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.
2025
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Atle Wehn HegnesAbstract
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Anita SønstebyAbstract
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Anita SønstebyAbstract
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Tomasz Leszek WoznickiAbstract
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Katrine Marie Brynildsrud Peter Horvath Michael Angeloff Wenche Dramstad Adam Eindride Naas Kerstin Potthoff Anders BrynAbstract
Expanding cities and urban densification is one of the major threats to biodiversity, ecosystem services and human welfare. Using Oslo, the capital city of Norway, as a case study this study addresses the following questions: (i) What vegetation changes have occurred between 1980s and 2021 and to what extent? (ii) What are the potential consequences of documented changes for biodiversity and other functions of green spaces? (iii) What future direction is the present development plan aiming for? To answer these questions, detailed vegetation maps (1:10 000) of Oslo from around 1980s were remapped in situ in 2021. We present results on land cover transformations, area statistics, and analyses of ecological impacts using landscape metrics. Our results document that large areas previously covered by vegetation types and cultivated land have been lost to urban densification. Housing dominated the new use. This loss of areas with vegetation types will affect ecosystem diversity negatively. On average, the total area and the mean patch area of each vegetation type decreased, whereas the mean Euclidean nearest-neighbor distance increased. These changes have lowered connectivity and increased fragmentation. Despite explicitly stated aims, previous efforts to reduce loss of areas with high biodiversity and maintain urban green spaces have not succeeded, and the planned future urban development indicates that a further decrease will follow in the next decades.
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Syngas biomethanation represents a promising pathway to convert recalcitrant feedstocks into biomethane. However, the hydrogen (H2) content in syngas is often insufficient or fluctuates, which affects the overall performance. This study evaluated the effect of H2 addition on syngas conversion efficiency and microbial community dynamics using two trickle bed reactors (TBRs). One TBR was fed with syngas, while another received syngas supplemented with H2. Both TBRs demonstrated the feasibility of converting CO from syngas to methane, with the H2 supplemented TBR outperforming the syngas-only TBR. The H2 supplemented TBR achieved over 90 % conversion rate at a gas loading rate of 15 NL/Lreactor/d and reached peak methane production at a gas loading rate at 20 NL/Lreactor/d. Microbial community structure analysis revealed a dominance of Methanobacterium, a known thermophilic hydrogenotrophic methanogen. Although H2 addition enhanced performance, a decline in conversion efficiency at higher gas loading rates highlights the need for further optimization.
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Authors
Xiaoge Fan Xiang Cao Min Zhang Jianwu Jiang Caihua Li Ou Fang Wenbing Wang Jin Zhang Nicholas Clarke Wenbo Liu Shengdao ShanAbstract
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Lennart Noordermeer Terje Gobakken Johannes Breidenbach Rune Eriksen Erik Næsset Hans Ole Ørka Ole Martin BollandsåsAbstract
Accurate field plot data on forest attributes are crucial in area-based forest inventories assisted by airborne laser scanning, providing an essential reference for calibrating predictive models. This study assessed how sample tree selection methods and plot data calculation methods affect the accuracy of field plot values of timber volume, Lorey’s mean height, and dominant height. We used data obtained from 12 420 circular sample plots of 250 m2, measured as part of the Norwegian national forest inventory and 45 local forest management inventories. We applied Monte Carlo simulations by which we tested various numbers of sample trees, methods to select sample trees, and methods to calculate plot-level values from tree-level measurements. Accuracies of plot values were statistically significantly affected by the number of sample trees, sample tree selection method, and calculation method. Obtained values of root mean square error ranged from 5% to 16% relative to the mean observed values, across the factors studied. Accuracy improved with increasing numbers of sample trees for all forest attributes. We obtained greatest accuracies by selecting sample trees with a probability proportional to basal area, and by retaining field-measured heights for sample trees and using heights predicted with a height-diameter model for non-sample trees. This study highlights the importance of appropriate sample tree selection methods and calculation methods in obtaining accurate field plot data in area-based forest inventories.
Authors
Simon BergAbstract
No abstract has been registered