Root traits and soil micro‐organisms as drivers of plant–soil feedbacks within the sub‐arctic tundra meadow

Spitzer, Clydecia M.; Wardle, David A.; Lindahl, Björn D.; Sundqvist, Maja K.; Gundale, Michael J.; Fanin, Nicolas; Kardol, Paul

doi:10.1111/1365-2745.13814

Cited by 11 publications

(7 citation statements)

References 67 publications

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“…For example, functional traits from the leaf economics spectrum (LES), and the related fast-slow strategies have been proven helpful in predicting PSFs (Baxendale et al 2014;Cortois et al 2016;Teste et al 2017;Png et al 2019). Focal plant species with fast life histories traits, indicated by high specific leaf area (SLA), N content and specific root length (SRL), suffered most from negative feedbacks (PSF home/away ), whereas species with more conservative traits, such as high dry matter content or average root diameter, showed more neutral or positive feedbacks (Cortois et al 2016;Spitzer et al 2022). So far, most studies use the functional traits of the focal plant species to predict the outcome of PSFs, but in theory, similarity in functional traits could be used in a similar way to phylogenetic similarity to predict the outcome of PSFs between plant species.…”

Section: Predictors Of Plant Soil Feedbacksmentioning

confidence: 99%

Using root economics traits to predict biotic plant soil-feedbacks

Rutten

Allan

2023

Plant Soil

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Plant-soil feedbacks have been recognised as playing a key role in a range of ecological processes, including succession, invasion, species coexistence and population dynamics. However, there is substantial variation between species in the strength of plant-soil feedbacks and predicting this variation remains challenging. Here, we propose an original concept to predict the outcome of plant-soil feedbacks. We hypothesize that plants with different combinations of root traits culture different proportions of pathogens and mutualists in their soils and that this contributes to differences in performance between home soils (cultured by conspecifics) versus away soils (cultured by heterospecifics). We use the recently described root economics space, which identifies two gradients in root traits. A conservation gradient distinguishes fast vs. slow species, and from growth defence theory we predict that these species culture different amounts of pathogens in their soils. A collaboration gradient distinguishes species that associate with mycorrhizae to outsource soil nutrient acquisition vs. those which use a “do it yourself” strategy and capture nutrients without relying strongly on mycorrhizae. We provide a framework, which predicts that the strength and direction of the biotic feedback between a pair of species is determined by the dissimilarity between them along each axis of the root economics space. We then use data from two case studies to show how to apply the framework, by analysing the response of plant-soil feedbacks to measures of distance and position along each axis and find some support for our predictions. Finally, we highlight further areas where our framework could be developed and propose study designs that would help to fill current research gaps.

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Section: Predictors Of Plant Soil Feedbacksmentioning

confidence: 99%

Using root economics traits to predict biotic plant soil-feedbacks

Rutten

Allan

2023

Plant Soil

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“…root mass per unit root volume). species, do-it-yourself roots have a higher concentration of chemicals involved in tissue construction and protection than outsourcing species (Spitzer et al, 2021(Spitzer et al, , 2022Xia et al, 2021).…”

Section: Forummentioning

confidence: 99%

“…Leaf and root traits have been used successfully to predict interspecific differences in soil microbial community composition (de Vries et al ., 2012; Semchenko et al ., 2018; Spitzer et al ., 2021), as well as litter decomposability and rhizodeposition and their effects on soil carbon and nitrogen cycling (Freschet et al ., 2012, 2013; Henneron et al ., 2020a,b; Williams et al ., 2022). With regard to PSF, the focus has been on developing functional trait‐based frameworks to predict plant responses to soil microbial communities, including specialist and generalist pathogens, mutualists and decomposers (Baxendale et al ., 2014; Kardol et al ., 2015; Cortois et al ., 2016; De Long et al ., 2019; Heinen et al ., 2020a; Semchenko et al ., 2022; Spitzer et al ., 2022). Phylogenetic relatedness has also been proposed as a predictor of PSF since weaker PSF is expected among closely related species if they accumulate similar biota in their rhizosphere.…”

Section: Predicting Plant–soil Interactions Using Functional Traitsmentioning

confidence: 99%

“…The potential for PSF to modulate species coexistence via species‐specific microbial legacies is further predicted to depend on the distance between co‐occurring species in functional trait space, with stronger feedbacks occurring among species with more contrasting trait values (Semchenko et al ., 2022; Rutten & Allan, 2023). These predictions are generally supported by several empirical studies (Lemmermeyer et al ., 2015; Fitzpatrick et al ., 2017; Kulmatiski et al ., 2017; Lekberg et al ., 2018; Xi et al ., 2021), although the strength of trait–PSF relationships varies between studies (Bukowski et al ., 2018; Heinen et al ., 2018) and evidence for root economic traits remains limited (Cortois et al ., 2016; Semchenko et al ., 2018; Spitzer et al ., 2022).…”

Section: Predicting Plant–soil Interactions Using Functional Traitsmentioning

confidence: 99%

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A trait‐based framework linking the soil metabolome to plant–soil feedbacks

Delory,

Callaway,

Semchenko

2023

New Phytologist

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SummaryBy modifying the biotic and abiotic properties of the soil, plants create soil legacies that can affect vegetation dynamics through plant–soil feedbacks (PSF). PSF are generally attributed to reciprocal effects of plants and soil biota, but these interactions can also drive changes in the identity, diversity and abundance of soil metabolites, leading to more or less persistent soil chemical legacies whose role in mediating PSF has rarely been considered. These chemical legacies may interact with microbial or nutrient legacies to affect species coexistence. Given the ecological importance of chemical interactions between plants and other organisms, a better understanding of soil chemical legacies is needed in community ecology. In this Viewpoint, we aim to: highlight the importance of belowground chemical interactions for PSF; define and integrate soil chemical legacies into PSF research by clarifying how the soil metabolome can contribute to PSF; discuss how functional traits can help predict these plant–soil interactions; propose an experimental approach to quantify plant responses to the soil solution metabolome; and describe a testable framework relying on root economics and seed dispersal traits to predict how plant species affect the soil metabolome and how they could respond to soil chemical legacies.

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“…While PSFs can be generated by a range of abiotic and biotic factors, soil microbial pathogens and mutualists have been identified as key putative drivers of PSFs (Smith‐Ramesh & Reynolds, 2017; Bennett & Klironomos, 2019; De Long et al ., 2019), although very few studies have truly related PSFs to microbial taxa (but see Packer & Clay, 2000; Esch et al ., 2021; Spitzer et al ., 2022). The tendency of plant hosts to accumulate a high diversity of arbuscular mycorrhizal fungi (AMF) in their rhizosphere and high rates of root colonization by AMF have been identified as primary predictors of more positive or less negative PSFs (Cortois et al ., 2016; Semchenko et al ., 2018; Liang et al ., 2020).…”

Section: Introductionmentioning

confidence: 99%

Light availability and plant shade tolerance modify plant–microbial interactions and feedbacks in subtropical trees

McCarthy-Neumann

Feng

et al. 2023

New Phytologist

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Summary Plant–soil feedbacks (PSFs) are an important mechanism of species coexistence in forest communities. However, evidence remains limited for how light availability regulates PSFs in species with different shade tolerance via changes in plant–microbial interactions. Here we tested in a glasshouse experiment how PSFs changed as a function of light availability and tree shade tolerance. Soil bacterial and fungal communities were profiled using the 16S rRNA and ITS2 gene sequencing, respectively. Under low light, individual PSFs were positively related to shade tolerance, while the least shade‐tolerant species produced the most positive PSFs under high light. Pairwise PSFs between species with contrasting shade tolerance were strongly positive under high light but negative under low light, thereby promoting the dominance of less shade‐tolerant species in forest gaps and species coexistence under closed canopy, respectively. Under high light, PSFs were related to soil microbial composition and diversity, with the relative abundance of arbuscular mycorrhizal fungi being the primary driver of PSFs. Under low light, none of soil microbial properties were significantly related to PSFs. These findings indicate PSFs and plant shade tolerance interact to promote species coexistence and improve our understanding of how soil microbes contribute to variation in PSFs.

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Root traits and soil micro‐organisms as drivers of plant–soil feedbacks within the sub‐arctic tundra meadow

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri bution-NonCo mmercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Cited by 11 publications

References 67 publications

Using root economics traits to predict biotic plant soil-feedbacks

Using root economics traits to predict biotic plant soil-feedbacks

A trait‐based framework linking the soil metabolome to plant–soil feedbacks

Light availability and plant shade tolerance modify plant–microbial interactions and feedbacks in subtropical trees

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