Effect of Light-Dark Cycles on Soil Bacterial Communities
Here, we detected numerous differentially abundant ASVs that displayed fluctuating patterns in ASV relative abundance and differences in network complexity over the 24-hr sampling period. We found that mean node degree (connectance) was significantly higher between 00:00 and 06:00 than between 12:00 and 18:00 for the native plots but significantly lower for the cleared sites between these times. This indicates a level of time-dependent changes in bacterial network complexity with inter-site variability. In other words, it appears that native site bacterial interactions increased in the early morning hours when it is darker (and colder) and decreased in the afternoon/evening when it is lighter, and vice versa for the cleared plots. Further, the ‘hub taxa’ analysis results showed that the bacteria with the highest node degree at the genus level were different at different sampling times. These findings support that light-dark cycles mediate changes in bacterial interactions (e.g., driven by time-dependent rhizosphere activity). One possible explanation for this light-dark cycling could be the transmission of biological rhythms from plants to the soil bacteria (Newman et al. 2022), as plants alter the physicochemical properties of the soil. Soil temperature, moisture and respiration also vary diurnally (Hu et al., 2016), which could affect these microbial interactions, as could methane fluxes via plant exudates or other microorganisms (Subke et al., 2018). The time-dependent changes observed in bacterial network complexity and ASV relative abundances suggest that the time of sampling should be considered in soil microbial studies. The differences in bacterial interactions between land cover types (between day and night) are equally as interesting. This inter-site variation suggests that vegetation complexity may influence rhizosphere microbial community interactions in combination with light-dark cycles. More research is needed to determine the drivers of this variation. However, we can speculate that vegetation community-mediated differences in soil biogeochemistry between the more complex remnant vegetation (i.e., our native plots) and the less diverse lawn (i.e., our cleared plots) sites—-resulting from factors such as variation in transpiration, shade, exudation, and pH—-may be responsible.
We did not observe a strong effect of time or light-dark cycles on the soil bacterial alpha or beta diversity at the community level in any plot. We are aware of no studies that have focused on characterising the light-dark cycles of soil bacterial communities in situ and to our knowledge, very few have used DNA-based approaches to study soil bacterial light-dark cycles. Landesman et al. (2019) was the only study prior to ours that had considered the effect of light-dark cycles on bacterial communities however, their primary focus was on seasonal variation. Light-dark patterns in bacterial communities were observed in the rhizospheres of Arabidopsis thaliana and rice in a range ofex situ greenhouse studies (Lu et al., 2021; Staley et al., 2017; Zhao, Ma, et al., 2021; 2022). It is possible that our study did not detect a light-dark effect at the sample community level because the soils were pooled at the plot level and did not specifically target root rhizospheres (separate from bulk soils), as per the studies mentioned above. While there is variation in the life cycles of different bacterial taxa, the bacterial turnover rates in bulk soils (further away from the rhizosphere) are expected to be slower and therefore may not vary over such short temporal scales (Joergensen & Wichern, 2019; Sokol et al., 2022). However, as used in some greenhouse experiments (Baraniya et al., 2018; Dai et al., 2022; Staley et al., 2017), transcriptomics may reveal new insights into the light-dark cycles of bacterial community activity and plant exudates in vegetation community-wide studies. Future studies could apply these transcriptomic approaches that generate activity level data of soil bacterial communities rather than focusing on changes in community composition.