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.
2023
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Miguel Las Heras Hernandez Francis Isidore Barre Nils Maximilian Dittrich Avijit Vinayak Pandit Anne Falk Øgaard Daniel B. MüllerAbstract
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Alexandra Kruse Jana Spulerova Csaba Centeri Sebastian Eiter Viviana Ferrario Suzan Jurgens Drago Kladnik Zdeněk Kučera Teodor Marusca Dragomir Neculai Hans Renes Hanne Sickel Maurizia Sigura Martina Slámová Kari Stensgaard Peter StrasserAbstract
This paper provides an overview of traditional hay-making structures and the related agricultural landscapes in Europe. The information was collected using a standardised questionnaire that was completed by experts from different countries. What all countries had in common was that hay production with its corresponding structures was widespread. However, the scope and importance differed among the countries today. We found differences in type and extent, in degree of awareness, and in the cultural meaning of hay-making structures. The differences were connected with built structures, as well as with other tangible and intangible aspects of cultural heritage. The distribution of the broad variety of hay-making-related structures, especially semipermanent ones, has changed throughout history, as well as the hay-making techniques, as a result of agrarian specialisation, land reclamation, and consolidation. Today, in some countries, the relevance of hay-making was mainly connected to horse keeping and landscape management (like in Germany and Hungary), while in others (like Slovakia and Slovenia), it was still predominantly used for cattle and sheep.
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Monitoring and managing Earth’s forests in an informed manner is an important requirement for addressing challenges like biodiversity loss and climate change. While traditional in situ or aerial campaigns for forest assessments provide accurate data for analysis at regional level, scaling them to entire countries and beyond with high temporal resolution is hardly possible. In this work, we propose a method based on deep ensembles that densely estimates forest structure variables at country-scale with 10-m resolution, using freely available satellite imagery as input. Our method jointly transforms Sentinel-2 optical images and Sentinel-1 syntheticaperture radar images into maps of five different forest structure variables: 95th height percentile, mean height, density, Gini coefficient, and fractional cover. We train and test our model on reference data from 41 airborne laser scanning missions across Norway and demonstrate that it is able to generalize to unseen test regions, achieving normalized mean absolute errors between 11% and 15%, depending on the variable. Our work is also the first to propose a variant of so-called Bayesian deep learning to densely predict multiple forest structure variables with well-calibrated uncertainty estimates from satellite imagery. The uncertainty information increases the trustworthiness of the model and its suitability for downstream tasks that require reliable confidence estimates as a basis for decision making. We present an extensive set of experiments to validate the accuracy of the predicted maps as well as the quality of the predicted uncertainties. To demonstrate scalability, we provide Norway-wide maps for the five forest structure variables.
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Arne BardalenAbstract
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Birch wood is a potential feedstock for biogas production in Northern Europe; however, the lignocellulosic matrix is recalcitrant preventing efficient conversion to methane. To improve digestibility, birch wood was thermally pre-treated using steam explosion at 220 °C for 10 min. The steam-exploded birch wood (SEBW) was co-digested with cow manure for a period of 120 days in continuously fed CSTRs where the microbial community adapted to the SEBW feedstock. Changes in the microbial community were tracked by stable carbon isotopes- and 16S r RNA analyses. The results showed that the adapted microbial culture could increase methane production up to 365 mL/g VS day, which is higher than previously reported methane production from pre-treated SEBW. This study also revealed that the microbial adaptation significantly increased the tolerance of the microbial community against the inhibitors furfural and HMF which were formed during pre-treatment of birch. The results of the microbial analysis indicated that the relative amount of cellulosic hydrolytic microorganisms (e.g. Actinobacteriota and Fibrobacterota) increased and replaced syntrophic acetate bacteria (e.g. Cloacimonadota, Dethiobacteraceae, and Syntrophomonadaceae) as a function of time. Moreover, the stable carbon isotope analysis indicated that the acetoclastic pathway became the main route for methane production after long-term adaptation. The shift in methane production pathway and change in microbial community shows that for anaerobic digestion of SEBW, the hydrolysis step is important. Although acetoclastic methanogens became dominant after 120 days, a potential route for methane production could also be a direct electron transfer among Sedimentibacter and methanogen archaea.