Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2026
Authors
Tor MykingAbstract
Invitert foredrag UiB i forbindelse med tildeling av æresdoktorat til Paul Smith, BCGI
Authors
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 TognettiAbstract
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.
Abstract
Addressing the issues of soil degradation and declining crop quality caused by the excessive application of chemical fertilizers, this study prepared a cyanobacterial–bamboo growth elicitor (CBGE) from cyanobacterial and bamboo powder through acid-hydrolysis technology and then co-applied with cyanobacterial biochar (CB). Five pot treatments were established: control (CK), root-applied CB (BR), soil-applied CB (BF), root-applied CBGE-modified CB (LZBR), and soil-applied CBGE-modified CB (LZBF). The results demonstrated that CBGE was rich in essential macronutrients (N, P, K) and bioactive substances including polysaccharides and dipeptides, while cyanobacterial biochar, with its abundant hydroxyl/carboxyl groups, showed strong adsorption of CBGE organic components. During cultivation, the LZBR treatment exhibited comprehensive advantages in improving rhizosphere soil organic carbon, humic substances, and cation exchange capacity. Environmental risk assessment indicated that soil heavy metal levels and associated health risks were low across all treatments, with no obvious short-term adverse effects observed. Soil application (BF, LZBF) maintained Bradyrhizobium dominance, whereas root application (BR, LZBR) enriched Chryseobacterium and Pseudomonas, driving organic matter mineralization and carbon‑nitrogen cycling. Moreover, functional predictions suggested that CBGE addition has the potential to reduce the abundance of functional genes associated with human pathogens, animal parasites, and plant pathogens. The LZBR treatment achieved balanced nutrient utilization through microbial functional network reconstruction, yielding the highest soybean whole-plant biomass (65.8 g/plant, +10.9% vs CK) and grain crude protein (210.56 g/kg, +33.3% vs CK). In conclusion, under the tested pot conditions, the application strategy of LZBR exhibited promising potential to synergistically improve soil health and crop quality.
Abstract
Increasing disturbance pressure from the spruce bark beetle (Ips typographus) challenges the reliability of timber supply in managed boreal forests. This study evaluates alternative optimization approaches for integrating bark beetle damage into regional forest planning in southern Norway. Using a simulation and optimization process, we compare three alternative optimization approaches: (i) deterministic linear programming ignoring disturbance risk, (ii) robust optimization protecting even-flow constraints against income variability, and (iii) stochastic programming using probabilistic disturbance scenarios. Two planning objectives were examined: maximizing the net present value (NPV) alone, and maximizing NPV subject to a minimum periodic timber harvest requirement. When only NPV was maximized, differences among the solutions were minor. The stochastic solution yielded a slightly higher expected NPV (0.1%) through earlier harvesting. Approximately 22% of deterministic scenarios outperformed the stochastic solution, highlighting the limited economic gains when focused on a purely financial objective. When prioritizing a targeted periodic timber supply the deterministic solution resulted in systematic harvest shortfalls under realized disturbances while the robust solution reduced shortfalls by increasing periodic harvests. The stochastic formulation substantially improved supply reliability, reducing expected harvest shortfalls from 1.9% (deterministic) and 1.1% (robust) to nearly 0% for the stochastic solution, albeit with a moderate reduction in the expected NPV. Results demonstrate that the value of incorporating disturbance uncertainty depends on management objectives. While economic efficiency alone provides limited incentive for risk integration, maintaining stable timber supply under increasing disturbance pressure benefits substantially from stochastic planning approaches.
Authors
Janine Schweier Raffaele Spinelli Francesco Latterini Natascia Magagnotti Rodolfo Picchio Stelian A. Borz Csongor Horvath Leo G. Bont Stephan HoffmannAbstract
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.
Abstract
Neural Radiance Fields (NeRF) have been widely adopted for reconstructing high-quality 3D scenes from 2D RGB images. However, achieving accurate 3D object segmentation within these reconstructed scenes remains challenging. Existing NeRF-based segmentation methods either rely on post-processing (SA3D), which produces noisy point clouds due to the absence of density field optimization, or employ joint training with additional segmentation heads (FruitNeRF), which can lead to suboptimal performance due to conflicting learning objectives. In this work, we propose InvNeRF-Seg (Input-substitution NeRF for Segmentation), a two-stage fine-tuning strategy for 3D object segmentation that preserves the original NeRF architecture and loss function entirely. We first train a standard NeRF on RGB images and then fine-tune it using 2D segmentation masks formatted as RGB-like inputs, without introducing any architectural modifications or additional loss functions. This input-substitution approach reshapes the density field to align with object regions while suppressing background density. We validate InvNeRF-Seg through comprehensive ablation studies examining the roles of density and color MLPs, loss function choices, and training strategies. Field density analysis reveals consistent semantic refinement: densities of object regions increase while background densities are suppressed. Experiments on synthetic fruit datasets and real-world soybean imagery demonstrate that InvNeRF-Seg produces cleaner 3D segmented point clouds compared to both SA3D and FruitNeRF, enabling more accurate downstream object counting. The method is further validated on a self-collected soybean dataset to demonstrate its applicability in real-world agricultural scenarios.
Abstract
In Norway, agroclimatic zones (ACZs) are a valuable tool for national analyses in subject areas concerning the optimized management of agricultural land resources. However, current Norwegian ACZs have been criticized for having an outdated standard climate normal (1931–1960), a limited representation of the local climatic variation, a lack of important model parameters, and weak methodological documentation. Therefore, this paper presents new ACZs for Norway that address these weaknesses. The most significant methodological updates are the use of the standard climate normal of 1991–2020, additional weather data variables, the downscaling of weather data to 250 m hexagons, and the incorporation of phenological crop models for spring wheat, spring barley, and forage grass. The grass model was calibrated with the number of grass harvests at research stations, while the grain models were calibrated with subsidy claim data. The modeled zones for the three crops were combined into the general ACZs. Example maps of the crop zones and new ACZs for the selected regions and the whole country are presented. The new ACZs are more robust, agronomically relevant, and better aligned with the current climatic conditions in Norway. The deliberate exclusion of factors other than climate ensures the new ACZs’ national comparability and their applicability in policy development, land-use planning, climate adaptation, and agronomic assessments at the national scale.
Authors
Tor MykingAbstract
No abstract has been registered
Authors
Elvira Castillo-Almansa Rubén G. Mateo Mercè Galbany-Casals Carme Blanco-Gavaldà Lucía D. Moreyra Cristina Roquet Christian Brochmann Abel Gizaw Seid Desalegn Chala Alfonso Susanna Juan A. CallejaAbstract
Climate change poses a significant threat to the Afrotemperate flora of the Eastern Afromontane Biodiversity Hotspot, particularly to species confined to high-elevation ecosystems such as those found on the African sky islands. This study evaluates the vulnerability of tropical Afroalpine and Afromontane Helichrysum taxa (Compositae) by assessing their climatic niches and predicting future shifts in distribution, range fragmentation, and altitudinal limits under climate change scenarios. Occurrence records for 14 taxa (eight Afroalpine and six Afromontane) were obtained from recent field campaigns, biodiversity databases and herbaria. Ensemble ecological niche models were developed combining Generalized Linear Models, Generalized Boosting Models, and Random Forest. Taxon-specific bioclimatic variables were selected after correlation analyses. The models were calibrated using current climate data and projected using the PSL-CM6A-LR and MRI-ESM2.0 climate models with both low- and high-emission scenarios. The results show that most Afrotemperate taxa currently occupy only a portion of their climatically suitable habitat, often in geographically distant areas. Future projections indicate significant range contractions and increased fragmentation. Afroalpine taxa could lose 50–66% of their suitable habitat, while Afromontane taxa could decline by 53–79%. Suitable areas were estimated to shift upwards in elevation, with limited potential for colonization of new areas, and with no significant latitudinal or longitudinal shifts. These findings represent the first continental-scale assessment of the impact of climate change on the Afrotemperate flora using ecological niche modelling. The projected climate-induced range losses and increased habitat fragmentation, in particular combined with increasing anthropogenic pressure in this region, highlight the urgent need for targeted conservation actions.
Abstract
This paper describes from a methodological point of view a recent attempt to test how Historic Landscape Characterisation (HLC) as developed with respect to the British landscape can be adapted and applied to the different and distinctive landscapes of a Norwegian upland territory, on the edges of the Hardangervidda plateau. This is an area characterised by mobility, close nature-culture interactions, and practices such as summer farming and short-distance transhumant practices. The research was carried out by two Norwegian agencies – NIKU and NIBIO – as part of a larger project known as PARKAS designed in the context of green transitions to promote better-integrated and publicly-responsible management and safeguarding of protected areas. We briefly describe the origins and principles of HLC in Britain, and then at greater length assess the suitability of HLC in Hardangervidda and key ways by which the approach would require modification and adaptation. A concrete method for a Hardangervidda HLC – and a suitable high-level classification – is identified and discussed.