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.
2016
Authors
Åge Arild Nyborg Hilde OlsenAbstract
Soil names from the soil classi cation systems are too complicated to decipher for most of our soil map users. To reach out to potential users of soil information, apart from people working with soil erosion related issues, we translated WRB unit names into user friendly map information, that shows soil quality and limiting soil properties on farmland.
Editors
Jannes Stolte Mehreteab Tesfai Lillian Øygarden Sigrun Hjalmarsdottir Kværnø Jacob Keizer Frank Verheijen Panos Panagos Cristiano Ballabio Rudi HesselAbstract
No abstract has been registered
Authors
Kjell AndreassenAbstract
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Authors
Emilio Alvarenga Sergey Hayrapetyan Lindis Skipperud Lusine Hayrapetyan Marte Sverdrup Linjordet Brit SalbuAbstract
No abstract has been registered
Authors
Habtamu AlemAbstract
No abstract has been registered
Authors
Elena Iordanova Vanguelova Eleonora Bonifacio Bruno de Vos Marcel R. Hoosbeek Torsten W. Berger Lars Vesterdal Kȩstutis E. Armolaitis Luisella Celi Lucian Constantin Dincǎ O. Janne Kjønaas Pavel Pavlenda Jukka Pumpanen Ülle Püttsepp Brian Reidy Primož Simončič Brian Tobin Miglena ZhiyanskiAbstract
Spatially explicit knowledge of recent and past soil organic carbon (SOC) stocks in forests will improve our understanding of the effect of human- and non-human-induced changes on forest C fluxes. For SOC accounting, a minimum detectable difference must be defined in order to adequately determine temporal changes and spatial differences in SOC. This requires sufficiently detailed data to predict SOC stocks at appropriate scales within the required accuracy so that only significant changes are accounted for. When designing sampling campaigns, taking into account factors influencing SOC spatial and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need to be defined: profile, plot, forests, catchment, national or wider. Scaling up SOC stocks from point sample to landscape unit is challenging, and thus requires reliable baseline data. Knowledge of the associated uncertainties related to SOC measures at each particular scale and how to reduce them is crucial for assessing SOC stocks with the highest possible accuracy at each scale. This review identifies where potential sources of errors and uncertainties related to forest SOC stock estimation occur at five different scales—sample, profile, plot, landscape/regional and European. Recommendations are also provided on how to reduce forest SOC uncertainties and increase efficiency of SOC assessment at each scale.
Authors
Elena I. Vanguelova Eleonora Bonifacio Bruno De Vos Marcel R. Hoosbeek Torsten W. Berger Lars Vesterdal Ketutis Armolaitis L. Celi Lucian Dinca O. Janne Kjønaas Pavel Pavlenda Jukka Pumpanen Ülle Püttsepp Brian Reidy Primož Simončič Brian Tobin Miglena ZhiyanskiAbstract
No abstract has been registered
Authors
Geir-Harald StrandAbstract
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Abstract
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Abstract
No abstract has been registered