Portal de Periódicos da CAPES

Peeking into the black box: a trait‐based approach to predicting plant–soil feedback

2015; Wiley; Volume: 206; Issue: 1 Linguagem: Inglês

10.1111/nph.13283

1469-8137

Paul Kardol, G. F. Veen, François P. Teste, Michael P. Perring,

Peatlands and Wetlands Ecology

‘Belowground biotic interactions are poorly studied, yet they are key to driving plant–soil feedbacks.’ Trait variation among plant species is increasingly being used to predict effects of plant species and communities on ecosystem functioning, but plant traits have not yet been integrated in PSF studies. Differences in plant functional traits drive litter decomposability, which in turn can have strong legacy effects on soil nutrient availability (Cornwell et al., 2008). For example, high %N litter generally decomposes faster than low %N litter. In addition, plants may develop a specialized, ‘species-specific’ decomposer community, which could lead to accelerated decomposition in the vicinity of the plant where the litter originates from, so-called ‘home-field advantage’ (Veen et al., 2015). Any such plant-induced shifts in soil nutrient availability may in turn feed back to plant performance, directly, or indirectly as mediated by root-associated organisms (Manning et al., 2008) (Fig. 1). Here, Ke et al. are the first to show that shifts in soil N availability resulting from variation in litter decomposability can determine the strength of PSF in mycorrhizal-dominated communities but not in those communities dominated by soil pathogens. These results contribute greatly to better understanding when species-specific interactions between plants and decomposer communities may affect PSF by showing that litter decomposability drive PSFs under certain conditions only. Mycorrhizal fungi increase in abundance in response to enhanced N availability released from easily-decomposable litter, which allows plants to further deplete soil N pools. However, Ke et al. showed that the strength of this feedback strongly depended on the physiological traits of the mycorrhizas. For example, high mycorrhizal N uptake coefficients and carbon (C) : N ratios may limit N supply to the plant if the mycorrhizal fungi are themselves limited by N; this would result in immobilization of N by the fungi with little transfer to the plant. As such, the role of mycorrhizal symbioses in N-driven feedback loops would not only depend on the N status of the soil, but also on the interplay between the trait values of both partners (Fig. 1). Yet, positive effects of enhanced N availability on plant growth would trade-off against accumulation of root pathogens (higher value for root quality traits, and high host densities) leading to no net plant growth response. Instead, in pathogen-dominated soils the strength of feedback would be largely driven by plant defense traits and seedling growth rates and thus not litter decomposability. These findings elegantly illustrate the implications of the interplay between soil microbial traits (Orwin et al., 2011; Krause et al., 2014) and plant root traits (Bardgett et al., 2014) in plant population and community dynamics. Ke et al. first considered root pathogens and mycorrhizal fungi as two extremes (negative and positive) of direct plant–microbe interactions, presumably a simplification that was imposed as a ‘first step’ in successful simulation of PSF strength; simplification allows mechanistic understanding. To inform on the importance of interactions among soil organisms (Fig. 1), they then simulated systems with both groups of organisms present, and considered gradients in the effect of pathogens or mycorrhizas on each other. For instance, pathogens and mycorrhizas could interact symmetrically following competition theory. Otherwise, mycorrhizal fungi could inhibit pathogens through the production of antimicrobial metabolites. By simulating the case of increased litter decomposability, Ke et al. showed that PSF remained positive when mycorrhizal fungi were better competitors or effectively inhibited pathogens. Negative PSF was rarely observed whatever the relative competitive abilities in this increased litter decomposability case, confirming the result that when pathogen communities dominated, litter decomposability was unimportant in determining feedback strength. Here, we note that Ke et al. included only a small subset of the potential interactions among soil organisms that can potentially affect the strength of PSF (e.g. Wardle, 2006), and did not account for changes in decomposer community composition in response to litter quality. Generally, easily degradable litter would be associated with a ‘fast’ bacterial-dominated community while recalcitrant litter would be associated with a ‘slow’ fungal-dominated community (Wardle et al., 2004). Remaining challenges include empirical integration and model development between the complementary research fields of trait-based ecology and PSF. A promising avenue to better predict variation in PSF strength could involve considering within-group trait shifts and modeling the diversity of physiological traits of dominant soil organisms coupled with model plant species (Fig. 2). Understanding how Ke et al.'s findings are affected by different nutrient supply pathways (e.g. supply of phosphorus (P) through root exudates and inorganic unavailable pathways (Perring et al., 2008)), feedback across plant nutrient-acquisition strategies (F. P. Teste et al., unpublished; Fig. 2) and other microbial interactions (e.g. when mycorrhizas become parasitic rather than mutualistic) would also be useful. Subsequent studies could also address strength of PSF and interactions with soil communities under P-limiting conditions and co-limiting N and P conditions while varying the proportion of arbuscular and ectomycorrhizal fungi. Acknowledging the physiological diversity and consequent trait variation of root symbioses will likely be important in interpreting the outcomes of future integrative PSF experiments. In particular, when plant species show large positive feedback, research efforts could focus on whether plants connected to each other by mycorrhizal networks (Simard et al., 2012) regulate feedback strength. Including ‘connectivity’ traits such as the capacity to form and benefit from mycorrhizal networks may increase our understanding of the far-reaching influence of mycorrhizas in acquisition and relocation of nutrients, ultimately determining PSF strength. Recent mycorrhizal network studies have shown favorable allocation of resources (i.e. N and P) by mycorrhizal fungi to plants that supply more C; this mirrors economic theory that considers mycorrhizal fungi as ‘biological markets’ (Fellbaum et al., 2014). The role of mycorrhizal networks in PSF studies offers another mechanism to explain how the strength of the positive feedback is reinforced with greater mycorrhizal abundance. Ke et al. provided an impressive model that coupled litter and microbial-mediated PSFs in an elegant and detailed way that allowed prediction of the strength and direction of PSFs. The important contribution made by Ke et al. mainly resides in how we can now decipher the interactive effects that result from the processes traditionally well-hidden in the ‘black box’ (Cortois & De Deyn, 2012). This modeling effort, and that of future studies combining trait-based experimental and observational investigations, will give us a better understanding of the context-dependency of negative and positive feedbacks and highlight which parts of the soil communities are promoting feedback. Recent developments in understanding the role of microbial (Krause et al., 2014) and root traits (Bardgett et al., 2014) in driving ecosystem processes have paved the way for further unraveling the complexity of PSFs. Importantly, this research may have far-reaching implications, since context-dependency may be particularly key for agricultural systems as we try to reduce the environmental impact of agricultural practices and use limited resources more efficiently; for example, by promoting mycorrhizal communities rather than pathogenic communities to enable positive PSF for pasture or crop species, as well as potentially increasing soil C storage. Restoration and conservation efforts may also benefit through trait-based approaches and a consideration of PSFs (Kardol & Wardle, 2010). Ultimately, trait-based approaches can be used to predict how plant and soil communities, and hence, their impact on ecosystem functioning, respond to disturbances and environmental changes. Finally, fundamentally, trait-based modeling approaches not only improve our mechanistic understanding of the fascinating and complex nature of plant–soil relationships, they are shedding some much-needed light in the ‘black box’.