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
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.
Sammendrag
Land-use changes threaten ecosystems and are a major driver of species loss. Plants may adapt or migrate to resist global change, but this can lag behind rapid anthropogenic changes to the environment. Our data show that natural modulations of the microbiome of grassland plants in response to experimental land-use change in a common garden directly affect plant phenotype and performance, thus increasing plant tolerance. In contrast, direct effects of fertilizer application and mowing on plant phenotypes were less strong. Land-use intensity-specific microbiomes caused clearly distinguishable plant phenotypes also in a laboratory experiment using gnotobiotic strawberry plants in absence of environmental variation. Therefore, natural modulations of the plant microbiome may be key to species persistence and ecosystem stability. We argue that a prerequisite for this microbiome-mediated tolerance is the availability of diverse local sources of microorganisms facilitating rapid modulations in response to change. Thus, conservation efforts must protect microbial diversity, which can help mitigate the effects of global change and facilitate environmental and human health.
Sammendrag
Algal-based wastewater remediation systems (phycoremediation) include phycosphere bacterial communities that influence algal growth, pollutant remediation, and downstream applications of biomass as fertilizers or bio-stimulants. This study investigated the bacterial community dynamics in a novel phycoremediation system using a co-culture of the green algae Stigeoclonium sp. and Oedogonium vaucheri. Bacterial abundance was estimated using flow cytometry (FCM), while community composition was assessed through 16S rRNA gene metabarcoding. Additionally, 28 bacterial strains were isolated from the bioremediation experiment, cultured, genetically characterized for identification and screened for production of the auxin phytohormone indole-3-acetic acid (IAA). Metabarcoding showed that the free-living bacterial community consisted of bacteria from both the wastewater effluent and the algal inocula, while the attached phycosphere community was dominated by bacteria from the algal inocula, indicating the stability of the algae-associated phycosphere. Taxa known to include plant growth-promoting bacteria (PGPB) were abundant, and several strains produced IAA. The bacterial community composition, combined with the potential production of phytohormone by isolated bacteria indicates symbiotic or commensal algae-microbe interactions within the phycosphere bacterial communities. Sterile filtration of wastewater effluent, including only the algal inoculum bacterial communities, reduced algal biomass production and increased bacterial abundance. This study highlights the critical role of microbial interactions in engineered ecosystems and provides insights for optimizing algal-based wastewater treatment technologies.
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.
Forfattere
Shuang Yin Xinli Chen Gabin Piton César Terrer Zhenghu Zhou Gerlinde B. De Deyn Isabelle Bertrand Daniel Rasse Ji Chen Jose Antonio Navarro-Cano Diego AbalosSammendrag
Increasing species diversity in agroecosystems appears as a promising venue to restore or increase soil organic carbon (SOC). It has been hypothesized that this effect is largely driven by the greater variation of root systems in plant mixtures, which may promote complementarity. However, the magnitude of this synergistic effect and the root traits driving it are uncertain. The objective of this study is to determine which root trait composition optimizes plant mixture effects on SOC. To do so, we combined a global meta-analysis of 407 paired SOC content observations under mixed species vs. monocultures across grasslands and croplands, and root traits extracted from the GRooT database. The results show that high root mycorrhizal colonization and root tissue density for the species in the mixture have higher positive effects on SOC content. Our analysis also indicates that combining species with high similarity for these traits represents a preferable trait combination to increase SOC with plant mixtures, challenging the current paradigm around plant trait complementarity effects. We observed that the positive response of SOC content to species mixtures was tightly associated with increased root biomass and soil microbial biomass carbon, indicating an important contribution of belowground and microbial residuals to SOC. Additionally, SOC enhancements by plant species mixtures were more likely to be realized in regions with high precipitation, clay-rich soils, and when legumes are present. Our meta-analysis lays out a root-trait framework to enhance SOC with plant mixtures, which can serve as a guide for species and variety selection for field experiments and on-farm applications.
Forfattere
Simen Gustu JohansenSammendrag
Det er ikke registrert sammendrag
Forfattere
Tove Vaaje-KolstadSammendrag
Det er ikke registrert sammendrag
Sammendrag
I Hurdalsplattformen skriver Regjeringen at de ønsker å: «Etablere en storstilt satsing på norsk bioenergi og avansert biodrivstoff i transportsektoren». De ønsker å utvikle en plan som viser hvordan det kan skje «uten at det svekker naturens opptak og lagring av CO2, samt hvor bruken av knappe bioressurser skal prioriteres for å sikre effektive utslippskutt.». Samtidig viser Grønn bok publisert i oktober 2023 at Norge er helt avhengige av biodrivstoff for å nå klimamålene. Vi ser på mulighetsrommet for en slik satsning basert på norsk råstoff, rammer i norsk og europeisk lov og regelverk for en slik satsning, og basert på dette analyserer vi hvilken rolle norskprodusert biodrivstoff kan spille i oppnåelsen av norske klimamål i 2030 under EUs klimarammeverk.