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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.

2026

2025

Sammendrag

Fine-scale, spatially explicit forest attribute maps are essential for guiding forest management and policy decisions. Such maps, based on the combination of National Forest Inventory (NFI) and remote sensing datasets, have a long tradition in the Nordic countries. Harmonizing the pixel size among national forest attribute maps would considerably improve the utility of the maps for users. However, the maps are often aligned with the NFI plot size, and the influence of creating these maps at different spatial resolutions (i.e. pixel sizes) is little studied. We assess the stand-level uncertainty (RMSE) of biomass, volume, basal area, and Lorey’s height estimates resulting from the aggregation of maps across varying spatial resolutions. Models fit at 16 m native resolution using more than 14 000 NFI plots were applied for predictions at pixels sizes (side lengths) of 1, 5, 10, 16, and 30 m. For independent validation, we used more than 600 field plots – that cover a total area of 24 ha and were clustered within 65 stands across Norway. For all attributes, the lowest RMSEs, ranging from 6.86% for Lorey’s height to 13.86% for volume, were observed for predictions at pixel sizes of 5 m to 16 m. The RMSE changes across resolutions were generally small (< 5%) for biomass, volume, and basal area. For Lorey’s height, changing the spatial resolution resulted in large RMSEs of up to 25%. Overall, our findings suggest that the main forest attributes can be mapped at a finer resolutions without complex adjustments.

Sammendrag

The objective of this study was to demonstrate how height growth recalculated to periodic site index could be used to monitor and identify climatic drivers for growth variations. We used data from Norway’s National Forest Inventory (NFI), with attention to Norway spruce in the lowlands (<500 m a.s.l.) of southeastern Norway. We recalculated height growth to periodic site index and extracted a time series with annual values. We supplemented this with climatic data, i.e. monthly mean temperature, precipitation and deMartonne aridity index. The results showed that a characteristic two-peaked time series in volume growth in Norway 1994–2020 corresponded well to a time series of periodic site index for Norway spruce in the specific region mentioned above. Statistical analyses showed that for spruce, the periodic site index was higher in cold and moist summers than in warm and dry. Spruce mortality in this region tripled during 2012–22 when June temperature increased considerably, while periodic site index decreased. This corroborates warm and dry weather in June to be a main stress factor for spruce. In conclusion, periodic site index has a potential for being implemented for monitoring site productivity and for identification of climatic drivers.