Math, models, microbes: Diving into the complex soil community interactions of plant-soil feedbacks

Guest post by Tyler Poppenwimer (University of Tennessee) and Michael Van Nuland (University of Tennessee)

A major challenge for predicting the strength and direction of plant-soil feedbacks (PSF) is understanding the interactions between plant traits, belowground communities, and the soil processes both compartments influence. A new article by Ke et al. (2015) uses a modeling approach to test how interactions between litter- and root-mediated pathways can influence which plant and soil biota traits are important mechanisms that drive PSF. Here, we will unpack their model in a simple way and touch on some of the interesting ecological and evolutionary implications. The model developed by Ke et al. attempts to capture the complexities involved in PSF by considering six major elements wherein each element interacts. Although highly complex, we can easily illustrate this model by following the movement of nitrogen through the system. In seedlings and adults, nitrogen is obtained through both a natural ability and mycorrhizal-mediated pathway. Both seedlings and adults then fix carbon in an amount proportional to their acquisition of nitrogen. Additionally, adults use nitrogen to produce seedlings and litter whilst seedlings use it to mature to adulthood. Plants do not survive indefinitely and eventually die via natural or pathogenic causes. Once deceased, they produce litter proportional to their carbon biomass. Once this biomass has been converted into litter, either through death or production thereof, it decomposes and nitrogen is deposited into the soil. Once in the soil, nitrogen can be acquired by mycorrhizae or plants and the cycle repeats. Although this is the main system, the model also includes the additional actions of competition between pathogens and mycorrhizae, mycorrhizal and pathogenic uptake of nutrients from the plants, light competition among adults and seedlings, and abiotic fluctuations of soil nitrogen. The model is necessarily complex – take a look at Figure 1 if you don’t believe us. This is so that it can realistically capture the interactions of major elements that structure PSF. Their use of differential equations wherein each element depends on the actions of the others greatly increases the realism of their model. For example, the production of seedlings depends on the adult’s uptake of nitrogen from the soil, which is (in part) dependent on mycorrhizae (whose actions can be influenced by pathogenic competition), where pathogenic competition is dependent on the amount of nitrogen obtained from deceased plants. Yeah, lots of moving parts. Further strengthening their model, they present a partially closed system where a majority of the nitrogen must be recycled in an efficient fashion to avoid breakdowns. Although strengthened by the aforementioned qualities, like all models it contains potential weaknesses. A potential weakness is their assumption that nitrogen is evenly distributed in the soil such that all plants have equal access to all nitrogen. Additionally, it is assumed that nitrogen uptake is not proportional to the biomass of the plant, it is only proportional to the life stage (seedling or adult). In spite of these shortcomings, the model is able to realistically capture the interactions of PSF, highlighting the role of soil microbes in plant-soil conditioning and the reciprocal effects of soils on plant survival. Plant phenotypes construct soil niches, which given phenotypic variation results in differing soil conditions that are the basis of PSF. Given this well-known fact, it is surprising that relating plant traits to PSF is relatively rare. Ke et al. show that it is high-time to incorporate plant traits if we are to boost our understanding when it comes to predicting feedbacks (Kardol et al. 2015). They illustrate the strength of this approach by correlating litter decomposability with PSF strength based on differing traits of the soil community (e.g., mycorrhizal or pathogen heavy). It might also prove useful to explore how the other plant traits considered in their model would relate to PSF strength. For instance, how might the pattern change if plant defense traits (tissue C:N or pathogen mortality rate) were used to predict PSF strength from similar literature data? It might be expected (as their model suggests) that defense traits would be more important for determining PSF resulting from pathogens or mycorrhizae (Figure 2). Similarly, as the authors point out, simplifying mycorrhizae down to a positive effect on plants goes against biological realism a bit, since root-associated fungi function along a parasitism-mutualism continuum (Johnson et al. 1997). It might be interesting to somehow program that for similar models in the future, whereby plant trait variation would alter fungal traits along a negative-positive scale, thereby affecting PSF outcomes. The authors predict that invaders with high litter decomposability perform better with increasing mycorrhizal abundance. However, this might not be universal – especially when we consider the example of invasive pines, which have tough leaves and low litter decomposability. In areas where pines have been introduced and spread quickly, it has been shown that the invasion is dependent on the presence of mycorrhizal associations (i.e., a change in relative abundance of mycorrhizae from 0 to 1+; Dickie et al. 2010). What we think is an important take-away though, is that plant-microbe interactions (mediated by traits) are increasingly being recognized as having strong implications for species range dynamics – both from an experimental and now from a modeling standpoint.  There are some interesting evolutionary implications from the paper that we won’t discuss in detail here, but are worthwhile to ponder (and discuss in the comments section!). For example, if plant litter chemistry is heritable, then the fact that root-associated communities dictate the trait effect on PSF enters into the realm of quantitative and population genetics. In this sense, the Ke et al. findings are consistent with previous work on the mechanistic basis of plant-soil linkages that result in evolutionary interactions (Kylafis and Loreau 2008, Schweitzer et al. 2014), but add a new level of specificity and complexity by avoiding the familiar black-box perspective to tackle some of the major soil biotic interactions. Overall, we thought this was an excellent paper from multiple standpoints and would love to hear your thoughts! References Dickie IA et al. (2010) Co‐invasion by Pinus and its mycorrhizal fungi. New Phytologist 187: 475-484. Johnson NC et al. (1997) Functioning of mycorrhizal associations along the mutualism–parasitism continuum*. New Phytologist 135: 575-585. Kardol P et al. (2015) Peeking into the black box: a trait-based approach to predicting plant-soil feedback. New phytologist 206: 1-4. Ke P-J et al. (2015) The soil microbial community predicts the importance of plant traits in plant–soil feedback. New Phytologist 206: 329-341. Kylafis G & Loreau M (2008) Ecological and evolutionary consequences of niche construction for its agent. Ecology letters 11: 1072-81. Schweitzer JA et al. (2014) Are there evolutionary consequences of plant–soil feedbacks along soil gradients? Functional Ecology 28: 55-64.

Sequencing meta-analysis workshop, Manchester, 18-20 May 2015

We are organizing a workshop to bring together ecologists and bioinformaticians to work on a meta-analysis of sequencing data with the aim of exploring patterns in belowground biodiversity.

The description and biogeography of belowground biodiversity is severely lagging behind that of aboveground diversity. This is despite increasing recognition of the importance of soil organisms for ecosystem functioning, including carbon and nitrogen cycling, and feedbacks to plant community composition, which underlie ecosystem services such as food production and climate mitigation. Moreover, recent evidence suggests that patterns of belowground biodiversity might not follow those of aboveground biodiversity. Thus, belowground biodiversity offers a unique opportunity to test and develop ecological theory. However, bringing together soil biodiversity data is challenging, especially when it comes to sequencing data, because pipelines and metadata are not standardized.

Confirmed speakers/leaders of the workshop are:

–Dr Kelly Ramirez, Netherlands Institute of Ecology, the Netherlands and GSBI

–Dr Rob Griffiths, CEH Wallingford, UK

–Dr Jennifer Talbot, Boston University, USA

-Dr Hyun Soon Gweon, CEH Wallingford, UK

–Dr John Davison, University of Tartu, Estonia

The aim of this workshop is to bring together ecologists and bioinformaticians to do a meta-analysis of sequencing data of soil microbial communities. Both publicly available data and participants’ data will be used, and the anticipated outcome is a publication in a peer-reviewed journal. The workshop will consist of lectures by our invited speakers to highlight recent advances, and participants will be expected to give a short presentation about their background and expertise. The majority of time will be spent identifying ecological questions to address with the data, analyzing the data in novel ways, and drafting a manuscript.

Spaces for this workshop are limited, and we are seeking motivated ecologists and bioinformaticians of all career stages to participate in, and contribute to, the workshop. Participants are expected to bring their own dataset of soil microbial (principally bacterial) community sequencing data (including metadata), and to have some experience in analyzing sequencing data.

The call for participants is now open. Applications should consist of a one-page CV, description of the dataset(s) that the applicant will bring to the workshop, and a statement (500 words maximum) of what the applicant will contribute to, and hopes to get out of, the workshop, including proposed hypotheses to be explored during the workshop.

Send your application to besplantsoileco@gmail.com before April the 10^th 5pm. Applicants will be notified whether they have been selected for the workshop by April the 17^th. For questions email Franciska de Vries: franciska.devries@manchester.ac.uk

Registration fee: £75 (students)/£100 (BES members)/£125 (others)

 

Soil biodiversity and soil community composition determine ecosystem multifunctionality

This paper, by Cameron Wagg et al., which was published online early in PNAS last month, describes the results of a very interesting experiment in which the authors manipulated soil biodiversity and measured the effect of these manipulations on a range of ecosystem functions.

More specifically, they created a gradient of reduced soil biodiversity (including a range of faunal and microbial groups) by sieving the soil through a number of decreasing mesh sizes, adding the fraction that passed through the sieve to sterilized soil, while also adding the sterilized fraction that remained on top of the sieve. They then grew plant communities consisting of common grasslands species in the soil for 14 and for 24 weeks, in two separate experiments. At the end of the first experiment, and after 12 and 24 weeks of the second experiment, they measured plant diversity and productivity, carbon sequestration, litter decomposition, nitrogen turnover, N₂O emission, phosphorus and nitrogen leaching as ecosystem functions, and fungal and bacterial diversity (by TRFLP), mycorrhizal root colonization (microscopically), and nematode abundance (microscopically).

They then used these data to relate the ecosystem functions measured to the soil biodiversity treatments. In addition, they calculated z-scores for the range of ecosystem functions measured as well as for all groups of organisms quantified, and regressed these against each other to answer the question whether ecosystem multifunctionality is related to soil biodiversity. This approach, of summarising a number of ecosystem processes into one ecosystem multifunctionality index, has been used previously by Maestre et al. (2012).

Their findings are very interesting and will make a lot of soil ecologists very happy: they find that a number of the individual ecosystem functions are reduced with declining biodiversity, but also that ecosystem multifunctionality is positively correlated with overall soil biodiversity.

When taking a closer look at the data, it becomes clear that the reduction in soil biodiversity varies between groups and isn’t linear with the decreasing mesh sizes – mycorrhiza and nematodes drop down sharply after the third ‘dilution’, whereas the other parameters show a more gradual decline. The authors have taken this into account by not only relating ecosystem functioning to the diversity treatments, but also to the abundance and diversity of individual groups. When taking a closer look at this, it becomes clear that the microbial properties measured have a far stronger effect than nematode abundance. In addition, the effect of reduced soil biodiversity on a range of functions is indirect, through effects of plant productivity and diversity.

Of course, it is very easy to criticise aspects of this study. You can question whether bacterial and fungal diversity, microbial biomass, mycorrhizal colonization, and nematode abundance together are a realistic representation of soil biodiversity. For example, why was nematode diversity not assessed? And why not higher trophic levels, such as Collembola and mites? Microbes and nematodes are only a fraction of the soil food web (Fig. 1). With the current analyses, the title ‘Soil microbial diversity and community composition determine ecosystem multifunctionality’ might have been more appropriate.

A (simplified) example of a soil food web, with the groups measured by Wagg et al. (2014) indicated by the dashed line.

Also, it would have been interesting to see root biomass in addition to mycorrhizal colonisation – a number of recent papers point to the importance of roots for ecosystem functioning (e.g. Orwin et al. 2010, Grigulis et al. 2013)

A more technical comment relates to the measurement of nitrogen turnover – this was assessed by measuring the uptake of ¹⁵N from Lolium multiflorum litter into aboveground L. multiflorum biomass. So, this measurement might be a proxy for L. multiflorum biomass, which decreases with decreasing soil biodiversity, rather than for nitrogen turnover.

On another note, and I would be very interested in other people’s opinion, I am wondering about the value of using an index for ecosystem multifunctionality. True, this averages across ecosystem functions and can therefore inform management to optimize overall ecosystem functioning. However, are the ecosystems that have the greatest average functioning really the most sustainable, and thus, desirable ecosystems? Are all ecosystem functions equally important? There might be trade-offs between different ecosystem functions – for example between crop yield and nitrogen retention, or between decomposition and carbon sequestration. We might want to optimize a certain function in a certain area, of which we already know that it has potential in delivering a certain function, rather than promoting multifunctionality across the board. For example, peatlands store large amounts of carbon because of their low decomposition rates, and agricultural production systems have high yields but low carbon sequestration.

However, in this paper, the multifunctionality index serves the purpose of summarizing overall ecosystem functioning, which shows a strong and positive relationship with soil biodiversity. Done like this, it summarizes a range of measurements that non-specialists might struggle to interpret – thus, it simplifies and reinforces the message of the paper that soil biodiversity determines ecosystem functioning.

Experiments like this require an enormous amount of work, and you simply can’t include everything. It is incredibly difficult to modify soil biodiversity without simultaneously changing soil properties, and the authors of this paper have achieved this by used an elegant method of reducing soil biodiversity. Thus, in contrast to many earlier studies, they were truly able to mechanistically elucidate the role of groups of soil organisms in ecosystem functioning.

This paper adds to the growing body of literature that soil biodiversity plays a crucial role in ecosystem functioning, and highlights the importance of conserving, and promoting, soil biodiversity. That’s what I like to hear!