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.
2015
Authors
Andrew N. Sharpley Lars Bergström Helena Aronsson Marianne Bechmann Carl Bolster Katarina Börling Faruk Djodjic Helen P. Jarvie Oscar F. Schoumans Christian Stamm Karin S. Tonderski Barbro Ulen Risto Uusitalo Paul J. A. WithersAbstract
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Interactions between soil properties and climate affect forage grass productivity. Dynamic models, simulating crop performance as a function of environmental conditions, are valid for a specific location with given soil and weather conditions. Extrapolations of local soil properties to larger regions can help assess the requirement for soil input in regional yield estimations. Using the LINGRA model, we simulated the regional yield level and variability of timothy, a forage grass, in Akershus and Østfold counties, Norway. Soils were grouped according to physical similarities according to 4 sets of criteria. This resulted in 66, 15, 5 and 1 groups of soils. The properties of the soil with the largest area was extrapolated to the other soils within each group and input to the simulations. All analyses were conducted for 100 yr of generated weather representing the period 1961-1990, and climate projections for the period 2046-2065, the Intergovernmental Panel on Climate Change greenhouse gas emission scenario A1B, and 4 global climate models. The simulated regional seasonal timothy yields were 5-13% lower on average and had higher inter-annual variability for the least detailed soil extrapolation than for the other soil extrapolations, across climates. There were up to 20% spatial intra-regional differences in simulated yield between soil extrapolations. The results indicate that, for conditions similar to these studied here, a few representative profiles are sufficient for simulations of average regional seasonal timothy yield. More spatially detailed yield analyses would benefit from more detailed soil input.
Authors
Annelene Pengerud Per Stålnacke Marianne Bechmann Gitte Blicher-Mathiesen Arvo Iital Jari Koskiaho Katarina Kyllmar Ainis Lagzdins Arvydas PovilaitisAbstract
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Authors
Seyda Ozkan Bente Aspeholen Åby Tomas Persson Klaus Mittenzwei Mats Höglind Øyvind Hoveid Lillian ØygardenAbstract
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Elevated nutrient concentrations in streams in the Norwegian agricultural landscape may occur due to faecal contamination. Escherichia coli (E. coli) has been used conventionally as an indicator of this contamination; however, it does not indicate the source of faecal origin. This work describes a study undertaken for the first time in Norway on an application of specific host-associated markers for faecal source tracking of water contamination. Real-time quantitative polymerase chain reaction (qPCR) on Bacteroidales host-specific markers was employed for microbial source tracking (MST) to determine the origin(s) of faecal water contamination. Four genetic markers were used: the universal AllBac (Bacteroidales) and the individual specific markers BacH (humans), BacR (ruminants) and Hor-Bac (horses). In addition, a pathogenicity test was carried out to detect the top seven Shiga toxin-producing E. coli (STEC) serogroups. The ratio between each individual marker and the universal one was used to: (1) normalise the markers to the level of AllBac in faeces, (2) determine the relative abundance of each specific marker, (3) develop a contribution profile for faecal water contamination and (4) elucidate the sources of contamination by highlighting the dominant origin(s). The results of the qPCR MST analyses indicated the actual contributions of humans and animals to faecal water contamination. The pathogenicity test revealed that water samples were STEC positive at a low level, which was in proportion to the concentration of the ruminant marker. The outcomes were verified statistically by coupling the findings of major contamination sources with observations in the field regarding local land use (residential or agricultural). Furthermore, clear correlations between the human marker and E. coli counts as well as the ruminant marker and STEC quantity in faecally contaminated water were observed. The results of this study have the potential to help identify sources of pollution for targeted mitigation of nutrient losses.
2014
Abstract
No abstract has been registered