Résumé
Microbial ecologists often obtain data from sampling a piece of geographic space. These are likely to be spatially autocorrelated. Autocorrelation removes degrees of freedom from the usual tests of inferential statistics and can generate spurious correlations among variables, with the consequence that suspected causal relations may not hold. This paper describes methods that can be used to explore the spatial structure of ecological data and to include spatial location as a variable in the study of relationships and models. The relationship between environmental heterotrophic bacteria and phytoplankton, well established in aquat environments, is re-examined in the Thau brackish lagoon (Mediterranean coast of France). It did not hold for the bacteria growing on bioMerieux nutrient agar (BNA), which are presumably of continental origin; their spatial gradient can only partly be explained by the particulate organic carbon variable (POC) and not at all by phytoplankton biomass (CHL A), despite the existence of a spurious correlation between BNA and CHL A. The spatial gradient of abundance of heterotrophs growing on marine agar (MA), expected to be mostly of marine origin, can be entirely explained by POC and CHL A. Different segments of the bacterial community, both reacting positively to variations of the particulate organic carbon, may follow partly, or not, variations of phytoplankton biomass. The mode of analysis developed here extends to many other spatially distributed processes in ecology and other fields.