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.
2026
Forfattere
Jo Jorem AarsethSammendrag
Intervju om gås og problematikk rundt beiteskader og avføring på badestrand
Sammendrag
Hogsten i enkelte regioner bryter med over hundre års utvikling.
Forfattere
Tor MykingSammendrag
Invitert foredrag UiB i forbindelse med tildeling av æresdoktorat til Paul Smith, BCGI
Forfattere
Michele Torresani Vítězslav Moudrý Christopher R. Hakkenberg Vojtěch Barták Duccio Rocchini Stefano Puliti Paweł Hawryło Krzysztof Stereńczak Alexander Cotrina-Sanchez Gabriele Giuseppe Antonio Satta Luca da Ros Patrick Kacic Roberto TognettiSammendrag
Monitoring forests globally through the assessment of structural characteristics is indispensable in times of increasing disturbances and biodiversity loss. The recent development of a 1-meter resolution Global Canopy Height Map by Meta and the World Resources Institute (Meta/WRI CHM) offers new opportunities for large-scale forest structure analysis. However, its reliability for estimating key forest structural metrics in selected forest sites of the Italian Alps remains largely untested. In this study, we compared estimates of canopy cover, mean and maximum canopy height, tree count, and crown size computed from the Meta/WRI CHM with the corresponding metrics computed from airborne laser scanning (ALS)-based CHMs across five forested sites in Alpine ecosystems representing diverse forest structures, species compositions, and management practices. Our results show that the Meta/WRI CHM provides reliable estimates of canopy cover (R = 0.82–0.92, RMSE = 8%–15%) and, to some extent, mean canopy height (R = 0.69–0.85, RMSE = 2.2–2.9 m). However, it substantially underestimates maximum canopy height and fails to reliably estimate tree count, positions, and crown size, overestimating the number of trees by 200–750 per hectare. In addition, the quality of the evaluated metrics estimates varied with respect to topographic gradients (i.e., slope, aspect, and altitude). Our findings define clear application boundaries for the Meta/WRI CHM in Alpine forest environments: while the product can support stand-level estimates of canopy cover and mean canopy height, it remains unsuitable for estimating maximum canopy height and individual-tree-level metrics such as tree count, tree position, and crown size. Future efforts should focus on refining global CHMs to improve accuracy and expand their applicability for forest monitoring.
Forfattere
Janine Schweier Raffaele Spinelli Francesco Latterini Natascia Magagnotti Rodolfo Picchio Stelian A. Borz Csongor Horvath Leo G. Bont Stephan HoffmannSammendrag
Purpose of review This review traces the development of mini forestry crawlers (MFCs) from earlier small-scale skidding machines to modern remote-controlled tool carriers, and evaluates their current applications, technological characteristics, operational performance, safety, soil impact, ergonomics, and automation potential. Recent findings Recent studies show that MFCs have evolved from simple extraction-oriented machines into multifunctional platforms whose suitability depends on machine class, task–machine matching, site conditions, and work organisation. Field and bench studies report productivity, soil impacts, operator workload, remote-controlled felling performance, non-harvesting applications, and early automation functions. Summary Mini forestry crawlers are most effective in constrained-access settings and in tasks that align with their limited payload while benefitting from high manoeuvrability, remote operation, and multifunctionality. Their advantages are therefore conditional on careful deployment, particularly with respect to soil moisture, turning intensity, traffic frequency, and operator workload. Future evaluations should adopt integrated performance metrics that jointly assess productivity, soil response, and human workload under realistic operating conditions.
Foredrag – Spotlight on genetic diversity - can arboretums take a broader responsibility?
Tor Myking
Forfattere
Tor MykingSammendrag
Det er ikke registrert sammendrag
Sammendrag
Introduction Leaf area index (LAI) estimation is sensitive to sensor field of view (FOV), within-plot spatial heterogeneity, and sampling layout. Because LAI influences canopy radiation transmission, microclimate and vegetation–atmosphere exchange, robust field estimation is important for biometeorological and ecosystem research. Methods We evaluated these effects in mature Norway spruce [ Picea abies (L.) H. Karst] stands in the Czech Republic across 15 sites at elevations of 407–1,019 m a.s.l., using a combined gap-fraction approach based on LAI-2200 PCA measurements and digital hemispherical photography. At each site, a measured 9 × 9 grid of 81 below-canopy measurement points with 2-m spacing was used as an operational within-plot benchmark for mean optically derived LAI and spatial structure. Monte Carlo subsampling was then used to compare how reduced layouts, including random, row-wise, column-wise, block-wise, and spatially balanced block–row–column layouts, reproduced the full-grid benchmark mean. Results Narrower FOVs produced higher stand-level optically derived LAI estimates and greater within-plot variability. The full grids also showed directional spatial structure, with stronger autocorrelation along the north–south column direction than along the west–east row direction, although this contrast weakened under the narrowest FOV. Reduced layouts with more even spatial coverage outperformed random sampling. The spatially balanced block–row–column layout performed most consistently, whereas the row-wise layout provided little improvement. Approximately 25–36 well-distributed below-canopy measurements were sufficient to keep reduced-layout LAI deviations within 0.15 m 2 m −2 of the full-grid benchmark, whereas 7–9 measurements were enough to remain within 5% of this benchmark in most stands. Discussion Spatially balanced sampling can therefore improve the robustness and efficiency of stand-level optically derived LAI estimation, with relevance to forest biometeorology, ecosystem monitoring, and the validation of satellite-derived LAI products.
Forfattere
Simone Bianchi Cornelia Roberge Johannes Schumacher Johannes Breidenbach Kari T. Korhonen Harri MäkinenSammendrag
Sustainable forest management needs growth models. Few studies have explored regional models in Fennoscandia despite similar conditions and challenges. We examined the feasibility of regional models for basal area increment of Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), and birch (Betula pendula Roth. and Betula pubescens Ehrh.). We compiled over 880,000 growth observations and estimated competition indices, climate variables, and site fertility classes by integrating data from recent National Forest Inventories (2004–2023) in Finland, Norway, and Sweden. Using Random Forest models, we identified the main growth drivers across countries (tree size, accumulated temperature sum, latitude, competition, and site fertility), with minor differences in their responses across countries. However, periodic NFI measurements could not capture the effect of additional climate variables. Using species-specific nonlinear mixed models, we demonstrated that predictive regional models can be fitted using those main drivers. Although we achieved only moderate predictive performance (Weighted Absolute Percentage Error of 45–71%, depending on the species and country), there were no residual geographical biases. The results confirm the potential of Fennoscandian growth models to address shared challenges. Future work should better account for site fertility, integrate process-based approaches for climate responses, and carry out independent validation.
Forfattere
Geir Wæhler Gustavsen Philip Bester Van Niekerk Jonas Niklewski Christian Brischke Gry AlfredsenSammendrag
This cross-country study examineed perceptions of maintenance for coated wooden cladding in residential buildings across Norway, Sweden, and Germany. As timber cladding gains popularity in European homes, understanding expectations around cleaning, recoating, and replacement intervals becomes increasingly important. An online survey gathered responses from over 3,000 participants aged 18–89, randomly selected from representative regional panels in each country. The survey focused on the perception of maintenance practices and intervals, while also collecting data on personality traits, risk aversion, and socioeconomic background. Perceived maintenance practices for coated timber cladding differed across countries, but individual characteristics were generally more influential than national context. Most respondents accepted longer cleaning intervals than recommended, while their preferences more closely aligned with guidelines for recoating. Acceptance of replacement intervals varied markedly by country. Longer acceptable maintenance intervals were associated with a higher preference for uncoated cladding, particularly in Germany and Sweden. Younger age, urban residence, limited experience, and selected demographic and personality traits were linked to more intensive maintenance preferences.
Forfattere
Binbin Xiang Maciej Wielgosz Stefano Puliti Kamil Král Martin Krůček Azim Missarov Rasmus AstrupSammendrag
The segmentation of forest LiDAR 3D point clouds, including both individual tree and semantic segmentation, is fundamental for advancing forest management and ecological research. However, current approaches often struggle with the complexity and variability of natural forest environments. We present ForestFormer3D, a new unified and end-to-end framework designed for precise individual tree and semantic segmentation. ForestFormer3D incorporates ISA-guided query point selection, a score-based block merging strategy during inference, and a one-to-many association mechanism for effective training. By combining these new components, our model achieves state-of-the-art performance for individual tree segmentation on the newly introduced FOR-instanceV2 dataset, which spans diverse forest types and regions. Additionally, ForestFormer3D generalizes well to unseen test sets (Wytham woods and LAUTx), showcasing its robustness across different forest conditions and sensor modalities. The FOR-instanceV2 dataset and the ForestFormer3D code are publicly available at https://bxiang233.github.io/FF3D/.