October Reading List: Ecosystem Functioning

Theme of the month: microbes to ecosystem functioning

I wanted to get back to some of main goals in microbial ecology: relating microbial composition (or changes in composition) to function. This part of microbial ecology can lean heavily on the work done in community ecology from macroorganisms. In particular, there is a need to move beyond describing patterns of species richness and diversity to get at the functional consequences of this variation across spatiotemporal scales. This allows the use of a trait-based framework to really link traits to ecosystems and to link them inevitably to measures of diversity. As a primer, I would highly recommend reading this book chapter by Enquist et al (2013) which provides a thorough read through of trait based frameworks, including its influences from Grime's Mass Ratio and Metabolic Scaling Theory - both of which can be applied to microbial systems.

Without further ado, here are some recent papers tackling this topic:

Linking Microbial Diversity to Functioning

Traits underlie an organism's response to both biotic and abiotic factors. These traits will underline a particular organism's geographic distribution. For the most part, studies infer traits from microbial surveys, but linking these remain incredibly difficult. For one, it's impossible to quantify every trait for every microbes in a system. Of course, we can borrow from community ecology and concentrate on the more abundant, dominant members in a system (e.g., some of my work on Curtobacterium [1]). But this requires a lot of work, from isolation, characterization, developing relevant assays, collecting geographic distribution data, etc. Much more feasible is assaying for community-wide "traits" or determining function from aggregated functional responses (e.g., respiration). These approaches should allow for the formulation of hypotheses on microbial trait responses (for more see these two recent reviews here [2,3,4]).

Environmental Gradients

Traits by Gradients. Each line represents a different taxa. A) Physiological response curve of trait performance by some environmental variable (temperature) C) Expected niche of each taxa based on physiological measurements [5]

All microbial communities exist on environmental gradients of temperature, moisture, pH, etc. How communities will respond to these environmental variables requires an understanding of the variation among taxa [5]. These ideas have been around for decades in studies with macrobes, but only recently have microbial ecologists begun to assess community responses along gradients.

​For instance, I will highlight two papers here:
Glassman et al. used a large-scale reciprocal transplant experiment to look at how decomposition rates would change across a climate gradient co-varying in temperature and precipitation [6]. Another recent study looked at how salinity functioned as an environmental filter to investigate the aggregate trait response and its link to community structure [7].

Plants to soil to ecosystems

Going to finish off with 3 papers I liked this past year or so. They are all related to soil microbiomes so sorry for any marine or human microbiome people out there!

Do plants, bacteria, and fungi respond similarly by the same environmental variables? A recent study  applies trait-based ecology to investigate the effects of temperature [8]. Specifically, should shifts in temperature correspond to shifts in plant traits and microbial function? And are there ecological feedbacks between plants and their microbes?

Speaking of the soil microbiome affecting plant health. Wei et al. found that small variation in the initial soil microbiome can affect the health of plants throughout their experiment [9]. These results highlight the plant disease dynamics can be driven by highly deterministic processes based on the microbial composition and functional properties. Lastly, plants can regulate their rhizosphere microbial community by releasing chemical exudates from their roots [10]. The release of these exudates follows a "chemical succession" of microbes driving community assembly.

Papers:

1. Chase AB, Gomez-Lunar Z, Lopez AE, Li J, Allison SD, Martiny AC, Martiny JBH. (2018). Emergence of soil bacterial ecotypes along a climate gradient. Environmental Microbiology 20: 4112-4126.

2. Lajoie G, Kembel SW. (2019). Making the most of trait-based approaches for microbial ecology. Trends in Microbiology 27: 814-823.

3. Wang JT, Egidi E, Li J, Singh BK. (2019). Linking microbial diversity with ecosystem functioning through a trait framework. Journal of Biosciences 44: 109.

4. Malik AA, Martiny JBH, Brodie EL, Martiny AC, Treseder KK, Allison SD. (2019). Defining trait-based microbial strategies with consequences for soil carbon cycling under climate change. The ISME Journal 1-9.

5. McGill BJ, Enquist BJ, Weiher E, Westoby M. (2006). Rebuilding community ecology from functional traits. Trends in Ecology and Evolution 4: 178-185.

6. Glassman SI, Weihe C, Li J, Albright MBN, Looby CI, Martiny AC, Treseder KK, Allison SD, Martiny JBH. (2018). Decomposition responses to climate depend on microbial community composition. Proceedings to the National Academy of Sciences 115(47): 11994-11999.

7. Rath KM, Maheshwari A, Rousk J. Linking microbial community structure to trait distributions and functions using salinity as an environmental filter. mBio 10(4): e01607-19.

8. Buzzard V, Michaletz ST, Deng Y, He Z, Ning D, Shen L, Tu Q, Van Nostrand JD, Vooreckers JW, Wang J, Weiser MD, Kaspari M, Waide RB, Zhou J, Enquist BJ. (2019). Continental scale structuring of forest and soil diversity via functional traits. Nature Ecology and Evolution 3: 1298-1308.

9. Wei Z, Gu Y, Friman VP, Kowalchuk GA, Xu Y, Shen Q, Jousset A. (2019). Initial soil microbiome composition and functioning predetermine future plant health. Science Advances 5(9): eaaw0759.

10. Zhalnina K, Louie KB, Hao Z, Mansoori N, da Rocha UN, Shi S, Cho H, Karaoz U, Loque D, Bowen BP, Firestone MK, Northen TR, Brodie EL. (2018). Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly. Nature Microbiology 3: 470-480.