Biotic homogenization, i.e. an increase in community similarity through time or space, is a commonly observed response to environmental change, but our mechanistic understanding of this process is relatively limited, especially for microbial communities. This process may be especially difficult to study due to the fact that only a minority of taxa tends to be active at any given point, hence in the case of rapid changes to the environment, detecting community changes may be challenging without focusing on the active fraction. RNA- and DNA-based community inference may help to distinguish the active fraction of a community from the “seed bank” of inactive taxa. Using these two community inference methods, we asked how soil microbial communities respond to land use change in sites undergoing transition from rainforest to crop agriculture via slash-and-burn in the Congo Basin. We used a spatially explicit design with RNA-DNA co-extraction from each sample to investigate mechanisms of community homogenization.
Results/Conclusions
Our results indicate that the magnitude of community homogenization is larger in the RNA-inferred (i.e. active) community than the DNA-inferred community. We show that as the soil environment changes and loses spatial structure, the RNA-inferred community structure tracks environmental variation and loses spatial structure. The DNA-inferred community loses its association with environmental variability. Homogenization of the DNA-inferred community appears to instead be driven by the range expansion of a minority of taxa shared between the forest and conversion sites. Our results suggest that complementing DNA-based surveys with RNA can provide a unique perspective on community responses to environmental change.