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
Attiq Ur Rehman Jahn Davik Petteri Karisto Janne Kaseva Saila Karhu Marja Rantanen Ismo Strandén Timo Hytönen Alan H. Schulman Tuuli HaikonenAbstract
No abstract has been registered
Authors
Ingrid Marie Garfelt Paulsen Isabell Eischeid Åshild Ønvik Pedersen Jakob J. Assmann Nigel Yoccoz Jesper Bruun Mosbacher Eeva M Soininen Virve RavolainenAbstract
The normalized difference vegetation index (NDVI) is a critical tool for studying Arctic vegetation patterns and changes, but more knowledge is needed about its links with plant biomass and disturbances, especially in sparsely vegetated habitats in the High Arctic. Here, we investigate the relationship between NDVI and vascular plant biomass, summer temperature, goose disturbance, and winter damage in Dryas ridge and moss tundra habitats on Svalbard, all recorded in the corresponding year across a 5-year time series. We test these relationships using mixed-effect models at two spatial resolutions (10 cm and 10 m) and two extents with data from drone and Sentinel-2 imagery. We found that in our plots, an increase in biomass of 100 g m−2 increased NDVI from drone imagery by 0.08 ± 0.03 (95% CI) for Dryas ridge and by 0.04 ± 0.03 for moss tundra. Despite record-warm summers, temperature of the same summer was not associated with NDVI in our time-series. In moss tundra, severe goose disturbance had a negative relationship with drone NDVI in plots, while in Dryas ridge habitat, winter damage had no clear correspondence with NDVI. Our study provides an example of context dependencies highlighted in remote-sensing literature in the Arctic, encouraging future studies to include effects of disturbance on NDVI and to establish habitat-specific relationships with NDVI.
Abstract
No abstract has been registered
Authors
Bashiri Iddy Muzzo Kelvyn Bladen Andres Perea Shelemia Nyamuryekung’e Juan J. VillalbaAbstract
No abstract has been registered
Authors
Jianfeng Gu Xinxin Ma Yiwu Fang Hongmei Li Deliang Peng Xiuhai Gan Xingyue Li Baolin Shao Ricardo Holgado Sergei A. SubbotinAbstract
No abstract has been registered
Authors
Dagnew Yebeyen Burru Jayaraman Durai Melaku Anteneh Chinke Gudeta W. Sileshi Yashwant S. Rawat Belachew Gizachew Zeleke Selim Reza Fikremariam Haile Desalegne Kassa Toshe WorassaAbstract
No abstract has been registered
Authors
Anna Skarin Minna Turunen Svein Eilertsen Heidi Rautiainen Tim Horstkotte Camilla Risvoll Anna-Marja Kaddik Tom Lifjell Majken Paulsen Laura Post Sirpa Rasmus Hans Tømmervik Birgitta ÅhmanAbstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
Context Dairy farming contributes approximately 2.5 % of annual global anthropogenic greenhouse gas (GHG) emissions, necessitating effective mitigation strategies. Two approaches are often discussed: low-intensity, low-cost production with minimal reliance on purchased inputs; and high-intensity production with higher-yielding cows to reduce land use and reduce methane emissions per unit of milk. Objective The objective was to identify management factors and farm characteristics that explain variations in GHG emissions, environmental, and economic performance. Indicators included were GHG emissions, land use occupation, energy intensity, nitrogen intensity, and gross margin. Methods Life Cycle Assessment (LCA) was used to calculate the environmental impacts for 200 commercial dairy farms in Central Norway based on farm activities, purchased inputs, machinery, and buildings from 2014 to 2016. A multiple regression analysis with backward elimination was conducted to highlight important variables for environmental impact and economic outcome. Results and conclusions A higher share of dairy cows was found to be the most important factor in reducing GHG emissions, energy and nitrogen intensity, and land use but also to decrease gross margin. Additional key factors for reducing environmental impact included less purchased nitrogen fertiliser, and higher forage yield. There were no statistical correlations between GHG emissions and gross margin per MJ of human-edible energy delivered. Significance Conducting LCA for many dairy farms allows to highlight important factors influencing environmental impact and economic outcome. Using the delivery of human-edible energy from milk and meat as a functional unit allows for a combined evaluation of milk and meat production on a farm.
Abstract
No abstract has been registered