path-valued process called the Brownian
snake. To understand this representation as well as to apply it, one
needs to derive some remarkable properties of branching trees embedded
in linear Brownian motion, which are of independent interest. A nice
application of these developments is a simple construction of the random
measure called ISE, which was proposed by Aldous as a tree-based model
for random distribution of mass and seems to play an important role in
asymptotics of certain models of statistical mechanics. We use the
Brownian snake approach to investigate connections between super-
processes and partial differential equations. These connections are
remarkable in the sense that almost every important probabilistic
question corresponds to a significant analytic problem.