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
Jørgen A.B. MølmannAbstract
No abstract has been registered
Authors
Abdul Ghafoor Nizamani Geir Torgersen Magdalena EdvardsenAbstract
Green walls are increasingly integrated into building envelopes, but their long-term operation depends on maintaining both living and technical components. This study examines maintenance practices, operating-cost evidence and post-installation responsibility for building-integrated green-wall systems in Norway. An exploratory multiple-case study used six built green-wall projects, four semi-structured interviews with professionals in maintenance, supply, municipal practice and research, and case-specific documentation supplemented by relevant standards, certification and policy material. Operational requirements varied substantially between systems and settings. Exposed outdoor systems followed a marked seasonal cycle involving irrigation shutdown, spring recommissioning, vegetation maintenance and system inspection, whereas the indoor case operated year-round. Across the documented cases and interview examples, maintenance frequencies ranged from approximately every two weeks to one or two scheduled visits per year. Wall-specific cost data were limited and heterogeneous, and operating figures could not be compared reliably per square metre because service scope, access requirements, system complexity, scale and seasonal workload differed between projects. Interviews further indicated that practical operating knowledge often remained with suppliers and specialist providers while longer-term responsibility shifted towards owners and building operators. Maintainable access to technical components, usable operation and maintenance documentation, monitoring arrangements and post-installation service were therefore important during the transition to routine operation. The findings indicate that maintainability is partly determined by decisions made during design and procurement. Irrigation design, seasonal operation, maintenance access, expected operating requirements and transfer of technical knowledge should therefore be considered alongside installation requirements.
Authors
Susanne Zazzera Bjørn Arild Hatteland Silje Maria Midthjell Høydal Ieva Rozite-Arina Inger Elisabeth MårenAbstract
Land-use changes and agricultural intensification have been attributed as the main anthropogenic drivers of declines in insect pollinators. Anthropogenic coastal heathlands are one of the ecosystems that have suffered the most from these intensifications, as traditional management practices have discontinued and only 10% of last century´s coastal heathlands remain. We collected data during the field season of 2022 on pollinator communities with emphasis on bumblebees, in two different habitat types: open and degenerate heathlands in an UNESCO Biosphere Reserve in Western Norway. Here, we aim to get an insight into how pollinator communities may change as more heathlands are left without active management practices like prescribed burning and livestock grazing. Species composition varied between the two habitat types. Degenerate heathlands typically had a higher abundance of some relatively common species in Norway, like B. pratorum, while the red-listed species B. muscorum was recorded exclusively in open heathlands. B. jonellus was more abundant in degenerate sites despite being known to forage on Ericaceae. This may be due to an additional floral diversity and nesting/over-wintering sites here compared to the open sites. Further research should explore potential impacts of landscape characteristics like fragmentation and land-use change on the abundance and diversity of pollinators in heathlands.
Authors
Marit Jørgensen Ragnhild Borchsenius Ellen Elverland Frøydis Gillund Khaled Murad Agha Kauê de Sousa Ievina SturiteAbstract
A stable supply of high-quality forage is essential for the economic sustainability of milk and meat production, the most important agricultural sectors in Norway. Successful forage production relies on selecting species, cultivars, and seed mixtures suited to the diverse agroecological conditions, which vary widely in latitude and altitude. Climate change modifies production boundaries unpredictably. Without on-farm performance data, there is a risk of recommending new varieties or seed mixtures that underperform in farmers' fields. To address this, we propose the tricot method: a participatory, large-scale, and cost-effective testing approach where farmers test new seed mixtures directly in their fields. This approach involves many farmers in conducting small, simple experiments. Each trial consists of an incomplete block with three options out of the total ten options in the trial. Farmers evaluate these options based on predetermined criteria using digital tools. These mini trials, combined with data on management, climate, and soil, are collected into the ClimMob software, which performs statistical analyses and provides feedback. When all data are aggregated, this approach can provide robust statistical results on optimal seed mixtures for various local conditions. This method also strengthens collaboration between researchers, advisors, and farmers, contributing to more sustainable and resilient agricultural practices.
Authors
Marit Jørgensen Ragnhild Borchsenius Ellen Elverland Frøydis Gillund Khaled Murad Agha Kauê de Sousa Ievina SturiteAbstract
No abstract has been registered
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Authors
Jirata Shiferaw Abosse Bekele Megersa Feleke Zewge Ståle Haaland Samuel Assefa Fasil Ejigu EregnoAbstract
No abstract has been registered
Abstract
Longitudinal analysis of a patient’s screening history is fundamental to mammography interpretation. Yet existing deep learning models struggle with the irregular, continuous-time nature of screening data, where patient histories involve unevenly timed multi-view exams paired with evolving textual reports. To address this gap, we introduce Dynamo, a novel multi-modal pretraining dynamic framework for longitudinal mammography with two key innovations to model exam timelines as latent trajectories, i.e., a coarse-fine grained exam-level temporal encoder based on Neural Controlled Differential Equations (Neural CDEs) and a Temporal Visual Question Answering (TVQA) loss for query-driven masked token prediction conditioned on temporal context. We perform comprehensive evaluations on downstream tasks including risk prediction using large-scale datasets (EMBED and CSAW-CC), BI-RADS assessment, and breast density classification. Across all benchmarks, Dynamo achieves overall gains over state-of-the-art vision-only and CLIP-style models, improving both calibration and temporal reasoning. On the EMBED dataset, representative gains include 11.81% relative reduction in Risk Prediction’s Brier Score, 3.59% relative improvement in BI-RADS ϰ, and 2.39% relative improvement in BI-RADS AUC in zero-shot settings. Our code is available at this URL.