Understanding the assembly of ecosystems to estimate the number of species atdifferent spatial scales is a challenging problem. Until now, maximum entropyapproaches have lacked the important feature of considering space in anexplicit manner. We propose a spatially explicit maximum entropy model suitableto describe spatial patterns such as the species area relationship and theendemic area relationship. Starting from the minimal information extracted frompresence/absence data, we compare the behavior of two models considering theoccurrence or lack thereof of each species and information on spatialcorrelations. Our approach uses the information at shorter spatial scales toinfer the spatial organization at larger ones. We also hypothesize a possibleecological interpretation of the effective interaction we use to characterizespatial clustering.
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