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
Authors
Bolette BeleAbstract
This thesis aims to document, discuss, and get a deeper understanding of how heritage values and natural resources in the summer farming landscape interact and can be maintained for the future. The integrated relationship between food production, landscape, biodiversity, and traditional ecological knowledge has been the focus. Through a mixed method approach and by using qualitative and quantitative data in eight papers (Paper I-VIII), the study contributes to a collection of topics essential for a more integrated understanding of the traditional land use system and products and services provided to society. NO: Hovedformålet med denne avhandlingen har vært å dokumentere, diskutere, og øke forståelsen for samspillet mellom kulturarven og naturressursene i det norske seterlandskapet, og hvordan de kan ivaretas for framtida. Det har blitt satt et spesielt fokus på sammenhengene mellom matproduksjonen, landskapet, biodiversiteten, og den tradisjonelle økologiske kunnskapen. Ved hjelp av kvalitative og kvantitative data og metoder har åtte artikler (Paper I-VIII) gitt resultater som til sammen skaper en mer integrert forståelse av det norske seterlandskapet og de produkter og tjenester som seterbruket bidrar med til samfunnet.
Abstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Sanandam Bordoloi Artemi Cerdà Csilla Farkas Katarína Hegedüšová Vantarová Giora J. Kidron Ľubomír LichnerAbstract
No abstract has been registered
Authors
Lorène J. Marchand Jožica Gričar Paolo Zuccarini Inge Dox Bertold Mariën Melanie Verlinden Thilo Heinecke Peter Prislan Guillaume Marie Holger Lange Jan Van den Bulcke Josep Penuelas Patrick Fonti Matteo CampioliAbstract
No abstract has been registered
Authors
João Carlos de Moraes Sá Rattan Lal Klaus Lorenz Yadunath Bajgai Carla Gavilan Manan Kapoor Ademir De Oliveira Ferreira Clever Briedis Thiago Inagaki Lutecia Beatriz Canalli Daniel Ruiz Potma Gonçalves Jeankleber BortoluzziAbstract
No abstract has been registered
Authors
Anita SønstebyAbstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Tomasz Leszek WoznickiAbstract
No abstract has been registered
Authors
Alexey Mikaberidze Christian Cruz Ayalsew Zerihun Abel Barreto Pieter S. Beck Rocío Calderón Carlos Camino Rebecca Campbell Stephanie Delalieux Frederic Fabre Elin Falla Stuart Fraser Kaitlin Gold Carlos Gongora-Canul Frédéric Hamelin Dalphy Ondine Camira Harteveld Cheng-Fang Hong Melen Leclerc Da-Young Lee Murillo Lobo Jr Anne-Katrin Mahlein Emily McLay Paul Melloy Stephen Parnell Uwe Rascher Jack Rich Irene Sarlotti Samuel Soubeyrand Susie Sprague Antony Surano Sandhya Takooree Thomas Taylor Suzanne Touzeau Pablo Zarco-Tejada Nik CunniffeAbstract
Plant diseases impair yield and quality of crops and threaten the health of natural plant communities. Epidemiological models can predict disease and inform management. However, data are scarce, since traditional methods to measure plant diseases are resource intensive and this often limits model performance. Optical sensing offers a methodology to acquire detailed data on plant diseases across various spatial and temporal scales. Key technologies include multispectral, hyperspectral and thermal imaging, and light detection and ranging; the associated sensors can be installed on ground-based platforms, uncrewed aerial vehicles, aeroplanes and satellites. However, despite enormous potential for synergy, optical sensing and epidemiological modelling have rarely been integrated. To address this gap, we first review the state-of-the-art to develop a common language accessible to both research communities. We then explore the opportunities and challenges in combining optical sensing with epidemiological modelling. We discuss how optical sensing can inform epidemiological modelling by improving model selection and parameterisation and providing accurate maps of host plants. Epidemiological modelling can inform optical sensing by boosting measurement accuracy, improving data interpretation and optimising sensor deployment. We consider outstanding challenges in: A) identifying particular diseases; B) data availability, quality and resolution, C) linking optical sensing and epidemiological modelling, and D) emerging diseases. We conclude with recommendations to motivate and shape research and practice in both fields. Among other suggestions, we propose to standardise methods and protocols for optical sensing of plant health and develop open access databases including both optical sensing data and epidemiological models to foster cross-disciplinary work.