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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.

2026

Sammendrag

Defibrert trefiber testes av stadig flere dyrkere, enten som del av en blanding, eller som enkeltstående vekstmedium. Et spørsmål vi ofte blir stilt er hvor mye kalk substratet med trefiber trenger. Trefiber har lav pH når den er fersk, nesten tilsvarende torv, og det har fått mange til å anta at de skal behandles likt. Det er feil. Den lave pH-en forsvinner raskt ved oppstart av planteproduksjon, og kalker du som du ville gjort med torv, blir det surr.

Sammendrag

Bruk av trefiber vil redusere miljøbelastningen ved å erstatte energikrevende steinullproduksjon med et fornybart materiale basert på rest-råstoff fra norsk skogindustri. Ved endt bruk kan trefibermaterialet komposteres, brukes som jordforbedringsmiddel eller brennes for energigjenvinning, i motsetning til steinull som ender på deponi. Etter lovende resultater med Fibergrow® trefibermatter i tomat i 2022 og 2023, gjennomførte vi nye forsøk i 2025 for å bekrefte disse funnene.

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Climate change poses a significant threat to the Afrotemperate flora of the Eastern Afromontane Biodiversity Hotspot, particularly to species confined to high-elevation ecosystems such as those found on the African sky islands. This study evaluates the vulnerability of tropical Afroalpine and Afromontane Helichrysum taxa (Compositae) by assessing their climatic niches and predicting future shifts in distribution, range fragmentation, and altitudinal limits under climate change scenarios. Occurrence records for 14 taxa (eight Afroalpine and six Afromontane) were obtained from recent field campaigns, biodiversity databases and herbaria. Ensemble ecological niche models were developed combining Generalized Linear Models, Generalized Boosting Models, and Random Forest. Taxon-specific bioclimatic variables were selected after correlation analyses. The models were calibrated using current climate data and projected using the PSL-CM6A-LR and MRI-ESM2.0 climate models with both low- and high-emission scenarios. The results show that most Afrotemperate taxa currently occupy only a portion of their climatically suitable habitat, often in geographically distant areas. Future projections indicate significant range contractions and increased fragmentation. Afroalpine taxa could lose 50–66% of their suitable habitat, while Afromontane taxa could decline by 53–79%. Suitable areas were estimated to shift upwards in elevation, with limited potential for colonization of new areas, and with no significant latitudinal or longitudinal shifts. These findings represent the first continental-scale assessment of the impact of climate change on the Afrotemperate flora using ecological niche modelling. The projected climate-induced range losses and increased habitat fragmentation, in particular combined with increasing anthropogenic pressure in this region, highlight the urgent need for targeted conservation actions.

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This paper describes from a methodological point of view a recent attempt to test how Historic Landscape Characterisation (HLC) as developed with respect to the British landscape can be adapted and applied to the different and distinctive landscapes of a Norwegian upland territory, on the edges of the Hardangervidda plateau. This is an area characterised by mobility, close nature-culture interactions, and practices such as summer farming and short-distance transhumant practices. The research was carried out by two Norwegian agencies – NIKU and NIBIO – as part of a larger project known as PARKAS designed in the context of green transitions to promote better-integrated and publicly-responsible management and safeguarding of protected areas. We briefly describe the origins and principles of HLC in Britain, and then at greater length assess the suitability of HLC in Hardangervidda and key ways by which the approach would require modification and adaptation. A concrete method for a Hardangervidda HLC – and a suitable high-level classification – is identified and discussed.

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Sustainable food production in West Africa is increasingly challenged by declining soil fertility, erratic rainfall, and demographic pressures that intensify demand for land. In this context, farmers often respond to stagnating yields by expanding cultivated areas, a strategy that accelerates the conversion of fallows and natural habitats into cropland. This study investigates whether agroecology informed sustainable intensification (SI) packages can improve technical land use efficiency and thereby reduce the incentive for agricultural expansion. The analysis focuses on smallholder maize systems across Northern Ghana, where land degradation and climate variability pose persistent constraints. Using farm level survey data from 372 maize producers across the Northern, Upper East, and Upper West regions, we estimate technical land use efficiency with a translog stochastic frontier model that treats land as a fixed input. This methodological choice provides a direct interpretation of efficiency as the effective land required to produce observed output. The SI package examined includes improved seed, more balanced fertilizer applications, and agroecological practices such as residue retention and intercropping. A matched comparison group of non adopters allows us to isolate adoption effects. The results show that SI adopters are, on average, 21% more land efficient than non participants, implying that approximately 24% less land would be needed to produce the same quantity of maize. Efficiency improvements are most pronounced among farmers initially furthest from the production frontier, indicating substantial equity gains when targeting less efficient producers. The analysis further highlights the importance of enabling conditions: education, advisory services, and access to credit all significantly enhance the likelihood and effectiveness of adoption. These findings strengthen the argument for agroecological transition pathways that bundle technological, institutional, and financial interventions. Such integrated approaches can raise productivity, limit pressure on land expansion, and contribute to land degradation neutrality and climate resilience in the savanna agroecosystems of West Africa.

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Ecological stoichiometry offers a mechanistic framework for linking soil biogeochemical processes with nitrogen (N) and phosphorus (P; collectively, NP) runoff losses in agroecosystems. This review synthesizes recent advances to elucidate how soil carbon: nitrogen: phosphorus (C:N:P) ratios regulate NP runoff losses through coupled soil–microbial processes. Crucially, we highlight that agricultural practices reshape soil stoichiometry primarily through labile nutrient pools and microbial biomass, whereas total soil nutrient ratios generally remain stable due to strong buffering capacity. Due to the relatively weak stoichiometric homeostasis of soil microorganisms, these shifts in labile C:N:P ratios strongly constrain microbial growth, community composition, and enzyme production. Consequently, stoichiometric imbalance acts as a primary regulator of key biochemical pathways—specifically soil organic carbon (SOC) mineralization, nitrification, and denitrification—that determine the mobilization of inorganic NP forms prone to runoff. Stoichiometric regulation exhibits dual characteristics of integration and independence. Soil C:N:P ratios simultaneously influence multiple biochemical processes, while each process responds to stoichiometric constraints with distinct threshold behaviors. These thresholds can be described by process-specific stoichiometric boundary limits, expressed as (C : N/P)max, beyond which reaction rates approach zero under element-limiting conditions. Despite growing empirical evidence, most existing models fail to explicitly incorporate these microbial-mediated stoichiometric constraints or (C : N/P)max thresholds, leading to predictive uncertainties. By framing NP runoff losses as emergent outcomes of stoichiometrically constrained processes, this review provides a robust theoretical basis for improving runoff modeling accuracy and developing stoichiometry-guided soil management strategies to mitigate agricultural non-point source pollution.

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Introduction Leaf area index (LAI) estimation is sensitive to sensor field of view (FOV), within-plot spatial heterogeneity, and sampling layout. Because LAI influences canopy radiation transmission, microclimate and vegetation–atmosphere exchange, robust field estimation is important for biometeorological and ecosystem research. Methods We evaluated these effects in mature Norway spruce [ Picea abies (L.) H. Karst] stands in the Czech Republic across 15 sites at elevations of 407–1,019 m a.s.l., using a combined gap-fraction approach based on LAI-2200 PCA measurements and digital hemispherical photography. At each site, a measured 9 × 9 grid of 81 below-canopy measurement points with 2-m spacing was used as an operational within-plot benchmark for mean optically derived LAI and spatial structure. Monte Carlo subsampling was then used to compare how reduced layouts, including random, row-wise, column-wise, block-wise, and spatially balanced block–row–column layouts, reproduced the full-grid benchmark mean. Results Narrower FOVs produced higher stand-level optically derived LAI estimates and greater within-plot variability. The full grids also showed directional spatial structure, with stronger autocorrelation along the north–south column direction than along the west–east row direction, although this contrast weakened under the narrowest FOV. Reduced layouts with more even spatial coverage outperformed random sampling. The spatially balanced block–row–column layout performed most consistently, whereas the row-wise layout provided little improvement. Approximately 25–36 well-distributed below-canopy measurements were sufficient to keep reduced-layout LAI deviations within 0.15 m 2 m −2 of the full-grid benchmark, whereas 7–9 measurements were enough to remain within 5% of this benchmark in most stands. Discussion Spatially balanced sampling can therefore improve the robustness and efficiency of stand-level optically derived LAI estimation, with relevance to forest biometeorology, ecosystem monitoring, and the validation of satellite-derived LAI products.

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Semi‐natural grasslands are valuable habitat for bumblebees ( Bombus spp.) in Fennoscandia. These grasslands are often maintained by livestock such as free‐ranging sheep, but it is unclear if sheep grazing impacts bumblebee communities, and if so, which grazing intensity is best. We compared bumblebee species richness and abundance on semi‐natural grasslands in southeastern Norway at varying levels of disturbance by sheep (0–1680 initially released). We used Bayesian hierarchical models to test the intermediate disturbance hypothesis, that the highest bumblebee abundance and richness would occur at moderate grazing intensity, while considering other important habitat variables: distance to forest, meadow size, sward height, and availability of flowers, litter, and bare soil. We found no support for the intermediate disturbance hypothesis but rather a negative relationship between the number of sheep released and measures of bumblebee species richness and abundance from targeted netting. Effects varied among the most common species. B. pratorum and B. wurflenii were more sensitive to the number of sheep released than were B. jonellus . Bumblebee abundance estimated by two capture methods (blue vane trapping and targeted netting) was only weakly correlated and bumblebee species richness estimated from traps was unrelated to any of our predictor variables. Practical implication . Our results suggest a weak negative influence of any amount of sheep grazing on bumblebee abundance and richness. Targeted netting was a more reliable method than blue vane traps to assess effects on the bumblebee community.

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Sustainable forest management needs growth models. Few studies have explored regional models in Fennoscandia despite similar conditions and challenges. We examined the feasibility of regional models for basal area increment of Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), and birch (Betula pendula Roth. and Betula pubescens Ehrh.). We compiled over 880,000 growth observations and estimated competition indices, climate variables, and site fertility classes by integrating data from recent National Forest Inventories (2004–2023) in Finland, Norway, and Sweden. Using Random Forest models, we identified the main growth drivers across countries (tree size, accumulated temperature sum, latitude, competition, and site fertility), with minor differences in their responses across countries. However, periodic NFI measurements could not capture the effect of additional climate variables. Using species-specific nonlinear mixed models, we demonstrated that predictive regional models can be fitted using those main drivers. Although we achieved only moderate predictive performance (Weighted Absolute Percentage Error of 45–71%, depending on the species and country), there were no residual geographical biases. The results confirm the potential of Fennoscandian growth models to address shared challenges. Future work should better account for site fertility, integrate process-based approaches for climate responses, and carry out independent validation.

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The four main apple cultivars in Norway, ‘Discovery’, ‘Summerred’, ‘Red Gravenstein’, and ‘Red Aroma’, account for approximately 80% of the market volume. These cultivars provide good yields in a Nordic climate with a short growing season but have relatively limited storage and shelf life. The main challenges are the rapid loss of firmness and senescence-related disorders, both of which are connected to ripening and ethylene. Several projects investigated possible ways to secure fruit quality at the consumer level by improving conditions at the packinghouse. One of the factors to evaluate was ethylene levels in fruit storage rooms. Ethylene concentrations were measured in cold storage rooms with varying volumes of fruit using a portable instrument equipped with an electrocatalytic sensor for continuous, in-situ measurement of ethylene in the air. Ethylene concentrations between 10 and 35 ppm were measured in 18% of the rooms, whereas 82% had concentrations between 0 and 10 ppm. Fruit samples were assessed for ethylene production rates in their expected cold storage period. The values obtained were used to evaluate the risk of high ethylene levels in certain rooms before packaging, to recommend which cultivars could be kept in the same rooms, and for how long. Treatment with 1-methylcyclopropene (1-MCP) was also tested to improve fruit quality during storage further. The 1-MCP treatment revealed considerable potential for maintaining the postharvest quality of the tested Norwegian apples.