  Understanding the assembly of ecosystems to estimate the number of species at
different spatial scales is a challenging problem. Until now, maximum entropy
approaches have lacked the important feature of considering space in an
explicit manner. We propose a spatially explicit maximum entropy model suitable
to describe spatial patterns such as the species area relationship and the
endemic area relationship. Starting from the minimal information extracted from
presence/absence data, we compare the behavior of two models considering the
occurrence or lack thereof of each species and information on spatial
correlations. Our approach uses the information at shorter spatial scales to
infer the spatial organization at larger ones. We also hypothesize a possible
ecological interpretation of the effective interaction we use to characterize
spatial clustering.
