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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.

2007

Sammendrag

Forty samples each of leaves, bark and wood of mountain birch (Betula pubescens EHRH.) were collected along a 120 km long south-north transect running through Norway\"s largest city, Oslo. Concentrations of 26 chemical elements (Ag, As, Au, B, Ba, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, La, Mg, Mn, Mo, Na, Ni, P, Pb, S, Sb, Sr, Ti and Zn) as well as loss on ignition for the three sample materials are reported. By far the highest concentrations of most elements appear in the leaves. Prominent exceptions are Au and Pb, both of which are enriched in wood, indicating the importance of root-uptake, and As which is enriched in bark. Bedrock lithology, ore occurrences, soil pH and urban contamination all have a visible influence on the element concentrations in mountain birch leaves, bark and wood. It is often impossible to differentiate between all the factors that can influence element concentrations in the three sample materials. Mountain birch bark shows the strongest anthropogenic impact of the city of Oslo for dust-related elements (Fe, La, Ti) and Sb. Even in mountain birch bark the influence of the city on element concentrations is no longer discernible from the background variation at a distance of less than 20 km from Oslo centre. Compared to terrestrial moss, mountain birch appears to be of little value as a biomonitor for urban contamination.

Sammendrag

Predicting the yield and quality of sawn timber continues to be a challenging task, influenced by several stochastic processes: Log dimension and shape under bark varies, accuracy of sawing is not perfect, etc. This work presents an annotated model based on an approach successfully applied in the industry through a couple of decades. A number of important timber yield predictors are identified, and the following models give unbiased yield estimates. Being in need of adjustment before transferring to new locations, the approach might be considered a powerful tool to analyse and improve the operation, rather than a complete model in itself. Nevertheless, the notional, purely geometric, models might be superior for analysing unfamiliar sawing patterns, even if they tend to overestimate the yield. Thus, the two methods should preferably be used in combination, rather than one replacing the other. Finally, the everyday use of such models is illustrated and a procedure for associating sawn timber with suitable logs is outlined.