RESUMO
The way strong environmental gradients shape multispecific assemblages has allowed us to examine a suite of ecological and evolutionary hypotheses about structure, regulation and community responses to fluctuating environments. But whether the highly diverse co-occurring microorganisms are shaped in similar ways as macroscopic organisms across the same gradients has yet to be addressed in most ecosystems. Here, we characterize intertidal biofilm bacteria communities, comparing zonation at both the "species" and community levels, as well as network attributes, with co-occurring macroalgae and invertebrates in the same rocky shore system. The results revealed that the desiccation gradient has a more significant impact on smaller communities, while both desiccation and submersion gradients (surge) affect the larger, macroscopic communities. At the community level, we also confirmed the existence of distinct communities within each intertidal zone for microorganisms, similar to what has been previously described for macroorganisms. But our results indicated that dominant microbial organisms along the same environmental gradient exhibited less differentiation across tidal levels than their macroscopic counterparts. However, despite the substantial differences in richness, size and attributes of co-occurrence networks, both macro- and micro-communities respond to stress gradients, leading to the formation of similar zonation patterns in the intertidal rocky shore.
Assuntos
Ecossistema , Microbiota , Biodiversidade , Bactérias/genéticaRESUMO
Co-occurrence methods are increasingly utilized in ecology to infer networks of species interactions where detailed knowledge based on empirical studies is difficult to obtain. Their use is particularly common, but not restricted to, microbial networks constructed from metagenomic analyses. In this study, we test the efficacy of this procedure by comparing an inferred network constructed using spatially intensive co-occurrence data from the rocky intertidal zone in central Chile to a well-resolved, empirically based, species interaction network from the same region. We evaluated the overlap in the information provided by each network and the extent to which there is a bias for co-occurrence data to better detect known trophic or non-trophic, positive or negative interactions. We found a poor correspondence between the co-occurrence network and the known species interactions with overall sensitivity (probability of true link detection) equal to 0.469, and specificity (true non-interaction) equal to 0.527. The ability to detect interactions varied with interaction type. Positive non-trophic interactions such as commensalism and facilitation were detected at the highest rates. These results demonstrate that co-occurrence networks do not represent classical ecological networks in which interactions are defined by direct observations or experimental manipulations. Co-occurrence networks provide information about the joint spatial effects of environmental conditions, recruitment, and, to some extent, biotic interactions, and among the latter, they tend to better detect niche-expanding positive non-trophic interactions. Detection of links (sensitivity or specificity) was not higher for well-known intertidal keystone species than for the rest of consumers in the community. Thus, as observed in previous empirical and theoretical studies, patterns of interactions in co-occurrence networks must be interpreted with caution, especially when extending interaction-based ecological theory to interpret network variability and stability. Co-occurrence networks may be particularly valuable for analysis of community dynamics that blends interactions and environment, rather than pairwise interactions alone.