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
Forfattere
Geir Wæhler Gustavsen Philip Bester van Niekerk Jonas Niklewski Christian Brischke Gry AlfredsenSammendrag
With increased focus on sustainable building materials and the growing popularity of uncoated wooden cladding, understanding consumer acceptance of aesthetic changes becomes crucial for sustainable architectural choices. This study investigated consumer acceptance of uncoated wooden cladding in Norway, Sweden, and Germany, focusing on personality traits and perceptions. Using an online survey with 3112 participants, the study found that preference for uncoated wooden cladding was similar (around 20%) across the three countries, despite diferences in the prevalence of wooden cladding. A natural consequence of weathering of wood exposed outdoors is greying of the surface. The survey presented participants with images of uncoated wooden cladding with varying degrees of grey discolouration. Participants rated the acceptability of these claddings based on their preferences. Acceptance of this discolouration difered by country, Norwegians preferred intermediatecoloured panels, Swedes preferred darker panels, and Germans accepted all panels. Personality traits measured using the Big Five personality inventory and socioeconomic factors infuenced preferences. In Norway and Sweden, those accepting the discolouration of uncoated wooden cladding included introverts, highly conscientious individuals, young people, females, and those with tertiary education. Additionally, in Norway and Germany, openness to experience was linked to acceptance, while strong emotional control was signifcant only in Norway. This study underscores the complexity of consumer preferences for uncoated wooden cladding, demonstrating that personality traits, in conjunction with cultural and demographic variables, jointly infuence perception. The fndings ofer valuable insights for architects, builders, and policymakers seeking to advance sustainable construction practices while optimising consumer satisfaction in the housing sector.
Forfattere
Fulvio Di Fulvio Tord Snäll Pekka Lauri Nicklas Forsell Mikko Mönkkönen Daniel Burgas Clemens Blattert Kyle Eyvindson Astor Toraño-Caicoya Marta Vergarechea Clara Antón Fernandéz Julian Klein Rasmus Astrup Jani Lukkarinen Samuli Pitzén Eeva PrimmerSammendrag
The EU Biodiversity Strategy (EUBDS) for 2030 aims to conserve and restore biodiversity by protecting large areas throughout the European Union. A target of the EUBDS is to protect 30 % of the EU’s land area by 2030, with 10 % being strictly protected (including all primary and old growth forests) and 20 % being managed ‘closer to nature’. Even though this will have a positive impact on biodiversity, it may negatively impact the EU’s wood-based bioeconomy. In this study, we analyze how alternative interpretations and distributions of the EU’s protection targets may affect future woody biomass harvest levels, exports of wood commodities, and the spatial distribution of managed areas under wood demands aligned with SSP2-RCP1.9. Using the model GLOBIOM-Forest, we simulate scenarios representing a variety of interpretations and geographic distributions of the EUBDS targets. The EUBDS targets would have a limited impact on EU harvest levels since the EU can still increase its wood harvest between 21 % and 24 % by 2100. With strict protection of 30 % of the area, the EU harvest level can still be increased by 10 %. Moreover, the most likely scenario (10 %/20 % protection within each MS) will result in increased net exports in the coming decades, but a slight decline after 2050. However, if protection is intended to also represent site productivity or to re-establish a green infrastructure, then EU net exports will also decline before 2050. With the decreased EU roundwood harvest, increased harvest will occur in other biomes and mostly leaking into boreal regions.
Sammendrag
Det er ikke registrert sammendrag
Forfattere
Komi Mensah Agboka Elfatih M. Abdel-Rahman Daisy Salifu Brian Kanji Frank T. Ndjomatchoua Ritter Atoundem Guimapi Sunday Ekesi Landmann TobiasSammendrag
This study introduces a hybrid approach that combines unsupervised self-organizing maps (SOM) with a supervised convolutional neural network (CNN) to enhance model accuracy in vector- borne disease modeling. We applied this method to predict insecticide resistance (IR) status in key malaria vectors across Africa. Our results show that the combined SOM/CNN approach is more robust than a standalone CNN model, achieving higher overall accuracy and Kappa scores among others. This confirms the potential of the SOM/CNN hybrid as an effective and reliable tool for improving model accuracy in public health applications. • The hybrid model, combining SOM and CNN, was implemented to predict IR status in malaria vectors, providing enhanced accuracy across various validation metrics. • Results indicate a notable improvement in robustness and predictive accuracy over traditional CNN models. • The combined SOM/CNN approach demonstrated higher Kappa scores and overall model accuracy.
Sammendrag
In broiler breeding, precise counting is crucial for improving production efficiency and ensuring animal welfare. Nevertheless, counting chickens precisely is a challenging task especially when young chicks always huddle for warmth. Although deep learning has been widely taken in different counting related tasks, more accurate localization and counting of chickens in high stocking density scenes still has not been well investigated. We propose a point supervised dense chickens flock counting network (PCCNet), which directly utilizes points as learning targets. The network adopts information feature fusion to assist the identification of broilers high stocking density scenes. In addition, considering the distance of neighboring points as matching cost in point matching algorithms is advantageous for generating more reasonable matching results, facilitating model convergence. To validate the effectiveness of the proposed network, a Chicken Counting Dataset (CCD) is built, consisting of two subsets separated by different ages: CCD_A and CCD_B. The accuracies of PCCNet on the two subsets of CCD are 97.85% and 97.06%, with corresponding Mean Absolute Errors (MAE) of 1.966 and 5.173, and Root Mean Square Errors (RMSE) values of 3.474 and 7.034, respectively. Our model achieves better broiler counting performance than other state-of-the-art (SOTA) methods.
Forfattere
Johan A. Stenberg Daniel Flø Lawrence Richard Kirkendall Anders Nielsen Selamawit Tekle Gobena Beatrix Alsanius Jorunn Børve Paal Krokene Christer Magnusson Mogens Nicolaisen Line Nybakken Iben Magrete Thomsen May-Guri Sæthre Sandra A.I. WrightSammendrag
Citripar, a biological plant protection product containing the parasitic wasp Anagyrus vladimiri, is requested to be approved for use in Norway. The product is intended to be used against mealybugs, particularly Planococcus citri (citrus mealybug) and Planococcus ficus (vine mealybug) feeding on fruits, berries, vegetables and herbs in greenhouses and plastic tunnels, and on indoor plants. The Norwegian Food Safety Authority, therefore, asked the Norwegian Scientific Committee for Food and Environment to perform a risk assessment of the product. Occurrence and distribution in Norway: No observations of Anagyrus vladimiri have been reported from Norway. Potential for establishment and spread: VKM assesses that Anagyrus vladimiri will not be able to establish and spread in Norway under current conditions due to the absence of host organisms and too low winter temperatures, even in the warmest parts of the country. Potential effects on biodiversity: VKM assesses that Anagyrus vladimiri will not affect biodiversity in Norway, as there are currently no known native hosts for the wasp to parasitize. Taxonomic challenges that may affect the risk assessment: Anagyrus vladimiri belongs to the wasp family Encyrtidae, a family that includes the genus Anagyrus, many of which have quite tangled taxonomic histories. Individuals of what is now known as Anagyrus vladimiri were for many years identified as belonging to Anagyrus pseudococci. Anagyrus pseudococci and A. vladimiri are members of a complex of nearly indistinguishable species that are informally referred to as the Anagyrus pseudococci complex: A. pseudococci, A. vladimiri, A. kamali, A. dactylopii, A. kivuensis, and A. callidus. These species have been used for biological control of various mealybug species. Should incorrectly identified Anagyrus be imported to Norway, there would be no consequences for biological diversity, since the other species in the Anagyrus pseudococci complex are also host specific to mealybug genera that are not found in the Norwegian fauna, and they are physiologically unfit for the current Norwegian climate.
Forfattere
Emmanuel O. Anedo Dennis Beesigamukama Benson Mochoge Nicholas K. Korir Solveig Haukeland Xavier Cheseto Moses Nyongesa Patrick Pwaipwai Sevgan Subramanian Abdou Tenkouano Betty Kibaara Chrysantus M. TangaSammendrag
Potato production is hindered by soil degradation and nematode infestation. Mineral fertilizers and synthetic nematicides are costly and cause negative impacts on humans and the environment, while organic fertilizers are less effective for soil health and nematode management. This study demonstrates the contribution of black soldier fly frass fertilizer (BSFFF) in nematode suppression and potato productivity when compared to commercial mineral fertilizer, organic fertilizer (SAFI), and nematicide. The on-farm experiments consisted of eight treatments: BSFFF, SAFI, BSFFF+5%chitin, NPK+nematicide, 50%BSFFF+50%NPK, 50%SAFI+50%NPK, 50%BSFFF+5% chitin+50%NPK, and control (unfertilized soil). Results revealed that all fertilizer treatments significantly increased potato growth, number of tubers (34 – 61%), and tuber yield (20 – 72%) relative to the control. Application of BSFFF+5% chitin produced 9 – 28% higher tubers per plant compared to other treatments. Over 26% higher tuber yield was achieved using BSFFF+5% chitin compared to NPK+nematicide treatment. Soil amendment with BSFFF+5% chitin caused 5–35% higher reduction in the number of cysts per 200 g soil-1 compared to NPK+nematicide and SAFI treatments. The same treatment reduced the PCN reproduction rate by 20% and 75% compared to NPK + nematicide and SAFI, respectively. Both BSFFF and NPK+nematicide treatments achieved comparable suppression of the number of eggs and infective juveniles (J2) per cyst-1 and eggs g-1 of soil. However, BSFFF+5% chitin reduced the number of eggs and J2 per cyst-1 and eggs g-1 of soil by 55–92% compared to SAFI. Our findings demonstrate that chitin-fortified BSFFF can significantly contribute to potato cyst nematode suppression and boost potato yields in smallholder farming systems, thus, making it a promising and sustainable alternative to commercial fertilizers and nematicides. Adopting this regenerative and multipurpose fertilizer will reduce reliance on synthetic fertilizers and nematicides, which are costly and harmful to the environment and human health.
Forfattere
Arti Rai Magne Nordang Skårn Abdelhameed Elameen Torstein Tengs Mathias Amundsen Oskar Schnedler Bjorå Lisa Karine Haugland Igor A. Yakovlev May Bente Brurberg Tage ThorstensenSammendrag
The phenylpropanoid pathway, regulated by transcription factors of the MYB family, produces secondary metabolites that play important roles in fertilization and early phase of fruit development. The MYB46 transcription factor is a key regulator of secondary cell wall structure, lignin and flavonoid biosynthesis in many plants, but little is known about its activity in flowers and berries in F. vesca. For functional analysis of FvMYB46, we designed a CRISPR-Cas9 construct with an endogenous F. vesca-specific U6 promoter for efficient and specific expression of two gRNAs targeting the first exon of FvMYB46. This generated mutants with an in-frame 81-bp deletion of the first conserved MYB domain or an out-of-frame 82-bp deletion potentially knocking out gene function. In both types of mutant plants, pollen germination and fruit set were significantly reduced compared to wild type. Transcriptomic analysis of flowers revealed that FvMYB46 positively regulates the expression of genes involved in processes like xylan biosynthesis and metabolism, homeostasis of reactive oxygen species (ROS) and the phenylpropanoid pathway, including secondary cell wall biosynthesis and flavonoid biosynthesis. Genes regulating carbohydrate metabolism and signalling were also deregulated, suggesting that FvMYB46 might regulate the crosstalk between carbohydrate metabolism and phenylpropanoid biosynthesis. In the FvMYB46-mutant flowers, the flavanol and flavan-3-ol contents, especially epicatechin, quercetin-glucoside and kaempferol-3-coumaroylhexoside, were reduced, and we observed a local reduction in the lignin content in the anthers. Together, these results suggest that FvMYB46 controls fertility and efficient fruit set by regulating the cell wall structure, flavonoid biosynthesis, carbohydrate metabolism, and sugar and ROS signalling in flowers and early fruit development in F. vesca.
Sammendrag
Existing methods for resource nexus analysis do not cover all aspects of complex resource management problems. Key methodological challenges include setting the scale, scope, and resolution of a nexus analysis, as well as adequately representing the quantity and quality of resource interactions. Additionally, determining the degree of collaborative governance for resource management, accounting for the role of existing policies, and developing robust scenarios for future predictions are also crucial constraints. To address these limitations, we developed a conceptual model of the resources nexus for Otta valley in Norway, an area characterized by resource use trade-offs across interconnected systems. We introduced the concept of ‘‘resource scapes’’ which is the physical availability, key interactions, management networks, and policies governing a resource at a specific time and place. We defined resource scapes for water, energy, and biomass resources in the studied area. Employing stock and flow loops, social network analysis, material flow accounting, and policy reviews, we developed the model in a layered topology using the coupled component modeling approach. In addition, we developed future resource scenarios nested within national pathways– the Norwegian nexus pathways (NNPs)– aligned with the five globally adopted shared-socioeconomic pathways (SSPs), using a narrative downscaling approach. Our results show that annual variations in resource balances are connected to changing externalities. A low Network External-Internal (EI) index (0.392) indicates weak overall collaborative governance of nexus resources. Our modeling framework (1) addresses limitations in current nexus methods, (2) facilitates testing of alternative policy interventions under future scenarios, and (3) provides a framework for development of integrated assessment models. This approach merges the concept of nexus governance with integrated assessment modeling, thereby enhancing the application of nexus approach for efficient resource management which will be crucial in future as climate and socioeconomic conditions evolve.
Forfattere
Stefano Puliti Emily R. Lines Jana Müllerová Julian Frey Zoe Schindler Adrian Straker Matthew J. Allen Lukas Winiwarter Nataliia Rehush Hristina Hristova Brent Murray Kim Calders Nicholas Coops Bernhard Höfle Liam Irwin Samuli Junttila Martin Krůček Grzegorz Krok Kamil Král Shaun R. Levick Linda Luck Azim Missarov Martin Mokroš Harry J. F. Owen Krzysztof Stereńczak Timo P. Pitkänen Nicola Puletti Ninni Saarinen Chris Hopkinson Louise Terryn Chiara Torresan Enrico Tomelleri Hannah Weiser Rasmus AstrupSammendrag
1. Proximally sensed laser scanning presents new opportunities for automated forest ecosystem data capture. However, a gap remains in deriving ecologically pertinent information, such as tree species, without additional ground data. Artificial intelligence approaches, particularly deep learning (DL), have shown promise towards automation. Progress has been limited by the lack of large, diverse, and, most importantly, openly available labelled single-tree point cloud datasets. This has hindered both (1) the robustness of the DL models across varying data types (platforms and sensors) and (2) the ability to effectively track progress, thereby slowing the convergence towards best practice for species classification. 2. To address the above limitations, we compiled the FOR-species20K benchmark dataset, consisting of individual tree point clouds captured using proximally sensed laser scanning data from terrestrial (TLS), mobile (MLS) and drone laser scanning (ULS). Compiled collaboratively, the dataset includes data collected in forests mainly across Europe, covering Mediterranean, temperate and boreal biogeographic regions. It includes scattered tree data from other continents, totaling over 20,000 trees of 33 species and covering a wide range of tree sizes and forms. Alongside the release of FOR-species20K, we benchmarked seven leading DL models for individual tree species classification, including both point cloud (PointNet++, MinkNet, MLP-Mixer, DGCNNs) and multi-view 2D-based methods (SimpleView, DetailView, YOLOv5). 3. 2D Image-based models had, on average, higher overall accuracy (0.77) than 3D point cloud-based models (0.72). Notably, the performance was consistently >0.8 across scanning platforms and sensors, offering versatility in deployment. The top-scoring model, DetailView, demonstrated robustness to training data imbalances and effectively generalized across tree sizes. 4. The FOR-species20K dataset represents an important asset for developing and benchmarking DL models for individual tree species classification using proximally sensed laser scanning data. As such, it serves as a crucial foundation for future efforts to classify accurately and map tree species at various scales using laser scanning technology, as it provides the complete code base, dataset, and an initial baseline representative of the current state-of-the-art of point cloud tree species classification methods.