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.

2021

Sammendrag

Skogens helsetilstand påvirkes i stor grad av klima og værforhold, enten direkte ved tørke, frost og vind, eller indirekte ved at klimaet påvirker omfanget av soppsykdommer og insektangrep. Klimaendringene og den forventede økningen i klimarelaterte skogskader gir store utfordringer for forvaltningen av framtidas skogressurser. Det samme gjør invaderende skadegjørere, både allerede etablerte arter og nye som kan komme til Norge i nær framtid. I denne rapporten presenteres resultater fra skogskadeovervåkingen i Norge i 2020 og trender over tid. I den landsrepresentative skogovervåkingen har kronetettheten hos gran og furu holdt seg stabil i 2020 sammenlignet med tidligere år. Det ble registrert lite misfarging hos bartrærne. Skadenivået hos både bartrær, bjørk og andre løvtrær var lavere enn i 2019. Abiotiske faktorer med snø, vind og tørke som de viktigste årsakene dominerte skadebildet hos alle treslag. Kjemiske analyser av luft og nedbør i den intensive skogovervåkingen viser at det fortsatt er høyest verdier av antropogene svovel- og nitrogenforbindelser på den sørligste overvåkingsflata i Birkenes grunnet langtransportert forurensing. Den høyeste konsentrasjonen av nitrogendioksid i luft ble målt på stasjonen i Hurdal i 2020, noe som skyldes utslipp fra veitrafikken i regionen. Det var lave nivåer av bakkenært ozon i Norge i 2020 og ingen overskridelser av UNECEs grenseverdi på 5000 ppb-timer for skog. Vegetasjonsanalysene fra Hurdal har påvist en endring i bunn-vegetasjonens artssammensetning grunnet økt lystilgang og mye barnålstrø. Både hogst utenfor overvåkingsflata og flere skrantende, råteangrepne og døde grantrær i flata har bidratt til økt lystilgang og til større strømengde på bakken. Mange grantrær på flata i Hurdal er sterkt preget av råte med lav kronetetthet og mye misfarging. Flere trær på flata har dødd de seinere årene som følge av råteskader, ofte i kombinasjon med andre faktorer som vindfelling og skader etter tørken i 2018 med påfølgende barkbilleangrep. Overvåking av bjørkemålere har vist at fjellbjørkeskogen både i Nord-Norge og fjellregionene i sørlige halvdel av landet har vært utsatt for betydelige utbrudd av bjørkemålere i løpet av perioden 2012–2018. Overvåkingsdata fra 2019 og 2020 tyder imidlertid på at målerbestandene nå er lave eller i sterk tilbakegang i det meste av landet. I Troms har målerbestandene allerede nådd et bunnpunkt, og bestandene er nedadgående også i fjellet i Sør-Norge. Vi forventer derfor at skogen i mesteparten av Norge vil bli mindre utsatt for angrep av bjørkemålere de neste par årene. De fleste fylkene hadde en økning i fangstverdiene i barkbilleovervåkingen i 2020-sesongen. Alle fangstverdiene var imidlertid under 10 000 biller per felle, mens de høyeste verdiene ved slutten av utbruddet på 1970-tallet var rundt 25 000 biller per felle. Fylkene rundt Oslofjorden hadde noen lokale tilfeller av tørke- og barkbilleskader. Det ble ikke funnet noen tydelig økning av fellefangstene i tiden for en annen generasjon, men modellberegninger viser at stor granbarkbille har nok døgngrader til å gjennomføre to generasjoner før overvintring. I august 2020 ble soppen Diplodia sapinea funnet på sterkt skadet vrifuru i Ås kommune. Tidligere har det blitt gjort noen få funn av soppen på andre bartrearter i det samme området. D. sapinea er vanlig i varmere strøk på flere kontinenter, spesielt på furuarter. De pågående klima-endringene har trolig bidratt til at soppen har kunnet spre og etablere seg mot nord, men vi kan heller ikke utelukke innførsel av soppen via plantemateriale til bruk i grøntanlegg eller skog. D. sapinea er trolig bare i etableringsfasen i Norge, og har til dags dato gjort liten skade på våre stedegne bartrær.....

2020

Til dokument

Sammendrag

Boreal forests constitute a large portion of the global forest area, yet they are undersampled through field surveys, and only a few remotely sensed data sources provide structural information wall-to-wall throughout the boreal domain. ArcticDEM is a collection of high-resolution (2 m) space-borne stereogrammetric digital surface models (DSM) covering the entire land area north of 60° of latitude. The free-availability of ArcticDEM data offers new possibilities for aboveground biomass mapping (AGB) across boreal forests, and thus it is necessary to evaluate the potential for these data to map AGB over alternative open-data sources (i.e., Sentinel-2). This study was performed over the entire land area of Norway north of 60° of latitude, and the Norwegian national forest inventory (NFI) was used as a source of field data composed of accurately geolocated field plots (n=7710) systematically distributed across the study area. Separate random forest models were fitted using NFI data, and corresponding remotely sensed data consisting of either: i) a canopy height model (ArcticCHM) obtained by subtracting a high-quality digital terrain model (DTM) from the ArcticDEM DSM height values, ii) Sentinel-2 (S2), or iii) a combination of the two (ArcticCHM+S2). Furthermore, we assessed the effect of the forest- and terrain-specific factors on the models’ predictive accuracy. The best model (,i.e., ArcticCHM+S2) explained nearly 60% of the variance of the training set, which translated in the largest accuracy in terms of root mean square error (RMSE=41.4 t ha−1 ). This result highlights the synergy between 3D and multispectral data in AGB modelling. Furthermore, this study showed that despite the importance of ArcticCHM variables, the S2 model performed slightly better than ArcticCHM model. This finding highlights some of the limitations of ArcticDEM, which, despite the unprecedented spatial resolution, is highly heterogeneous due to the blending of multiple acquisitions across different years and seasons. We found that both forest- and terrain-specific characteristics affected the uncertainty of the ArcticCHM+S2 model and concluded that the combined use of ArcticCHM and Sentinel-2 represents a viable solution for AGB mapping across boreal forests. The synergy between the two data sources allowed for a reduction of the saturation effects typical of multispectral data while ensuring the spatial consistency in the output predictions due to the removal of artifacts and data voids present in ArcticCHM data. While the main contribution of this study is to provide the first evidence of the best-case-scenario (i.e., availability of accurate terrain models) that ArcticDEM data can provide for large-scale AGB modelling, it remains critically important for other studies to investigate how ArcticDEM may be used in areas where no DTMs are available as is the case for large portions of the boreal zone.

Sammendrag

Nation-wide Sentinel-2 mosaics were used with National Forest Inventory (NFI) plot data for modelling and subsequent mapping of spruce-, pine-, and deciduous-dominated forest in Norway at a 16 m × 16 m resolution. The accuracies of the best model ranged between 74% for spruce and 87% for deciduous forest. An overall accuracy of 90% was found on stand level using independent data from more than 42 000 stands. Errors mostly resulting from a forest mask reduced the model accuracies by ∼10%. The produced map was subsequently used to generate model-assisted (MA) and poststratified (PS) estimates of species-specific forest area. At the national level, efficiencies of the estimates increased by 20% to 50% for MA and up to 90% for PS. Greater minimum numbers of observations constrained the use of PS. For MA estimates of municipalities, efficiencies improved by up to a factor of 8 but were sometimes also less than 1. PS estimates were always equally as or more precise than direct and MA estimates but were applicable in fewer municipalities. The tree species prediction map is part of the Norwegian forest resource map and is used, among others, to improve maps of other variables of interest such as timber volume and biomass.

Sammendrag

Past: In the early twentieth century, forestry was one of the most important sectors in Norway and an agitated discussion about the perceived decline of forest resources due to over-exploitation was ongoing. To base the discussion on facts, the young state of Norway established Landsskogtakseringen – the world’s first National Forest Inventory (NFI). Field work started in 1919 and was carried out by county. Trees were recorded on 10 m wide strips with 1–5 km interspaces. Site quality and land cover categories were recorded along each strip. Results for the first county were published in 1920, and by 1930 most forests below the coniferous tree line were inventoried. The 2nd to 5th inventories followed in the years 1937–1986. As of 1954, temporary sample plot clusters on a 3 km × 3 km grid were used as sampling units. Present: The current NFI grid was implemented in the 6th NFI from 1986 to 1993, when permanent plots on a 3 km × 3 km grid were established below the coniferous tree line. As of the 7th inventory in 1994, the NFI is continuous, and 1/5 of the plots are measured annually. All trees with a diameter ≥ 5 cm are recorded on circular, 250 m2 plots. The NFI grid was expanded in 2005 to cover alpine regions with 3 km × 9 km and 9 km × 9 km grids. In 2012, the NFI grid within forest reserves was doubled along the cardinal directions. Clustered temporary plots are used periodically to facilitate county-level estimates. As of today, more than 120 variables are recorded in the NFI including bilberry cover, drainage status, deadwood, and forest health. Landuse changes are monitored and trees outside forests are recorded. Future: Considerable research efforts towards the integration of remote sensing technologies enable the publication of the Norwegian Forest Resource Map since 2015, which is also used for small area estimation at the municipality level. On the analysis side, capacity and software for long term growth and yield prognosis are being developed. Furthermore, we foresee the inclusion of further variables for monitoring ecosystem services, and an increasing demand for mapped information. The relatively simple NFI design has proven to be a robust choice for satisfying steadily increasing information needs and concurrently providing consistent time series.

Sammendrag

In this study, we aim at developing ways to directly translate raw drone data into actionable insights, thus enabling us to make management decisions directly from drone data. Drone photogrammetric data and data analytics were used to model stand-level immediate tending need and cost in regeneration forests. Field reference data were used to train and validate a logistic model for the binary classification of immediate tending need and a multiple linear regression model to predict the cost to perform the tending operation. The performance of the models derived from drone data was compared to models utilizing the following alternative data sources: airborne laser scanning data (ALS), prior information from forest management plans (Prior) and the combination of drone +Prior and ALS +Prior. The use of drone data and prior information outperformed the remaining alternatives in terms of classification of tending needs, whereas drone data alone resulted in the most accurate cost models. Our results are encouraging for further use of drones in the operational management of regeneration forests and show that drone data and data analytics are useful for deriving actionable insights. Key words: UAV, DAP, forest inventory, photogrammetry, precommercial thinning, airborne laser scanning.

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Sammendrag

Spruce-fir-beech mixed forests cover a large area in European mountain regions, with high ecological and socio-economic importance. As elevation-zone systems they are highly affected by climate change, which is modifying species growth patterns and productivity shifts among species. The extent to which associated tree species can access resources and grow asynchronously may affect their resistance and persistence under climate change. Intra-specific synchrony in annual tree growth is a good indicator of species specific dependence on environmental conditions variability. However, little attention has been paid to explore the role of the inter-specific growth asynchrony in the adaptation of mixed forests to climate change. Here we used a database of 1790 tree-ring series collected from 28 experimental plots in spruce-fir-beech mixed forests across Europe to explore how spatio-temporal patterns of the intra- and inter-specific growth synchrony relate to climate variation during the past century. We further examined whether synchrony in growth response to inter-annual environmental fluctuations depended on site conditions. We found that the inter-specific growth synchrony was always lower than the intra-specific synchrony, for both high (inter-annual fluctuations) and low frequency (mid- to long-term) growth variation, suggesting between species niche complementarity at both temporal levels. Intra- and inter-specific synchronies in inter-annual growth fluctuations significantly changed along elevation, being greater at higher elevations. Moreover, the climate warming likely induced temporal changes in synchrony, but the effect varied along the elevation gradient. The synchrony strongly intensified at lower elevations likely due to climate warming and drying conditions. Our results suggest that intra- and inter-specific growth synchrony can be used as an indicator of temporal niche complementarity among species. We conclude that spruce-fir-beech mixtures should be preferred against mono-specific forests to buffer climate change impacts in mountain regions.