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Publications

NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.

2025

Abstract

The year-to-year variation in the availability of lingonberries (Vaccinium vitis-idaea L.) is a challenge for commercial exploitation. There is also a need to identify the best locations for lingonberry harvesting. Here, we present research that utilized field observations from the Norwegian National Forest Inventory to model and map the association between lingonberry cover and stand characteristics. Additionally, a set of permanent sampling plots were established for annual recording of berry yields in different Norwegian regions, representing variations in slope and forest characteristics. Ultimately, the recorded information on yield from the temporary sample plots were combined with predictions from the cover model, as well as data from remote sensing and climatic data from nearby weather stations (for locations see Figure 1a) to derive: 1) a model for lingonberry yield, and 2) and a yield map covering all forest land in Norway. Variables included in the final berry yield model are main tree species, soil parent material, mean temperature June-August, stand basal area, latitude, slope and distance to coastline (Miina et al., 2024).

To document

Abstract

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.