  We use a novel statistical tool, the mark correlation functions (MCFs), to
study clustering of galaxy-size halos as a function of their properties and
environment in a high-resolution numerical simulation of the LambdaCDM
cosmology. We applied MCFs using several types of continuous and discrete
marks: maximum circular velocity of halos, merger mark indicating whether halos
experienced or not a major merger in their evolution history, and a stripping
mark indicating whether the halo underwent a tidal stripping. We find that
halos which experienced a relatively early (z>1) major merger or mass loss (due
to tidal stripping) in their evolution histories are over-abundant in halo
pairs with separations < 3 Mpc/h. This result can be interpreted as spatial
segregation of halos with different merger histories, qualitatively similar to
the morphological segregation in the observed galaxy distribution. The analysis
presented in this paper demonstrate that MCFs provide powerful, yet
algorithmically simple, quantitative measures of segregation in the spatial
distribution of objects with respect to their various properties (marks).
