Published in

Springer, Plant and Soil, 2023

DOI: 10.1007/s11104-023-05948-1

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Using root economics traits to predict biotic plant soil-feedbacks

Journal article published in 2023 by Gemma Rutten ORCID, Eric Allan ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

AbstractPlant-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.