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
Felix Seidel Jorge Álvaro‐Fuentes Martin A. Bolinder Claudia Di Bene Mariangela Diacono Eugenio Diaz‐Pines Sophia Götzinger Thomas Kätterer Sonja G. Keel Katharina M. Keiblinger Jens Leifeld Jan Peter Lesschen Ioanna Panagea Daniel Rasse Christoph Rosinger Greet Ruysschaert Florian Schneider Daria Seitz Heide Spiegel Marjetka Suhadolc Silvia Vanino Axel DonAbstract
Soil degradation threatens global agriculture by compromising soil health, while sustainable agricultural management enhances soil functionality and carbon (C) storage, thereby contributing to climate change mitigation. This study estimates the feasible C sequestration potential of ten agricultural management practices across Europe, by applying practice‐specific emission factors and identifying areas suitable for additional implementation. For each management option, the implementation area was defined based on environmental and technical limitations and, if applicable, EU regulations. The objective of this study is to identify general patterns, relative magnitudes, and plausible ranges of carbon sequestration potentials across Europe. Considering soil C from 0 to 50 cm depth, biochar application shows the highest and most robust potential, contributing approximately 34%–47% of the total estimated annual C sequestration rate. This is followed by agroforestry, contributing 24%–45% (of which ~10% occurs in soils and ~90% in biomass), and zero tillage with 11%–15%. Optimised crop residue management (4%–6%), forage legumes and temporary ley rotations (4%–5%), and cover cropping (2%–3%) contribute comparatively smaller shares. Non‐inversion tillage and irrigation offered a marginal C sequestration potential. By implementing all non‐mutually exclusive management options, the greenhouse gas (GHG) mitigation potential is estimated at approximately 20%–30% of current, annual, agricultural GHG emissions in Europe (740 Mt. CO 2 e yr. −1 ), including the land‐use, land‐use change and forestry (LULUCF) sector. For the EU‐27, this corresponds to a similar range of 20%–31% of annual agricultural GHG emissions (614 Mt. CO 2 e yr. −1 ), also including the LULUCF sector. Evaluating trade‐offs and synergies of each management option is essential for achieving sustainable soil management. The success of C sequestration efforts in European agriculture depends on scaling up improved management practices. Meanwhile, soil C stocks decrease and entrenched policy as well as economic and other adoption barriers suggest that even the conservative scenario may be overly optimistic.
Abstract
In East Africa, including Tanzania, the vast majority of the population relies on fuelwood for domestic energy consumption, particularly for cooking. This heavy dependence on biomass has significant implications for forest resources, contributing to forest disturbances, but has not been sufficiently investigated until now. This study aims to explore these dynamics in Mainland Tanzania between 2001 and 2023 by assessing Tree Cover Loss, Above-Ground Biomass, biomass loss and demand trends, and evaluating the fraction of Non-Renewable Biomass. The study integrates remote sensing data from Global Forest Watch, national household budget surveys, and published literature, applying geospatial analysis and statistical modelling. Results showed that between 2001 and 2023 AGB declined, with a consistent drop in biomass density. Total Biomass Loss rose from 39 Mt in 2001 to 70.1 Mt in 2022, while Total Biomass Demand surged from 22.6 to 55.4 Mt. The gap between supply and demand narrowed slightly, suggesting a possible increase in resource use efficiency for energy provision. Out of 26 regions, 11 are net consumers, and 15 are net suppliers. This illustrates the uneven distribution of biomass resources and demand nationwide. The fraction of Non- Renewable Biomass rose from 23.8% in 2001 to 34.1% in 2012 and then stabilized. About 79% of this in 2022 was due to cooking-related biomass demand, highlighting unsustainable biomass use. Overall, this study offers critical insights into forest resource use in Tanzania, with implications for sustainable management and climate policy. The refined estimates of biomass dynamics and fraction of Non-Renewable Biomass support more targeted, data-driven decision-making. While limitations exist, the results emphasize the need for better monitoring to support sustainable energy and forestry strategies.
Abstract
Tree falls along linear infrastructures and in particular powerlines pose a significant economic, safety and environmental challenge for the companies and institutions managing these infrastructures. The quick progression and affordability of remote sensing technologies such as drone-based inventories offers the opportunity to quickly and efficiently map individual trees along these infrastructures, enabling precise vegetation management to reduce risks. Here, we show how the hybrid empirical and mechanistic wind risk model ForestGALES can be applied to assess the vulnerability of individual trees to windfalls along selected powerlines in southern Norway. The validation dataset contained 180 recorded individual tree falls along powerlines from the winter 2020–2021. There was no major wind event recorded that winter. However, still, the ForestGALES model performed adequately, with an AUC (area under the curve) of 0.67. Combining the vulnerability index from ForestGALES with all other available tree and environmental variables in a machine learning model (extreme gradient boost algorithm) did however significantly improve the prediction performance. These results highlight how a combination of high-quality remote sensing data at the individual tree level can be utilized with ForestGALES and machine learning to provide managers with high-resolution vulnerability information for vegetation management.
Authors
Geir-Harald StrandAbstract
This paper examines strategies that can be used to determine the appropriate binarization of predictive land-cover maps to produce categorical land-cover maps, in this study used to separate peatland from non-peatland. Seven different strategies were applied to two predictive peatland maps, and the accuracy of the resultant binary land cover maps was evaluated. The main objective was to find the most effective approach to include as much peatland as possible, while simultaneously keeping the amount of noise (false positives) in the peatland map at a minimum. The best overall results were obtained with metrics related to correlation in the confusion matrix. Cohen’s Kappa and the F1 score (defined as the harmonic mean of precision and recall) both reached their maximum at the same cutoff value, producing a land cover map with relatively high recall and limited amounts of noise in terms of false positive results. Maximizing the F1 score does not necessarily produce the optimal result for all applications. The intended purpose of the map must also be considered when deciding whether it is more important to increase true positive results or minimize false positives. In this study, selecting the cutoff point by maximizing Cohen’s Kappa or the F1 score proved to be the most effective overall strategy for dichotomizing the maps. Other strategies may be more appropriate when the distribution of the predictive scores is more balanced or there is a partisan preference for enhancing either user’s accuracy or producer’s accuracy.
Authors
Mojtaba Shafiei Mohammad Gharesifard Brian Thomas Nazimul Islam Stephan Dietrich Hamidreza Mosaffa Matjaž Mikoš Taha Ouarda Seyedeh Simin Mirhashemi Dehkordi Zahra Abdollahi Thom Bogaard Salvatore GrimaldiAbstract
Water plays a central connecting role within the climate system, linking meteorological, hydrological, and earth system processes with societal dimensions such as water resource demands and risks associated with pollution, droughts, and floods. Global water challenges are addressed through multiple international agendas related to sustainable development, climate change, biodiversity, and water security. While these agendas share broadly aligned objectives, they differ in scope, scale, and modes of operationalization. Together, they shape how scientific knowledge is mobilized, policies are formulated, and actions are implemented. As the 2030 Agenda approaches its conclusion, there is a growing need to review and map global water agendas in order to better understand their interactions and support more coherent responses to complex water challenges. Rather than viewing global water agendas as parallel and independent efforts, they can be understood as interconnected learning pathways through which shared objectives, knowledge, and practical experience evolve over time. From this perspective, synergies emerge across these learning pathways through reflection, coordination, and exchange between science, policy, and practice. Clarifying how such synergies can be recognized, supported, and strengthened is therefore essential for advancing more integrated and impactful responses to global water challenges. The Strategic UN Synergy Working Group (SUN) operates within the IAHS HELPING Science for Solutions Decade (2023–2032) and aims to strengthen the contribution of hydrological science to international policy processes and practical implementation programmes. Guided by the HELPING paradigm, SUN facilitates bottom-up engagement, open science, and co-creation principles to support learning across scales and the translation of hydrological knowledge into policy and action. This contribution introduces the vision, structure, and core activities of the SUN Working Group, with a focus on understanding global water agendas and supporting synergies through a science–policy–practice approach. SUN builds on the understanding of global water agendas as interconnected learning pathways, and we will illustrate how coordinated learning pathways can help advance more coherent, integrated, and future-oriented global water agenda.
Abstract
No abstract has been registered
Abstract
Small retention ponds are increasingly recognised as effective nature-based solutions for managing hydrological extremes in Norway’s agricultural catchments. Typically located in upper catchment areas or at the forest–agriculture interface, these ponds temporarily store runoff during intense rainfall events and snowmelt. In addition to flood mitigation, they provide important co-benefits by reducing soil erosion and sediment transport and by protecting agricultural drainage systems from erosion and overflow during extreme events, thereby supporting long-term soil productivity. Although individual storage volumes are limited, their cumulative impact at the catchment scale can be substantial when retention ponds are strategically distributed across the landscape. This study investigates the potential effects of small retention ponds using process-based hydrological modelling with SWAT+ to support catchment-scale climate adaptation planning in a Norwegian agricultural catchment. SWAT+ enables an improved representation of hydrological connectivity between managed landscapes and the stream network through its flexible spatial structure and rule-based management algorithms. The model is calibrated using a constraint-based approach that integrates both soft and hard data to represent streamflow and sediment dynamics in the Lierelva catchment. Multiple retention ponds are implemented to assess their cumulative effects on streamflow and sediment transport. Finally, the study discusses key challenges associated with modelling catchment–NBS interactions using SWAT+.
Authors
Dalphy Ondine Camira Harteveld Abdelhameed Elameen Simo Maduna Adam Vivian-Smith Andrea Podavkova Sabine Oettl Stefanie Maria Primisser Jorunn BørveAbstract
Small, superficial rot spots occurring around lenticels postharvest on apple in Norway have not been identified but were assumed to be underdeveloped Neofabraea lesions. Fungal isolation from such spots on fruit from the 2022 season revealed both Neofabraea perennans and Ramularia spp., identified by B-tubulin and ITS sequencing, respectively. In the 2023 season, isolations were made from fruit with spots resembling dry lenticel spot caused by Ramularia mali. The aim of this study was to identify the Ramularia species associated with the postharvest fruit spots in Norway. Multiple gene regions of five Norwegian isolates (E20, E21 from 2022; 13,15 and 18 from 2023) and three reference isolates, R. mali, R. eucalypti, and R. collo-cygni, were sequenced and used for phylogenetic analysis. The Norwegian isolates were distinct from the included reference isolates, but clustered with other Ramularia species. Isolates 13, 18 and E21 clustered with Ramularia vizellae, while isolates 15 and E20 were most closely related to Ramularia phacae-frigidae. Isolate E20 was sequenced using the Oxford Nanopore Technologies MinION platform. Pathogenicity was assessed in a field inoculation study using isolate E21, resulting in typical spot development on inoculated fruit. Ramularia vizellae has previously been reported from dead apple leaf litter and other woody hosts in the Netherlands and Iran, while R. phacae-frigidae was originally described from Phaca frigida in Switzerland. Neither species has previously been reported in association with apple fruit spotting. While Ramularia mali has caused outbreaks on apple in several European countries, recent studies hypothesize that the symptoms may be caused by a species complex with regional variation. The present results identify candidate species contributing to this complex in Norway and highlight the need for further studies to improve species delimitation and pathogenicity.
Authors
Nina SvartedalAbstract
No abstract has been registered
Abstract
No abstract has been registered