Plants exude a diverse cocktail of metabolites into the soil as response to exogenous and endogenous factors. So far, root exudates have mainly been studied under artificial conditions due to methodological difficulties. In this study, each five perennial grass and forb species were investigated for polar and semi-polar metabolites in exudates under field conditions. Metabolite collection and untargeted profiling approaches combined with a novel classification method allowed the designation of 182 metabolites. The composition of exuded polar metabolites depended mainly on the local environment, especially soil conditions, whereas the pattern of semi-polar metabolites was primarily affected by the species identity. The profiles of both polar and semi-polar metabolites differed between growth forms, with grass species being generally more similar to each other and more responsive to the abiotic environment than forb species. This study demonstrated the feasibility of investigating exudates under field conditions and to identify the driving factors of exudate composition.

The active bacterial rhizobiomes and root exudate profiles of phytometers of six plant species growing in central European temperate grassland communities were investigated in three regions located up to 700 km apart, across diverse edaphic conditions and along a strong land use gradient. The recruitment process from bulk soil communities was identified as the major direct driver of the composition of active rhizosphere bacterial communities. Unexpectedly, the effect of soil properties, particularly soil texture, water content, and soil type, strongly dominated over plant properties and the composition of polar root exudates of the primary metabolism. While plant species-specific selection of bacteria was minor, the RNA-based composition of active rhizosphere bacteria substantially differed between rhizosphere and bulk soil. Although other variables could additionally be responsible for the consistent enrichment of particular bacteria in the rhizosphere, distinct bacterial OTUs were linked to the presence of specific polar root exudates independent of individual plant species. Our study also identified numerous previously unknown taxa that are correlated with rhizosphere dynamics and hence represent suitable targets for future manipulations of the plant rhizobiome.

0

In the rhizosphere, plants are exposed to a multitude of different biotic and abiotic factors, to which they respond by exuding a wide range of secondary root metabolites. So far, it has been unknown to which degree root exudate composition is species‐specific and is affected by land use, the local impact and local neighborhood under field conditions. In this study, root exudates of 10 common grassland species were analyzed, each five of forbs and grasses, in the German Biodiversity Exploratories using a combined phytometer and untargeted liquid chromatography‐mass spectrometry (LC‐MS) approach. Redundancy analysis and hierarchical clustering revealed a large set of semi‐polar metabolites common to all species in addition to species‐specific metabolites. Chemical richness and exudate composition revealed that forbs, such as Plantago lanceolata and Galium species, exuded more species‐specific metabolites than grasses. Grasses instead were primarily affected by environmental conditions. In both forbs and grasses, plant functional traits had only a minor impact on plant root exudation patterns. Overall, our results demonstrate the feasibility of obtaining and untargeted profiling of semi‐polar metabolites under field condition and allow a deeper view in the exudation of plants in a natural grassland community.

The relatively new research discipline of Eco-Metabolomics is the application of metabolomics techniques to ecology with the aim to characterise biochemical interactions of organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical approach to measure many thousands of metabolites in different species, including plants and animals. Changes in metabolite concentrations can provide mechanistic evidence for biochemical processes that are relevant at ecological scales. These include physiological, phenotypic and morphological responses of plants and communities to environmental changes and also interactions with other organisms. Traditionally, research in biochemistry and ecology comes from two different directions and is performed at distinct spatiotemporal scales. Biochemical studies most often focus on intrinsic processes in individuals at physiological and cellular scales. Generally, they take a bottom-up approach scaling up cellular processes from spatiotemporally fine to coarser scales. Ecological studies usually focus on extrinsic processes acting upon organisms at population and community scales and typically study top-down and bottom-up processes in combination. Eco-Metabolomics is a transdisciplinary research discipline that links biochemistry and ecology and connects the distinct spatiotemporal scales. In this review, we focus on approaches to study chemical and biochemical interactions of plants at various ecological levels, mainly plant–organismal interactions, and discuss related examples from other domains. We present recent developments and highlight advancements in Eco-Metabolomics over the last decade from various angles. We further address the five key challenges: (1) complex experimental designs and large variation of metabolite profiles; (2) feature extraction; (3) metabolite identification; (4) statistical analyses; and (5) bioinformatics software tools and workflows. The presented solutions to these challenges will advance connecting the distinct spatiotemporal scales and bridging biochemistry and ecology

Primary and secondary metabolites exuded by plant roots have mainly been studied under laboratory conditions, while knowledge of root exudate patterns of plants growing in natural communities is very limited. Focusing on ten common European grassland plant species, we asked to which degree exuded metabolite compositions are specific to species or growth forms (forbs and grasses), depend on environments and local neighbourhoods, and reflect traditional plant functional traits. Root exudates were collected under field conditions and analysed using a non-targeted gas chromatography coupled mass spectrometry (GC-MS) approach. In total, we annotated 153 compounds of which 36 were identified by structure and name as metabolites mainly derived from the primary metabolism. Here we show by using variance partitioning, that the composition of exuded polar metabolites was mostly explained by plot identity, followed by plant species identity while plant species composition of the local neighbourhood played no role. Total and root dry biomass explained the largest proportion of variance in exudate composition, with additional variance explained by traditional plant traits. Although the exudate composition was quite similar between the two growth forms, we found some metabolites that occurred only in one of the two growth forms. Our study demonstrated the feasibility of measuring polar exudates under non-sterile field conditions by mass spectrometry, which opens new avenues of research for functional plant ecology.

There is growing interest in the application of plant functional trait-based approaches for development of sustainable land-use strategies. In this context, one crucial task is to identify and measure plant traits, which respond to land-use intensity (response traits) and simultaneously have an impact on ecosystem functions (effect traits). We hypothesized that species-specific leaf chemical composition, which may function both as response and effect trait, can be derived from Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectroscopy tools in combination with multivariate statistical methods We investigated leaf ATR-FTIR spectra of two grasses, Poa pratensis L. and Dactylis glomerata L., and one forb, Achillea millefolium L. collected in grassland plots along a land-use intensity gradient in three regions of Germany. ATR-FTIR spectra appear to function as biochemical fingerprints unique to each species. The spectral response to land-use intensity was not consistent among species and less apparent in the two grasses than in the forb species. Whereas land-use intensification enhanced protein and cellulose content in A. millefolium, giving rise to changes in six spectral bands in the frequency range of 1088–1699 cm−1, only cellulose content increased in D. glomerata, affecting the bands of 1385–1394 cm−1. Poa pratensis spectra exhibited minimal changes under the influence of land-use, only in the spectral bands of 1373–1375 cm−1 associated with suberin-like aliphatic compounds. Our findings suggest that some species’ leaf chemical composition is responsive to land-use intensity, and thus, may have a predictive value for ecosystem services provided by those species within grassland vegetation (i.e., herbage yield quality).

Plant functional traits are widely used to predict community productivity. However, they are rarely used to predict individual plant performance in grasslands. To assess the relative importance of traits compared to environment, we planted seedlings of 20 common grassland species as phytometers into existing grassland communities varying in land‐use intensity. After 1 year, we dug out the plants and assessed root, leaf, and aboveground biomass, to measure plant performance. Furthermore, we determined the functional traits of the phytometers and of all plants growing in their local neighborhood. Neighborhood impacts were analyzed by calculating community‐weighted means (CWM) and functional diversity (FD) of every measured trait. We used model selection to identify the most important predictors of individual plant performance, which included phytometer traits, environmental conditions (climate, soil conditions, and land‐use intensity), as well as CWM and FD of the local neighborhood. Using variance partitioning, we found that most variation in individual plant performance was explained by the traits of the individual phytometer plant, ranging between 19.30% and 44.73% for leaf and aboveground dry mass, respectively. Similarly, in a linear mixed effects model across all species, performance was best predicted by phytometer traits. Among all environmental variables, only including land‐use intensity improved model quality. The models were also improved by functional characteristics of the local neighborhood, such as CWM of leaf dry matter content, root calcium concentration, and root mass per volume as well as FD of leaf potassium and root magnesium concentration and shoot dry matter content. However, their relative effect sizes were much lower than those of the phytometer traits. Our study clearly showed that under realistic field conditions, the performance of an individual plant can be predicted satisfyingly by its functional traits, presumably because traits also capture most of environmental and neighborhood conditions.

QuestionsTo what extent is trait variation in grasses and forbs driven by land‐use intensity, climate, soil conditions and plant diversity of the local neighbourhood? Do grass and forb species differ in the degree of intraspecific trait variation?LocationManaged grasslands in three regions of Germany.MethodsUsing a phytometer approach, we raised 20 common European grassland species (ten forbs and ten grasses) and planted them into 54 plots of different land‐use types (pasture, meadow, mown pasture). After 1 yr in the field, we measured above‐ and below‐ground plant functional traits. Linear mixed effects models (LMEM) were used to identify the most powerful predictors for every trait. Variation partitioning was applied to assess the amount of inter‐ and intraspecific trait variation in grasses and forbs explained by environmental conditions (land‐use intensity, climate and soil conditions) and plant species diversity of the local neighbourhood.ResultsFor 12 out of the 14 traits studied, either land‐use intensity or local neighbourhood diversity were predictors in the best LMEM. Land‐use intensity had considerably stronger effects than neighbourhood diversity. Root dry matter content and root phosphorus concentration of forbs were more affected by land‐use intensity than those of grasses. For almost all traits, intraspecific trait variation of grasses was much higher than that of forbs, while traits of forbs varied more among species. Overall, inter‐ and intraspecific variation was of the same magnitude.ConclusionThe similar magnitude of intra‐ and interspecific trait variation suggests that both sources should be considered in grassland studies at a scale similar to that of our study. The high amount of intraspecific trait variation that was explained by environmental factors and local neighbourhood diversity clearly demonstrates the high potential of species to adjust to local conditions, which would be ignored when only considering species mean trait values.