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
Abstract
Viroids are the smallest known nucleic acid‐based infectious agents of plants and consist of single‐stranded, circular, non‐coding RNAs that can cause significant crop diseases. The potato spindle tuber viroid (PSTVd), a model Pospiviroidae member, severely impacts Solanaceous hosts like potato and tomato, causing substantial yield reductions. Its 359‐nucleotide, rod‐like genome, with five functional domains, mediates nuclear replication, systemic movement via plasmodesmata and phloem, and evasion of host RNA silencing. High mutation rates generate diverse quasi‐species, enhancing adaptability. Recent multi‐omics studies reveal PSTVd reprogramming of host transcriptomes, epigenomes, and metabolomes, disrupting defence, hormone signalling, and photosynthesis. Within the plant holobiont, PSTVd modulates interactions with viruses, notably via RNA‐directed DNA methylation, and may affect rhizosphere microbial communities indirectly via changes in host physiology, an area that remains poorly resolved. This review synthesises advances in PSTVd structure, infection mechanisms, and holobiont interactions, highlighting its role in uncovering RNA‐mediated pathogenesis principles. Key knowledge gaps persist regarding host factors facilitating systemic spread and interactions with other organisms, such as microbial communities. Ongoing PSTVd research is essential to address this gap and guide strategies for viroid‐resistant crops and sustainable control.
Abstract
Collection, processing and provision of comprehensive geometric information of forest roads is decisive for its technical classification to facilitate sustainable timber supply chains. An automized classification system based on the mobile proximal sensor platform RoadSens was developed, applied and validated through a case study approach in Eastern Norway. Six sample roads of various vegetation stages were surveyed through RoadSens and complemented through sampled total station measurements for validation purposes. The determined geometric parameters road slope, curvature and width were used for technical classification following the national forest road standard. Road width was identified as the main constraint in meeting the standard, resulting in a general downgrading of the sampled roads according to its technical class. The results showed a root mean square error (RMSE) ranging from ±0.53 to 1.50 m (12–33%) depending on the road and vegetation stage compared to the validation data. Despite these accuracy constraints, the application case study already indicates a general need for improvement of road data acquisition and updating of associated databases. The study underscores that, despite the challenges and limitations, there is a clear need for an automated sensing and classification system, which offers a cost-effective alternative to manual surveying and requires less specialized expertise.
Abstract
Aim Four different grassland types of varying land-use intensity and history were investigated for changes in plant species composition and richness over a 7- to 10-year period. Shifts in species occurrence frequencies and species-specific indicator values for nectar production were analyzed to assess how vegetation changes may influence the availability of floral rewards. Location Norwegian mainland. Methods We utilized survey (2004–2008) and resurvey (2011–2018) data from the Norwegian Monitoring Program for Agricultural Landscapes, examining vegetation in managed and unmanaged grasslands from 538 permanent vegetation plots within 97 monitoring squares across Norway. Using species-specific indicator values for nectar production, we tested how compositional changes in vascular plant communities are reflected in the occurrence frequency and cover of pollen- and nectar-providing plants. Results Grassland species composition has slightly shifted toward communities more dominated by later successional species, particularly those associated with shadier and wetter conditions. Major changes in the occurrence frequencies of individual species suggest a decline in pollen and nectar production. Specifically, 29 of 40 species (72.5%) that showed significant decreases in frequency were flowering plants important for pollinators. Across all grassland types, the average cover of pollen- and nectar-producing plants has declined over time, indicating a reduction in floral resources available to pollinating insects. Conclusions Our findings indicate a gradual transition in grassland habitats toward conditions that may be less favorable to pollinators, as reflected by changes in species occurrence frequencies and plant cover. Additionally, plant species associated with moist environments are likely to increase in abundance under continued climate change. This study highlights the value of systematic grassland monitoring within agricultural landscapes as an effective tool for detecting vegetation changes, even over short time spans. Such monitoring supports timely decision-making and the implementation of targeted management strategies to preserve ecologically and economically important habitat types.
Abstract
This study quantified field-scale nitrogen (N) and phosphorus (P) removal by crop harvests, balances, and use efficiencies in 14 grass fields in the Timebekken catchment. Measurements of grass yields, nutrient concentrations, manure composition, and soil properties across multiple fields and farms were combined with survey data. Results showed large variation across farms and fields in day matter yield, nutrient inputs, removals, balances, and use efficiencies. Annual dry matter yield ranged 6,830–12,800 kg ha-1 (mean 9,010 kg ha-1) in 2024 and 7,480–12,130 kg ha⁻¹ (mean 9,800 kg ha⁻¹) in 2025. In 2024, nutrient inputs as mineral fertilizers and manure ranged 169–362 kg N ha⁻¹ (mean 240 kg ha⁻¹) and 23–57 kg P ha⁻¹ (mean 40 kg ha⁻¹). Corresponding nutrient removal ranged 150–303 kg N ha⁻¹ (mean 220 kg ha⁻¹) and 22–40 kg P ha⁻¹ (mean 29 kg ha⁻¹). Nutrient balances ranged from −111 to +182 kg ha⁻¹ (+14 kg ha⁻¹) for N and from −14 to +35 kg ha⁻¹ (12 kg ha⁻¹) for P. Nutrient use efficiency (input∕removal) ranged 50%–166% (mean 100%) for N and 38%–160% (mean 80%) for P. Overall, results indicate consistent management within farms but clear differences between farms, and therefore substantial potential for improving fertilizer and manure precision while maintaining yields. Phosphorus yield exceeded 27 kg ha-1 in several fields, in some 35 kg ha-1, which are the maximal allowed fertilizer limits from 2033. This substantiates farmers’ concerns about these limits being too low, yet average P inputs still exceeded crop demand. Despite lower topsoil P-AL in 2023 than in 2005, soil P status remained high, likely sustaining yields under stricter P limits. Elevated subsoil P highlights long-term loss risks and the need for targeted mitigation measures in hotspot areas. The study also calls for more monitoring of manure nutrients, yields, and soil P properties.
Authors
Tore Flatlandsmo Berglen Christine Forsetlund Solbakken Hilde Thelle Uggerud Jenny Lovisa Alexandra Jensen Guttorm Christensen Tone Roksvåg AandahlAbstract
Did you know that stairstep moss can be used as a sampler for air pollution? Researchers at NILU have collected this kind of moss on several occasions and examined it for metals and other pollutants.
Authors
Belachew Gizachew ZelekeAbstract
Tropical forests, despite their critical environmental and socio-economic roles, remain highly vulnerable to deforestation, forest degradation, and climate-related disturbances. There is a growing demand for robust and transparent forest monitoring systems, particularly under REDD+, the Paris Agreement’s Enhanced Transparency Framework (ETF), and emerging climate-finance mechanisms. Conventional approaches based on field inventories and traditional remote sensing are often constrained by limited or uneven field data, persistent cloud cover, complex forest conditions, and limited institutional and technical capacity. This review examines how artificial intelligence (AI) and machine learning (ML) are being integrated into remote sensing–based tropical forest monitoring to address these structural constraints. Using a semi-systematic synthesis of peer-reviewed studies, complemented by operational platforms and grey literature, the review assesses AI/ML approaches, remote sensing datasets, and applications relevant to national and large-scale monitoring. Evidence is synthesized across five analytical dimensions: AI/ML model families and workflows, multi-sensor datasets and training resources, operational monitoring platforms, application domains (including deforestation, degradation, and biomass/carbon estimation), and cross-cutting technical, institutional, and governance barriers. The review finds that AI/ML-enabled remote sensing, particularly those combining optical, radar, and LiDAR time series within cloud-based platforms, has substantially improved the automation, scalability, and speed of tropical forest monitoring. However, effective and equitable adoption remains constrained by limitations in training and validation data, dependence on proprietary platforms and data, uneven technical capacity, and unresolved governance and ethical challenges. Emerging solutions, including open and representative training datasets, platform-agnostic processing infrastructures, long-term capacity building, and inclusive data-governance frameworks, are identified as critical enablers of credible and nationally owned AI/ML-enabled forest-monitoring systems. The review highlights that AI/ML can play a transformative role in supporting climate mitigation, biodiversity conservation, and informed decision-making. This potential, however, depends on transparent data governance arrangements, long-term capacity building, and platform-agnostic infrastructures that support national ownership.
Authors
Karen Ane Frøyland Skjennum Jan Mulder Gijsbert Dirk Breedveld Thomas Hartnik Nicolas Estoppey Erlend Grenager SørmoAbstract
The present study investigates the long-term immobilization efficiency of biochar on target per- and polyfluoroalkyl substances (PFAS) and precursors in well-drained soils contaminated by aqueous film-forming foam (AFFF) (Ʃ27PFAS = 1624 ± 276 µg/kg) over 2 years. The total oxidizable precursor (TOP) assay revealed a large precursor reservoir in the soil. Fifteen outdoor field-scale columns were packed with contaminated soil (48 kg) without (control columns, triplicates) and with biochar amendments: Three sewage sludge-based biochars were homogeneously mixed into the soil at a 1% (w/w) dose in triplicate columns. One of the biochars was additionally applied as a barrier at the column base (1% w/w) in a separate set of columns. The best-performing biochar immobilized long-chain PFAS by 91.0 ± 35.0% and short-chain PFAS by 96.7 ± 32.9%, possibly due to a well-developed porosity. Compared to the control columns, the fluctuating PFAS leaching were negligible in columns amended with the best-performing biochar, but the immobilization efficiency of short-chain PFAS decreased after one year (from 97.8% to 74.2%). Applying biochar as a barrier was two times more effective than homogenous mixing, and the effect was most pronounced for long-chain PFAS. Our findings suggest that biochar may immobilize precursors, notably CF3-CF5 precursors, to the same extent or better than their typical target perfluoroalkyl acids transformation products. More research is, however, needed to confirm these trends. Going beyond simple lab experiments, this study suggests that biochar is a promising solution for PFAS remediation and brings the technology closer to field application.
Authors
Ulrika Jansson Asplund Damian Petkovic Karlsen Anne Krag Brysting Rune Halvorsen Håvard Kauserud O. Janne Kjønaas Johan AsplundAbstract
After five centuries of selective cutting in the boreal Fennoscandian forest there was a shift to stand replacing harvest (clear-cutting) in the 1940s. This shift altered light conditions experienced by the forest understory profoundly, from semi-open conditions to light regimes altering between very open in the recently clear-cut forest to very dense some decades later. In this study, we investigated the long-term effects of clear-cutting on vascular plants and bryophytes. Our study system consists of twelve pairs of mesic spruce forests in Southeastern Norway, with a previously clear-cut, but now mature stand and a near-natural forest within each pair. Vascular plant cover was almost twice as high in the near-natural than in the mature, previously clear-cut forest sites, despite similar standing volume and light availability. Overall, previous clear-cutting did not have long-term effects on species richness, but vascular plant species richness was more responsive to soil Ca, a key driver of plant community composition, in the near natural forests. Likewise, the community composition showed a stronger association with soil chemistry in near-natural forests, suggesting that management alters natural drivers of understory communities. The long-lasting effects of clear-cutting was distinct for understory cover and mainly driven by common species such as the keystone species Vaccinium myrtillus, which was substantially less abundant in previously clear-cut stands.
Authors
Ming Yu Sebastian Kepfer-Rojas Yamina Micaela Rosas Teresa Gómez de la Bárcena Inger Kappel Schmidt Per Gundersen Ludovica D'Imperio Carsten W. Mueller Lars VesterdalAbstract
Afforestation of agricultural land is widely promoted as a nature-based solution to enhance carbon (C) sequestration and mitigate atmospheric CO2 levels. However, the temporal dynamics of soil organic carbon (SOC) after afforestation, particularly in mineral soils, remain uncertain due to the complex interaction of biogeochemical processes and their spatial variability. We investigated changes in SOC sequestration over five decades of afforestation on former cropland by extending the chronosequence approach with three repeated soil inventories in oak (Quercus robur L.) and Norway spruce (Picea abies (L.) Karst.) stands. Aboveground biomass C stocks were also quantified to evaluate the contribution of SOC to post-agricultural ecosystem C stocks. Forest floor C stocks increased rapidly in the early years and stabilized after approximately three decades, with consistently higher accumulation under Norway spruce than oak. In contrast, mineral SOC stocks in 0-25 cm depth increased with forest age by 0.18 ± 0.06 Mg ha−1 yr−1 under oak and 0.44 ± 0.07 Mg ha−1 yr−1 under Norway spruce. These contrasting trends in forest floor and mineral soil indicated a shift in C source-sink strength over time and between species. After 50 years of afforestation, total ecosystem C stocks in afforested stands reached up to 75% of those in a 200-year-old forest, with most new C stored in biomass (84-86%), followed by mineral soil (10-11%) and forest floor (4-5%). Despite higher sequestration of new C in Norway spruce stands, the relative distribution across ecosystem compartments was similar between tree species.
Authors
L. Duncanson P. M. Montesano A. Neuenschwander A. Zarringhalam N. Thomas D. M. Minor M. A. Wulder J. C. White E. Guenther T. Feng V. Leitold S. Hancock J. Armston Stefano Puliti A. I. Mandel S. Shah C. Silva M. Purslow J. Bruening Johannes Breidenbach Erik Næsset Svetlana Saarela N. Hunka J. R. Kellner S. P. Healey D. Schepaschenko J. Wallerman C. S. R. Neigh N. Carvalhais R. DubayahAbstract
Forest aboveground biomass Density (AGBD) maps provide important constraints on climate and carbon cycle models and enable the long-term monitoring of carbon stocks. NASA's latest spaceborne lidar instruments provide unprecedented observations of forest structure that are used to compile spatially continuous, locally trained maps of circa 2020 AGB density and stock. To address a geographical limitation of the International Space Station deployed GEDI instrument, herein we map high northern latitude forests with a fusion of NASA's ICESat-2 mission, Harmonized Landsat Sentinel-2 (HLS), and Copernicus GLO-30 topographic data. We report a domain-wide estimate for boreal forests of 72.96 +/− 0.61 Pg AGB. Combining these maps with those of tropical and temperate forests from GEDI products provides a global estimate of 2020 biomass stocks of 593.49 +/− 11.47 Pg AGB. We analyze biomass means and totals across the boreal domain in different land cover types, slope classes, and ecoregions. We compare these products to national estimates of AGB stocks for high latitude countries, finding good general agreement between national reports and EO-based estimates, particularly for countries with robust National Forest Inventories (NFIs) and boreal forests, while underestimation of high AGBD in tall, dense forests remains a challenge for AGBD mapping. Satellite products can be used to support wide area estimation of aboveground biomass, and the maps described here provide insights into carbon stocks, patterns, and dynamics at scales relevant to forest management. These open access data products serve as a baseline to assess future changes associated with drought, fire, insects, deforestation, and degradation.