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.
2012
Authors
Christian Brischke Linda Meyer Gry Alfredsen Miha Humar Lesley Francis Per Otto Flæte Pia Larsson-BrelidAbstract
The material-inherent resistance of wood is one of the most important qualities influencing the durability of timber. Hence, it has also a major effect on the service life to be expected from a timber construction. In addition, design details and the respective climatic conditions determine durability and make it impossible to treat wood durability as an absolute value. Moreover, the reference magnitude varies between locations because of climatic differences. Durability classification is therefore based on comparing a certain performance indicator between the timber in question and a reference timber. Finally, the relative values (= resistance factors) are grouped and related to durability classes, which can refer to a high range of service lives for a certain location. The insufficient comparability of such durability records turned out to be a key problem for the service life prediction of timber structures, even when the climatic conditions are clearly defined. This study aimed therefore on an inventory of literature data, directly based on service life measures, not masked by a durability classification schedule. It focused on natural durability of timber tested in the field under above-ground conditions. In total 395 durability recordings from 31 different test sites worldwide and based on ten different test methods have been considered for the calculation of resistance factors: 190 for hardwoods and 205 for softwoods. Nevertheless, the considered datasets were heterogeneous in quality and quantity; the resulting resistance factors suffered from high variation. In many cases information was presented too condensed and incompletely, which is inescapable for instance in journal articles. To increase the amount of available, comparable, and directly service-life related data a reliable platform is needed. A proposal for a corresponding data base is provided in part 2 of this paper.
Abstract
K-nearest neighbor (kNN) approaches are popular statistical methods for predicting forest attributes in airborne laser scanning (ALS) based inventories. Their main upsides are the simplicity to predict multivariate response variables and their freeness of distributional assumptions on the conditional response.One of their largest draw-backs is that predictions outside the range of the reference data inherently result in an under- or overestimation. This property of kNN approaches is known as extrapolation bias and aggravates with an increasing number of neighbors (k) used for the prediction.This study presents one possibility to reduce extrapolation biases of predictions based on the area-based approach (ABA) by using individual tree crown (ITC) approaches within those specific areas of a low density ALS acquisition where the point density might be sufficiently high for using ITC methods.In the proposed strategy, additional (or artificial) reference plots augmented field measured plots. Artificial plots were created by applying ITC segmentation to a canopy height model derived from high density ALS data. The response variable biomass per hectare was predicted for every segment following a semi-ITC approach.The segment predictions were aggregated on the artificial plot level. The artificial plots were then treated in the same way as the original reference data to make predictions in areas with low density ALS data based on the ABA. It was hereby assumed that the predicted plot level response on the artificial plots is equivalent with the observed plot level response on the original reference data.The data consisted of 110 reference plots with a smaller data range than the 201 independent validation plots. Considerable extrapolation bias was visible if only the reference plots were used for the prediction. Almost no extrapolation bias was found if the prediction was based on reference plots augmented by artificial plots. The root mean squared error (RMSE) of the biomass predictions based on the reference plots was 39.1%. The RMSE reduced to 29.8% if the reference plots were augmented by artificial plots.
Abstract
No abstract has been registered
Authors
Tor J. JohansenAbstract
No abstract has been registered
Authors
Marte Meland Celine ReboursAbstract
The algae industry in Norway has long tradition in exploiting natural resources. The seaweed constitute an important part of the ecosystem and are of important commercial value. This article describes the established seaweed industry in Norway.
Authors
Grete K. Hovelsrud Ingrid Kvalvik Halvor Dannevig Inger Hanssen-Bauer Sigridur Dalmannsdottir Lars Rønning Eivind Uleberg Bob van OortAbstract
An interdisciplinary study, based on downscaled climate change scenarios and interviews with local farmers in Northern Norway, has assessed biological and agronomic effects of climate change, and interaction with political, economic and social factors. The study confirms that farmers are facing complex challenges. Negative effects from climate change combine with other challenges.
Authors
Marte Meland Celine ReboursAbstract
In Norway, regulations for harvesting seaweed apply to seabed algae such as Laminaria hyperborea. Harvest of foreshore algae such as Ascophyllum nodosum is not regulated, but is regulated by private owner rights because the species grow in the tidal zone. Environmental protection laws and other regulations can restrict areas for harvesting. Regulations of aquaculture of seaweed are under development.
Abstract
The ExFlood project started in 2010 and concentrates on the reduction of peak flow during extreme events. The project is in progress, and results are preliminary. The project is funded by the Norwegian Research Council, NORKLIMA program.
Authors
Abdelhameed Elameen DenisTourvieille de Labrouhe Emmanuelle Mestries Sonja Klemsdal Sophia Ahmed François DelmotteAbstract
Plasmopara halstedii is a diploid oomycete plant pathogen causing downy mildew on sunflower (Helianthus annuus). Due to changes in cultural systems and the introduction of new exotic cultivars, the pathogen developed many races and have now become a serious problem affecting sunflower growing fields in Europe. The yield losses in sunflower crop caused by P. halstedii can be up to 85 %.
Authors
Even Riiser Ingrid Holtsmark Hege Særvold Steen S. Swaminathan Navin Khanna Ralph Bock Jihong Liu ClarkeAbstract
The global spread of dengue fever threatens a large percentage of the world’s population. The disease causes great human suffering, a high mortality from dengue haemorrhagic fever and its complications, and major costs. There is currently no vaccine to prevent dengue virus infection. Our project aims to express a tetravalent vaccine candidate in tobacco chloroplasts, a cost effective system, and hence to contribute to innovation and bio-economy as a long term goal.