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.
2025
Forfattere
Alouette van Hove Kristoffer Aalstad Vibeke Lind Claudia Arndt Vincent Odongo Rodolfo Ceriani Francesco Fava John Hulth Norbert PirkSammendrag
Considerable uncertainties and unknowns remain in the regional mapping of methane sources, especially in the extensive agricultural areas of Africa. To address this issue, we developed an observing system that estimates methane emission rates by assimilating drone and flux tower observations into an atmospheric dispersion model. We used our novel Bayesian inference approach to estimate emissions from various ruminant livestock species in Kenya, including diverse herds of cattle, goats, and sheep, as well as camels, for which methane emission estimates are particularly sparse. Our Bayesian estimates aligned with Tier 2 emission values of the Intergovernmental Panel on Climate Change. In addition, we observed the hypothesized increase in methane emissions after feeding. Our findings suggest that the Bayesian inference method is more robust under non-stationary wind conditions compared to a conventional mass balance approach using drone observations. Furthermore, the Bayesian inference method performed better in quantifying emissions from weaker sources, estimating methane emission rates as low as 100 g h−1. We found a ± 50 % uncertainty in emission rate estimates for these weaker sources, such as sheep and goat herds, which reduced to ± 12 % for stronger sources, like cattle herds emitting 1000–1500 g h−1. Finally, we showed that radiance anomalies identified in hyperspectral satellite data can inform the planning of flight paths for targeted drone missions in areas where source locations are unknown, as these anomalies may serve as indicators of potential methane sources. These promising results demonstrate the efficacy of the Bayesian inference method for source term estimation. Future applications of drone-based Bayesian inference could extend to estimating methane emissions in Africa and other regions from various sources with complex spatiotemporal emission patterns, such as wetlands, landfills, and wastewater disposal sites. The Bayesian observing system could thereby contribute to the improvement of emission inventories and verification of other emission estimation methods.
Forfattere
Federico Dragoni M. Seyedalmoosavi Lorraine Balaine Serena Bonizzi Anna Sandrucci Nicola Alessi Giorgio Ragaglini Klaus Mittenzwei Lennart Kokemohr Aurelie Wilfart Emma Soule Joanna Fratczak-Muller Xabier Diaz De Otalara Monika Suchowska-Kisielewicz Grete H. M. Jørgensen Barbara AmonSammendrag
Det er ikke registrert sammendrag
Forfattere
Federico Dragoni Lorraine Balaine Serena Bonizzi Anna Sandrucci Kobe Coorevits David Janke Giorgio Ragaglini Klaus Mittenzwei Lennart Kokemohr Aurélie Wilfart Emma Soulé Joanna Fratczak-Muller Xabier Díaz de Otálora Wilfried Winiwarter Grete H. M. Jørgensen Barbara AmonSammendrag
Dairy production systems are an essential backbone of European agriculture but have become highly specialized, heavily relying on external inputs, lacking resilience and meeting a desirable level of circularity to a limited extent. When livestock is re-coupled with grasslands and diversified crops, dairy production systems provide valuable ecosystem services through their interaction with land, vegetation and soil. The aim of the DairyMix project (www.dairymix.eu) is to address this topic through systems thinking, defining region-specific concepts for sustainable and circular integrated crop-forestry-livestock systems for dairy production in Europe and Latin America. Data from a wide range of dairy case study farms were collected in Germany, Italy, France, Norway, Ireland, Poland, Brazil and Argentina. To assess the environmental performances of the case studies, Life Cycle Assessment (LCA) was carried out; economic and social sustainability indicators were also calculated. A multi-criteria assessment framework was implemented, and models covering the cropping system and other farm components were integrated to compute and assess circularity indicators. Precision farming technologies, such as the ICT-based Online Tool for monitoring Indoor barn Climate, animal stress and emission (OTICE), were developed, contributing to tailored solutions and management tools for regional agricultural challenges. Agroforestry practices were assessed, and qualitative in-depth interviews were conducted in selected case studies. In particular, the farmers’ willingness to implement agroforestry, mixed farming and improve nutrient circularity was investigated. Preliminary findings are as follows: 1) Agroforestry, as a valuable multifunctional practice (e.g., increasing biodiversity, carbon sequestration, animal welfare), can provide alternative feed resources for ruminants. Nutritional value and digestibility tests on leaves of five tree species in Northern Italy revealed that mulberry (Morus nigra L.) has a nutritional profile comparable to lucerne or polyphytic meadows. This and other species can potentially be included as an alternative fodder in dairy cow diets. 2) Farmers are motivated by both environmental concerns and profitability. According to our findings, they intuitively value circular and sustainable practices and show attachment to the land, often originating from farm inheritance. Key barriers to implementing sustainable and circular practices included insufficient earnings, high workload, workforce shortages, and limited access to insurance. Bureaucracy, frequent policy changes, and unstable expectations further hindered the adoption of such practices. Farmers notably emphasized the lack of consumer knowledge about production processes and product origins, highlighting the need for more education and awareness. The project results are being incorporated into the DairyMix online platform. The DairyMix platform will display results from: i) the multi-criteria assessment, allowing the users to evaluate the effect of varying the weights of the sustainability principle considered; ii) the modelling of mitigation measures and alternative cropping scenarios in representative dairy production systems across Europe and Latin America. Users will be asked for feedback, which will be incorporated into the platform. In contrast to “one-fit-all” solutions, the DairyMix interactive platform will present a range of options for the sustainability of farming systems for dairy production, favouring the adoption of informed decisions for circular and integrated crop-forestry-livestock in different regions.
Forfattere
Grete H. M. Jørgensen Quentin Lardy Haldis Kismul Shelemia Nyamuryekung'e Mårten Hetta Mohammad Ramin Vibeke LindSammendrag
Det er ikke registrert sammendrag
Forfattere
Federico Dragoni Lorraine Balaine Serena Bonizzi Anna Sandrucci Kobe Coorevits David Janke Giorgio Ragaglini Klaus Mittenzwei Lennart Kokemohr Aurélie Wilfart Emma Soulé Joanna Fratczak-Muller Xabier Díaz de Otálora Wilfried Winiwarter Grete H. M. Jørgensen Barbara AmonSammendrag
Poster til GGAA 2025 konferansen
Forfattere
Grete H. M. Jørgensen Quentin Lardy Haldis Kismul Shelemia Nyamuryekung'e Mårten Hetta Mohammad Ramin Vibeke LindSammendrag
Det er ikke registrert sammendrag
Forfattere
Grete H. M. JørgensenSammendrag
Foredrag for Brønnøysund videregående skole VG1
Forfattere
Grete H. M. JørgensenSammendrag
Presentasjon for skoleklasse 6-9 trinn Tjøtta skole i anledning forskningsdagene
Forfattere
Grete H. M. JørgensenSammendrag
Forelsening til elever ved Polarsirkelen videregående skole i anledning forskningsdagenes arrangement "Bestill en forsker"
Forfattere
Elisabet Nadeau Qasim Mashood Romuald Cazes Håvard Steinshamn Matilda Johansson Anna HessleSammendrag
Det er ikke registrert sammendrag