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
Sammendrag
Study region: Six forest dominant catchments in Norway: two are micro- (< 10 km 2 meso- (< 1000 km 2 ) and two are macro-scale (> 10000 km 2 ), two are ) catchments. Study focus: This study focuses on the combined climate and forest impacts on streamflow, hydrological components as well as flood and low flow levels. In addition, the relative contributions of climate and forest impacts are distinguished. New hydrological insights for the region: This study provides the first hydrological projections in Norwegian catchments driven by both the climate projections and their corresponding forest projections. Due to warmer climate and higher precipitation under the Representative Concentration Pathway scenarios (RCP2.6 and RCP4.5), continuous increase in forest timber volume is projected in five out of six catchments. The combined effects of climate and forest development lead to median changes in annual streamflow ranging from 2 % to 8 %. Climate is the major driver of streamflow changes, and forest growth slightly offsets the increase in streamflow caused by climate and reduces runoff generation locally. Forest growth reduces the flood levels caused by climate by up to 3 % in all catchments except one with large clear-cutting areas. Forest growth leads to increase in low flow levels in three coniferous forest dominant catchments while it aggravates the low flow conditions in the catchments with high coverage of deciduous forest in the summer half-year.
Sammendrag
Green roofs provide vital functions within the urban ecosystem, from supporting biodiversity, to sustainable climate-positive ESS provisioning. However, how plant communities should best be designed to reach these objectives, and how specific green roof systems vary in their capacity to support these functions is not well understood. Here we compiled data on plant traits and plant–insect interaction networks of a regional calcareous grassland species pool to explore how designed plant communities could be optimised to contribute to ecological functionality for predefined green roof solutions. Five distinct systems with practical functionality and physical constraints were designed, plant communities modelled using object-based optimization algorithms and evaluated using five ecological functionality metrics (incl. phylogenetic and structural diversity). Our system plant communities supported a range of plant–insect interactions on green roofs, but not all species were equally beneficial, resulting in wide-ranging essentiality and redundancy in ecological processes. Floral traits were not predictive of pollinator preferences, but phylogeny was observed to govern the preferences. Large differences in ecological functionality can be expected between green roofs depending on system design and the extent of the plant community composition. Multifunctionality covariance diverged between systems, suggesting that ecological functionality is not inherently universal but dependent on structural limitations and species pool interactions. We conclude that informed system design has a potential to simultaneously support ecosystem services and urban biodiversity conservation by optimising green roof plant communities to provide landscape resources for pollinating insects and herbivores.
Sammendrag
Understanding long-term effects of clear-cutting on current soil carbon (C) fluxes in boreal forests is important in the perspective of global C cycling and future forest management decisions. We studied twelve pairs of forest stands in South-Eastern Norway, each comprised of one previously clear-cut stand and one near-natural stand with similar macroclimate, topography and soil properties. We measured aboveground tree litterfall continuously during two consecutive years and soil respiration fluxes monthly during the snow-free period of one year. Ground vegetation litterfall was estimated from destructive biomass sampling. The previously clear-cut stands had on average 12 % higher annual soil respiration rates, 20 % greater tree litterfall, and tended to have greater total aboveground litterfall (12 %), while the near-natural stands had greater litterfall from ground vegetation (45 %). Litterfall from ground vegetation was strongly linked with below-canopy light transmission, but the contribution of this flux to the total aboveground litterfall was minor. Soil respiration rates were related to microclimate, nitrogen concentration in aboveground tree litter and tree basal area. Though, only basal area could be linked to management type differences in soil respiration, that likely has additional unidentified drivers. We found similar temperature sensitivities of soil respiration in the two management types. We emphasise that age of the dominating trees is an integrated part of the differences between these two types of forest stands. Jointly, our results suggest limited differences in the current net soil C balance of near-natural and previously clear-cut stands.
Forfattere
Margit Oami Kollstrøm Ulrike Böcker Anne Kjersti Uhlen Annbjørg Kristoffersen Jon Arne Dieseth Erik Tengstrand Shiori KogaSammendrag
The gluten-viscoelastic properties are essential for breadmaking quality and are affected by both genotypes and environments, such as weather conditions. However, it is still not clear how weather conditions cause variation in gluten quality and at which stage of the grain filling they are critical. The aim of the study was to explore the relationship between weather parameters during grain filling and the viscoelastic properties of gluten. The gluten of spring wheat varieties grown over 17 seasons, resulting in a total of 70 different environments, was analyzed with the Kieffer extensibility rig. The variation in viscoelastic properties of gluten was mainly explained by environment, followed by genotype, while the genotype*environment interaction was small. The results also indicated that the periods around heading and physical maturity were the most critical when weather conditions affected the gluten quality. Our results also revealed that factors other than weather conditions are responsible for the variation in gluten quality.
Forfattere
Alexander N. Hristov André Bannink Marco Battelli Alejandro Belanche M. Cecilia Cajarville Sanz Gonzalo Fernandez-Turren Florencia Garcia Arjan Jonker David A. Kenny Vibeke Lind Sarah J. Meale David Meo Zilio Camila Muñoz David Pacheco Nico Peiren Mohammad Ramin Luca Rapetti Angela Schwarm Sokratis Stergiadis Katerina Theodoridou Emilio M. Ungerfeld Sanne van Gastelen David R. Yáñez-Ruiz Sinead M. Waters Peter LundSammendrag
There is a need for rigorous and scientifically-based testing standards for existing and new enteric methane mitigation technologies, including antimethanogenic feed additives (AMFA). The current review provides guidelines for conducting and analyzing data from experiments with ruminants intended to test the antimethanogenic and production effects of feed additives. Recommendations include study design and statistical analysis of the data, dietary effects, associative effect of AMFA with other mitigation strategies, appropriate methods for measuring methane emissions, production and physiological responses to AMFA, and their effects on animal health and product quality. Animal experiments should be planned based on clear hypotheses, and experimental designs must be chosen to best answer the scientific questions asked, with pre-experimental power analysis and robust post-experimental statistical analyses being important requisites. Long-term studies for evaluating AMFA are currently lacking and are highly needed. Experimental conditions should be representative of the production system of interest, so results and conclusions are applicable and practical. Methane-mitigating effects of AMFA may be combined with other mitigation strategies to explore additivity and synergism, as well as trade-offs, including relevant manure emissions, and these need to be studied in appropriately designed experiments. Methane emissions can be successfully measured, and efficacy of AMFA determined, using respiration chambers, the sulfur hexafluoride method, and the GreenFeed system. Other techniques, such as hood and face masks, can also be used in short-term studies, ensuring they do not significantly affect feed intake, feeding behavior, and animal production. For the success of an AMFA, it is critically important that representative animal production data are collected, analyzed, and reported. In addition, evaluating the effects of AMFA on nutrient digestibility, animal physiology, animal health and reproduction, product quality, and how AMFA interact with nutrient composition of the diet is necessary and should be conducted at various stages of the evaluation process. The authors emphasize that enteric methane mitigation claims should not be made until the efficacy of AMFA is confirmed in animal studies designed and conducted considering the guidelines provided herein.
Sammendrag
Urban green structures (UGS) play important roles in enhancing urban ecosystems by providing benefits such as mitigating the urban heat island effect, improving air quality, supporting biodiversity, and aiding in stormwater management. Accurately mapping UGS is important for sustainable urban planning and management. Traditional methods of mapping such as manual mapping, aerial photography interpretation and pixel-based classification have limitations in terms of coverage, accuracy, and efficiency. Object-based image analysis (OBIA) has gained prominence due to its ability to incorporate both spectral and spatial information making it particularly effective for classification of high-resolution satellite data. This paper reviews the application of OBIA on satellite images for UGS mapping, focusing on various data sources, popular segmentation methods, and classification techniques, highlighting their respective advantages and limitations. Key segmentation methodologies discussed include multi-resolution segmentation and watershed segmentation. For classification, the review covers machine learning techniques such as random forests, support vector machines, and convolutional neural networks, among others. Several case studies highlight the successful implementation of OBIA in diverse urban environments by demonstrating improvements in classification accuracy and detail. The review also addresses the challenges associated with OBIA, such as dealing with heterogenous urban landscapes, data sources and with OBIA methods itself. Future directions for UGS mapping include the integration of deep learning algorithms, advancements in satellite data technologies, and the development of standardized classification frameworks. By providing a detailed analysis of the current state-of-the-art in object-based UGS mapping, this review aims to guide future research and practical applications in UGS management.
Forfattere
Mostafa Hoseini Helle Ross Gobakken Stephan Hoffmann Csongor Horvath Johannes Rahlf Jan Bjerketvedt Stefano Puliti Rasmus AstrupSammendrag
RoadSens is a platform designed to expedite the digitalization process of forest roads, a cornerstone of efficient forest operations and management. We incorporate stereo-vision spatial mapping and deep-learning image segmentation to extract, measure, and analyze various geometric features of the roads. The features are precisely georeferenced by fusing post-processing results of an integrated global navigation satellite system (GNSS) module and odometric localization data obtained from the stereo camera. The first version of RoadSens, RSv1, provides measurements of longitudinal slope, horizontal/vertical radius of curvature and various cross-sectional parameters, e.g., visible road width, centerline/midpoint positions, left and right sidefall slopes, and the depth and distance of visible ditches from the road’s edges. The potential of RSv1 is demonstrated and validated through its application to two road segments in southern Norway. The results highlight a promising performance. The trained image segmentation model detects the road surface with the precision and recall values of 96.8 and 81.9 , respectively. The measurements of visible road width indicate sub-decimeter level inter-consistency and 0.38 m median accuracy. The cross-section profiles over the road surface show 0.87 correlation and 9.8 cm root mean squared error (RMSE) against ground truth. The RSv1’s georeferenced road midpoints exhibit an overall accuracy of 21.6 cm in horizontal direction. The GNSS height measurements, which are used to derive longitudinal slope and vertical curvature exhibit an average error of 5.7 cm compared to ground truth. The study also identifies and discusses the limitations and issues of RSv1, which provide useful insights into the challenges in future versions.
Forfattere
Rasmus Bang Stine Samsonstuen Bjørn Gunnar Hansen Mario Guajardo Hanne Møller Jon Kristian Sommerseth Julio C. Goez Ola FlatenSammendrag
CONTEXT Researchers have identified numerous strategies to improve economic performance and reduce greenhouse gas (GHG) emission intensity in combined milk and beef production on dairy farms. However, there remains a need to better understand how the effectiveness of these strategies varies under different operational conditions. OBJECTIVE This study aims to examine how the economic and GHG emission intensity mitigation effectiveness of increased milk yield, extended longevity of dairy cows, reduced age at first calving, and intensified beef production from bulls depend on operational conditions in dual purpose cattle systems. METHOD We present a quantitative framework to (1) economically optimize production at farm level under various constraints and (2) calculate corresponding GHG emissions. The framework is tailored for Norwegian dual-purpose cattle systems and used to assess the economic and GHG emission intensity mitigation effects of incremental adjustments in relevant decisions. RESULTS AND CONCLUSIONS The results show that increased milk yield, extended productive life of dairy cows, reduced age at first calving, and lower slaughter age of bulls can lead to economic and climatic win-wins in terms of higher gross margins and reduced emissions per kg of protein produced. However, they may also result in lose-win and win-lose outcomes depending on the operational conditions. All four measures free up roughage production capacity, which, if used to maintain/increase milk and/or beef production, typically results in economic gains. However, if e.g., the available milk quota or space prevent this, economic losses may occur. The climate impact also depends on how the freed-up capacity is used: if it boosts production, the effects vary based on the scale and type of increase and the farm's initial setup, while unused capacity leads to reduced emission intensity. Conflicts typically arise when: 1) the extra capacity increases less climate-friendly production, raising emission intensity despite economic gains, or 2) extra capacity cannot be used, causing economic losses despite climate benefits. Our results also show that what can be labeled a win in climate terms, and to what extent, depends on the selected target metric(s). SIGNIFICANCE Governments and societies strive to balance food production with environmental goals. In this context, it is essential to identify farm-level economic and climatic win-win and lose-win scenarios, not only for farmers but also for policymakers and the broader society. This study could inform decision-making and policy development, potentially enhancing economic and climatic performance in combined milk and meat production.
Sammendrag
Optimised contributions of green infrastructure (GI) to urban ecosystem services are strongly related to its multifunctionality. The challenge, however, is that the concept of multifunctionality still needs to be transformed into an operationalised assessment to evaluate current performance, which is instrumental in supporting spatial planning and policy strategies. Using the case of Stavanger City (Norway), the study conducted a spatial assessment of the multifunctionality of the urban green infrastructure. The study used a comprehensive set of 27 function indicators estimated for each of the 156 spatial units classified by their type, age, size, and biophysical characteristics. Correlation patterns among indicators and how the average and effective multifunctionality related to unit characteristics were analysed using correlation and multivariate approaches. The study demonstrated weak correlations between function indicators but revealed some potential trade-offs and function bundles. Notably, bundles related to tree cover (e.g. C sequestration, stormwater retention) had negative relationships with facilitation measures. There was a large overlap in functions between GI types associated with public green spaces and parks. Moreover, the characteristics of green infrastructure units, like size and age, primarily affected multifunctionality through effects on function indicators. Regarding the city-wide multifunctionality, we found some turnover and subsetting of functions among units, supporting multifunctionality at larger spatial scales. However, the average contributions from different GI types were similar. The study highlights the need to understand correlation patterns among function indicators and function bundles as critical to benefit from synergies and avoid unintentional trade-offs when designing and managing urban green areas.
Forfattere
Jian Liu Faruk Djodjic Barbro Ulén Helena Aronsson Marianne Bechmann Lars Bergström Tore Krogstad Katarina KyllmarSammendrag
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