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.