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.
2020
Authors
Vibeke Stærkebye Nørstebø Svein Olav Krøgli Misganu Debella-Gilo Gerardo Alfredo Perez Valdes Kristin Tolstad Uggen Wenche DramstadAbstract
A transition to a bioeconomy implies an increased focus on efficient and sustainable use of biological resources. A common, but often neglected feature of these resources is their location dependence. To optimize their use, for example in bioeconomic industrial clusters, this spatial aspect should be integrated in analyses. Optimal design and localization of a bioeconomic cluster with respect to the various biological and non-biological resources required for the cluster, the composition of industrial facilities in the cluster, as well as the demands of the outputs of the cluster, is crucial for profitability and sustainability. We suggest that optimal design and location of bioeconomic clusters can benefit from the use of a Multicriteria Decision Analysis (MCDA) in combination with Geographic Information Systems (GIS) and Operations Research modeling. The integration of MCDA and GIS determines a set of candidate locations based on various criteria, including resource availability, accessibility, and usability. A quantitative analysis of the flow of resources between and within the different industries is then conducted based on economic Input-Output analysis. Then, the cluster locations with the highest potential profit, and their composition of industrial facilities, are identified in an optimization model. A case study on forest-based bioeconomic clusters in the Østfold county of Norway is presented to exemplify this methodology, the expectation being that further implementation of the method at the national level could help decision makers in the planning of a smoother transition from a fossil-based economy to a bioeconomy.
Abstract
No abstract has been registered
Authors
Hans Renes Csaba Centeri Sebastian Eiter Bénédicte Gaillard Alexandra Kruse Zdenek Kucera Oskar Puschmann Michael Roth Martina SlámováAbstract
From the Middle Ages until the twentieth century, water meadows in Europe were primarily irrigated to improve their productivity and to lengthen the growing season. They were water management systems designed to collect and use water and to discharge it: water had to be kept moving. This chapter presents a general overview and a history of research on European water meadows. It also examines examples from the sandy landscapes of northwestern Europe, from Slovakia, and Norway. Three main types of water meadows are distinguished: simple dam systems, more elaborate catchworks, and highly developed bedworks. Of these, bedworks were technically and organizationally the most complex; they were also the most costly in construction and maintenance. Most water meadows were abandoned in the twentieth century; in many places, however, their traces can still be recognized in the landscape. They are both an interesting part of European agrarian and landscape heritage and a carrier of regional identity. In recent years, a number of water meadows have been restored, for ecological, water management, tourism, and heritage purposes.
Abstract
No abstract has been registered
Authors
Grete StokstadAbstract
No abstract has been registered
Authors
Cathrine Brekke Linn Fenne Groeneveld Theodorus Meuwissen Nina Svartedal Steffen Weigend Peer BergAbstract
The aim of this study was to evaluate genetic diversity within and between lines at the Norwegian live poultry gene bank as well as assessing the conservation value in an international context. Eight lines including the national breed, Jærhøns, were genotyped with the 600K Affymetrix® Axiom® Chicken Genotyping Array. The white egg layers were generally more inbred than the brown layers. Comparative analyses were carried out with 72 international populations of different origins. The lines that were last bred for commercial production in Norway, Norbrid, are clearly separated from the rest of the international set and more closely related to the current commercial lines. The brown egg layer Norbrid 7 has the highest relative contribution to genetic diversity. The Norwegian genebank lines are of conservation value in a national and international perspective, as they all add genetic diversity to the global set.
Authors
Heidi KnutsenAbstract
«Norwegian Agriculture – Status and Trends 2019» provides a brief overview of major aspects of agriculture in Norway and summarises some of the information that is annually published within the sector.
Authors
Christian PedersenAbstract
No abstract has been registered
Abstract
The abstract classification system Nature in Norway (NiN) has detailed ecological definitions of a high number of ecosystem units, but its applicability in practical vegetation mapping is unknown because it was not designed with a specific mapping method in mind. To investigate this further, two methods for mapping – 3D aerial photographic interpretation of colour infrared photos and field survey – were used to map comparable neighbouring sites of 1 km2 in Hvaler Municipality, south-eastern Norway. The classification accuracy of each method was evaluated using a consensus classification of 160 randomly distributed plots within the study sites. The results showed an overall classification accuracy of 62.5% for 3D aerial photographic interpretation and 82.5% for field survey. However, the accuracy varied for the ecosystem units mapped. The classification accuracy of ecosystem units in acidic, dry and open terrain was similar for both methods, whereas classification accuracy of calcareous units was highest using field survey. The mapping progress using 3D aerial photographic interpretation was more than two times faster than that of field survey. Based on the results, the authors recommend a method combining 3D aerial photographic interpretation and field survey to achieve effectively accurate mapping in practical applications of the NiN system.
Abstract
Aim: Distribution modelling is a useful approach to obtain knowledge about the spatial distribution of biodiversity, required for, for example, red-list assessments. While distribution modelling methods have been applied mostly to single species, modelling of communities and ecosystems (EDM; ecosystem-level distribution modelling) produces results that are more directly relevant for management and decision-making. Although the choice of predictors is a pivotal part of the modelling process, few studies have compared the suitability of different sets of predictors for EDM. In this study, we compare the performance of 50 single environmental variables with that of 11 composite landscape gradients (CLGs) for prediction of ecosystem types. The CLGs represent gradients in landscape element composition derived from multivariate analyses, for example “inner-outer coast” and “land use intensity.” Location: Norway. Methods: We used data from field-based ecosystem-type mapping of nine ecosystem types, and environmental variables with a resolution of 100 × 100 m. We built nine models for each ecosystem type with variables from different predictor sets. Logistic regression with forward selection of variables was used for EDM. Models were evaluated with independently collected data. Results: Most ecosystem types could be predicted reliably, although model performance differed among ecosystem types. We identified significant differences in predictive power and model parsimony across models built from different predictor sets. Climatic variables alone performed poorly, indicating that the current climate alone is not sufficient to predict the current distribution of ecosystems. Used alone, the CLGs resulted in parsimonious models with relatively high predictive power. Used together with other variables, they consistently improved the models. Main conclusions: Our study highlights the importance of variable selection in EDM. We argue that the use of composite variables as proxies for complex environmental gradients has the potential to improve predictions from EDMs and thus to inform conservation planning as well as improve the precision and credibility of red lists and global change assessments.conservation planning, distribution modelling, ecosystem classification, ecosystem types, IUCN Red List of Ecosystems, landscape gradients, spatial prediction, species response curves