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
Håvard EikemoSammendrag
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Forfattere
Mark Ramsden Berit Nordskog Tor-Einar Skog Dave Skirvin Angelo Marguglio Antonio Caruso Christophe Pradal Lise Jorgensen Mette Sonderskov Nikos Georgantzis Marko Debeljak Jurij Marinko Harm Brinks Bjorn Andersson Ilias Travlos Eleanor Dearlove Neil PaveleySammendrag
Crop protection and pest management are major economic and environmental concerns throughout Europe. The consultation of decision support systems (DSS) to guide decisions relating to Integrated Pest Management (IPM) is one of the key principles of IPM, reducing the ambiguity around potential risks to crop health. ‘Pests’ in this context include invertebrate pests, weeds and pathogens. The impact of DSS can be limited by a lack of awareness of DSS availability, inconsistencies in the user functions of different DSS, regional fragmentation of access, and a lack of transparency of the origin, validity, and benefits of DSS. Failure to address these limitations undermines trust in IPM DSS and leads to a reluctance of farmers and advisors to invest time in consulting multiple DSS sources as part of their agronomic decision toolbox. The EU-funded IPM Decisions project (Grant agreement ID: 817617) addressed these limitations by creating a Europe-wide free-access online platform. The IPM Decisions platform was designed in consultation with farmers, advisors and wider stakeholders to increase access to and uptake of IPM DSS integrated within it. It offers an end-point for IPM researchers and DSS developers to make adapted and novel DSS available to users, and provides a ‘one-stop shop' for farmers and advisors looking to consult free access or paid IPM DSS. Dedicated dashboards within the platform facilitate farm set up, consultation of DSS, comparison of DSS outputs, and adjustment of model parameters for adaption to different pests/regions. The IPM Decisions digital infrastructure enables easy integration of models and data with external platforms, providing a framework for accessing and sharing models and data between researchers and developers. The platform therefore provides both a ready to go user interface for new DSS, as well as the infrastructure to support and connect existing and future user interfaces.
Sammendrag
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Sammendrag
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Sammendrag
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Forfattere
Tatsiana Espevig Kristine Sundsdal Victoria Stornes Moen Ramsøy Kate Entwistle, The Turf Disease Centre Usoltseva Marina, Botaniska Analysgruppen Sabine Braitmaier, ProSementis GmbH Daniel Hunt, University of Applied Science Osnabrück Carlos Guerrero Monica Skogen Erik LysøeSammendrag
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Forfattere
Kristiina Matilda Maria Visakorpi Zafar A. Reshi Oriol Grau Anne Muola Anna Orczewska Koenraad Van Meerbeek Bente Jessen GraaeSammendrag
Invasive species are one of the greatest threats to biodiversity. However, our understanding of how these species persist and spread in novel environments remains limited. Specifically, the relative importance of species interactions versus environmental conditions and the role of rapid evolutionary adaptation are not fully understood. Here, we investigate the impact of these factors on the distribution of the invasive Himalayan balsam ( Impatiens glandulifera ). We examined whether the climatic niche of the species is pre-adapted to the environmental conditions in the introduced range through niche modeling. Field surveys were conducted to assess the importance of herbivory and competition, and greenhouse treatments were used to investigate local adaptation. We found that the species has not yet fully occupied the suitable climatic space in its introduced range in Europe. Our results suggest that the species may have experienced enemy release while also facing increased biotic pressure at the northern range edge. We identified adaptive differentiation in flowering time, which enhances reproductive success when plants grow in climates similar to their origin. Our results indicate that Himalayan balsam has rapidly adapted to differences in growing season length in its introduced range, with trait plasticity providing an adaptive advantage. Together, these findings suggest that the species may continue to spread across its introduced range in Europe.
Sammendrag
Research on Sonchus arvensis L. is underrepresented despite its status as a widespread perennial arable weed in the Northern Hemisphere. This study investigates, based on a comparison of literature data and recent plant metric data, whether there are indications of a problematic expansion in Germany and identified two knowledge gaps. The recent plant metric data were taken between 2019–2024 at various sites in Germany, Norway, and Finland. We structured the results in subchapters along the life-stages of S. arvensis given in their headings: ‘Propagules in the soil’, ‘Plant establishment’, ‘Rosette growth’, ‘Plant height’, ‘Seed production’ and ‘Plant senescence’. In Germany, S. arvensis has a rosette diameter measuring 34–58 cm and a height of 40–98 cm, although a height of up to 220 cm has been recorded in 2024 in Germany. Rosette diameter and plant height data indicate at least no smaller sizes compared to studies and plant metric data from other countries. Notably, 142 seeds per head were counted in Germany, indicating a source for successful spatial spreading. We address two knowledge gaps related to the research question in the title. One regarding whether vegetative growth contributes to the spread of S. arvensis , and another concerning how its phenological development is influenced by temperature and photoperiod. In addition, we recommend monitoring the species biology and ecology on agricultural fields in Germany.
Forfattere
Komi Mensah Agboka Frank Thomas Ndjomatchoua Ritter Atoundem Guimapi Luca Rossini Abdelmutalab G. A. Azrag Quinto Juma Meltus Tobias Landmann Sunday Ekesi Elfatih M. Abdel‐RahmanSammendrag
The multitasking lesser mealworm ( Alphitobius diaperinus ) is a special beetle known as a pest in poultry, a resource for waste degradation and an alternative for protein production. This study compares the predictive accuracy of correlative species distribution models (SDMs) with a risk index derived from a mechanistic model. The study derives the mechanistic‐based risk index from the ordinary differential equation that describes the population dynamics of A. diaperinus using the temperature‐dependent bio‐demographic rates, while the ensemble SDM is derived using well‐known algorithms such as maximum entropy, random forest and so forth. We finally propose a hybrid model combining both approaches using a weighted average approach. When overlaid on occurrence data, the predictive accuracy of the mechanistic model globally varied across temporal scales, with the highest performance observed in the October–December quarter (27% of occurrences were predicted correctly). The comparison across geographic regions model had the best performance in Asia (94.4% accuracy), outperforming the two scenario SDMs (78.3%). In contrast, the correlative ensemble SDM performed better in Europe (93%), where we have most of the data, but was very sensitive to data gaps, especially in Africa. Finally, the proposed hybrid model outperforms both individual models in the global scenario (86.5% accuracy). These findings highlight the strengths and limitations of both modelling approaches and provide critical insights to optimise pest management strategies, sustainable utilisation and ecological forecasting by refining SDM through the integration of biological realism and empirical data.
Forfattere
Komi Mensah Agboka Frank Thomas Ndjomatchoua Luca Rossini Ritter Atoundem Guimapi Elfatih M. Abdel-RahmanSammendrag
The biological life cycle of terrestrial arthropods, using temperature as the primary driving factor has a large interest for insect pests in agriculture, forestry, urban ecosystems, as constitutes the basics for the development of mathematical models for decision making. A recent study proposed a physiologically-based risk index (RI) which finds large applications in the definition of risk maps; however, further case studies are needed to better explore its strengths and limitations. This study aims to extend this knowledge by presenting an application of the RI on two economically significant pests: the fall armyworm Spodoptera frugiperda and the stem borer Busseola fusca, major treats for maize production. • While the case of S. frugiperda follows the theoretical expectations, providing values RI > 1 for temperature ranges typical of the regions of its confirmed persistence, the model fails for B. fusca, as RI < 1 for weather conditions where field presence and damage are well-documented. • Accordingly, we trace the breakdown to limiting model assumptions, particularly temperature-only drivers, linear cause-and-effect biodemographic parameters, omission of seasonal dynamics, and reliance on laboratory parameters. • This dual-case contrast highlights both the potential and limitations of RI and calls for refinements that include a broader ecological realism and data availability.