Depolymerization of high‐molecular weight organic nitrogen (N) represents the major bottleneck of soil N cycling and yet is poorly understood compared to the subsequent inorganic N processes. Given the importance of organic N cycling and the rise of global change, we investigated the responses of soil protein depolymerization and microbial amino acid consumption to increased temperature, elevated atmospheric CO₂, and drought. The study was conducted in a global change facility in a managed montane grassland in Austria, where elevated CO₂ (eCO₂) and elevated temperature (eT) were stimulated for 4 years, and were combined with a drought event. Gross protein depolymerization and microbial amino acid consumption rates (alongside with gross organic N mineralization and nitrification) were measured using ¹⁵N isotope pool dilution techniques. Whereas eCO₂ showed no individual effect, eT had distinct effects which were modulated by season, with a negative effect of eT on soil organic N process rates in spring, neutral effects in summer, and positive effects in fall. We attribute this to a combination of changes in substrate availability and seasonal temperature changes. Drought led to a doubling of organic N process rates, which returned to rates found under ambient conditions within 3 months after rewetting. Notably, we observed a shift in the control of soil protein depolymerization, from plant substrate controls under continuous environmental change drivers (eT and eCO₂) to controls via microbial turnover and soil organic N availability under the pulse disturbance (drought). To the best of our knowledge, this is the first study which analyzed the individual versus combined effects of multiple global change factors and of seasonality on soil organic N processes and thereby strongly contributes to our understanding of terrestrial N cycling in a future world.

Fixation of atmospheric N₂ by free-living diazotrophs accounts for an important proportion of nitrogen naturally introduced to temperate grasslands. The effect of plants or fertilization on the general microbial community has been extensively studied, yet an understanding of the potential combinatorial effects on the community structure and activity of free-living diazotrophs is lacking. In this study we provide a multilevel assessment of the single and interactive effects of different long-term fertilization treatments, plant species and vicinity to roots on the free-living diazotroph community in relation to the general microbial community in grassland soils. We sequenced the dinitrogenase reductase (nifH) and the 16S rRNA genes of bulk soil and root-associated compartments (rhizosphere soil, rhizoplane and root) of two grass species (Arrhenatherum elatius and Anthoxanthum odoratum) and two herb species (Galium album and Plantago lanceolata) growing in Austrian grassland soils treated with different fertilizers (N, P, NPK) since 1960. Overall, fertilization has the strongest effect on the diazotroph and general microbial community structure, however with vicinity to the root, the plant effect increases. Despite the long-term fertilization, plants strongly influence the diazotroph communities emphasizing the complexity of soil microbial communities’ responses to changing nutrient conditions in temperate grasslands.

Increasing warming, atmospheric CO₂ and drought are expected to change the water dynamics of terrestrial ecosystems. Yet, limited knowledge exists about how the interactive effects of these factors will affect grassland water uptake, and whether adaptations in fine root production and traits will alter water uptake capacity. In a managed C₃ grassland, we tested the individual and combined effects of warming (+3°C), elevated CO₂ (eCO₂; +300 ppm) and drought on root water uptake (RWU) as well as on fine root production, trait adaptation, and fine root‐to‐shoot production ratios, and their relationships with RWU capacity. High temperatures, amplified by warming, exacerbated RWU reductions under drought, with negligible water‐sparing effects from eCO₂. Drought, both under current and future (warming, eCO₂) climatic conditions, shifted RWU towards deeper soil layers. Overall, RWU capacity related positively to fine root production and specific root length (SRL), and negatively to mean root diameters. Warming effects on traits (reduced SRL, increased diameter) and the ratio of fine root‐to‐shoot production (increased) were offset by eCO₂. We conclude that under warmer future conditions, irrespective of shifts in water sourcing, it is particularly hot droughts that will lead to increasingly severe restrictions of grassland water dynamics.

Grassland vegetation typically comprises the species groups grasses, herbs, and legumes. These species groups provide different functional traits and feed values. Therefore, knowledge of the botanical composition of grasslands can enable improved site-specific management and livestock feeding. A systematic approach was developed to analyze vegetation of managed permanent grassland using hyperspectral imaging in a laboratory setting. In the first step, hyperspectral images of typical grassland plants were recorded, annotated, and classified according to species group and plant parts, that is, flowers, leaves, and stems. In the second step, three different machine learning model types—multilayer perceptron (MLP), random forest (RF), and partial least squares discriminant analysis (PLS-DA)—were trained with pixel-wise spectral information to discriminate different species groups and plant parts in individual models. The influence of radiometric data calibration and specific data preprocessing steps on the overall model performance was also investigated. While the influence of proper radiometric calibration was negligible in our setting, specific preprocessing variants, including smoothening and derivation of the spectrum, were found to be beneficial for classification accuracy. Compared to extensively preprocessed data, raw spectral data yielded no statistically decreased performance in most cases. Overall, the MLP models outperformed the PLS-DA and RF models and reached cross-validation accuracies of 96.8% for species group and 88.6% for plant part classification. The obtained insights provide an essential basis for future data acquisition and data analysis of grassland vegetation.

In this eight-year grassland field trial, we compared the fertilization effects of biomass ashes (BMAs) and carbonated lime (CaCO₃) in combined application with cattle slurry (CS). Our study focused on plant coverage, forage yield, and quality, as well as soil physicochemical and microbiological properties. The fertilization strategies included CS mixed with BMA or CaCO₃ applied three times a year and a separate annual application of ash or CaCO₃, independent of CS. Samplings were performed in 2010, 2014, and 2018. Despite an absence of observable effects on soil, microbial properties, and forage quality, CS application, with or without BMA/CaCO₃, resulted in higher forage yields compared to the unfertilized control and plots receiving only ash or CaCO₃. Forage properties remained consistent across treatments. However, the combined application of CS with both ash and CaCO₃ led to a reduction in volatile organic compounds, total carbon, total nitrogen, nitrate, and electrical conductivity in the soil from 2010 to 2018. Additionally, the relative abundance of specific microbial families (Nitrosomonadaceae, Acidothermaceae, Bacillaceae, and Peptostreptococcaceae) varied based on whether soils received a single amendment or a combination thereof. Our findings suggest that BMA is a valuable substitute for traditional liming agents, regardless of the application mode.