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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.

2022

Abstract

The objective of this report is to investigate the role of animal breeding in the partner European countries — in terms of (1) increase of the competitiveness of breeders’ association and (2) conservation of animal genetic resources including breeding programmes — to generate relevant lessons for African partner countries in addressing livestock and poultry productivity and quality challenges in Africa.

Abstract

Plant genetic resources form the biological basis for all plant-based agricultural production. In the genetic diversity lie opportunities to adjust, improve and adapt the crop production to current or future needs. In addition, the diversity of species and varieties in Norwegian agriculture represents an important part of our cultural heritage. Conservation and sustainable use of plant genetic resources is a global concern and FAO has established a global action plan that highlights priorities for conservation and use of plant genetic diversity at national level. This report points to results, trends and challenges within this field in Norway and is the Norwegian contribution to the FAO report "Third State of the World's Plant Genetic Resources" (expected 2023).

Abstract

The number of people affected by snow avalanches during recreational activities has increased over the recent years. An instrument to reduce these numbers are improved terrain classification systems. One such system is the Avalanche Terrain Exposure Scale (ATES). Forests can provide some protection from avalanches, and information on forest attributes can be incorporated into avalanche hazard models such as the automated ATES model (AutoATES). The objectives of this study were to (i) map forest stem density and canopy-cover based on National Forest Inventory and remote sensing data and, (ii) use these forest attributes as input to the AutoATES model. We predicted stem density and directly calculated canopy-cover in a 20 Mha study area in Norway. The forest attributes were mapped for 16 m × 16 m pixels, which were used as input for the AutoATES model. The uncertainties of the stem number and canopy-cover maps were 30% and 31%, respectively. The overall classification accuracy of 52 ski-touring routes in Western Norway with a total length of 282 km increased from 55% in the model without forest information to 67% when utilizing canopy cover. The F1 score for the three predicted ATES classes improved by 31%, 9%, and 6%.