Marika Truu’s research while affiliated with University of Tartu and other places

Background and aims: Response of subarctic grassland's belowground to soil warming is key for understanding ecosystem's adaptation to future climate. Functionally different belowground plant organs can respond differently to changes in soil temperature (Ts). We aimed to understand the belowground adaptation mechanisms by analyzing the dynamics and chemistry of fine roots and rhizomes in relation to plant community composition and soil chemistry, along with the duration and magnitude of soil warming. Methods: We investigated the effects of duration (medium-term warming (MTW; 11 yr) and long-term warming (LTW; >60 yr) and magnitude (0-8.4 °C) of soil warming on the belowground plant biomass (BPB), fine root biomass (FRB) and rhizome biomass (RHB) in geothermally warmed subarctic grasslands. We evaluated the changes in BPB, FRB, and RHB and the corresponding carbon (C) and nitrogen (N) pools in the context of ambient, Ts < +2 °C and Ts > +2 °C scenarios. Key results: BPB decreased exponentially in response to an increase in Ts under MTW, whereas FRB declined under both MTW and LTW. The proportion of rhizomes increased and the C-N ratio in rhizomes decreased under LTW. The C and N pools in BPB in highly warmed plots under MTW were 50% less than in the ambient, whereas under LTW, C and N pools in warmed plots were similar to that in non-warmed plots. Approximately 78% of the variation in FRB, RHB and C and N concentration and pools in fine roots and rhizomes was explained by the duration and magnitude of soil warming, soil chemistry, plant community functional composition, and aboveground biomass. Plant's belowground biomass, chemistry and pools were related to a shift in the grassland's plant community composition- the abundance of ferns increased and BPB decreased towards higher Ts under MTW, while the recovery of belowground C and N pools under LTW was related to higher plant diversity. Conclusion: Our results indicate that plant community-level adaptation of belowground to soil warming occurs over long periods. We provide insight into the potential adaptation phases of subarctic grasslands.

Engineered nanoparticles, including silver nanoparticles (AgNPs), are released into the environment mainly through wastewater treatment systems. Knowledge of the impact of AgNPs on the abundance and removal efficiency of antibiotic resistance genes (ARGs) in wastewater treatment facilities, including constructed wetlands (CWs), is essential in the context of public health. This study evaluated the effect of increased (100-fold) collargol (protein-coated AgNPs) and ionic Ag+ in municipal wastewater on the structure, abundance, and removal efficiency of the antibiotic resistome, integron-integrase genes, and pathogens in a hybrid CW using quantitative PCR and metagenomic approaches. The abundance of ARGs in wastewater and the removal efficiency of ARGs in the hybrid system were significantly affected by higher Ag concentrations, especially with collargol treatment, resulting in an elevated ARG discharge of system effluent into the environment. The accumulated Ag in the filters had a more profound effect on the absolute and relative abundance of ARGs in the treated water than the Ag content in the water. This study recorded significantly enhanced relative abundance values for tetracycline (tetA, tetC, tetQ), sulfonamide (sul1, sul2), and aminoglycoside (aadA) resistance genes, which are frequently found on mobile genetic elements in collargol- and, to a lesser extent, AgNO3-treated subsystems. Elevated plasmid and integron-integrase gene levels, especially intI1, in response to collargol presence indicated the substantial role of AgNPs in promoting horizontal gene transfer in the treatment system. The pathogenic segment of the prokaryotic community was similar to a typical sewage community, and strong correlations between pathogen and ARG proportions were recorded in vertical subsurface flow filters. Furthermore, the proportion of Salmonella enterica was positively related to the Ag content in these filter effluents. The effect of AgNPs on the nature and characteristics of prominent resistance genes carried by mobile genetic elements in CWs requires further investigation.

Methane (CH4) emissions generated from waste management facilities represent a serious global warming concern. The objective of this study was to monitor a fully instrumented biocover capable of abating fugitive CH4 emissions from a closed landfill located at Kudjape, Saaremaa Island, Estonia. This investigation documented the alteration in the emission of CH4, carbon dioxide, and temperature fluctuation for a monitoring period of 10 years after the implementation of biocover. The fine fraction reclaimed from landfill mining along with natural mineral soil and sewage sludge compost in a proportion of 3:1:1 was used as a biocover substrate. CH4 emissions were monitored at the surface and from three locations at a regular depth of 25 cm up to 2 m inside the biocover layer. The measurements recorded from three gas monitoring wells present different scenarios of a typical landfill due to the heterogenous nature of waste and non-homogeneous distribution of landfill gas load to the methaneoxidation layer, namely, a) desired situation where a permanent reduction in CH4 concentration took place over time; b) hot-spot with an extremely high concentration of CH4 albeit consistent decrease over the years; c) a location with minimal initial concentration of CH4. Multivariate analysis showed that the CH4 concentration dynamics and parameters reflecting the CH4 oxidation process activity were different in biocover across the landfill. Based on data analysis results, the CH4 oxidation process stabilizes in biocover in 5–6 years after establishing the cover.

Agricultural application of plant-beneficial bacteria to improve crop yield and alleviate the stress caused by environmental conditions, pests, and pathogens is gaining popularity. However, before using these bacterial strains in plant experiments, their environmental stress responses and plant health improvement potential should be examined. In this study, we explored the applicability of three unsupervised machine learning-based data integration methods, including principal component analysis (PCA) of concatenated data, multiple co-inertia analysis (MCIA), and multiple kernel learning (MKL), to select osmotic stress-tolerant plant growth-promoting (PGP) bacterial strains isolated from the rice phyllosphere. The studied datasets consisted of direct and indirect PGP activity measurements and osmotic stress responses of eight bacterial strains previously isolated from the phyllosphere of drought-tolerant rice cultivar. The production of phytohormones, such as indole-acetic acid (IAA), gibberellic acid (GA), abscisic acid (ABA), and cytokinin, were used as direct PGP traits, whereas the production of hydrogen cyanide and siderophore and antagonistic activity against the foliar pathogens Pyricularia oryzae and Helminthosporium oryzae were evaluated as measures of indirect PGP activity. The strains were subjected to a range of osmotic stress levels by adding PEG 6000 (0, 11, 21, and 32.6%) to their growth medium. The results of the osmotic stress response experiments showed that all bacterial strains accumulated endogenous proline and glycine betaine (GB) and exhibited an increase in growth, when osmotic stress levels were increased to a specific degree, while the production of IAA and GA considerably decreased. The three applied data integration methods did not provide a similar grouping of the strains. Especially deviant was the ordination of microbial strains based on the PCA of concatenated data. However, all three data integration methods indicated that the strains Bacillus altitudinis PB46 and B. megaterium PB50 shared high similarity in PGP traits and osmotic stress response. Overall, our results indicate that data integration methods complement the single-table data analysis approach and improve the selection process for PGP microbial strains.

Silver nanoparticles (AgNPs) threaten human and ecosystem health, and are among the most widely used engineered nanomaterials that reach wastewater during production, usage, and disposal phases. This study evaluated the effect of a 100-fold increase in collargol (protein-coated AgNP) and Ag⁺ ions concentrations in municipal wastewater on the microbial community composition of the filter material biofilms (FMB) and the purification efficiency of the hybrid treatment system consisting of vertical (VF) and horizontal (HF) subsurface flow filters. We found that increased amounts of collargol and AgNO3 in wastewater had a modest effect on the prokaryotic community composition in FMB and did not significantly affect the performance of the studied system. Regardless of how Ag was introduced, 99.9% of it was removed by the system. AgNPs and AgNO3 concentrations did not significantly affect the purification efficiency of the system. AgNO3 induced a higher increase in the genetic potential of certain Ag resistance mechanisms in VFs than collargol; however, the increase in Ag resistance potential was similar for both substances in HF. Hence, the microbial community composition in biofilms of vertical and horizontal flow filters is largely resistant, resilient, or functionally redundant in response to AgNPs addition in the form of collargol.

In this study, the effect of seed treatment with Achromobacter xylosoxidans AUM54 and glycolipid-type biosurfactants produced by this bacterial strain to suppress Ralstonia solanacearum, which causes bacterial wilt in tomato plants, was investigated. Applying biosurfactant in combination with the biosurfactant-producing bacteria reduced the R. solanacearum population on the tomato seed surface by 44% and reduced the seed infection percentage by 87%. In addition, these treatments induced resistance in tomato plants against this pathogen, evidenced by the increased activities of defence-related enzymes, such as phenylalanine ammonia-lyase, polyphenol oxidase, and peroxidase, and reduced the percentage of disease severity (DS).

The anthropogenic release of oil hydrocarbons into the cold marine environment is an increasing concern due to the elevated usage of sea routes and the exploration of new oil drilling sites in Arctic areas. The aim of this study was to evaluate prokaryotic community structures and the genetic potential of hydrocarbon degradation in the metagenomes of seawater, sea ice, and crude oil encapsulating the sea ice of the Norwegian fjord, Ofotfjorden. Although the results indicated substantial differences between the structure of prokaryotic communities in seawater and sea ice, the crude oil encapsulating sea ice (SIO) showed increased abundances of many genera-containing hydrocarbon-degrading organisms, including Bermanella, Colwellia, and Glaciecola. Although the metagenome of seawater was rich in a variety of hydrocarbon degradation-related functional genes (HDGs) associated with the metabolism of n-alkanes, and mono- and polyaromatic hydrocarbons, most of the normalized gene counts were highest in the clean sea ice metagenome, whereas in SIO, these counts were the lowest. The long-chain alkane degradation gene almA was detected from all the studied metagenomes and its counts exceeded ladA and alkB counts in both sea ice metagenomes. In addition, almA was related to the most diverse group of prokaryotic genera. Almost all 18 good- and high-quality metagenome-assembled genomes (MAGs) had diverse HDGs profiles. The MAGs recovered from the SIO metagenome belonged to the abundant taxa, such as Glaciecola, Bermanella, and Rhodobacteracea, in this environment. The genera associated with HDGs were often previously known as hydrocarbon-degrading genera. However, a substantial number of new associations, either between already known hydrocarbon-degrading genera and new HDGs or between genera not known to contain hydrocarbon degraders and multiple HDGs, were found. The superimposition of the results of comparing HDG associations with taxonomy, the HDG profiles of MAGs, and the full genomes of organisms in the KEGG database suggest that the found relationships need further investigation and verification.

Peatland drainage based on ditch systems is a widely used forestry management practice in the boreal and hemiboreal forests to improve tree growth. This study investigated the morphological variation in absorptive roots (first- and second-order roots) across the distance gradient from the ditch with four sampling plots (5, 15, 40, and 80 m) in six drained peatland forests dominated by Downy birch and Norway spruce. The dominating tree species had a significant effect on the variation in absorptive root morphological traits. The absorptive roots of birch were thinner with a higher specific root area and length (SRA and SRL), higher branching intensity (BI), and lower root tissue density (RTD) than spruce. The distance from the ditch affected the absorptive root morphological traits (especially SRA and RTD), but this effect was not dependent on tree species and was directionally consistent between birch and spruce. With increased distance from the ditch (from plot 5 to plot 80), the mean SRA increased by about 10% in birch and 5% in spruce; by contrast, the mean RTD decreased by about 10% in both tree species, indicating a potential shift in nutrient foraging. However, soil physical and chemical properties were not dependent on the distance from the ditch. We found a species-specific response in absorptive root morphological traits to soil properties such as peat depth, pH, and temperature. Our results should be considered when evaluating the importance of morphological changes in absorptive roots when trees acclimate to a changing climate.