Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2019
Authors
Simona Caputo Maria Papale Carmen Rizzo Stefania Giannarelli Antonella Conte Federica Moscheo Marco Graziano Paul Eric Aspholm Massimo Onor Emilio De Domenico Stefano Miserocchi Luigi Michaud Maurizio Azzaro Angelina Lo GiudiceAbstract
Anthropogenic impact over the Pasvik River (Arctic Norway) is mainly caused by emissions from runoff from smelter and mine wastes, as well as by domestic sewage from the Russian, Norwegian, and Finnish settlements situated on its catchment area. In this study, sediment samples from sites within the Pasvik River area with different histories of metal input were analyzed for metal contamination and occurrence of metal-resistant bacteria in late spring and summer of 2014. The major differences in microbial and chemical parameters were mostly dependent on local inputs than seasonality. Higher concentrations of metals were generally detected in July rather than May, with inner stations that became particularly enriched in Cr, Ni, Cu, and Zn, but without significant differences. Bacterial resistance to metals, which resulted from viable counts on amended agar plates, was in the order Ni2+>Pb2+>Co2+>Zn2+>Cu2+>Cd2+>Hg2+, with higher values that were generally determined at inner stations. Among a total of 286 bacterial isolates (mainly achieved from Ni- and Pb-amended plates), the 7.2% showed multiresistance at increasing metal concentration (up to 10,000 ppm). Selected multiresistant isolates belonged to the genera Stenotrophomonas, Arthrobacter, and Serratia. Results highlighted that bacteria, rapidly responding to changing conditions, could be considered as true indicators of the harmful effect caused by contaminants on human health and environment and suggested their potential application in bioremediation processes of metal-polluted cold sites.
Authors
Cornelya Klutsch Vetle Schwensen Lindgren Thrond Oddvar Haugen Natalia Polikarpova Paul Eric Aspholm Ida Marie Luna Fløystad Kristin Forfang Simo Maduna Tommi Nyman Hans Geir Eiken Per-Arne Amundsen Snorre HagenAbstract
No abstract has been registered
Authors
Habtamu AlemAbstract
No abstract has been registered
Abstract
Complex communities of microorganisms influence plant and agroecosystem health and productivity. Bacteria and fungi constitute a major part of the wheat head microbiome. A microorganism’s ability to colonize or infect a wheat seed is influenced by interacting microbiome. In Norway, wheat seed lots are routinely analysed for the infestation by Fusarium head blight and seedling blight diseases, such as Fusarium and Microdochium spp., and glume blotch caused by Parastagonospora nodorum using traditional methods (plating grain on PDA, recording presence or absence of fungal colonies) The purpose is to decide if the seed quality is suitable for sowing and whether seed treatment is needed. This method is time consuming, require knowledge within fungal morphology, and do not facilitate identification to species level in all cases. Molecular methods such as sequencing could allow detection and quantification of “all” microbial DNA, only limited by the specificity of the primers. Microbial profiling (metabarcoding) can be very time and cost-effective, since a mixture of many samples can be analysed simultaneously for both fungi and bacteria, and other microbes if required. In our project “Phytobiome” we used metabarcoding to analyse microbial communities in wheat heads and verify this information with results from qPCR and plate studies for a more complete study. Around 150 spring wheat seed lots from the years 2016-2017 (including two cultivars) were selected for analysis. One of the main objectives was to find microorganisms associated with seed germination. We will present findings from this work, but also some challenges when using PCR-based sequencing methods, especially regarding Fusarium head blight fungi.
Authors
Janneche Utne Skåre Jan Alexander Marte Haave Ignacy Jakubowicz Helle Katrine Knutsen Amy Lusher Martin Ogonowski Kirsten Eline Rakkestad Ida Skaar Line Emilie Sverdrup Martin Wagner Angelika Agdestein Johanna Eva Bodin Edel O. Elvevoll Gro Ingunn Hemre Dag Olav Hessen Merete Hofshagen Trine Husøy Åshild Krogdahl Asbjørn Magne Nilsen Trond Rafoss Olaug Taran Skjerdal Inger-Lise Steffensen Tor A Strand Vigdis Vandvik Yngvild WastesonAbstract
No abstract has been registered
Authors
Olalla Díaz-Yáñez Blas Mola-Yudego José Ramón González-OlabarriaAbstract
Snow and wind damages are one of the major abiotic disturbances playing a major role in forest ecosystems and affecting both stand dynamics and forest management decisions. This study analyses the occurrence of wind and snow damage on Norwegian forests, based on data from four consecutive forest inventories (1995–2014). The methodological approach is based on boosted regression trees, a machine learning method aiming to demonstrate the effects of different variables on damage probability and their interactions as well as to spatialize damage occurrence to make predictions. In total, 313 models are fitted to detect trends, interactions and effects among the variables. The main variables associated with damage occurrence are consistent across all the models and include: latitude, altitude and slope (related to site and location), and tree density, mean diameter and height (related to forest characteristics). The results show that stand dominant height is a key variable in explaining damage probability, whereas stand slenderness has a limited effect. More heterogeneous forest structures make birch dominated stands more resistant to damage. Finally, the models are translated into occurrence maps, to provide landscape-level information on snow and wind damage hazard. Further application of the models can be oriented towards assessing the probability of damage for alternate stand management scenarios.
Authors
Marleen Pallandt Bernhard Ahrens Sönke Zaehle Marion Schrumpf Holger Lange Markus ReichsteinAbstract
Soil organic carbon (SOC) is the largest terrestrial carbon pool. Changes in the hydrological cycle affect C-cycle turnover, with potential effects on the global C balance’s response to global change. However, large scale model representations of the sensitivity of soil carbon to soil moisture, through decomposition and interactions with nutrient cycles, are largely empirical to semi-empirical and uncertain. To better represent these dynamics, the aims of this PhD project* are to: • Investigate the role of soil moisture on SOC decomposition over a vertical profile; • Assess which moisture controls are (most) important in a multi-layered, mechanistic soil biogeochemistry model, the Jena Soil Model (JSM, Fig 2); • Update and improve the representations of soil moisture dynamics in JSM and evaluate this model for multiple sites along a moisture gradient and global scale.
Authors
Bernhard Ahrens Marleen Pallandt Markus Reichstein Holger Lange Marion Schrumpf Sonke ZaehleAbstract
The Jena Soil Model (JSM) is a multi-layer mechanistic soil biogeochemistry model with explicit representations of vertical transport, mineral sorption, and microbial control on decomposition rates. Reaction rates are further modified by temperature and moisture. While temperature determines the maximum reaction velocity (Vmax), moisture reduces this rate nonlinearly if either the diffusion of substrate is restricted (at low soil moisture) or oxygen availability for microbes is limited (at wet conditions). This moisture control on soil organic matter formation and decomposition is represented with the Dual Arrhenius Michaelis-Menten (DAMM) model concept (Davidson et al. 2012) and influences the reaction rates of microbial depolymerisation of litter and microbial residue pools as well as DOC (dissolved organic matter) uptake. Sorption of DOM and microbial residues to mineral surfaces is moisture dependent through a Langmuir sorption approach. We will validate the carbon cycle representation of moisture control on soil organic matter decomposition in JSM by comparing simulations with measured carbon stocks and respiration rates from different ecosystems ranging from boreal upland forests and wetlands to Mediterranean savannas. The modular structure of JSM will allow us to investigate the effect of moisture control on each decomposition step (depolymerisation, microbial uptake and growth, and OC sorption) separately.
Abstract
Temperature during seed maturation can induce an epigenetic memory effect in growth phenology of Norway spruce (Picea abies (L.) Karst.) that lasts for several years. To quantify the epigenetic modifications induced by natural climatic variation, common garden experiments with plants originating from different provenances and seed years were performed. Plants from warmer seed years showed delayed phenology with later bud flush, bud set and growth cessation. This effect was quantified by linear models of phenology traits as a function of climate indices for the origin and seed year of the plants. Significant effects of the temperature during seed production (seed year) was found for the bud set in seedlings in their first growing season and for bud flush and growth cessation in the 7th-8th growing season from seed. The models suggest that growth start and growth cessation are delayed 0.7–1.8 days per 100 additional degree days experienced by the seed during embryo development and seed maturation. Models that include factors that are known to induce epigenetic effects could be used to better predict future performance of forest reproductive material.
Abstract
No abstract has been registered