Understanding the spatial and temporal dynamics of rain forests is a challenge for assessing the impact of disturbance on forest stands and tree populations. Still few studies address the modelling of spatial patterns of tree density. Here, we present Hierarchical bayesian (HB) models for the local density of juveniles trees in a tropical forest. These models are specifically designed to handle zero inflation and spatial autocorrelation in the data. Height types of models were built and compared through a Hierarchical bayesian approach: Poisson and Negative Binomial generalized linear models, zero-inflated versions of these models and finally a spatial generalization of the four previous models. Spatial dependency in juvenile pattern was modeled through a Conditional Auto Regressive process. An application is presented at the Paracou experimental site (French Guiana). At this site, permanent sample plots settled in a previously undisturbed forest received silvicultural treatments in 1986-1988. Juvenile density of a timber species, Eperua falcata (Caesalpiniaceae), was evaluated in 2003 within 10 m10 m cells and served as response in the models. Explanatory variables described three aspects of environmental heterogeneity inside the plots: topography (elevation and slope) was derived from a Digital Elevation Model; stand variables and population variables, either static or dynamic, were calculated from basal area on 20 m-radius circular subplots.