Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2022
Forfattere
Erling Johan Solberg Vebjørn Veiberg Olav Strand Brage Bremset Hansen Christer Moe Rolandsen Roy Andersen Morten Heim Mai Irene Solem Frode Holmstrøm Aksel Granhus Rune Eriksen Siri Wølneberg BøthunSammendrag
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Forfattere
Christian Wilhelm Mohr Gunnhild Søgaard Gry Alfredsen Clara Antón-Fernández Katharina Hobrak Ignacio SevillanoSammendrag
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Forfattere
Johannes Schumacher Håvard Toft Larsen Paul McLean Marius Hauglin Rasmus Astrup Johannes BreidenbachSammendrag
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%.
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The British forestry sector lacks reliable dynamic growth models for stands of improved Sitka spruce, the most important commercial forest type in Great Britain. The aim of this study is to fill this gap by trialling a new modelling framework and to lay the foundations of a future dynamic growth simulator for that forest type. First, we present single tree diameter and height increment models that are climate sensitive and include explicit competition effects. The predictions from the increment models are pooled to project diameter and height at a given age. These projections are then used as inputs to an integrated taper model from which stochastic tree volume predictions are obtained. Retrospective data from over 1400 trees collected in two extensive genetic trials in Scotland and Wales were used for the purposes of this study. Diameter increment and height increment predictions were highly accurate and diameter and height projections proved consistent. The predicted volume at the time of harvesting also exhibited a high degree of accuracy, which shows the robustness of our approach. Further data will be needed in the future to recalibrate the present models and extend their range of validity to the whole of Great Britain.
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Forfattere
Kjersti Holt HanssenSammendrag
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