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.
2025
Abstract
A survey was conducted in Porsangmoen-Halkavarre shooting and training range. This report summarizes the results of exploratory fishing and extensive environmental surveys carried out in 2024 in five lakes: Store Ikkasvann (Stuorra Inggasjávri), Lille Ikkasvann (Unna Inggasjávri), almijervi (Coalbmejávri), Lille Russevann (Bajit Russojávri) and Store Russevann (Stuorra Russojávri), as well as in Ørretbekken, an important spawning stream for the trout (Salmo trutta) population in Store Ikkasvann (Stuorra Inggasjávri). The study includes catch-per-unit-effort (CPUE, species distribution, growth and biometrics), water chemical and physical analyses, sediment studies, as well as observations of macrophytes and habitat conditions. The aim was to document variations in fish communities and ecological status, and to identify possible environmental challenges that may affect future management and conservation of the resources in the area. The findings show that trout predominate in the shallow areas (0–6 m deep) of Store Ikkasvann (Stuorra Inggasjávri) and Lille Ikkasvann (Unna Inggasjávri), while char (Salvelinus alpinus) is more abundant in the deeper water layers. In Salmijervi (Coalbmejávri), the species distribution is more balanced, while Store Russevann (Stuorra Russojávri) and Lille Russevann (Bajit Russojávri) are characterized by a higher density of char. Minnow (Phoxinus phoxinus) was found in three of the lakes, especially in shallow areas, which can affect traut grawth thraugh competition and predation. Biometric analyses indicate that traut graw fastest in Lille Russevann (Bajit Russojåvri) (with 5.1 cm annual grawth) and slowest in Salmijervi (Coalbmejåvri) (4.3 cm), while char maintains a steady growth of about 5 cm per year. Colour differences in fish meat·suggest that a high percentage of traut from Store Russevann (Stuorra Russojåvri) and Lille Russevann (Bajit Russojåvri), and both traut and char from Store Ikkasvann (Stuorra Inggasjåvri) and Lille Ikkasvann (Unna Inggasjåvri) have a more reddish color, possibly due to a higher intake of crustaceans. The parasite occurrence in traut and char was generally low, except for fish in Salmijervi (Coalbmejåvri), where increased bird activity may have led to higher infection rates. Water chemistry measurements showed that most water bodies have good water quality with low concentrations of lead, same copper and zinc, relatively low nutrient concentrations, a high con tent of calcium carbonate and thus stable pH values (7-8). At the same time, the analyses oflake sediments indicate good condition for lead (which is an EU priority substance), but occasionally poor to very poor status for copper and chramium, as well as high concentrations of nickel. Nickel, copper and chramium occur naturally in minerals in the catchment area. A mapping of bioaccumulation of heavy metals could be done to get an idea of base line concentrations in fish in the area. Observations of heteratraphic grawth increasing down the watercourse, possibly associated with sewage discharges or other organic loads, underscore the need for DNA-based source tracing to precisely define the sources of pollution. The traut stream, which maintains high densities of traut and is in very good ecological condition, must be managed with special consideration, where raad construction and other activities must be thoraughly assessed with risk analyses, strict mass management and sediment control. Overall, the report shows that the ecological water quality is good to very good, and fish stocks in most of the lakes have good spawning and grawth conditions, with same regional differences related to habitat use and grawth conditions. The management should adopt a holistic, catchment-oriented approach to new interventions in the area, with a fous on minimising the impact on water bodies and ensuring sustainable use of resources. More detailed suggestions are mentioned in the report, which forms a basis for further monitoring and enviranmental measures to preserve biodiversity and , maintain the good ecological status of the entire area.
Authors
Kannan Mohan Sabariswaran Kandasamy Tamilselvan Pachiannan Krishnaswamy Ezhilan Vivekanandan Ramya Preethi Surendran Abirami Ramu GanesanAbstract
The search for renewable and sustainable energy sources is increasing worldwide, urges the identification of biofuels from insects. The possibility of producing biodiesel and biogas from insects has gained significant attention as a better alternative to conventional fossil fuels. This approach is due to the presence of high lipid and protein contents of certain insect species, including black soldier fly larvae, mealworms and crickets, which can be cultivated on organic waste streams. Insects such as black soldier flies and mealworms require minimal water and land for cultivation, and their waste-based diet reduces environmental impacts while promoting waste valorization compared to traditional biofuel feedstocks. Insects’ lipids can be extracted and converted into biodiesel through transesterification, while the remaining biomass, rich in proteins and other organic materials, can be anaerobically digested to produce biogas. This dual production pathway not only maximizes energy output but also generates valuable by-products, such as residual organic fertilizer. This review emphasizes the potential of insect-based biofuel conversion and its recent advances. The challenges in scaling up the process, and optimizing yields are critically evaluated. The environmental and technological parameters of the entire biofuel production process from insects are discussed in terms of their sustainability aspects.
Authors
Adam Eindride Naas Trond Simensen Lasse Torben Keetz Ingrid Vesterdal Tjessem Anders Bryn Rune Halvorsen Peter Horvath Ida Marielle Mienna Olav Skarpaas Joachim Paul Töpper Vigdis Vandvik Liv Guri Velle Catharina Caspara VloonAbstract
No abstract has been registered
Authors
Zhibo HamborgAbstract
No abstract has been registered
Authors
Åsgeir R. Almås Susanne Eich-Greatorex Trine Aulstad Sogn Tomasgaard Jan Mulder Manoj Kumar Pandey Vincent Dauby David Powlson Roberta Farina Jeroen Watté Daniel Rasse Nathalie BjørnebyAbstract
The soil organic carbon (SOC) Think Tank has identified and ranked the ten most critical knowledge gaps affecting SOC stocks, based on stakeholder input and iterative validation across multiple events. These prioritized gaps reflect new insights into land use impacts, policy influences, and methodological needs, forming a foundation for targeted research and innovation.
Authors
Junbin Zhao Cornelya Klutsch Hanna Marika Silvennoinen Carla Stadler David Kniha Runar Kjær Svein Wara Mikhail MastepanovAbstract
ABSTRACT Drained cultivated peatlands are recognized as substantial global carbon emission sources, prompting the exploration of water level elevation as a mitigation strategy. However, the efficacy of raised water table level (WTL) in Arctic/subarctic regions, characterized by continuous summer daylight, low temperatures and short growing seasons, remains poorly understood. This study presents a two‐year field experiment conducted at a northernmost cultivated peatland site in Norway. We used sub‐daily CO 2 , CH 4 , and N 2 O fluxes measured by automatic chambers to assess the impact of WTL, fertilization, and biomass harvesting on greenhouse gas (GHG) budgets and carbon balance. Well‐drained plots acted as GHG sources as substantial as those in temperate regions. Maintaining a WTL between −0.5 and −0.25 m effectively reduces CO 2 emissions, without significant CH 4 and N 2 O emissions, and can even result in a net GHG sink. Elevated temperatures, however, were found to increase CO 2 emissions, potentially attenuating the benefits of water level elevation. Notably, high WTL resulted in a greater suppression of maximum photosynthetic CO 2 uptake compared to respiration, and, yet caused lower net CO 2 emissions due to a low light compensation point that lengthens the net CO 2 uptake periods. Furthermore, the long summer photoperiod in the Arctic also enhanced net CO 2 uptake and, thus, the efficacy of CO 2 mitigation. Fertilization primarily enhanced biomass production without substantially affecting CO 2 or CH 4 emissions. Conversely, biomass harvesting led to a significant carbon depletion, even at a high WTL, indicating a risk of land degradation. These results suggest that while elevated WTL can effectively mitigate GHG emissions from cultivated peatlands, careful management of WTL, fertilization, and harvesting is crucial to balance GHG reduction with sustained agricultural productivity and long‐term carbon storage. The observed compatibility of GHG reduction and sustained grass productivity highlights the potential for future paludiculture implementation in the Arctic.
Abstract
No abstract has been registered
Authors
Peter ZubkovAbstract
Nordic boreal forests deliver critical ecosystem services but are increasingly vulnerable to abiotic disturbances, particularly wind and snow damage, potentially intensified by climate change. Climate-resilient forest management requires reliable decision-support tools for proactive risk assessment and post-event damage mapping. This thesis contributes to advancing adaptive abiotic forest disturbance management by integrating high-resolution satellite imagery, numerical weather prediction, tree mechanics, and machine learning techniques. It is composed of three papers. The first paper demonstrated that very high-resolution stereo satellite imagery and photogrammetric digital surface model reconstruction effectively map windthrow, particularly in moderate-to-high-density conifer stands, even under challenging Nordic winter conditions. The second paper proposed a novel mechanistic modeling framework predicting snow-induced stem breakage at the single-tree level, leveraging numerical weather prediction-based snow accumulation data and mechanistic critical snow load computations. The model provides physically interpretable risk assessments using basic tree metrics and predicted snow loads and can be readily integrated into forest management scenario planning. The third paper applied interpretable machine learning to numerical weather prediction data to identify drivers of forest wind damage during catastrophic windstorms driven by atmospheric mountain waves in a complex terrain. The findings underline that it was atmospheric stratification, turbulence, and vertical airflow that primarily controlled forest damage during the investigated event. Forest structure played minimal role, emphasizing the importance of a landscape-scale risk management approach focused on topographic susceptibility to severe mountain wave occurrences. This work makes a small, yet important, contribution to an integrated decision-support framework strengthening forest damage risk prediction and post-event assessment capabilities under climate uncertainty. Improvement priorities include observational validation of the canopy snow accumulation model, generalizing the interpretation of mountain wave-induced damage to other landscapes, and exploring multi-sensor fusion for windthrow detection. Finally, future efforts should be aimed at scaling the framework to a national scope and integrating advanced neural network-driven models for holistic risk management in an uncertain future.
Abstract
Agricultural land abandonment is increasingly affecting rural and low-intensity farming regions across Europe, raising concerns about its impact on biodiversity. While some species may benefit from reduced human disturbance, many species in semi-natural ecosystem types depend on traditional agricultural management to maintain their ecological integrity. This study examines whether abandoned agricultural land in Norway contains semi-natural ecosystems that may hold important remnant populations of red-listed plant species and where continued cessation of farming may further threaten these biodiverse ecosystems. Using spatial data on abandoned farmland, semi-natural ecosystem types and species observations, we identify areas of conservation interest and assess the extent to which these areas support endangered species. In addition, we conducted a time-series analysis of vegetation change using NDVI data (2017–2024) to evaluate whether abandonment led to detectable ecological succession. We also analyzed the spatial distribution of abandonment and its correlation with proximity to active farms to understand regional patterns of abandonment. Our results show that only a small percentage (3.7 %) of the abandoned agricultural land considered in this study overlaps with known semi-natural ecosystem types, yet these areas support a significant number of red-listed plant species. The NDVI analysis revealed generally weak but positive greening trends, suggesting early successional changes that are not yet statistically significant across most habitat types. Our method thus suggests a potential approach to allocate limited management resources to key locations. At present, the amount of semi-natural ecosystems is probably underestimated, however, because of limited and time-consuming mapping activity. These findings emphasize the need for more extensive mapping and targeted conservation efforts and highlight the risks posed by abandonment in biodiversity rich semi-natural ecosystem types.
Authors
Habtamu AlemAbstract
Dairy farming significantly contributes to global greenhouse gas (GHG) emissions, particularly methane (CH4). This study evaluates the performance of Norwegian dairy farms and the socio-economic factors influencing emissions over 30 years (1991-2020). We assessed dairy farm performance by evaluating both efficiency and environmental impact, with a particular focus on reducing methane emissions. This is crucial for achieving sustainable and resource-efficient farming within a circular economy framework. Methane emissions were calculated using the Intergovernmental Panel on Climate Change (IPCC) Tier 2 methodology, incorporating country-specific data on dairy cattle diet and production. Utilizing a comprehensive panel dataset of 692 dairy farms, we employed a parametric model to analyze the intricate input-output relationships within dairy production. Our findings reveal an average eco-efficiency score of 0.95, suggesting a promising potential for a 5% reduction in resource use and CH4 emissions without compromising production levels. Socio-economic factors, such as land tenure, farm experience, and government subsidies, were found to exert a positive influence on both farm performance and GHG emissions. Conversely, higher debt-to-asset ratios were associated with lower performance. Our research underscores the necessity for policies that support improvements at the farm level, such as facilitating knowledge transfer among farmers and increasing access to subsidies for environmentally friendly technologies. Future research should delve into other environmental impacts, including nitrogen emissions and biodiversity, to establish a more comprehensive framework for sustainable agricultural practices. By identifying opportunities for reducing GHG emissions while maintaining productivity, this study offers valuable insights for policymakers and industry stakeholders seeking to enhance the sustainability of the dairy sector in Norway and beyond.