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Ecology
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Ecology
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Using plant‐soil feedbacks to predict plant biomass in diverse communities

Authors: Kulmatiski, Andrew; Beard, Karen H.; Grenzer, Josephine; Forero, Leslie E.; Heavilin, Justin;

Using plant‐soil feedbacks to predict plant biomass in diverse communities

Abstract

AbstractIt has become clear that plants can create soils that affect subsequent plant growth. However, because plant‐soil feedbacks (PSFs) are typically measured in monoculture experiments, it remains unclear to what extent PSFs affect plant growth in communities. Here we used data from a factorial PSF experiment to predict the biomass of 12 species grown in 162 plant community combinations. Five different plant growth models were parameterized with either monoculture biomass data (Null) or with PSF data (PSF) and model predictions were compared to plant growth observed in communities. For each of the five models, PSF model predictions were closer to observed species biomass in communities than Null model predictions. PSFs, which were associated with a 28% difference in plant biomass across soil types, explained 10% more variance than Null models. Results provided strong support for a small role for PSFs in predicting plant growth in communities and suggest several reasons that PSFs, as traditionally measured in monoculture experiments, may overestimate PSF effects in communities. First, monoculture data used in Null models inherently includes “self ” PSF effects. Second, PSFs must be large relative to differences in intrinsic growth rates among species to change competitive outcomes. Third, PSFs must vary among species to change species relative abundances.

Country
United States
Related Organizations
Keywords

580, model, symbiant, Ecology and Evolutionary Biology, coexistence, Life Sciences, Plant Development, prediction, Biodiversity, Plants, facilitation, soil, symbiont, coexistence; community assembly; competition; facilitation; model; pathogen; prediction; soil; symbiont, Soil, community assembly, Biomass, competition, Plant Physiological Phenomena, pathogen

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    23
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Average
Top 10%
Green
hybrid
Related to Research communities
Energy Research