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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.

2025

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Sammendrag

https://www.khrono.no/ni-prosjekter-far-107-millioner-til-forskning-pa-miljo-klima-mat-og-folkehelse/911199?fbclid=IwY2xjawJo3AxleHRuA2FlbQIxMQABHhWMmmCbAcMieP8ZeLA0HMDq743F1LmAEOKMrnKI3QHe_LHW-Y5Uif_TKZkv_aem_IZtj0WrXGDqYU5QNdo3vAw

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Sammendrag

The solute exclusion technique (SET) is often used to characterise the nano-porous structure of water-swollen cell walls. SET is based on the immersion of water-saturated wood samples in solutions of probe molecules of known size. Based on determined concentration differences in the solution before and after immersion, the accessible water within the wood is determined for each probe. However, this assumes that the concentration of probe molecules is the same in the pores of the material as in the surrounding bulk solution, but the concentration in narrow pores is actually lower than in the bulk solution. This study investigated the nano-porous structure of water-swollen wood cell walls by incorporating these known effects of concentration differences in narrow pores into the analysis. Based on solute exclusion measurements on both untreated and hydrothermally treated Norway spruce wood, the study explored the effect of modification on the nano-porous cell wall structure as well as potential sources of uncertainties such as soaking time, osmotic effects and probe molecule adsorption. The results suggested that the water-swollen, nano-porous structure of untreated and hydrothermally treated Norway spruce was dominated by one characteristic pore size which increased by hydrothermal treatment. The exact size depended on the assumed geometry of the pores.

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Reliable estimates of the size and composition of harvested populations over time are key to designing adequate population management plans, regardless of management objectives. In Norway, a national system for collecting and analysing hunter-reported data on red deer (Cervus elaphus) has been operational for about 20 years. The system was expected to provide population metrics that would substantially improve deer population management routines at the municipal level. This has proven to be challenging when using existing state-of-the-art estimation methodology. The main reasons are that the variation in the observation data is generally much larger than population abundance variability, and that one does not have a clear understanding of the stochastic process generating the observation data. Here, using hunter-reported observation data and harvest data from six Norwegian municipalities collected in the period 2007–2023, we show that a straightforward estimation methodology based on population modelling can produce robust abundance estimates despite frequent low quality of the observation data. Its major assets are that it does not involve strong assumptions about the stochastic processes underlying the observation process and that it does not involve assumptions about initial population size and structure in terms of prior statistical distributions. We anticipate that the method can be applied in several other population management contexts, and we think that the results offer fresh perspectives on to what extent noisy citizen-collected time series data can be used to inform management decisions.