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.
2019
Authors
Rasmus Astrup Johannes Rahlf Knut Bjørkelo Misganu Debella-Gilo Arnt Kristian Gjertsen Johannes BreidenbachAbstract
This paper describes the development and utility of the Norwegian forest resources map (SR16). SR16 is developed using photogrammetric point cloud data with ground plots from the Norwegian National Forest Inventory (NFI). First, an existing forest mask was updated with object-based image analysis methods. Evaluation against the NFI forest definitions showed Cohen's kappa of 0.80 and accuracy of 0.91 in the lowlands and a kappa of 0.73 and an accuracy of 0.96 in the mountains. Within the updated forest mask, a 16×16 m raster map was developed with Lorey's height, volume, biomass, and tree species as attributes (SR16-raster). All attributes were predicted with generalized linear models that explained about 70% of the observed variation and had relative RMSEs of about 50%. SR16-raster was segmented into stand-like polygons that are relatively homogenous in respect to tree species, volume, site index, and Lorey's height (SR16-vector). When SR16 was utilized in a combination with the NFI plots and a model-assisted estimator, the precision was on average 2–3 times higher than estimates based on field data only. In conclusion, SR16 is useful for improved estimates from the Norwegian NFI at various scales. The mapped products may be useful as additional information in Forest Management Inventories.
Abstract
No abstract has been registered
Authors
Carmen Morales-Rodríguez Sten Anslan Marie-Anne Auger-Rozenberg Sylvie Augustin Yuri Baranchikov Amani Bellahirech Daiva Burokienė Dovilė Čepukoit Ejup Çota Kateryna Davydenko H. Tuğba Doğmuş Lehtijärvi Rein Drenkhan Tiia Drenkhan René Eschen Iva Franić Milka Glavendekić Maarten de Groot Magdalena Kacprzyk Marc Kenis Natalia Kirichenko Iryna Matsiakh Dmitry L. Musolin Justyna A. Nowakowska Richard O’Hanlon Simone Prospero Alain Roques Alberto Santini Venche Talgø Leho Tedersoo Anne Uimari Andrea Vannini Johanna Witzell Steve Woodward Antonios Zambounis Michelle ClearyAbstract
The number of invasive alien pest and pathogen species affecting ecosystem functioning, human health and economies has increased dramatically over the last decades. Discoveries of invasive pests and pathogens previously unknown to science or with unknown host associations yet damaging on novel hosts highlights the necessity of developing novel tools to predict their appearance in hitherto naïve environments. The use of sentinel plant systems is a promising tool to improve the detection of pests and pathogens before introduction and to provide valuable information for the development of preventative measures to minimize economic or environmental impacts. Though sentinel plantings have been established and studied during the last decade, there still remains a great need for guidance on which tools and protocols to put into practice in order to make assessments accurate and reliable. The sampling and diagnostic protocols chosen should enable as much information as possible about potential damaging agents and species identification. Consistency and comparison of results are based on the adoption of common procedures for sampling design and sample processing. In this paper, we suggest harmonized procedures that should be used in sentinel planting surveys for effective sampling and identification of potential pests and pathogens. We also review the benefits and limitations of various diagnostic methods for early detection in sentinel systems, and the feasibility of the results obtained supporting National Plant Protection Organizations in pest and commodity risk analysis.
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Authors
Cornelya KlutschAbstract
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Authors
Roger HoltenAbstract
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Authors
Roger HoltenAbstract
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No abstract has been registered