Is the microbiome a good restoration indicator?
Back in 2009, when researchers were still using biochemical markers or microbial metabolites to investigate the soil microbial communities, Harris 1 summarized two directions of the application of microbes to restoration:
1. Indicate the state of the ecosystem in reference to ‘target’ sites or conditions
2. Be manipulated so as to enhance the speed with which the system can be moved along to the desired state by overcoming ‘biotic barriers,’ either the absence of desirable components (mutualists) or the presence of undesirable (such as invasive plants).
Nowadays, the development of sequencing techniques allows researchers to know what microbes present in the soil by comparing the sequences of the extracted soil DNA with the genome library of known microbes. Although we cannot grow or transplant microbes as we can do to plant, monitoring, inventory, survey, and assessment of microbial communities are not so different from plant communities.
Yan and his coworkers published a series of papers 2–4 telling the same story: restoration sites which have been restored for a longer time and have similar soil properties and vegetation composition to the remnant/reference sites tend to have a more similar microbial communities composition to the remnant/reference sites (see figures below). Their studies offer the possibility of using microbial community composition to monitor the restoration processes.
Using microbial communities as a restoration indicator has many appealing advantages. The first one will be the objectivity of sampling. The collection of soil samples for sequencing is simple: removing the plant litters and collecting a couple of grams of soil with any sterilized equipment, putting the soil in a sterilized bag, and stored with ice. In comparison, plant sampling such as cover or biomass relies on samplers’ judgment or experience on plant identification, which might lead to the inconsistent recording between samplers. Imagining that you want to sample hundreds of sites across the southwest, “calibrating” all samplers from different areas sounds more realistic than do all sampling by yourself, but asking them to send you a small bag of soil may be an easier idea for you and your samplers. Secondly, the DNA of microbial communities contains a giant amount of information. From the Cornell framework manual of soil health5, many indicators are directly related to microbial communities, such as root pathogen pressure assessment, potentially mineralizable nitrogen, and cellulose decomposition rate. Investigating soil microbial communities might save your budget on soil chemical analysis (although its price is trivial compared to sequencing, who will say no to giveaways?). They might even reflect disturbance through “legacy effect”6. Different disturbances, such as flood7, drought8, and the application of pesticide9 or fertilizer10 can lead to a long-term impact. The history of sites is important to the planning of restoration and the disturbance during the restoration is crucial to develop adaptive plans. The patterns of microbial communities responding to specific disturbances are something that plant sampling might not tell us. Thirdly, the microbiome is such an important but still undiscovered world around us. One possibility for the failure of Biosphere II is that we overlook the function of soil microbial communities. Ecological theory informs the practice of restoration and restoration reversely contributes to the development of ecological theory. The same logic can be applied to microbial ecology.
The recovering of soil microbial communities during restoration is not surprising. On one hand, microbial communities are sensitive to environmental changes. The addition of organic matter11, nitrogen fertilizer12, and the presence of invasive species13,14 can all change the microbial communities with predictable patterns. On the other hand, microbes play a central role in nutrient cycling and soil aggregate formation in soil. Some of them are essential to plant communities, either as mutualists or pathogens. A healthy microbiome is a signal of the recovering ecosystem function, which is one of the objectives of ecological restoration. However, the mechanism behind the microbial indicator is still confounding. We might think the abundance of microbial taxa is relevant to its corresponding function. For example, the more nitrogen fixers should lead to more available nitrogen in the soil or faster nitrogen fixation. However, Graham15 modeled the processes in nitrogen cycling with environmental factors and the abundance of corresponding microbes. She found that including microbial abundance did not enhance the explanatory power on the rate of nitrogen cycling. In another study, Graham16 found that microbial community structure did a better job than the abundance, but did not improve the prediction of carbon and nitrogen cycle all the time. Why is that? Noah and Walsh17 summarized a couple of reasons why microbial communities do not respond to the change of plant communities, which can also be the answer here. Maybe microbes don’t care about plants or restoration at all. Maybe the microbial taxonomy cannot correctly infer its function. Maybe microbes evolve and disperse so fast that those microbes with similar functions are not necessary to have a closer genome. Maybe those microbes being sequenced are just passing by, dormant, or even dead instead of playing a role in the ecosystem processes. Long story short, sequencing data might include too many noises. Those traces, which could be a functional group, a species, a protein, or a small piece of the gene, showing the connection between microbial communities and the changing in the environment, might be covered by the massive amount of data generated by sequencing.
To sum up, sequencing techniques shed a light on the path of using microbial communities as restoration indicators. As far as the eye can see, the path bristled with thorns. We do not fully understand the data. We are not sure about the spatial heterogeneity of microbial communities. We do not have as many sampling techniques as plant sampling. However, as Harris might not expect sequencing can be widely applied to microbial ecology in 2020, we can hardly imagine how the techniques will be in the next 10 years. Is the microbiome a good restoration indicator? It isn’t, but it will be.
Reference
1. Harris, J. Soil microbial communities and restoration ecology: facilitators or followers? 325, 2008–2010 (2009).
2. Yan, D. et al. Soil bacterial community differences along a coastal restoration chronosequence. Plant Ecol. 221, 795–811 (2020).
3. Yan, D. et al. A soil archaeal community responds to a decade of ecological restoration. Restor. Ecol. rec.13033 (2019). doi:10.1111/rec.13033
4. Gellie, N. J. C., Mills, J. G., Breed, M. F. & Lowe, A. J. Revegetation rewilds the soil bacterial microbiome of an old field. Mol. Ecol. 26, 2895–2904 (2017).
5. Moebius-Clune, B. N. et al. Comprehensive Assessment of Soil Health - The Cornell Framework Manual. (2016). doi:10.1080/00461520.2015.1125787
6. Cuddington, K. Legacy Effects: The Persistent Impact of Ecological Interactions. Biol. Theory 6, 203–210 (2011).
7. Macé, O. G., Steinauer, K., Jousset, A., Eisenhauer, N. & Scheu, S. Flood-induced changes in soil microbial functions as modified by plant diversity. PLoS One 11, 1–15 (2016).
8. Preece, C., Verbruggen, E., Liu, L., Weedon, J. T. & Peñuelas, J. Effects of past and current drought on the composition and diversity of soil microbial communities. Soil Biol. Biochem. 131, 28–39 (2019).
9. Sederholm, M. R., Schmitz, B. W., Barberán, A. & Pepper, I. L. Effects of metam sodium fumigation on the abundance, activity, and diversity of soil bacterial communities. Appl. Soil Ecol. 124, 27–33 (2018).
10. Dai, Z. et al. Long-term nitrogen fertilization decreases bacterial diversity and favors the growth of Actinobacteria and Proteobacteria in agro-ecosystems across the globe. Glob. Chang. Biol. 24, 3452–3461 (2018).
11. Huang, F. et al. Impact of farmland mulching practices on the soil bacterial community structure in the semiarid area of the loess plateau in China. Eur. J. Soil Biol. 92, 8–15 (2019).
12. de Vries, F. T., Hoffland, E., van Eekeren, N., Brussaard, L. & Bloem, J. Fungal/bacterial ratios in grasslands with contrasting nitrogen management. Soil Biol. Biochem. 38, 2092–2103 (2006).
13. Liao, C. et al. Altered ecosystem carbon and nitrogen cycles by plant invasion: A meta-analysis. New Phytol. 177, 706–714 (2008).
14. Gornish, E. S., Franklin, K., Rowe, J. & Barberán, A. Buffelgrass invasion and glyphosate effects on desert soil microbiome communities. Biol. Invasions (2020). doi:https://doi.org/10.1007/s10530-020-02268-8
15. Graham, E. B. et al. Do we need to understand microbial communities to predict ecosystem function? A comparison of statistical models of nitrogen cycling processes. Soil Biol. Biochem. 68, 279–282 (2014).
16. Graham, E. B. et al. Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes? Front. Microbiol. 7, 1–10 (2016).
17. Fierer, N. & Walsh, C. Expectation is the root of all heartache: Plant species identity and the rhizosphere microbiome. (2020). Available at: http://fiererlab.org/2020/01/30/expectation-is-the-root-of-all-heartach….