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
Abstract
This study has applied FAO’s resilience assessment tool «SHARP+» to 14 farm enterprises practicing mountain summer farming (stølsdrift) in the Valdres region, representing the first use of this tool in a Norwegian context. The questionnaire was adapted to better capture local agricultural practices and institutional conditions, and structured interviews with farm managers were conducted in November 2025. Technical resilience scores ranged from 4.9 to 7.4 out of 10 (mean 6.2), and self-assessed scores from 5.9 to 7.9 (mean 6.9). The strongest areas were Government and institutional support (9.3) and Education and knowledge (8.5). The weakest were Livestock nutrition (3.5), Reasonably profitable (3.8), and Globally autonomous and locally interdependent (3.2), pointing to structural constraints related to feed self-sufficiency, farm profitability, and dependence on external inputs. Self-assessed scores consistently exceeded technical scores, particularly in production-related modules. Farmers' stated priorities — climate adaptation, infrastructure, farm economy, cooperation, and policy — largely aligned with the weakest areas in the technical assessment. The 2018 drought was the most critical environmental event reported by ten of the fourteen interviewees during their career as farmers.
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.
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
Nina SvartedalAbstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Desalegn Chala Diress Tsegaye Alemu Habtamu Alem Belachew Asalf Tadesse Melesse Eshetu_Moges Nega Tassie Abate Ayalew Wondie Aklilu Tilahun Tadesse Abebayehu Aticho Alemu Gonsamo Lanhui Wang Erick Lundgren Jeffrey Kerby Jens Christian SvenningAbstract
Abstract Water hyacinth is among the world’s most damaging aquatic invasive plants, forming dense mats that disrupt ecosystem functioning, fisheries, navigation, and livelihoods across tropical and subtropical freshwater systems. Its rapid spread is driven by clonal propagation, short life cycles, and prolific seed production, particularly under nutrient-enriched conditions. Although mechanical, chemical, and biological control methods are widely applied, their long-term effectiveness remains uncertain when underlying eutrophication persists. Here, we present a large-scale, one-time water hyacinth removal campaign in Lake Tana, Ethiopia’s largest lake and a UNESCO Biosphere Reserve, as a representative nutrient-rich tropical freshwater system. Using high-resolution satellite imagery, we quantified coverage one month before removal, one month after removal, and one year later. We integrated SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis with a socio-ecological system map to assess mitigation mechanisms and identify sustainable management pathways capable of providing long-term solutions to halt water hyacinth proliferation in freshwater bodies. The campaign removed over 75% (~1271 ha) of water hyacinth, yet within one year the plant resurged to levels ~18% higher than pre-removal. This rebound highlights the ecological resilience of water hyacinth and the limitations of short term, noncontinuous control strategies. Our analysis identifies unmanaged catchment nutrient inputs as the primary driver of proliferation. Lake Tana serves as a model system demonstrating that water hyacinth functions less as a traditional invader and more as a bioindicator of eutrophication. We propose a transferable conceptual and methodological framework combining continuous removal, catchment-based nutrient management, and circular bioeconomy approaches, offering globally relevant lessons for sustainable management of nutrient-enriched tropical freshwater systems.
Abstract
Errors in thematically detailed land-cover maps have large consequences for downstream applications. Moreover, simulation-based studies suggest that land-cover classifiers are sensitive to errors in reference data. We (1) quantified the expected error from field interpretation of land-cover types; (2) the sensitivity of classifiers to reference data errors; and (3) the error transferred from reference data to classifiers. Lastly, we (4) recommended strategies to reduce errors. The study area was mapped by 12 field interpreters divided into three equal-sized experience-level groups. The field-based land-cover maps were aggregated to three thematic resolutions and used to train 6804 land-cover classifiers by varying inputs, algorithm, and hyperparameter values. Separately from the first field campaign, four field interpreters classified validation data points, which were used to quantify error for each field interpreter and land-cover classifier, as the proportion of incorrectly classified validation points. We observed (1) generally high and varying levels of interpreter error; (2) a strong relationship between interpreter and classifier error; and (3) a net positive transfer of errors from reference data to classifiers. Because classifier error seems largely driven by interpreter error at the levels commonly observed in thematically detailed land-cover mapping, we (4) recommend strategies to reduce interpreter error before modelling.
Abstract
Aim Four different grassland types of varying land-use intensity and history were investigated for changes in plant species composition and richness over a 7- to 10-year period. Shifts in species occurrence frequencies and species-specific indicator values for nectar production were analyzed to assess how vegetation changes may influence the availability of floral rewards. Location Norwegian mainland. Methods We utilized survey (2004–2008) and resurvey (2011–2018) data from the Norwegian Monitoring Program for Agricultural Landscapes, examining vegetation in managed and unmanaged grasslands from 538 permanent vegetation plots within 97 monitoring squares across Norway. Using species-specific indicator values for nectar production, we tested how compositional changes in vascular plant communities are reflected in the occurrence frequency and cover of pollen- and nectar-providing plants. Results Grassland species composition has slightly shifted toward communities more dominated by later successional species, particularly those associated with shadier and wetter conditions. Major changes in the occurrence frequencies of individual species suggest a decline in pollen and nectar production. Specifically, 29 of 40 species (72.5%) that showed significant decreases in frequency were flowering plants important for pollinators. Across all grassland types, the average cover of pollen- and nectar-producing plants has declined over time, indicating a reduction in floral resources available to pollinating insects. Conclusions Our findings indicate a gradual transition in grassland habitats toward conditions that may be less favorable to pollinators, as reflected by changes in species occurrence frequencies and plant cover. Additionally, plant species associated with moist environments are likely to increase in abundance under continued climate change. This study highlights the value of systematic grassland monitoring within agricultural landscapes as an effective tool for detecting vegetation changes, even over short time spans. Such monitoring supports timely decision-making and the implementation of targeted management strategies to preserve ecologically and economically important habitat types.
Authors
Ming Yu Sebastian Kepfer-Rojas Yamina Micaela Rosas Teresa Gómez de la Bárcena Inger Kappel Schmidt Per Gundersen Ludovica D'Imperio Carsten W. Mueller Lars VesterdalAbstract
Afforestation of agricultural land is widely promoted as a nature-based solution to enhance carbon (C) sequestration and mitigate atmospheric CO2 levels. However, the temporal dynamics of soil organic carbon (SOC) after afforestation, particularly in mineral soils, remain uncertain due to the complex interaction of biogeochemical processes and their spatial variability. We investigated changes in SOC sequestration over five decades of afforestation on former cropland by extending the chronosequence approach with three repeated soil inventories in oak (Quercus robur L.) and Norway spruce (Picea abies (L.) Karst.) stands. Aboveground biomass C stocks were also quantified to evaluate the contribution of SOC to post-agricultural ecosystem C stocks. Forest floor C stocks increased rapidly in the early years and stabilized after approximately three decades, with consistently higher accumulation under Norway spruce than oak. In contrast, mineral SOC stocks in 0-25 cm depth increased with forest age by 0.18 ± 0.06 Mg ha−1 yr−1 under oak and 0.44 ± 0.07 Mg ha−1 yr−1 under Norway spruce. These contrasting trends in forest floor and mineral soil indicated a shift in C source-sink strength over time and between species. After 50 years of afforestation, total ecosystem C stocks in afforested stands reached up to 75% of those in a 200-year-old forest, with most new C stored in biomass (84-86%), followed by mineral soil (10-11%) and forest floor (4-5%). Despite higher sequestration of new C in Norway spruce stands, the relative distribution across ecosystem compartments was similar between tree species.
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
Field-based ecosystem maps are often used to support environmental impact assessments (EIAs) in later stages of spatial planning. During the early stages, however, information on geographical distributions of ecosystems is typically unavailable. This can result in uninformed decisions, with negative consequences for biodiversity and ecosystem services. Although model-based maps offer low-cost wall-to-wall coverage, they are rarely used for spatial planning. Using Norway as a study system, we aimed to: (1) quantify the coverage of field-based ecosystem maps in areas reserved for development; (2) use a model-based map to assess ecosystem extents in these areas; and (3) provide guidance on how model-based maps can support spatial planning. We first collated municipality-level land-use plans and intersected these with existing field-based ecosystem maps created for EIAs. Then, we constructed a model-based map for 17 ecosystem types with a 10 m × 10 m resolution that was intersected with the unsurveyed land-use plans. We estimated that 4.2 km2 of land is reserved for development in an average municipality, of which 0.3 km2 is covered by field-based maps. Our model-based map indicates, with moderate uncertainty, that 260 km2 covered by red-listed ecosystem types is at risk of being affected if unsurveyed land reserves are developed. However, improvements in model training and uncertainty quantification methodology should be considered to increase utility of the maps. We provide guidelines for using model-based ecosystem maps in spatial planning, especially in early planning stages, aiming to support decision-making while taking the limitations of model-based maps into account.