Plant-enzyme interactions along gradients of resource stoichiometry (PEGasuS)

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Identifying stoichiometric niches for multiple macro and micro nutrients is increasingly considered as a promising tool to understand and predict plant performance under different environmental conditions. There is a strong basis that the stoichiometries of plants, soils, soil microbes and ecoenzymes active in different element cycles are coupled. The rhizosphere is a hotspot of such interactions. Connecting concepts of stoichiometry with morphological traits in real-world grasslands (above- and belowground) is still in its infancy. PEGasuS targets at disentangling these interactions for 13 grassland plant species, characterized by different niche optima along the gradient of land-use intensity (LUI) as well as by different above- and belowground functional traits, and their rhizosphere ecoenzyme kinetics to assess the consequences of these interactions for plant versus rhizosphere microbial nutrition (C:N:P:S and further bioelements: Mg, Ca, K, Cu, Mn, Zn, Fe). The factors driving five coupled stoichiometric niche volumes (leaves, roots, rhizosphere soil solution, microbial biomass and ecoenzyme kinetics) will be identified by combining mixed model and information theoretic approaches. Despite their sensitivity, enzymatic substrate affinities or catalytic efficiencies are not yet used to unravel stoichiometric relationships in plant-soil interactions. We will detect enzyme reactions by an extended Michaelis-Menten approach using non-linear mixed effect models. The outcome will improve the mechanistic understanding on how the degree of stoichiometric homeostasis may constrain the species’ distribution and their competitive abilities in real-world grasslands with different LUI and how plant-enzyme stoichiometric feedbacks recover after LUI reduction compared to established reference plots with low LUI and/or LUI components over the last >10 years. At 60 grassland EPs (45 EPs of the joint multi-site experiment REX plus 15 low LUI EPs) and 45 reduced LUI plots (RPs), we will identify species-specific stoichiometric regulation strategies (all three exploratories). Biodiversity Exploratories data characterizing the “plant community environment” together with our project data characterizing the “target plant species environment” enable the identification of mechanisms driving plant-enzyme feedbacks along gradients of LUI and their response to three years of LUI reduction. In this way, we will disentangle the effects of plant taxonomic and functional diversity at plot and individuum level as well as of LUI-induced resource gradients on the plant-enzyme interaction in a multielement stoichiometric framework. This knowledge is expected to generate substantial added value to the framework of the Biodiversity Exploratories and will contribute to a better mechanistic understanding of the effects of LUI and LUI reduction on ecosystem functioning (carbon and nutrient turnover) as well as related production services (fodder quality and quantity).