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.
2023
Authors
Inger Martinussen Mathias Amundsen Aksel Granhus Antje Gonera Marius Hauglin Anne Linn Hykkerud Laura Jaakola Mikko Kurttila Jari Miina Rainer Peltola Gesine Schmidt Josefine Skaret Baoru Yang Kjersti AabyAbstract
Almost 95% of the area in Norway is wilderness and 38% of the land area is covered by woods. These areas are abundant in valuable renewable resources, including wild berries. In our neighbouring countries, Sweden and Finland, wild berries are already a big industry. At the same time, on the market the Norwegian wild berries are almost non-existent and berries are left unexploited. Lingonberry (Vaccinium vitis-idaea) is one of the most abundant and economically important wild berries in the Nordic countries. Nevertheless, lingonberry has a large untapped potential due to its unique health effects and potential for increased value creation. It is estimated that 111,500 t of lingonberry are produced in the Norwegian woods. Norway is a long and diverse country with a range of climatic conditions. Adaptations to different conditions can give differences in both yield and quality of wild berries. Yields vary enormously from year to year and among different locations. A steady supply, predictable volumes and high quality are vital for successful commercialization of wild berries. To increase the utilization of berries, there is a need for increased knowledge regarding availability and quality variation of the berries. In addition, the Norwegian market suffers from high labour costs and cannot compete in product price. Innovative solutions and new knowledge on quality aspects can open possibilities for value creation. Toward achieving this goal, we have created a project called “WildBerries”, the main objective of which is to produce research-based knowledge that will create the basis for increased commercial utilization of Norwegian wild berries.
Authors
Sofia Junttila Jonas Ardö Zhanzhang Cai Hongxiao Jin Natascha Kljun Leif Klemedtsson Alisa Krasnova Holger Lange Anders Lindroth Meelis Mölder Steffen M. Noe Torbern Tagesson Patrik Vestin Per Weslien Lars EklundhAbstract
No abstract has been registered
2022
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Authors
Jogeir N. Stokland Kjersti Holt Hanssen Delphine Derrien Bernhard Zeller Alice Budai Daniel RasseAbstract
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Authors
Marta Vergarechea Rasmus Astrup Clemens Blattert Astor Toraño Caicoya Daniel Burgas Mikko Monkkonen Kyle Eyvindson Fulvio Di Fulvio Knut Øistad Jani Lukkarinen Antón-Fernández ClaraAbstract
No abstract has been registered
Authors
Marta Vergarechea Rasmus Astrup Carolin Fischer Knut Øistad Clemens Blattert Markus Hartikainen Kyle Eyvindson Fulvio Di Fulvio Nicklas Forsell Daniel Burgas Astor Toraño-Caicoya Mikko Mönkkönen Clara Antón FernandézAbstract
To mitigate climate change, several European countries have launched policies to promote the development of a renewable resource-based bioeconomy. These bioeconomy strategies plan to use renewable biological resources, which will increase timber and biomass demands and will potentially conflict with multiple other ecosystem services provided by forests. In addition, these forest ecosystem services (FES) are also influenced by other, different, policy strategies, causing a potential mismatch in proposed management solutions for achieving the different policy goals. We evaluated how Norwegian forests can meet the projected wood and biomass demands from the international market for achieving mitigation targets and at the same time meet nationally determined targets for other FES. Using data from the Norwegian national forest inventory (NFI) we simulated the development of Norwegian forests under different management regimes and defined different forest policy scenarios, according to the most relevant forest policies in Norway: national forest policy (NFS), biodiversity policy (BIOS), and bioeconomy policy (BIES). Finally, through multi-objective optimization, we identified the combination of management regimes matching best with each policy scenario. The results for all scenarios indicated that Norway will be able to satisfy wood demands of up to 17 million m3 in 2093. However, the policy objectives for FES under each scenario caused substantial differences in terms of the management regimes selected. We observed that BIES and NFS resulted in very similar forest management programs in Norway, with a dominance of extensive management regimes. In BIOS there was an increase of set aside areas and continuous cover forestry, which made it more compatible with biodiversity indicators. We also found multiple synergies and trade-offs between the FES, likely influenced by the definition of the policy targets at the national scale.
Abstract
No abstract has been registered
Abstract
Tree diameter increment (ΔDBH) and total tree height increment (ΔHT) are key components of a forest growth and yield model. A problem in complex, multi-species forests is that individual tree attributes such as ΔDBH and ΔHT need to be characterized for a large number of distinct woody species of highly varying levels of occurrence. Based on more than 2.5 million ΔDBH observations and over 1 million ΔHT records from up to 60 tree species and genera, respectively, this study aimed to improve existing ΔDBH and ΔHT equations of the Acadian Variant of the Forest Vegetation Simulator (FVS-ACD) using a revised method that utilize tree species as a random effect. Our study clearly highlighted the efficiency and flexibility of this method for predicting ΔDBH and ΔHT. However, results also highlighted shortcomings of this approach, e.g., reversal of plausible parameter signs as a result of combining fixed and random effects parameter estimates after extending the random effect structure by incorporating North American ecoregions. Despite these potential shortcomings, the newly developed ΔDBH and ΔHT equations outperformed the ones currently used in FVS-ACD by reducing prediction bias quantified as mean absolute bias and root mean square error by at least 11% for an independent dataset and up to 41% for the model development dataset. Using the revised ΔDBH and ΔHT estimates, greater prediction accuracy in individual tree aboveground live carbon mass estimation was also found in general but performance varied with dataset and accuracy metric examined. Overall, this analysis highlights the importance and challenges of developing robust ΔDBH and ΔHT equations across broad regions dominated by mixed-species, managed forests.