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.
2014
Authors
Trygve S. Aamlid Tatsiana Espevig Arne Tronsmo Klaus Paaske Lars Wiik Trond Olav Pettersen Anne Steensohn Ove Hetland Anne Mette Dahl Jensen Per Göran AndersonAbstract
This report presents results from a project testing Turf G+/WPG (fungal products containing Gliocladium catenulatum) and Turf S+/WPS (bacterial products containing Streptomyces spp.), both from Interagro BIOS AB, and Vacciplant (seaweed product containing laminarine) from Nordisk Alkali AB, for the control of Microdochium nivale and other diseases on golf greens. Five field trials were carried out in Denmark, Sweden and Norway from October 2011 to September 2014, and Turf G+/WPG and Turf S+ were tested also in vitro. None of the test-products gave any consistent disease control in the field trials. A significant reduction in Microdochium nivale from 3 % of plot area on untreated plots to 2 % on treated plots was seen in one trial, but this was considered to be of little practical relevance. In all other trials with more severe attacks of Microdochium nivale, only the fungicide control treatment showed a significant reduction in disease compared with the untreated control. On average for all field trials over three years, the higher rate of Vacciplant, the combination of Turf G+/WPG and Turf S+/WPS, and the fungicide treatment gave, in turn, 22, 24 and 87 % less microdochium patch in the fall, but among these, only the effect of fungicide was significant. The effects of the biological products on pink or gray (Typhula incarnata) snow mold after snow melt were even smaller. In the in vitro trials, Turf S+ provided good control of Microdochium nivale at 6 and 16 ̊C, but Turf G+/WPG was effective only at the higher temperature. However, since these results could not be repeated under field conditions, we have to conclude that none of the test products represent any real alternative to fungicides for control of M. nivale or other diseases on Scandinavian golf courses.
Abstract
Reliable methods are required to predict changes in soil carbon stocks. Process-based models often require many parameters which are largely unconstrained by observations. This induces uncertainties which are best met by using repeated measurements from the same sites. Here, we compare two carbon models, Yasso07 and Romul, in their ability to reproduce a set of field observations in Norway. The models are different in the level of process representation, structure, initialization requirements and calibration- and parameterization strategy. Field sites represent contrasting tree species, mixture and soil types. The number of repetitions of C measurements varies from 2 to 6 over a period of up to 35 years, and for some of the sites, which are part of long-term monitoring programs, plenty of auxiliary information is available. These reduce the danger of overparametrization and provide a stringent testbed for the two models. Focus is on the model intercomparison, using identical site descriptions to the extent possible, but another important aspect is the upscaling of model results to the regional or national scale, utilizing the Norwegian forest inventory system. We suggest that a proper uncertainty assessment of soil C stocks and changes has to include at least two (and preferably more) parametrized models.
Authors
Holger Lange Lise Dalsgaard Signe Kynding Borgen Silje Skår O. Janne Kjønaas Kjell AndreassenAbstract
Reliable methods are required to predict changes in soil carbon stocks. Process-based models often require many parameters which are largely unconstrained by observations. This induces uncertainties which are best met by using repeated measurements from the same sites. Here, we compare two carbon models, Yasso07 and Romul, in their ability to reproduce a set of field observations in Norway. The models are different in the level of process representation, structure, initialization requirements and calibration- and parameterization strategy. Field sites represent contrasting tree species, mixture and soil types. The number of repetitions of C measurements varies from 2 to 6 over a period of up to 35 years, and for some of the sites, which are part of long-term monitoring programs, plenty of auxiliary information is available. These reduce the danger of overparametrization and provide a stringent testbed for the two models. Focus is on the model intercomparison, using identical site descriptions to the extent possible, but another important aspect is the upscaling of model results to the regional or national scale, utilizing the Norwegian forest inventory system. We suggest that a proper uncertainty assessment of soil C stocks and changes has to include at least two (and preferably more) parametrized models.
Abstract
No abstract has been registered
Authors
Laura Kirwan John Connolly Caroline Brophy Ole Hans Baadshaug Gilles Bélanger Allistair Black Tim Carnus Rosemary Collins Jure Cop Ignacio Delgado Alex De Vliegher Anjo Elgersma Bodil Frankow-Lindberg Piotr Golinski Philippe Grieu Anne-Maj Gustavsson Aslaug Helgadottir Mats Höglind Olivier Huguenin-Elie Marit Jørgensen Zydre Kadziuliene Tor Lunnan Andreas Lüscher Päivi Kurki Claudio Porqueddu Maria Teresa Sebastia Ulrich Thumm David Walmsley John FinnAbstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
A wide range of forest products and industries have been examined in life cycle analyses (LCA). Life cycle data are essential for identifying forestry operations that contribute most to carbon emissions. Forestry can affect net CO2 emissions by changing carbon stocks in biomass, soil and products, by supplying biofuels to replace fossil fuels as well as by establishing new forests. The transport of forest products is crucial to greenhouse gas (GHG) emissions. We conceptualize the chain from seed production, silviculture, harvesting, and timber transport to the industry as a system. Inputs to the system are energy and fuel, the output represents GHG emissions. The reference functional unit used for the inventory analysis and impact assessment is one cubic meter of harvested timber under bark. GHG emissions from forestry in East Norway were calculated for the production of one such unit delivered to the industry gate in 2010 (cradle-to-gate inventory), showing that timber transport from the forest to the final consumer contributed with more than 50 % to the total GHG emissions. To assess uncertainty of model approaches, the LCA was conducted with two different models, SimaPro and GaBi, both using the Ecoinvent database with data adapted to European conditions.
Abstract
A wide range of forest products and industries have been examined in life cycle analyses (LCA). Life cycle data are essential for identifying forestry operations that contribute most to carbon emissions. Forestry can affect net CO2 emissions by changing carbon stocks in biomass, soil and products, by supplying biofuels to replace fossil fuels as well as by establishing new forests. The transport of forest products is crucial to greenhouse gas (GHG) emissions. We conceptualize the chain from seed production, silviculture, harvesting, and timber transport to the industry as a system. Inputs to the system are energy and fuel, the output represents GHG emissions. The reference functional unit used for the inventory analysis and impact assessment is one cubic meter of harvested timber under bark. GHG emissions from forestry in East Norway were calculated for the production of one such unit delivered to the industry gate in 2010 (cradle-to-gate inventory), showing that timber transport from the forest to the final consumer contributed with more than 50 % to the total GHG emissions. To assess uncertainty of model approaches, the LCA was conducted with two different models, SimaPro and GaBi, both using the Ecoinvent database with data adapted to European conditions.
Abstract
No abstract has been registered
Authors
Gunnhild SøgaardAbstract
No abstract has been registered